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RUANN JANSER SOARES DE CASTRO
EXPERIMENTAL MIXTURE DESIGN AS A TOOL FOR PROTEASES
PRODUCTION BY Aspergillus niger AND OBTAINING OF PROTEIN
HYDROLYSATES WITH MULTIPLE FUNCTIONAL AND BIOLOGICAL
PROPERTIES
APLICAÇÃO DA FERRAMENTA DE PLANEJAMENTO EXPERIMENTAL DE
MISTURAS COMO ESTRATÉGIA PARA PRODUÇÃO DE PROTEASES POR Aspergillus
niger E OBTENÇÃO DE HIDROLISADOS PROTEICOS COM MÚLTIPLAS
PROPRIEDADES FUNCIONAIS E BIOLÓGICAS
CAMPINAS
2015
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UNIVERSIDADE ESTADUAL DE CAMPINAS
FACULDADE DE ENGENHARIA DE ALIMENTOS
RUANN JANSER SOARES DE CASTRO
EXPERIMENTAL MIXTURE DESIGN AS A TOOL FOR PROTEASES PRODUCTION
BY Aspergillus niger AND OBTAINING OF PROTEIN HYDROLYSATES WITH
MULTIPLE FUNCTIONAL AND BIOLOGICAL PROPERTIES
APLICAÇÃO DA FERRAMENTA DE PLANEJAMENTO EXPERIMENTAL DE
MISTURAS COMO ESTRATÉGIA PARA PRODUÇÃO DE PROTEASES POR Aspergillus
niger E OBTENÇÃO DE HIDROLISADOS PROTEICOS COM MÚLTIPLAS
PROPRIEDADES FUNCIONAIS E BIOLÓGICAS
Orientadora: Prof.ª Dr.ª Helia Harumi Sato
CAMPINAS
2015
Tese apresentada à Faculdade de Engenharia de Alimentos da
Universidade Estadual de Campinas como parte dos requisitos
exigidos para a obtenção do título de Doutor em Ciência de Alimentos
Thesis presented to the School of Food Engineering of the
University of Campinas in partial fulfillment of the requirements
for the degree of Doctor in the area of Food Science
ESTE EXEMPLAR CORRESPONDE À VERSÃO
FINAL DA TESE DEFENDIDA PELO ALUNO RUANN
JANSER SOARES DE CASTRO E ORIENTADA PELA
PROF.ª DR.ª HELIA HARUMI SATO
Assinatura da orientadora
Ficha catalográfica
Universidade Estadual de Campinas
Biblioteca da Faculdade de Engenharia de Alimentos
Helena Joana Flipsen - CRB 8/5283
Castro, Ruann Janser Soares de, 1987-
C279e CasExperimental mixture design as a tool for proteases production by Aspergillus
niger and obtaining of protein hydrolysates with multiple functional and biological
properties / Ruann Janser Soares de Castro. – Campinas, SP : [s.n.], 2015.
CasOrientador: Hélia Harumi Sato.
CasTese (doutorado) – Universidade Estadual de Campinas, Faculdade de
Engenharia de Alimentos.
Cas1. Protease. 2. Hidrolisados proteicos. 3. Atividade biológica. 4. Propriedades
funcionais. 5. Planejamento experimental de misturas. I. Sato, Hélia Harumi,1952-.
II. Universidade Estadual de Campinas. Faculdade de Engenharia de Alimentos.
III. Título.
Informações para Biblioteca Digital
Título em outro idioma: Aplicação da ferramenta de planejamento experimental de misturas
como estratégia para a produção de proteases por Aspergillus niger e obtenção de hidrolisados
proteicos com múltiplas propriedades funcionais e biológicas
Palavras-chave em inglês:Proteases
Protein hydrolysates
Biological activity
Functional properties
Experimental mixture design
Área de concentração: Ciência de Alimentos
Titulação: Doutor em Ciência de Alimentos
Banca examinadora:Hélia Harumi Sato [Orientador]
Juliano Lemos Bicas
Júnio Cota Silva
Luciana Francisco Fleuri
Marcela Pavan Bagagli
Data de defesa: 02-03-2015
Programa de Pós-Graduação: Ciência de Alimentos
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Banca examinadora
Profa. Dra. Hélia Harumi Sato
Orientadora – DCA/FEA/UNICAMP
Prof. Dr. Juliano Lemos Bicas
Membro Titular – DCA/FEA/UNICAMP
Dr. Júnio Cota Silva
Membro Titular – VTT Brasil Pesquisa e Desenvolvimento
Profa. Dra. Luciana Francisco Fleuri
Membro Titular – UNESP
Dra. Marcela Pavan Bagagli
Membro Titular – Lanagro/MAPA
Prof. Dr. Alexandre Leite Rodrigues de Oliveira
Membro Suplente – Instituto de Biologia/UNICAMP
Dr. Francisco Fábio Cavalcante Barros
Membro Suplente - INPI
Profa. Dra. Luciana Ferracini dos Santos
Membro Suplente – UNIARARAS
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Dedico este trabalho à minha família e aos
meus amigos por todo apoio, carinho e companheirismo.
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Agradecimentos
Ao meu querido e bom Deus por estar comigo em todos os momentos me dando força e a certeza
de que Ele está no comando de tudo.
À mainha e ao “pain”, Ivoneide e Antonio, por serem as pessoas que mais se alegram pelas
minhas conquistas, por todo amor, compreensão e apoio!
À minha querida irmã, Ruanna, pelo companheirismo, apoio e pelos ótimos momentos
compartilhados.
Aos meus tios, tias, primos e avós por serem pessoas tão maravilhosas e que me fazem tão bem.
À professora Hélia, pelo cuidado, carinho, atenção, preocupação, paciência, dedicação e por todo
conhecimento compartilhado ao longo desses anos de muito aprendizado e crescimento.
Aos meus amigos da Engenharia de Alimentos da UFC: Renata, Moara, Talita, Thiago, Monique,
Millena, Delane, Tatiane, Karina, Niédila e Cinthia por estarem sempre presentes apesar da
distância, pelo incentivo, carinho e amizade sincera.
Às professoras Suzana Cláudia e Claudia Martins da UFC, por terem me ensinado a base da
pesquisa e pelo conhecimento imprescindível que tem me acompanhado ao longo desses anos.
À professora Maria do Carmo Passos Rodrigues da UFC, pelos ensinamentos, apoio, carinho,
torcida e pelas longas horas de conversa. Por ser uma pessoa tão especial, que me incentiva a ir
cada vez mais longe e se alegra por cada conquista alcançada.
À professora Elizabeth Mary Cunha da Silva da UFC pelo enorme carinho e consideração.
Ao Dr. Gustavo Saavedra da Embrapa Agroindústria Tropical de Fortaleza pela oportunidade de
estágio, incentivo e conhecimento compartilhado.
Aos meus amigos da Embrapa Agroindústria Tropical: Adriana, Ana Paula, Andréa, Carina,
Carol, Cyntia, Genilton, Helder, Janaína, Kally, Leise, Luciana, Manuella, Mariza, Millena,
Myrella, Natália Lima, Natália Moura, Rakel e Virna, por sempre me receberem de portas
abertas, pela amizade sincera e por todos os momentos de apoio, incentivo e força.
À delegação cearense da FEA: Aliciane, Ana Laura, Bruna, Carine, Carol, Jessika, Mirela e
Wellington por trazerem um pouco do Ceará para Campinas.
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Aos meus amigos do Laboratório de Bioquímica de Alimentos da FEA: André, Bia, Bruna,
Camilo, Dani, Débora, Elaine, Erica, Eulália, Fabíola, Fernanda, Gilberto, Giulia, Isabela,
Jessika, Joelise, Lívia, Marcela, Paula Menezes, Paula Speranza, Ricardo, Tati, Val e Viviane,
pelos momentos de descontração, ajuda e acolhimento.
Agradecimento especial à Fabíola pela demonstração diária de carinho, cuidado e
companheirismo. À Paulinha pelas horas de conversa e descontração, pelos conselhos e apoio. À
Val e à Bia por todo o carinho, atenção e força. À Vivi pela companhia diária nos almoços, pelo
cuidado e amizade.
Às minhas alunas de iniciação científica Juliana Albernaz, Marília Soares e Tânia Nishide por me
darem a oportunidade de orientá-las, pelo trabalho desenvolvido sempre com muita
responsabilidade e competência e pela ótima convivência.
À Bianca Pelici, à Paula Okuro e ao Tainan pela amizade, parceria nas corridas e treinos e por
estarem sempre a postos para ajudar.
Aos amigos adquiridos ao longo desses anos na república, disciplinas e outros laboratórios:
Alaíde, Angélica, Cyntia Cabral, David, Janclei, Luiz Vieira, Manu, Renata, Rodrigo, Tiago e
Verônica.
Ao Dr. Marcio Schmiele e ao Laboratório de Cereais, Raízes e Tubérculos pelo auxílio nas
análises de granulometria e composição centesimal dos resíduos agroindustriais utilizados neste
estudo.
Ao professor Alexandre Oliveira e ao Rodrigo Fabrizzio do Laboratório de Regeneração Nervosa
(IB-Unicamp) pelo suporte e auxílio dados para execução dos experimentos de atividade anti-
adipogênica.
Ao Gepea pela grande oportunidade de participar como orientador em alguns projetos, pela
competência e seriedade sempre presentes durante os serviços prestados.
Aos alunos de graduação da FEA que tive o privilégio de ser PED nas disciplinas de Bioquímica
e que foram tão importantes para o meu amadurecimento profissional.
A todos os professores que fazem parte da FEA pela competência e contribuição com valiosos
conhecimentos repassados durante as disciplinas.
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Aos funcionários da FEA: Cosme, Marcos Sampaio, Marcos A. de Castro, Guiomar e Jardette
pela competência e auxílio prestados.
Aos funcionários da Biblioteca da FEA: Sueli de Fátima Faria, Cláudia Romano, Monica
Wohnrath e José Carlos Marcondes pelo auxílio prestado. Agradecimento especial à Bianca
Fernandes, Geraldo Silva e Márcia Sevillano pela atenção e disposição em ajudar sempre.
Às funcionárias da limpeza, D. Vilani e Elizângela, por manterem a organização e limpeza do
nosso ambiente de trabalho e pela simpatia dos “bons dias” de todas as manhãs.
À Bunge Alimentos S.A., Cooper Ovos e Alibra pela doação de material para execução deste
trabalho.
Aos membros da banca examinadora: Dr. Alexandre Leite Rodrigues de Oliveira, Dr. Francisco
Fábio Cavalcante Barros, Dr. Juliano Lemos Bicas, Dr. Júnio Cota Silva, Dra. Luciana Francisco
Fleuri, Dra. Luciana Ferracini dos Santos e Dra. Marcela Pavan Bagagli pela valorosa
contribuição neste trabalho.
Ao CNPq pela concessão da bolsa de estudos.
À FAPESP pelo apoio financeiro necessário ao desenvolvimento deste trabalho.
Ao Departamento de Ciência de Alimentos, à Faculdade de Engenharia de Alimentos e à
Unicamp pela grande oportunidade de desenvolvimento, aprimoramento dos conhecimentos
científicos e formação profissional.
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Sempre que possível, não deixes de cooperar com quem precisa de ajuda.
Não respondas simplesmente ao teu próximo:
“Vai e volta amanhã, e eu te darei algo”, se o tens disponível agora e podes ajudar.
(Provérbios 3:27-28)
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Resumo
O presente trabalho teve como objetivo utilizar a técnica de delineamento experimental de
misturas como estratégia para a produção de proteases por Aspergillus niger LBA02 em
fermentação semissólida utilizando formulações contendo diferentes resíduos agroindustriais e
produção de hidrolisados proteicos com atividades biológicas e funcionais utilizando a hidrólise
enzimática simultânea de proteínas de diferentes fontes. Efeitos sinérgicos e significativos entre
as misturas quaternárias de farelo de trigo, farelo de soja, farelo de algodão e casca de laranja
foram observados durante a fermentação de A. niger LBA02, atingindo aumentos de 33,7, 7,6,
30,8 e 581,7%, respectivamente, na produção de proteases em comparação com os substratos
utilizados de forma isolada. O estudo das características bioquímicas das preparações enzimáticas
mostrou que a linhagem de A. niger LBA02 foi capaz de secretar diferentes tipos de proteases em
resposta a cada substrato. De um modo geral, as proteases apresentaram atividade ótima a 50 °C e
na faixa de pH de 3 a 4. As maiores diferenças entre as preparações de proteases foram
observadas para os parâmetros cinéticos e termodinâmicos de ativação e inativação térmica. Na
hidrólise enzimática de misturas contendo proteína isolada de soja, proteínas do soro de leite e da
clara de ovo utilizando a preparação comercial Flavourzyme® 500L foram observados efeitos
sinérgicos entre as formulações contendo misturas binárias ou ternárias, para vários parâmetros.
Para atividade antioxidante determinada pelo método DPPH, a mistura contendo proteínas do
soro de leite e proteínas da clara de ovo apresentaram aumentos de 45,1 e 37,3% na atividade,
quando comparada aos hidrolisados obtidos com as duas fontes de forma isolada,
respectivamente. Entre as propriedades funcionais, a capacidade emulsificante foi a que
apresentou maior efeito sinérgico, onde os hidrolisados contendo a mistura ternária de proteína
isolada de soja, proteínas do soro de leite e da clara de ovo, alcançaram valores 2 a 12 vezes
superiores, em relação aos hidrolisados obtidos de forma isolada. A determinação da atividade
anti-adipogênica dos hidrolisados revelou que o tratamento de células pré-adipócitas 3T3-L1 com
a mistura binária de proteínas do soro de leite e da clara de ovo na concentração de 1.200 ppm
reduziu o acúmulo relativo de lipídeos nas células em até 47,9%. Em relação à atividade
antimicrobiana, a linhagem de Staphylococcus aureus ATCC 6538 foi a única que apresentou
inibição do crescimento quando cultivada em meio suplementado com uma mistura binária de
proteína isolada de soja e proteínas da clara de ovo não hidrolisadas, resultando em inibição de
16,82%. Os hidrolisados obtidos com misturas binárias de proteínas do soro de leite e da clara de
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ovo ou proteína isolada de soja e soro de leite estimularam o crescimento de bactérias lácticas e
probióticas, resultando em aumentos de 29,4 a 100% comparados aos meios não suplementados.
A utilização de composições contendo diferentes preparações comerciais de proteases para
hidrólise de proteína isolada de soja e estudo da atividade antioxidante mostrou diferentes
resultados para cada método utilizado. Para inibição dos radicais DPPH, os hidrolisados obtidos
com Flavourzyme® 500L combinada com Alcalase
® 2.4L mostraram o maior efeito sinérgico,
com aumentos de 10,9 e 13,2% da atividade antioxidante, em comparação aos hidrolisados
produzidos com as enzimas isoladas. Os hidrolisados obtidos utilizando a mistura ternária de
Flavourzyme® 500L, Alcalase
® 2.4L e YeastMax
® A apresentaram o maior poder de inibição da
auto-oxidação do ácido linoleico.
Palavras-chave: proteases, hidrolisados proteicos, atividade biológica, propriedades funcionais,
planejamento experimental de misturas.
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Abstract
This study aimed to use the mixture experimental design technique as a strategy to produce
proteases by Aspergillus niger LBA02 under solid state fermentation, using formulations
containing different agroindustrial wastes. It also aimed to produce protein hydrolysates with
biological and functional activities using the simultaneous enzymatic hydrolysis of proteins from
the different sources. Synergistic and significant effects between the quaternary mixtures of
wheat bran, soybean meal, cottonseed meal and orange peel were observed during fermentation
by A. niger LBA02, reaching increases of 33.7, 7.6, 30.8 and 581.7%, respectively, for the
production of proteases as compared to the isolated substrates. The study of the biochemical
properties of the enzyme preparations showed that the strain of A. niger LBA02 was able to
secrete different types of proteases in response to each substrate. In general, the proteases showed
optimal activity at 50 °C in the pH range from 3 to 4. The major differences between the protease
preparations were observed for the kinetic and thermodynamic parameters of thermal activation
and inactivation. In the enzymatic hydrolysis of mixtures containing soy protein isolate, bovine
whey protein and egg white protein using the commercial preparation FlavourzymeTM
500L,
synergistic effects were observed for various parameters between formulations containing binary
or ternary mixtures,. For antioxidant activity as determined by the DPPH assay, the mixture
containing bovine whey protein and egg white protein showed increases of 45.1 and 37.3% in
their activities as compared to hydrolysates obtained with the isolated proteins, respectively. Of
the functional properties, the emulsifying capacity showed the greatest synergistic effect, the
hydrolysates containing the ternary mixture of soy protein isolate, bovine whey protein and egg
white protein, showing increases ranging from 2 to 12-fold as compared to the hydrolysates
obtained using isolated substrates. The determination of the anti-adipogenic activity of the
hydrolysates indicated that the treatment of 3T3-L1 preadipocyte cells with 1200 ppm of the
mixture containing bovine whey protein and egg white protein reduced the relative lipid
accumulation to 47.9%. With respect to antimicrobial activity, the strain of Staphylococcus
aureus ATCC 6538 was the only one which showed growth inhibition when cultivated in a
medium supplemented with a non-hydrolyzed binary mixture of soy protein isolate and egg white
protein, resulting in inhibition of 16.82%. The hydrolysates obtained with binary mixtures of
bovine whey protein and egg white protein or soy protein isolate and bovine whey protein
stimulated the growth of probiotic and lactic acid bacteria, reaching increases from 29.4 to 100%
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when compared to non-supplemented media. The use of formulations containing various
commercial preparations of proteases for the hydrolysis of soy protein isolate and the study of
antioxidant activities showed different results for each method. For DPPH radical scavenging, the
hydrolysates obtained with FlavourzymeTM
500L combined with AlcalaseTM
2.4L showed greater
synergistic effects, with increases of 10.9 and 13.2% in antioxidant activity as compared to the
hydrolysates produced with individual enzymes. The hydrolysates obtained from ternary mixtures
of FlavourzymeTM
500L, AlcalaseTM
2.4L and YeastMaxTM
A showed the greatest power of
inhibition of linoleic acid autoxidation.
Keywords: proteases, protein hydrolysates, biological activities, functional properties,
experimental mixture design.
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Sumário
Introdução ........................................................................................................................................ 1
Referências ...................................................................................................................................... 4
Capítulo I: Produção de enzimas por fermentação semissólida: aspectos gerais e uma
avaliação direcionada às características físico-químicas dos substratos para otimização de
processos. ........................................................................................................................................ 7
Resumo ............................................................................................................................................ 8
1. Introdução .................................................................................................................................... 9
2. Avaliação de parâmetros de cultivo para FSS ...........................................................................14
2.1. Tamanho de partículas... .................................................................................................14
2.2. Capacidade de absorção de água.. ..................................................................................17
2.3. Composição química.......................................................................................................19
3. Considerações finais.............................................................................................................. ....20
Referências .................................................................................................................................... 21
Capítulo II: Peptídeos com atividade biológica: processos de obtenção, purificação,
identificação e potenciais aplicações. ......................................................................................... 27
Resumo .......................................................................................................................................... 28
1. Introdução .................................................................................................................................. 29
2. Principais processos de obtenção de peptídeos bioativos..........................................................32
2.1. Fermentação....................................................................................................................32
2.2. Hidrólise enzimática........................................................................................................35
3. Concentração, purificação e identificação de peptídeos bioativos............................................37
4. Propriedades biológicas de peptídeos bioativos........................................................................39
4.1. Peptídeos com atividade antimicrobiana.........................................................................39
4.2. Peptídeos com atividade antioxidante.............................................................................42
4.3. Peptídeos com atividade antiadipogênica.......................................................................48
4.4. Peptídeos com atividade anti-hipertensiva......................................................................49
4.5. Indução do crescimento de bactérias ácido lácticas e probióticas..................................52
5. Conclusão .................................................................................................................................. 53
Referências .................................................................................................................................... 54
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Capítulo III: Improving the functional properties of milk proteins: focus on the specificities
and mechanisms of action of proteolytic enzymes .................................................................... 67
Abstract ......................................................................................................................................... 68
1. Introduction ............................................................................................................................... 69
2. Functional properties of milk proteins ...................................................................................... 71
2.1. Solubility ........................................................................................................................ 71
2.2. Gelation properties ......................................................................................................... 72
2.3. Emulsifying properties ................................................................................................... 73
3. Conclusion ................................................................................................................................. 75
References ..................................................................................................................................... 76
Capítulo IV: Improving the protease production by Aspergillus niger under solid state
fermentation by substrate formulation using statistical mixture design ............................... 79
Abstract ......................................................................................................................................... 80
1. Introduction ............................................................................................................................... 81
2. Materials and Methods .............................................................................................................. 82
2.1. Agroindustrial wastes and centesimal composition ........................................................ 82
2.2. Microorganism culture ................................................................................................... 82
2.3. Protease production and sampling .................................................................................. 83
2.4. Statistical mixture design................................................................................................ 83
2.5. Determination of protease activity ................................................................................. 84
2.6. Calculations and statistics ............................................................................................... 85
3. Results and Discussion .............................................................................................................. 85
3.1. Chemical composition of the agroindustrial wastes ....................................................... 85
3.2. Synergistic and antagonistic effects of the agroindustrial wastes on protease
production……………………………………………………………………………………..88
3.3. Interpretation of contour plots ........................................................................................ 90
3.4. Model fitting, regression analysis and validation tests ................................................... 93
4.Conclusion .................................................................................................................................. 96
References ..................................................................................................................................... 96
Capítulo V: A new approach for proteases production by Aspergillus niger based on the
kinetic and thermodynamic parameters of the enzymes obtained ......................................... 99
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Abstract ....................................................................................................................................... 100
1. Introduction ............................................................................................................................. 101
2. Materials and Methods ............................................................................................................ 102
2.1. Chemical composition of the agroindustrial wastes ..................................................... 102
2.2. Microorganism culture ................................................................................................. 102
2.3. Protease production and sampling ................................................................................ 103
2.4. Determination of protease activity ............................................................................... 103
2.5. Activation energy and temperature quotient (Q10) ....................................................... 103
2.6. Determination of the kinetic parameters Km and Vmax ............................................... 104
2.7. Determination of kinetic and thermodynamic parameters for thermal inactivation ..... 104
2.7.1. Kinetic parameters for thermal inactivation ......................................................... 104
2.7.2. Thermodynamic parameters for thermal inactivation .......................................... 105
2.8. Substrate specificity of the proteases ............................................................................ 105
2.9. Calculations and statistics ............................................................................................. 106
3. Results and Discussion ............................................................................................................ 106
3.1. Chemical composition of the agroindustrial wastes ..................................................... 106
3.2. Biochemical properties of the proteases from A. niger LBA02 ................................... 108
3.2.1. Activation energy and temperature quotient (Q10) ................................................ 108
3.2.2. Kinetic parameters Km and Vmax ........................................................................ 111
3.2.3. Thermal inactivation ............................................................................................. 112
3.2.4. Substrate specificity of the enzyme ........................................................................ 119
4. Conclusions ............................................................................................................................. 120
Acknowledgements ..................................................................................................................... 121
References ................................................................................................................................... 121
Capítulo VI: Production, biochemical properties of proteases secreted by Aspergillus niger
under solid state fermentation in response to different agroindustrial substrates and their
application for production of whey protein hydrolysates with antioxidant activities ........ 125
Abstract ....................................................................................................................................... 126
1. Introduction ............................................................................................................................. 127
2. Materials and Methods ............................................................................................................ 128
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2.1. Physical–chemical characterization of the agroindustrial wastes ................................. 128
2.1.1. Chemical composition of the agroindustrial wastes ............................................. 128
2.1.2. Determination of the water absorption index (WAI) of the agroindustrial wastes128
2.1.3. Particle size ........................................................................................................... 129
2.1.4. Packing density ..................................................................................................... 129
2.2. Microorganism culture ................................................................................................. 129
2.3. Determination of the microorganism growth: radial growth rate and biomass estimation
by glucosamine level ............................................................................................................... 129
2.4. Protease production and sampling ................................................................................ 130
2.5. Effects of pH and temperature on the activity and stability of the protease determined
using an experimental design .................................................................................................. 131
2.6. Determination of protease activity ............................................................................... 131
2.7. Determination of milk-clotting activity ........................................................................ 132
2.8. Application of the proteases to protein hydrolysis ....................................................... 132
2.9. Determination of antioxidant activities ........................................................................ 133
2.9.1. DPPH radical-scavenging activity ........................................................................ 133
2.9.2. Total antioxidant capacity ..................................................................................... 133
2.10. Calculations and statistics ............................................................................................. 133
3. Results and Discussion ............................................................................................................ 134
3.1. Chemical composition of the agroindustrial wastes ..................................................... 134
3.2. The influence of the water absorption index (WAI) on protease production ............... 135
3.3. The influence of the granulometric distribution and the apparent density of the
agroindustrial wastes on protease production .......................................................................... 136
3.4. Determination of the microorganism growth ............................................................... 139
3.5. Biochemical characteristics of protease from A. niger LB02 ....................................... 140
3.5.1. Effects of pH and temperature on the activity and stability of the protease
determined using an experimental design ............................................................................ 140
3.5.2. Determination of milk-clotting activity ................................................................. 146
3.6. Application of the proteases from A. niger to bovine whey protein hydrolysis and
antioxidant activities of the hydrolysates ................................................................................ 147
4. Conclusion ............................................................................................................................... 150
xxiii
References ................................................................................................................................... 150
Capítulo VII: Comparison and synergistic effects of intact proteins and their hydrolysates
on the functional properties and antioxidant activities in a simultaneous process of
enzymatic hydrolysis ................................................................................................................. 155
Abstract ....................................................................................................................................... 156
1. Introduction ............................................................................................................................. 157
2. Materials and Methods ............................................................................................................ 158
2.1. Reagents........................................................................................................................ 158
2.2. Preparation of protein hydrolysates .............................................................................. 158
2.3. Statistical mixture design.............................................................................................. 158
2.4. TCA soluble protein content ......................................................................................... 159
2.5. Antioxidant activities .................................................................................................... 159
2.5.1. ORAC assay ........................................................................................................... 159
2.5.2. DPPH radical-scavenging activity ........................................................................ 160
2.5.3. Inhibition of linoleic acid autoxidation ................................................................. 160
2.6. Functional properties .................................................................................................... 161
2.6.1. Solubility ................................................................................................................ 161
2.6.2. Heat stability ......................................................................................................... 161
2.6.3. Emulsifying property ............................................................................................. 161
2.6.4. Foaming capacity .................................................................................................. 162
2.7. Calculations and statistics ............................................................................................. 162
3. Results and Discussion ............................................................................................................ 163
3.1. Comparison of the functional properties between the intact proteins and their
hydrolysates ............................................................................................................................. 163
3.2. Comparison of the antioxidant activities between the intact proteins and their
hydrolysates ............................................................................................................................. 165
3.3. Comparison of the TCA soluble protein content between the intact proteins and their
hydrolysates ............................................................................................................................. 165
3.4. Synergistic effects and antagonistic effects of the intact proteins and their hydrolysates
on functional properties, antioxidant activities and TCA soluble protein content .................. 166
3.5. Mixture contour plots for functional properties, antioxidant activities and TCA soluble
protein contents........................................................................................................................ 168
xxiv
3.6. Analysis of variance (ANOVA) and models for the functional properties, antioxidant
activities and TCA soluble protein contents of the intact proteins and their hydrolysates ..... 170
4. Conclusions ............................................................................................................................. 173
Acknowledgments ....................................................................................................................... 173
References ................................................................................................................................... 173
Capítulo VIII: Synergistic effects of protein hydrolysates on the suppression of lipid
accumulation in 3T3-L1 adipocytes ......................................................................................... 177
Abstract ....................................................................................................................................... 178
1. Introduction ............................................................................................................................. 179
2. Materials and Methods ............................................................................................................ 180
2.1. Reagents........................................................................................................................ 180
2.2. Preparation of protein hydrolysates .............................................................................. 180
2.3. Statistical mixture design.............................................................................................. 181
2.4. Determination of the TCA-soluble protein ................................................................... 182
2.5. Inhibition of the relative lipid accumulation in the 3T3-L1 adipocytes ....................... 182
2.5.1. Cell culture ............................................................................................................ 182
2.5.2. Assay for the relative lipid accumulation (RLA) ................................................... 182
2.5.3. Effect of the concentration of the protein hydrolysates and various treatments on
the RLA. ............................................................................................................................... 183
2.5.4. Fractionation of the hydrolysates by ultrafiltration .............................................. 183
2.6. Calculations and statistics ............................................................................................. 184
3. Results and Discussion ............................................................................................................ 184
3.1. Comparative analysis of the TCA-soluble protein and the RLA (%) between the intact
proteins and their hydrolysates. ............................................................................................... 184
3.2. Synergistic and antagonistic effects of the intact proteins and their hydrolysates on the
TCA-soluble protein and the RLA (%) ................................................................................... 185
3.3. Mixture-contour plots for TCA-soluble protein and RLA (%) .................................... 187
3.4. Analysis of variance (ANOVA) and models for the TCA-soluble protein and the RLA
(%) of the intact proteins and their hydrolysates ..................................................................... 189
3.5. Effect of the concentration of protein hydrolysates and various treatments on the
RLA…………………………………………………………………………………………..191
3.6. Fractionation of the hydrolysates by ultrafiltration. ..................................................... 193
xxv
4. Conclusions ............................................................................................................................. 195
Acknowledgments ....................................................................................................................... 195
References ................................................................................................................................... 195
Capítulo IX: Atividade antimicrobiana de hidrolisados de proteína isolada de soja, soro de
leite e clara de ovo. .................................................................................................................... 199
Resumo ........................................................................................................................................ 200
1. Introdução ................................................................................................................................ 201
2. Material e métodos .................................................................................................................. 202
2.1. Protease ......................................................................................................................... 202
2.2. Determinação da atividade de protease ........................................................................ 203
2.3. Obtenção dos hidrolisados proteicos ............................................................................ 203
2.4. Determinação da atividade antimicrobiana .................................................................. 205
2.4.1. Micro-organismos e condições de cultivo ............................................................. 205
2.4.2. Determinação da atividade antimicrobiana ......................................................... 205
2.5. Análises estatísticas ...................................................................................................... 206
3. Resultados e Discussão ........................................................................................................... 206
4. Conclusões .............................................................................................................................. 216
Referências bibliográficas ........................................................................................................... 217
Capítulo X: Growth promotion of bifidobacteria and lactic acid bacteria strains by protein
hydrolysates using a statistical mixture design ....................................................................... 221
Abstract ....................................................................................................................................... 222
1. Introduction ............................................................................................................................. 223
2. Materials and Methods ............................................................................................................ 224
2.1. Reagents........................................................................................................................ 224
2.2. Preparation of protein hydrolysates .............................................................................. 224
2.3. Determination of the TCA-soluble proteins ................................................................. 225
2.4. Growth performance of bifidobacteria and lactic acid bacteria strains in the media
supplemented with intact and hydrolyzed proteins ................................................................. 225
2.4.1. Microorganisms and culture conditions ............................................................... 225
2.4.2. Bacterial growth in the media supplemented with intact and hydrolyzed proteins226
xxvi
2.4.3. Effect of concentration of protein hydrolysates on cell growth ............................ 226
2.5. Calculations and statistics ............................................................................................. 226
3. Results and Discussion ............................................................................................................ 227
3.1. Comparative analysis of the TCA-soluble proteins and bacteria growth between the
intact proteins and their hydrolysates. ..................................................................................... 227
3.2. Synergistic and antagonistic effects of the intact proteins and their hydrolysates on the
TCA-soluble proteins and bacteria growth (%) ....................................................................... 229
3.3. Mixture contour plots for TCA-soluble proteins and bacteria growth (%) .................. 230
3.4. Analysis of variance (ANOVA) and models for the TCA-soluble proteins and bacteria
growth (%) ............................................................................................................................... 231
3.5. Effect of the concentration of the protein hydrolysates on cell growth ........................ 233
4. Conclusion ............................................................................................................................... 235
Acknowledgements ..................................................................................................................... 235
References ................................................................................................................................... 235
Capítulo XI: Synergistic actions of proteolytic enzymes for production of soy protein
isolate hydrolysates with antioxidant activities: an approach based on enzymes
specificities.. ............................................................................................................................... 239
Abstract ....................................................................................................................................... 240
1. Introduction ............................................................................................................................. 241
2. Material and Methods .............................................................................................................. 243
2.1. Reagents........................................................................................................................ 243
2.2. Enzymes........................................................................................................................ 243
2.3. Determination of protease activity ............................................................................... 243
2.4. Kinetic parameters for thermal inactivation ................................................................. 243
2.5. Preparation of protein hydrolysates .............................................................................. 244
2.6. Statistical mixture design.............................................................................................. 244
2.7. Determination of TCA soluble protein content ............................................................ 246
2.8. Determination of antioxidant activities ........................................................................ 246
2.8.1. DPPH radical-scavenging activity ........................................................................ 246
2.8.2. Inhibition of linoleic acid autoxidation ................................................................. 246
2.8.3. Reducing power assay ........................................................................................... 247
xxvii
2.8.4. Total antioxidant capacity ..................................................................................... 247
2.9. Calculations and statistics ............................................................................................. 248
3. Results and Discussion ............................................................................................................ 248
3.1. Investigation of thermal inactivation modulation of the enzyme by the substrate or
products from soy protein isolate hydrolysis using kinetic parameters................................... 248
3.2. Synergistic and antagonistic effects of the proteases on production of soy protein isolate
hydrolysates with antioxidant activities .................................................................................. 252
4. Conclusion ............................................................................................................................... 259
References ................................................................................................................................... 260
Conclusões gerais ....................................................................................................................... 265
Sugestões para trabalhos futuros ............................................................................................. 269
xxviii
1
Introdução
As proteases constituem um dos grupos de enzimas mais importantes comercialmente,
respondendo por aproximadamente 60% do mercado mundial de enzimas, sendo amplamente
utilizadas nas indústrias de detergentes, couro, produtos farmacêuticos, alimentos e biotecnologia
(Vijayaraghavan et al., 2014). Estas enzimas estão amplamente distribuídas na natureza e podem
ser obtidas a partir de uma grande diversidade de fontes, tais como plantas, animais e micro-
organismos. Destas fontes, os micro-organismos apresentam um grande potencial para a
produção de proteases, devido à sua diversidade bioquímica e susceptibilidade à manipulação
genética. Além disso, as proteases microbianas são predominantemente extracelulares,
diminuindo a necessidade de etapas complexas para a recuperação da enzima a partir do meio
fermentativo (Muthulakshmi et al., 2011).
Diversas espécies de fungos filamentosos têm sido exploradas em processos fermentativos
para a produção de metabólitos e enzimas industriais. Aspergillus niger possui uma longa
tradição de utilização industrial na produção de enzimas e ácidos orgânicos. Muitos destes
produtos foram listados como ''Geralmente Reconhecidos como Seguros (GRAS)'' pelo FDA
(Food and Drug Administration) (Schuster et al., 2002). De acordo com Pel et al. (2007), o
sequenciamento do genoma de A. niger identificou cerca de 198 genes envolvidos na codificação
de proteases, tornando-se assim uma das mais importantes fontes de proteases fúngicas.
Nos últimos anos, processos biotecnológicos inovadores têm explorado a fermentação
semissólida (FSS) como uma tecnologia promissora. No caso específico do cultivo de fungos
filamentosos, a FSS mostra-se um processo atraente visto que os substratos sólidos apresentam
características semelhantes ao habitat natural dos fungos, resultando em melhor crescimento e
secreção de uma ampla variedade de enzimas. Características da FSS, como menor risco de
contaminação, maior produtividade, utilização de substratos de baixo custo, simplicidade de
processamento, maior facilidade de separação e purificação de produtos, requisitos mais baixos
de energia e menor produção de águas residuais tornam esse processo mais atrativo quando
comparado à fermentação submersa (Chutmanop et al. , 2008;. Chen et al, 2014).
Na literatura, diferentes resíduos agroindustriais têm sido utilizados para a produção de
protease por FSS, como farelos de trigo, soja, arroz e lentilha e cascas de laranja, maçã e banana
(Chutmanop et al, 2008; Monton et al, 2013; Karatas et al, 2013).
2
A expressão e secreção de diferentes conjuntos de proteases e outras enzimas pelo micro-
organismo podem ser reguladas pelo tipo de substrato utilizado como fonte de carbono e
nitrogênio. Este é um aspecto particularmente importante, sendo uma nova abordagem para a
obtenção de preparações enzimáticas com propriedades bioquímicas desejáveis.
A caracterização bioquímica de enzimas é importante para avaliar o seu potencial
biotecnológico. O estudo de propriedades, tais como especificidade de substrato, pH ótimo de
atuação, perfis de temperatura para atividade e estabilidade, características cinéticas e
termodinâmicas pode ser utilizado para direcionar a aplicação destas enzimas em processos
industriais específicos (Castro e Sato, 2013).
Dentre as aplicações de proteases, processos envolvendo a hidrólise de proteínas têm sido
estudados para a produção de peptídeos com atividade biológica. Peptídeos bioativos são
definidos como frações específicas de proteínas com sequência de aminoácidos que promovem
um impacto positivo em várias funções biológicas, incluindo efeitos como atividades:
antioxidante, anti-hipertensiva, antitrombótica, antiadipogênica e antimicrobiana (Biziulevicius et
al., 2006; Zhang et al., 2010; Tsou et al., 2010; Tavares et al., 2011). Estes peptídeos apresentam
sequências de 2-20 aminoácidos e massas moleculares inferiores a 6000 Da.
A bioatividade é definida principalmente pela composição e sequência de aminoácidos
(Sarmadi e Ismail, 2010). Essa enorme diversidade funcional coloca os peptídeos e as proteínas
em posição de destaque no campo das aplicações biotecnológicas (Miranda e Liria, 2008), sendo
apontados por alguns autores como possíveis substitutos de substâncias químicas utilizadas como
fármacos ou conservadores de alimentos (Hong et al., 2008).
Os processos de produção de proteases assim como os de hidrólise enzimática de
proteínas para obtenção de peptídeos bioativos têm sido extensivamente relatados na literatura
utilizando substratos de forma individual. A formulação de meios fermentativos utilizando a
mistura de diferentes resíduos agroindustriais, bem como a hidrólise enzimática simultânea de
formulações contendo mais de um tipo de proteína pode ser utilizada como estratégia para
balancear componentes específicos, resultando em produtos com características mais atrativas.
O planejamento de misturas é uma classe especial de delineamento experimental, onde as
proporções entre os componentes ou fatores, assim como as interações entre os mesmos e os seus
efeitos sobre a variável resposta podem ser utilizados para maximizar resultados e aperfeiçoar
3
processos. A utilização desta técnica permite um melhor entendimento dos dados experimentais,
pois inclui avaliação estatística e geração de gráficos e modelos que facilitam a interpretação dos
resultados assim como a verificação de efeitos sinérgicos ou antagônicos entre os componentes
das misturas.
Nesse contexto, o presente trabalho visou utilizar a técnica de delineamento experimental
de misturas como estratégia para a produção de proteases por Aspergillus niger LBA02 em
fermentação semissólida utilizando formulações contendo diferentes resíduos agroindustriais e
produção de hidrolisados com propriedades multifuncionais utilizando a hidrólise enzimática
simultânea de formulações contendo proteínas de diferentes fontes. O estudo da obtenção de
hidrolisados proteicos com atividade antioxidante utilizando diferentes preparações comerciais de
proteases de forma isolada ou combinada também foi relatado. O trabalho encontra-se dividido
em forma de capítulos como descrito a seguir.
O Capítulo I consiste em uma Revisão Bibliográfica sobre aspectos gerais relacionados
aos processos de fermentação semissólida (FSS), incluindo a produção de diversos metabólitos
com foco principalmente na produção de enzimas e uma discussão de parâmetros ligados às
características físico-químicas dos resíduos agroindustriais utilizados para FSS e a influência
destes sobre a produção de enzimas.
O Capítulo II visa discutir os principais processos utilizados para obtenção de peptídeos
bioativos, com destaque para a fermentação e hidrólise enzimática. Métodos de isolamento,
purificação e caracterização destes peptídeos, aspectos relacionados às diferentes atividades
biológicas destes peptídeos, incluindo atividade antioxidante, antimicrobiana, anti-hipertensiva,
antiadipogênica e indução do crescimento de bactérias probióticas também foram apresentados.
O Capítulo III apresenta uma abordagem especial com foco na discussão dos mecanismos
de ação e especificidades de diferentes proteases e a influência destas características sobre as
propriedades funcionais de hidrolisados obtidos a partir de proteínas do leite, incluindo
solubilidade, capacidade de gelificação e propriedades emulsificantes.
O Capítulo IV foi composto pelo estudo da produção de proteases por A. niger LBA02
por fermentação semissólida utilizando como substratos farelo de trigo, farelo de soja, farelo de
algodão e casca de laranja individualmente ou combinados em misturas binárias, ternárias ou
quaternárias.
4
O Capítulo V inclui a determinação das características bioquímicas das preparações
enzimáticas de proteases produzidas em farelo de trigo, farelo de soja, farelo de algodão, casca de
laranja e a mistura quaternária destes substratos, com ênfase em parâmetros cinéticos e
termodinâmicos e especificidade quanto ao substrato.
O Capítulo VI relata a produção de proteases por A. niger LBA02 em farelo de trigo,
farelo de soja e farelo de algodão com uma discussão focada principalmente nos aspectos físico-
químicos dos substratos e o impacto dos mesmos sobre a produção da enzima. As características
bioquímicas das preparações de proteases, incluindo pH e temperatura ótimos para atividade
catalítica e estabilidade e atividade coagulante do leite foram determinadas. O perfil de atividade
antioxidante de hidrolisados de proteínas do soro de leite utilizando as diferentes preparações de
proteases também foi investigado.
Os Capítulos VII, VIII, IX e X relatam o estudo da hidrólise enzimática simultânea de
diferentes fontes de proteínas, incluindo proteína isolada de soja, proteínas do soro de leite e da
clara de ovo de forma individual e combinadas em formulações binárias e ternárias. A avaliação
de efeitos sinérgicos e antagônicos entre as diferentes fontes de proteínas sobre as propriedades
funcionais (solubilidade, estabilidade térmica, capacidade emulsificante e de formação de
espuma) e atividades biológicas (atividade antioxidante, anti-adipogênica, estímulo do
crescimento de bactérias lácticas e probióticas e atividade antimicrobiana) foi apresentada.
O Capítulo XI aborda a hidrólise enzimática de proteína isolada de soja utilizando
diferentes proteases comerciais de forma individual ou combinadas em formulações binárias e
ternárias. A determinação da atividade antioxidante dos hidrolisados obtidos foi discutida dando
especial atenção aos mecanismos de ação de cada preparação enzimática.
Referências
BIZIULEVICIUS, G. A., KISLUKHINA, O. V., KAZLAUSKAITE, J., ZUKAITE, V. Food-
protein enzymatic hydrolysates possess both antimicrobial and immunostimulatory activities: a
“cause and effect” theory of bifunctionality. FEMS Immunology and Medical Microbiology, v.
46, p. 131-138, 2006.
CASTRO, R. J. S., SATO, H. H. Synergistic effects of agroindustrial wastes on simultaneous
production of protease and α-amylase under solid state fermentation using a simplex centroid
mixture design. Industrial Crops and Products, v. 49, p. 813-821, 2013.
5
CHEN, H.-Z., LIU, Z.-H., DAI, S.-H. A novel solid state fermentation coupled with gas stripping
enhancing the sweet sorghum stalk conversion performance for bioethanol. Biotechnology for
Biofuels, v. 7, p. 1-13, 2014.
CHUTMANOP, J., CHUICHULCHERM, S., CHISTI, Y., SIRINOPHAKUN, P. Protease
production by Aspergillus oryzae in solid-state fermentation using agroindustrial substrates.
Journal of Chemical Technology and Biotechnology, v. 83, p. 1012-1018, 2008.
HONG, F. MING, L., YI, S., ZHANXIA, L., YONGQUAN, W., CHI, L. The antihypertensive
effect of peptides: a novel alternative to drugs? Peptides, v. 29, p. 1062-1071, 2008.
KARATAS, H., UYAR, F., TOLAN, V., BAYSAL, Z. Optimization and enhanced production of
α-amylase and protease by a newly isolated Bacillus licheniformis ZB-05 under solid-state
fermentation. Annals of Microbiology, v. 63, p. 45–52. 2013.
MIRANDA, M. T. M., LIRIA, C. W. Técnicas de análise e caracterização de peptídeos e
proteínas. In: PESSOA JR., A. e KILIKIAN, B. V. Purificação de Produtos Biotecnológicos.
Barueri: Manole, 2008, cap. 21, p. 411 – 427.
MONTON, S., UNREAN, P., PIMSAMARN, J., KITSUBUN, P., TONGTA, A. Fuzzy logic
control of rotating drum bioreactor for improved production of amylase and protease enzymes by
Aspergillus oryzae in solid-state fermentation. Journal of Microbiology and Biotechnology, v.
23, n. 3, p. 335–342, 2013.
MUTHULAKSHMI, C., GOMATHI, D., KUMAR, D. G., RAVIKUMAR, G., KALAISELVI,
M., UMA, C. Production, purification and characterization of protease by Aspergillus flavus
under solid state fermentation. Jordan Journal of Biological Sciences, v. 4, p. 137-148, 2011.
PEL, H. J. et al. Genome sequencing and analysis of the versatile cell factory Aspergillus niger
CBS 513.88. Nature Biotechnology, v. 25, p. 221-231, 2007.
SARMADI, B. H., ISMAIL, A. Antioxidative peptides from food proteins: a review. Peptides, v.
31, p. 1949-1956, 2010.
SCHUSTER, E., DUNN-COLEMAN, N., FRISVAD, J. C., VAN DIJCK, P. W. On the safety of
Aspergillus niger – a review. Applied Microbiology and Biotechnology, v. 59, p. 426–435,
2002.
6
TAVARES, T. G., CONTRERAS, M. M., AMORIM, M., MARTÍN-ÁLVAREZ, P. J.,
PINTADO, M. E., RECIO, I., MALCATA, F. X. Optimisation, by response surface
methodology, of degree of hydrolysis and antioxidant and ACE-inhibitory activities of whey
protein hydrolysates obtained with cardoon extract. International Dairy Journal, v. 21, p. 926-
933, 2011.
TSOU, M. J., KAO, F. J., TSENG, C. K., CHIANG, W. D. Enhancing the anti-adipogenic
activity of soy protein by limited hydrolysis with Flavourzyme and ultrafiltration. Food
Chemistry, v. 122, p. 243–248, 2010.
VIJAYARAGHAVAN, P., LAZARUS, S., VINCENT, S. G. P. De-hairing protease production
by an isolated Bacillus cereus strain AT under solid-state fermentation using cow dung:
biosynthesis and properties. Saudi Journal of Biological Sciences, v. 21, p. 27–34, 2014.
ZHANG, L., LI, J., ZHOU, K. Chelating and radical scavenging activities of soy protein
hydrolysates prepared from microbial proteases and their effect on meat lipid peroxidation.
Bioresource Technology, v. 101, p. 2084–2089, 2010.
7
Capítulo I: Produção de enzimas por fermentação semissólida: aspectos gerais
e uma avaliação direcionada às características físico-químicas dos
substratos para otimização de processos.
8
Resumo
A fermentação semissólida (FSS) vem sendo utilizada como uma tecnologia promissora para a
produção de diversos metabólitos microbianos, como as enzimas. Características deste processo,
como menor risco de contaminação, maior produtividade, utilização de substratos de baixo custo,
simplicidade de processamento, maior facilidade de separação e purificação de produtos, menor
requerimento de energia e menor produção de água residual tornam esse processo mais atrativo
quando comparado à fermentação submersa (FSm). Nesse contexto, o presente trabalho teve
como objetivo apresentar aspectos gerais relacionados aos processos de FSS traçando um
paralelo com processos de FSm. O potencial de aplicação da FSS foi fundamentalmente
embasado em dados sobre a produção de diversos metabólitos em uma análise comparativa com a
FSm com foco principalmente na produção de enzimas. A discussão de importantes parâmetros
relacionados essencialmente às características físico-químicas dos resíduos agroindustriais
utilizados para FSS e a influência destes sobre a produção de diversas enzimas também foi
apresentada.
Palavras-chave: fermentação semissólida; resíduos agroindustriais; enzimas; parâmetros físico-
químicos.
9
1. Introdução
A fermentação semissólida (FSS) vem ganhando muita credibilidade na indústria
biotecnológica nos últimos anos pelo potencial de aplicação na produção de metabólitos
biologicamente ativos, além de possuir uma grande gama de aplicações nas indústrias de
alimentos, combustível, química e farmacêutica. Além disso, a busca por processos sustentáveis e
ecologicamente corretos em substituição aos tradicionais processos químicos para a fabricação de
produtos transformou fortemente o setor industrial. Nesse contexto, a FSS alcançou muita
relevância, por apresentar diversas características que a torna ecologicamente correta (Thomas et
al., 2013).
A FSS envolve o crescimento de micro-organismos em materiais sólidos úmidos em que
os espaços entre as partículas destes materiais encontram-se preenchidos com uma fase gasosa
contínua. É importante ressaltar que a palavra “fermentação” dentro do conceito de “fermentação
semissólida” é geralmente utilizada no sentido mais amplo de “processos microbianos
controlados” e não implica que o micro-organismo está necessariamente utilizando vias
metabólicas fermentativas durante o seu cultivo (Mitchell et al., 2006).
Nos últimos anos, processos biotecnológicos inovadores têm explorado a FSS como uma
tecnologia promissora para a produção de metabólitos secundários de alto valor agregado, como
antibióticos, enzimas, ácidos orgânicos, biopraguicidas, biossurfactantes, biocombustíveis e
bioaromas (Pandey et al., 2000; Abraham et al., 2013).
Dentre estes metabólitos e devido à alta demanda industrial, as enzimas apresentam
grande potencial de aplicação. As enzimas de origem microbiana possuem grande notoriedade e
consequentemente interesse nos campos de pesquisa, pelo fato de os micro-organismos serem
excelentes fontes e apresentarem ampla diversidade bioquímica e susceptibilidade a manipulação
genética (Rao et al., 1998). Fungos filamentosos, leveduras e bactérias são amplamente utilizados
para a produção de enzimas por FSS. No caso específico do cultivo de fungos filamentosos, a
FSS mostra-se um processo atraente visto que os substratos sólidos apresentam características
semelhantes ao habitat natural dos fungos, resultando em melhor crescimento e secreção de uma
ampla variedade de enzimas. Características da FSS, como menor risco de contaminação
bacteriana (baixa atividade de água), maior produtividade, utilização de substratos de baixo custo,
simplicidade de processamento, maior facilidade de separação e purificação de produtos,
10
requisitos mais baixos de energia e menor produção de água residual tornam esse processo mais
atrativo quando comparado à fermentação submersa (FSm) (Chutmanop et al., 2008; Chen et al.,
2014). É importante ressaltar, que embora a FSS possua algumas vantagens em relação à FSm, a
avaliação do processo mais adequado será função de parâmetros como o tipo de micro-organismo
utilizado (bactérias, leveduras ou fungos filamentosos), suas exigências nutricionais e morfologia
de crescimento e consequentemente dos produtos de interesse, não existindo assim uma indicação
de qual o melhor processo. Um resumo comparativo sobre as principais características da FSm e
FSS, no qual é possível observar vantagens e desvantagens para cada tipo de processo, é
apresentado na Tabela 1. Dados relativos a alguns processos para a produção de diversos
metabólitos por FSm e FSS são apresentados na Tabela 2.
Tabela 1 – Comparação entre as principais características dos processos de fermentação
semissólida (FSS) e submersa (FSm).
A FSS desperta maior interesse econômico em regiões, como o Brasil, com abundância
em biomassa e resíduos agroindustriais de baixo custo (Castilho et al., 2000), como algodão,
arroz, laranja, soja e trigo que atingiram juntos no anos de 2012-2013, uma produção agrícola
nacional de aproximadamente 117 milhões de toneladas e uma produção mundial de 1,84 bilhão
de toneladas (FAO, 2014) (Figura 1). O processamento destes insumos dá origem a subprodutos
de baixo valor agregado, como farelos e tortas, mas de alto valor nutritivo, sendo grande parte
Características FSm FSS
Meio de cultivo Complexo Simples
Geração de efluentes Alta Baixa
Espaço requerido Grande Pequeno
Contaminação bacteriana Risco alto Baixo risco
Solubilidade e difusão de O2 Menor Maior
Energia necessária Demanda alta Demanda baixa
Controle de temperatura Simples Complexo
Controle de pH Simples Complexo
Controle da agitação Simples Complexo
Controle de nutrientes e produtos Simples Complexo
Custo Maior Menor
Recuperação e purificação de produtos Mais complexo Maior facilidade
Produtividade Menor Maior
11
destinada à alimentação animal. A utilização destes resíduos como substrato para o
desenvolvimento de processos biotecnológicos, como a produção de enzimas por FSS é um
exemplo promissor da obtenção de biomoléculas de alto valor agregado, como as enzimas, a
partir de substratos de baixo custo (Tabela 3).
Figura 1 – Dados sobre a produção brasileira e mundial (milhões de toneladas) de alguns
produtos agroindustriais que dão origem a resíduos utilizados em processos fermentativos
semissólidos (FAO, 2014).
0
10
20
30
40
50
60
70
80
90
Algodão Arroz Laranja Soja Trigo
Pro
duçã
o b
rasi
leir
a (m
ilhões
de
tonel
adas
)
0
100
200
300
400
500
600
700
800
Algodão Arroz Laranja Soja Trigo
Pro
du
ção
mu
nd
ial
(mil
hõ
es d
e to
nel
adas
)
12
Tabela 2 – Comparação entre os processos de fermentação semissólida (FSS) e submersa (FSm) para a produção de diversos
metabólitos por micro-organismos.
Metabólito
de interesse
Micro-
organismo
Meios de Cultivo Produção Referência
FSm FSS FSm FSS
Feruloil
esterase
Aspergillus
niger
Concentração em g L-1
: tartarato de
amônio (1,842), extrato de levedura (0,5),
KH2PO4 (0,2), CaCl2 (0,0132), MgSO4
(0,5), polpa de beterraba (15,0), maltose
(2,5)
Concentração em g por 100 g de polpa de
beterraba seca: tartarato de amônio (12,3),
extrato de levedura (3,4), KH2PO4 (1,3),
CaCl2 (0,09), MgSO4 (3,3) e maltose (2,5)
2,2
nkat g−1
9,6
nkat g−1
Asther et al.,
2002
Proteases Aspergillus
oryzae
Concentração em g L-1
: KH2PO4 (1,0),
MgSO4 (5,0), NaCl (5,0) e FeSO4 (0,04);
farelo de trigo (2,0%)
Farelo de trigo suplementado com solução
de sais com composição semelhante à
utilizada para o FSm
8,7
U g-1
31,2
U g-1
Sandhya et
al., 2005
Lipases Aspergillus
spp.
Concentração em g L-1
: farelo de trigo
(10,0), extrato de levedura (45,0), óleo de
soja (20,0), KH2PO4 (2,0) e MgSO4 (1,0).
Solução de elementos traço (mg L−1
):
FeSO4 (0,63), MnSO4 (0,01) e ZnSO4
(0,62)
Mistura de farelo de soja (85,7%) e casca
de arroz (14,3%) suplementada com
solução salina contendo (g L-1
): KH2PO4
(2,0), MgSO4 (1,0). Solução de elementos
traço (mg L−1
): FeSO4 (0,63), MnSO4
(0,01) e ZnSO4 (0,62). Azeite de oliva
(2,0% p/p) e nitrato de sódio (2,0% p/p)
4,52
U
25,22
U
Colla et al.,
2010
Tanino acil
hidrolase
Lactobacillus
plantarum
Concentração em g L-1
: ácido tânico
(13,16), glicose (1,5), NH4Cl (1,0), CaCl2
(1,0), K2HPO4 (0,5), KH2PO4 (0,5),
MgSO4 (0,5) e MnSO4 (0,03)
Casca de café suplementada com solução
mineral contendo (g L-1
): ácido tânico
(10,0); NH4NO3, (5,0); KH2PO4 (1,0);
NaCl (1,0), MgSO4 (1,0) e CaCl2 (0,5)
9,13
U mL-1
5,32
U mL-1
Natarajan e
Rajendran,
2012
Proteases Aspergillus
oryzae
Polpa de tomate (40 g L-1
) suplementada
com farelo de trigo (7,92 g L-1
) e NaCl
(1,18 g L-1
)
10g de polpa de tomate suplementada com
caseína (19,79 g L-1
) e NaCl (0,92 g L-1
)
2.343,5
U g-1
21.309
U g-1
Belmessikh
et al., 2013
Queratinases Aspergillus
niger
Concentração em g L-1
: (NH4)2SO4 (3,5),
KH2PO4 (1,0), MgSO4 (0,5), KCl (0,1),
ZnSO4 (5×10-3
) e pena de galinha (10
penas por L)
Mistura de penas de galinha (0,4 g) e farelo
de trigo (40 g) umedecida com solução de
(NH4)2SO4 (0,9%)
21,3
U mL-1
172,7
U mL-1
Mazotto et
al., 2013
Monacolina
K
Monascus
purpureus
Concentração em g L-1
: glicerol (180,0),
farelo de soja (20,0), NaNO3 (2,0),
MgSO4 (1,0), K2HPO4 (1,0), ZnSO4 (2,0)
e milhocina (10 mL L-1
)
Composição semelhante à utilizada para a
FSm com adição de agar (4,0%)
2.047,03
mg L-1
458,37
mg L-1
Zhang et al.,
2013
13
Tabela 3 – Produção de enzimas com aplicações industriais utilizando diferentes resíduos agroindustriais e fermentação semissólida
(FSS).
Enzima Micro-organismo Substratos Condições de cultivo Referência
Protease Populações microbianas nativas Resíduos de fibra de soja
Relação sólido:líquido: 1:1
Temperatura de incubação: 37 °C
Tempo de fermentação: 96 h
Abraham et al.,
2013
Elagitanase Aspergillus niger Bagaço de cana, sabugo de
milho e casca de coco
Tempo de fermentação: 32 h
Temperatura de incubação: 35-40 °C
Inóculo: 2×107 esporos g
-1
Buenrostro-
Figueroa et al.,
2014
Protease Aspergillus niger Farelos de trigo, soja e
algodão
Umidade inicial do meio: 50%
Tempo de fermentação: 24-96 h
Temperatura de incubação: 30 °C
Inóculo: 107 esporos g
-1
Castro et al.,
2014
Poligalacturonase Aspergillus sojae Farelo de trigo
Umidade inicial do meio: 62%
Temperatura de incubação: 37 °C
Tempo de fermentação: 96 h
Inóculo: 107 esporos g
-1
Demir e Tari,
2014
Xilanase Trichoderma viride
Farelos de trigo, soja, e
girassol, casca de arroz,
bagaço de cana e sabugo de
milho
Relação líquido:sólido: 11:10
Tempo de fermentação: 7 dias
Temperatura de incubação: 30 °C
Inóculo: 10%
Irfan et al., 2014
Peroxidase Phanerochaete chrysosporium Resíduos de mandioca
Relação líquido:sólido: 2:1
Tempo de fermentação: 10 dias
Temperatura de incubação: 30 °C
Li et al., 2014
Quitinase Penicillium ochrochloron MTCC 517 Farelos de trigo e arroz
Umidade inicial do meio: 70-74%
Tempo de fermentação: 72-96 h
Temperatura de incubação: 30 °C
Patil e Jadhav,
2014
Xilanase Sporotrichum thermophile Torta de pinhão manso
Relação sólido:líquido: 1:1,5
Temperatura de incubação: 35 °C
Tempo de fermentação: 96 h
Inóculo: 6%
Sadaf e Khare,
2014
Protease e lipase Aspergillus versicolor Torta de pinhão manso
Umidade inicial do meio: 20-70%
Tempo de fermentação: 24-240 h
Temperatura de incubação: 20-35 °C
Inóculo: 103-10
8 esporos mL
-1
Veerabhadrappa
et al., 2014
14
O presente trabalho teve como objetivo apresentar aspectos importantes para a otimização
de processos e produção de enzimas por FSS, incluindo parâmetros físico-químicos dos
substratos e algumas estratégias que vêm sendo utilizadas no meio científico.
2. Avaliação de parâmetros de cultivo para FSS
Vários aspectos importantes devem ser considerados para o desenvolvimento e otimização
de bioprocessos em FSS. Estes incluem principalmente a seleção adequada das variáveis a serem
utilizadas no processo, como a linhagem microbiana, substratos, umidade inicial do meio,
temperatura de incubação e inóculo. Nesse trabalho, será dada especial atenção aos parâmetros
físico-químicos dos substratos, como tamanho de partícula, capacidade de absorção de água e
composição química.
A seleção adequada do substrato é um aspecto de suma importância para FSS, pois o
material sólido vai atuar como suporte físico e fonte de nutrientes. Diversos materiais podem ser
utilizados como suportes para FSS, dentre os quais podemos citar suportes inertes como
vermiculita, perlita e polietileno, que podem ser embebidos com uma solução nutriente adequada
para o crescimento microbiano e suportes naturais, como os resíduos agroindustriais, que por si
só apresentam características suficientes para o desenvolvimento satisfatório dos micro-
organismos e para os quais será dada especial atenção neste trabalho. Características físico-
químicas destes substratos vêm sendo utilizadas como importantes parâmetros para o estudo da
produção de enzimas por FSS. A influência do tamanho de partículas, capacidade de absorção de
água e composição química de substratos sobre a produção de enzimas por FSS será discutida a
seguir.
2.1. Tamanho de partículas
O tamanho das partículas do substrato é um importante fator para a produção de enzimas
por FSS uma vez que está diretamente relacionado com a porosidade do meio de cultivo. A
avaliação deste parâmetro pode ser realizada por técnicas de distribuição granulométrica
utilizando peneiras com diâmetros de abertura conhecidos ou pela determinação da densidade
aparente.
Uma avaliação mais criteriosa deste parâmetro inclui a classificação das propriedades das
partículas com base nas estruturas porosas dos substratos que afetarão diretamente o crescimento
microbiano e a bioconversão dos substratos. Estas propriedades podem ser classificadas em
15
intrapartículas (propriedades térmicas, teor de umidade, granulometria, porosidade e cinética de
processos biológicos) e extrapartículas (propriedades de transferência de calor, permeabilidade e
condições de transferência de massa). É importante notar que as características das partículas dos
substratos possuem impacto direto em vários outros parâmetros, já que a FSS é um sistema
combinado de três fases principais: o substrato propriamente dito que é a fase sólida, a retenção
de água na matriz e nos espaços interpartículas que é a fase líquida e o gás presente nos espaços
ou poros que é a fase gasosa (Figura 2) (Mitchel et al., 2006; Chen e He, 2012).
Figura 2 – Esquema ilustrativo do arranjo de partículas sólidas e dos componentes principais do
sistema de FSS durante o cultivo de fungos filamentosos (Figura adaptada de Mitchel et al.,
2006).
Hifas de fungos
filamentosos
Partícula
sólida úmida
Gotículas de água nos
espaços interpartículas
Fase
gasosa
Água e nutrientes absorvidos
pela partícula
16
Em geral, partículas de substrato com tamanho reduzido proporcionam uma maior área de
superfície para o ataque microbiano, o que é considerado um fator desejável. É importante
ressaltar que partículas muito pequenas podem ter um efeito contrário, resultando em
aglomeração, redução da difusão de oxigênio e consequentemente do crescimento dos micro-
organismos, enquanto partículas maiores fornecem maiores espaços entre si, melhores condições
de transferência de calor e massa, mas podem resultar em superfície limitada para o ataque
microbiano (Pandey et al., 2001; Wong et al., 2011; Chen e He, 2012; Ruiz et al., 2012). Nesse
contexto, meios de cultivos com distribuição de tamanho de partículas heterogêneo ou com
tamanhos de partículas intermediários, seriam mais adequados para a produção de enzimas por
FSS, pois apresentariam os requisitos necessários para uma difusão satisfatória de oxigênio
aliados a uma maior área superficial para o crescimento microbiano.
Melikoglu et al., (2013) estudaram a influência de diversos parâmetros de cultivo sobre a
produção de proteases e glicoamilases pelo micro-organismo Aspergillus awamori por FSS
utilizando resíduos de pão. As partículas dos resíduos de pão fracionadas em tamanhos variando
de 5 a 50 mm foram utilizadas como meios de cultivo e apresentaram um efeito direto sobre o
crescimento microbiano e produção das enzimas durante as fermentações. Os maiores valores
para produção simultânea de protease e glicoamilase foram 56,4 e 73,6 U g-1
, respectivamente,
detectados para as fermentações conduzidas com partículas com diâmetro de 20 mm. O micro-
organismo respondeu de maneira diferente em relação à produção das enzimas em partículas de
tamanhos extremos. Para a produção de glicoamilase, os menores valores de atividade foram
detectados para as fermentações conduzidas com partículas de 5 e 10 mm, enquanto para
protease, os menores valores foram detectados para tamanho de partículas de 50 mm.
Buenrostro-Figueroa et al., (2014) avaliaram a utilização de resíduos lignocelulósicos
incluindo bagaço de cana, sabugo de milho, casca de coco e caule de candelila (Euphorbia
antisyphilitica) para produção de elagitanase por A. niger em FSS. Um dos parâmetros avaliados
incluiu a determinação da densidade aparente dos resíduos e a influência sobre a produção da
enzima. Segundo Chávez-González et al., (2010), a densidade aparente fornece informações
sobre o grau de compactação dos materiais, estando diretamente relacionado ao espaço disponível
para a transferência de massa e energia. Valores mais altos de densidade aparente implicam em
menor relação entre área e volume, o que pode resultar em problemas de difusão de oxigênio pela
redução dos espaços vazios entre as partículas. Os autores detectaram uma influência direta da
17
densidade aparente sobre a produção de elagitanase, onde os menores valores de atividade
enzimática foram detectados nos meios compostos por caule de candelila, com densidade
aparente de 0,86 g cm-3
, ao passo que, os maiores valores foram obtidos para os meios
fermentados com casca de coco, que apresentou densidade de 0,82 g cm-3
, um valor intermediário
entre os resíduos avaliados.
2.2. Capacidade de absorção de água
Outro parâmetro importante a ser considerado é a capacidade de retenção de água pelo
substrato. Essa medida indica a capacidade das partículas do substrato em absorver água e está
ligada diretamente à disponibilidade de grupos hidrofílicos para ligação com as moléculas de
água (Mussatto et al., 2009). Essa capacidade é crucial para o crescimento microbiano e
fermentação, pois apresenta impacto direto sobre características físicas do meio de cultivo, como
por exemplo, sobre as dimensões dos poros que podem ser alteradas pelo inchaço das partículas
sólidas após a absorção da água, tornando-se favoráveis ou não para a biodegradação e
bioconversão da biomassa (Chen e He, 2012). O conteúdo adequado de água no meio de cultivo
apresenta também uma importante função ligada à disponibilidade e difusão de nutrientes e aos
mecanismos de troca gasosa entre dióxido de carbono e oxigênio durante a fermentação (Torrado
et al., 2011).
A determinação da umidade crítica dos substratos também pode ser utilizada
paralelamente à estimativa da capacidade de absorção de água dos substratos. Esse parâmetro
representa a quantidade de água fortemente ligada ao suporte, e que, portanto não está disponível
para utilização pelos micro-organismos; sendo assim, recomenda-se a utilização de substratos
com baixos valores de umidade crítica (Melikoglu et al., 2013).
A determinação da capacidade de absorção de água e da umidade crítica de bagaço de
malte (resíduo da indústria cervejeira), palha de trigo, sabugos de milho, cascas de café, cortiça
de carvalho e esponja vegetal foi utilizada como parâmetro de seleção do substrato mais
adequado para produção de β-frutofuranosidase por Aspergillus japonicus ATCC 20236
(Mussatto et al., 2009). Os valores mais altos para capacidade de absorção de água foram
observados para palha de trigo, bagaço de malte e casca de café, com valores estimados em 9,95,
9,03 e 8,30 g de água por g de material, respectivamente. Para umidade crítica, bagaço de malte,
cortiça de carvalho e palha de trigo apresentaram valores de 60, 58 e 57%, respectivamente;
18
sendo estes, os mais elevados. De acordo com os autores, uma avaliação isolada destes
parâmetros não pode ser utilizada para uma indicação precisa de qual substrato induziria uma
maior produção da enzima β-frutofuranosidase por A. japonicus ATCC 20236. No entanto, estes
parâmetros podem ser usados para estimar em qual substrato, a adesão celular e o crescimento
microbiano serão favorecidos. A maior produção da enzima foi detectada quando o micro-
organismo foi cultivado em sabugo de milho, que apresentou o menor valor de umidade crítica
(50%) e o segundo menor valor para capacidade de absorção de água (3,77 g de água/g de
material) (Mussatto et al., 2009).
Orzua et al., (2009) avaliaram a viabilidade de utilização de 10 resíduos agroindustriais
como suportes para o crescimento de uma linhagem de A. niger em FSS. Os autores incluíram os
parâmetros de capacidade de absorção de água e umidade crítica dos resíduos como
determinantes para uma seleção mais adequada. O estudo apontou que, casca de coco, polpa de
maçã, cascas de limão e laranja foram os materiais de maior potencial para utilização em FSS,
uma vez que apresentaram alta capacidade de absorção de água, níveis de umidade crítica
considerados adequados, além de terem permitido uma boa taxa de crescimento da linhagem de
A. niger.
Embora haja uma indicação de que substratos com maior capacidade de absorção de água
sejam mais adequados para o cultivo de fungos filamentos em FSS, é possível inferir que quando
estes valores superam um determinado limite, os mecanismos envolvidos no desenvolvimento
dos micro-organismos e consequentemente na secreção de enzimas ficam comprometidos. Duas
considerações importantes devem ser feitas acerca disso; a primeira avaliando os substratos com
altos índices de absorção de água e a segunda, os substratos com baixa capacidade. Materiais com
alta capacidade de absorção de água apresentam um efeito desejável que é a manutenção dos
níveis de umidade ao longo do processo fermentativo. No entanto, se a quantidade de água
adicionada ao meio de cultivo for alta o suficiente para ser totalmente absorvida pelo material,
mas resulte em valores de umidade inicial muito elevados, pode haver diminuição da porosidade,
perda da estrutura da partícula, redução das trocas gasosas e maior susceptibilidade à
contaminação bacteriana; fenômenos estes que impactam negativamente o desenvolvimento e a
produção de enzimas pelos micro-organismos. Por outro lado, os substratos com baixa
capacidade de absorção de água possuem uma limitação com relação à quantidade de água a ser
adicionada aos meios de cultivo, o que pode resultar em baixa umidade inicial e
19
consequentemente redução na solubilidade de nutrientes, menor grau de inchaço do substrato e
maior tensão superficial das partículas de água, dificultando o crescimento microbiano.
2.3. Composição química
A produção de enzimas por FSS pode ser afetada pela presença de componentes químicos
específicos que podem ser adicionados ou estarem presentes naturalmente nos substratos e que
atuam como indutores. É válido ainda ressaltar que os substratos devem apresentar uma
proporção adequada entre os nutrientes que serão utilizados como fontes de carbono e nitrogênio
(relação C:N) para um crescimento satisfatório dos micro-organismos durante a fermentação
(Castro et al., 2014).
Ghanem et al., (2000) avaliaram a produção de xilanase por Aspergillus terreus utilizando
palha e farelo de trigo, sabugo de milho, casca de arroz e bagaço de cevada como substratos para
FSS. A investigação incluiu a avaliação entre a produção e o teor de celulose nos substratos, o
qual pode ser indutor da secreção da enzima. Dentre os substratos avaliados, a palha de trigo
apresentou maior quantidade de celulose (50,7%) resultando também em maior produção de
xilanase por A. terreus (16,16 U mL-1
).
Resíduos agroindustriais obtidos a partir de extração de óleo de sementes têm sido
relatados como potenciais substratos para a produção de lipases por micro-organismos devido ao
conteúdo residual de lipídeos que podem ser indutores da produção destas enzimas (Azeredo et
al., 2007; Rigo et al., 2010). Ferraz et al., (2012) estudaram a produção de lipases por
Sporobolomyces ruberrimus utilizando farelo de soja, farelo de arroz e bagaço de cana como
substratos em FSS. Dentre os resíduos avaliados, o farelo de arroz apresentou o maior conteúdo
de lipídeos (16,43%) e permitiu maior produção de lipases pelo micro-organismo.
Thanapimmetha et al., (2012) realizaram uma análise comparativa com o trabalho de
Chutmanop et al., (2008) sobre a produção de proteases pela mesma linhagem de A. oryzae
utilizando como substratos torta de pinhão-manso, farelo de trigo e farelo de arroz. A avaliação
mostrou que a produção de proteases em farelo de arroz e farelo de trigo foi 22 e 30% menor,
respectivamente, que a observada em torta de pinhão-manso. O aumento da produção de
proteases em torta de pinhão-manso foi relacionado ao alto teor de proteínas presente nesse
substrato. Quando os teores de proteína foram comparados entre os substratos, a torta de pinhão-
manso apresentou 60%, enquanto os valores estimados para os farelos de arroz e trigo foram 13-
20
14% e 12-17%, respectivamente. Segundo estes autores, as proteases secretadas pelos micro-
organismos podem ser estimuladas pelos aminoácidos presentes nas proteínas, o que resultou na
maior produção de proteases no substrato com maior quantidade de proteína. Resultados
semelhantes foram observados por Castro et al. (2014), onde o conteúdo de proteína apresentou
uma forte e significativa correlação com a produção de proteases por A. niger utilizando farelos
de trigo, soja e algodão durante as primeiras 48h de cultivo semissólido.
3. Considerações finais
A fermentação semissólida (FSS) é um processo promissor para a produção de diversas
biomoléculas, dentre elas, as enzimas. Uma análise comparativa entre este processo e a
fermentação submersa mostra as diversas vantagens da FSS. A otimização de processos para
produção de enzimas por FSS inclui o estudo de diversos parâmetros de cultivo, os quais são
extremamente variáveis dependendo da enzima que se deseja obter, do substrato utilizado e do
micro-organismo. Na presente revisão foi dada especial atenção aos parâmetros físico-químicos
dos resíduos agroindustriais, incluindo tamanho de partícula, capacidade de absorção de água e
composição química. Embora estes parâmetros tenham sido discutidos de forma isolada para uma
melhor compreensão do impacto de cada um sobre os processos fermentativos, torna-se
necessária uma avaliação conjunta de diversos fatores assim como da contribuição particular de
cada um para a definição das condições mais adequadas de cultivo microbiano para atingir altos
níveis de produtividade das moléculas de interesse.
21
Referências
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residues by native microbial populations for bench-scale alkaline protease production.
Biochemical Engineering Journal, v. 74, p. 15-19, 2013.
ASTHER, M., HAON, M., ROUSSOS, S., RECORD, E., DELATTRE, M., LESAGE-
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26
27
Capítulo II: Peptídeos com atividade biológica: processos de obtenção,
purificação, identificação e potenciais aplicações.
28
Resumo
Avanços tecnológicos recentes têm despertado grande interesse para o uso de peptídeos com
atividade biológica. Peptídeos bioativos podem ser definidos como frações específicas de
proteínas com sequência contendo de 2 a 20 aminoácidos que promovem um impacto positivo em
várias funções biológicas, incluindo efeitos como atividades: antioxidante, anti-hipertensiva,
antitrombótica, antiadipogênica, antimicrobiana e anti-inflamatória. Características especiais
como a baixa toxicidade e alta especificidade colocam estas moléculas em posição de destaque
para aplicação na indústria alimentícia e farmacêutica. Nesse contexto, o presente trabalho visa
discutir os principais processos utilizados para obtenção de peptídeos bioativos, com destaque
para a fermentação e hidrólise enzimática, sendo abordados também a associação de diferentes
tecnologias e o uso de processos auxiliares. Um levantamento sobre métodos de isolamento,
purificação e caracterização destes peptídeos, como cromatografia e espectrometria de massas,
foi realizado no sentido de mostrar as principais técnicas de identificação das estruturas dos
peptídeos bioativos. Por fim, foram discutidos aspectos relacionados à atividade antioxidante,
antimicrobiana, anti-hipertensiva, antiadipogênica e indução do crescimento de bactérias
probióticas por peptídeos obtidos através de diferentes processos e variadas fontes proteicas.
Palavras-chave: proteínas, hidrólise enzimática, fermentação, peptídeos bioativos.
29
1. Introdução
As proteínas têm relevância fundamental como componentes dos alimentos.
Nutricionalmente, são fontes de aminoácidos essenciais, indispensáveis para o crescimento,
manutenção do organismo e também fonte de energia. Em alimentos proteicos, possuem a
capacidade de afetar propriedades físico-químicas e sensoriais, como a solubilidade, viscosidade,
gelificação e estabilidade da emulsão.
Algumas proteínas da dieta possuem propriedades biológicas específicas, fazendo destas,
ingredientes potenciais de alimentos funcionais (Korhonen et al., 1998). Um alimento funcional
pode ser definido como qualquer alimento, que além das funções nutritivas básicas, fornece
benefícios adicionais à saúde, regulando uma ou mais funções no organismo (Diplock et al.,
1999; Hernández-Ledesma et al., 2011).
Estudos recentes têm relacionado a prevalência de doenças cardiovasculares, obesidade,
hipertensão, diabetes e câncer à fatores alimentares. Em resposta ao aumento na percepção sobre
a relação entre alimentos e saúde, o mercado de alimentos funcionais sofreu um grande impulso.
As propriedades funcionais das proteínas alimentares decorrem do fato de que, durante a
digestão gastrointestinal, elas são hidrolisadas gerando uma grande variedade de peptídeos.
Alguns destes peptídeos apresentam características estruturais que permitem a interação com
peptídeos endógenos, os quais são responsáveis por funções vitais no organismo, podendo atuar
como neurotransmissores, hormônios ou agentes reguladores (Hernández-Ledesma et al., 2014).
Processos envolvendo a hidrólise de proteínas têm sido estudados para a produção de
peptídeos com atividade biológica. Mellander (1950) foi responsável pelo primeiro estudo
relacionando a ingestão de peptídeos bioativos derivados de proteínas hidrolisadas de caseína ao
aumento da calcificação óssea em recém-nascidos raquíticos. Desde então, peptídeos com
inúmeras bioatividades foram identificados. De acordo com os Bancos de Dados Biopep e BioPD
(Bioactive peptide database), mais de 1200 diferentes peptídeos bioativos encontram-se
registrados em suas bases (Singh et al., 2014).
Peptídeos bioativos são definidos como frações específicas de proteínas, com sequência
de aminoácidos que promovem um impacto positivo em várias funções biológicas, incluindo
atividades: antioxidante, anti-hipertensiva, antitrombótica, antiadipogênica, antimicrobiana, anti-
inflamatória e imunomoduladoras (Biziulevicius et al., 2006; Tsou et al., 2010; Zhang et al.,
30
2010; Tavares et al., 2011; Ahn et al., 2015). Estes peptídeos apresentam sequências de 2-20
aminoácidos e massas moleculares inferiores a 6000 Da. A bioatividade é definida
principalmente pela composição e sequência de aminoácidos (Sarmadi e Ismail, 2010). Essa
enorme diversidade funcional coloca os peptídeos e as proteínas em posição de destaque no
campo das aplicações biotecnológicas (Miranda e Liria, 2008), sendo apontados por alguns
autores como possíveis substitutos de substâncias químicas utilizadas como fármacos ou
conservadores de alimentos (Hong et al., 2008; Uhlig et al., 2014).
De acordo com Uhlig et al., (2014) há uma perspectiva muito importante para a utilização
de peptídeos bioativos na área farmacêutica. Alguns peptídeos em fase de ensaios clínicos têm
apresentado resultados muito promissores no tratamento de doenças cardiovasculares, infecciosas
e de origem metabólica. Os peptídeos apresentam uma importante vantagem competitiva com os
medicamentos tradicionais devido à algumas características, como: 1) são moléculas que
apresentam alta especificidade pelas células ou tecidos alvos, resultando em baixo ou nenhum
efeito tóxico e exigindo baixas concentrações para uma atuação efetiva (característica
extremamente importante, principalmente para os tratamentos de doenças durante um tempo
prolongado); 2) as moléculas químicas presentes nos medicamentos tradicionais muitas vezes
apresentam efeito cumulativo no organismo. Em casos de metabolismo deficiente, incluindo os
mecanismos de biotransformação, transporte, absorção e excreção, no qual estas moléculas
seriam excretadas ainda na forma ativa, a possibilidade de danos ao ambiente tornaria-se alta. Por
outro lado, peptídeos sofrem pouco ou nenhum acúmulo no organismo e são facilmente
degradados no ambiente (Uhlig et al., 2014).
Diferentes vias são utilizadas na obtenção de peptídeos bioativos, dentre as quais podemos
citar: fermentação, hidrólise enzimática ou a associação dos dois processos (Figura 1). No
processo de fermentação, a aplicação de culturas de bactérias lácticas com atividade proteolítica,
leva à formação de peptídeos bioativos, principalmente durante a fabricação de produtos lácteos.
A hidrólise enzimática envolve a aplicação de enzimas proteolíticas digestivas, vegetais ou de
origem microbiana em um processo de hidrólise limitada, levando a redução de fatores
alergênicos, assim como melhoria da digestibilidade e formação de peptídeos com atividade
biológica (Korhonen, 2009). Uma estratégia utilizada em algumas pesquisas científicas
demonstrou que a fermentação utilizando bactérias ácido lácticas em associação com a aplicação
de enzimas de grau alimentício resultou em produtos finais com características mais interessantes
31
quando comparados aos processos isolados. A combinação das técnicas, além de aumentar o teor
de peptídeos dos produtos fermentados, resultou em efeitos biológicos e funcionais diversificados
(Hafeez et al., 2014).
Figura 1 – Principais vias de obtenção de peptídeos e ensaios de bioatividade.
Em adição aos processos convencionais citados anteriormente, a associação de diferentes
tecnologias vem mostrando resultados eficazes na geração de peptídeos funcionais (Korhonen,
2009). O uso de ultrafiltração e nanofiltração são exemplos de tecnologias que têm sido estudadas
para refinar e fracionar peptídeos bioativos, permitindo uma separação em tamanhos selecionados
e direcionando para aplicações específicas (Quirós et al., 2007; Picot et al., 2010).
Bactérias ou fungos
produtores de proteases
Homogeneização
à alta pressão
Peptídeos
bioativos
Hidrolisados proteicos
Ultrafiltração ou nanofiltração
Proteases:
vegetais, animais ou
microbianas.
Fermentação microbiana
Proteínas animais ou vegetais
Isolamento, purificação
e identificação
Atividades biológicas:
métodos in vitro e in vivo
Anti-hipertensiva Antimicrobiana Antiadipogênica
Anti-inflamatória Imunomoduladoras Antioxidante
32
Peptídeos bioativos podem ser obtidos a partir de proteínas de origem animal ou vegetal.
As fontes vegetais geralmente incluem cereais, como o trigo, arroz, aveia, centeio e milho e
algumas leguminosas, como soja, ervilha e grão de bico. Entre as fontes vegetais, a soja é uma
das mais estudadas para obtenção de peptídeos por ser uma importante fonte de proteína
alimentar (Ortiz-Martinez et al., 2014). As fontes de proteínas animais por sua vez, também
apresentam grande potencial de aplicação. Uma das linhas de pesquisa mais estudadas e
promissoras é a produção de hidrolisados proteicos a partir de proteínas derivadas de carne, que
além de possuírem importantes atividades biológicas e serem excelentes fontes de nutrientes
como aminoácidos essenciais, minerais e vitaminas, podem ser utilizados como intensificadores
de sabor e agentes emulsificantes (Mora et al., 2014; Lafarga e Hayes, 2014). Outras fontes de
proteínas animais como ovo e peixe também foram estudadas quanto às suas propriedades
biológicas (Sakanaka et al., 2004; Theodore et al., 2008).
O conhecimento dos parâmetros críticos de processo é de fundamental importância para
obtenção de hidrolisados proteicos com características biológicas e funcionais desejáveis. Estes
parâmetros incluem: a fonte de proteína utilizada e suas características como composição química
e variações sazonais; a preparação enzimática e os aspectos relacionados à pureza, especificidade
quanto ao substrato, atividade específica, condições de pH e temperatura para a atividade e
estabilidade e as condições de processo, incluindo as concentrações de enzima e substrato, pH,
temperatura, tempo de reação. Um conhecimento prévio e a identificação destes parâmetros
podem ser utilizados como ferramentas para a obtenção de produtos com funções distintas, no
âmbito de produzir peptídeos multifuncionais, ou ainda diferentes peptídeos com funções
específicas e consequentemente com uma contribuição particular (Li-Chan, 2015).
Nesse contexto, o presente trabalho visou abordar avanços da pesquisa científica
envolvendo os processos de obtenção, purificação e identificação, atividades biológicas e
potencial de aplicação de peptídeos bioativos.
2. Principais processos de obtenção de peptídeos bioativos
2.1. Fermentação
A aplicação de processos fermentativos para obtenção de peptídeos bioativos está
relacionada principalmente com a fabricação de produtos derivados de leite, o qual possui
naturalmente proteínas precursoras de moléculas bioativas (Schanbacher et al., 1997; Akalın et
33
al., 2014). A fermentação do leite envolve uma série de vias metabólicas, que são responsáveis
pela geração de metabólitos que contribuem de forma significativa na obtenção de atributos
químicos, bioquímicos e nutricionais de produtos fermentados. O sistema proteolítico de
bactérias ácido lácticas (BAL) é complexo e constituído por três componentes principais:
proteases ligadas à parede celular que promovem a hidrólise inicial da caseína do leite a
oligopeptídeos; transportadores específicos que conduzem os oligopeptídeos para o citoplasma e
peptidases intracelulares que finalizam o processo de hidrólise dos oligopeptídeos a aminoácidos
livres e/ou peptídeos de menor massa molecular (Chaves-López et al., 2014). A capacidade
destes micro-organismos em produzir enzimas proteolíticas faz delas potenciais produtoras de
peptídeos bioativos, os quais podem ser liberados durante o processo de fabricação de produtos
fermentados. Alguns micro-organismos são extensivamente relatados na literatura por possuírem
um sistema proteolítico eficaz na hidrólise de proteínas e liberação de peptídeos com atividade
biológica, entre eles merecem destaque: Lactobacillus helveticus, Lactobacillus delbrueckii ssp.
bulgaricus, Lactococcus lactis ssp. diacetylactis, Lactococcus lactis ssp. cremoris e
Streptococcus salivarius ssp. thermophylus (Hernández-Ledesma et al., 2011). Além da
utilização de micro-organismos vivos, as enzimas proteolíticas isoladas de BAL também têm sido
utilizadas com sucesso em processos de hidrólise enzimática e produção de peptídeos bioativos
(Choi et al., 2012).
Embora os produtos lácteos tenham destaque nas pesquisas científicas que envolvem a
produção destes peptídeos por fermentação, foi demonstrado que produtos fermentados derivados
de soja, feijão, arroz e trigo também apresentaram atividade biológica (Inoue et al., 2009;
Nakahara et al., 2010; Hati et al., 2014; Limón et al., 2015) (Tabela 1).
34
Tabela 1 - Obtenção de peptídeos com diferentes atividades biológicas por meio de processo fermentativo utilizando diversas fontes
de proteína.
Micro-organismo Fonte proteica Condições do processo fermentativo Peptídeos Bioatividade Referência
Streptococcus thermophilus e
Lactobacillus bulgaricus
+
Protease Flavourzyme®
Leite de soja Processo de fermentação submersa
conduzido durante 5 h a 43 °C Tyr-Pro-Tyr-Tyr Anti-hipertensiva
Tsai et al.,
2008
Aspergillus oryzae Arroz, soja e
caseína
Processo de fermentação em estado
sólido conduzido durante 40 h a 30 °C Val-Pro-Pro; Ile-Pro-Pro Anti-hipertensiva
Inoue et al.,
2009
Aspergillus sojae Soja e trigo
Processo de fermentação em estado
sólido conduzido durante 192 h a
20-45 °C e umidade de 95%
Gly-Tyr; Ala-Phe; Val-
Pro; Ala-Ile; Val-Gly Anti-hipertensiva
Nakahara et
al., 2010
Enterococcus faecalis
TH563
Lactobacillus delbrueckii
subsp. bulgaricus LA2
Leite bovino
Processo de fermentação submersa
conduzido durante 24 h a 37 °C
(Enterococcus faecalis) ou 44 °C
(Lactobacillus delbrueckii)
Peptídeos com massa
molecular inferior a 5000
Da
Anti-hipertensiva e
imunomodulatória
Regazzo et
al., 2010
L. acidophilus ATCC 4356 e
Lc. lactis subsp. lactis GR5
Caseinato de
sódio
Processo de fermentação submersa
conduzido durante 5h a 30 °C
(Lactococcus lactis) ou 37 °C (L.
acidophilus) com agitação de 140 rpm
Peptídeos com massa
molecular inferior a 3000
Da
Imunomodulatória Stuknyte et
al., 2011
B. subtilis 10160 Colza
Processo de fermentação em estado
sólido conduzido durante 6 dias a 32 °C
e umidade relativa de 85 ± 5%
Peptídeos com massa
molecular entre 180 e
5500 Da
Antioxidante He et al.,
2012
Bifidobacterium longum
KACC91563 Caseína
Processo de fermentação submersa
conduzido durante 24 h Val-Leu-Pro-Val-Gln Antioxidante
Chang et
al., 2013
Lactobacillus casei spp.
pseudoplantarum
Proteína
concentrada de
soja
Processo de fermentação submersa
conduzido durante 36 h a 37 °C Leu-Ile-Val-Thr-Gln Anti-hipertensiva
Vallabha e
Tiku, 2014
B. subtilis ATCC 6051 Feijão
Processo de fermentação em estado
sólido conduzido durante 96 h a 30 °C e
umidade relativa de 90%
Peptídeos com massa
molecular entre 6,2 e
201,2 kDa
Antioxidante
Anti-hipertensiva
Limón et
al., 2015
35
2.2. Hidrólise enzimática
A hidrólise enzimática é uma das técnicas mais rápidas, seguras e de fácil controle para a
produção de peptídeos bioativos, podendo ser utilizada para melhorar propriedades funcionais e
biológicas de proteínas, assim como agregar valor a subprodutos de baixo valor comercial (Zarei
et al., 2014).
As proteases catalisam a reação de hidrólise das ligações peptídicas das proteínas e ainda
podem apresentar atividade sobre ligações éster e amida. Todas as proteases apresentam certo
grau de especificidade quanto ao substrato, em geral relacionado aos aminoácidos envolvidos na
ligação peptídica a ser hidrolisada e àqueles adjacentes a eles (Santos e Koblitz, 2008). Essa
especificidade em adição às condições de hidrólise (pH, temperatura, tempo) afetam o tamanho e
a sequência de aminoácidos na cadeia peptídica, além da quantidade de aminoácidos livres, que
por sua vez influenciam a atividade biológica dos hidrolisados (Tsou et al., 2010a; Sarmadi e
Ismail, 2010). A utilização de uma protease com atividade específica ou a combinação de
diversas proteases não específicas tem sido utilizada como estratégia para a produção de
peptídeos bioativos mais efetivos e estáveis por implicarem em reduzidos tempos de reação para
obtenção do grau de hidrólise requerido assim como a obtenção de diferentes perfis,
principalmente relacionados à composição e distribuição de massa molecular dos peptídeos. Estes
processos são especialmente utilizados em indústrias alimentícias e farmacêuticas utilizando
proteases de origem animal, vegetal e microbiana (Singh et al., 2014).
Um grande número de estudos demonstrou a liberação de peptídeos com atividade
biológica após a hidrólise de proteínas (Tabela 2).
36
Tabela 2 - Aplicação de proteases para obtenção de peptídeos com atividade biológica a partir de diferentes fontes de proteína.
Protease Condições de
hidrólise Fonte proteica
Bioatividade dos
peptídeos Peptídeos Método de identificação Referência
Alcalase®
pH 8,0; 50 °C; 3 h
E:S = 1:20
[S] = 5,0%
Soja Antiadipogênese
Peptídeos com
massa molecular
entre 754 e 3897
Da
Cromatografia líquida acoplada
à espectrometria de massas
Mejia et al.,
2010
Flavourzyme®
pH 7,0; 50 °C; 2 h
E:S = 1:100
[S] = 2,5%
Proteína isolada
de soja Antiadipogênese
Peptídeos com
massa molecular
inferior a 1300 Da
Cromatografia de exclusão
molecular de alta performance
Tsou et al.,
2010a
Neutrase®
pH 6,0; 45 °C; 4 h
E:S = 1:100
[S] = 2,5%
Proteína isolada
de soja Antiadipogênese
Peptídeos com
massa molecular
entre 1300 e 2200
Da
Cromatografia de exclusão
molecular de alta performance
Tsou et al.,
2010b
Pepsina pH 5,5; 23 °C
[S] = 1,0%
Hemoglobina
bovina
Antimicrobiana
Anti-hipertensiva
Peptídeos com
massa molecular
entre 668 e 4430
Da
Espectrometria de massas com
ionização por “electrospray”
(ESI/MS)
Adje et al.,
2011
Alcalase®
pH 8,0; 50 °C; 3 h
[E] = 0,2 mg mL-1
[S] = 8,0%
Feijão Antioxidante
Anti-inflamatória
Peptídeos com
massa molecular
entre 445 e 2148
Da
Espectrometria de massas com
ionização/dessorção a laser
assistida por matriz
(MALDI-TOF)
Oseguera-
Toledo et al.,
2011
Alcalase®
Flavourzyme®
Protamex®
Neutrase®
Pepsina
Tripsina
pH 7,0; 50 °C; 8 h
pH 7,0; 50 °C; 8 h
pH 7,0; 50 °C; 8 h
pH 7,0; 50 °C; 8 h
pH 2,0; 37 °C; 8 h
pH 8,0; 37 °C; 8 h
Salmão Antioxidante
Anti-inflamatória
Peptídeos com
massa molecular
entre 1000 e 2000
Da
Cromatografia de exclusão
molecular de alta performance Ahn et al., 2012
37
3. Concentração, purificação e identificação de peptídeos bioativos
Diversas técnicas podem ser utilizadas para o isolamento, identificação e caracterização
de proteínas e peptídeos. As técnicas cromatográficas estão entre as mais aplicadas, destacando-
se a cromatografia líquida de alta eficiência (CLAE) como a mais utilizada (Singh et al., 2014). A
técnica de CLAE de fase reversa, por exemplo, pode ser utilizada para fracionar peptídeos com
base em suas propriedades hidrofóbicas (Pownall et al., 2010). Técnicas de eletroforese em gel e
ultrafiltração também foram utilizadas como métodos auxiliares na caracterização estrutural e
composição química de peptídeos (Roblet et al., 2012; Singh et al., 2014).
A espectrometria de massas, por sua vez, representou um grande avanço na identificação
de sequências peptídicas e estudos sobre os perfis de proteínas e seus produtos de hidrólise. O
desenvolvimento de interfaces, nas quais a ionização do analito por métodos que permitem a
obtenção de íons a partir de moléculas sensíveis à temperatura e/ou pouco voláteis, como a
ionização por eletronebulização ("electrospray ionization") e a ionização/dessorção a laser
assistida por matriz (MALDI-TOF) surgiram recentemente como importantes ferramentas para a
identificação e caracterização de proteínas e peptídeos bioativos utilizando espectrometria de
massas. A técnica de cromatografia líquida acoplada à espectrometria de massas é comumente
utilizada para identificar sequências peptídicas (Chiaradia et al., 2008; Contreras et al., 2008;
Singh et al., 2014).
Peptídeos com atividade anticoagulante obtidos a partir do peixe “goby” (Awaous
guamensis) e uma protease de Bacillus licheniformis foram fracionados por cromatografia de
exclusão molecular e cromatografia líquida de alta eficiência de fase reversa e identificados por
espectrometria de massas. A solução de hidrolisados contendo os peptídeos foi aplicada à coluna
de filtração em gel Sephadex G-25 (5,2 x 56 cm) pré-equilibrada e eluída com água destilada.
Frações de 4,5 mL foram coletadas utilizando-se fluxo de 0,5 mL min-1
e a absorbância
mensurada a 220 nm para determinar o perfil de eluição dos peptídeos. As frações com maior
atividade anticoagulante foram recolhidas e purificadas em coluna de fase reversa Vydac C18 (10
x 250 mm, Grace-Vydac) e eluídas por gradiente linear de acetonitrila (0 a 40% v/v) e fluxo de
0,6 mL min-1
. A massa molecular e a sequência de aminoácidos dos peptídeos foram
determinadas utilizando um espectrômetro de massas triploquadrupolo com fonte de ionização
por electrospray (Applied Biosystems API 3000, PE Sciex, Toronto, Canadá). Quatro sequências
38
peptídicas apresentaram alta atividade anticoagulante e foram identificadas como Leu-Cys-Arg,
His-Cys-Phe, Cys-Leu-Cys-Leu-Arg e Cys-Arg-Arg (Nasri et al., 2012).
Tsou et al., (2013) utilizaram como estratégia para purificação e identificação de
peptídeos bioativos obtidos a partir de proteína isolada de soja e protease Flavourzyme®, o
fracionamento sequencial com membranas de ultrafiltração de diferentes tamanhos,
cromatografia em gel, cromatografia líquida de alta eficiência de fase reversa e espectrometria de
massas. Os hidrolisados foram inicialmente fracionados em membranas de ultrafiltração de 30,
10 e 1 kDa. A fração retentada da membrana de 1 kDa foi selecionada para purificação com base
em sua capacidade em estimular a lipólise em células pré-adipócitas 3T3-L1. O retentado de 1
kDa foi então aplicado em coluna Superdex® peptide 10/300 GL (10 x 300 mm; GE Healthcare)
equilibrada e eluída com acetonitrila 30% e fluxo de 0,5 mL min-1
. Frações de 1,0 mL foram
coletadas e curvas de eluição foram construídas a partir das medidas de absorbância a 214 nm. As
frações com maior atividade antiadipogênica foram recolhidas e purificadas em coluna de fase
reversa Develosil® ODS-HG-5 (4,6 x 250 mm, Nomura Chemical) e eluídas por um gradiente
linear de acetonitrila (5 a 75%) e fluxo de 1,0 mL min-1
. A fração com maior atividade anti-
adipogênica foi submetida a uma segunda etapa de purificação em coluna de fase reversa
utilizando gradientes lineares de acetonitrila de 10 a 40%. Os peptídeos foram finalmente
identificados por cromatografia líquida acoplada à espectrometria de massas. Três peptídeos com
as seguintes sequências de aminoácidos Ile-Leu-Leu, Leu-Leu-Leu e Val-His-Val-Val foram
identificados como os responsáveis pela atividade anti-adipogênica dos hidrolisados de proteína
isolada de soja.
Peptídeos com atividade anti-hipertensiva foram isolados e identificados a partir de
hidrolisados de gelatina extraída de pele de arraia (Okamejei kenojei). Inicialmente, os
hidrolisados foram submetidos à ultrafiltração em membranas de 1 kDa e os peptídeos com
massa molecular inferior à este corte foram recolhidos. A etapa de purificação consistiu na
aplicação de etapas sequenciais de isolamento por cromatografia líquida rápida de proteínas
(FPLC) (AKTA, Amersham Bioscience Co., Uppsala, Suécia) utilizando a coluna de troca iônica
de fluxo rápido HiPrep 16/10 (16 x 100 mm, Amersham Biosciences, Piscataway, NJ, EUA) e a
coluna de filtração em gel GE Healthcare Superdex® Peptide 10/300 GL (10 x 300 mm). Os
peptídeos purificados foram então identificados utilizando a técnica de espectrometria de massas
39
MALDI-TOF. Dois peptídeos purificados mostraram alta atividade anti-hipertensiva e foram
identificados como Leu-Gly-Pro-Leu-Gly-His-Gln com massa molecular estimada em 720 Da e
Met-Val-Gly-Ser-Ala-Pro-Gly-Val-Leu com massa molecular de 829 Da (Ngo et al., 2015).
4. Propriedades biológicas de peptídeos bioativos
Peptídeos bioativos de proteínas alimentares têm sido estudados extensivamente ao longo
da última década para elucidar seu potencial biológico e influência sobre os principais sistemas
do corpo humano, como: digestivo, cardiovascular, nervoso e imunológico. Alguns peptídeos
bioativos apresentaram atividades biológicas com impacto positivo sobre a saúde, dentre as quais
podemos citar: atividade antimicrobiana (Adje et al., 2011), anti-hipertensiva (Alemán et al.,
2011), antioxidante (Zhang et al., 2009) anticancerígena (Alemán et al., 2011), antiadipogênica
(Tsou et al., 2010), imunomoduladoras (Huang et al., 2010) e anti-inflamatória (Ahn et al.,
2015); portanto têm perspectivas de serem incorporados como ingredientes em alimentos
funcionais, nutracêuticos e medicamentos, onde essas bioatividades podem ser aliadas no
controle e prevenção de doenças (Agyei e Danquah, 2012).
A obtenção e características de peptídeos com atividade antimicrobiana, antioxidante,
antiadipogênica, anti-hipertensiva e aplicação na indução do crescimento de bactérias lácticas e
probióticas estão descritas neste trabalho.
4.1. Peptídeos com atividade antimicrobiana
Ao longo das últimas décadas, um número crescente de micro-organismos patogênicos
desenvolveu resistência aos antibióticos convencionais, gerando sérios problemas no tratamento
de infecções, principalmente de indivíduos imunocomprometidos. Aliado a este fato, o
desenvolvimento de novos antibióticos apresentou uma diminuição neste mesmo período. Duas
causas principais justificam o aumento da resistência de micro-organismos aos antibióticos: o uso
indiscriminado destes medicamentos em condições não recomendadas de uso, como tempo ou
dosagem inferiores para um tratamento efetivo, e a capacidade de mutação genética dos micro-
organismos, que aumenta a dificuldade de desenvolvimento de drogas baseadas em mecanismos
específicos de ação (Harrison et al., 2014). Nesse contexto, a utilização de fontes naturais de
compostos antimicrobianos possui um enorme potencial de aplicação, visto que possuem
características interessantes como baixa toxicidade e alta especificidade. Esses mecanismos
podem ser melhor compreendidos ao compararmos o modo de ação de peptídeos antimicrobianos
40
sobre células bacterianas (unicelulares) e animais (pluricelulares). As membranas bacterianas
possuem uma camada rica em fosfolipídeos carregados negativamente e com essas porções
voltadas para meio externo, o que facilita a interação com os peptídeos que em sua maioria estão
carregados positivamente. Por outro lado, as células animais são compostas, principalmente, por
lipídeos não carregados na camada mais externa, enquanto as porções carregadas negativamente
estão voltadas para o interior celular (citoplasma) (Matsuzaki, 1999) (Figura 2).
Figura 2 – Especificidade de peptídeos antimicrobianos mediante membranas de organismos
pluricelulares (células animais) e unicelulares (bactérias) (Figura adaptada de Zasloff, 2002).
Peptídeos antimicrobianos estão amplamente distribuídos na natureza e representam um
componente essencial do sistema imunológico. Eles são reconhecidamente, a primeira linha de
defesa do organismo contra a colonização de micro-organismos exógenos, com papel
fundamental na regulação de populações bacterianas em mucosas e outras superfícies epiteliais
(Boman e Hultmark, 1987; Bevins e Zasloff, 1990; Zasloff, 2002). Mais de 800 peptídeos
antimicrobianos já foram descritos em plantas e animais (Boman, 2003). Apesar da diversidade
na estrutura primária, a grande maioria dos peptídeos antimicrobianos possui cadeias curtas de
41
aminoácidos, que são caracterizadas pela predominância de aminoácidos catiônicos e
hidrofóbicos (Zasloff, 2002; Dashper et al., 2007) (Figura 2). A reduzida massa molecular das
frações peptídicas, com consequente maior exposição dos resíduos de aminoácidos e suas cargas,
e a formação de pequenos canais na bicamada lipídica foram relacionados com o poder
antimicrobiano, pois causam modificações que aumentam a interação peptídeo-membrana
(Gobbetti et al., 2004; Patrzykat e Douglas, 2005; Gómez-Guillén et al., 2010).
O mecanismo exato de ação de muitos peptídeos antimicrobianos ainda não está bem
estabelecido, e devido ao grande número de peptídeos já conhecidos, acredita-se na probabilidade
de existirem mecanismos distintos de ação (Dashper et al., 2007).
Além dos naturalmente presentes nos sistemas de defesa de plantas e animais, peptídeos
com atividade antimicrobiana já foram identificados em diversos hidrolisados proteicos.
Hidrolisados de caseína de leite bovino obtidos a partir da hidrólise enzimática com
quimosina foram avaliados quanto ao poder antimicrobiano. Cinco diferentes peptídeos
antibacterianos foram isolados a partir da extremidade carboxílica da αs2-caseína. As frações de
peptídeos f (181-207), f (175-207) e f (164-207) apresentaram amplo espectro de ação e foram
capazes de inibir diversas bactérias Gram+ e Gram-; os valores de concentração inibitória mínima
(CIM) de cada fração variaram de 21,0 a 168,0 mg mL-1
, 10,7 a 171,2 mg mL-1
e 4,8 a 76,2 mg
mL-1
, respectivamente. É válido ainda ressaltar que o potencial de inibição destes peptídeos
contra bactérias Gram+ foi tão alto quanto o dos conhecidos peptídeos antimicrobianos nisina e
lactoferricina B (McCann et al., 2005).
Peptídeos com atividade antimicrobiana foram preparados a partir de gelatina hidrolisada
com Alcalase® 2.4L (Sigma-Aldrich, Estados Unidos). As frações obtidas por ultrafiltração em
membranas de 1 e 10 kDa foram utilizadas para testes antimicrobianos contra 18 bactérias. As
bactérias mais sensíveis na presença das frações testadas foram: Lactobacillus acidophilus,
Bifidobacterium lactis, Shewanella putrafaciens e Photobacterium phosphoreum (Gómez-Guillén
et al., 2010). Hidrolisados de hemoglobina bovina tratada com pepsina foram purificados por
CLAE e testados quanto ao poder antimicrobiano contra duas linhagens Gram- (Escherichia coli,
Salmonella enteritidis) e três Gram+ (Kocuria luteus A270, Staphylococcus aureus e Listeria
innocua). Os resultados obtidos mostraram que as frações peptídicas purificadas apresentaram
amplo espectro de ação, agindo contra 4 das 5 bactérias testadas (Kocuria luteus A270, Listeria
42
innocua, Escherichia coli e Staphylococcus aureus) com CIM variando entre 35,2 e 187,1 µM
(Adje et al., 2011).
Tellez et al. (2011) mostraram a eficiência de uma fração peptídica, isolada a partir de
leite fermentado com Lactobacillus helveticus, contra uma infecção proposital com Salmonella
enteritidis em ratos. A taxa de sobrevivência no grupo alimentado com a fração peptídica (0,02
µg por dia) foi superior ao grupo alimentado com metade da dose (0,01 µg por dia) e ao grupo
controle.
O potencial antimicrobiano de proteína isolada de soro de leite hidrolisada por diferentes
enzimas gastrointestinais foi verificado por Théolier et al., (2013). Os resultados obtidos por
estes autores mostraram que hidrolisados proteicos obtidos com tripsina e quimotripsina não
apresentaram atividade antibacteriana contra Listeria ivanovii HPB28 e Escherichia coli
MC4100, enquanto os hidrolisados produzidos por ação da enzima pepsina apresentaram
atividade significativa. Os hidrolisados foram fracionados por cromatografia líquida de alta
eficiência de fase reversa, resultando em cinco frações com alta atividade antibacteriana e CIM
variando de 20,0 a 35,0 µg mL-1
. Uma fração peptídica obtida a partir de água residuária
proveniente do cozimento de anchovas (Engraulis japonicus) e ação da enzima Protamex®,
apresentou alta atividade antimicrobiana contra Staphylococcus aureus. A fração identificada
apresentou a sequência peptídica Gly-Leu-Ser-Arg-Leu-Phe-Thr-Ala-Leu-Lys e massa molecular
estimada em 1,1 kDa (Tang et al., 2015).
4.2. Peptídeos com atividade antioxidante
A formação de radicais livres, tais como superóxido (O˙2-) e hidroxila (˙OH), é uma
consequência inevitável em organismos aeróbios durante a respiração. Estes radicais são muito
instáveis e reagem rapidamente com outros grupos ou substâncias no organismo, ocasionando
lesões celulares ou nos tecidos (Zhang et al., 2009). Uma quantidade excessiva desses radicais no
organismo foi associada ao desenvolvimento de várias doenças, como aterosclerose, artrite,
diabetes e câncer (Gu et al., 2015). Por serem espécies altamente reativas, os radicais livres
podem causar danos às proteínas e mutações no DNA, oxidação de fosfolipídeos de membrana e
modificação em lipoproteínas de baixa densidade (LDL) (Pihlanto, 2006). Em alimentos, a
oxidação também afeta diretamente a qualidade, comprometendo caraterísticas como sabor,
43
aroma e coloração. Nesse contexto, a presença de substâncias que inibem reações oxidativas que
comprometem a qualidade dos alimentos é de suma importância.
É importante ressaltar que a capacidade de eliminação de radicais livres por compostos
antioxidantes é determinada por vários fatores, como: reatividade química e consequentemente a
taxa de eliminação destes radicais, o destino do produto derivado após a reação antioxidante-
radical, interação com outras substâncias antioxidantes, concentração e mobilidade no meio
ambiente e mecanismos de absorção, distribuição, retenção e metabolismo (Niki, 2010).
Antioxidantes são considerados importantes nutracêuticos apresentando diversos
benefícios à saúde, e são definidos como quaisquer substâncias que retardam ou inibem
significativamente a oxidação de um substrato. Atualmente, alguns antioxidantes sintetizados
artificialmente como hidroxitolueno butilado (BHT), hidroxianisol butilado (BHA) e
tertbutilhidroquinona (TBHQ), têm sido empregados para prevenir os danos oxidativos em
alimentos e biosistemas. No entanto, estes produtos químicos sofrem uma tendência de uso cada
vez mais limitada por apresentar riscos potenciais à saúde humana, como danos ao DNA,
toxicidade e efeitos colaterais (Wang et al., 2014; Chi et al., 2015). Consequentemente, há um
interesse crescente entre os pesquisadores para obtenção de moléculas antioxidantes mais seguras
a partir de fontes naturais, como os peptídeos provenientes de proteínas hidrolisadas (Senphan e
Benjakul, 2014; Chi et al., 2015).
Alguns peptídeos com atividade antioxidante têm ocorrência natural em alimentos. A
glutationa (γ-Glu-Cys-Gly) e a carnosina (β-alanil-L-histidina) são antioxidantes naturalmente
presentes em tecidos musculares e apresentam capacidade de doar elétrons, quelar metais e íons e
inibir a peroxidação lipídica (Samaranayaka e Li-Chan, 2011). Além dos naturalmente presentes,
peptídeos obtidos a partir de alimentos proteicos hidrolisados têm sido relatados por terem
capacidade antioxidante similar ou superior a antioxidantes sintéticos como o BHT, sendo assim
uma fonte segura para aplicação em alimentos (Yasufumi et al., 2001).
Os mecanismos de ação que explicam a atividade antioxidante de peptídeos não são
totalmente compreendidos, mas vários estudos mostraram a capacidade de peptídeos em inibir a
peroxidação lipídica (Sakanaka et al., 2004), eliminar radicais livres (Gómez-Guillén, 2010),
quelar íons metálicos (Alemán et al., 2011) e eliminar espécies reativas de oxigênio (Zhuang e
Sun, 2011). Assim como para outras atividades biológicas, as propriedades antioxidantes dos
44
peptídeos estão relacionadas com sua composição, estrutura e hidrofobicidade (Chen et al.,
1998). A presença dos aminoácidos tirosina, triptofano, metionina, lisina e cisteína, foi relatada
como importante fator para a ação antioxidante dos peptídeos, especialmente pela capacidade de
redução do Fe3+
a Fe2+
e atividade quelante de íons Fe2+
e Cu2+
(Wang e De Mejia, 2005; Huang
et al., 2010; Carrasco-Castilla et al., 2012). Deve-se ressaltar, que não só a presença, mas também
a sequência destes aminoácidos na cadeia peptídica desempenha papel importante no poder
antioxidante (Rajapakse et al., 2005). A capacidade antioxidante de peptídeos pode ser avaliada
por diversos métodos in vitro, nos quais estão envolvidos diferentes mecanismos de ação e
consequentemente medem atividades distintas (Tabela 3).
Além da avaliação in vitro, a atividade antioxidante pode ser avaliada por métodos in
vivo, os quais utilizam modelos animais. A capacidade antioxidante in vivo é determinada por
vários fatores, já que estas substâncias devem ser absorvidas, transportadas, distribuídas e retidas
adequadamente nos fluidos biológicos, células e tecidos. A biodisponibilidade destes compostos,
o efeito da dosagem e a duração dos tratamentos têm sido estudados por análise de fluidos
biológicos e tecidos humanos e animais após a ingestão (Niki, 2010; Alam et al., 2013). A Tabela
4 mostra alguns destes métodos e o princípio de cada avaliação.
45
Tabela 3 – Principais métodos de determinação de atividade antioxidante in vitro de peptídeos e respectivos mecanismos de cada
método.
Método Mecanismo Reação Medida realizada Referência
DPPH Captura do
radical DPPH
O radical DPPH (2,2-difenil-1-picril-hidrazil) reage com antioxidantes
doadores de hidrogênio, com mudança de coloração violeta para amarela.
Redução da absorbância
a 517 nm
Sharma e
Bhat, 2009
ORAC
Captura de
radical
peroxila
O radical peroxila, gerado pela decomposição do AAPH [dicloreto de 2,2’-
azobis (2-amidinopropano)] na presença de oxigênio atmosférico, reage
com um indicador fluorescente formando um produto não fluorescente. Na
presença de antioxidantes, a fluorescência é preservada.
Redução de
fluorescência (excitação
a 485 nm e emissão a
520 nm)
Dávalos et
al., 2004
FRAP
Poder de
redução de
ferro
Na presença de antioxidantes doadores de elétrons, o complexo Fe3+
-TPTZ
[2,4,6-tri(2-piridil)-1,3,5-triazina] é reduzido a Fe2+
-TPTZ, com mudança
de coloração azul clara para azul escura
Aumento da absorbância
a 593 nm
Ou et al.,
2002
ABTS Captura do
radical ABTS
O radical ABTS (ácido 2,2'-azinobis-(3-etilbenzotiazolino-6-sulfônico) é
estabilizado na presença de antioxidantes doadores de hidrogênio, com
mudança de coloração verde escura para verde clara.
Redução da absorbância
a 734 nm
Gómez-
Guillén et
al., 2010
Habilidade em
quelar metais de
transição (Cu²+)
Quelação de
Cu²+
Reação de complexação de Cu2+
com violeta de pirocatecol gerando um
produto colorido. A presença de antioxidantes diminui a formação do
complexo Cu2+
-pirocatecol com consequente redução da intensidade de
cor.
Redução da absorbância
a 620 nm
Theodore et
al., 2008
Habilidade em
quelar metais de
transição (Fe²+)
Quelação de
Fe²+
Reação de complexação de Fe2+
com ferrozina gerando um produto
colorido. A presença de antioxidantes diminui a formação do complexo
Fe2+
-ferrozina com consequente redução da intensidade de cor.
Redução da absorbância
a 562 nm
Nazeer e
Kulandai,
2012
TBARS
Quantificação
de produtos de
peroxidação
de lipídica
Reação do ácido tiobarbitúrico com produtos da decomposição dos
hidroperóxidos, sendo o malonaldeído, o principal elemento quantificado.
Absorbância e atividade antioxidante são inversamente proporcionais.
Aumento da absorbância
a 532 nm
Raghavan e
Kristinsson,
2008
46
Tabela 4 – Principais métodos de determinação de atividade antioxidante de peptídeos e proteínas hidrolisadas in vivo e respectivos
mecanismos de ação e princípios de cada determinação.
Método Amostra avaliada Animais Tecido/órgão
avaliado Mecanismo de ação e princípios de cada determinação Referência
Superóxido
dismutase (SOD)
Peptídeo isolado a
partir de hidrolisado
de plasma suíno
Ratos da
linhagem Wistar,
machos e adultos
Fígado
A SOD é uma enzima que catalisa a dismutação do
radical superóxido em peróxido de hidrogênio e
oxigênio, tendo assim um importante papel de proteção
celular contra espécies reativas de oxigênio
Liu et al.,
2011
Catalase (CAT)
Peptídeo isolado de
proteína hidrolisada
de peixe
Ratos da
linhagem Wistar,
albinos, machos e
adultos
Lisado de
eritrócitos
(sangue)
A CAT é uma enzima responsável pela conversão de
peróxido de hidrogênio em água e oxigênio,
apresentando assim um dos principais mecanismos de
eliminação e radicais livres no organismo
Nazeer et al.,
2012
Teor de glutationa
reduzida (GSH)
Isolado proteico de
sementes de arruda
da Síria (Peganum
harmala)
Ratos albinos e
machos
Fígado e
plasma
sanguíneo
GSH é um redutor intracelular que apresenta um
importante papel de proteção celular contra radicais
livres, peróxidos e outros compostos tóxicos
Soliman et
al., 2013
Glutationa-S-
transferase (GST)
Peptídeo isolado de
proteína hidrolisada
de mexilhão
Ratos machos e
adultos Fígado
GST é um sistema enzimático localizado no citosol que
catalisa a conjugação de moléculas eletrofílicas reativas
com a glutationa, facilitando o metabolismo e excreção
de toxinas e consequentemente reduzindo a ocorrência de
danos celulares como mutações no DNA
Kim et al.,
2013
Glutationa
peroxidase (GPx)
Hidrolisados de
glúten de milho
Camundongos
Kunming machos
e fêmeas
Fígado e
plasma
sanguíneo
A GPx é uma enzima que catalisa a reação entre
hidroperóxidos com glutationa reduzida levando à
formação de glutationa dissulfeto e o produto de redução
de hidroperóxidos
Liu et al.,
2014
Determinação do
teor de
malonaldeído
Hidrolisados de
proteína de peixe
(Salaria basilisca)
Ratos da
linhagem Wistar,
machos e adultos
Fígado e
plasma
sanguíneo
O malonaldeído é um produto intermediário da
peroxidação lipídica e, portanto sua quantificação pode
ser utilizada como indicativo da presença de radicais
livres
Ktari et al.,
2014
47
Os métodos in vitro são os mais utilizados para a avaliação da atividade antioxidante de
proteínas hidrolisadas. Nazeer e Kulandai (2012) avaliaram as propriedades antioxidantes de
hidrolisados proteicos de peixe obtidos por tratamento enzimático utilizando diferentes proteases
(papaína, pepsina, tripsina e quimotripsina). A atividade antioxidante foi avaliada pela redução do
radical DPPH, poder de redução do ferro e habilidade em quelar metais. Todos os hidrolisados
apresentaram atividade antioxidante, sendo que os obtidos com pepsina e tripsina mostraram
maior atividade. Li et al. (2012) verificaram que hidrolisados proteicos de carpa preparados com
Alcalase® 2.4L e papaína apresentaram atividade antioxidante utilizando-se as metodologias
ABTS, DPPH, poder de redução do Fe3+
e habilidade em quelar Fe2+
. Najafian e Babji (2015)
estudaram a atividade antioxidante de proteína miofibrilar de peixe (Pangasius sutchi)
hidrolisada utilizando as preparações enzimáticas de proteases papaína, Alcalase® e
Flavourzyme®. Os graus de hidrólise variaram de acordo com a enzima utilizada e atingiram
valores de 36,53 a 89,17%. Os hidrolisados obtidos a partir de 60 min de hidrólise utilizando
papaína apresentaram atividade antioxidante superior aos demais no método TBARS e nos
métodos que mediram a habilidade em quelar Fe2+
e o poder de redução do Fe3+
. Os hidrolisados
obtidos com a enzima Alcalase® mostraram maior atividade contra o radical DPPH enquanto os
obtidos com Flavourzyme® apresentaram atividade superior contra o radical ABTS.
A determinação da atividade antioxidante por métodos in vivo é baseada principalmente
em medidas de atividade enzimática. A diminuição da atividade de enzimas antioxidantes como a
catalase (CAT), glutationa peroxidase (GPx), superóxido dismutase (SOD) e glutationa-S-
transferase (GST) influenciam criticamente a susceptibilidade de vários tecidos ao estresse
oxidativo e está associada ao desenvolvimento de diversas doenças (Ktari et al., 2014). Liu et al
(2014) investigaram as propriedades antioxidantes de hidrolisados proteicos de glúten de milho
preparados utilizando as proteases Alcalase®
, Flavourzyme®
e Protamex®. A atividade
antioxidante dos hidrolisados foi avaliada por métodos in vivo. Os experimentos foram realizados
com 40 camundongos da linhagem Kunming (25,0 ± 2,0 g) com 4-5 semanas de idade. Os
camundongos foram aleatoriamente divididos em cinco grupos experimentais contendo oito
animais cada, sendo igualmente divididos em machos e fêmeas. Os grupos foram tratados da
seguinte maneira: o grupo I foi utilizado como controle e recebeu a dieta de base comum a todos
os grupos; o grupo II foi tratado diariamente com padrão de vitamina E (83 mg/kg/dia) durante
10 dias; os grupos III, IV e V foram tratados com 300, 700 e 1000 mg/kg/dia dos hidrolisados,
48
respectivamente, durante 10 dias. Os resultados obtidos mostraram que os hidrolisados obtidos
utilizando a combinação das enzimas Alcalase e Protamex produziram peptídeos com alta
atividade antioxidante. O perfil de distribuição da massa molecular dos hidrolisados mostrou
peptídeos com tamanho entre 250 e 1200 Da. A ingestão de 300 mg kg-1
de peptídeos resultou em
aumento das atividades enzimáticas de superóxido dismutase, glutationa-peroxidase e reduziu os
teores de malonaldeído no fígado e sangue dos camundongos em comparação ao grupo controle e
ao tratado com vitamina E, indicando um grande potencial antioxidante.
4.3. Peptídeos com atividade antiadipogênica
A obesidade é resultado de um desequilíbrio entre a ingestão e a real necessidade de
energia, levando a um crescimento patológico de células adipócitas (Aoyama et al., 2000). A
quantidade de tecido adiposo pode ser controlada por inibição da adipogênese em células
precursoras ou pré-adipócitas, como os pré-adipócitos 3T3-L1, que são os modelos mais bem
caracterizados para o estudo de adipogênese. Muitos fatores de transcrição estão envolvidos na
diferenciação de células pré-adipócitas em adipócitos, e a inibição ou regulação destes fatores
pode levar a uma diminuição do acúmulo de gordura no organismo (Tsou et al., 2010). A
glicerol-3-fosfato desidrogenase (GPDH) é uma enzima que ocupa uma posição chave no
metabolismo da glicose, e está ligada à biossíntese de fosfolipídeos e triglicerídeos (Harding et
al., 1975; Tsou et al., 2010b). A supressão da atividade GPDH pode resultar na inibição da
diferenciação bem como na redução do acúmulo de lipídeos em células 3T3-L1, assim a
determinação da atividade desta enzima pode ser empregada para avaliar o efeito antiadipogênico
(Hirai et al., 2005). Outra enzima envolvida no processo de adipogênese é a ácido graxo sintetase
(FAS), a qual participa da síntese endógena de ácidos graxos saturados de cadeia longa a partir
dos precursores acetil-CoA e malonil-CoA (Rahman et al., 2008; Maier et al., 2008). Tem sido
relatado que certas frações de proteínas hidrolisadas possuem a capacidade de inibir a ação destas
enzimas, regulando assim o processo de diferenciação celular e o acúmulo relativo de lipídeos.
De acordo com Kim et al. (2007), estes hidrolisados apresentam grande potencial em tratamentos
antiobesidade por diminuírem o acúmulo de gordura no organismo.
Martinez-Villaluenga et al., (2008) estudaram a produção de hidrolisados obtidos a partir
de proteínas de soja utilizando a preparação comercial de proteases Alcalase®. Os hidrolisados
foram avaliados quanto ao efeito sobre o acúmulo relativo de lipídeos em células pré-adipócitas
49
3T3-L1 e mostraram supressão variando de 29 a 46%. Os autores também avaliaram a atividade
anti-adipogênica de diferentes frações da proteína de soja e detectaram que as unidades da fração
de β-conglicinina apresentaram um maior número de peptídeos responsáveis pela inibição do
acúmulo de lipídeos em células 3T3-L1 quando comparadas às subunidades de glicinina.
Tsou et al. (2010a) estudaram a aplicação da preparação comercial de proteases
Flavourzyme®
na hidrólise de proteína isolada de soja e avaliaram a capacidade antiadipogênica
das frações dos hidrolisados obtidas por ultrafiltração. Os resultados revelaram que a hidrólise
limitada de proteína isolada de soja permitiu a obtenção de hidrolisados com grande capacidade
antiadipogênica, e que as frações obtidas por ultrafiltração inibiram mais eficientemente a
atividade GPDH, sendo a fração obtida com membranas de 1 kDa, a mais efetiva (59% de
inibição). A atividade antiadipogênica de hidrolisados de proteína isolada de soja após tratamento
enzimático com Neutrase e o efeito do fracionamento por ultrafiltração sobre a bioatividade
foram estudados por Tsou et al. (2010b). Assim como no estudo anterior, os resultados
mostraram que peptídeos com baixa massa molecular (entre 1.300 e 2.200 Da) foram mais
efetivos na inibição da atividade GPDH.
Mejia et al. (2010) avaliaram o efeito de hidrolisados proteicos de soja enriquecidos com
β-conglicinina (proteína naturalmente presente na soja) sobre a atividade da FAS e adipogênese
em adipócitos humanos in vitro. Os resultados mostraram que alterações genotípicas nas
subunidades da proteína de soja (enriquecimento com β-conglicinina) produziram perfis
peptídicos que levaram à inibição da FAS e diminuição do acúmulo de lipídeos in vitro. A
quantidade de hidrolisados de proteína de soja necessária para inibir 50% da atividade da FAS
(IC50) variou de 50-175 µM. Um peptídeo com capacidade antiadipogênica foi isolado por
ultrafiltração, filtração em gel e CLAE a partir de hidrolisados proteicos de soja. A capacidade
antiadipogênica foi confirmada por meio da inibição da diferenciação de células pré-adipócitas
3T3-L1. O inibidor de adipogênese foi identificado com um tripeptídeo (Ile-Gln-Asn), tendo um
valor de IC50 de 0,014 mg de proteína mL-1
(Kim et al., 2007).
4.4. Peptídeos com atividade anti-hipertensiva
A hipertensão arterial afeta cerca de 25% da população adulta em todo o mundo, e há uma
previsão de que este número atinja 29% da população até 2025, o que representa um total de 1,56
bilhão de pessoas (Ngo et al., 2015). Embora seja um distúrbio controlável, a hipertensão está
50
associada ao desenvolvimento de doenças cardiovasculares, como arteriosclerose, infarto de
miocárdio e acidente vascular cerebral (Sheih et al., 2009). A enzima conversora de angiotensina
(ECA) desempenha um papel importante na regulação da pressão arterial porque catalisa a
conversão da angiotensina I (forma inativa) em angiotensina-II (vasoconstritor), além de inativar
a bradicinina (vasodilatador). Consequentemente inibidores sintéticos da ECA, tais como
captopril e enalapril são muitas vezes utilizados para tratar a hipertensão e outras doenças
relacionadas com o coração. No entanto, os inibidores sintéticos podem causar diversos efeitos
colaterais, como tosse, alteração do paladar, erupções cutâneas e angioedema (Alemán et al.,
2011).
É bem reconhecido, que proteínas alimentares contêm sequências primárias de peptídeos
capazes de modular funções fisiológicas específicas (Hong et al., 2008). Muitos tipos de
peptídeos bioativos com atividade inibidora da ECA foram isolados de hidrolisados proteicos e
produtos fermentados. O dipeptídeo Ala-Pro e o tripeptídeo Phe-Ala-Pro, por exemplo,
apresentam estruturas análogas às drogas captopril e enalapril, respectivamente (Figura 3).
Figura 3 - Estruturas de medicamentos inibidores da ECA e os seus peptídeos análogos (Figura
adaptada de Matsui e Matsumoto, 2006).
H
H C
2
N C
H
CH 3
C
O
NCOOH
CO
C2
CH2
H
H
2CH
2C
COOHN
O
C
3CH
H
C NC
H
H N
O
HS C
H
H
C
H
CH3
C
O
NCOOH
COOHN
O
C
3CH
H
CH N2
Captopril
Ala-Pro
Enalapril
Phe-Ala-Pro
51
Frações peptídicas de proteína de soja hidrolisada com pepsina foram separadas por
cromatografia de troca iônica, filtração em gel e CLAE e apresentaram atividade inibitória sobre
a ECA. Quatro sequências de aminoácidos foram identificadas como potenciais inibidoras da
ECA: Ile-Ala (IC50 153 µM), Tyr-Leu-Ala-Gly-Asn-Gln (IC50 14 µM), Phe-Phe-Leu (IC50 37
µM) e Ile-Tir-Leu-Leu (IC50 42 µM). Quando administrados em uma dose de 2,0 g de peso
corporal kg-1
em ratos hipertensos durante 15 semanas, as frações de peptídeos reduziram
consideravelmente a pressão arterial (Chen et al., 2003).
Peptídeos com atividade anti-hipertensiva foram isolados de hidrolisados proteicos de
leite após fermentação com bactérias lácticas e hidrólise enzimática com a protease comercial
Prozyme® 6. Os peptídeos foram identificados como Gly-Thr-Trp e Gly-Val-Trp, e apresentaram
atividade inibitória da ECA com valores de IC50 de 464,4 e 240,0 µM, respectivamente (Chen et
al., 2007). Hernández-Ledesma et al. (2007) hidrolisaram proteínas do leite humano com pepsina
e pancreatina para estudo das propriedades anti-hipertensivas de peptídeos e verificaram que os
hidrolisados derivados da β-caseína mostraram potente ação inibidora da ECA, com IC50 de 21
µM.
Chaves-López et al., (2014) estudaram o efeito da combinação de culturas microbianas
previamente selecionadas como proteolíticas e a capacidade de liberação de peptídeos com
atividade inibidora da ECA durante produção de leite fermentado. Foram utilizadas as linhagens
de leveduras Torulaspora delbruekii KL66A, Galactomyces geotrichum KL20B, Pichia
kudriavzevii KL84A e Kluyveromyces marxianus KL26A e linhagens de bactérias ácido lácticas
Lactobacillus plantarum LAT03, Lb. plantarum KLAT01 e Enterococcus faecalis KE06 (não
virulenta). Os resultados obtidos indicaram que a combinação de diferentes culturas pode
aumentar significativamente os teores de peptídeos com atividade anti-hipertensiva. A
combinação mais eficaz para a produção destes peptídeos foi P. kudriavzevii KL84A, Lb.
plantarum LAT3 e E. faecalis KL06, com IC50 para atividade de inibição da ECA de 30,63 µg
mL-1
.
O efeito anti-hipertensivo de um peptídeo de caseína bovina previamente identificado
como Met-Lys-Pro foi investigado in vitro e in vivo. Os ensaios in vitro basearam-se na
capacidade de inibição da ECA e os estudos in vivo foram conduzidos utilizando grupos de ratos
naturalmente hipertensos. Os animais foram tratados com soluções de peptídeos (10 mg kg-1
)
52
duas vezes ao dia e enalapril (10 mg kg-1
) em única dose diária durante 28 dias consecutivos. Os
ensaios in vitro mostraram que o peptídeo apresentou atividade inibidora da ECA com IC50 de
0,43 µM. Já para os ensaios in vivo, a pressão arterial dos animais apresentou valores de 171,7,
163,3 e 139,7, respectivamente, para os grupos controle, tratado com solução de peptídeos e
tratado com enalapril, indicando diferenças e reduções significativas na pressão arterial entre os
grupos controle e os tratados com peptídeos (p < 0,05) e enalapril (p < 0,01) (Yamada et al.,
2015).
4.5. Indução do crescimento de bactérias ácido lácticas e probióticas
Bactérias ácido lácticas não possuem capacidade para sintetizar todos os aminoácidos
necessários para o seu crescimento. Assim, estes micro-organismos devem hidrolisar proteínas
durante o processo de fermentação de produtos lácteos para obtenção de aminoácidos livres e
pequenos peptídeos como fontes nutricionais essenciais para seu crescimento. O sistema
proteolítico de bactérias ácido lácticas compreende três mecanismos básicos e é composto por: 1)
uma ou mais enzimas proteolíticas presentes na parede celular, também conhecida como
proteases do envelope celular, as quais têm a capacidade de hidrolisar proteínas do leite a
peptídeos contendo de 4 a 30 resíduos de aminoácidos; 2) sistema de transporte de peptídeos
composto por proteínas de ligação, duas permeases responsáveis pela formação dos canais de
transporte e duas ATPases que fornecem energia ao sistema e 3) um conjunto de peptidases
intracelulares que promoverão a hidrólise dos peptídeos inicialmente transportados para o interior
das células a aminoácidos (Hafeez et al., 2014).
Apesar de todo o aparato proteolítico, vários estudos têm demonstrado que a
suplementação do leite com fontes de proteínas previamente hidrolisadas apresentaram impacto
positivo sobre o crescimento de bactérias lácticas e probióticas. Estes estudos são impulsionados
principalmente em virtude de duas características principais deste grupo de micro-organismos: 1)
bactérias lácticas e probióticas são bastante exigentes nutricionalmente, especialmente com
relação ao aporte de aminoácidos e 2) o conjunto de aminoácidos e peptídeos livres no leite não é
suficiente para garantir o crescimento bacteriano ideal neste substrato, podendo assim dificultar
processos de fermentação nos quais estes micro-organismos estejam envolvidos (Zhang et al,
2011). Assim, diferentes fontes de proteína têm sido avaliadas na suplementação de meios de
53
cultura para estudo da indução do crescimento de espécies de bactérias ácido lácticas e
probióticas (McComas Jr. e Gilliland, 2003; Zhang et al , 2011; Prasanna et al., 2012).
McComas Jr. e Gilliland (2003) investigaram o crescimento de bactérias lácticas e
probióticas em amostras de leite bovino suplementadas com hidrolisados de proteína de soro de
leite. Os resultados obtidos mostraram que os hidrolisados não apresentaram efeitos sobre o
crescimento de L. delbrueckii ssp. bulgaricus e S. thermophilus; no entanto, aumentos
significativos sobre o crescimento de Bifidobacterium longum e L. acidophilus foram observados.
Prasanna et al., (2012) estudaram a suplementação de leite bovino desnatado com
diferentes fontes de proteínas hidrolisadas e os efeitos sobre o crescimento de bactérias
probióticas e observaram que o tipo ou fração da proteína utilizada influenciava diretamente no
crescimento dos micro-organismos. A concentração final de células de B. longum subsp. infantis
CCUG 52486 e B. infantis NCIMB 702.205 foi superior quando estas linhagens foram cultivadas
em amostras de leite suplementadas com hidrolisados de caseína, em comparação com outras
frações proteicas hidrolisadas a partir de lactoalbumina, concentrado proteico de soro de leite ou
isolado proteico de soro de leite.
5. Conclusão
Peptídeos com atividade biológica podem ser definidos como sequências específicas de
aminoácidos que promovem efeitos fisiológicos benéficos. As tecnologias para obtenção de
peptídeos bioativos envolvem a hidrólise de proteínas por enzimas exógenas de origem
microbiana, vegetal ou animal e processos fermentativos utilizando-se fungos ou bactérias. A
ampla diversidade bioquímica das proteases, assim como a existência de fontes proteicas com
composições variadas de aminoácidos, torna possível a obtenção de peptídeos com funções
biológicas distintas e/ou até mesmo com multifuncionalidade, assim como as condições de
processo. Entre as técnicas de purificação e identificação, os métodos cromatográficos e a
espectrometria de massas surgem como importantes ferramentas. O estudo sobre os processos de
obtenção assim como o entendimento da sua multifuncionalidade e avaliação utilizando métodos
in vitro e in vivo tornam-se aliados na aplicação de peptídeos bioativos como potentes agentes
biológicos naturais que podem ser utilizados em conjunto ou até mesmo em substituição a
substâncias sintéticas em processos de conservação de produtos alimentícios, na administração de
alimentos funcionais e na produção de fármacos.
54
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67
Capítulo III: Improving the functional properties of milk proteins: focus on
the specificities and mechanisms of action of proteolytic enzymes
Revista: Current Opinion in Food Science
68
Abstract
The modification of milk proteins by enzymatic hydrolysis has great potential for optimizing
functional properties. The most common method of improving the functional properties of milk
proteins is to evaluate the hydrolysis parameters. However, a limited number of studies correlated
their results with the biochemical properties of the proteolytic enzymes to understand the
mechanism of action by which the functional properties of the milk proteins are affected by the
specificity of the proteases. In this review, the primary focus is the use of enzymatic hydrolysis of
milk proteins as a tool for enhancing their functional properties, emphasizing protein solubility,
gelation, and emulsion capacities. In particular, there is a discussion of the specificities and
mechanisms of action of the proteolytic enzymes.
Keywords: milk proteins, proteases, specificities, functional properties.
69
1. Introduction
Milk proteins are key functional components and provide desirable characteristics to food
products and food systems to which they are added [1]. The functionality of food proteins refers
to their physicochemical properties and is generally classified into two main groups,
hydrodynamic or hydration-related, including water absorption, solubility, viscosity, and
gelation, and surface-active properties, such as emulsification, foaming, and film formation [2,
3].
During the last decade, industrial-scale technologies suitable for the industrial production
of milk-derived proteins have been developed, resulting in many different grades and types of
protein enriched products [3, 4]. Milk proteins have enhanced functional properties by altering
the protein and non-protein composition, and/or modifying the proteins by enzymatic treatments
[5, 6].
Enzymatic hydrolysis disrupts the protein tertiary structure and reduces the molecular
weight of the protein, enhancing the interaction of peptides with themselves and with the
environment, and consequently altering their functional properties [7]. Notably, the nature of the
protein modification is influenced by several hydrolysis parameters, including the reaction
conditions, such as pH, temperature, degree of hydrolysis, and enzyme specificities, and intrinsic
characteristics of each food, such as ionic strength, concentration of calcium and other polyvalent
ions, sugars, and hydrocolloids [3, 8, 9].
The modification of milk proteins based on enzymatic hydrolysis has broad potential and
are likely an innovative tool in food protein processing for optimizing the techno-functional and
tropho-functional properties of proteins in food products [10, 11, 12]. Several studies showed that
the enzymatic hydrolysis of milk proteins resulted in increased protein solubility, heat stability,
emulsion capacity, foaming properties and surface hydrophobicity, which make hydrolysates
suitable for ingredients in other foods, including dairy products (Table 1).
70
Table 1 – Enzymatic hydrolysis of milk proteins using proteases with different mechanisms of action and parameters of hydrolysis and
the effects on the functional properties of the hydrolysates.
Protein
source Enzymes
Mechanism
of action Parameters of hydrolysis
Degree of
hydrolysis Changes in functional properties Reference
Milk protein
concentrates
Chymotrypsin
Trypsin
Pepsin
Papain
Endoproteases
pH 8.0 / 50 °C / 5-10 min
pH 8.0 / 37 °C / 10-60 min
pH 2.0 / 37 °C / 240-720 min
pH 6.8 / 60 °C / 30-180 min
24.3-24.4%
14.8-15.1%
5.0-5.7%
7.2-9.8%
Solubility was improved in the pH range
of 4.6 to 7.0
Surface hydrophobicity and gel strength
were reduced
Emulsification capacity was increased
[13]
Whey
protein
isolate
AlcalaseTM
2.4L Endoprotease pH 8.0 / 45 °C / 5-120 min 10.0-20.3%
The gelling properties showed an increase
with increase in the degree of hydrolysis [14]
Whey
protein
concentrate
AlcalaseTM
2.4L
Prolyve TM
1000
Endoproteases pH 7.0 / 50 °C / 30-300 min 12.0-19.2%
10.0-15.9%
AlcalaseTM
2.4L hydrolysates formed a soft
gel at DH of 16.9%
Prolyve TM 1000 hydrolysates showed no
evidence of gel formation
[15]
Whey
protein
concentrate
FlavourzymeTM
500L
Endoprotease /
Exoprotease pH 5.0 / 50 °C / 120 min 19.4%
Increase in solubility and decrease in heat
stability and emulsion activity index [16]
Sodium
caseinate
Papain
Pancreatin
Trypsin
Endoproteases
pH 7.0 / 37 °C / 10 min – 24 h
pH 8.0 / 37 °C / 10 min – 24 h
pH 8.0 / 37 °C / 10 min – 24 h
13.32-22.06%
9.42-20.91%
14.86-20.68%
The solubility of hydrolysates varied with
the enzyme type. Papain-treated
hydrolysates exhibited higher solubility,
followed by trypsin and pancreatin
hydrolysates
For most hydrolysate samples, the
emulsifying properties were improved
[17]
Whey
protein
isolate
Chymotrypsin
Pepsin Endoproteases
pH 7.8 / 37 °C / 180 min
pH 2.6 / 37 °C / 180 min
10.6%
11.0%
Chymotrypsin hydrolysates formed
nanoemulsions
Pepsin hydrolysates did not form
nanoemulsions
[18]
71
There are a few detailed studies about the specificity and mechanisms of action of the
proteolytic enzymes and the manner in which these characteristics affect the functional properties
of the milk protein hydrolysates. Therefore, information of these mechanisms is valuable for
optimizing the enzymatic hydrolysis of milk proteins with different properties directed to specific
applications.
In this review, the primary focus is on the enzymatic hydrolysis of milk proteins as a tool
to enhance their functional properties, with emphasis on protein solubility, gelation, and emulsion
capacities. A specific discussion of the specificities and mechanisms of action of the proteolytic
enzymes and how these characteristics affect the functional properties of milk protein
hydrolysates will be reviewed.
2. Functional properties of milk proteins
2.1. Solubility
Solubility is one of the most important functional properties of protein hydrolysates and
largely determines their use in foods. This parameter was highly correlated with the reduction in
molecular weight and an increase in the number of smaller, more hydrophilic, and more solvated
polypeptide units via enzymatic hydrolysis, resulting in an increase in the exposed net charge
density [19]. A decrease in solubility after enzymatic hydrolysis may occur when the protein
molecule exposes more hydrophobic groups, therefore, to improve the solubility of milk proteins,
limited and selective hydrolysis is a critical point [7, 16]. A comparative study using three
different proteases showed that the solubility of sodium caseinate hydrolysates varied with the
enzyme type, presenting an interesting correlation with the enzymes specificities. Of the three
enzymes, the hydrolysates obtained with papain exhibited a greater capability of improving the
solubility of sodium caseinate, followed by trypsin and pancreatin [17]. Papain is a cysteine
endopeptidase that exhibits broad substrate specificity and specifically hydrolyzes arginine,
lysine and phenylalanine bonds [20, 21] (Figure 1). The open conformation of papain allows it
rapidly and extensively degrade larger bovine β-casein molecules, an abundant milk protein, to
smaller peptides originating predominantly from the C-terminus, which results in the formation
of a hydrophilic surface and in increase of protein solubility [22]. Trypsin is a serine protease
with a narrow specificity that only hydrolyzes peptide bonds involving the carboxylic group of
lysine and arginine residues [23] (Figure 1). Pancreatin is an enzymatic complex comprising
72
lipase, amylase and proteolytic enzymes, including trypsin, chymotrypsin and elastase, which has
more target cleavage sites in the proteins and may hydrolyze the protein more randomly.
Pancreatin preferentially cleaves N-terminal phosphorylated regions and the C-terminal
hydrophobic regions of casein molecules, showing similar profiles with casein hydrolysates
obtained via trypsin [24] (Figure 1). Because of their specificities, the interactions between the
peptides generated from enzymatic hydrolysis with pancreatin and/or trypsin may increase,
resulting in hydrolysates with lesser protein solubility compared to hydrolysates obtained using
papain [17, 24, 25].
Figure 1 – Proteolytic enzymes and their specificities for cleavage of peptide bonds.
2.2. Gelation properties
Enzymatic hydrolysis can result in the release of peptides with less hydrophobic
properties and more charge than the intact protein, decreasing the interactions between peptide
fragments and consequently, gel formation. In this case, the selection of the most suitable enzyme
plays a central role in protein hydrolysis and it is essential to thoroughly investigate the substrate
73
specificity using specific milk protein substrates and proteases with different mechanisms of
action [26]. The gelation properties of milk proteins hydrolysates are due to the hydrophobic
interactions between hydrophobic peptide aggregates, with a minor contribution by hydrogen
bonds and electrostatic interactions. Spellman et al. [15] showed that whey protein concentrate
hydrolyzed with two commercial preparations of proteases under the same hydrolysis conditions
resulted in protein hydrolysates with different capacities for gel formation, attributed to the
enzymes specificities. In their studies, the main proteolytic component of both enzymes Alcalase
2.4LTM
and Prolyve 100TM
that were used for whey protein concentrate hydrolysis is subtilisin
Carlsberg (EC 3.4.21.62). Subtilisin proteases are serine proteases with relatively low substrate
specificity, but they preferentially cleave peptide bonds after large non-β-branched hydrophobic
residues [15]. Although both enzymes had subtilisin activities, Alcalase 2.4L
TM presents a
specific activity of glutamyl endopeptidase that is not present in Prolyve 100TM
and is responsible
for cleaving peptide bonds after a glutamic acid and to a lesser extent, aspartic acid residues. This
explains its ability to digest substrates with glutamic acid residues at the C-terminus, such as
casein phosphopeptides and whey proteins [15, 26]. The whey protein hydrolysates obtained with
Alcalase 2.4L
TM resulted in the formation of a soft gel, whereas the Prolyve 100
TM hydrolysates
showed no evidence of gel formation, suggesting that the glutamyl endopeptidase activity in
Alcalase 2.4L
TM improved the gelation properties of the whey protein concentrate [15].
2.3. Emulsifying properties
Emulsions, specifically nanoemulsions, are widely used in food and pharmaceutical
industries to deliver poorly water-soluble bioactive compounds and drugs [27, 28]. Conventional
emulsions are a dispersion of two completely or partially immiscible liquids formed by
mechanical shear. Proteins have been used as emulsifiers because of their amphiphilic
characteristics and because they can unfold and re-orientate at the interface [29]. These
macromolecules can be substituted for common emulsifiers that confer weak stabilization and
have toxicological concerns for long-term use [28, 29]. Milk proteins have good emulsifying
capacity [28, 30], and the hydrolysis of these proteins can expose groups buried inside the tertiary
structure allowing new interactions at the interface of the emulsions droplets, such as disulfide
and non-polar bonds to improve the emulsification capacity [28, 31]. Luo et al. [17] observed that
papain and trypsin treatment of casein reduced the surface hydrophobicity of the hydrolyzed
protein; however, pancreatin treatment increased this parameter during the first 4 h of the
74
treatment and significantly reduced it after 24 h. The emulsion activity (EAI) and emulsion
stability index (ESI) were increased for the three proteases, except for the papain treatment after
1 h and pancreatin treatment after 24 h. Trypsin treatment of casein resulted in a higher EAI and
ESI after 24 h compared to papain and pancreatin, although the degree of hydrolysis was nearly
the same (approximately 20%), reinforcing the high substrate specificity of trypsin compared to
papain and pancreatin. Castro & Sato [16] observed that bovine whey protein hydrolyzed with
FlavourzymeTM
500L protease for 2 h had an emulsion activity index reduced by 12%.
FlavourzymeTM
500L is a neutral protease from Aspergillus oryzae that hydrolysis a variety of
peptide bonds, promoting a high degree of hydrolysis [32] (Figure 1). Banach et al. [13] observed
that chymotrypsin and trypsin hydrolysis of milk protein concentrate increased the EAI and ESI
of the hydrolyzed protein, but papain did not change these indices. These observations indicate
that the protease substrate specificity leads to different hydrolysate products with specific
interactive sites on the surface and specific molecular masses that improve the ability of the
peptide to adsorb to the interface of an immiscible liquid emulsion. Extensive hydrolysis can
produce large amounts of free amino acids and short-chain peptides that decrease the emulsifying
properties of proteins (Figure 2). By contrast, limited proteolysis exposes hydrophobic and
hydrophilic residues, enhances the amphiphilic characteristics of proteins, and improves
emulsification [20, 30, 33, 34].
75
Figure 2 - Proteolytic enzymes with high and low specificities and their effects on production of
peptides with emulsifying properties. Red dots are hydrophobic moieties and green “x” are free
amino acids.
3. Conclusion
The enzymatic hydrolysis of milk proteins has great potential for enhancing their
functional properties and is becoming one of the most frequently used tools in food protein
processing. Several studies showed the effect of the parameters of hydrolysis, such as pH,
temperature, time, and enzyme:substrate ratio, which affected the functional properties of the
milk proteins. A particular focus on the specificities and mechanisms of action of proteolytic
enzymes is critical for obtaining milk protein hydrolysates with highly desirable characteristics.
The evaluation of hydrolysis sites, including the composition, distribution and interactions of the
amino acid residues of milk proteins, is fundamental for regulating their functional properties,
such as solubility, gelation and emulsification. Based on the mechanisms of action and substrate
specificities of different proteolytic enzymes, it is possible to modulate milk protein hydrolysates
to balance their functional properties for specific applications in the food and pharmaceutical
industries.
Inta
ct P
rote
in
Water
Em
uls
ion Water
Oil Oil
High specificity
protease (eg. trypsin)
Low specificity
protease (eg. subtilisin)
Migration and reorientation
of protein fragments to the
oil-water interface
Small peptides and free
amino acids can not bind to
the oil-water interface and
reorientate
Hy
dro
lyze
d
Pro
tein
76
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79
Capítulo IV: Improving the protease production by Aspergillus niger under
solid state fermentation by substrate formulation using statistical mixture
design
Revista: Industrial Crops and Products
80
Abstract
Wheat bran, soybean meal, cottonseed meal and orange peel, alone or in combinations, were used
as the substrates for protease production by Aspergillus niger LBA02 under solid state
fermentation using a simplex-lattice mixture design. Correlation analysis suggested that protein
and ash contents exerted relevant and positive impact on proteases secretion in the first 48 h
fermentation, while higher carbohydrates content negatively influenced the production at the
initial hours of fermentation. Synergistic and antagonistic effects of agroindustrial wastes were
observed during the fermentation time. The highest protease activity was found using the medium
containing the binary mixture of wheat bran (1/2) and soybean meal (1/2), reaching 262.78 U g-1
after 48 h fermentation. The most prominent synergetic effects were observed on fermentations
performed using the medium composed by the four agroindustrial wastes in equal proportions at
48 and 72 h fermentation, reaching increases of 33.7, 7.6, 30.8 and 581.7% and 11.6, 131.4, 69.5
and 547.0%, respectively, in protease production as compared to the individual substrates. The
results suggest that the application of the statistical mixture designs is an attractive method for
improving protease production and identifying optimum formulations using different substrates.
Keywords: protease; solid state fermentation; agroindustrial wastes; statistical mixture design.
81
1. Introduction
Proteases are multifunctional enzymes that catalyze the hydrolysis of proteins to
polypeptides and oligopeptides to amino acids. These enzymes accounting for nearly 60% of the
whole enzyme market and have been used in a wide variety of applications including the
production of pharmaceuticals, detergents, fertilizers or textiles and in processes in leather, food
and biotechnology industries (Ramakrishna et al., 2010; Yin et al., 2013; Abraham et al., 2014).
They can be isolated from plants, animals and microorganisms. Among these sources, the
microorganisms show great potential for protease production due to their broad biochemical
diversity and their susceptibility to genetic manipulation. It has been estimated that microbial
proteases represent approximately 40% of the total worldwide enzyme sales (Rao et al., 1998).
Several species of filamentous fungi have been exploited in industrial processes for the
production of metabolites and industrial enzymes. A. niger has a long tradition of safe use in the
production of enzymes and organic acids. Many of these products have listed as a ‘‘Generally
Recognized as Safe (GRAS)’’ by the US Food and Drug Administration (Schuster et al., 2002).
A. niger is one of the most important sources of fungal proteases. According Pel et al., (2007),
genome sequencing shows that A. niger has 198 proteins involved in proteolytic degradation
process.
Proteolytic enzymes can be produced by submerged and solid state fermentation. For the
growth of fungi, solid state fermentation is most appropriate method because the solid substrates
resemble the natural habitat of the fungi and improving their growth and the secretion of a wide
range of extracellular enzymes. Some characteristics make solid state fermentation more
attractive than submerged fermentation: simplicity, low cost, high yields and concentrations of
the enzymes and the use of inexpensive and widely available agricultural residues as substrates
(Chutmanop et al., 2008). This process arouses most economical interest in regions such as
Brazil, which has abundant biomass and agroindustrial wastes with low cost, such as the residues
from the processing of soybeans, wheat, cottonseed and oranges, that reached a world production
of approximately 1.1 billion tons in 2013 (FAO, 2014). The use of these wastes as substrates for
the development of biotechnological processes such as the enzymes production by solid state
fermentation is a promising example of obtaining biomolecules with high added value from low
cost substrates.
82
The biochemical characterization of enzymes is important to evaluate their
biotechnological potential. The study of the protease properties, such as the substrate specificity,
the optimum catalytic pH conditions and the temperature and stability profiles, can be used to
predict the successful application of the enzyme to particular industries or processes (Castro and
Sato, 2013).
Statistical methods were applied to different engineering problems for improving the
performance and to find the optimum process variables. Statistical mixture designs are special
class of response surface designs where the proportions of the components or factors are
considered important. It involves the use of different combinations between the components for
changing mixture composition and exploring how such changes will affect a specific response.
The interactions between the components of a mixture for maximizing the response are studied
using mixture design approach (Rao and Baral, 2011).
In this work, a simplex-lattice mixture design has been applied to investigate the presence
of synergistic or antagonistic effects of different agroindustrial wastes for protease production by
Aspergillus niger LBA02 under solid state fermentation. The correlation between the chemical
components of the agroindustrial wastes with the protease production was further studied.
2. Materials and Methods
2.1. Agroindustrial wastes and centesimal composition
Wheat bran, soybean meal, and cottonseed meal were kindly provided by Bunge Foods
S/A. Orange peel was purchased from local market of Campinas (Sao Paulo, Brazil). To be used
as matrix support, the orange peel was grinded, washed three times with distilled water and dried
at 50 °C for 24-48 h.
Moisture, protein content, lipids and ash of the agroindustrial wastes were determined by
AOAC methods (AOAC, 2010). The carbohydrate content was measured by difference between
the total value of 100% and the sum of the other components. The tests were performed in
triplicate and the results were expressed as the mean ± standard deviation.
2.2. Microorganism culture
The strain used in this study was A. niger LBA02, previously selected as a proteolytic
strain from the culture collection of the Laboratory of Food Biochemistry, School of Food
83
Engineering, University of Campinas. The strain was periodically subcultured and maintained on
potato dextrose agar slants. To produce fungal spores, the microorganism was inoculated into a
medium composed of 10 g wheat bran and 5 mL of solution containing 1.7% (w/v) NaHPO4 and
2.0% (w/v) (NH4)2SO4 and incubated for 3 days at 30 °C. The fungal spores were dispensed into
sterile Tween 80 solution (0.3%) to prepare the inoculum for fermentation. The number of spores
per milliliter in the spore suspension was determined with a Neubauer cell counting chamber.
2.3. Protease production and sampling
The protease production was performed under solid state fermentation using the individual
substrates, binary, ternary or quaternary mixtures of their in various proportions in 250 mL
Erlenmeyer flasks containing 20 g medium. The initial cultivation parameters, defined in
previous studies in our laboratory (data no shown), as the most appropriate conditions for
protease production by A. niger LBA02, were 50 % moisture, temperature set at 30 °C, and an
inoculum level of 107 spores g
-1.
The protease activity was tested at 24 h intervals during 96 h fermentation. The crude
extract was obtained by the addition of 100 mL distilled water. After 1h at rest, the solution was
filtered through a filter membrane to obtain an enzyme solution free of any solid material.
2.4. Statistical mixture design
The mixture design of experiment was used to obtain the optimum composition between
the agroindustrial wastes for maximum protease production and to evaluate the interaction effects
in a blend of components. A four component augmented simplex-lattice design has been
employed in which each components is studied in six levels, namely 0 (0%), 1/8 (12.5%), 1/4
(25%), 1/2 (50%), 5/8 (62.5%) and 1 (100%) (Table 1).
Special cubic regression models were fitted for variations of all studied responses as
function of significant (p < 0.05) interaction effects between the proportions, with acceptable
determination coefficients (R2 > 0.90). Eq. (1) represents these models:
where Yi is the predicted response; ‘q’ represents the number of components in the system; ‘Xi,
Xj, Xk’ are the coded independent variables; ‘βi’ is the regression coefficient for each linear effect
𝑌𝑖 = 𝛽𝑖𝑋𝑖 + 𝛽𝑖𝑗
𝑞
𝑖<𝑗
𝑞
𝑖=1
𝑋𝑖𝑋𝑗 + 𝛽𝑖𝑗𝑘𝑋𝑖𝑋𝑗𝑋𝑘
𝑞
𝑖<𝑗<𝑘
84
term; and ‘βij’ and ‘βijk’ are the binary and ternary interaction effect terms, respectively.
StatisticaTM
10 software from Statsoft Inc. (Tulsa, Oklahoma, USA) was employed for the
experimental design, data analysis and model building.
Table 1 – Matrix of the simplex-lattice mixture design for protease production by A. niger
LBA02 under solid state fermentation using different agroindustrial wastes and their mixtures as
substrates.
*All the formulated medium had the moisture level adjusted to 50% according to the initial moisture.
2.5. Determination of protease activity
The protease activity was measured using azocasein as the substrate according to Charney
and Tomarelli (1947) and described by Castro and Sato (2013). The reaction mixture containing
0.5 mL 0.5% (w/v) azocasein (Sigma), pH 5.0, and 0.5 mL of the enzyme solution was incubated
for 40 min. The reaction was stopped by adding 0.5 mL 10% TCA and the test tubes were
centrifuged at 17,000 x g for 15 min at 25 °C. A 1.0 mL aliquot of the supernatant was
neutralized with 1.0 mL 5 M KOH. One unit of enzyme activity (U) was defined as the amount of
enzyme required to increase the absorbance at 428 nm by 0.01 under the assay conditions
described.
Run
Independent variables
Wheat bran Soybean meal Cottonseed meal Orange peel
x1 x2 x3 x4
1 1 0 0 0
2 0 1 0 0
3 0 0 1 0
4 0 0 0 1
5 1/2 1/2 0 0
6 1/2 0 1/2 0
7 1/2 0 0 1/2
8 0 1/2 1/2 0
9 0 1/2 0 1/2
10 0 0 1/2 1/2
11 5/8 1/8 1/8 1/8
12 1/8 5/8 1/8 1/8
13 1/8 1/8 5/8 1/8
14 1/8 1/8 1/8 5/8
15 1/4 1/4 1/4 1/4
85
2.6. Calculations and statistics
The Tukey test was used to check the significant differences between the groups analyzed
that were considered significant when p-value ≤ 0.05. Pearson correlation coefficient was used to
measure the strength of linear dependence between two responses. The correlation coefficient
ranges from – 1 to 1. A value of 1 implies that a linear equation describes the relationship
between the responses was perfectly and positive, while a value of -1 indicate a perfectly and
negative correlation. A value of 0 implies that there is no linear correlation between the
responses. The correlations between analyzed parameters were considered significant when the p-
value ≤ 0.10.
3. Results and Discussion
3.1. Chemical composition of the agroindustrial wastes
The centesimal compositions of the agroindustrial wastes used as fermentation substrates
for production of protease by A. niger LBA02 under solid state fermentation are showed in Table
2.
Table 2 – Average values of the centesimal composition (%) of the agroindustrial wastes used for
protease production by A. niger LBA02 under solid state fermentation.
Results are presented as the mean (n = 3) ± SD, and those with different letters are significantly different, with p < 0.05. Tukey
tests were applied between the chemical components of each substrate (not between different substrates). Carbohydrate content
(%) was measured by difference between the total value of 100% and the sum of the other components.
The enzymes production under solid state fermentation can be affected by the composition
of the substrates and various cultivation factors. On protease production, for example, the
presence of protein sources can induce the enzyme secretion by the microorganism. On the other
hand, the substrate must have a carbon to nitrogen ratio (C:N) suitable for the fermentation
(Castro and Sato, 2013). Soybean meal and cottonseed meal were the materials with higher
protein content and orange peel showed the major C:N ratio (Table 3).
Chemical components Wheat bran Soybean meal Cottonseed meal Orange peel
Moisture (%) 12.77 ± 0.08a 11.93 ± 0.02
a 6.42 ± 0.01
a 7.92 ± 0.08
a
Protein (%) 14.74 ± 0.51b 49.24 ± 0.07
b 25.91 ± 0.60
b 7.01 ± 0.08
b
Carbohydrates (%) 63.04c 31.53
c 55.80
c 79.68
c
Lipids (%) 4.47 ± 0.22d 1.40 ± 0.02
d 7.83 ± 0.01
d 1.95 ± 0.13
d
Ash (%) 4.98 ± 0.06e 5.90 ± 0.04
e 4.04 ± 0.01
e 3.44 ± 0.11
e
86
Table 3 - Correlation analysis between the chemical components of the agroindustrial wastes with the protease production by A. niger
LBA02 under solid state fermentation at 24, 48, 72 and 96 h.
Results are presented as the mean (n = 3) ± SD, and those with different letters are significantly different, with p < 0.05. Tukey tests were applied between the runs for each
fermentation time (not between different fermentation time). *The correlations between analyzed parameters were considered significant when the p-value ≤ 0.10.
Runs C:N Protein
(%)
Carbohydrate
(%)
Lipids
(%)
Ash
(%)
Protease production (U g-1
)
24 h 48 h 72 h 96 h
1 4.28 16.89 72.27 5.12 5.72 101.10 ± 5.73b 183.98 ± 5.65
f, g 178.00 ± 9.17
b, c 184.08 ± 6.84
a
2 0.64 55.91 35.80 1.59 6.70 130.10 ± 3.45a 228.60 ± 7.30
b, c 85.85 ± 3.10
f, g 63.77 ± 1.70
i
3 2.15 27.69 59.63 8.36 4.32 66.18 ± 1.05e 188.03 ± 7.65
f, g 117.17 ± 7.18
e 125.20 ± 2.28
c, d
4 11.37 7.61 86.53 2.12 3.74 40.62 ± 4.54f 36.08 ± 3.33
j 30.70 ± 3.40
h 14.00 ± 1.64
j
5 1.48 36.4 54.04 3.36 6.21 99.58 ± 1.47b 262.78 ± 10.39
a 90.20 ± 1.21
f, g 58.40 ± 1.14
i
6 2.96 22.29 65.95 6.74 5.02 69.22 ± 1.99d, e
176.27 ± 9.88g 137.92 ± 2.66
d 135.95 ± 5.76
c
7 6.48 12.25 79.40 3.62 4.73 74.18 ± 3.10c, d, e
99.75 ± 4.26i 97.55 ± 4.68
f 122.28 ± 8.83
c, d
8 1.14 41.8 47.72 4.98 5.51 105.63 ± 2.58b 221.73 ± 4.07
c, d 90.95 ± 4.69
f, g 105.42 ± 6.98
e, f
9 1.93 31.76 61.17 1.86 5.22 79.50 ± 6.81c, d
133.35 ± 5.60h 75.32 ± 1.69
g 71.37 ± 2.62
h, i
10 4.14 17.65 73.08 5.24 4.03 65.12 ± 3.95e 201.42 ± 9.94
d, e, f 179.07 ± 7.08
b 165.92 ± 7.55
b
11 3.09 21.96 67.91 4.71 5.42 84.25 ± 4.63c 218.92 ± 6.03
c, d, e 119.85 ± 4.97
e 83.75 ± 3.18
g, h
12 1.20 41.47 49.68 2.94 5.91 131.95 ± 4.57a 202.95 ± 5.55
d, e, f 116.68 ± 4.88
e 62.82 ± 2.45
i
13 2.25 27.36 61.59 6.33 4.72 103.93 ± 3.36b 198.22 ± 4.81
e, f, g 161.85 ± 8.71
c 111.45 ± 6.37
d, e
14 1.20 41.47 49.68 2.94 5.91 71.18 ± 1.50d, e
125.62 ± 8.80h 141.18 ± 5.63
d 163.27 ± 8.54
b
15 2.35 27.03 63.56 4.30 5.12 99.70 ± 1.49b 245.97 ± 13.35
a, b 198.63 ± 5.32
a 91.13 ± 2.48
f, g
Correlation analysis between the protease production and C:N
Pearson coefficient -0.67 -0.75 -0.33 -0.21
p-value 0.007* 0.001
* 0.234 0.462
Correlation analysis between the protease production and the protein content (%)
Pearson coefficient 0.71 0.52 -0.10 -0.17
p-value 0.003* 0.049
* 0.723 0.558
Correlation analysis between the protease production and the carbohydrates content (%)
Pearson coefficient -0.71 -0.58 0.03 0.08
p-value 0.003* 0.023
* 0.927 0.758
Correlation analysis between the protease production and the lipids content (%)
Pearson coefficient -0.19 0.27 0.50 0.54
p-value 0.491 0.322 0.056* 0.036
*
Correlation analysis between the protease production and the ash content (%)
Pearson coefficient 0.77 0.52 -0.01 -0.06
p-value 0.001* 0.047
* 0.978 0.828
87
The Pearson coefficient was used to verify the correlation between the chemical
components and the C:N ratio in the substrates with the protease production. The analysis
indicated positive and significant correlations between the protein and the ash contents (%) in the
substrates with the protease production at 24 h and 48 h fermentation. In contrast, negative and
significant correlations between the C:N ratio and the carbohydrate content with the protease
production were observed at 24h and 48 h fermentation. Positive and significant correlations
were detected at 72 and 96 h fermentation between the protease production and the lipids content
(Table 3).
These results suggested that an adequate supply of proteins as nitrogen source can induce
the protease production at the first hours of fermentation. On the other hand, high content of
carbon source can cause catabolic repression, a mechanism particularly important in the
regulation of the extracellular enzymes that degrade complex substrates in organisms exposed to
changing environments, which probably happened in the present study. An interesting
observation included the positive and significant impact of the ash content on the protease
production. The ash content can be defined as the measurement of the mineral content and other
inorganic matter in biomass. The presence of considerable amounts of minerals such as
potassium, phosphorus and calcium is a relevant characteristic for use of substrates in solid state
fermentation (Chutmanop et al., 2008). It is important to note that the lipids only presented
significant effects on protease production at the last hours of fermentation, as it is considered a
nutrient source not readily metabolizable. In addition to the content of each chemical component,
their specific structure, molecular weight, residues and chain length, especially for proteins and
carbohydrates, can influence the enzymes production. Chutmanop et al., (2008) reported the
protease production by A. oryzae using wheat bran and rice bran with similar content of proteins.
These authors observed higher protease production in rice bran and associated it to the easy
digestion of rice bran proteins compared to wheat bran proteins. The presence of diferent types of
carbohydrates, such as non-starch polysaccharides (pectin, cellulose, hemicellulose) or starch,
can be hardly or easily assimilated, respectively, by microorganisms for use as a carbon source.
88
Several studies describe the use of agroindustrial wastes as potent substrates for the
production of proteases by filamentous fungi of the genus Aspergillus. Thanapimmetha et al.,
(2012) observed maximum yields of protease production by a strain of A. oryzae using Jatropha
curcas seed cake as a substrate under solid state fermentation. The highest secretion of protease
was measured to be 3,094 U g DM−1
(units of protease per gram of dry material). Shivakumar
(2012) screened 11 different substrates, including 8 cereals and 3 agroindustrial residues, for
protease production by Aspergillus sp. under solid state fermentation and found that wheat flour,
wheat bran and soya flour proved superior protease production, reaching activities of 320, 280
and 160 U g-1
, respectively. Veerabhadrappa et al., (2014) evaluated the protease production by
A. versicolor CJS-98 under solid state fermentation using Jatropha seed cake and reached a
maximum protease activity of 3,366 U g-1
at 96 h. Castro et al., (2015) investigated the protease
production under solid state fermentation by A. awamori IOC-3914 using babassu cake as
substrate and observed maximum production of 31.8 U g-1
at 168 h fermentation.
3.2. Synergistic and antagonistic effects of the agroindustrial wastes on protease
production
The interactions amongst the four substrates in the protease production were studied in the
15 assays using a simplex-lattice mixture design (Table 1 and Table 3). The highest protease
activities were found using the medium containing wheat bran (1/2) and soybean meal (1/2) (run
5) and the formulation composed by the quaternary mixture of the substrates in equal proportions
(run15), reaching 262.78 and 245.97 U g-1
, respectively, after 48 h fermentation.
Synergistic and antagonistic effects between the different agroindustrial wastes in the
protease production were detected during all the fermentation time. The highest and similar
protease activities at 24 h fermentation were observed in runs 2 and 12, enabling the application
of isolated or mixture of substrates. A synergistic effect was detected in the medium composed of
wheat bran (1/8), soybean meal (5/8), cottonseed meal (1/8) and orange peel (1/8) (run 12),
resulting in increases of 30.5, 1.42, 99.4 and 224.8% of protease production as compared to the
individual substrates, respectively. At 48 h fermentation, the medium formulated with the binary
mixture of wheat bran (1/2) and cottonseed meal (1/2) (run 5) presented increases of 42.8 and
14.9% in protease production as compared to the individual substrates, respectively. The medium
composed by the four agroindustrial wastes in equal proportions (run 15) showed strong and
89
synergetic effects at 48 h fermentation, reaching increases of 33.7, 7.6, 30.8 and 581.7% and at
72 h reaching increases of 11.6, 131.4, 69.5 and 547.0%, respectively, in protease production as
compared to the individual substrates (Table 3).
The lowest values for protease activities were detected when orange peel was used as
isolated substrate, however, important synergistic effects were observed when combining it with
cottonseed meal. The protease production in cottonseed meal (run 3) and orange peel (run 4)
reached 117.17 and 30.70 U g-1
, respectively, while in the mixture of these two substrates in
equal proportions (run 10), the protease production reached 179.08 U g-1
at 72 h fermentation,
which represented increases of 52.8 and 483.3% in protease production as compared to the
individual substrates. This same formulation (run10) showed similar results at 96 h fermentation,
resulting in increases of 32.5 and 1,085% of the protease production as compared to the isolated
substrates (runs 3 and 4, respectively) (Table 3).
Antagonistic effects between the agroindustrial wastes were observed too, characterized by
the decrease in protease production when mixtures were used for fermentation. In general, the
combination of orange peel with wheat bran or soybean meal decreased the protease production.
For example, at 48 h fermentation, the protease production in the medium composed by wheat
bran (1/2) and orange peel (1/2) (run 7) was 99.75 U g-1
, while the production in wheat bran (run
1) and orange peel (run 4) as isolated substrates were 183.98 and 36.08 U g-1
, respectively.
Although, this result represents an increase in protease production compared to the assay
performed using orange peel as isolated substrate (run 4), a decrease of 45.8% in protease
production was observed compared to the fermentation using wheat bran in isolated form (run 1).
The same occurred in run 9 at 48 h, that presented a decrease of 71.4% in protease production for
the fermentation medium composed by soybean meal (1/2) and orange peel (1/2) as compared to
the assay performed using soybean meal (run 2) as an isolated substrate (Table 3).
The application of statistical mixture designs for enzymes production under solid state
fermentation is a scarce process described in the scientific literature. Some researchers used
predefined combinations of substrates to optimize enzyme production by microorganisms, so
there was no use of a statistical tool that allowed the construction of models and prediction of
responses at different substrate formulations. Chutmanop et al., (2008) studied the protease
production under solid state fermentation using a strain of A.oryzae (Ozykat-1) and reported a
90
protease production of 1,200 U g-1
within 96 h fermentation using a substrate mixture of 75% rice
bran and 25% wheat bran. Lazim et al., (2009) studied the production of thermophilic alkaline
protease by Streptomyces sp. CN902 using different agroindustrial residues individually or in
combination as the substrate under solid state fermentation. Different solid substrates such as
wheat bran, barley bran, rice bran, olive spinet, oats bran, chopped date stones and chopped dried
fish were tested. The results showed the binary mixture of wheat bran with chopped date stones
(5:5) proved to be the best as it gave the highest enzyme activity (90.5 U g−1
), which represented
increases of 21.5 and 30.2% when compared to individual substrates wheat bran (74.5 U g−1
) and
chopped date stones (69.5 U g−1
), respectively. Delabona et al., (2013) used the experimental
mixture design as a tool to enhance glycosyl hydrolases (xylanase, β-glucosidase and filter paper
activity) production by Trichoderma harzianum P49P11 under submerged fermentation. The
components studied were delignified steam-exploded bagasse, sucrose and soybean flour and
their combinations in the culture media. It was found that a mixed culture medium could
significantly maximize the enzymes production. These results corroborated with the present study
and showed that the statistical mixture design is an attractive process for find optimum
formulations and production of high amounts of enzymes.
3.3. Interpretation of contour plots
The variation of the amounts protease produced by A. niger LBA02 using different
agroindustrial wastes proportions is also shown using mixture contour plots, in which, each factor
(pure mixture component) is represented in a corner of an equilateral triangle; each point within
this triangle refers to a different proportion of components in the mixture (Figures 1 and 2). The
maximum percentage of each ingredient considered by the regression is placed at the
corresponding corner while the minimum is positioned at the middle of the opposite side of the
triangle. The center of the triangle represents the mixture in equal parts (Martinello et al., 2006).
A contour plot provides a two-dimensional view where all points that have the same response are
connected to produce contour lines of constant responses (Rao and Baral, 2011).
Figures 1 and 2 show the contour plots for protease production at 48 h fermentation
(maximum production) and for the runs selected to validation tests in each fermentation time,
respectively. It was observed profile changes in protease production in response to different
substrate formulations. The contour plots for 48 h fermentation indicated maximum responses in
91
three different formulations with predicted values above 260 U g-1
. In the medium contained the
ternary mixtures of wheat bran, soybean meal and cottonseed meal or wheat bran, soybean meal
and orange peel, the zones of maximum response variables were located towards the side of
triangle having mixtures of wheat bran and soybean meal as the substrates. This indicates that the
addition of wheat bran and soybean meal helps to improve the response variables whereas the
addition of orange peel has negative effects on the response variable. The addition of equal
proportions of wheat bran, cottonseed meal and orange peel helped to improve the response
variables, reaching values up to 260 U g-1
, as indicated by the zone of maximum protease activity
that was located in the center of the contour plot (Figure 1). From the contour plots for 48 h
fermentation, the protease production was decreased when the medium contained the ternary
mixture of soybean meal, cottonseed meal and orange peel, with a maximum predicted value of
180 U g-1
(Figure 1).
Figure 1 - Mixture contour plots for protease production by A. niger LBA02 at 48 h fermentation
as function of significant (p < 0.05) interaction effects of agroindustrial wastes proportions.
> 260 < 260 < 196 < 156 < 116 < 76 < 36
0.00
0.25
0.50
0.75
1.00
Orange
peel0.00
0.25
0.50
0.75
1.00
Wheat
bran
0.00 0.25 0.50 0.75 1.00
Cottonseed
meal
> 260 < 260 < 192 < 152 < 112 < 72 < 32
0.00
0.25
0.50
0.75
1.00
Orange
peel0.00
0.25
0.50
0.75
1.00
Wheat
bran
0.00 0.25 0.50 0.75 1.00
Soybean
meal
> 260 < 260 < 240 < 220 < 200 < 180
0.00
0.25
0.50
0.75
1.00
Cottonseed
meal0.00
0.25
0.50
0.75
1.00
Wheat
bran
0.00 0.25 0.50 0.75 1.00
Soybean
meal
> 220 < 220 < 152 < 112 < 72 < 32
0.00
0.25
0.50
0.75
1.00
Orange
peel0.00
0.25
0.50
0.75
1.00
Soybean
meal
0.00 0.25 0.50 0.75 1.00
Cottonseed
meal
92
Figure 2 shows the variation of the protease activity in the fermentations performed using
the formulations selected to validation tests. These assays were randomly selected and not
necessarily indicate the maximum protease production at the fermentation time. Two
formulations showed maximum protease production when equal proportions of soybean meal,
cottonseed meal and orange peel or wheat bran, cottonseed meal and orange peel were used as the
substrates, reaching values above 170 U g-1
at 24 h fermentation and above 180 U g-1
at 96 h
fermentation. At 48 h fermentation, the binary mixture of soybean meal and cottonseed meal
favoured the enzyme production, while at 72 h fermentation, the medium composed by
cottonseed meal and orange peel was more appropriate with predicted values above 150 U g-1
.
This can be verified by observing the mixture surface plots (Figure 2).
Figure 2 - Mixture contour plots for protease production by A. niger LBA02 during 24, 48, 72
and 96 h fermentation as function of significant (p < 0.05) interaction effects of agroindustrial
wastes proportions. These assays were randomly selected for validation tests.
> 260 < 260 < 192 < 152 < 112 < 72 < 32
0.00
0.25
0.50
0.75
1.00
Orange
peel0.00
0.25
0.50
0.75
1.00
Wheat
bran
0.00 0.25 0.50 0.75 1.00
Soybean
meal
> 170 < 170 < 144 < 124 < 104 < 84 < 64 < 44
0.00
0.25
0.50
0.75
1.00
Orange
peel0.00
0.25
0.50
0.75
1.00
Soybean
meal
0.00 0.25 0.50 0.75 1.00
Cottonseed
meal
> 170 < 170 < 152 < 132 < 112 < 92 < 72 < 52 < 32
0.00
0.25
0.50
0.75
1.00
Orange
peel0.00
0.25
0.50
0.75
1.00
Wheat
bran
0.00 0.25 0.50 0.75 1.00
Cottonseed
meal
> 180 < 180 < 136 < 96 < 56 < 16
0.00
0.25
0.50
0.75
1.00
Orange
peel0.00
0.25
0.50
0.75
1.00
Wheat
bran
0.00 0.25 0.50 0.75 1.00
Cottonseed
meal
24 h 48 h
72 h 96 h
93
3.4. Model fitting, regression analysis and validation tests
The response data based on the independent variables was obtained from the experiments
and recorded in Table 4. The experiments were conducted with triplicates and found that there
was good agreement between the replicates. All the independent and response variables were
fitted to special cubic models.
The coefficient of determination R2 and the F test (analysis of variance-ANOVA) were
used to verify the quality of fit of the models. Table 4 contains the models, corresponding R2
of
the regression equations for the responses as well as the corresponding F-ratio and p-values. The
high R2, which were above 0.90, indicate that all response functions adequately fit the
experimental data, and the models can be used for predictive purposes in the protease production
by A. niger LBA02 under solid state fermentation using different substrates and their mixtures.
As showed in Table 4, the predicted regression equations represent the models with the
significant factors for production protease at 24, 48, 72 and 96 h fermentation. The negative
quadratic (binary) and cubic (ternary) terms of fitted regression equation showed the antagonistic
effects as well the positive quadratic and cubic terms indicated synergistic effects of the
agroindustrial wastes on the protease production. The highest significant effects of the
independent variables showed changes in the profile during the fermentation time. In the first 48
h fermentation, the soybean meal (x2) exerted the highest significant effect on the protease
production followed by wheat bran (x1) at 24 h fermentation or cottonseed meal (x3) at 48 h
fermentation. On the other hand, after 72 and 96 h fermentation, the highest significant effect was
caused by wheat bran (x1), followed by cottonseed meal (x3), soybean meal (x2) and orange peel
(x4) (Table 4). At 24 h fermentation, the ternary interaction between soybean meal, cottonseed
meal and orange peel (x2x3x4) showed the highest positive significant effect on protease
production, while the interaction between wheat bran, cottonseed meal and orange peel (x1x3x4)
presented the highest negative significant effect. At 48 h fermentation, the ternary interaction of
wheat bran (x1), cottonseed meal (x3) and orange peel (x4) showed strong positive and significant
effect on protease production, while at 72 and 96 h fermentation, this effect was detected for the
mixture composed by soybean meal, cottonseed meal and orange peel (x2x3x4) (Table 4).
94
Table 4 - Analysis of variance (ANOVA) including models, R2 and probability values for the
final reduced models for protease production at 24, 48, 72 and 96 h fermentation.
*F-ratio = Fcalculated/Ftabulated
Response: protease production at 24 h fermentation
Source of variation Sum of
squares
Degrees of
freedom
Mean of
squares F-ratio
* R² p-value
Regression 26,255.46 11 2,386.86 57.12 0.97 <0.001
Residual 768.81 33 23.29
Total 27,024.27
Special cubic model: Y = 103.1x1 + 128.4x2 + 66.6x3 + 40.5x4 - 61.5x1x2 – 59.3x1x3 + 35.7x2x3 + 49.4x3x4 +
1,500.5x1x2x3 – 1,212.1x1x2x4 – 1,254.1x1x3x4 + 2,470.5x2x3x4
Response: protease production at 48 h fermentation
Source of variation Sum of
squares
Degrees of
freedom
Mean of
squares F-ratio R² p-value
Regression 146,303.9 7 20,900.55 59.94 0.95 <0.001
Residual 6,887.1 37 186.14
Total 153,191.0
Special cubic model: Y = 177.4x1 + 233.5x2 + 185.1x3 + 30.4x4 + 235.7x1x2 + 353.0x3x4 + 3,672.6x1x3x4 –
1,961.5x2x3x4
Response: protease production at 72 h fermentation
Source of variation Sum of
squares
Degrees of
freedom
Mean of
squares F-ratio R² p-value
Regression 84,089.51 8 10,511.19 58.04 0.96 <0.001
Residual 3,564.69 36 99.02
Total 87,654.20
Special cubic model: Y = 172.6x1 + 80.8x2 + 109.2x3 + 27.9x4 – 153.8x1x2 + 76.1x2x4 + 433.1x3x4 – 1,438.1x1x2x3
+ 5,249.0x2x3x4
Response: protease production at 96 h fermentation
Source of variation Sum of
squares
Degrees of
freedom
Mean of
squares F-ratio R² p-value
Regression 92,031.84 13 7,079.37 117.72 0.99 <0.001
Residual 1,073.36 31 34.62
Total 93,105.20
Special cubic model: Y = 184.5x1 + 64.1x2 + 125.6x3 + 14.4x4 – 260.6x1x2 – 73.2x1x3 + 94.5x1x4 + 45.3x2x3 +
131.5x2x4 + 386.8x3x4 – 9,431.2x1x2x3 + 2,286.7x1x2x4 + 1,038.7x1x3x4 + 4,815.7x2x3x4
95
Validation tests were performed to determine the accuracy of the polynomial models
obtained for protease production by A. niger LBA02 using different agroindustrial wastes and
their mixtures (Table 5).
Table 5 - Validation tests performed to determine the adequacy of the polynomial models
obtained for the protease production using agroindustrial wastes in different formulations.
Results are presented as the mean (n = 3) ± SD, and those with different letters are significantly different, with p < 0.05. RSD (%):
relative standard deviation. x1 – wheat bran; x2 – soybean meal; x3 – cottonseed meal; x4 – orange peel.
The validation tests were conducted in two ways: 1) assays randomly selected for each time
fermentation and 2) assays selected from the matrix of the statistical mixture design which the
protease production was maximum for each fermentation time. The tests were performed in
triplicate and the results were presented in Table 5. According to the regression models (Table 4),
the most of experimental values agreed with the values predicted by the models within a 95%
confidence interval, thereby confirming the validity of the models for the evaluated responses
(Table 5). Although the predicted value for maximum protease production at 72 h fermentation
did not agree with the experimental response (p < 0.05), the relative standard deviation (RSD)
was low and this model can be considered as predictive (Table 5).
Randomized tests used for models validation
Protease production Independent variables Predicted
response
Experimental
response
RSM
(%) x1 x2 x3 x4
24 h fermentation 0.000 0.333 0.333 0.333 179.08a 179.80 ± 5.55
a 0.40
48 h fermentation 0.000 0.333 0.333 0.333 188.66b 182.63 ± 5.38
b -3.30
72 h fermentation 0.333 0.000 0.333 0.333 151.16c 148.53 ± 8.92
c -1.77
96 h fermentation 0.333 0.000 0.333 0.333 191.67d 184.80 ± 5.02
d -3.93
Tests performed for maximum protease production
24 h fermentation 0.125 0.625 0.125 0.125 128.82e 130.25 ± 4.95
e 1.09
48 h fermentation 0.500 0.500 0.000 0.000 259.83f 258.98 ± 11.35
f -0.33
72 h fermentation 0.250 0.250 0.250 0.250 180.40g 195.65 ± 1.77
h 7.79
96 h fermentation 1.000 0.000 0.000 0.000 184.46i 181.68 ± 7.67
i -1.53
96
4. Conclusion
The results obtained in the present study suggested that the application of the statistical
mixture designs for protease production by A. niger LBA02 using different agroindustrial wastes
under solid state fermentation is an attractive method for improving the performance and to find
the optimum formulations. Binary mixtures containing wheat bran (1/2) and soybean meal (1/2)
resulted in maximal protease production during all fermentation time, reaching 262.7 U g-1
at 48
h fermentation. Increases ranging from 7.6 to 581.7% in protease production, compared to
individual substrates, were observed when quaternary mixtures of wheat bran, soybean meal,
cottonseed meal and orange peel in equal proportions were used as substrate at 48 h fermentation,
reaching a maximum protease production of 245.9 U g-1
. The process proposed in this study can
be extended to other enzymes groups produced by microorganisms, such as lipases, pectinases,
cellulases and invertases allowing the obtaining of multi-enzyme complexes in a simplified
combination of agroindustrial wastes with different characteristics for maximizing the enzymes
production using mixture designs.
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fermentation bioreactor with forced aeration for the production of hydrolases by Aspergillus
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production of protease and α-amylase under solid state fermentation using a simplex centroid
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Martinello, T., Kaneko, T.M., Velasco, M.V.R., Taqueda, M.E.S., Consiglieri, V.O., 2006.
Optimization of poorly compactable drug tablets manufactured by direct compression using the
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Pel, H. J. et al., 2007. Genome sequencing and analysis of the versatile cell factory Aspergillus
niger CBS 513.88. Nature Biotechnol., 25 (2), 221-231.
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metalloprotease from dry grass pea (Lathyrus sativus L.) seeds. Appl. Biochem. Biotechnol., 160,
63-71.
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biotechnological aspect of microbial proteases. Microbiol. Mol. Biol. Res., 62, 597–635.
Rao, P. V., Baral, S. S., 2011. Experimental design of mixture for the anaerobic co-digestion of
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Schuster, E., Dunn-Coleman, N., Frisvad, J.C., Van Dijck, P.W.M., 2002. On the safety of
Aspergillus niger – a review. Appl. Microbiol. Biotechnol., 59, 426–435.
Shivakumar, S., 2012. Production and characterization of an acid protease from a local
Aspergillus sp. by solid substrate fermentation. Archives Appl. Sci. Res., 4 (1), 188-199.
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99
Capítulo V: A new approach for proteases production by Aspergillus niger
based on the kinetic and thermodynamic parameters of the enzymes
obtained
Revista: Biocatalysis and Agricultural Biotechnology
100
Abstract
This study reports the proteases production by Aspergillus niger LBA02 under solid state
fermentation using different agroindustrial wastes and the variation of the biochemical properties
of these proteases in response to each substrate. The biochemical properties of the proteases
varied widely when produced in wheat bran (PWB), soybean meal (PSM), cottonseed meal
(PCM), orange peel (POP) and the quaternary mixture of them (PQM). The lower value for
activation energy (Ea) was detected for protease POP (16.32 kJ mol-1
) and the higher for protease
PQM (19.48 kJ mol-1
). The temperature quotient (Q10) values ranging from 1.20 to 1.28 at
temperatures between 35-55 °C. The higher Vmax/Km ratio was 562.79 U mL g-1
mg-1
for the
protease PSM. The order of thermal stability of the proteases at temperatures ranging from 40 to
60 °C as revealed from t1/2 and D values and thermodynamic parameters Ead (activation energy
for irreversible deactivation), ΔH (enthalpy), ΔG (Gibbs free energy) and ΔS (entropy) was:
PWB > PQM > POP > PSM > PCM. In the study of the substrate specificity, the best substrate
was hemoglobin from bovine blood. Our study provides a new point of view for proteases
production under solid state fermentation, which was possible to evaluate the most suitable
substrate for secretion of enzymes with more attractive characteristics based on their biochemical
properties, such as high thermal stability.
Keywords: protease; substrate specificities; thermodynamic and kinetic parameters.
101
1. Introduction
Proteases constitute one of the commercially important groups of extracellular microbial
enzymes, accounting for nearly 60% of the whole enzyme market and are frequently used in
detergent, leather, pharmaceuticals, food and biotechnology industries (Vijayaraghavan et al.,
2014). These enzymes are found in a wide diversity of sources such as plants, animals and
microorganisms. Among these sources, the microorganisms show great potential for protease
production due to their broad biochemical diversity and their susceptibility to genetic
manipulation. In addition, microbial proteases are predominantly extracellular and can be
secreted in the fermentation medium, decreasing the requirement of complex steps for enzyme
recovery (Muthulakshmi et al., 2011). It has been estimated that microbial proteases represent
approximately 40% of the total worldwide enzyme sales (Rao et al., 1998).
Several species of filamentous fungi have been exploited in industrial processes for the
production of metabolites and industrial enzymes. A. niger has a long tradition of safe use in the
production of enzymes and organic acids. Many of these products have listed as a ‘‘Generally
Recognized as Safe (GRAS)’’ by the US Food and Drug Administration (Schuster et al., 2002).
A. niger is one of the most important sources of fungal proteases. According Pel et al. (2007),
genome sequencing shows that A. niger has 198 proteins involved in proteolytic degradation
process.
In the past years, new and innovative biotechnological processes have explored solid state
fermentation (SSF) as a promising technology. For the growth of fungi, SSF is an attractive
process because the solid substrates resemble the natural habitat of the fungi and improving their
growth and the secretion of a wide range of extracellular enzymes. Some characteristics make
solid state fermentation more attractive than submerged fermentation: lower risk of
contamination, higher productivity, use of inexpensive substrates, simplicity on downstream
processing, easier separation and purification of products, lower energy requirements and lesser
production of wastewater (Chutmanop et al., 2008; Chen et al., 2014).
The biochemical characterization of enzymes is important to evaluate their
biotechnological potential. The study of the protease properties, such as the substrate specificity,
the optimum catalytic pH conditions, the temperature and stability profiles, and kinetic and
102
thermodynamic characteristics can be used to predict the successful application of the enzyme to
particular industries or processes (Castro and Sato, 2013).
Several studies use the high levels of production or productivity as a criterion for selecting
the most suitable substrate for obtaining of enzymes under solid state fermentation. However, the
expression and secretion of different sets of proteases and other enzymes, as well as their
biochemical properties, can be regulated by the type of substrate used as carbon and nitrogen
source (Speranza et al., 2011; Farnell et al., 2012). In this context, the main objectives of the
present study were to evaluate the proteases production by A. niger LBA02 under solid state
fermentation using different agroindustrial wastes and to determine the biochemical properties of
the proteases produced in each agroindustrial waste, with emphasis on the kinetic and
thermodynamic parameters and substrate specificities. This evaluation provides a new point of
view to select the most suitable substrate for proteases production under solid state fermentation.
2. Materials and Methods
2.1. Chemical composition of the agroindustrial wastes
Wheat bran, soybean meal and cottonseed meal were kindly provided by Bunge Foods
S/A. Orange peel was purchased from local market of Campinas (Sao Paulo, Brazil). To be used
as matrix support, the orange peel was grinded, washed three times with distilled water and dried
at 50 °C for 24-48 h.
Moisture, protein content, lipids and ash of the agroindustrial wastes were determined by
AOAC methods (AOAC, 2010). The carbohydrate content was determined by difference between
the total value of 100% and the sum of the other components. The tests were performed in
triplicate and the results were expressed as the mean ± standard deviation.
2.2. Microorganism culture
The microorganism used in this study was A. niger LBA02, previously selected as a
proteolytic strain from the culture collection of the Laboratory of Food Biochemistry, School of
Food Engineering, University of Campinas. The strain was periodically subcultured and
maintained on potato dextrose agar slants. To produce fungal spores, the microorganism was
inoculated into a medium composed of 10 g wheat bran and 5 mL of solution containing 1.7%
(w/v) NaHPO4 and 2.0% (w/v) (NH4)2SO4 and incubated for 3 days at 30 °C. The fungal spores
103
were dispensed into sterile Tween 80 solution (0.3%) to prepare the inoculum for fermentation.
The number of spores per milliliter in the spore suspension was determined with a Neubauer cell
counting chamber.
2.3. Protease production and sampling
The protease production was performed under solid state fermentation using the individual
substrates and the quaternary mixture of their in equal proportions in 250 mL Erlenmeyer flasks
containing 20 g medium. The cultivation parameters were 50% moisture, temperature set at
30 °C, and an inoculum level of 107 spores g
-1. The protease activity was tested at 24 h intervals
during a 96 h fermentation. The crude extract was obtained by the addition of 100 mL distilled
water. After 1h at rest, the solution was filtered through a filter membrane to obtain an enzyme
solution free of any solid material.
2.4. Determination of protease activity
The protease activity was measured using azocasein as the substrate according to Charney
and Tomarelli (1947) and described by Castro and Sato (2013). The reaction mixture containing
0.5 mL 0.5% (w/v) azocasein (Sigma), pH 5.0, and 0.5 mL of the enzyme solution was incubated
for 40 min. The reaction was stopped by adding 0.5 mL 10% TCA and the test tubes were
centrifuged at 17,000 x g for 15 min at 25 °C. A 1.0 mL aliquot of the supernatant was
neutralized with 1.0 mL 5 M KOH. One unit of enzyme activity (U) was defined as the amount of
enzyme required to increase the absorbance at 428 nm by 0.01 under the assay conditions
described.
2.5. Activation energy and temperature quotient (Q10)
The activation energy (Ea) was determined by incubating the protease with 0.5%
azocasein at various temperatures ranging from 40 to 60 °C in 50 mM acetate buffer (pH 5.0).
The dependence of the rate constants with temperature was assumed to follow the Arrhenius Law
and Ea was calculated from the slope of the plot of 1000/T vs. ln (protease activity), where
Ea = -slope×R, R (gas constant) = 8.314 J K-1
mol-1
and T is the absolute temperature in Kelvin
(K) (Jakób et al., 2010).
The effect of temperature on the rate of reaction was expressed in terms of temperature
quotient (Q10), which is the factor by which the rate increases due to a rise in the temperature by
104
10 °C. Q10 was calculated by the equation given by Dixon and Webb (1979), as shown in
Equation 1:
Q10 = antilogɛ (Ea × 10/RT2) (1)
2.6. Determination of the kinetic parameters Km and Vmax
Azocasein (pH 5.0) was used over the concentration ranges 1.0-10.0 mg mL-1
to
determine the kinetic parameters Km and Vmax of the proteases from A. niger LBA02. The
Michaelis-Menten constant (Km) and maximum velocity (Vmax) values were determined as the
reciprocal absolute values of the intercepts on the x and y axes, respectively, of the linear
regression curve.
2.7. Determination of kinetic and thermodynamic parameters for thermal inactivation
2.7.1. Kinetic parameters for thermal inactivation
The protease stability as a function of incubation time was evaluated. For this, the enzyme
was incubated for 300 min at temperatures ranging from 40 to 60 °C and the samples were
collected at various times for determination of the residual protease activity. The value of the
deactivation rate constant (kd) for the protease produced in different agroindustrial substrates,
expressed as an exponential decay, was found by plotting ln (A/A0) vs. time using the
experimental data as shown in Equation 2:
A = A0 × e-k
dt (2)
Where t is time, A0 is the initial enzyme activity and A is the enzyme activity at a determined
time t.
The activation energies for denaturation (Ead) of protease were calculated by plotting
ln (kd) vs. −1/RT as shown in Equation 3:
kd = Ae−Ead/RT
(3)
Where R is the universal gas constant = 8.314 J K-1
mol-1
and T is the absolute temperature in
Kelvin (K).
The apparent half-life of the enzyme, defined as the time where the residual activity
reaches 50%, was estimated as shown in Equation 4:
105
t1/2 = ln (0.5) / kd (4)
Decimal reduction time (D value) was defined as the time required for a one-log10
reduction or 90% reduction in the initial enzyme activity at a specific temperature. The D value is
related to the first-order deactivation rate constant (kd) and it was calculated as shown in Equation
5:
D = 2.303 / kd (5)
2.7.2. Thermodynamic parameters for thermal inactivation
Thermodynamic parameters for proteases produced in different agroindustrial substrates
were estimated using the Eyring absolute rate, as shown in Equation 6:
kd = (kB×T/h)×e(-ΔH/RT)
×e(ΔS/R)
(6)
Where, kB is the Boltzmann constant (1.38×10−23
J K-1
); T is the absolute temperature in Kelvin;
h is the Planck constant (6.63 × 10−34
J s); ΔH is the enthalpy of activation, kJ mol-1; and ΔS is
the entropy of activation, J/mol K. The enthalpy of activation, ΔH, given in Equation 7, can be
calculated using the activation energies for denaturation as shown in Equation 3.
Similarly, the free energy of activation, ΔG, can be calculated using Equation 8. Finally,
entropy of activation, ΔS, represented in Equation 9, can be calculated using the enthalpy (ΔH)
and free energies of activation (ΔG).
ΔH = Ead – RT (7)
ΔG = -RT ln [kd×h/kb×T] (8)
ΔS = (ΔH – ΔG)/T (9)
2.8. Substrate specificity of the proteases
The proteases produced by A. niger LBA02 in wheat bran, soybean meal, cottonseed
meal, orange peel and the quaternary mixture were assayed for substrate specificity by using
different substrates: casein, whey protein, soybean protein concentrate, soy protein isolate,
hemoglobin from bovine blood, gelatin and albumin from egg white. The enzyme concentrations
were adjusted to 20.0 U per mL of reaction, according to the activity of each protease, as
previously determined. The substrates were dissolved in 50 mM acetate buffer (pH 5.0) at the
concentration of 10 mg mL-1
. The reaction mixture containing 1.0 mL of each substrate and
106
1.0 mL of the enzyme solution was incubated at 50 °C for 60 min. The reaction was stopped by
adding 1.0 mL 10% TCA. The test tubes were centrifuged at 17,000 x g for 15 min at 5 °C and
the absorbance of the supernatant was measured at 280 nm. The results were expressed as relative
activity (%) using the substrate casein as the standard (100% relative activity).
2.9. Calculations and statistics
Values were expressed as the arithmetic mean. The Tukey test was used to check the
significant differences between the groups analyzed. The differences were considered significant
when p-value ≤ 0.05.
Pearson correlation coefficient was used to measure the strength of linear dependence
between two responses. The correlation coefficient ranges from – 1 to 1. A value of 1 implies that
a linear equation describes the relationship between the responses was perfectly and positive,
while a value of -1 indicate a perfectly and negative correlation. A value of 0 implies that there is
no linear correlation between the responses. The correlations between analyzed parameters were
considered significant when the p-value ≤ 0.10.
3. Results and Discussion
3.1. Chemical composition of the agroindustrial wastes
The centesimal compositions of the agroindustrial wastes used as fermentation substrates
for production of protease by A. niger LBA02 under solid state fermentation are showed in Table
1. The enzymes production under solid state fermentation can be affected by the composition of
the substrates and various cultivation factors. On protease production, for example, the presence
of protein sources can induce the enzyme secretion by the microorganism. On the other hand, the
substrate must have a carbon to nitrogen ratio (C:N) suitable for the fermentation (Castro and
Sato, 2013). Soybean meal and cottonseed meal were the materials with higher protein content
and wheat bran showed the major C:N ratio (Table 2).
107
Table 1 – Average values of the centesimal composition (%) of the agroindustrial wastes used for
protease production by A. niger LBA02 under solid state fermentation.
Results are presented as the mean (n = 3) ± SD, and those with different letters are significantly different, with p < 0.05. Tukey
tests were applied between the chemical components of each substrate (not between different substrates). Carbohydrate content
(%) was measured by difference between the total value of 100% and the sum of the other components.
Table 2 - Correlation analysis between the ratio (C:N) and the protein content of the
agroindustrial wastes in dry basis with the protease production by A. niger LBA02 under solid
state fermentation at 24, 48, 72 and 96 h.
Results are presented as the mean (n = 3) ± SD, and those with different letters are significantly different, with p < 0.05. Tukey
tests were applied between the runs for each fermentation time (not between different fermentation time). *The correlations
between analyzed parameters were considered significant when the p-value ≤ 0.10.
The Pearson coefficient was used to verify the correlation between the C:N ratio and the
protein content in the substrates with the protease production. The correlation analysis indicated a
positive and significant correlation between the protein content (%) in the substrates and the
protease production at 24 h (Pearson coefficient = 0.80; p = 0.10). In contrast, it was observed a
negative and significant correlation between the C:N ratio and the protease production at 24 h
(Pearson coefficient = -0.80; p = 0.10) and 48 h fermentation (Pearson coefficient = -0.96;
Chemical components Wheat bran Soybean meal Cottonseed meal Orange peel
Moisture (%) 12.77 ± 0.08a 11.93 ± 0.02
a 6.42 ± 0.01
a 7.92 ± 0.08
a
Protein (%) 14.74 ± 0.51b 49.24 ± 0.07
b 25.91 ± 0.60
b 7.01 ± 0.08
b
Carbohydrates (%) 63.04c 31.53
c 55.80
c 79.68
c
Lipids (%) 4.47 ± 0.22d 1.40 ± 0.02
d 7.83 ± 0.01
d 1.95 ± 0.13
d
Ash (%) 4.98 ± 0.06e 5.90 ± 0.04
e 4.04 ± 0.01
e 3.44 ± 0.11
e
Substrates C:N Protein
content (%)
Protease production (U g-1
)
24 h 48 h 72 h 96 h
Wheat bran 4.28 16.89 101.10 ± 5.73a 183.98 ± 5.65
b 178.00 ± 9.17
b 184.08 ± 6.84
a
Soybean meal 0.64 55.91 130.10 ± 3.45b 228.60 ± 7.30
a 85.85 ± 3.10
c 63.77 ± 1.70
b
Cottonseed meal 2.15 27.69 66.18 ± 1.05c 188.03 ± 7.65
b 117.17 ± 7.18
d 125.20 ± 2.28
c
Orange peel 11.37 7.61 40.62 ± 4.54d 36.08 ± 3.33
c 30.70 ± 3.40
e 14.00 ± 1.64
d
Quaternary mixture 2.35 27.03 99.70 ± 1.49a 245.97 ± 13.35
a 198.63 ± 5.32
a 91.13 ± 2.48
e
Correlation analysis between the protease production and C:N
Pearson coefficient -0.80* -0.96
* -0.56 -0.48
p-value 0.10 0.01 0.32 0.42
Correlation analysis between the protease production and the protein content (%)
Pearson coefficient 0.80* 0.70 0.03 -0.05
p-value 0.10 0.19 0.96 0.94
108
p = 0.01) (Table 2). These results confirm that an adequate supply of proteins as nitrogen source
can induce the protease production at the first hours of fermentation.
Several studies describe the use of agroindustrial wastes as potent substrates for the
production of proteases by filamentous fungi of the genus Aspergillus (Esparza et al., 2011; Leng
and Xu, 2011). It is important to note that a standard assay is essential for comparing the results
of different studies. In several studies, research groups used different methodologies to determine
the protease activities, which may result in differences in the substrates, incubation times, pH and
temperatures of the reaction mixtures. The experimental data variability complicates the
comparisons among different studies. As such, a report of higher protease activities values does
not necessarily suggest a higher production. Negi and Banerjee (2006) observed maximum yields
of protease production by a strain of A. awamori MTCC 6652 using wheat bran as a substrate
under solid state fermentation. The highest secretion of protease was measured to be 1,930 U g-1
.
Chutmanop et al. (2008) studied the protease production under solid state fermentation using
strain of A. oryzae (Ozykat-1) and reported a protease production of ∼1,200 U g−1
within 96 h
fermentation using a substrate mixture of 75% rice bran and 25% wheat bran. Shivakumar (2012)
screened 11 different substrates, including eight cereals and three agroindustrial residues, for
protease production by Aspergillus sp. under solid state fermentation and found that wheat flour,
wheat bran and soy flour proved superior protease production, reaching activities of 320, 280 and
160 U g-1
, respectively.
3.2. Biochemical properties of the proteases from A. niger LBA02
3.2.1. Activation energy and temperature quotient (Q10)
The influence of temperature on activity of the proteases produced in different
agroindustrial wastes were shown in Fig. 1. Accordingly, the proteases exhibited optimal activity
at 50 °C, except the protease POP, which presented maximum activity in a range of temperatures
between 50 and 55 °C. However, a rapid loss of activity was observed over 55 °C.
The activation energies of the proteases were calculated at temperatures between 35 and
65 °C. The Arrhenius plots in temperature range from 35 °C to up to the optimum reaction
temperatures, 55 °C for protease POP and 50 °C for other proteases, showed a linear variation
with temperature increase, suggesting that the proteases from A. niger LBA02 have single
conformations up to the transition temperatures (Fig. 2). Based on Arrhenius plots, inflection
109
points were observed in temperature range from 35 °C to up to the optimum reaction
temperatures and deflections above these points, indicating that catalysis reactions suppress
enzymatic deactivation below the inflection points. Thus, Ea presented positive values at
temperatures ranging from 35 °C to up to the optimum temperature for activity of each enzyme.
The lower Ea value was detected for protease POP (16.32 kJ mol-1
) and the higher for protease
PQM (19.48 kJ mol-1
). Negative Ea values were observed above the optimum temperatures for
activity (Table 3). Melikoglu et al. (2013) reported similar results for a protease from Aspergillus
awamori, which presented activation energies (Ea) for bread protein hydrolysis of 36.8 kJ mol-1
in the temperature range from 30 to 55 °C and − 62.0 kJ mol-1
in the temperature range from 55
to 65 °C.
Fig. 1. Effect of reaction temperature, between 35 and 65 °C with +5 °C increments, on enzyme
activities of the proteases from A. niger LBA02 produced under solid state fermentation using
wheat bran (PWB), soybean meal (PSM), cottonseed meal (PCM), orange peel (POP) and the
quaternary mixture of these agroindustrial wastes (PQM).
The effect of temperature on rate of reaction was measured in terms of temperature
quotient (Q10). The Q10 values ranging from 1.20 to 1.23 between temperatures 35-55 °C for
protease POP, and other proteases showed Q10 values ranging from 1.22 to 1.28 at temperatures
between 35-50 °C (Table 3).
0
50
100
150
200
250
35 40 45 50 55 60 65
Pro
teas
e (U
g-1
)
Temperature ( C)
PWB PSM PCM POP PQM
110
Fig. 2. Arrhenius plots for the determination of activation energies (Ea) of the proteases from A.
niger LBA02 produced under solid state fermentation using wheat bran (PWB), soybean meal
(PSM), cottonseed meal (PCM), orange peel (POP) and the quaternary mixture of these
agroindustrial wastes (PQM).
3.08 3.12 3.16 3.20 3.24 3.28
1000/T (K)
4.7
4.8
4.9
5.0
5.1
ln (
Vm
ax)
3.08 3.12 3.16 3.20 3.24 3.28
1000/T (K)
4.9
5.0
5.1
5.2
5.3
ln (
Vm
ax)
3.08 3.12 3.16 3.20 3.24 3.28
1000/T (K)
4.7
4.8
4.9
5.0
5.1
ln (
Vm
ax)
3.00 3.04 3.08 3.12 3.16 3.20 3.24 3.28
1000/T (K)
3.0
3.1
3.2
3.3
3.4
3.5
ln (
Vm
ax)
3.08 3.12 3.16 3.20 3.24 3.28
1000/T (K)
5.0
5.1
5.2
5.3
5.4
ln (
Vm
ax)
PWB PSM
PCM POP
PQM
111
Table 3 - Activation energies for azocasein hydrolysis and Q10 of the proteases from A. niger
LBA02 produced under solid state fermentation of wheat bran (PWB), soybean meal (PSM),
cottonseed meal (PCM), orange peel (POP) and the quaternary mixture of these substrates in
equal proportions (PQM).
3.2.2. Kinetic parameters Km and Vmax
Enzyme kinetics parameters Km and Vmax were calculated from the Lineweaver-Burk
graphs for the proteases form A. niger LBA02 produced in different agroindustrial wastes and are
presented in Table 4. The Km value for a given enzyme provides an indication of the binding
strength of that enzyme to its substrate, thus, a low Km indicates a higher affinity for the
substrate. The Vmax can be defined as the maximum velocity as the total amount of enzyme
participates in the reaction. This measurement is theoretical and has an approximate value
because at given time, it would require all enzyme molecules to be tightly bound to their
substrates (Bisswanger, 2002; Goyeneche et al., 2013).
The proteases from A. niger LBA02 showed different values for Km and Vmax in
response to the agroindustrial wastes used as the substrates for enzyme production under the solid
Temperature range (°C) PWB
Ea (kJ moL-1
) R² Q10
35-50 17.33 0.99 1.25-1.22
50-65 -63.23 0.96
Temperature range (°C) PSM
Ea (kJ moL-1
) R² Q10
35-50 19.44 0.93 1.28-1.25
50-65 -67.53 0.98
Temperature range (°C) PCM
Ea (kJ moL-1
) R² Q10
35-50 18.38 0.96 1.26-1.24
50-65 -68.19 0.99
Temperature range (°C) POP
Ea (kJ moL-1
) R² Q10
35-55 16.32 0.92 1.23-1.20
55-65 -111.60 0.96
Temperature range (°C) PQM
Ea (kJ moL-1
) R² Q10
35-50 19.48 0.97 1.28-1.25
50-65 -70.28 0.99
112
state fermentation. The greatest affinity for the substrate azocasein was observed for PSM, with
Km value estimated at 0.44 mg mL-1
, followed by PCM, PWB, PQM and POP. The maximum
reaction rate (Vmax) value was 344.83 U g-1
for protease PQM (Table 4). Vmax/Km ratio was
taken as the criterion to evaluate substrates specificity (Altunkaya and Gokmen, 2008). The
higher Vmax/Km ratio was 562.79 U mL g-1
mg-1
for the protease PSM, followed by the
proteases PCM and PQM, which showed values of 225.45 and 212.85 U mL g-1
mg-1
(Table 4).
Table 4 - Kinetic parameters Km and Vmax for the proteases from A. niger LBA02 produced
under solid state fermentation of wheat bran (PWB), soybean meal (PSM), cottonseed meal
(PCM), orange peel (POP) and the quaternary mixture of these substrates in equal proportions
(PQM).
*Protease activity determined using azocasein as the substrate at 50 °C and pH 5.0.
3.2.3. Thermal inactivation
The residual protease activities after treatment at different temperatures are presented in
Fig. 3. It can be observed that the deactivation rates of the proteases depend on the substrate in
which they were produced (Table 5). The proteases from A. niger LBA02 produced in wheat bran
(PWB), orange peel (POP) and the quaternary mixture of substrates (PQM) showed higher
stability in temperatures ranging from 40 to 50 °C, retaining above 70% of the initial activity
after 30 min incubation, but they lose 50-65% of their original activities after 15 min of
incubation at 55 °C. The proteases produced using soybean meal (PSM) and cottonseed meal
(PCM) as substrates presented low stability, reducing about 70% of initial activity in the first
minutes of the heat treatment at 40 °C and up to 90% at temperatures ranging from 55 to 60 °C
(Fig. 3). These data were used to estimate the kinetic and thermodynamic parameters for thermal
inactivation of the proteases using Arrhenius plots (Fig. 4).
Protease Km (mg mL-1
) Vmax (U g-1
) R² Vmax / Km (U mL g-1
mg-1
)
PWB 1.32 248.65 0.98 188.37
PSM 0.44 247.63 0.99 562.79
PCM 1.05 236.70 0.99 225.43
POP 1.92 42.74 0.97 22.26
PQM 1.62 344.83 0.98 212.85
113
Fig. 3. Thermal deactivation of proteases from A. niger LBA02 produced under solid state
fermentation using wheat bran (PWB), soybean meal (PSM), cottonseed meal (PCM), orange
peel (POP) and the quaternary mixture of these agroindustrial wastes (PQM).
0
20
40
60
80
100
0 30 60 90 120
Res
idu
al a
ctiv
ity (
%)
Time (min)
40°C 45°C 50°C 55°C 60°C
0
20
40
60
80
100
0 30 60 90 120
Res
idu
al a
ctiv
ity (
%)
Time (min)
40°C 45°C 50°C 55°C 60°C
0
20
40
60
80
100
0 30 60 90 120
Res
idu
al a
ctiv
ity (
%)
Time (min)
40°C 45°C 50°C 55°C 60°C
0
20
40
60
80
100
0 30 60 90 120
Res
idu
al a
ctiv
ity (
%)
Time (min)
40°C 45°C 50°C 55°C 60°C
0
20
40
60
80
100
0 30 60 90 120
Res
idu
al a
ctiv
ity (
%)
Time (min)
40°C 45°C 50°C 55°C 60°C
PWB PSM
PCM POP
PQM
114
Table 5 - Thermodynamic and kinetic parameters for thermal deactivation of proteases from A.
niger LBA02 produced under solid state fermentation of wheat bran (PWB), soybean meal
(PSM), cottonseed meal (PCM), orange peel (POP) and the quaternary mixture of these substrates
in equal proportions (PQM).
Temperature (°C) PWB
kd (min-1
) t1/2 (min) D (min) R²
Ead (kJ moL-1
) 40 0.0005 1386.29 4605.20 0.95
45 0.0016 433.22 1439.13 0.95
50 0.0051 135.91 451.49 0.94
197.08 55 0.0160 43.32 143.91 0.84
60 0.0463 14.97 49.73 0.97
Temperature (°C) PSM
kd (min-1
) t1/2 (min) D (min) R²
Ead (kJ moL-1
) 40 0.0126 55.01 182.75 0.80
45 0.0162 42.79 142.14 0.89
50 0.0234 29.62 98.40 0.85
74.20 55 0.0401 17.29 57.42 0.90
60 0.0684 10.13 33.66 0.97
Temperature (°C) PCM
kd (min-1
) t1/2 (min) D (min) R²
Ead (kJ moL-1
) 40 0.0124 55.90 185.69 0.77
45 0.0181 38.30 127.22 0.85
50 0.0248 27.95 92.85 0.88
69.21 55 0.0476 14.56 48.37 0.95
60 0.0562 12.33 40.97 0.88
Temperature (°C) POP
kd (min-1
) t1/2 (min) D (min) R²
Ead (kJ moL-1
) 40 0.0019 364.81 1211.89 0.94
45 0.0053 130.78 434.45 0.98
50 0.0067 103.45 343.67 0.97
107.92 55 0.0122 56.82 188.74 0.97
60 0.0281 24.67 81.94 0.99
Temperature (°C) PQM
kd (min-1
) t1/2 (min) D (min) R²
Ead (kJ moL-1
) 40 0.0011 630.13 2093.27 0.92
45 0.0023 301.37 1001.13 0.96
50 0.0086 80.60 267.74 0.98
178.48 55 0.0335 20.69 68.73 0.97
60 0.0491 14.12 46.90 0.97
115
Fig. 4. Pseudo-first-order plots for irreversible thermal denaturation of proteases from A. niger
LBA02 produced under solid state fermentation using wheat bran (PWB), soybean meal (PSM),
cottonseed meal (PCM), orange peel (POP) and the quaternary mixture of these agroindustrial
wastes (PQM).
-2
-1
0
1
2
3
4
5
0 15 30 45 60 75 90 105 120
ln (
Ut/
U0)
Time (min)
40°C 45°C 50°C 55°C 60°C
-5
-4
-3
-2
-1
0
1
2
3
4
5
0 15 30 45 60 75 90 105 120
ln (
Ut/
U0)
Time (min)
40°C 45°C 50°C 55°C 60°C
-4
-3
-2
-1
0
1
2
3
4
5
0 15 30 45 60 75 90 105 120
ln (
Ut/
U0)
Time (min)
40°C 45°C 50°C 55°C 60°C
1
2
3
4
5
0 15 30 45 60 75 90 105 120
ln (
Ut/
U0)
Time (min)
40°C 45°C 50°C 55°C 60°C
-2
-1
0
1
2
3
4
5
0 15 30 45 60 75 90 105 120
ln (
Ut/
U0)
Time (min)
40°C 45°C 50°C 55°C 60°C
PWB PSM
PCM POP
PQM
116
The half-life (t1/2) of an enzyme, at a given temperature, is the time it takes for the activity
to reduce to a half of its original/initial activity. The decimal reduction time (D value) is defined
as the time required for a 90% reduction in the initial enzyme activity. Higher values of these
parameters at the specific operating temperature are important and desirable for industrial
applications since indicate the resistance of the enzyme to thermal inactivation. The protease
PWB showed the highest thermal resistance when compared to the other proteases preparations,
reaching D values ranging from 4,605.20 to 49.73 min, t1/2 ranging from 1,386.29 to 14.97 min at
temperatures between 40 and 60 C. It’s important to note that the protease PWB showed the
highest thermal resistance at the optimum temperature for activity (50 °C), presenting D value
and t1/2 estimated in 451.49 and 135.91 min, respectively. It can be seen that the inactivation rate
constants (kd) increased with increased temperature for all proteases. The kd values ranged from
slowest for protease PWB of 5×10-3
min-1
at 40 °C to fastest for protease PSM of 0.0684 min-1
at
60 °C (Table 4). The Ead for proteases deactivation were calculated using Arrhenius plots (Fig. 5)
and showed values in the order of PCM < PSM < POP < PQM < PWB, indicating thermal
stability in reverse order (Table 5). A neutral protease produced by Aspergillus oryzae CICIM
F0899 was kinetically characterized and the results showed half-lives (t1/2) of 20.4 and 14.2 min
at 55 and 60 °C, respectively (Wang et al., 2013). Sant’Anna et al. (2013) studied the kinetic
modeling of thermal inactivation of a protease from Bacillus sp. and showed D values of 432.54,
131.41, 17.98 and 7.82 min at 45, 50, 55 and 65 °C, respectively.
The stability of a protein is the result of a balance between stabilizing and destabilizing
forces, which are influenced by hydrophobic and electrostatic interactions, hydrogen and
disulfide bonds and folding degree of the molecule (Ortega et al., 2004). Thus, the investigation
of thermodynamic parameters such as enthalpy (ΔH), entropy (ΔS) and free energy (ΔG) of the
proteases from A. niger LBA02 was performed to understand the behavior of these molecules in
different conditions and the results are given in Table 6. These thermodynamic parameters varied
widely when the proteases produced in different agroindustrial wastes were compared.
117
Fig. 5. Arrhenius plots to calculate activation energy ‘Ea(d)’ for irreversible thermal
inactivation/denaturation of proteases from A. niger LBA02 produced under solid state
fermentation using wheat bran (PWB), soybean meal (PSM), cottonseed meal (PCM), orange
peel (POP) and the quaternary mixture of these agroindustrial wastes (PQM).
3.00 3.05 3.10 3.15 3.20
1000/T (K)
-4.4
-4.0
-3.6
-3.2
-2.8
ln (
kd)
3.00 3.05 3.10 3.15 3.20
1000/T (K)
-4.4
-4.0
-3.6
-3.2
-2.8
ln (
kd)
3.00 3.05 3.10 3.15 3.20
1000/T (K)
-6.5
-6.0
-5.5
-5.0
-4.5
-4.0
-3.5
-3.0
ln (
kd)
3.00 3.05 3.10 3.15 3.20
1000/T (K)
-7.0
-6.5
-6.0
-5.5
-5.0
-4.5
-4.0
-3.5
-3.0
-2.5
ln (
kd)
3.00 3.05 3.10 3.15 3.20
1000/T (K)
-8.0
-7.5
-7.0
-6.5
-6.0
-5.5
-5.0
-4.5
-4.0
-3.5
-3.0ln
(k
d)
PWB PSM
PCM POP
PQM
118
Table 6 - Thermodynamic parameters for thermal deactivation of proteases from A. niger LBA02
produced under solid state fermentation of wheat bran (PWB), soybean meal (PSM), cottonseed
meal (PCM), orange peel (POP) and the quaternary mixture of these substrates in equal
proportions (PQM).
Temperature (°C) PWB
ΔH (kJ moL-1
) ΔG (kJ moL-1
) ΔS (J moL-1
K-1
)
40 194.48 107.28 278.45
45 194.43 105.95 278.12
50 194.39 104.55 278.02
55 194.35 103.09 278.11
60 194.31 101.76 277.80
Temperature (°C) PSM
ΔH (kJ moL-1
) ΔG (kJ moL-1
) ΔS (J moL-1
K-1
)
40 71.60 98.87 -87.09
45 71.55 99.83 -88.87
50 71.51 100.45 -89.55
55 71.47 100.58 -88.70
60 71.43 100.68 -87.80
Temperature (°C) PCM
ΔH (kJ moL-1
) ΔG (kJ moL-1
) ΔS (J moL-1
K-1
)
40 66.61 98.91 -103.16
45 66.56 99.53 -103.61
50 66.52 100.30 -104.52
55 66.48 100.11 -102.48
60 66.44 101.22 -104.40
Temperature (°C) POP
ΔH (kJ moL-1
) ΔG (kJ moL-1
) ΔS (J moL-1
K-1
)
40 105.32 103.80 4.84
45 105.27 102.79 7.82
50 105.23 103.81 4.39
55 105.19 103.83 4.16
60 105.15 103.14 6.04
Temperature (°C) PQM
ΔH (kJ moL-1
) ΔG (kJ moL-1
) ΔS (J moL-1
K-1
)
40 175.88 105.22 225.62
45 175.83 104.99 222.66
50 175.79 103.14 224.82
55 175.75 101.07 227.58
60 175.71 101.59 222.47
119
ΔH is seen as a measure of the number of non-covalent bounds broken in forming a
transition state for enzyme inactivation. In general, large values of ΔH are associated with
increased enzyme stability (Olusesan et al., 2011; Batista et al., 2014). ΔH showed the lowest
value (66.44 kJ mol-1
) at 60 °C for protease PCM and the highest (194.48 kJ mol
-1) for protease
PWB at 40 C. Gibbs free energy (ΔG) measures the spontaneity of a reaction. Therefore, the
protein stability is directly related to ΔG values, where high ΔG values indicate higher thermal
stability of the enzyme (Batista et al., 2014). The higher ΔG values were observed for protease
PWB, which presented ΔG of 107.28 kJ mol-1
at 40 °C and 101.76 kJ mol-1
at 60 °C, followed by
proteases PQM and POP (Table 5). ΔS represent the variation in the extent of local disordering
between transition state and the ground state (Subhedar and Gogate, 2014). Thus, an increase in
ΔS implies an increase in the number of protein molecules in the transition active state and
increase in disorder (of the active site or of the structure), which is the main driving force of heat
denaturation (Singh and Chhatpar, 2011; Melikoglu et al., 2013). According to Olusesan et al.
(2011), positive ΔS values are found if the rate-limiting reaction is the protein unfolding, as result
of moderately high values of ΔH and low values of ΔG. On the other hand, negative ΔS values
are result of moderately low values of ΔH and high values of ΔG, which is in well agreement
with the present study. The proteases PSM and PCM presented negative values for ΔS, which
indicate that the rate-limiting reaction probably involves the aggregation of partially unfolded
enzyme molecules which predominate during the exposure of protein to high temperatures
(Olusesan et al., 2011).
3.2.4. Substrate specificity of the enzyme
The activities of the proteases from A. niger LBA02 produced in wheat bran (PWB),
soybean meal (PSM), cottonseed meal (PCM), orange peel (POP) and the quaternary mixture of
these substrates (PQM) against various proteinaceous substrates were examined (Table 7). PWB,
PSM and PCM showed a high level of catalytic activity against all substrates evaluated, with
relative activities superior to casein, used as standard (100% relative activity). However, the
protease POP presented the lower proteolytic activities against the substrates, reaching a
maximum relative activity of 83.32% for hemoglobin from bovine blood and a minimum value of
22.39% for soy protein concentrate. It can be noted that the substrate specificity demonstrated
different values in response to the different agroindustrial wastes used for protease production.
The use of quaternary mixture of agroindustrial wastes for enzymes production resulted in
120
proteases with higher catalytic activities for the substrates hemoglobin from bovine blood, gelatin
and egg albumin compared to the proteases obtained by fermentation of the isolated
agroindustrial wastes. The best substrate for the proteases was hemoglobin from bovine blood
with the highest relative activities of 183.84, 147.06, 186.81, 83.32 and 496.47% for PWB, PSM,
PCM, POP and PQM, respectively (Table 7).
Table 7 - Substrate specificity of the proteases from A. niger LBA02 produced under solid state
fermentation using wheat bran (PWB), soybean meal (PSM), cottonseed meal (PCM), orange
peel (POP) and the quaternary mixture of these agroindustrial wastes (PQM).
Results are presented as the mean (n = 3) ± SD, and those with different letters are significantly different, with p < 0.05. Tukey
tests were applied between the relative activities of substrates for each protease preparation (not between different proteases).
Yossan et al. (2006) reported that cytochrome C, soybean protein isolate and casein were
good substrates for protease from Bacillus megaterium with the relative protease activity of 114,
109 and 100%, respectively. A protease from Aspergillus sp. showed relative protease activity of
130, 121 and 114% for gelatin, casein and egg albumin, respectively, when bovine serum
albumin was used as control (100%) (Shivakumar et al., 2012).
4. Conclusions
The results obtained in our study showed that the protease production by A. niger
LBA02 and the biochemical properties of these proteases can be regulated by the agroindustrial
waste used as the substrate in solid state fermentation. Higher levels of protein in the
agroindustrial wastes showed as important factor, inducing the protease production in the first 24
h of fermentation. Kinetic and thermodynamic parameters indicated that the enzymes showed
different profiles for thermal inactivation, where the proteases produced in wheat bran (PWB)
Substrate Relative activity (%)
PWB PSM PCM POP PQM
Casein 100.00 ± 4.37a 100.00 ± 6.39a 100.00 ± 1.33a 100.00 ± 3.01a 100.00 ± 8.88a
Whey protein 106.26 ± 0.36b 102.21 ± 2.60a 108.79 ± 4.63b, e 57.99 ± 0.27b 96.83 ± 2.66a
Soy protein concentrate 126.26 ± 9.08c, d, f 105.88 ± 6.11a, b 108.79 ± 2.05b 22.39 ± 2.24c 30.69 ± 1.84b
Soy protein isolate 126.26 ± 2.79c 101.47 ± 3.39a 106.59 ± 3.66b 42.08 ± 2.75d 37.04 ± 5.52b
Hemoglobin from
bovine blood 183.84 ± 2.22e 147.06 ± 2.97c 186.81 ± 1.50d 83.32 ± 7.04e 496.47 ± 3.58c
Gelatin 115.15 ± 5.47d 114.71 ± 2.22b 114.29 ± 0.81e 54.98 ± 3.37b 179.89 ± 4.76d
Egg albumin 137.37 ± 3.42f 112.50 ± 1.77b 127.47 ± 2.12f 50.42 ± 8.04b, d 215.17 ± 2.41e
121
and using the quaternary mixture of the substrates (PQM) presented the most thermal resistance,
while the protease produced in cottonseed meal (PCM) had the lowest thermal resistance. The
protease produced using orange peel as the substrate (POP) showed the lowest value for
activation energy, indicating that there was a lower energy requirement for azocasein hydrolysis.
The proteases produced in different substrates also exhibit large differences for the kinetic
parameters Km and Vmax and substrate specificities. Our study showed interesting results about
the secretion of proteases by A. niger LBA02 in response to different agroindustrial wastes,
providing a new point of view for enzymes production under solid state fermentation, such as
selecting of the most suitable substrate for obtaining enzymes with more attractive properties.
Acknowledgements
The work described in this paper was substantially supported by the Department of Food
Science, School of Food Engineering, University of Campinas, which are gratefully
acknowledged. Acknowledgements to the National Counsel of Technological and Scientific
Development – CNPq by the granting of scholarship.
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125
Capítulo VI: Production, biochemical properties of proteases secreted by
Aspergillus niger under solid state fermentation in response to different
agroindustrial substrates and their application for production of whey
protein hydrolysates with antioxidant activities
Revista: Biocatalysis and Agricultural Biotechnology
126
Abstract
This study reports the proteases production by Aspergillus niger LBA02 under solid state
fermentation (SSF) using different agroindustrial wastes as substrates and the correlation between
the protease production and some physical-chemical parameters. The biochemical properties of
the proteases produced in each substrate and their application in enzymatic hydrolysis of bovine
whey protein for obtaining antioxidant hydrolysates were further investigated. The highest
protease production was obtained using wheat bran as the substrate at 96 h fermentation. The
results for chemical composition showed that the substrates with higher protein content induced
the protease production at the first 48 h of fermentation. The crude extracts of proteases from A.
niger LBA02 produced in wheat bran (PWB), soybean meal (PSM) and cottonseed meal (PCM)
showed different biochemical properties. The biochemical characterization showed that the
enzymes were most active over the pH range 3.0-4.0 and was stable from pH 2.5-4.5. The
optimum temperature for activity was approximately 50 °C, and the enzymes were stable at 40-
50 °C. The PWB showed higher ratio milk-clotting/protease activities (15.24) compared to PSM
(0.38) and PCM (6.28). Bovine whey protein hydrolysates showed different antioxidant activities
in response to each protease. The highest DPPH radical scavenging was observed for PCM
hydrolysates while PWB hydrolysates showed maximum activity in total antioxidant capacity
assay.
Keywords: protease; solid state fermentation; agroindustrial wastes; biochemical properties;
enzymatic hydrolysis; antioxidant activities.
127
1. Introduction
Proteases are multifunctional enzymes accounting for nearly 60% of the whole enzyme
market and are frequently used in detergent, leather, pharmaceuticals, food and biotechnology
industries (Ramakrishna et al., 2010; Yin et al., 2013). They can be isolated from plants, animals
and microorganisms. Of these sources, the microorganisms show great potential for protease
production due to their broad biochemical diversity and their susceptibility to genetic
manipulation. It has been estimated that microbial proteases represent approximately 40% of the
total worldwide enzyme sales (Rao et al., 1998).
Several species of filamentous fungi have been exploited in industrial processes for the
production of metabolites and industrial enzymes. A. niger has a long tradition of safe use in the
production of enzymes and organic acids. Many of these products have listed as a ‘‘Generally
Recognized as Safe (GRAS)’’ by the US Food and Drug Administration (Schuster et al., 2002).
A. niger is one of the most important sources of fungal proteases. According to Pel et al., (2007),
genome sequencing shows that A. niger has 198 proteins involved in proteolytic degradation
process.
Proteolytic enzymes can be produced by submerged and solid state fermentation. For the
growth of fungi, solid state fermentation is most appropriate method because the solid substrates
resemble the natural habitat of the fungi and improving their growth and the secretion of a wide
range of extracellular enzymes. Some characteristics make solid state fermentation more
attractive than submerged fermentation: simplicity, low cost, high yields and concentrations of
the enzymes and the use of inexpensive and widely available agricultural residues as substrates
(Chutmanop et al., 2008).
The biochemical characterization of enzymes is important to evaluate their biotechnological
potential. The study of the protease properties, such as the substrate specificity, the optimum
catalytic pH conditions and the temperature and stability profiles, can be used to predict the
successful application of the enzyme to particular industries or processes (Castro and Sato,
2014a). Previous work has shown that the expression and secretion of different sets of proteases
and other enzymes, as well as their biochemical properties, can be regulated by the type of
substrate used as carbon and nitrogen source (Speranza et al., 2011; Farnell et al., 2012).
128
The application of proteases to the hydrolysis of animal and plant proteins to increase their
biological and functional properties has attracted much attention. The antioxidant activities of
protein hydrolysates are extensively reported in several studies. It is postulated that the
antioxidant characteristics of peptides comes from their abilities to inactivate reactive oxygen
species (ROS), scavenge free radicals, chelate prooxidative transition metals, and reduce
hydroperoxides (Zhou et al., 2012). Thus, studies of the application of new proteolytic enzyme
sources are critical to advancing the knowledge concerning bioactive peptides.
In this context, the main objectives of the present study were to evaluate the production of
the protease by A. niger LBA02 under solid state fermentation using different agroindustrial
wastes and to verify the correlation between some physical–chemical parameters, including
chemical composition, water absorption index, particle size and packing density with the protease
production. In addition, the biochemical properties of the proteases produced in each
agroindustrial waste, including the optimum pH and temperature for activity and stability and
milk-clotting activities were investigated. After the biochemical characterization, the application
of the different preparations of proteases to protein hydrolysis for the study of the antioxidant
properties of the hydrolysates was evaluated.
2. Materials and Methods
2.1. Physical–chemical characterization of the agroindustrial wastes
2.1.1. Chemical composition of the agroindustrial wastes
Moisture, protein content, lipids and ash of the agroindustrial wastes wheat bran, soybean
meal and cottonseed meal were determined by AOAC methods (AOAC, 2010). The carbohydrate
content was determined by difference between the total value of 100% and the sum of the other
components. The tests were performed in triplicate and the results were expressed as the mean ±
standard deviation.
2.1.2. Determination of the water absorption index (WAI) of the agroindustrial wastes
Their water absorption index (WAI) of the agroindustrial wastes was determined using the
method of Anderson et al. (1969) with slight modifications. Briefly, the sample (1.25 g) was
suspended in 15 mL of distilled water in a 50 mL centrifuge tube. The slurry was manually
stirred for 1 min at room temperature (25 °C) and centrifuged at 8000 x g and 25 °C for 15 min.
129
The supernatants were discarded, and the WAI was calculated from the weight of the remaining
gel and expressed as g gel g-1
dry weight.
2.1.3. Particle size
The particle sizes of the agroindustrial wastes were determined using AOAC method
965.22 (AOAC, 2010). The sieves used had the following opening values: 1.680, 0.841, 0.595,
0.250, 0.177 and 0.149 mm. One hundred g of the material were transferred to top of set of sieves
(opening value: 1.680 mm) assembled and fixed in a sieve shaker (Telastem, Produtest Model T,
Sao Paulo, Brazil). The sieves were kept under constant shaking at 3,600 vpm for 5 minutes to
separate the fractions and the retained material on each sieve was weighed. The experiments were
performed in triplicate and the results expressed as percentage.
2.1.4. Packing density
The packing densities of the agroindustrial wastes were quantified by apparent densities
using the dry substrates and the substrates with initial moisture adjusted to 50%. One hundred g
of each sample was transferred to standard graduated plastic cylinders and vertically agitated
until no change in volume. Apparent densities were calculated as the ratio between the sample
mass and its total volume and expressed in g cm-³.
2.2. Microorganism culture
The strain used in this study was A. niger LBA02, previously selected as a proteolytic
strain from the culture collection of the Laboratory of Food Biochemistry, School of Food
Engineering, University of Campinas. The strain was periodically subcultured and maintained on
potato dextrose agar slants. To produce fungal spores, the microorganism was inoculated into a
medium composed of 10 g wheat bran and 5 mL of solution containing 1.7% (w/v) NaHPO4 and
2.0% (w/v) (NH4)2SO4 and incubated for 3 days at 30 °C. The fungal spores were dispensed into
sterile Tween 80 solution (0.3%) to prepare the inoculum for fermentation. The number of spores
per milliliter in the spore suspension was determined with a Neubauer cell counting chamber.
2.3. Determination of the microorganism growth: radial growth rate and biomass
estimation by glucosamine level
The assays for determination of the microorganism growth rate were performed in Petri
dishes. The agroindustrial wastes have the initial humidity adjusted to 50% and an aliquot of
130
100 µL spore suspension containing 107 spores mL
-1 was inoculated in the central region of the
Petri dishes containing the substrates. The dishes were incubated at 30 °C for the time required to
completely cover all materials. The fungal radial growth was monitored and the results were
expressed in mm.
Fungal biomass estimation was carried out according to described by Ramachandran et al.
(2005) with slight modifications. This determination was based in the N-acetyl glucosamine
released by the acid hydrolysis of the chitin, present in the cell wall of the fungi. Dried fermented
sample (0.5 g) was mixed with concentrated sulphuric acid (2.0 mL) and the reaction mixture was
kept for 24 h at 30 °C. The mixture was diluted with 10 mL of distilled water, autoclaved at 15
psi pressure for l h and filtered through a filter membrane to obtain a solution free of any solid
material. The filtered solution was neutralized with 5 M NaOH and made to 50 mL with distilled
water. The reaction mixture containing 1.0 mL of the sample (resulting from the extractions
described above) and 1.0 mL of acetyl acetone reagent (1.0 mL of acetyl acetone and 50 mL of
0.5 M sodium carbonate solution) was incubated for 20 min in a boiling water bath. After
cooling, a 6.0 mL aliquot of ethanol was added followed by the addition of 1.0 mL Ehrlich
reagent (2.67 g of p-dimethylamino benzaldehyde in 1:1 mixture of analytical reagent grade
ethanol and concentrated hydrochloric acid and made up to 100 mL) and incubated at 65 °C for
10 min. After cooling, the absorbance of the reaction mixture was read at 530 nm against the
blank reagent. The reference standard was a glucosamine (Sigma) solution prepared daily in
distilled water and diluted (14.0–2.0 mg L-1
) for the preparation of the standard curve. The
biomass estimation was tested at 12 h intervals during 96 h fermentation and the results were
expressed as mg glucosamine per gram dry substrate.
2.4. Protease production and sampling
Wheat bran, soybean meal, and cottonseed meal were kindly provided by Bunge Foods
S/A. These agroindustrial wastes were used for the protease production by A. niger LBA02. The
protease production was performed under solid state fermentation in 250 mL Erlenmeyer flasks
containing 20 g medium. The cultivation parameters were 50% moisture, temperature set at
30 °C, and an inoculum level of 107 spores g
-1. The protease activity was tested at 24 h intervals
during a 96 h fermentation. The crude extract was obtained by the addition of 150 mL distilled
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water. After 1h at rest, the solution was filtered through a filter membrane to obtain an enzyme
solution free of any solid material.
2.5. Effects of pH and temperature on the activity and stability of the protease
determined using an experimental design
The optimum pH and temperature for activity and stability were determined using a
central composite rotatable design (CCRD) with three replicates at the central point and four
axial points (a total of 11 runs). To study the protease stability, the enzyme was incubated for 1 h
at various pH values and temperatures.
The experiments were randomized to maximize the variability in the observed responses
caused by extraneous factors. A second-order model equation was used for this model,
represented by Equation 1:
𝑌 = 𝛽0 + 𝛽𝑖𝑥𝑖 + 𝛽𝑖𝑗𝑥𝑖𝑥𝑗
𝑛
𝑗=𝑖+1
𝑛−1
𝑖=1
𝑛
𝑖=1
(1)
where Y is the estimated response, i and j equal values from 1 to the number of variables (n), β0 is
the intercept term, βi values are the linear coefficients, βij values are the quadratic coefficients,
and xi and xj are the coded independent variables. The coefficient of determination R2 and the F
test [analysis of variance (ANOVA)] were used to verify the quality of the fit of the second-order
model equation. The relationships between the responses and the variables were determined using
the StatisticaTM
10.0 software package from Statsoft Inc.
2.6. Determination of protease activity
The protease activity was measured using azocasein as the substrate according to Charney
and Tomarelli (1947) and described by Castro and Sato (2013). The reaction mixture containing
0.5 mL 0.5% (w/v) azocasein (Sigma), pH 5.0, and 0.5 mL of the enzyme solution was incubated
for 40 min. The reaction was stopped by adding 0.5 mL 10% TCA and the test tubes were
centrifuged at 17,000 x g for 15 min at 25 °C. A 1.0 mL aliquot of the supernatant was
neutralized with 1.0 mL 5 M KOH. One unit of enzyme activity (U) was defined as the amount of
enzyme required to increase the absorbance at 428 nm by 0.01 under the assay conditions
described.
132
2.7. Determination of milk-clotting activity
Milk-clotting activity was determined according to the methods described by Ahmed et
al., (2009). The substrate skim milk was dissolved in 200 mM phosphate buffer pH 6.5
containing 0.01 M CaCl2 at a final concentration of 100 mg mL-1
. A 2.0 mL aliquot of the
substrate was pre-incubated for 10 min at 37 °C, to which 0.2 mL of enzyme solutions were
added, and the curd formation was observed while manually rotating the test tube from time to
time. A comparative evaluation was performed using different preparations of commercial
proteases. The identification of discrete particles indicated the end point of the reaction. One
milk-clotting unit is defined as the amount of enzyme that clots 10 mL of the substrate within 40
min.
MCA (U mL-1
) = (2400 / clotting time (s)) × dilution factor.
2.8. Application of the proteases to protein hydrolysis
Bovine whey protein was used as the substrate for enzymatic hydrolysis and was kindly
provided by Alibra Ingredients Ltd. (Campinas, Brazil). The crude extracts of proteases produced
in wheat bran, soybean meal and cottonseed meal by A. niger LBA02 were concentrated by
ammonium sulfate (80%) precipitation, dialysis and freeze-drying. The partial purified
preparations were used for protein hydrolysis experiments. The enzyme concentrations were
adjusted to 50 U per mL of reaction mixture. The proteins were suspended in acetate buffer to a
final concentration of 100 mg mL-1
, and 50 mL aliquots of the mixtures were distributed in 125
mL Erlenmeyer flasks. Hydrolysis was performed at the optimum temperature and pH value of
the enzyme activity for 240 min. After hydrolysis, the samples were incubated in a water bath at
100 °C for 20 min for protease inactivation. The mixtures were centrifuged at 17,000 x g at 5 °C
for 20 min, and the supernatants containing the peptides were collected and freeze-dried for the
determination of their antioxidant activities and functional properties.
133
2.9. Determination of antioxidant activities
2.9.1. DPPH radical-scavenging activity
The DPPH (2,2-diphenyl-1-picrylhydrazyl) (Sigma-Aldrich, Steinheim, Germany)
radical-scavenging activity of the protein hydrolysates was determined as described by Bougatef
et al. (2009). A 500 µL aliquot of the protein hydrolysates at different concentrations was mixed
with 500 µL 99.5% ethanol and 125 µL 0.02% DPPH in 99.5% ethanol. The mixture was then
kept at room temperature in the dark for 60 min, and the reduction of the DPPH radical was
measured at 517 nm using a UV-visible spectrophotometer (Beckman DU 70 spectrophotometer,
Beckman-Coulter, Inc., Fullerton, CA, USA). The DPPH radical-scavenging activity was
calculated as follows:
The control reaction was performed in the same manner, except that distilled water was
used instead of sample. The tests were performed in triplicate.
2.9.2. Total antioxidant capacity
Total antioxidant capacity of the hydrolysates was performed according to the method
described by Prieto et al., (1999). An aliquot of 0.1 mL of the protein hydrolysates solutions at 10
mg mL-1
was mixed with 1.0 mL of the reagent solution containing 0.6 M sulphuric acid, 28 mM
sodium phosphate and 4 mM ammonium molybdate. The reaction mixtures were then incubated
at 90 °C and kept in the dark for 90 min. The samples were cooled to room temperature and the
absorbance was measured at 695 nm. An appropriate control was prepared with 1.0 mL of the
reagent solution and 0.1 mL distilled water. The results were expressed in function of the
absorbance considering that the absorbance was directly proportional to the total antioxidant
capacity.
2.10. Calculations and statistics
Values are expressed as the arithmetic mean. The Tukey test was used to check the
significant differences between the groups analyzed. The differences were considered significant
when p-value ≤ 0.05.
𝑅𝑎𝑑𝑖𝑐𝑎𝑙 𝑠𝑐𝑎𝑣𝑒𝑛𝑔𝑖𝑛𝑔 𝑎𝑐𝑡𝑖𝑣𝑖𝑡𝑦 % = 𝐴𝑏𝑠𝑜𝑟𝑏𝑎𝑛𝑐𝑒 𝑜𝑓 𝑐𝑜𝑛𝑡𝑟𝑜𝑙 − 𝐴𝑏𝑠𝑜𝑟𝑏𝑎𝑛𝑐𝑒 𝑜𝑓 𝑠𝑎𝑚𝑝𝑙𝑒
𝐴𝑏𝑠𝑜𝑟𝑏𝑎𝑛𝑐𝑒 𝑜𝑓 𝑐𝑜𝑛𝑡𝑟𝑜𝑙 ∗ 100
134
Pearson correlation coefficient was used to measure the strength of linear dependence
between two responses. The correlation coefficient ranges from – 1 to 1. A value of 1 implies that
a linear equation describes the relationship between the responses was perfectly and positive,
while a value of -1 indicate a perfectly and negative correlation. A value of 0 implies that there is
no linear correlation between the responses. The correlations between analyzed parameters were
considered significant when the p-value ≤ 0.10.
3. Results and Discussion
3.1. Chemical composition of the agroindustrial wastes
The centesimal compositions of the agroindustrial wastes used as fermentation substrates
for production of protease by A. niger LBA02 under solid state fermentation are showed in Table
1. The enzymes production under solid state fermentation can be affected by the composition of
the substrates and various cultivation factors. The presence of protein sources can induce the
enzyme secretion by the microorganism. On the other hand, the substrate must have a carbon to
nitrogen ratio (C:N) suitable for the fermentation (Castro and Sato, 2014a). Soybean meal and
cottonseed meal were the materials with higher protein content and wheat bran showed the major
C:N ratio (Table 1).
Table 1 – Average values of the centesimal composition (%) of the agroindustrial wastes used for
protease production by A. niger LBA02 under solid state fermentation.
Results are presented as the mean (n = 3) ± SD, and those with different letters are significantly different, with p < 0.05. Tukey
tests were applied between the chemical components for each substrate (not between different substrates). Carbohydrate content
(%) was measured by difference between the total value of 100% and the sum of the other components.
The Pearson coefficient was used to verify the correlation between the C:N ratio and the
protein content in the substrates with the protease production. The correlation analysis indicated a
strong, positive and significant correlation between the protein content (%) in the substrates and
the protease production at 24 h (Pearson coefficient = 0.99; p = 0.08) and 48 h fermentation
(Pearson coefficient = 0.99; p = 0.06). In contrast, it was observed a negative and significant
Chemical components Wheat bran Soybean meal Cottonseed meal
Moisture (%) 12.77 ± 0.08a 11.93 ± 0.02
a 6.42 ± 0.01
a
Protein (%) 14.74 ± 0.51b 49.24 ± 0.07
b 25.91 ± 0.60
b
Carbohydrates (%) 63.04c 31.53
c 55.80
c
Lipids (%) 4.47 ± 0.22d 1.40 ± 0.02
d 7.83 ± 0.01
d
Ash (%) 4.98 ± 0.06e 5.90 ± 0.04
e 4.04 ± 0.01
e
135
correlation between the C:N ratio and the protease production at 24 h fermentation (Pearson
coefficient = -0.98; p = 0.10) (Table 2). These results confirm that an adequate supply of proteins
as nitrogen source can induce the protease production at the first hours of fermentation.
Table 2 – Correlation analysis between the ratio (C:N) and the protein content of the
agroindustrial wastes with the protease production by A. niger LBA02 under solid state
fermentation at 24, 48, 72 and 96 h.
*The correlations between analyzed parameters were considered significant when the p-value ≤ 0.10.
3.2. The influence of the water absorption index (WAI) on protease production
The WAI indicates the quantity of water that can be absorbed by the support. Materials
with high WAI are preferred for solid state fermentation since their moisture content can be
modified during the solid state culturing (Robledo et al., 2008). Wheat bran showed higher WAI
values; whereas the soybean meal showed the lowest WAI values (Fig. 1a). The highest values
for production of protease were observed in the substrates with higher WAI values, indicating a
positive impact of this physical–chemical parameter on enzymes production, probably caused by
the maintenance of the moisture throughout the fermentation process (Fig. 1a). Orzua et al.,
(2009) studied ten agroindustrial wastes for their suitability as fungus immobilization carrier for
solid-state fermentation and pointed out the materials with high water absorption capacity as the
most appropriate for use in SSF.
Substrate C:N Protein content
(%)
Protease production (U g-1
)
24 h 48 h 72 h 96 h
Wheat bran 4.27 14.74 13.40 81.46 176.21 186.42
Soybean meal 0.64 49.24 20.74 152.38 138.04 94.04
Cottonseed meal 2.15 25.91 16.61 110.25 111.71 118.83
Correlation analysis between the protease production and C:N
Pearson coefficient -0.98 -0.98 0.67 0.99
p-value 0.10* 0.13 0.54 0.10
*
Correlation analysis between the protease production and the protein content (%)
Pearson coefficient 0.99 0.99 -0.42 -0.89
p-value 0.08* 0.06
* 0.73 0.29
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3.3. The influence of the granulometric distribution and the apparent density of the
agroindustrial wastes on protease production
An important parameter in SSF is the particle size of the substrate since it is directly
related to porosity, the material compaction degree, therefore, the available space for mass and
energy transfer (Figueroa et al., 2013). In this work, the determination of particle size distribution
and the apparent density were used to evaluate the characteristics of the agroindustrial wastes and
their impact on protease production by A. niger LBA02.
Generally, small substrate particles provide larger surface area for microbial attack and
this is considered as a desirable factor. However, too small particles may result in agglomeration
and poor growth, whereas larger particles provide better inter-particle space but limited surface
for microbial attack (Pandey et al., 2001). Therefore, it is necessary to arrive at a compromised
particle size for a particular process. Wheat bran showed more heterogeneous particle size
distribution, with a predominance of particles ranging from 0.258 to 1.68 mm (Fig. 1b) and the
highest protease production was achieved at 96 h fermentation when this agroindustrial waste
was used as the substrate, reaching 186.42 U g-1
(Fig. 2a). Soybean and cottonseed meals showed
particle sizes greater, with granulometric distribution of 72.9 and 83.5% of particles larger than
1.68 mm, respectively (Fig. 1b). Although the protease acitivities (U g-1
) were lower in the latter
two substrates, the productivity indicated higher values when soybean meal was used as the
substrate, reaching 3.47 U g-1
h-1
at 48 h fermentation, while the maximum productivity detected
when wheat bran was used as the substrate was 2.45 U g-1
at 72 h fermentation, followed by the
cottonseed meal (2.30 U g-1
h-1
at 48 h fermentation) (Fig. 2). Important factors can be considered
from these results: when the particle size exceeded a particular value, the enzymes production can
be affected owing to reduction of contact surface between substrate’s particles and fungus.
However, small particle sizes affect the air supplied in terms of the aeration which can hinder the
microbial growth (Vaseghi et al., 2013).
The lowest apparent density values were obtained with wheat bran (0.32 g cm-3
) and
cottonseed meal (0.33 g cm-3
) as dry substrates (Fig. 1c). When the substrates have the initial
moisture adjusted to 50% for simulation of the real fermentation conditions, increases in the
apparent densities were observed. A high value of apparent density was found in soybean meal as
dry or moist substrate, showing values of 0.72 and 0.80 g cm-3
, respectively, which might to
137
result in problems as compactation, impairing the mass and energy transference (Fig. 1c). No
significant correlations (p-value ≤ 0.10) were observed between the apparent densities and the
protease production.
Fig. 1 - Water absorption index (WAI) (a), the granulometric fractions (% retained) (b) and
apparent density (g cm-3
) (c) of the agroindustrial wastes used for protease production by A. niger
LBA02 under solid state fermentation; fungal growth (d) and biomass estimation (glucosamine)
(e).
0
1
2
3
4
5
6
Wheat bran Soybean meal Cottonseed meal
WA
I (g
of
wat
er/g
dri
ed s
ubst
rate
)
0
15
30
45
60
75
90
1.68 0.841 0.595 0.250 0.177 0.149 <0.149
Gra
nulo
met
ric
frac
tio
ns
(% r
etai
ned
)
Opening (mm)
Wheat bran Soybean meal Cottonseed meal
0.32
0.72
0.33
0.63
0.80
0.55
Wheat bran Soybean meal Cottoseed meal
Ap
par
ent
den
sity
(g
/cm
³)
Dry substrate Moist substrate
0
15
30
45
60
75
90
0 24 48 72 96 120 144
Fu
ngal
rad
ial
gro
wth
(m
m)
Time (h)
Wheat bran Soybean meal Cottonseed meal
a
c
b
d
0
20
40
60
80
100
0 24 48 72 96 120
Glu
cosa
min
e (m
g g
-1)
Time (h)
Wheat bran Soybean meal Cottonssed meal
e
138
Fig. 2 - The protease production (U g-1
) and productivity (U g-1
h-1
) by A. niger LBA02 under
solid state fermentation using agroindustrial wastes: wheat bran (a), soybean meal (b) and
cottonseed meal (c).
a
b
c
0
1
2
3
4
0
40
80
120
160
200
0 24 48 72 96
Pro
ductiv
ity (U
g-1
h-1)
Pro
duct
ion (
U g
-1)
Fermentation time (h)
Production Productivity
0
1
2
3
4
0
40
80
120
160
200
0 24 48 72 96
Pro
ductiv
ity (U
g-1
h-1)
Pro
duct
ion (
U g
-1)
Fermentation time (h)
Production Productivity
0
1
2
3
4
0
40
80
120
160
200
0 24 48 72 96
Pro
ductiv
ity (U
g-1
h-1)
Pro
duct
ion (
U g
-1)
Fermentation time (h)
Production Productivity
139
Several studies describe the use of agroindustrial wastes as potent substrates for the
production of proteases by filamentous fungi of the genus Aspergillus (Mukhtar and Haq, 2009;
Esparza et al., 2011; Leng and Xu, 2011). It is important to note that a standard assay is essential
for comparing the results of different studies. In several studies, research groups used different
methodologies to determine the protease activities, which may result in differences in the
substrates, incubation times, pH and temperatures of the reaction mixtures. The experimental data
variability complicates the comparisons among different studies. As such, a report of higher
protease activities does not necessarily suggest a higher production. Negi and Banerjee (2006)
observed maximum yields of protease production by a strain of A. awamori MTCC 6652 using
wheat bran as a substrate under solid state fermentation. The highest secretion of protease was
measured to be 1,930 U g-1
. Chutmanop et al., (2008) studied the protease production under solid
state fermentation of wheat bran, rice bran and their mixtures using strain of A. oryzae (Ozykat-1)
and reported a protease production of ∼1,200 U g−1
within 96 h fermentation using a substrate
mixture of 75% rice bran and 25% wheat bran. Shivakumar (2012) screened 11 different
substrates, including 8 cereals and 3 agroindustrial residues, for protease production by
Aspergillus sp. under solid state fermentation and found that wheat flour, wheat bran and soya
flour proved superior protease production, reaching activities of 320, 280 and 160 U g-1
,
respectively.
3.4. Determination of the microorganism growth
Filamentous fungi are the most widely microorganisms used in SSF because of their
ability to grow in solid substrates even in the absence of free water (Prakash et al., 2008; Orzua et
al., 2009). In the present work, wheat bran, soybean meal and cottonseed meal were used as
substrates for solid-state cultivation and evaluation of A. niger LBA02 growth into the
agroindustrial wastes. Fig. 1d shows the fungal radial growth (mm) in each substrate for 144 h
cultivation. In general, the microorganism had also good growth when cultivated in all substrates.
It can be noted that A. niger LBA02 exhibited a slight tendency to decrease their growth rate
when cultivated in soybean meal, reaching the maximum growth (80 mm) after 120h cultivation,
while the time required to completely cover wheat bran and cottonseed meal was 96 h. No
significant correlations (p-value ≤ 0.10) were observed between the protease production and the
water absorption index with the radial growth. However, the apparent densities showed a strong,
negative and significant correlation (Pearson coefficient ≤ − 0.99; p-value ≤ 0.10) with the fungal
140
radial growth, indicating a decrease in A. niger LBA02 growth with increasing of the apparent
densities values of the agroindustrial wastes.
Fig. 1e shows the evolution of fungal cellular growth as estimated by glucosamine level in
each substrate for 120 h cultivation. A. niger LBA02 exhibited a maximum growth when
cultivated in wheat bran, reaching glucosamine level of 90.33 mg g-1
, followed by soybean meal
(83.35 mg g-1
) and cottonseed meal (73.61 mg g-1
) after 96 h cultivation. Incubation beyond this
period did not result any further increase in glucosamine content. The glucosamine level showed
a strong, positive and significant correlation (Pearson coefficient ≥ 0.92; p-value ≤ 0.01) with the
fungal radial growth, confirming the agreement between these parameters as an important tool to
estimate the fungal growth in solid state fermentation. The protease production in the three
substrates showed a good and significant correlation with the glucosamine content, resulting in
Pearson coefficients of 0.91 (p-value = 0.03), 0.83 (p-value = 0.08) and 0.90 (p-value = 0.04) for
wheat bran, soybean meal and cottonssed meal, respectively, indicating an increase of the
protease production with increase of the glucosamine level.
3.5. Biochemical characteristics of protease from A. niger LB02
3.5.1. Effects of pH and temperature on the activity and stability of the protease determined
using an experimental design
The crude extracts of proteases produced in wheat bran (PWB), soybean meal (PSM) and
cottonseed meal (PCM) were biochemically characterized. Table 3 shows the CCRD matrix with
its independent variables (pH and temperature) and the results for protease activity and stability.
In the study of the determination of the optimum pH and temperature for activity, the highest
values obtained for PSB and PCM, were observed in the central points (runs 9-11) (50 °C, pH
4.5), averaging 148.04 and 106.36 U g-1
, respectively, while the PWB showed higher protease
activity (163.35 U g-1
) when incubated at 50 °C pH 2.0 (run 5). For protease stability, the highest
values obtained for PWB, PSM and PCM were observed when the enzymes were incubated at
50 °C pH 4.5 (runs 9-11).
141
Table 3 - The CCRD matrix used to determine the pH and temperature for optimum activity and
stability of the proteases from A. niger LBA02 produced in wheat bran, soybean meal and
cottonseed meal, with the coded and real values for the variables and responses.
1Proteases from A. niger LBA02 produced in wheat bran (PWB), soybean meal (PSM) and cottonseed meal (PCM). 2Residual
protease activity (%) of the proteases from A. niger LB02 produced in wheat bran (PWB), soybean meal (PSM) and cottonseed
meal (PCM) after incubation for 1h at different pH and temperatures.
Optimum pH and temperature for the protease activity
Run x1 / pH x2 /Temperature (°C) PWB1 (U g
-1) PSM
1 (U g
-1) PCM
1 (U g
-1)
1 -1.0 (2.73) -1.0 (39.4) 143.83 ± 1.70 44.12 ± 0.51 64.95 ± 0.56
2 +1.0 (6.27) -1.0 (39.4) 23.92 ± 0.67 23.23 ± 0.69 12.20 ± 0.73
3 -1.0 (2.73) +1.0 (60.6) 148.03 ± 1.36 41.63 ± 0.33 49.37 ± 1.56
4 +1.0 (6.27) +1.0 (60.6) 26.95 ± 0.13 25.38 ± 1.33 17.92 ± 0.53
5 -1.41 (2.0) 0.0 (50.0) 163.35 ± 10.10 77.12 ± 0.78 83.80 ± 4.09
6 +1.41 (7.0) 0.0 (50.0) 12.95 ± 0.13 13.72 ± 1.32 10.33 ± 1.50
7 0.0 (4.5) -1.41 (35.0) 120.58 ± 2.58 56.92 ± 1.48 66.92 ± 1.27
8 0.0 (4.5) +1.41 (65.0) 81.02 ± 2.90 68.40 ± 0.93 60.28 ± 2.19
9 0.0 (4.5) 0.0 (50.0) 149.93 ± 2.33 102.55 ± 2.65 104.60 ± 2.38
10 0.0 (4.5) 0.0 (50.0) 148.45 ± 1.98 102.28 ± 0.90 107.65 ± 1.23
11 0.0 (4.5) 0.0 (50.0) 145.75 ± 5.24 101.08 ± 2.42 106.83 ± 0.85
pH and temperature for the protease stability
Run x1 / pH x2 /Temperature (°C) PWB (%)2 PSM (%)
2 PCM (%)
2
1 -1.0 (2.73) -1.0 (39.4) 63.20 ± 0.33 73.17 ± 3.42 79.02 ± 2.89
2 +1.0 (6.27) -1.0 (39.4) 11.99 ± 4.33 35.92 ± 6.21 12.01 ± 0.96
3 -1.0 (2.73) +1.0 (60.6) 25.58 ± 0.48 31.58 ± 2.07 1.17 ± 0.57
4 +1.0 (6.27) +1.0 (60.6) 1.43 ± 0.80 8.27 ± 1.00 2.78 ± 1.32
5 -1.41 (2.0) 0.0 (50.0) 56.31 ± 1.26 46.51 ± 6.42 74.75 ± 3.89
6 +1.41 (7.0) 0.0 (50.0) 2.42 ± 3.62 4.54 ± 0.15 4.61 ± 1.17
7 0.0 (4.5) -1.41 (35.0) 62.86 ± 1.59 71.13 ± 5.96 80.07 ± 0.93
8 0.0 (4.5) +1.41 (65.0) 4.81 ± 1.65 10.42 ± 0.36 2.76 ± 1.87
9 0.0 (4.5) 0.0 (50.0) 97.48 ± 2.09 100.00 ± 3.36 96.32 ± 1.30
10 0.0 (4.5) 0.0 (50.0) 98.73 ± 2.28 96.78 ± 5.01 95.57 ± 1.02
11 0.0 (4.5) 0.0 (50.0) 100.00 ± 0.86 91.92 ± 3.28 100.00 ± 2.27
142
The proteases PWB and PSM demonstrated lower stability at temperatures above 60 °C
and pH range 6.0-7.0, reaching residual activities of 1.43 (run 4) and 4.54% (run 6); while for
PCM, the minimum value was detected when the enzyme was incubated at 60.6 °C and pH 2.73
(run 3), reaching residual activity of 1.17% (Table 3). The limited variability of the central points
(runs 9-11) indicated good reproducibility of the experimental data (Table 3).
Table 4 shows the models, R2, F-values, probability values for the final reduced models
and the validation tests performed under the conditions predicted by the models of the pH and
temperature for optimum activity and stability of the proteases from A. niger produced in wheat
bran (PWB), soybean meal (PSM) and cottonseed meal (PCM). For protease activity, the linear
and quadratic terms for the pH (x1) and temperature (x2) demonstrated a significant effect (p <
0.05) and the interaction pH x temperature (x1x2) showed no significant effects (p < 0.05) (Table
4). The estimated regression coefficients for the protease stability showed high statistical
significance (p < 0.05). The linear terms of pH (x1) and temperature (x2) showed positive effects
on the protease stability, while the quadratic terms indicated negative effects. These results
showed that the increasing pH and temperature positively influenced the stability of proteases,
but from a certain value, this effect started to be negative and quadratic. The interaction term
(pH×T) demonstrated positive effect for PWB and PCM stability but was not statistically
significant for PSM stability (Table 4).
An analysis of variance (ANOVA) showed that 89-98% of the total variation was
explained by the models. All F-values calculated for the regressions were greater than the
tabulated F-values (p-value < 0.01), reflecting the statistical significance of the model equations
(Table 4).
143
Table 4 - Models, R2, F-test, probability values and validation tests for the final reduced models of the pH and temperature for
optimum activity and stability of the proteases from A. niger LBA02 produced in wheat bran, soybean meal and cottonseed meal.
1Proteases from A. niger LBA02 produced in wheat bran (PWB), soybean meal (PSM) and cottonseed meal (PCM). 2Residual protease activity (%) of the proteases from A. niger
produced in wheat bran (PWB), soybean meal (PSM) and cottonseed meal (PCM) after incubation for 1h at different pH and temperatures. x1 – pH; x2 – temperature. The proteases
used to determine the pH and temperature for optimum activity and stability were obtained under the following fermentation conditions: initial moisture content of 50%, inoculum
level of 107 spores g-1, incubation temperature at 30 °C for 72 h fermentation.
Optimum pH and temperature for the protease activity
Responses Equations F-test F tabulated R² p-value
PWB (U g-1
) Y = – 460.68 + 60.50pH – 10.28pH2 + 22.36T – 0.23T
2 67.30 4.53 0.98 <0.001
PSM (U g-1
) Y = – 633.49 + 87.21pH – 10.68pH2 + 22.19T – 0.22T
2 11.97 4.53 0.89 0.005
PCM (U g-1
) Y = – 627.29 + 85.94pH – 11.02pH2 + 23.03T – 0.23T
2 21.22 4.53 0.93 0.005
pH and temperature for the protease stability
PWB (%) Y = – 684.14 + 75.49pH – 11.58pH2 + 27.02T – 0.30T
2 + 0.36pH×T 72.84 3.45 0.98 <0.001
PSM (%) Y = – 589.94 + 90.36pH – 10.98pH2 + 21.90T – 0.24T
2 131.32 4.01 0.98 <0.001
PCM (%) Y = – 437.07 + 79.55pH – 10.35pH2 + 16.16T – 0.18T
2 + 0.13pH×T 23.97 3.45 0.96 0.002
Validation tests
Maximum protease activity Predicted response (U g-1
) Experimental response (U g-1
)
PWB pH 3.0 Temperature 48.7 °C 173.46 181.20 ± 13.72
PSM pH 4.0 Temperature 50.4 °C 103.97 102.55 ± 1.78
PCM pH 4.0 Temperature 49.5 °C 110.49 106.36 ± 4.58
Maximum protease stability Predicted response Experimental response
PWB pH 3.5 – 4.5 Temperature: 45-50 °C ≥ 95% / ≥ 170.49 U g-1
101.27 ± 1.55% / 172.67 ± 2.69 U g-1
PSM pH 3.5 – 4.5 Temperature: 45-50 °C ≥ 95% / ≥ 89.67 U g-1
101.63 ± 3.37% / 91.13 ± 3.07 U g-1
PCM pH 3.0 – 4.5 Temperature: 40-50 °C ≥ 95% / ≥ 109.10 U g-1
102.78 ± 2.37% / 112.13 ± 2.66 U g-1
144
The surface responses were generated from the models. In general, all proteases were
more active in the acidic pH range (2.0-5.0) and at temperatures above 45 °C. However, the
proteases from A. niger LBA02 obtained by cultivation in wheat bran (PWB), soybean meal
(PSM) and cottonseed meal (PCM) showed some different characteristics in response to each
substrate. PSM and PCM were more active in the pH range 3.5-4.5 and temperature range 45-55
°C, while PSM showed higher activity in the pH range 2.0-4.5 and temperature range 45-60 °C
(Fig. 3). In the study of the protease stability, an evaluation of the response surfaces demonstrated
that the PWB, PSM and PCM showed different ranges for pH and temperature and stability.
PWB and PSM were more stable in the pH range 3.0-5.0 and in the temperature below 50 °C
after 1 h, retaining above 64% of the protease activity. PCM showed a higher range of stability,
with retention of the protease activity above 64% at pH range 2.0-5.0 and temperatures below
50 °C (Fig. 4).
Validation tests were performed to determine the accuracy of the polynomial models
obtained for the protease activity and stability with three assays (Table 4). The optimum
conditions for PWB, PSM and PCM activities determined according to the CCRD analysis were:
pH 3.0 and 48.7 °C, pH 4.0 and 50.4 °C, pH 4.0 and 49.5 °C, respectively. The optimum
conditions for protease stability of PWB, PSM and PCM showed similar profiles; for retention of
residual protease activity superior to 95%, the incubation conditions were: pH range 3.5 to 4.5
and 40-50 °C. The Tukey test showed that the experimental values agreed with the values
predicted by the models within a 95% confidence interval, thereby confirming the validity of the
models for the evaluated responses (Table 4).
The protease produced by A. niger LBA02 demonstrated pH and temperature activity and
stability profiles similar to those of the acid proteases from A. niger. An acid protease synthesized
by A. niger NRRL 1785 showed retention of 60% relative activity and above over a wide range
of pH 2.5-5.5 and was also stable up when incubated at 50 °C pH 4.0 for 1 h (Olajuyigbe et al.,
2003). A protease from A. niger ATCC 11414 exhibited maximum activity at pH 4.0 and 50 °C
and it was stable in a wide pH range (2.2-10.0) and at temperatures lower than 70 °C (Esparza et
al., 2011). An acidic protease from A. niger BCRC 32720 showed the optimum pH and
temperature activity at 2.5 and 50 C, respectively and was stable at pH 2.0−4.0 and temperatures
below 40 °C (Yin et al., 2013).
145
Fig. 4 – Response surfaces for maximum enzymes activities (U g-1
) and stability (% residual
activity) of the proteases from A. niger LBA02 produced in wheat bran (a, A), soybean meal (b,
B) and cottonseed meal (c, C) as a function of the pH and the temperature (°C).
> 160
< 160
< 124
< 104
< 84
< 64
< 44
2
3
4
5
6
7
pH
35
40
45
50
55
60
65
Temperature (°C)
20
40
60
80100120140160180
Protease (U
g-1
)
> 95 < 95 < 64 < 44 < 24 < 4
2
3
4
5
6
7
pH
3540
4550
5560
65
Temperatura (°C)
20
40
60
80
100
Pro
tease (%)
> 90
< 90
< 63
< 48
< 33
< 18
< 3
2
3
4
5
6
7
pH
3540
4550
5560
65
Temperature (°C)
15
30
45
60
75
90
105
Pro
tease (U g
-1)
> 95 < 95 < 64 < 44 < 24 < 4
2
3
4
5
6
7
pH
3540
4550
5560
65
Temperature (°C)
20
40
60
80
100
Pro
tease (%)
> 105
< 105
< 78
< 63
< 48
< 33
< 18
2
3
4
5
6
7
pH
3540
4550
5560
65
Temperature (°C)
15
30
45
60
75
90
105
120
Pro
tease (U g
-1)
> 95 < 95 < 64 < 44 < 24 < 4
2
3
4
5
6
7
pH
3540
4550
5560
65
Temperature (°C)
20
40
60
80
100
Pro
tease (%)
a
b
c
A
B
C
146
3.5.2. Determination of milk-clotting activity
A summary with the results for milk-clotting and protease activities of the enzymes
produced by A. niger LBA02 compared to other proteases preparations is presented in Table 5.
As shown, the commercial rennet from A. niger had the higher ratio clotting/protease activities
compared to other proteases. It was found that the clotting and protease activities of the
commercial rennet from A. niger were 3,908.79 U mL-1
and 26.46 U mL-1
, respectively. The
milk-clotting activity demonstrated different values in response to the different agroindustrial
wastes used for protease production. The PWB showed higher ratio clotting/protease activities
(15.24) compared to other commercial preparations of proteases, such as FlavourzymeTM
500L
(0.13) and Alcalase 2.4LTM
(8.01).
Table 5 - Ratio of milk-clotting activity/protease activity of the proteases from A. niger LBA02
produced under solid state fermentation using wheat bran (PWB), soybean meal (PSM) and
cottonseed meal (PCM) as substrates and other coagulants.
¹Protease activity determined using azocasein as the substrate at 37 °C and pH 6.5. The proteases used to determine the ratio of
milk-clotting activity/protease activity were obtained under the following fermentation conditions: initial moisture content of
50%, inoculum level of 107 spores g-1, incubation temperature at 30 °C for 72 h fermentation.
Fazouane-Naimi et al., (2010) showed that an acid protease produced by solid state
fermentation of A. niger FFB1 exhibited specific proteolytic and milk-clotting activities of
3,020.0 and 1,858.0 U mg-1
, respectively.
Enzymes Clotting activity
(U mL-1
)
Protease activity¹
(U mL-1
)
Ratio
(Clotting/Protease)
PWB 22.22 1.46 15.24
PSM 0.56 1.44 0.38
PCM 5.80 0.92 6.28
FlavourzymeTM
500L 1,136.36 8,513.00 0.13
AlcalaseTM
2.4L 111,627.91 13,944.67 8.01
Rennet from A. niger 3,908.79 26.46 147.72
147
3.6. Application of the proteases from A. niger to bovine whey protein hydrolysis and
antioxidant activities of the hydrolysates
Bovine whey proteins were separately hydrolyzed with the proteases from A. niger
LBA02 produced in the different agroindustrial wastes. The antioxidant activity of the
hydrolysates was evaluated using DPPH radical scavenging and total antioxidant activity
methods.
As shown in Figure 5, the bovine whey protein exhibited increase in antioxidant activities
after enzymatic hydrolysis. The antioxidant activities showed a strong positive and significant
correlation with the protein concentration (Pearson coefficient > 0.95, p-value < 0.01), with
maximum activities detected at 10 mg mL-1
. It can be noted that the antioxidant activities
demonstrated different values in response to the proteases produced in each agroindustrial waste.
DPPH is a stable free radical that shows maximal absorbance at 517 nm in ethanol. When
DPPH encounters a hydrogen-donating substance, such as an antioxidant, the radical is
scavenged and the absorbance is reduced by changing color from purple to yellow (Chen et al.,
2012). The highest DPPH radical scavenging was observed for PCM hydrolysates, followed by
PWB and PSM hydrolysates, which presented maximum activities of 84.5, 82.8 and 64.1% at 10
mg mL-1
. These values represented increases between 7.0 and 9.2-fold higher than non-
hydrolyzed protein.
Total antioxidant capacity is a method based on the reduction of Mo (VI) to Mo (V) by
the antioxidant agent (electron donation capacity) and the subsequent formation of a green
phosphate/Mo (V) complex at acidic pH (Prieto et al., 1999; Bougatef et al., 2009). For total
antioxidant activity, the hydrolysates showed maximum activity in following order: PWB > PSM
> PCM hydrolysates at 10 mg mL-1
, as was determined by their absorbance at 695 nm (Fig. 5).
148
Fig. 5 – Antioxidant activities (DPPH radical scavenging (a) and total antioxidant activity (b)) for
whey protein non-hydrolyzed and hydrolysates obtained with the proteases from A. niger LBA02
produced in wheat bran (PWB), soybean meal (PSM) and cottonseed meal (PCM).
These results demonstrate that the bovine whey protein hydrolysates possess hydrogen-
and electron-donating abilities, exhibiting adequate potency to react with free radicals.
Table 6 contains the correlation analysis between the different methods used to assess the
antioxidant activities and showed that non-hydrolyzed protein and all hydrolysates were
positively correlated (Pearson coefficient = 0.96–0.99; p-values < 0.01).
.
0,00
0,10
0,20
0,30
0,40
0,50
0,60
0 2 4 6 8 10
Abso
rban
ce 6
95 n
m
Protein concentration (mg mL-1)
Non-hydrolyzed PWB PSM PCM
0
15
30
45
60
75
90
0 2 4 6 8 10
DP
PH
rad
ical
sca
ven
gin
g (
%)
Protein concentration (mg mL-1)
Non-hydrolyzed PWB PSM PCM
a
b .
.
.
.
.
. .
.
149
According Adjonu et al., (2013), the relatively high correlation between methods with
different reaction pathways suggests that the results complemented each other when it came to
assessing the antioxidant activities of proteins and their hydrolysates, and may also provide some
insight into their mechanisms of action. These authors observed correlation coefficients ranging
from 0.56 to 0.99 between ORAC and ABTS radical scavenging methods for samples of whey
protein isolate hydrolysates, which is consistent with the results reported in our study.
Table 6 – Correlations analysis between DPPH radical scavenging and total antioxidant activity
methods for non-hydrolyzed and hydrolyzed bovine whey protein.
Bovine whey protein Pearson correlation coefficients (R
2)
DPPH radical scavenging vs. total antioxidant activity
Non-hydrolyzed 0.96
PWB-hydrolysates 0.99
PSM-hydrolysates 0.98
PCM-hydrolysates 0.97
Luo et al., (2014) studied the enzymatic hydrolysis of sodium caseinate using papain,
pancreatin and trypsin and investigated the antioxidant properties of the hydrolysates using
different methods. The antioxidant activities showed different results in response to the proteases
used for enzymatic hydrolysis and in function of the methods. DPPH scavenging activity of
papain hydrolysates was higher than the other two groups, reaching a maximum value about 50%
after 24 h reaction. The hydrolysates obtained using pancreatin after 24 h hydrolysis, exhibited
the greatest reducing power, which was 2-fold that of non-hydrolyzed protein.
Castro and Sato (2014b) reported a comparative study with a pre-purified protease from
A. oryzae produced under solid state fermentation using wheat bran as substrate and two
commercial proteases (FlavourzymeTM
500L and AlcalaseTM
2.4L) for bovine whey protein
hydrolysis and study of the antioxidant properties of the hydrolysates. The results indicated that
the antioxidant capacity of whey protein increased after enzymatic hydrolysis. For the proteases
that were evaluated, the antioxidant activity increased approximately 2-fold, and the highest
DPPH radical scavenging (73.62% at 5 mg mL-1
) was observed in whey protein hydrolysates that
were prepared with the pre-purified enzyme from A. oryzae. Hydrolysates obtained with
150
FlavourzymeTM
500L and AlcalaseTM
2.4L reached maximum DPPH radical scavenging of 61.24
and 57.22% at 5 mg mL-1
.
4. Conclusion
The results obtained in our study showed that the protease production by A. niger
LBA02 can be affected by some physical chemical parameters, as the particle size and the water
absorption index of the agroindustrial wastes used in solid state fermentation. Higher levels of
protein in the agroindustrial wastes showed as important factor, inducing the protease production
in the first 48 h of fermentation. The biochemical characterization showed that the proteases
produced in different agroindustrial wastes exhibited different properties. The enzymes were
most active in the pH range 3.0-4.0 at 50 °C and stable from pH 2.5 to 4.5 at 40-50 °C. The
application of the proteases produced using different agroindustrial wastes as substrates to bovine
whey protein hydrolysis increased the antioxidant properties of the protein and resulted in
hydrolysates with different profiles of antioxidant activity.
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155
Capítulo VII: Comparison and synergistic effects of intact proteins and
their hydrolysates on the functional properties and antioxidant activities in
a simultaneous process of enzymatic hydrolysis
Revista: Food and Bioproducts Processing
156
Abstract
Soy protein isolate (SPI), bovine whey protein (BWP) and egg white protein (EWP) were
hydrolyzed with the FlavourzymeTM
500L protease, and the interactions of these substrates and
their mixtures on their functional properties and antioxidant activities were studied using a
simplex centroid mixture design. Synergistic effects between the formulations containing binary
or ternary mixtures were observed for several parameters, especially the DPPH radical-
scavenging activity and emulsion activity index, which exhibited increases of up to 45.0 and
1,200%, respectively, after enzymatic hydrolysis compared to the isolated substrates. The results
suggest that the application of the statistical mixture designs in a simultaneous process of
enzymatic hydrolysis using different protein sources is an attractive method for improving
enzyme performance and identifying optimum formulations.
Keywords: enzymatic hydrolysis; protein hydrolysates; functional properties; antioxidant
activities; mixture design.
157
1. Introduction
Processes involving protein hydrolysis have been studied for bioactive peptide
production. Bioactive peptides can be defined as specific amino acid sequences that promote
beneficial biological activities. Bioactive peptides can be produced by enzymatic hydrolysis
using digestive, microbial and plant enzymes. Limited and controlled proteolysis unfolds protein
chains, reduces the incidence of allergenic factors and increases the formation of small peptides
with biological activities (Korhonen, 2009).
In the last decade, enzymatic hydrolysis of proteins from animal and plant sources for
the production of bioactive peptides have attracted much attention, and the antioxidant activities
of peptides have been extensively reported in several studies. The action mechanism of peptides
with antioxidant properties is related to the inactivation of reactive oxygen species (ROS),
scavenging of free radicals, chelation of prooxidative transition metals and reduction of
hydroperoxides (Zhou et al., 2012a).
In addition to their antioxidant activities, protein hydrolysates have shown interesting
functional properties, such as high solubility, resulting in increases in the concentration of free
amino and carboxyl groups. Hydrolysis disrupts the protein tertiary structure and reduces the
molecular weight of the protein consequently altering its functional properties (Liu et al., 2010).
Different protein sources have been used for enzymatic hydrolysis, such as rice, egg
white protein and whey protein (Zhao et al, 2012; Naik et al., 2013; Hoppe et al., 2013).
However, these reports investigated enzymatic hydrolysis using separate substrates, and no
investigation using statistical mixture designs has been reported.
Mixture designs are a special class of response surface designs where the proportions of
the components or factors are considered important rather than their magnitude and are useful in
the design of mixtures. The interactions between the components of a mixture can be studied
using the mixture design approach aiming to maximize the response. Statistical methods have
been applied to different engineering problems to improve performance and to find the optimum
process variables (Rao and Baral, 2011).
In the present study, a simplex centroid mixture design was used to produce
hydrolysates from different protein sources by enzymatic hydrolysis to study the effects of these
mixtures on functional properties and antioxidant activities.
158
2. Materials and Methods
2.1. Reagents
Ammonium thiocyanate, ferrous chloride, linoleic acid, trichloroacetic acid (TCA), 2,2′-
azobis(2-methylpropionamidine) dihydrochloride (97%) (AAPH), fluorescein, (±)-6-hydroxy-
2,5,7,8-tetramethylchromane-2-carboxylic acid (Trolox) and 2,2-diphenyl-1-picrylhydrazyl
(DPPH) were purchased from Sigma-Aldrich (Steinheim, Germany). All other purchased
chemicals were of commercially available grade.
2.2. Preparation of protein hydrolysates
The soy protein isolate (SPI), bovine whey protein (BWP) and egg white protein (EWP)
used as the substrates for enzymatic hydrolysis were kindly provided by Bunge Foods S/A
(Gaspar, Brazil), Alibra Ingredients Ltd. (Campinas, Brazil) and Cooperovos (Mogi das Cruzes,
Brazil), respectively. The commercial protease, FlavourzymeTM
500L from Aspergillus oryzae
(Novozymes Latin America Ltd., Araucária, Brazil) was used for enzymatic hydrolysis. The
enzyme concentrations were adjusted to 0 (control) or 50 U per mL of reaction mixture according
to the previously determined protease activity. The proteins were suspended in a buffer to a final
concentration of 100 mg mL-1
, and 50-milliliter aliquots of the mixtures were distributed in 125
mL Erlenmeyer flasks. Hydrolysis was performed for 120 min at the optimum temperature and
pH value of the enzyme according to the supplier's information: 50 °C and pH 5.0. After
hydrolysis, the samples were incubated in a water bath at 100 °C for 20 min for protease
inactivation. The mixtures were centrifuged at 17,000 x g at 5 °C for 20 min, and the supernatants
containing the peptides were collected and freeze-dried for the determination of their antioxidant
activities, functional properties and TCA soluble protein contents.
The protein content in the freeze-dried supernatants was determined using the Biuret
method, and the results were expressed in milligrams of protein per grams of freeze-dried sample.
2.3. Statistical mixture design
The experimental mixture design was used to obtain the optimum mixture compositions
of the different protein sources for maximum antioxidant activity and to investigate the presence
of either synergistic or antagonistic effects in a blend of the components. A three component
augmented simplex centroid design was employed in which each component was studied at four
159
levels, namely 0 (0%), 1/3 (33%), 1/2 (50%) and 1 (100%) (Table 1). Quadratic or special cubic
regression models were fitted for the variations of all the responses studied as a function of
significant (p < 0.05) interaction effects between the proportions, thereby obtaining acceptable
determination coefficients (R² > 0.70). Equation 1 represents these models as follows:
where ‘Yi’ is the predicted response; ‘q’ represents the number of components in the system; ‘Xi,
Xj, Xk’ are the coded independent variables; ‘βi’ is the regression coefficient for each linear effect
term; and ‘βij’ and ‘βijk’ are the binary and ternary interaction effect terms, respectively.
StatisticaTM
10 software from Statsoft Inc. (Tulsa, Oklahoma, USA) was employed for the
experimental design, data analysis and model building.
To confirm the validity of the models, three assays were performed under randomly
selected test conditions, and the experimental values were compared with the predicted values by
the models within a 95% confidence interval.
2.4. TCA soluble protein content
The TCA soluble protein content of the hydrolysates was determined using a modified
version of the method described by Pericˇin et al. (2009). A 1.0 mL aliquot of the hydrolysate
was added to an equal volume of 0.44 mol L-1
trichloroacetic acid (TCA). The mixture was
incubated for 30 min at room temperature and then centrifuged at 17,000 x g for 15 min. A 0.22
mol L-1
TCA soluble protein fraction was obtained, and the supernatant of the hydrolysate
mixture (without the addition of TCA) was analyzed using the Lowry method (1951), which uses
bovine serum albumin as the standard protein to determine the protein content. The results were
expressed as a percentage and were calculated as the ratio of the 0.22 mol L-1
TCA soluble
protein content to the total protein content in the supernatant of the hydrolysate mixture.
2.5. Antioxidant activities
2.5.1. ORAC assay
The antioxidant activity of the hydrolysates was estimated by the ORAC method as
developed by Dávalos et al. (2004) and described by Macedo et al. (2011), which uses
𝑌𝑖 = 𝛽𝑖𝑋𝑖 + 𝛽𝑖𝑗
𝑞
𝑖<𝑗
𝑞
𝑖=1
𝑋𝑖𝑋𝑗 + 𝛽𝑖𝑗𝑘𝑋𝑖𝑋𝑗𝑋𝑘
𝑞
𝑖<𝑗<𝑘
??
160
fluorescein (FL) as the ‘‘fluorescent probe’’. The automated ORAC assay was performed using a
Novo Star MicroplateTM
reader (BMG LABTECH, Germany) with fluorescence filters for an
excitation wavelength of 485 nm and an emission wavelength of 520 nm. The measurements
were made in a COSTARTM
96 plate. The reaction was performed at 37 °C and was started by the
thermal decomposition of AAPH in a 75 mM phosphate buffer (pH 7.4) due to the sensitivity of
FL to the pH value. A solution of FL (0.4 µg mL-1
) in phosphate buffered saline (PBS) (75 mM;
pH 7.4) was prepared daily and stored in complete darkness. The reference standard was a 75 µM
Trolox solution prepared daily in distilled water, and the standard was diluted (1,500 - 1.5 µmol
L-1
) for the preparation of the Trolox standard curve. In each well, 120 µL of the FL solution was
mixed with either 20 µL of sample, distilled water (blank) or standard (Trolox solutions) before
adding 60 µL of AAPH (108 mg mL-1
). The fluorescence was measured immediately after the
addition of AAPH, and measurements were taken every minute for 75 min. The ORAC values
were calculated from the difference between the area under the FL decay curve and that of the
blank (net AUC). Regression equations for the net AUC and antioxidant concentration were
calculated for all samples. The ORAC values were expressed as µmol of Trolox equivalent g-1
of
protein hydrolysate (Trolox EQ µmol g-1
).
2.5.2. DPPH radical-scavenging activity
The DPPH radical-scavenging activity of the hydrolysates was determined as described
by Bougatef et al. (2009). An aliquot (500 µL) of each sample (5 mg mL-1
) was mixed with 500
µL of 99.5% ethanol and 125 µL of DPPH (0.2 mg mL-1
) in 99.5% ethanol. The mixture was
then kept at room temperature in the dark for 60 min, and the reduction of the DPPH radical was
measured at 517 nm using a UV-Visible spectrophotometer. The DPPH radical-scavenging
activity was calculated as follows (Equation 2):
Radical scavenging activity (%) = [(Absorbance of control - Absorbance of sample) /
(Absorbance of control)] * 100.
2.5.3. Inhibition of linoleic acid autoxidation
The lipid peroxidation inhibition activity was measured in a linoleic acid emulsion system
according to the method described by Nazeer and Kulandai (2012) with slight modifications. A
20 mg aliquot of each hydrolysate was dissolved in 10 mL of 50 mM phosphate buffer (pH 7.0)
and was later added to 130 µL of a linoleic acid solution and 10 mL of 99.5% ethanol. The total
161
volume was then adjusted to 25 mL with distilled water. The mixture was incubated in a 50-mL
assay tube with a screw cap at 42 ± 1 °C for 5 days in a dark room. The degree of oxidation of
linoleic acid was measured using the ferric thiocyanate method of Sakanaka et al. (2004) with
slight modifications. To 10 µL of the reaction mixture, 4.7 mL of 75% ethanol, 0.1 mL of 30%
ammonium thiocyanate and 0.1 mL of 20 mM ferrous chloride solution in 3.5% HCl were added.
After a 3-min incubation, the color development, which represents the linoleic acid oxidation,
was measured at 500 nm. The antioxidative capacity of inhibiting peroxide formation in the
linoleic acid system was expressed as follows: Inhibition (%) = [(Absorbance of control -
Absorbance of sample) / (Absorbance of control)] * 100.
2.6. Functional properties
2.6.1. Solubility
Protein solubility was determined according to a method described by Li et al. (2012)
with slight modifications. Solutions containing 100 mg of the protein hydrolysates were dispersed
in 10 mL of distilled water (pH 6.5 ± 0.3) at room temperature and centrifuged at 17000 x g for
10 min. The total protein content of the samples was determined by dissolving the sample in 0.5
mol L−1
NaOH and determining the protein content using the Biuret method. The protein
solubility was calculated as follows: solubility (%) = (protein content in supernatant / total
protein content in sample) × 100.
2.6.2. Heat stability
To determine the heat stability of the non-hydrolyzed proteins and their hydrolysates, 100
mg protein samples were dispersed in 10 mL of distilled water (pH 6.5 ± 0.3). After heating at
93 °C for 1 min, the solution was cooled in an ice water bath and centrifuged at 17,000 x g for 10
min. The protein content was determined using the Biuret method. The heat stability was
calculated as follows: stability (%) = (protein content in supernatant after heat treatment / total
protein content before the heat treatment) × 100.
2.6.3. Emulsifying property
The emulsifying property was measured using a modified version of the method described
by Pearce and Kinsella (1979). Vegetable oil (0.5 mL) and 1.5 mL aliquots of 10 mg mL−1
protein solutions were mixed and homogenized for 1 min. A 50 μL aliquot of the emulsion was
162
removed from the bottom of the container at 0 min after homogenization and mixed with 4.95 mL
of a 1 mg mL−1
sodium dodecyl sulfate (SDS) solution, and the absorbance was measured at 500
nm. The emulsifying activity index (EAI) was calculated as follows: EAI (m2 g
−1) = (2 × 2.303 ×
A500) / (0.25 × protein weight (g)).
2.6.4. Foaming capacity
Foaming capacity was measured using a modified version of the method described by
Klompong et al. (2007). Protein solutions (10 mL; 10 mg mL−1
) were homogenized for 1 min.
The foaming capacity, which was expressed as a percentage, was calculated as the ratio of the
volume after whipping (mL) to the volume before whipping (mL).
2.7. Calculations and statistics
The values were expressed as the arithmetic means. Tukey’s test was used to test for
significant differences between the groups analyzed, and the differences were considered to be
significant at p < 0.05.
163
3. Results and Discussion
3.1. Comparison of the functional properties between the intact proteins and their
hydrolysates
The results for all the parameters were evaluated from two points of view as follows: 1) a
comparative analysis of the functional properties, antioxidant activities and TCA soluble protein
contents of the hydrolyzed and non-hydrolyzed proteins in their respective runs of the statistical
mixture design to verify any changes caused by enzymatic hydrolysis; and 2) evaluation of the
synergistic or antagonistic interactions of the hydrolyzed proteins and their mixtures on the
functional properties, antioxidant activities and TCA soluble protein contents.
The effects of the interactions among the three substrates on the functional properties,
antioxidant activities and TCA soluble protein contents were studied for the 7 described assays
using a simplex centroid mixture design (Table 1). Selective enzymatic hydrolysis under
controlled conditions has been used to improve the solubility, heat stability, emulsifying
properties and foaming properties of proteins. However, the present study showed that enzymatic
hydrolysis increased protein solubility, except for EWP and its mixtures. Several other studies
have also shown that enzymatic hydrolysis increases solubility. This result may be due to the
decrease in molecular size of the protein creating small peptides and unfolding the protein
molecule leading to the exposition of more polar and ionizable groups on the protein surface,
which could improve the ability of the protein molecule to form hydrogen bonds with water,
thereby augmenting solubility. However, other studies have reported a decrease in solubility after
hydrolysis, which may occur when the protein molecule exposes more hydrophobic groups (Liu
et al., 2010). For most of the formulations evaluated, the hydrolysates exhibited a tendency to
decrease their foaming capacities and heat stability. In contrast, the emulsion activity index
showed increases of 61.4, 107.0 and 155.2% for the SPI (1/2) plus EWP (1/2) binary formulation,
BWP (1/2) plus EWP (1/2) binary formulation and the ternary mixture (SPI, BWP and EWP in
equal proportions), respectively. The presence of short peptides, as shown by the increase in TCA
soluble protein content, may be associated with the change in these functional properties. In
addition, although the small peptides have the ability to rapidly diffuse towards the interface, they
are less efficient in stabilizing emulsions because they do not readily agglomerate to produce a fat
globule membrane due to charge repulsion (Turgeon et al., 1991).
164
Table 1 - Matrix of the simple centroid mixture design used to study the functional properties and antioxidant activities of the different
protein sources and their hydrolysates obtained by enzymatic hydrolysis.
a, b, c...The results are presented as the mean (n = 3) ± SD, and those with different letters are significantly different, with p < 0.05. Tukey tests were applied between the runs for each
parameter (not between different parameters). x1 – soy protein isolate (SPI); x2 – bovine whey protein (BWP); x3 – egg white protein (EWP).
Mixture design Functional properties
Run
Independent
variables Solubility (%) Heat stability (%) Emulsion activity index (m² g
-1) Foaming capacity (%)
x1 x2 x3 Non-
hydrolyzed Hydrolysates Non-hydrolyzed Hydrolysates
Non-
hydrolyzed Hydrolysates
Non-
hydrolyzed Hydrolysates
1 1 0 0 11.19 ± 0.62a 99.17 ± 1.67
a 100.44 ± 2.30
a 100.49 ± 4.24
a 30.67 ± 0.09
a 4.26 ± 0.22
a 20.00 ± 5.00
b, c 22.50 ± 2.50
a
2 0 1 0 21.09 ± 1.02b 86.52 ± 4.00
b 101.90 ± 1.39
a 88.02 ± 1.64
b, c 15.31 ± 0.09
b 13.53 ± 0.07
b 0.00 ± 0.00
d 0.00 ± 0.00
b
3 0 0 1 82.14 ± 2.55c 26.92 ± 0.48
c 91.68 ± 1.15
d 86.56 ± 0.92
c 26.55 ± 0.09
c 27.41 ± 0.07
c 52.33 ± 2.52
a 37.50 ± 2.50
c
4 1/2 1/2 0 41.44 ± 1.58d 88.16 ± 3,50
b 95.01 ± 1.53
d 90.76 ± 4.13
b, c 14.62 ± 0.12
d 13.86 ± 0.09
b 0.00 ± 0.00
d 0.00 ± 0.00
b
5 1/2 0 1/2 89.53 ± 2.29e 39.27 ± 0.61
d 99.72 ± 1.66
a, b 94.78 ± 1.37
a, b 22.95 ± 0.07
e 37.05 ± 0.15
d 28.33 ± 2.89
b 27.50 ± 2.50
a
6 0 1/2 1/2 94.78 ± 1.84f 36.09 ± 2.01
d 81.41 ± 0.69
e 99.23 ± 1.90
a 23.95 ± 0.06
f 49.58 ± 0.07
e 45.00 ± 5.00
a 5.83 ± 1.44
d
7 1/3 1/3 1/3 86.99 ± 1.67c, e
49.46 ± 5.25e 96.15 ± 0.70
b, c 99.70 ± 2.59
a 22.19 ± 0.20
g 56.62 ± 0.06
f 12.33 ± 2.52
c 8.33 ± 1.44
d
Antioxidant activities
TCA soluble protein (%) Protein content in freeze-dried
supernatants (mg g-1
)
Run
ORAC (µmol Trolox EQ g-1
) DPPH radical scavenging (%) Inhibition of linoleic acid
autoxidation (%)
Non-
hydrolyzed Hydrolysates
Non-
hydrolyzed Hydrolysates
Non-
hydrolyzed Hydrolysates
Non-
hydrolyzed Hydrolysates
Non-
hydrolyzed Hydrolysates
1 229.54 ± 8.04a 1157.18 ± 134.66
a 27.18 ± 0.15
a 51.55 ± 0.56
a 24.95 ± 0.02
a 22.01 ± 0.15
a 30.70 ± 0.71
a 62.47 ± 1.91
a, c 525.0 ± 11.78
a 579.0 ± 11.97
b
2 52.64 ± 0.69e 160.72 ± 26.26
d 17.13 ± 2.33
b 29.81 ± 0.48
b 49.63 ± 0.06
b 3.99 ± 0.02
b 37.24 ± 1.63
b 56.70 ± 1.67
b 301.5 ± 17.74
b 679.1 ± 91.98
a
3 125.56 ± 4.39b 546.45 ± 55.75
b, c 33.39 ± 0.26
c 31.50 ± 0.24
b 65.72 ± 0.01
c 29.85 ± 0.03
c 16.42 ± 0.13
c 63.79 ± 2.78
a, c 896.1 ± 28.51
c 982.8 ± 15.29
c
4 90.71 ± 3.45c 530.02 ± 48.12
b, c 21.06 ± 0.10
d 38.53 ± 0.63
c 17.77 ± 0.01
d 2.55 ± 0.01
d 36.03 ± 0.99
b 65.07 ± 1.67
a 424.5 ± 15.44
d 548.6 ± 28.6
b
5 79.17 ± 1.63c, d
595.88 ± 80.74b 45.19 ± 1.86
e 47.84 ± 0.59
d 72.78 ± 0.01
e 32.68 ± 0.01
e 17.42 ± 0.24
c 61.72 ± 0.71
a, c 713.2 ± 21.95
e 742.6 ± 25.6
a
6 71.41 ± 0.41d 347.16 ± 64.81
c, d 29.41 ± 1.40
a 43.26 ± 0.94
e 47.95 ± 0.02
f 43.16 ± 0.04
f 16.99 ± 0.11
c 59.58 ± 2.06
b, c 605.9 ± 7.46
f 687.8 ± 12.38
a
7 82.96 ± 14.47c, d
403.33 ± 86.51b, c
36.60 ± 1.12c 35.42 ± 0.61
f 42.55 ± 0.06
g 27.59 ± 0.01
g 17.65 ± 0.12
c 62.28 ± 1.41
a, c 582.0 ± 12.69
g 639.6 ± 4.51
a
165
3.2. Comparison of the antioxidant activities between the intact proteins and their
hydrolysates
The results obtained in the ORAC and DPPH assays showed no significant correlation
(data not shown) because the ORAC and DPPH-scavenging assays have different reaction
mechanisms. The DPPH compound is a stable free radical that has an unpaired valence electron
on one atom of the nitrogen bridge, and it shows maximum absorbance at 517 nm in ethanol.
When DPPH encounters a hydrogen-donating substance, such as an antioxidant, the radical is
scavenged, and the absorbance is reduced. Scavenging of the DPPH radical is the basis of the
popular DPPH antioxidant assay (Guerard et al., 2007; Sharma and Bath, 2009). The ORAC
assay measures the antioxidant-scavenging activity against the peroxyl radical induced by AAPH
at 37 °C (Ou et al., 2001). This free radical causes damage to a fluorescent probe, thereby
decreasing the fluorescence intensity. The capacity of antioxidants to inhibit free radical damage
is measured as the degree of protection against the change in probe fluorescence in the ORAC
assay (Huang et al., 2002; Macedo et al., 2011). Thus, a report of higher ORAC activity does not
necessarily suggest greater DPPH-scavenging ability. In the ORAC assay, the SPI hydrolysates
showed an increase in antioxidant activity of up to 400% followed by the EWP (335.2%) and
BWP (205.3%) hydrolysates compared to the intact proteins. The increases were even greater in
the mixtures reaching up to 600% for the formulation containing SPI (1/2) and EWP (1/2)
compared to the intact protein mixture. In the DPPH assay, the SPI hydrolysates showed an
increase in antioxidant activity of up to 89.7% compared to the intact proteins followed by the
BWP hydrolysates (74.1%). However, the DPPH-radical scavenging of the EWP hydrolysates
and the intact proteins showed no statistically significant difference (p < 0.05). For the inhibition
of linoleic acid autoxidation, the enzymatic hydrolysis showed a negative impact because the
non-hydrolyzed proteins showed greater inhibition (%) than the hydrolysates. The formulation
containing SPI (1/2) and EWP (1/2) (non-hydrolyzed) (2 mg mL-1
) showed the maximum
inhibition of linoleic acid autoxidation reaching 72.78% after 5 days of storage at 42 °C.
3.3. Comparison of the TCA soluble protein content between the intact proteins and
their hydrolysates
The size of the peptides is known to be a significant factor in the overall antioxidant
activity and functional properties of protein hydrolysates. Proteolysis levels are often assessed by
166
global quantification of the soluble peptides in certain concentrations of trichloroacetic acid
(TCA). This parameter has been used as an indication of the amount of small peptides in protein
hydrolysates and has a positive correlation with the degree of hydrolysis (DH) (Zhou et al.,
2012b). As expected, the TCA soluble protein content of the hydrolysates showed significant
changes after enzymatic hydrolysis with increases in the values ranging from 52.2 (BWP) to
288.5% (EWP) compared to the intact proteins. In some studies, an increase in the TCA soluble
protein content of the protein hydrolysates increases the antioxidant activity. However, other
studies have reported a decrease in antioxidant activity with an increase in TCA soluble protein
content. During hydrolysis, peptides with antioxidant properties may be continuously formed and
degraded depending on their molecular structure, which is primarily affected by the hydrolysis
conditions (Vastag et al., 2010).
3.4. Synergistic effects and antagonistic effects of the intact proteins and their
hydrolysates on functional properties, antioxidant activities and TCA soluble protein
content
The analysis of the interaction between the different protein sources and their mixtures
after enzymatic hydrolysis showed synergistic and antagonistic effects. For functional properties,
most formulations containing the protein mixtures showed antagonistic effects, except for the
emulsion activity index, which showed a synergistic effect between the binary and ternary
mixtures. Increases of up to 12-, 4- and 2-fold were detected in the ternary mixture (run 7) (SPI,
BWP and EWP in equal proportions) compared to the respective isolated hydrolysates (runs 1, 2
and 3, respectively). Concerning to the antioxidant activities, the ORAC assay of the seven
formulations containing the SPI, BWP and EWP hydrolysates (alone or in combination) showed
an antagonistic effect for all the mixtures. The SPI hydrolysates showed the strongest antioxidant
activity reaching 1,157.18 µmol Trolox EQ g-1
. However, for the DPPH assays, the mixture
composed of BWP (1/2) plus EWP (1/2) (run 6) showed a synergistic effect with increases of
45.1 and 37.3% in DPPH-radical scavenging compared to the respective isolated hydrolysates
(runs 2 and 3, respectively). The TCA soluble protein content showed a similar profile in the 7
runs of the statistical mixture design ranging from 56.70 to 65.07%. The interactions among the
following formulations were not statistically significant (p < 0.05): SPI (1/2) plus EWP (1/2) (run
5), BWP (1/2) plus EWP (1/2) (run 6) and SPI, BWP and EWP (in equal proportions) (run 7)
(Table 1).
167
This study demonstrated that proteins, protein mixtures and their hydrolysates prepared
with FlavourzymeTM
500L showed different functional properties and antioxidant activities.
These differences could be attributed to the physicochemical characteristics, including size,
shape, amino acid composition, sequence, net charge, charge distribution,
hydrophobicity/hydrophilicity ratio, secondary structure, tertiary structure, quaternary structure,
molecular rigidity and molecular flexibility. Therefore, the enzymatic protein hydrolysates
obtained using binary or ternary mixtures of proteins may contain different concentrations and
compositions of peptides and free amino acids compared to the isolated substrates, which can be
associated to the synergistic or antagonistic effects. Marcuse (1962) and Liu et al. (2010)
reported that peptides containing certain amino acids, such as Tyr, Met, His, Lys, Gly and Trp,
can present antioxidant or prooxidative effects. Therefore, a variation in the levels of these amino
acids in the peptides in protein mixtures may result in higher (synergistic effect) or lower
(antagonistic effect) values of antioxidant activities. The emulsifying properties of soluble
proteins depend upon the hydrophilic/lipophilic balance, which is affected by the presence of
hydrophilic and hydrophobic groups in peptides. In the present study, synergistic effects were
observed when binary and ternary protein mixtures were used resulting in increased emulsion
activity indexes, which may be due to the appropriate balance and distribution of peptides with
hydrophobic and hydrophilic residues.
In addition, it is important to note that the simultaneous enzymatic hydrolysis of soy
protein isolate, bovine whey protein and egg white protein was investigated in the present study.
However, the process proposed in this study can be extended to other protein sources allowing
multifunctional hydrolysates to be obtained in a simplified combination process of proteins with
different physicochemical characteristics and chemical compositions for maximizing the
bioactivities using the statistical mixture designs.
Intarasirisawat et al. (2012) studied the antioxidative and functional properties of
protein hydrolysates from defatted skipjack tuna (Katsuwonous pelamis) roe hydrolyzed by
AlcalaseTM
2.4 L with different degrees of hydrolysis (DH 5-50%) using different assays (DPPH
radical-scavenging, ABTS radical-scavenging and superoxide anion radical-scavenging activities
as well as reducing power and chelating capacity). The results showed that the DPPH radical-
scavenging and ABTS radical-scavenging activities as well as the reducing power decrease with
increasing DH. In contrast, the metal-chelating activity and superoxide-scavenging activity
168
increase with increasing DH. With regard to the functional properties, enzymatic hydrolysis
increases the protein solubility to above 80%. However, the highest emulsion activity indexes and
foam stabilities of the hydrolysates are observed at low DH (5%). Liu et al. (2010) investigated
the functional properties of porcine blood plasma protein hydrolysates prepared with AlcalaseTM
at 6.2, 12.7 and 17.6% degrees of hydrolysis (DH), and they reported that hydrolysis increases
the protein solubility and decreases the emulsifying and foaming capacities of the plasma protein.
Zhou et al. (2012b) studied the antioxidant activities of hydrolysates prepared from sea urchin
(Strongylocentrotus nudus) gonads using DPPH radical-scavenging activity, reducing power,
hydroxyl radical-scavenging activity, hydrogen peroxide-scavenging activity, lipid peroxidation-
inhibiting activity and Fe2+
-chelating activity, and they observed the highest values for protein
hydrolysates with TCA soluble protein contents of up to 50%.
3.5. Mixture contour plots for functional properties, antioxidant activities and TCA
soluble protein contents
The variations in the functional properties and antioxidant activities of the hydrolysates
obtained from SPI, BWP and EWP were also depicted using mixture contour plots (Fig. 1 and
Fig. 2). On the response surfaces, each factor (pure mixture component) is represented in the
corner of an equilateral triangle, and each point within this triangle refers to a different proportion
of the components in the mixture. The maximum percentage of each ingredient considered by the
regression is placed at the corresponding corner, and the minimum percentage is positioned at the
middle of the opposite side of the triangle (Martinello et al., 2006). A contour plot provides a
two-dimensional view where all points that have the same response are connected to produce
contour lines of constant responses (Rao and Baral, 2011).
For the functional properties, high solubility was detected in the SPI hydrolysates with
values up to 90%. However, the zones of maximum response variables for heat stability were
located towards the side of the triangle having mixtures of SPI/EWP or BWP/EWP on the
vertices (Fig. 1). These results indicated that to certain extent, these protein proportions may be
added to improve the heat stability of the hydrolysates. The EWP hydrolysates showed the
maximum foaming capacity. The emulsion activity index showed more possibilities of mixture
applications to maximize the response variable. The addition of equal proportions of SPI, BWP
and EWP helped to improve the response variables reaching values up to 50 m² g-1
. The
169
antioxidant activities evaluated in the ORAC and DPPH-radical scavenging assays showed
similar profiles with maximum responses detected in the SPI hydrolysates. However, the
inhibition of linoleic acid autoxidation was greater in the hydrolysates prepared with mixtures of
BWP and EWP reaching values up to 40%. High TCA soluble protein contents were observed in
the mixtures containing SPI and BWP, which was verified by the mixture surface plots (Fig. 2).
Fig. 1 - Mixture contour plots for the functional properties (a: solubility; b: heat stability; c:
foaming capacity; d: emulsion activity index) of the protein hydrolysates.
> 90 < 90 < 80 < 70 < 60 < 50 < 40 < 30
0.00
0.25
0.50
0.75
1.00
EWP0.00
0.25
0.50
0.75
1.00
SPI
0.00 0.25 0.50 0.75 1.00
BWP
> 99 < 99 < 97 < 95 < 93 < 91 < 89 < 87
0.00
0.25
0.50
0.75
1.00
EWP0.00
0.25
0.50
0.75
1.00
SPI
0.00 0.25 0.50 0.75 1.00
BWP
> 35 < 35 < 30 < 25 < 20 < 15 < 10 < 5
0.00
0.25
0.50
0.75
1.00
EWP0.00
0.25
0.50
0.75
1.00
SPI
0.00 0.25 0.50 0.75 1.00
BWP
> 50 < 50 < 40 < 30 < 20 < 10
0.00
0.25
0.50
0.75
1.00
EWP0.00
0.25
0.50
0.75
1.00
SPI
0.00 0.25 0.50 0.75 1.00
BWP
c
a b
d
170
Fig. 2 - Mixture contour plots for the antioxidant activities (a: ORAC; b: DPPH; c: inhibition of
linoleic acid autoxidation (%)) and TCA soluble protein (d) of the protein hydrolysates.
3.6. Analysis of variance (ANOVA) and models for the functional properties, antioxidant
activities and TCA soluble protein contents of the intact proteins and their
hydrolysates
The response data based on the independent variables was obtained from the experiments
and recorded in Table 1. The experiments were conducted with triplicates. In almost all cases, a
good agreement existed between the original and triplicates. All the independent and response
variables were fitted to quadratic or special cubic models. The coefficient of determination (R2)
and the F-test (analysis of variance; ANOVA) were used to verify the quality of fit of the models.
Table 2 shows the models and corresponding R2, F-test and p-values of the regression equations
for the responses.
a b
d c
> 1000 < 1000 < 800 < 600 < 400 < 200
0.00
0.25
0.50
0.75
1.00
EWP0.00
0.25
0.50
0.75
1.00
SPI
0.00 0.25 0.50 0.75 1.00
BWP
> 50 < 50 < 46 < 42 < 38 < 34 < 30
0.00
0.25
0.50
0.75
1.00
EWP0.00
0.25
0.50
0.75
1.00
SPI
0.00 0.25 0.50 0.75 1.00
BWP
> 40 < 40 < 35 < 30 < 25 < 20 < 15 < 10 < 5
0.00
0.25
0.50
0.75
1.00
EWP0.00
0.25
0.50
0.75
1.00
SPI
0.00 0.25 0.50 0.75 1.00
BWP
> 65 < 65 < 63 < 61 < 59 < 57
0.00
0.25
0.50
0.75
1.00
EWP0.00
0.25
0.50
0.75
1.00
SPI
0.00 0.25 0.50 0.75 1.00
BWP
171
Table 2 - Models, R2, and probability values for the final reduced models of the functional properties and antioxidant activities.
Responses Models Equations (non-hydrolyzed proteins) F-test R² p-value
Solubility (%) Quadratic Y = 11.23x1 + 21.13x2 + 82.18x3 + 100.35x1x2 + 170.58x1x3 + 171.80x2x3 526.6 0.99 <0.001
Heat stability (%) Special cubic Y = 101.66x1 + 98.88x2 + 92.90x3 – 21.05x1x2 – 57.94x2x3 + 191.96x1x2x3 5.7 0.85 <0.001
Emulsion activity index (m² g-1) Special cubic Y = 30.67x1 + 15.31x2 + 26.55x3 – 33.49x1x2 – 22.64x1x3 + 12.08x2x3 + 78.55x1x2x3 2,686.6 0.99 <0.001
Foaming capacity (%) Special cubic Y = 20.00x1 + 52.33x3 – 40.00x1x2 – 31.33x1x3 + 75.33x2x3 – 330.00x1x2x3 44.1 0.98 <0.001
ORAC (µmol Trolox EQ g-1) Special cubic Y = 229.54x1 + 52.64x2 + 125.56x3 – 201.52x1x2 – 393.52x1x3 – 70.75x2x3 + 567.71 x1x2x3 84.2 0.99 <0.001
DPPH radical scavenging (%) Special cubic Y = 26.81x1 + 16.76x2 + 33.40x3 + 60.35x1x3 + 17.33x2x3 + 62.34x1x2x3 62.3 0.98 <0.001
Inhibition of linoleic acid
autoxidation (%) Special cubic Y = 24.95x1 + 49.63x2 + 65.72x3 – 78.07x1x2 + 109.80x1x3 – 38.91x2x3 – 92.41x1x2x3 416,715.7 0.99 <0.001
TCA soluble protein (%) Special cubic Y = 30.70x1 + 37.24x2 + 16.42x3 + 8.25x1x2 – 24.55x1x3 – 39.35x2x3 – 115.61x1x2x3 215.3 0.99 <0.001
Equations (hydrolysates)
Solubility (%) Quadratic Y = 99.14x1 + 86.49x2 + 26.89x3 – 18.16x1x2 – 94.53x1x3 – 81.98x2x3 101.6 0.99 <0.001
Heat stability (%) Quadratic Y = 100.33x1 + 86.86x2 + 87.30x3 + 52.75x2x3 6.4 0.80 <0.001
Emulsion activity index (m² g-1) Special cubic Y = 4.26x1 + 13.53x2 + 27.41x3 + 19.86x1x2 + 84.87x1x3 + 116.44x2x3 + 458.51x1x2x3 29,255.8 0.99 <0.001
Foaming capacity (%) Quadratic Y = 21.63x1 + 36.63x3 – 44.29x1x2 – 50.96x2x3 86.5 0.98 <0.001
ORAC (µmol Trolox EQ g-1) Quadratic Y = 1,160.81x1 + 156.15x2 + 541.89x3 – 572.01x1x2 – 1,080.05x1x3 20.4 0.95 <0.001
DPPH radical scavenging (%) Special cubic Y = 51.55x1 + 29.81x2 + 31.49x3 – 8.62x1x2 + 25.27x1x3 + 50.42x2x3 – 260.64x1x2x3 191.6 0.99 <0.001
Inhibition of linoleic acid
autoxidation (%) Special cubic Y = 22.01x1 + 3.99x2 + 29.85x3 – 41.78x1x2 + 26.99x1x3 + 104.94x2x3 – 28.18x1x2x3 59,133.3 0.99 <0.001
TCA soluble protein (%) Quadratic Y = 62.00x1 + 56.51x2 + 63.05x3 + 22.04x1x2 5.9 0.70 <0.001
172
The high coefficients of determination (R2), which were greater than 0.70 (Table 2),
indicated that all the response functions adequately fitted the experimental data and that the
models could be used for predictive purposes in the determination of the functional properties,
antioxidant activities and TCA soluble protein contents using the different protein sources and
their mixtures.
Validation tests were performed to determine the accuracy of the polynomial models
obtained for the functional properties and antioxidant activities of the different protein sources
and their hydrolysates using different formulations with three assays (Table 3). According to the
regression models (Table 2), the experimental values agreed with the values predicted by the
models within a 95% confidence interval, thereby confirming the validity of the models for the
evaluated responses (Table 3).
Table 3 - Validation tests performed to determine the adequacy of the polynomial models
obtained for the functional properties and antioxidant activities of the different protein sources
and their hydrolysates in different formulations.
Results are presented as the mean (n = 3) ± SD, and those with different letters are significantly different, with p < 0.05.
Comparisons were made between the observed and predict values for each correspondent response.
Responses
Non-hydrolyzed proteins
Independent variables Predicted
response
Experimental
response x1 (SPI) x2 (BWP) x3 (EWP)
Solubility (%) 0.66 0.17 0.17 60.34a 58.28 ± 2.18
a
Heat stability (%) 0.17 0.66 0.17 93.13b 94.62 ± 1.95
b
Emulsion activity index (m² g-1
) 0.17 0.17 0.66 24.68c 23.85 ± 1.32
c
Foaming capacity (%) 0.17 0.17 0.66 35.42d 32.50 ± 3.53
d
ORAC (µmol Trolox EQ g-1
) 0.66 0.17 0.17 123.81e 130.90 ± 7.93
e
DPPH radical scavenging (%) 0.17 0.66 0.17 26.17f 24.45 ± 2.87
f
Inhibition of linoleic acid autoxidation (%) 0.17 0.17 0.66 59.99g 58.41 ± 5.21
g
TCA soluble protein (%) 0.66 0.17 0.17 24.21h 24.95 ± 3.23
h
Hydrolysates
Solubility (%) 0.66 0.17 0.17 69.69i 68.92 ± 2.48
i
Heat stability (%) 0.33 0.33 0.34 97.37j 99.48 ± 3.62
j
Emulsion activity index (m² g-1
) 0.34 0.33 0.33 56.37l 56.92 ± 0.97
l
Foaming capacity (%) 0.17 0.17 0.66 20.86m 19.75 ± 2.77
m
ORAC (µmol Trolox EQ g-1
) 0.66 0.17 0.17 699.44n 641.56 ± 86.55
n
DPPH radical scavenging (%) 0.66 0.17 0.17 42.79o 42.12 ± 3.35
o
Inhibition of linoleic acid autoxidation (%) 0.17 0.17 0.66 37.18p 40.99 ± 4.23
p
TCA soluble protein (%) 0.33 0.34 0.33 62.95q 61.07 ± 2.85
q
173
4. Conclusions
The results suggested that the application of statistical mixture designs for the enzymatic
hydrolysis of different protein sources is an attractive process for improving their performance
and for finding the optimum mixture formulations of proteins with specific characteristics. The
maximum increases in antioxidant activities were observed in the formulations containing SPI
(1/2) and EWP (1/2) reaching up to 600%. Synergistic effects between the formulations
containing binary or ternary mixtures were observed for several parameters, especially for the
DPPH-radical scavenging and emulsion activity indexes, which showed increases of up to 45 and
1,200%, respectively, in their activities after enzymatic hydrolysis compared to the isolated
substrates. The functional properties of the hydrolysates, such as high solubility, suggested that
the hydrolysates could have wider applications in formulated food systems.
Acknowledgments
The authors gratefully acknowledge the São Paulo Research Foundation (FAPESP;
Project No. 2011/10429-9) and the Department of Food Science, School of Food Engineering,
University of Campinas for the substantial grants received.
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177
Capítulo VIII: Synergistic effects of protein hydrolysates on the suppression of
lipid accumulation in 3T3-L1 adipocytes
Revista: LWT Food Science and Technology
178
Abstract
Soy protein isolate (SPI), bovine whey protein (BWP) and egg white protein (EWP) were
hydrolyzed with the protease FlavourzymeTM
500L, and the interactions of these substrates for
the inhibition of the relative lipid accumulation (RLA) in 3T3-L1 preadipocytes during
differentiation was studied using a simplex-centroid mixture design. The results indicated that
there were synergistic effects for mixtures of intact and hydrolyzed proteins. The hydrolyzed
mixture containing BWP (1/2) plus EWP (1/2) at 800 ppm showed increases of up to 220 and
27% in their activities, respectively, compared to the isolated substrates, reaching a maximum
RLA suppression of 15.5%. The treatment in which the two-day postconfluent 3T3-L1
preadipocytes received 1200 ppm of the mixture containing BWP (1/2) plus EWP (1/2) at day
zero and every two days afterwards until the end of the experiment at day eight was demonstrated
to be more effective, reaching an RLA suppression of 47.9%. The results from the fractionation
by ultrafiltration indicated that the non-fractionated sample of BWP (1/2) and EWP (1/2) was the
most active for the anti-adipogenic activity and indicated that there is an important contribution
of peptide fractions with various molecular sizes in the inhibition of lipid accumulation in 3T3-
L1 cells.
Keywords: protein hydrolysates; synergistic effects; anti-adipogenic activity
179
1. Introduction
Bioactive peptides can be defined as specific amino-acid sequences that promote
beneficial biological activities. The size of active sequences may vary from 2 to 20 amino acid
residues, and many peptides are known to reveal multi-functional properties, such as antioxidant,
anti-adipogenic, antihypertensive and antimicrobial activities. In general, these bioactive peptides
are inactive within the sequence of parent protein and can be released by limited and controlled
hydrolysis using digestive, microbial and plant enzymes (Korhonen, 2009; Chen, Chi, Zhao &
Xu, 2012).
Accumulation of body fat arises from a chronic imbalance between energy acquisition and
expenditure that may lead to a pathologic growth of adipocytes, characterized by increased fat-
cell size and number (Shimomura, Hammer, Richardson, Ikemoto & Bashmakov, 1998; Mejia,
Martinez-Villaluenga, Roman & Bringe, 2010). It is known that the amount of adipose tissue can
be regulated by the inhibition of adipogenesis from precursor cells (Rahman et al., 2008).
Preadipocytes that do not yet contain a significant amount of lipid and resemble fibroblasts can
be cultured, and after differentiation is induced, the cell cultures may be used for metabolic
studies (Poulos, Dodson & Hausman, 2010). The preadipocyte differentiation can be stimulated
by treatment with adipogenic agents, including 3-isobutyl-1-methylxanthine, dexamethasone and
insulin, which induces postconfluent mitotic clonal expansion and begins to express adipocyte-
specific genes (Rubin, Hirsch, Fung & Rosen, 1978; Tsou, Kao, Tseng & Chiang, 2010). The
mature adipocytes contain single, large lipid droplets that appear to comprise the majority of the
cell volume and can be quantified as intracellular lipid or triglyceride content by staining with Oil
Red O (Green & Kehinde, 1975; Poulos, Dodson & Hausman, 2010). Thus, determining the
relative lipid accumulation in preadipocyte cells during differentiation could be used as a
convenient tool to evaluate the anti-adipogenesis effects of protein hydrolysates. The 3T3-L1
preadipocytes are one of the most well characterized and reliable models for studying
adipogenesis (Tsou, Kao, Tseng & Chiang, 2010). Several studies reported the reduction in body
fat and food intake when proteins were hydrolyzed into bioactive peptides (Martinez-Villaluenga,
Bringe, Berhow & Mejia, 2008; Tsou, Lin, Lu, Tsui & Chiang, 2010).
In the past decade, the enzymatic hydrolysis of proteins from animal and plant sources for
the production of bioactive peptides has attracted much attention. Among the biological
180
activities, the anti-adipogenic effects have been reported. In the literature, various protein sources
have been used for the enzymatic hydrolysis, such as rice, egg white protein and whey protein
(Zhao et al., 2012; Naik, Mann, Bajaj, Sangwan & Sharma, 2013; Hoppe, Jung, Patnaik & Zeece,
2013). However, these reports show many studies on enzymatic hydrolysis using distinct
substrates; no investigations were found using formulations containing mixtures of different
protein sources.
Mixture design is a special class of response surface design in which the proportions of
the components or factors are considered important, rather than their magnitude, and are useful in
the mixture design. The interactions between the components of a mixture for maximizing the
response are studied using a mixture-design approach. Statistical methods were applied to various
engineering problems to improve the performance and to find the optimum process variables
(Rao & Baral, 2011).
In this study, a simplex-centroid mixture design was used for the production of
hydrolysates of various protein sources by enzymatic hydrolysis, and the effects on the inhibition
of the relative lipid accumulation (RLA) in 3T3-L1 preadipocytes during differentiation were
studied. The effect of different fractions of the protein hydrolysates obtained by ultrafiltration on
RLA suppression in 3T3-L1 preadipocytes was also investigated.
2. Materials and Methods
2.1. Reagents
FlavourzymeTM
500L, 3-isobutyl-1-methylxanthine, water-soluble dexamethasone,
insulin, Oil Red O, sodium dodecyl sulfate (SDS) and trichloroacetic acid (TCA) were purchased
from Sigma-Aldrich (Steinheim, Germany). All other chemicals were purchased in the grade
commercially available.
2.2. Preparation of protein hydrolysates
Soy protein isolate (SPI), bovine whey protein (BWP) and egg white protein (EWP) were
used as substrates for enzymatic hydrolysis. The commercial protease FlavourzymeTM
500L from
Aspergillus oryzae was used for enzymatic hydrolysis. The protease activity was determined
using azocasein as the substrate, as described by Castro & Sato (2013). The enzyme
concentrations were adjusted to zero (control) and 50 U per mL of reaction, according to the
181
protease activity, as previously determined. The proteins were suspended in a 200-mM acetate
buffer at pH 5.0 to a final concentration of 100 mg mL-1
. Fifty-milliliter aliquots of the mixtures
were distributed in 125-mL Erlenmeyer flasks, and the hydrolysis was performed under the
optimum temperature and pH of the enzyme (50 °C, pH 5.0) for 120 min. After hydrolysis, the
samples were incubated in a water bath at 100 °C for 20 min for protease inactivation. The
mixtures were centrifuged at 17,000 x g and 5 °C for 20 min, and the supernatants containing
peptides were collected and freeze-dried for the determination of the TCA-soluble protein and the
suppression of the relative lipid accumulation (RLA) in the 3T3-L1 preadipocytes.
2.3. Statistical mixture design
The mixture design of the experiment was used to obtain the optimal mixture composition
of the various protein sources for the maximal inhibition of the relative lipid accumulation (RLA)
in 3T3-L1 preadipocytes during differentiation and to investigate the presence of either
synergistic or antagonistic effects in a blend of components. A three-component augmented
simplex-centroid design has been employed, in which each component is studied in four levels,
namely 0 (0%), 1/3 (33%), 1/2 (50%) and 1 (100%) (Table 1). Quadratic- or special-cubic-
regression models were fitted for variations of all of the studied responses as a function of the
significant (p < 0.05) interaction effects between the proportions, with acceptable determination
coefficients (R² > 0.70). Equation 1 represents these models:
where ‘Yi’ is the predicted response; ‘q’ represents the number of components in the system; ‘Xi,
Xj, Xk’ are the coded independent variables; ‘βi’ is the regression coefficient for each linear effect
term; and ‘βij’ and ‘βijk’ are the binary and ternary interaction effect terms, respectively.
StatisticaTM
10 software from Statsoft Inc. (Tulsa, Oklahoma, USA) was employed for the
experimental design, data analysis and model building.
To confirm the validity of the models, three assays were performed under randomly
selected test conditions, and the experimental values were compared with the predicted values by
the models within a 95% confidence interval.
𝑌𝑖 = 𝛽𝑖𝑋𝑖 + 𝛽𝑖𝑗
𝑞
𝑖<𝑗
𝑞
𝑖=1
𝑋𝑖𝑋𝑗 + 𝛽𝑖𝑗𝑘𝑋𝑖𝑋𝑗𝑋𝑘
𝑞
𝑖<𝑗<𝑘
??
182
2.4. Determination of the TCA-soluble protein
The TCA-soluble protein of the hydrolysates was determined with a modified version of
the method described by Pericˇin, Radulovic´-Popovic´, Vaštag, Madarev-Popovic´ & Trivic,
2009. A 1.0 mL aliquot of the protein hydrolysates was added to an equal volume of 0.44 mol L-1
trichloroacetic acid (TCA). The mixture was incubated for 30 min at room temperature. Then, the
mixture was centrifuged at 17,000 x g for 15 min. The obtained 0.22 mol L-1
TCA-soluble protein
fraction and the supernatant of the hydrolysate mixture (without the addition of TCA) were each
analyzed to determine the protein content using the Lowry method (Lowry, Rosenbrough & Fair,
1951), which uses bovine serum albumin as the standard protein. The TCA-soluble protein value,
expressed as a percentage, was calculated as the ratio of 0.22 mol L-1
TCA-soluble protein to the
total protein in the supernatant of the hydrolysate mixture. The assays were performed with four
replicates.
2.5. Inhibition of the relative lipid accumulation in the 3T3-L1 adipocytes
2.5.1. Cell culture
The 3T3-L1 preadipocytes (Rio de Janeiro Cell Bank, Rio de Janeiro, Brazil) were seeded
in a 24-well plate at a density of 103 cells/well. The cells were grown in Dulbecco's Modified
Eagle's Medium (DMEM) supplemented with 10% fetal bovine serum (FBS) at 37 °C in a 5%
CO2 humidified atmosphere. To induce preadipocytes differentiation, two days after reaching
100% confluence, the cells were stimulated for 48 h with 0.5 mM 3-isobutyl-1-methylxanthine,
0.1 µM dexamethasone, and 10 µg mL-1
insulin in DMEM supplemented with 10% FBS
(differentiation medium). Then, the preadipocytes were maintained and were fed every two days
with DMEM supplemented with 10% FBS and 10 µg mL-1
insulin (maturation medium) for an
additional eight days. For selection of the samples with the highest inhibition of the relative lipid
accumulation (RLA), the cells received 800 ppm of the intact or hydrolyzed proteins two days
postconfluence for 48 h and were fed two days with maturation medium for an additional eight
days. The control assays were performed using the cultivation medium without the protein
samples. The assays were performed in three replicates.
2.5.2. Assay for the relative lipid accumulation (RLA)
On day eight after differentiation, 3T3-L1 cells were stained with Oil Red O to determine
the intracellular lipid or triglyceride content (Green & Kehinde, 1975). The cells were fixed with
183
10% formaldehyde for 1 h at room temperature. After fixation, the cells were washed twice with
distilled water and twice with 60% isopropanol and allowed to air-dry. Then, the cells were
stained using 0.3% Oil Red O in isopropanol for 10 min at room temperature. After being stained
with Oil Red O lipid, the cells were washed with distilled water four times and were air-dried.
The Oil Red O dye-lipids complex was eluted by adding 100% isopropanol after 10 min of
incubation at room temperature. The absorbance of the complex was measured at 520 nm and
expressed as RLA (%): [(Ac-As)/(Ac)]×100, where Ac denotes the absorbance of the control cell
culture and As denotes the absorbance of the treated cell culture. The RLA suppression (%) was
calculated as follows: RLA suppression (%) = RLA (%) in the control assay - RLA (%) in the test
assay. The RLA (%) in the control assay was considered to be 100%.
2.5.3. Effect of the concentration of the protein hydrolysates and various treatments on the
RLA.
The protein hydrolysates with major RLA suppression at 800 ppm were evaluated at
various concentrations (from 400 to 1400 ppm). The assays were performed as described in
Section 2.5.1.
Two treatments were employed to examine the effect of the hydrolysates on the RLA
during preadipocyte differentiation. For treatment 1, the two-day postconfluent 3T3-L1
preadipocytes received 1200 ppm of the hydrolysates only at day zero during the early phase of
differentiation. For treatment 2, the two-day postconfluent 3T3-L1 preadipocytes received 1200
ppm of the protein hydrolysates at day zero and every two days afterwards until the end of the
experiment at day eight (from day zero to day eight). The assays were performed in three
replicates.
2.5.4. Fractionation of the hydrolysates by ultrafiltration
The hydrolysates with the highest stimulator effects on the inhibition of the relative lipid
accumulation (RLA) were subjected to ultrafiltration to assess the partitioning of active
compounds. The fractionation was performed in a series of centrifugal ultrafiltration filters with
molecular weight cut-off (MWCO) membranes of 30, 10 and 3 kDa (Millipore CorporationTM
Ultrafiltration Membranes, Billerica, USA). The effect of the fractions on the RLA (%) was
determined only using a cell culture with treatment 2. The assays were performed in three
replicates.
184
2.6. Calculations and statistics
The statistical analyses were performed using the MinitabTM
16.1.1 software package
from Minitab Inc. (USA). The values were expressed as the arithmetic mean. The Tukey test was
used to test for significant differences between the groups analyzed. The differences were
considered significant at p < 0.05.
The Pearson correlation coefficient was used to measure the strength of the linear
dependence between the two responses. The correlation coefficient ranges from - 1 to 1. A value
of 1 implies that a linear equation describing the relationship between the responses was perfect
and positive, and a value of -1 indicate a perfect and negative correlation. A value of zero implies
that there is no linear correlation between the responses. The correlations between the analyzed
parameters were considered significant when p < 0.10.
3. Results and Discussion
3.1. Comparative analysis of the TCA-soluble protein and the RLA (%) between the
intact proteins and their hydrolysates.
The results for all of the parameters were evaluated according to two points of view: 1)
comparative analysis of the TCA-soluble protein and the RLA (%) in 3T3-L1 preadipocytes
treated with hydrolyzed and non-hydrolyzed proteins in respective runs of the statistical-mixture
design to verify the changes caused by the enzymatic hydrolysis and 2) evaluation of the
synergistic or antagonistic interactions of the hydrolyzed and non-hydrolyzed proteins and their
mixtures on the TCA-soluble protein and the RLA (%).
The interactions among the three substrates in the TCA-soluble protein and the RLA (%)
were studied in the seven assays using a simplex-centroid mixture design (Table 1). The size of
the peptides is known to be a significant factor in the overall bioactivities and functional
properties of protein hydrolysates. The assessment of proteolysis levels is often achieved by
global quantification of the peptides soluble at certain concentrations of trichloroacetic acid
(TCA). This parameter has been used as an indication for the amount of small-sized peptides in
the protein hydrolysates and has a positive correlation with the degree of hydrolysis (DH) (Zhou
et al., 2012). As expected, the TCA-soluble protein of the hydrolysates showed significant
185
changes after the enzymatic hydrolysis with increased values ranging from 52.2% (BWP) to
288.5% (EWP) compared to intact proteins (Table 1).
After enzymatic hydrolysis, the mixture containing BWP (1/2) and EWP (1/2) showed the
highest increase in the RLA suppression (258.6%), followed by EWP (84.9%) and SPI (20.6%)
mixture compared to the intact proteins (Table 1). However, the mixtures containing SPI (1/2)
plus BWP (1/2) and SPI (1/2) plus EWP (1/2) showed a decrease in the RLA suppression after
enzymatic hydrolysis. The Pearson coefficient indicates a positive correlation between the TCA-
soluble protein and the RLA (%) (Pearson coefficient = 0.64; p = 0.12).
3.2. Synergistic and antagonistic effects of the intact proteins and their hydrolysates on
the TCA-soluble protein and the RLA (%)
The analysis of the interaction between the various protein sources and their mixtures
after enzymatic hydrolysis showed synergistic and antagonistic effects. The TCA-soluble protein
showed a similar profile in the seven runs of the statistical-mixture design, ranging from 56.70 to
65.07%. Interactions between the formulations: SPI (1/2) plus EWP (1/2) (run 5), BWP (1/2) plus
EWP (1/2) (run 6) and SPI, BWP and EWP (in equal proportions) (run 7) were not statistically
significant (p < 0.05).
For RLA suppression (%), synergistic effects were observed for mixtures of intact and
hydrolyzed proteins. The mixture containing BWP (1/2) plus EWP (1/2) hydrolysates (run 6)
showed increases of up to 220 and 27% in their activities compared to those of the isolated
substrates (runs 2 and 3) after enzymatic hydrolysis, reaching a maximum RLA suppression of
15.5%. The mixture of intact proteins in equal proportions of SPI and BWP (run 4) showed RLA
suppressions of 14.1%, indicating a synergistic effect between these proteins sources, with
increases of 81.1 and 195.6%, respectively, compared to the values for the isolated substrates
(runs 1 and 2).
186
Table 1 - Matrix of the simplex-centroid mixture design for study of the suppression of the relative lipid accumulation (RLA%) and
the RLA suppression (%) of various protein sources and their hydrolysates obtained by enzymatic hydrolysis and results for the TCA-
soluble protein (%).
a, b, c...Results are presented as the mean (n = 3) ± SD, and those with different letters are significantly different, with p < 0.05. Tukey tests were applied between the runs for each
response.
Mixture design TCA-soluble protein (%) RLA (%) RLA suppression (%)
Runs
Independent variables
x1
(SPI)
x2
(BWP)
x3
(EWP) Non-hydrolyzed Hydrolysates Non-hydrolyzed Hydrolysates Non-hydrolyzed Hydrolysates
1 1 0 0 30.70 ± 0.71a 62.47 ± 1.91
a, c 92.20 ± 2.67
a, b, c 90.59 ± 1.96
b, c 7.80 ± 2.67
a, b, c 9.41 ± 1.96
b, c
2 0 1 0 37.24 ± 1.63b 56.70 ± 1.67
b 95.22 ± 0.31
a 95.20 ± 2.34
b 4.78 ± 0.31
c 4.80 ± 2.34
c
3 0 0 1 16.42 ± 0.13c 63.79 ± 2.78
a, c 93.42 ± 2.45
a, b 87.83 ± 2.24
c, d 6.58 ± 2.45
b, c 12.17 ± 2.24
a, b
4 1/2 1/2 0 36.03 ± 0.99b 65.07 ± 1.67
a 85.87 ± 4.17
c 103.81 ± 0.67
a 14.13 ± 4.17
a -3.81 ± 0.67
d
5 1/2 0 1/2 17.42 ± 0.24c 61.72 ± 0.71
a, c 86.61 ± 3.01
b, c 93.71 ± 2.03
b, c 13.39 ± 3.01
a, b 6.29 ± 2.03
b, c
6 0 1/2 1/2 16.99 ± 0.11c 59.58 ± 2.06
b, c 95.66 ± 2.92
a 84.46 ± 1.17
d 4.34 ± 2.92
c 15.54 ± 1.17
a
7 1/3 1/3 1/3 17.65 ± 0.12c 62.28 ± 1.41
a, c 88.82 ± 0.48
a, b, c 89.70 ± 3.39
b, c, d 11.18 ± 0.48
a, b, c 10.30 ± 3.39
a, b, c
187
The limited hydrolysis of dietary proteins may give rise to particularly interesting
functional, organoleptic food properties, and it was required to maintain the structure or sequence
of the active peptides. Several studies have indicated that hydrolysis led to a reduction or increase
in the specific functionality, as was observed in our study. Tsou, Kao, Tseng & Chiang, (2010)
studied the effect of soy protein hydrolyzed with FlavourzymeTM
with DH 5.46–17.86% on the
suppression of the RLA in 3T3-L1 preadipocytes and showed that extensive hydrolysis (DH >
8.06%) resulted in a decrease of the RLA inhibition. Tsou, Lin, Lu, Tsui & Chiang (2010)
evaluated the effect of the limited hydrolysis of isolated soy protein with Neutrase on RLA
suppression in 3T3-L1 cells during differentiation and showed that the RLA suppression
increased with the DH and TCA-soluble protein increased, reaching approximately 13% of the
maximum RLA inhibition with DH 9.94-15.19%. On the other hand, with DH 18.08%, the RLA
inhibition decreases to 2.5%. Martinez-Villaluenga, Bringe, Berhow & Mejia (2008) tested the
effects of soy hydrolysates on RLA in 3T3-L1 adipocytes and showed the inhibition of lipid
accumulation of soy hydrolysates ranged from 29 to 46%.
3.3. Mixture-contour plots for TCA-soluble protein and RLA (%)
The variations in the TCA-soluble protein and the RLA (%) of the hydrolysates obtained
from SPI, BWP and EWP are also shown using mixture-contour plots (Fig. 1). On the response
surfaces, each factor (pure mixture component) is represented in the corner of an equilateral
triangle, and each point within this triangle refers to a different proportion of the components in
the mixture. The maximal percentage of each ingredient considered by the regression was placed
at the corresponding corner, and the minimal percentage was positioned at the middle of the
opposite side of the triangle (Martinello, Kaneko, Velasco, Taqueda & Consiglieri, 2006). A
contour plot provides a two-dimensional view in which all points that have the same response are
connected to produce contour lines of constant responses (Rao & Baral, 2011). The high levels of
TCA-soluble protein were observed in the mixtures contained SPI and BWP. This can be verified
by observing the mixture-surface plots (Fig. 1a).
The maximum responses for RLA suppression (%) were detected in the EWP
hydrolysates and mixtures containing BWP and EWP, reaching values of 12.2 and 15.5%,
respectively (Fig. 1c). The plots of the experimental versus the predicted responses suggested that
the experimental points were reasonably aligned, an indicator of the normal distribution (Fig. 1).
188
Fig. 1. Mixture-contour plots and fitted line plots between the experimental and the predicted
values for the TCA-soluble protein (a), the RLA (%) (b) and the RLA suppression (%) (c) of the
protein hydrolysates.
a
b
c
> 65 < 65 < 63 < 61 < 59 < 57
0.00
0.25
0.50
0.75
1.00
EWP0.00
0.25
0.50
0.75
1.00
SPI
0.00 0.25 0.50 0.75 1.00
BWP
52 54 56 58 60 62 64 66 68
Experimental values
55
56
57
58
59
60
61
62
63
64
65
66
Pre
dic
ted v
alues
> 99 < 99 < 97 < 93 < 89 < 85
0.00
0.25
0.50
0.75
1.00
EWP0.00
0.25
0.50
0.75
1.00
SPI
0.00 0.25 0.50 0.75 1.00
BWP
80 85 90 95 100 105 110
Experimental values
82
84
86
88
90
92
94
96
98
100
102
104
106
Pre
dic
ted v
alu
es
> 14 < 14 < 12 < 10 < 8 < 6 < 4 < 2
0.00
0.50
1.00
EWP0.00
0.25
0.50
0.75
1.00
SPI
0.00 0.25 0.50 0.75 1.00
BWP
0 2 4 6 8 10 12 14 16 18 20
Experimental values
0
2
4
6
8
10
12
14
16
18
Pre
dic
ted v
alues
189
3.4. Analysis of variance (ANOVA) and models for the TCA-soluble protein and the
RLA (%) of the intact proteins and their hydrolysates
The response data based on the independent variables was obtained from the experiments
and recorded in Table 1. The experiments were conducted in triplicate, and it was found that in
nearly all cases, there exists good agreement between the replicates. All of the independent and
response variables were fitted to linear, quadratic or special-cubic models. The coefficient of
determination R2 and the F test (analysis of variance-ANOVA) were used to verify the quality of
the fit of the models. Table 2 shows the models and the corresponding R2
of the regression
equations for the responses, as well as the corresponding F-ratio and p-values for each term in the
predicted regression equations. The high coefficients of determination (R2), which were above
0.70 (Table 2), indicate that all of the response functions adequately fitted the experimental data
and that the models could be used for predictive purposes in the determination of the TCA-
soluble protein and RLA (%), using the different protein sources and their mixtures. The negative
quadratic (binary) and cubic (ternary) terms of the fitted regression equation showed the
antagonistic effects, and the positive quadratic and cubic terms indicated synergistic effects of the
protein sources on the TCA-soluble protein and the RLA (%).
The highest values for the RLA (%) were detected in the 3T3-L1 pre-adipocytes treated
with non-hydrolyzed bovine whey protein (x2) followed by egg white protein (x3) and soy protein
isolate (x1). Regarding to the hydrolysates, the regression coefficients indicated higher values for
RLA (%) in the 3T3-L1 pre-adipocytes treated with bovine whey protein (x2), followed by soy
protein isolate (x1) and egg white protein (x3) (Table 2). It is important to note that, in both cases,
the higher values of the RLA (%) indicate a lower anti-adipogenic activity and so a lower
coefficient is more desirable. The binary and the ternary interactions of the protein hydrolysates
had significant (p < 0.05) effects, whereas for the non-hydrolyzed proteins, only the interactions
of soy protein isolate (x1) with bovine whey protein (x2) and bovine whey protein (x2) with egg
white protein (x3) were found to be significant (Table 2).
190
Table 2 - Analysis of variance (ANOVA), including models, R2 and probability values for the
final reduced models for the TCA-soluble proteins and the RLA (%).
Response: TCA-soluble proteins (non-hydrolyzed proteins)
Source of variation Sum of
squares
Degrees of
freedom
Mean of
squares Fcalculated/Ftabulated R² p-value
Regression 2,208.97 6 368.16 613.60/2.07 0.99 <0.001
Residual 12.69 21 0.60
Total 2,221.66
Special cubic model: Y = 30.70x1 + 37.24x2 + 16.42x3 + 8.25x1x2 – 24.55x1x3 – 39.35x2x3 – 115.61x1x2x3
Response: TCA-soluble proteins (protein hydrolysates)
Source of variation Sum of
squares
Degrees of
freedom
Mean of
squares Fcalculated/Ftabulated R² p-value
Regression 184.62 5 36.92 11.43/2.13 0.70 <0.001
Residual 71.12 22 3.23
Total 255.74
Quadratic model: Y = 62.00x1 + 56.51x2 + 63.05x3 + 22.04x1x2
Response: RLA % (non-hydrolyzed proteins)
Source of variation Sum of
squares
Degrees of
freedom
Mean of
squares Fcalculated/Ftabulated R² p-value
Regression 283.62 4 70.90 10.87/2.33 0.73 <0.001
Residual 104.41 16 6.52
Total 388.03
Quadratic model: Y = 92.09x1 + 95.73x2 + 93.94x3 – 30.48x1x2 – 23.93x1x3
Response: RLA % (protein hydrolysates)
Source of variation Sum of
squares
Degrees of
freedom
Mean of
squares Fcalculated/Ftabulated R² p-value
Regression 701.83 6 116.97 25.76/2.24 0.92 <0.001
Residual 63.50 14 4.54
Total 765.33
Special cubic model: Y = 90.59x1 + 95.20x2 + 87.83x3 + 43.66 x1x2 + 17.98x1x3 – 28.22x2x3 – 140.89x1x2x3
191
Validation tests were performed to determine the accuracy of the polynomial models
obtained for the TCA-soluble protein and the RLA (%) of the protein hydrolysates using various
formulations with three assays (Table 3). According to the regression models (Table 2), the
experimental values agreed with the values predicted by the models within a 95% confidence
interval, thereby confirming the validity of the models for the evaluated responses (Table 3).
Table 3 - Validation tests performed to determine the adequacy of the polynomial models
obtained for the TCA-soluble protein of the protein hydrolysates and the RLA (%) for the 3T3-L1
preadipocytes treated with various formulations of the protein hydrolysates at 800 ppm.
Results are presented as the mean (n = 3) ± SD, and those with different letters are significantly different, with p < 0.05.
Comparisons were made between the observed and predict values for each correspondent response.
3.5. Effect of the concentration of protein hydrolysates and various treatments on the
RLA.
The binary mixture of intact proteins containing SPI (1/2) and BWP (1/2) and the
hydrolyzed mixture of BWP (1/2) and EWP (1/2) showed the greatest RLA suppression in 3T3-
L1 cells at 800 ppm, so the effect of the sample concentration was evaluated. The 3T3-L1
preadipocytes were treated with 400-1400 ppm of the SPI and BWP (non-hydrolyzed) and the
hydrolyzed mixture of BWP and EWP during differentiation and a dose-dependent reduction of
the RLA was observed. The Pearson coefficient indicated a positive and significant correlation
between the concentration and the RLA inhibition (%) for both samples (Pearson coefficient >
0.84; p < 0.04). For the mixture containing SPI plus BWP (non-hydrolyzed), the higher RLA
inhibitions were 20.08 and 20.94% at 1000 and 1400 ppm, respectively. As for the hydrolyzed
mixture of BWP and EWP, the maximum RLA inhibition (32.78%) was detected at a
concentration of 1200 ppm (Fig. 2).
Responses
Independent variables Predicted
response
Experimental
response x1
(SPI)
x2
(BWP)
x3
(EWP)
TCA-soluble protein (%) 0.33 0.34 0.33 62.95a 61.07 ± 2.85
a
RLA (%) 1 1.00 0.00 0.00 90.59b 83.57 ± 8.07
b
RLA (%) 2 0.00 0.50 0.50 84.46c 87.24 ± 9.25
c
RLA (%) 3 0.33 0.33 0.34 89.56d 85.47 ± 5.82
d
192
Fig. 2. Effect of the concentration of intact proteins containing SPI (1/2) and BWP (1/2) and the
protein hydrolysates of BWP (1/2) and EWP (1/2) on the RLA suppression (%) in 3T3-L1
preadipocytes.
To study the effect of various treatments on the RLA (%) in the 3T3-L1 cells, two
treatments were performed using the hydrolyzed mixture of BWP (1/2) and EWP (1/2). The
results showed that the RLA (%) decreased significantly for both treatments. For treatment 1, in
which the two-day postconfluent 3T3-L1 preadipocytes received 1200 ppm of the hydrolysates
only at day zero during the early phase of differentiation, an RLA of 69.43% was observed,
resulting in the suppression of 30.57%. Treatment 2, in which the two-day postconfluent 3T3-L1
preadipocytes received 1200 ppm of the protein hydrolysates at day zero and every two days
afterwards until the end of the experiment at day eight, proved to be more effective, reaching an
RLA of 52.07% and, consequently, a suppression of 47.93% (Fig. 3).
0
5
10
15
20
25
30
35
400 600 800 1000 1200 1400
RL
A s
upp
ress
ion (
%)
Concentration (ppm)
Non-hydrolyzed Hydrolysates
193
Fig. 3. Effect of the various treatments on the RLA (%) in 3T3-L1 preadipocytes using the
hydrolyzed mixture of BWP (1/2) and EWP (1/2) at 1200 ppm.
3.6. Fractionation of the hydrolysates by ultrafiltration.
The hydrolyzed mixture of BWP (1/2) and EWP (1/2) was sequentially ultrafiltered to
obtain three fractions: (i) permeate 30 kDa (<30 kDa), (ii) permeate 10 kDa (<10 kDa) and (iii)
permeate 3 kDa (<3 kDa). Fig. 4 shows the effect of 1200 ppm of various fractions on the RLA
(%) at day eight during the 3T3-L1 cell differentiation with treatment 2. All of the fractions and
the non-fractionated sample showed a much lower RLA (%) than the control. The RLA varied
significantly ranging between 52.07 and 83.75%, resulting in suppressions of 47.93 and 16.25%
for the non-fractionated sample and the 3 kDa permeate, respectively. These results showed that
there is an important contribution of fractions of different sizes in the inhibition of lipid
accumulation in the 3T3-L1 cells during differentiation; thus, the use of ultrafiltration as a
concentration step subsequently became unnecessary, which was a positive aspect for the
process.
The sequential fractionation of protein hydrolysates by ultrafiltration has been reported to
separate and concentrate active compounds, enhancing their biological and functional properties.
Tsou, Kao, Tseng & Chiang (2010) investigated the anti-adipogenic activity of soy-protein-
isolate hydrolysates obtained by enzymatic hydrolysis using FlavourzymeTM
and further
separated by sequential ultrafiltration to obtain fractions ranging from 1 to 30 kDa. These authors
0
20
40
60
80
100
Control Treatment 1 Treatment 2
RL
A (
%)
194
reported that, among these fractions, the 1-kDa permeate had the highest anti-adipogenic effect,
resulting in a reduction of 59% in the activity of glycerol-3-phosphate dehydrogenase (GPDH),
an enzyme that has an important function in the metabolism linking glycolysis to phospholipid
and triglyceride biosynthesis (Harding, Pyeritz, Copeland & White, 1975). The sequential
ultrafiltration using membranes of 10 and 3 kDa was reported as an auxiliary step in the
purification of an adipogenesis-inhibitory peptide from black-soybean-protein hydrolysate by
Kim, Bae, Ahn, Lee & Lee (2007). Tsou, Lin, Lu, Tsui & Chiang (2010) reported that the
sequential fractionation of isolated soy protein hydrolyzed with Neutrase using ultrafiltration
proved to be a useful way to increase its anti-adipogenic activity, resulting in a reduction in the
GPDH activity and lipid accumulation in the 3T3-L1 preadipocyte cells treated with a 1-kDa
concentrate at 400 ppm.
Fig. 4. Effect of various ultrafiltered fractions of the hydrolyzed mixture of BWP (1/2) and EWP
(1/2) at 1200 ppm on the RLA (%) at day eight during 3T3-L1 preadipocyte differentiation with
treatment 2.
0
20
40
60
80
100
Control Not fractionated < 30 kDa < 10 kDa < 3 kDa
RL
A (
%)
Fractions
195
4. Conclusions
The results suggest that the application of the statistical-mixture design for the enzymatic
hydrolysis of various protein sources is an attractive process for improving the performance by
identifying the optimum mixture formulations of proteins with specific characteristics, for
example, increased RLA (%) suppression. The mixture containing BWP (1/2) plus EWP (1/2)
showed increases of up to 220 and 27% in their activities compared to those of the isolated
substrates after enzymatic hydrolysis, reaching a maximum RLA suppression of 15.5% at 800
ppm. The correlation analysis indicated a positive and significant correlation between the samples
concentration and the RLA suppression (%), reaching a maximum value of 47.93% for the
hydrolyzed mixture of BWP (1/2) and EWP (1/2) at 1200 ppm. Sequential fractionation of the
hydrolyzed mixture of BWP (1/2) and EWP (1/2) using ultrafiltration became unnecessary for
this process because the non-fractionated sample had the highest anti-adipogenic activity.
Acknowledgments
The work described in this paper was substantially supported by grants from São Paulo
Research Foundation – FAPESP (Project No. 2011/10429-9), the Department of Food Science,
the School of Food Engineering and the Department of Anatomy, Institute of Biology, University
of Campinas, which are gratefully acknowledged.
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198
199
Capítulo IX: Atividade antimicrobiana de hidrolisados de proteína isolada
de soja, soro de leite e clara de ovo.
200
Resumo
Processos envolvendo a hidrólise de proteínas têm sido estudados para a produção de peptídeos
com atividade biológica. No presente trabalho, hidrolisados de proteína isolada de soja, soro de
leite e clara de ovo foram preparados utilizando uma preparação comercial de protease de
Aspergillus oryzae (Flavourzyme® 500L) para a obtenção de peptídeos com atividade
antimicrobiana utilizando planejamento experimental de misturas. As hidrólises enzimáticas
foram conduzidas em frascos Erlenmeyers contendo 50 mL de solução de proteína (100 mg mL-1
)
durante 2 h a 50 °C e pH 5,0. Para a avaliação da atividade antimicrobiana das amostras de
proteínas hidrolisadas e não hidrolisadas foram utilizadas três culturas de leveduras: Candida
albicans ATCC 10231, Saccharomyces cerevisiae KL 88 e Kluyveromyces marxianus NRRL
7571 e três culturas bacterianas: Staphylococcus aureus ATCC 6538, Escherichia coli ATCC
11229 e Salmonella choleraesuis ATCC 14028. Os resultados mostraram que na maior parte dos
ensaios, a suplementação dos meios de cultivo com fontes de proteínas estimulou o crescimento
das bactérias patogênicas. A linhagem de S. aureus ATCC 6538 foi a única que apresentou
inibição significativa do crescimento quando cultivada em meio suplementado com uma mistura
binária de proteína isolada de soja (1/2) e proteínas da clara de ovo (1/2) não hidrolisadas,
resultando em inibição de 16,82%. Para as linhagens de leveduras, não foram observadas
mudanças nos perfis de inibição do crescimento quando comparadas as amostras hidrolisadas e
não hidrolisadas. A maior inibição observada foi detectada para a linhagem de S. cerevisiae KL
88 cultivada em meio suplementado com a mistura ternária de proteínas hidrolisadas em
proporções iguais, resultando em inibição de 15,42%.
Palavras-chave: proteases; hidrólise enzimática; hidrolisados proteicos; atividade
antimicrobiana.
201
1. Introdução
Processos envolvendo hidrólise de proteínas têm sido estudados para a produção de
peptídeos com atividade biológica. Peptídeos bioativos são definidos como frações específicas de
proteínas com sequência de aminoácidos que promovem um impacto positivo em várias funções
biológicas, incluindo efeitos como atividades: antioxidante, anti-hipertensiva, antitrombótica,
antiadipogênica e antimicrobiana (Zhang et al., 2010; Biziulevicius et al., 2006; Tsou et al.,
2010; Tavares et al., 2011). Estes peptídeos apresentam sequências de 2-20 aminoácidos e
massas moleculares inferiores a 6000 Da. A bioatividade é definida principalmente pela
composição e sequência de aminoácidos (Sarmadi e Ismail, 2010). Essa enorme diversidade
funcional coloca os peptídeos e as proteínas em posição de destaque no campo das aplicações
biotecnológicas (Miranda e Liria, 2008), sendo apontados por alguns autores como possíveis
substitutos de substâncias químicas utilizadas como fármacos ou conservadores de alimentos
(Hong et al., 2008).
Uma das formas mais comuns e rentáveis de produzir peptídeos bioativos é através da
hidrólise enzimática de proteínas (Hernández-Ledesma et al., 2011). Esse processo oferece
algumas vantagens, como: emprego de enzimas em concentrações muito baixas, reações rápidas
em condições suaves e alta especificidade, gerando um produto livre de resíduos químicos e com
melhores propriedades funcionais e nutricionais (Adler-Nissen, 1981).
Dentre as várias atividades biológicas de peptídeos, encontram-se os que apresentam a
capacidade de inibir o crescimento de micro-organismos. Peptídeos antimicrobianos estão
amplamente distribuídos na natureza e representam um componente essencial do sistema
imunológico. Eles são reconhecidamente, a primeira linha de defesa do organismo contra a
colonização de micro-organismos exógenos, com papel fundamental na regulação de populações
bacterianas em mucosas e outras superfícies epiteliais (Boman e Hultmark, 1987; Bevins e
Zasloff, 1990). Mais de 800 peptídeos antimicrobianos já foram caracterizados em plantas e
animais (Boman, 2003). Apesar da diversidade na estrutura primária, a grande maioria dos
peptídeos antimicrobianos possui cadeias curtas de aminoácidos, que são caracterizadas pela
predominância de aminoácidos catiônicos e hidrofóbicos. Embora haja diferenças significativas
nas estruturas secundária e terciária, peptídeos antimicrobianos são geralmente compostos por
uma superfície hidrofóbica e uma hidrofílica. O caráter anfipático destas moléculas é definitivo
202
no mecanismo de ação antimicrobiana permitindo uma maior interação com a membrana
bacteriana (Dashper et al., 2007). Em adição a característica anfipática, a reduzida massa
molecular das frações peptídicas, com consequente maior exposição dos resíduos de aminoácidos
e suas cargas, e a formação de pequenos canais na bicamada lipídica, foram relacionados com o
poder antimicrobiano, pois causam modificações que aumentam a interação peptídeo-membrana
(Gobetti et al., 2004, Patrzykat e Douglas, 2005, Gómez-Guillén et al., 2010).
Na literatura, diferentes fontes de proteínas têm sido utilizadas para a hidrólise
enzimática, tal como arroz, proteínas de clara de ovo e do soro de leite (Zhao et al., 2012; Naik et
al., 2013; Hoppe et al., 2013). No entanto, estas pesquisas relatam processos de hidrólise
enzimática utilizando substratos separadamente; nenhum trabalho foi encontrado utilizando
formulações contendo misturas de diferentes fontes de proteína.
O planejamento de misturas é uma classe especial de delineamento experimental, no qual
as proporções entre os componentes ou fatores, assim como as interações entre os mesmos e os
seus efeitos sobre a variável resposta podem ser utilizados para maximizar resultados e
aperfeiçoar processos. A utilização desta técnica permite um melhor entendimento dos dados
experimentais, pois inclui avaliação estatística e geração de gráficos e modelos que facilitam a
interpretação dos resultados assim como a verificação de efeitos sinérgicos ou antagônicos entre
os componentes das misturas.
Neste contexto, o objetivo do presente trabalho foi avaliar a atividade antimicrobiana de
proteínas de diferentes fontes utilizando a técnica de planejamento experimental de misturas.
Amostras de proteína isolada de soja, proteínas do soro de leite e da clara de ovo isoladas ou
combinadas em formulações binárias e/ou ternárias não hidrolisadas e hidrolisadas
enzimaticamente foram utilizadas na suplementação de meios de cultivo para avaliação do efeito
no crescimento de linhagens de bactérias e leveduras.
2. Material e métodos
2.1. Protease
A protease comercial Flavourzyme® 500L de Aspergillus oryzae foi utilizada para
obtenção dos hidrolisados proteicos (Sigma Aldrich).
203
2.2. Determinação da atividade de protease
A atividade proteolítica utilizando azocaseína como substrato foi determinada segundo a
metodologia de Charney e Tomarelli (1947), com modificações. A mistura reacional contendo
0,5mL de azocaseína (0,5% p/v), pH 5,0 e 0,5mL de solução enzimática foi incubada por 40 min
na temperatura ótima de atividade da preparação enzimática (pH 5,0 e 50 °C). A reação foi
paralisada pela adição de 1,0 mL de ácido tricloroacético (TCA 10%). A mistura reacional foi
centrifugada a 17.000 x g e o sobrenadante coletado. A formação do composto cromóforo
ocorreu pela adição de 1,0 mL de solução de hidróxido de potássio 5M a 1,0mL do sobrenadante
da mistura reacional centrifugada e a leitura de absorbância foi realizada a 428 nm. Uma unidade
de atividade proteolítica foi definida como a quantidade de enzima que produz uma diferença de
0,01 na absorbância a 428 nm por minuto de reação entre o branco reacional e a amostra nas
condições do ensaio.
2.3. Obtenção dos hidrolisados proteicos
Proteína isolada de soja, proteínas do soro de leite e proteínas da clara de ovo foram
utilizadas para a preparação de hidrolisados utilizando planejamento experimental de misturas.
Amostras de 50 mL das soluções de proteínas 10% (p/v) e protease Flavourzyme® 500L (50 U
por mL de mistura reacional) foram incubadas em pH 5,0, 50 °C sob agitação de 100 rpm durante
2h. Após a hidrólise, as soluções foram submetidas a tratamento térmico (100 °C por 20 min)
para inativação das proteases. As amostras foram centrifugadas a 17.000 x g a 5 °C por 20 min e
os sobrenadantes contendo os peptídeos bioativos foram coletados, congelados e liofilizados para
determinação da atividade antimicrobiana. O processo de hidrólise enzimática utilizando o
planejamento experimental de misturas englobou sete ensaios com os componentes avaliados em
4 níveis: 1) 0 (0%), 2) 1/3 (33%), 3) 1/2 (50%) e 4) 1 (100%) como mostrado na Tabela 1. Todos
os experimentos realizados foram analisados comparativamente com as suas respectivas amostras
não hidrolisadas.
204
Tabela 1 – Matriz do planejamento experimental de misturas para obtenção de peptídeos com
atividade antimicrobiana através da hidrólise enzimática de proteína isolada de soja (x1),
proteínas do soro de leite (x2) e proteínas da clara de ovo (x3).
Equações quadráticas ou cúbicas foram utilizadas para definição de modelos para cada
variável estudada, como mostrado abaixo:
𝑌𝑖 = 𝛽𝑖𝑋𝑖 + 𝛽𝑖𝑗
𝑞
𝑖<𝑗
𝑞
𝑖=1
𝑋𝑖𝑋𝑗 + 𝛽𝑖𝑗𝑘𝑋𝑖𝑋𝑗𝑋𝑘
𝑞
𝑖<𝑗<𝑘
onde 𝑌𝑖 representa a resposta estimada pelo modelo, q corresponde ao número de componentes
no sistema, ‘Xi, Xj, Xk’ correspondem às variáveis independentes codificadas, βi representa os
coeficientes de regressão linear para o efeito de cada termo, βij and βijk correspondem ao efeito de
interação entre as misturas binárias e ternárias. O coeficiente de correlação múltipla (R2) e o teste
de Fisher (análise de variância-ANOVA) foram utilizados para verificar a adequação estatística
dos modelos propostos codificados aos pontos reais. O software Statistica®
10 da Statsoft Inc.
(Tulsa, Oklahoma, EUA) foi utilizado para o planejamento experimental, análise de dados e
construção de modelos.
A variação dos resultados utilizando diferentes proporções de proteínas também foi
avaliada através de curvas de contorno, nas quais, cada fator é representado em um canto de um
triângulo equilátero, sendo cada ponto dentro do triângulo referente a uma proporção diferente de
componentes na mistura. A porcentagem máxima de cada componente considerado pela
regressão é colocada no canto correspondente, enquanto o mínimo é posicionado no meio do lado
oposto do triângulo e o centro representa a mistura dos três componentes em partes iguais.
Ensaios
Variáveis independentes
Proteína isolada de
soja
Proteínas do soro de
leite
Proteínas da clara de
ovo
x1 x2 x3
1 1 0 0
2 0 1 0
3 0 0 1
4 1/2 1/2 0
5 1/2 0 1/2
6 0 1/2 1/2
7 1/3 1/3 1/3
205
2.4. Determinação da atividade antimicrobiana
2.4.1. Micro-organismos e condições de cultivo
Para a avaliação da atividade antimicrobiana dos hidrolisados de proteína isolada de soja,
soro de leite e clara de ovo, foram utilizadas três culturas de leveduras: Candida albicans ATCC
10231, Saccharomyces cerevisiae KL 88 e Kluyveromyces marxianus NRRL 7571 e três culturas
bacterianas: Staphylococcus aureus ATCC 6538, Escherichia coli ATCC 11229 e Salmonella
choleraesuis ATCC 14028, previamente cultivadas em Ágar YM (para as linhagens de leveduras)
ou Ágar Nutriente (para as linhagens bacterianas) e mantidas em estoque a 4-8 °C. As culturas
foram inicialmente reativadas em 50 mL de caldo YM ou caldo nutriente durante 24 h a 30 °C
(para as linhagens de leveduras) ou 37 °C (para as linhagens bacterianas) sob agitação de 100
rpm. Em seguida, alíquotas de 1 mL das suspensões microbianas reativadas foram transferidas
para frascos Erlenmeyer de 125 mL com 50 mL de caldo YM ou caldo nutriente e incubados a 30
ou 37 °C e 100 rpm durante 8h. As suspensões microbianas foram previamente diluídas no meio
de cultura correspondente para obtenção da concentração final de inóculo desejada para os testes
de atividade antimicrobiana.
2.4.2. Determinação da atividade antimicrobiana
O crescimento microbiano foi monitorado utilizando-se o leitor de microplacas Novo
Star® (BMG LABTECH, Alemanha) a 600 nm. As medições foram realizadas em microplacas de
96 poços (TPP). Cada poço continha 100 µL da suspensão microbiana diluída em caldo YM ou
caldo nutriente com densidade óptica (DO) inicial ajustada para 0,2 a 600 nm e 100 µL das
soluções de proteína (0,5 mg mL-1
), previamente dissolvidas no meio de cultivo correspondente e
esterilizadas por filtração em membranas de 0,2 μm. As microplacas foram incubadas durante
24h a 30 ou 37 °C com posterior medida da absorbância a 600 nm. O experimento controle
consistiu no cultivo de 100 µL das suspensões microbianas e 100 µL de caldo YM ou caldo
nutriente (sem a adição dos hidrolisados proteicos) nas mesmas condições descritas
anteriormente. Os ensaios foram realizados com seis replicatas. O crescimento microbiano,
expresso em termos percentuais, foi calculado como a razão da DO600 dos meios contendo as
amostras de hidrolisados proteicos e a DO600 do ensaio controle.
206
2.5. Análises estatísticas
Os resultados foram analisados estatisticamente pelo teste de Tukey, realizado com
auxílio do software Minitab® 16.1.1 de Minitab Inc. (EUA). Os valores foram expressos como
média aritmética e considerados estatisticamente diferentes quando os valores de p foram
inferiores a 0,05.
3. Resultados e Discussão
Os resultados obtidos para atividade antimicrobiana de proteína isolada de soja, proteínas
do soro de leite e da clara de ovo hidrolisadas e não hidrolisadas estão apresentados nas Tabelas 2
e 3. Em termos gerais, as proteínas avaliadas neste estudo, nas condições de ensaio descritas,
apresentaram baixa ou nenhuma capacidade de inibição dos micro-organismos. Na maior parte
dos ensaios, a suplementação dos meios de cultivo com fontes de proteínas estimulou o
crescimento das bactérias patogênicas. É válido ressaltar que embora este estímulo tenha sido
observado, foi possível detectar mudanças nos perfis de crescimento das linhagens bacterianas
em uma análise comparativa entre os meios suplementados com proteínas não hidrolisadas e
hidrolisadas. A hidrólise enzimática das proteínas diminuiu o estímulo ao crescimento, embora os
valores ainda tenham sido superiores aos respectivos ensaios controle (100%) (Tabela 2) (Figura
1).
A linhagem de S. aureus ATCC 6538 mostrou o maior crescimento percentual dentre os
micro-organismos avaliados, atingindo 186,78%, na presença de proteína isolada de soja não
hidrolisada. Por outro lado, quando cultivada em meio suplementado com uma mistura binária de
proteína isolada de soja e proteínas da clara de ovo (ensaio 5) não hidrolisadas, esta mesma
linhagem apresentou crescimento de 83,18%, resultando em inibição de 16,82% do crescimento,
quando comparada ao ensaio controle (100%). Para as linhagens de E. coli ATCC 11229 e S.
choleraesuis ATCC 14028 não foram observadas inibições significativas no crescimento em
nenhum dos ensaios realizados (Tabela 2).
207
Para as linhagens de leveduras avaliadas, não foram observadas mudanças nos perfis de
inibição do crescimento quando comparadas as amostras hidrolisadas e não hidrolisadas. O
crescimento médio para as linhagens avaliadas variou de 84,5 a 95,5%, indicando assim níveis de
inibição entre 4,5 e 15,5%. A maior inibição observada foi detectada para a linhagem de S.
cerevisiae KL 88 cultivada em meio suplementado com a mistura ternária de proteínas
hidrolisadas em proporções iguais (ensaio 7), resultando em crescimento relativo de 84,58% e
consequente inibição de 15,42% (Tabela 3).
208
Tabela 2 - Estudo da atividade antimicrobiana de hidrolisados de proteína isolada de soja (x1), proteínas do soro de leite (x2) e
proteínas da clara de ovo (x3): composições das misturas e crescimento percentual de linhagens de bactérias patogênicas.
a, b, c Os resultados estão apresentados como média aritmética (n = 6) ± desvio padrão e as letras diferentes indicam diferença estatística entre os diferentes ensaios (p < 0,05).
Ensaios
Escherichia coli ATCC 11229 Salmonella choleraesuis ATCC 14028 Staphylococcus aureus ATCC 6538
Não hidrolisados Hidrolisados Não hidrolisados Hidrolisados Não hidrolisados Hidrolisados
1 127,98 ± 7,53a, b, c
116,08 ± 8,65b 119,25 ± 4,92
a 109,38 ± 2,25
a, b 186,78 ± 2,42
e 132,31 ± 6,35
d
2 133,43 ± 6,65a 130,43 ± 4,26
a 121,69 ± 0,90
a 114,51 ± 4,15
a 112,04 ± 4,03
c 159,62 ± 1,66
e
3 113,04 ± 6,66e 127,48 ± 7,56
a 105,95 ± 1,63
b 110,59 ± 2,96
a, b 110,56 ± 6,35
b, c 117,97 ± 5,66
b
4 131,44 ± 2,48a, b
122,78 ± 3,82a, b
118,43 ± 2,41a 107,06 ± 2,12
b, c 155,25 ± 8,06
d 93,77 ± 4,16
a
5 117,90 ± 3,06d, e
122,50 ± 2,08a, b
105,38 ± 2,80b 99,95 ± 4,05
d 83,18 ± 1,32
a 128,77 ± 6,23
c, d
6 120,13 ± 4,51c, d, e
123,42 ± 8,74a, b
105,78 ± 5,25b 101,52 ± 3,51
c, d 106,25 ± 6,31
b, c 92,86 ± 1,88
a
7 123,36 ± 7,37b, c, d
113,30 ± 4,67b 103,55 ± 4,35
b 94,13 ± 3,60
e 104,32 ± 2,64
b, c 121,03 ± 5,06
b, c
209
Tabela 3 - Estudo da atividade antimicrobiana de hidrolisados de proteína isolada de soja (x1), proteínas do soro de leite (x2) e
proteínas da clara de ovo (x3): composições das misturas e crescimento percentual de linhagens de leveduras.
a, b, c Os resultados estão apresentados como média aritmética (n = 6) ± desvio padrão e as letras diferentes indicam diferença estatística entre os diferentes ensaios (p < 0,05).
Mistura Candida albicans ATCC 10231 Kluyveromyces marxianus NRRL 7571 Saccharomyces cerevisiae KL 88
Não hidrolisados Hidrolisados Não hidrolisados Hidrolisados Não hidrolisados Hidrolisados
1 92,86 ± 1,40a 92,93 ± 0,32
a 91,24 ± 1,01
a 91,85 ± 0,34
a 93,51 ± 0,96
a 90,28 ± 1,09
a
2 92,48 ± 0,90a 95,26 ± 0,33
b 90,40 ± 0,93
a 92,05 ± 0,47
a 92,24 ± 0,17
a, c 93,21 ± 1,02
b
3 92,76 ± 1,10a 95,40 ± 0,61
b 90,08 ± 1,02
a 92,57 ± 1,31
a 93,24 ± 0,34
a 93,68 ± 1,82
b
4 94,12 ± 0,97a 95,05 ± 0,5
b 91,64 ± 0,81
a 91,75 ± 1,05
a 93,89 ± 0,56
a 92,74 ± 1,11
b
5 94,30 ± 0,57a 94,65 ± 0,46
b 93,07 ± 0,85
b 92,34 ± 0,94
a 95,43 ± 0,89
b 92,83 ± 1,51
a, b
6 94,19 ± 0,84a 95,25 ± 0,55
b 92,15 ± 0,83
a, b 94,99 ± 0,67
b 95,47 ± 2,00
a, b 92,98 ± 2,79ª
, b
7 94,74 ± 1,52a 92,51 ± 0,38
a 93,38 ± 1,05
b 91,97 ± 1,02
a 96,25 ± 1,54
b 84,58 ± 3,97
c
210
As equações geradas a partir das variáveis independentes e respostas foram ajustadas a
modelos lineares, quadráticos ou cúbicos de acordo com a significância estatística dos
coeficientes de regressão (Tabelas 4 e 5). O coeficiente de correlação múltipla (R2) e o teste F
(Análise de variância-ANOVA) foram utilizados para verificar a qualidade do ajuste dos modelos
aos valores reais. As Tabelas 4 e 5 mostram os modelos, os valores de R2 e de F, assim como os
valores de p para cada equação. As equações mostraram valores de R2, variando entre 0,42 e 0,98,
indicando que as equações foram capazes de explicar de 42 a 98% da variação dos resultados.
Valores de R² inferiores a 0,70 indicam baixa adequação estatística dos modelos propostos, o que
compromete a utilização dos mesmos para prever respostas em diferentes condições de ensaios.
Assim, alguns modelos apresentados não são indicados para prever as respostas para crescimento
microbiano. Os baixos valores dos coeficientes de correlação (R²) podem ser devido à pequena
variação nos valores das respostas mesmo em condições experimentais totalmente distintas.
Em adição aos resultados já apresentados, a análise das curvas de contorno facilita a
interpretação dos dados, assim como a verificação dos efeitos das variáveis independentes e de
suas interações. No planejamento experimental de misturas, a variação dos resultados utilizando
diferentes proporções de proteínas também foi avaliada através das curvas de contorno, nas quais,
cada fator é representado em um canto de um triângulo equilátero, sendo cada ponto dentro do
triângulo referente a uma proporção diferente de componentes na mistura. A porcentagem
máxima de cada componente considerado pela regressão é colocada no canto correspondente,
enquanto o mínimo é posicionado no meio do lado oposto do triângulo e o centro representa a
mistura dos três componentes em partes iguais. As curvas de contorno para o crescimento das
linhagens de bactérias e leveduras em meios suplementados com diferentes fontes de proteínas
hidrolisadas e não hidrolisadas são apresentadas nas Figuras 1 e 2.
211
Tabela 4 – Análise de variância (ANOVA) para verificação da adequação estatística dos modelos codificados aos pontos reais para as
diferentes respostas de crescimento de bactérias patogênicas em meios suplementados com proteínas não hidrolisadas e hidrolisadas.
Proteínas não hidrolisadas
Resposta Unidade Modelo Equação Fcalculado/
Ftabelado R² p-valor
Escherichia coli
ATCC 11229
Crescimento
(%) Linear Y = 127,64x1 + 132,89x2 + 111,16x3 30,71/3,23 0,61 <0,001
Salmonella
choleraesuis ATCC
14028
Crescimento
(%) Cúbico
especial
Y = 118,57x1 + 121,01x2 + 105,95x3 – 27,52x1x3 – 30,80x2x3 –
139,15x1x2x3 35,44/2,44 0,83 <0,001
Staphylococcus
aureus ATCC 6538
Crescimento
(%) Quadrático Y = 188,66x1 + 113,92x2 + 110,66x3 – 267,45x1x3 – 25,69x2x3 279,46/2,79 0,98 <0,001
Proteínas hidrolisadas
Escherichia coli
ATCC 11229
Crescimento
(%) Cúbico
especial Y = 116,15x1 + 130,23x2 + 127,75x3 – 22,28x2x3 – 241,09x1x2x3 8,84/2,60 0,49 <0,001
Salmonella
choleraesuis ATCC
14028
Crescimento
(%) Cúbico
especial
Y = 109,38x1 + 114,51x2 + 110,59x3 – 19,54x1x2 – 40,16x1x3 –
44,15x2x3 – 157,33x1x2x3 27,23/2,33 0,82 <0,001
Staphylococcus
aureus ATCC 6538
Crescimento
(%) Cúbico
especial
Y = 133,52x1 + 159,61x2 + 119,18x3 – 211,20x1x2 – 186,14x2x3 +
748,90x1x2x3 109,58/2,66 0,96 <0,001
212
Tabela 5 – Análise de variância (ANOVA) para verificação da adequação estatística dos modelos codificados aos pontos reais para as
diferentes respostas de crescimento de linhagens de leveduras em meios suplementados com proteínas não hidrolisadas e hidrolisadas.
Proteínas não hidrolisadas
Resposta Unidade Modelo Equação Fcalculado/
Ftabelado R² p-valor
Candida albicans
ATCC 10231
Crescimento
(%) Quadrático
Y = 92,86x1 + 92,48x2 + 92,76x3 + 5,84x1x2
+ 6,00x1x3 + 6,33x2x3 5,13/2,45 0,42 0,001
Kluyveromyces
marxianus
NRRL 7571
Crescimento
(%) Quadrático
Y = 91,20x1 + 90,36x2 + 90,04x3 + 3,99x1x2
+ 10,37x1x3 + 8,36x2x3 12,76/2,45 0,64 <0,001
Saccharomyces
cerevisiae
KL 88
Crescimento
(%) Quadrático
Y = 93,46x1 + 92,20x2 + 93,19x3 + 4,97x1x2
+ 9,15x1x3 + 11,84x2x3 12,04/2,45 0,63 <0,001
Proteínas hidrolisadas
Candida albicans
ATCC 10231
Crescimento
(%) Cúbico especial
Y = 92,93x1 + 95,23x2 + 95,37x3 + 3,85x1x2
+ 2,01x1x3 – 71,59x1x2x3 49,33/2,45 0,87 <0,001
Kluyveromyces
marxianus
NRRL 7571
Crescimento
(%) Cúbico especial
Y = 91,83x1 + 91,97x2 + 92,62x3 +
10,76x2x3 – 36,93x1x2x3 15,16/2,60 0,62 <0,001
Saccharomyces
cerevisiae
KL 88
Crescimento
(%) Cúbico especial
Y = 90,88x1 + 93,28x2 + 93,70x3 –
216,99x1x2x3 27,18/2,84 0,68 <0,001
213
Figura 1 - Curvas de contorno para crescimento percentual de E. coli ATCC 11229 (a, A), S.
choleraesuis ATCC 14028 (b, B) e S. aureus proteína isolada de soja, proteínas do soro de leite e
proteínas da clara de ovo não hidrolisadas (letras minúsculas) e hidrolisadas (letras maiúsculas)
com protease comercial Flavourzyme® 500L de A. oryzae.
> 132
< 132
< 128
< 124
< 120
< 116
< 112
0,00
0,25
0,50
0,75
1,00
Proteínas da
clara de ovo0,00
0,25
0,50
0,75
1,00
Proteína isolada
de soja
0,00 0,25 0,50 0,75 1,00
Proteínas do
soro de leite
> 130
< 130
< 128
< 126
< 124
< 122
< 120
< 118
< 116
< 114
0,00
0,25
0,50
0,75
1,00
Proteínas da
clara de ovo0,00
0,25
0,50
0,75
1,00
Proteína isolada
de soja
0,00 0,25 0,50 0,75 1,00
Proteínas do
soro de leite
> 120
< 120
< 114
< 110
< 106
< 102
0,00
0,25
0,50
0,75
1,00
Proteínas da
clara de ovo0,00
0,25
0,50
0,75
1,00
Proteína isolada
de soja
0,00 0,25 0,50 0,75 1,00
Proteínas do
soro de leite
> 114
< 114
< 110
< 106
< 102
< 98
< 94
0,00
0,25
0,50
0,75
1,00
Proteínas da
clara de ovo0,00
0,25
0,50
0,75
1,00
Proteína isolada
de soja
0,00 0,25 0,50 0,75 1,00
Proteínas do
soro de leite
> 180
< 180
< 160
< 140
< 120
< 100
< 80
0,00
0,25
0,50
0,75
1,00
Proteínas da
clara de ovo0,00
0,25
0,50
0,75
1,00
Proteína isolada
de soja
0,00 0,25 0,50 0,75 1,00
Proteínas do
soro de leite
> 150
< 150
< 132
< 122
< 112
< 102
< 92
0,00
0,25
0,50
0,75
1,00
Proteínas da
clara de ovo0,00
0,25
0,50
0,75
1,00
Proteína isolada
de soja
0,00 0,25 0,50 0,75 1,00
Proteínas do
soro de leite
a
b
c
A
B
C
214
Figura 2 - Curvas de contorno para crescimento percentual de C. albicans ATCC 10231 (a, A),
K. marxianus NRRL 7571 (b, B) e S. cerevisiae KL 88 (c, C) na presença de proteína isolada de
soja, proteínas do soro de leite e proteínas da clara de ovo não hidrolisadas (letras minúsculas) e
hidrolisadas (letras maiúsculas) com protease comercial Flavourzyme®
500L de A. oryzae.
Não hidrolisadas Não hidrolisadas Não hidrolisadas
> 94,6 < 94,5 < 94,1 < 93,7 < 93,3 < 92,9 < 92,5
0,00
0,25
0,50
0,75
1,00
Proteínas da
clara de ovo0,00
0,25
0,50
0,75
1,00
Proteína
isolada de soja
0,00 0,25 0,50 0,75 1,00
Proteínas do
soro de leite
> 95
< 95
< 94,5
< 94
< 93,5
< 93
< 92,5
0,00
0,25
0,50
0,75
1,00
Proteínas da
clara de ovo0,00
0,25
0,50
0,75
1,00
Proteína isolada
de soja
0,00 0,25 0,50 0,75 1,00
Proteínas do
soro de leite
> 93
< 92,6
< 92,1
< 91,6
< 91,1
< 90,6
< 90,1
0,00
0,25
0,50
0,75
1,00
Proteínas da
clara de ovo0,00
0,25
0,50
0,75
1,00
Proteína
isolada de soja
0,00 0,25 0,50 0,75 1,00
Proteínas do
soro de leite
> 94,5
< 94,1
< 93,6
< 93,1
< 92,6
< 92,1
< 91,6
0,00
0,25
0,50
0,75
1,00
Proteínas da
clara de ovo0,00
0,25
0,50
0,75
1,00
Proteína
isolada de soja
0,00 0,25 0,50 0,75 1,00
Proteínas do
soro de leite
> 95,5
< 95,2
< 94,7
< 94,2
< 93,7
< 93,2
< 92,7
< 92,2
0,00
0,25
0,50
0,75
1,00
Proteínas da
clara de ovo0,00
0,25
0,50
0,75
1,00
Proteína
isolada de soja
0,00 0,25 0,50 0,75 1,00
Proteínas do
soro de leite
> 92
< 91
< 89
< 87
< 85
0,00
0,25
0,50
0,75
1,00
Proteínas da
clara de ovo0,00
0,25
0,50
0,75
1,00
Proteína
isolada de soja
0,00 0,25 0,50 0,75 1,00
Proteínas do
soro de leite
a
b
c
A
B
C
215
Peptídeos com atividade antimicrobiana já foram identificados em diversos hidrolisados
proteicos. Biziulevicius et al., (2006) avaliaram o potencial antimicrobiano, frente a cepas de
bactérias e leveduras (Escherichia coli, Proteus vulgaris, Bacillus subtillis, Candida lambica e
Saccharomyces cerevisiae) de hidrolisados protéicos obtidos a partir do tratamento enzimático de
caseína, α-lactoalbumina, β-lactoglobulina, ovalbumina e albumina com proteases (tripsina, α-
quimiotripsina, pepsina e pancreatina) e verificaram que todos os hidrolisados obtidos
apresentaram atividade antimicrobiana contra as linhagens testadas. Hayes et al., (2006)
verificaram a presença de três frações peptídicas produzidas durante fermentação de caseinato de
sódio utilizando Lactobacillus acidophilus DPC6026, com atividade antibacteriana contra
linhagens patogênicas de Enterobacter sakazakii ATCC 12868 e Escherichia coli DPC5063. Liu
et al., (2008) em seus estudos com hidrolisados proteicos obtidos por digestão combinada com
alcalase e bromelina, observaram amplo espectro de ação de uma fração denominada CgPep33,
obtida após purificação por ultrafiltração, cromatografia de troca iônica, filtração em gel e
Cromatografia Líquida de Alta Eficiência (CLAE), contra diversos tipos de micro-organismos,
incluindo bactérias Gram positivas e negativas e fungos. CgPep33 foi capaz de inibir o
crescimento de todas as bactérias estudadas (Escherichia coli, Pseudomonas aeruginosa, Bacillus
subtilis e Staphylococcus aureus) e fungos (Botrytis cinerea e Penicillium expansum). Os valores
de IC50 (concentração necessária para inibir 50% do crescimento) variaram de 18,6-48,2 µg mL-1
.
As bactérias Gram positivas foram as que apresentaram maior sensibilidade, com valores de CIM
(concentração inibitória mínima) entre 40 e 60 µg mL-1
. Gómez-Guillén et al., (2010)
hidrolisaram gelatina com uma preparação comercial de proteases (Alcalase®
2.4L) e
submeteram os hidrolisados a fracionamento por ultrafiltração em membranas de 1 e 10 kDa. As
frações obtidas foram utilizadas para testes antimicrobianos contra 18 cepas bacterianas. As
bactérias mais sensíveis na presença das frações testadas foram: Lactobacillus acidophilus,
Bifidobacterium lactis, Shewanella putrafaciens e Photobacterium phosphoreum. Adje et al.,
(2011) estudaram a aplicação de pepsina na hidrólise de hemoglobina bovina para obtenção de
peptídeos com atividade antimicrobiana. Os hidrolisados foram purificados por CLAE e testados
quanto ao poder antimicrobiano contra duas linhagens Gram negativas (Escherichia coli,
Salmonella enteritidis) e três Gram positivas (Kocuria luteus A270, Staphylococcus aureus e
Listeria innocua). Os resultados obtidos mostraram que as frações peptídicas purificadas
apresentaram amplo espectro de ação, agindo contra quatro das cinco bactérias testadas (Kocuria
216
luteus A270, Listeria innocua, Escherichia coli e Staphylococcus aureus) com CIM variando
entre 35,2 e 187,1 µM. Tellez et al., (2011) mostraram a eficiência de uma fração peptídica,
isolada a partir de leite fermentado com Lactobacillus helveticus, contra uma infecção proposital
com Salmonella enteritidis em ratos. A taxa de sobrevivência no grupo alimentado com a fração
peptídica (0,02 µg por dia) foi superior ao grupo alimentado com uma dose inferior (0,01 µg por
dia) e ao grupo controle.
4. Conclusões
Os resultados obtidos neste estudo mostraram que a suplementação dos meios de cultivo
com fontes de proteínas estimulou o crescimento das bactérias E. coli ATCC 11229, S.
choleraesuis ATCC 14028 e S. aureus ATCC 6538. A linhagem de S. aureus ATCC 6538 foi a
única que apresentou inibição significativa do crescimento quando cultivada em meio
suplementado com uma mistura binária de proteína isolada de soja (1/2) e proteínas da clara de
ovo (1/2) não hidrolisadas, resultando em inibição de 16,82%. Para as linhagens de leveduras C.
albicans ATCC 10231, K. marxianus NRRL 7571 e S. cerevisiae KL 88, não foram observadas
mudanças nos perfis de inibição do crescimento quando comparadas as amostras hidrolisadas e
não hidrolisadas. A maior inibição observada foi detectada para a linhagem de S. cerevisiae KL
88 cultivada em meio suplementado com a mistura ternária de proteínas hidrolisadas em
proporções iguais, resultando em inibição de 15,42%. Embora não tenham sido detectados níveis
significativos de inibição do crescimento microbiano nas condições de ensaio utilizadas no
presente estudo, foi possível observar que a utilização de misturas de proteínas de diferentes
fontes apresentaram efeitos positivos sobre os resultados, atingindo maiores níveis de inibição do
crescimento quando comparadas às proteínas utilizadas isoladamente. Estudos posteriores são
necessários para determinar as melhores condições de obtenção dos hidrolisados e condições
específicas de aplicação dos mesmos em testes de atividade antimicrobiana.
217
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221
Capítulo X: Growth promotion of bifidobacteria and lactic acid bacteria
strains by protein hydrolysates using a statistical mixture design
Revista: Food Bioscience
222
Abstract
The use of different protein sources as supplement for cultivation of probiotic and lactic acid
bacteria species has been reported as an important way to guarantee optimum bacterial growth. In
this work, soy protein isolate (SPI), bovine whey protein (BWP) and egg white protein (EWP)
were hydrolyzed with the protease FlavourzymeTM
500L, and the effects of the media
supplemented with these different proteins and their mixtures on the growth performance of
bifidobacteria and lactic acid bacteria strains using a simplex centroid mixture design were
investigated. The results showed that the protein hydrolysis positively stimulated the bacteria
growth and that the mixtures of hydrolyzed proteins from different sources showed synergistic
effects on cell growth promotion. Compared with control, the cell growth of the mix culture of
Streptococcus thermophilus and Lactobacillus delbrueckii, Lactobacillus acidophilus and
Bifidobacterium lactis were increased with the supplementation of the media with mixtures of
BWP (1/2) plus EWP (1/2) and SPI (1/2) plus BWP (1/2) at 25 mg mL-1
in 100.0, 29.4 and
86.2%, respectively.
Keywords: protein hydrolysates, growth-stimulating, lactic acid bacteria, probiotic, mixture
design.
223
1. Introduction
Processes involving protein hydrolysis have been studied for bioactive peptide
production. Bioactive peptides can be defined as specific amino acid sequences that promote
beneficial biological activities. Bioactive peptides can be produced by enzymatic hydrolysis
using digestive, microbial and plants proteases. The limited and controlled proteolysis unfolds the
protein chains, can reduce the incidence of allergenic factors and also increase the formation of
small peptides with biological activities (Korhonen, 2009).
In the last decade, the enzymatic hydrolysis of proteins from animal and plant sources
for the production of bioactive peptides has attracted much attention. Among the biological
activities, the growth stimulation of probiotic bacteria has been reported. A characteristic of
bifidobacteria and lactic acid bacteria strains is their fastidious requirements for growth and
biological activities, particularly amino acids (Rajagopal & Sandine, 1990). The pool of free
amino acids and peptides in milk is not enough to guarantee optimum bacterial growth in this
substrate (Mills and Thomas, 1981; Zhang et al., 2011). Many ingredients have been evaluated to
stimulate the growth and activity of probiotic and lactic acid bacteria species, for example the
protein hydrolysates (Prasanna, Grandison & Charalampopoulos, 2012). As a result, much
interest has been focused in utilizing different protein sources as additives, such as whey protein
concentrate, whey protein isolate and casein hydrolysate, studying mainly the effect of these
compounds on the growth promotion of probiotic and lactic acid bacteria species (McComas Jr.
& Gilliland, 2003; Zhang et al., 2011; Prasanna, Grandison & Charalampopoulos, 2012).
In the literature, different protein sources have been used for enzymatic hydrolysis, such
as rice, egg white protein and whey protein (Zhao et al, 2012; Naik et al., 2013; Hoppe et al.,
2013). However, these reports show studies on enzymatic hydrolysis using distinct substrates; no
investigations were found using formulations containing mixtures of different protein sources as
well as their interaction effects.
Statistical methods have been applied for improving the performance, to find the
optimum process variables and formulations in different engineering problems (Rao & Baral,
2011). Statistical mixture designs are an interesting class of experimental designs where the
components or factors distributed in different proportions are used to verify the interactions
224
between the components of a mixture and maximizing the responses studied using mixture design
approach.
The general purpose of mixture design is to make possible estimates, through a contour
plots analysis of evaluated responses of a multicomponent system from a limited number of
experiments (Anarjan & Tan, 2013). In this experimental design, the total amount of material is
held constant because the response depends only on the proportions of the components present,
but not on the total amount of the mixture (Rao & Baral, 2011; Anarjan & Tan, 2013). In the
simplex centroid design, 2k
- 1 observations are taken, where k is the amount of pure components,
(k/2) is the binary mixtures with equal proportions and (k/3) is the ternary mixtures with equal
proportions (Scheffe, 1963).
In this work, a simplex centroid mixture design was used for production of hydrolysates
of different protein sources by enzymatic hydrolysis. The effects on the performance of
bifidobacteria and lactic acid bacteria strains grown in the media supplemented with different
protein sources and their mixtures were studied.
2. Materials and Methods
2.1. Reagents
FlavourzymeTM
500L, trichloroacetic acid (TCA) and MRS culture broth were purchased
from Sigma-Aldrich (Steinheim, Germany). All other chemicals were purchased in the grade
commercially available.
2.2. Preparation of protein hydrolysates
The soy protein isolate (SPI), bovine whey protein (BWP) and egg white protein (EWP)
used as the substrates for enzymatic hydrolysis were kindly provided by Bunge Foods S/A
(Gaspar, Brazil), Alibra Ingredients Ltd. (Campinas, Brazil) and Cooperovos (Mogi das Cruzes,
Brazil), respectively. The commercial protease obtained from Aspergillus oryzae (FlavourzymeTM
500L) was used for enzymatic hydrolysis. The enzyme concentrations were adjusted to 0
(control) and 50 U per mL of reaction, according to the protease activity, as previously
determined (Charney & Tomarelli, 1947). The proteins were suspended in a buffer to a final
concentration of 100 mg mL-1
. Fifty-milliliter aliquots of the mixtures were distributed in 125 mL
Erlenmeyer flasks and the hydrolysis was carried out under the optimum temperature and pH of
225
the enzyme (50 °C, pH 5.0) for 120 min. After hydrolysis, the samples were incubated in a water
bath at 100 °C for 20 min for protease inactivation. The mixtures were centrifuged at 17,000 x g
at 5 °C for 20 min and the supernatants containing peptides were collected and freeze-dried for
the determination of the TCA-soluble proteins and in the growth promotion of the bacteria
cultures.
2.3. Determination of the TCA-soluble proteins
The TCA-soluble proteins of the protein hydrolysates were determined with a modified
version of the method described by Pericˇin et al. (2009). A 1.0 mL aliquot of the hydrolysates
was added to an equal volume of 0.44 mol L-1
trichloroacetic acid (TCA). The mixture was
incubated for 30 min at room temperature. Then, the mixture was centrifuged at 17,000 x g for 15
min. The obtained 0.22 mol L-1
TCA-soluble proteins fraction and the supernatant of the
hydrolysate mixture (without the addition of TCA) were each analyzed to determine the protein
content using the Lowry method (1951), which uses bovine serum albumin as the standard
protein. The results were expressed as mg of TCA-soluble proteins per 100 mg of total protein in
sample.
2.4. Growth performance of bifidobacteria and lactic acid bacteria strains in the media
supplemented with intact and hydrolyzed proteins
2.4.1. Microorganisms and culture conditions
YFL811 (Streptococcus thermophilus and Lactobacillus delbrueckii), LA5 (Lactobacillus
acidofilus) and BB12 (Bifidobacterium lactis) freeze dried commercial cultures (from Chr.
Hansen China Company, Guangzhou, China) were used throughout this work. The stock cultures
were initially reactivated in 20 mL MRS broth under anaerobic conditions for 24 hr at 40 °C. The
reactivated cultures were sub-cultured twice at 24 hr intervals with 0.5% volume transfer to the
same medium. Then, 1 mL aliquot of the sub-cultured suspension was transferred to 125 mL
Erlenmeyer flasks with 50 mL of MRS broth and incubated at 40 °C and 50 rpm for 8 hr. The
cultures suspensions were diluted in the same medium to obtain the final concentration required
for inoculation of micro-assay plate wells.
226
2.4.2. Bacterial growth in the media supplemented with intact and hydrolyzed proteins
The study of the effects of the media supplemented with different protein sources and
their mixtures on the growth performance of the cultures was monitored using a Novo Star
MicroplateTM
reader (BMG LABTECH, Germany) at 600 nm. The measurements were made in a
96-well micro titer cell culture plates (TPP). To each well were added 100 μL of the culture
suspension diluted in MRS broth to optical density (OD) 0.2 at 600 nm and an equal volume of
protein solutions (0.5 mg mL-1
dissolved in the same medium); the mixtures were incubated for
24 hr at 40 °C and then OD at 600 nm were measured. As a control experiment, 100 μL of culture
suspension and 100 μL of MRS broth were applied into the wells. All assays were performed in
six replicate. The growth, expressed as a percentage, was calculated as the ratio of OD600 of the
samples to OD600 of the control.
2.4.3. Effect of concentration of protein hydrolysates on cell growth
The protein hydrolysates with major stimulator effects at 0.5 mg mL-1
on the bacteria
growth were evaluated at different concentrations: 0.5, 2.5, 5, 10, 15, 20 and 25 mg mL-1
. The
culture growths were carried out as described in Section 2.4.2, at 40 °C for 24 hr.
2.5. Calculations and statistics
The statistical analyzes were performed using the MinitabTM
16.1.1 software package
from Minitab Inc. (USA). Values are expressed as the arithmetic mean. The Tukey test was used
to test for significant differences between the groups analyzed. The differences were considered
significant at p < 0.05.
Pearson correlation coefficient was used to measure the strength of linear dependence
between two responses. The correlation coefficient ranges from – 1 to 1. A value of 1 implies that
a linear equation describes the relationship between the responses was perfectly and positive,
while a value of -1 indicate a perfectly and negative correlation. A value of 0 implies that there is
no linear correlation between the responses. The correlations between the analyzed parameters
were considered significant when p < 0.10.
227
3. Results and Discussion
3.1. Comparative analysis of the TCA-soluble proteins and bacteria growth between the
intact proteins and their hydrolysates.
The results for all parameters were evaluated on two points of view: 1) comparative
analysis of the TCA-soluble proteins and stimulation of the bacteria growth in the media
supplemented with hydrolyzed and non-hydrolyzed proteins in respective runs of the statistical
mixture design to verify the changes caused by the enzymatic hydrolysis and 2) evaluation of the
synergistic or antagonistic interactions of hydrolyzed, non-hydrolyzed proteins and their mixtures
on the TCA-soluble proteins and stimulation of the bacteria growth.
The interactions amongst the three substrates in the TCA-soluble proteins and bacteria
growth (%) were studied in the 7 assays using a simplex centroid mixture design (Table 1). The
size of peptides is known to be a significant factor in the overall bioactivities of protein
hydrolysates. Assessment of proteolysis levels is often achieved by global quantification of the
peptides soluble at certain concentrations of trichloroacetic acid (TCA). This parameter has been
used as an indication for the amount of small-sized peptides in the protein hydrolysates and has a
positive correlation with the degree of hydrolysis (DH) (Zhou et al., 2012). The TCA-soluble
proteins of the different protein sources showed significant changes after the enzymatic
hydrolysis. For SPI (run 2), the TCA-soluble proteins ranged from 30.70 mg (intact protein) to
62.47 mg (protein hydrolysates), resulting in an increase of 103.5%. For BWP (run 2) and EWP
(run 3), the observed increases were 52.2 and 288.5%, respectively, as compared to intact
proteins (Table 1).
The results showed that the enzymatic hydrolysis positively stimulated the bacteria
growth. The strain LA5 (L. acidophilus) showed increased growth ranging 12.9 to 19.4% higher
than control in the presence of the hydrolyzed proteins at 0.5 mg mL-1
. On the other hand, in the
medium supplemented with EWP (run 3), BWP (1/2) plus EWP (1/2) (run 6) and the ternary
mixture (run 7) as the non-hydrolyzed proteins, the LA5 growth was inhibited in 22.9, 28.3 and
6.7%, respectively. For the strain BB12 (B. lactis), the non-hydrolyzed proteins had a higher
stimulating effect on bacterial growth compared to the protein hydrolysates. The greatest
increases were observed in the medium supplemented with EWP (non-hydrolyzed) (run 3) and
BWP hydrolysates (run 2), which grew 28.8 and 25.2% higher, respectively, compared to control.
228
The mixed culture YFL811 (S. thermophilus and L. delbrueckii) showed increased growth
ranging 6.8 to 19.4% higher than control when the medium was supplemented with protein
hydrolysates. However, the EWP (run 3), the binary mixtures SPI (1/2) plus EWP (1/2) (run 5)
and BWP (1/2) plus EWP (1/2) (run 6) and the ternary mixture contained the three proteins in
equal proportions (run 7) as the non-hydrolyzed form, inhibited the growth from 6.8 to 10.8%
(Table 1). The Pearson coefficient indicates a positive and significant correlation between the
TCA-soluble proteins and the BB12 growth (%) in the presence of protein hydrolysates (Pearson
coefficient = 0.79; p = 0.04); for LA5 and YFL811, the correlations analysis between the TCA-
soluble proteins and the growth (%) were not statistically significant (p < 0.10).
Table 1 - Matrix of the simple centroid mixture design used to study the growth promotion of
bifidobacteria and lactic acid bacteria species in media supplemented with different protein
sources and their hydrolysates obtained by enzymatic hydrolysis and results for TCA-soluble
proteins.
a, b, c...The results are presented as the mean (n = 3) ± SD, and those with different letters are significantly different, with p < 0.05.
Tukey tests were applied between the runs for each response (not between different responses). YFL811 (Streptococcus
thermophilus and Lactobacillus delbrueckii), LA5 (Lactobacillus acidophilus) and BB12 (Bifidobacterium lactis). The controls
assays were considered 100%.
Run
Independent variables YFL811 growth (%) LA5 growth (%)
x1
(SPI) x2
(BWP) x3
(EWP)
Non-
hydrolyzed Hydrolysates
Non-
hydrolyzed Hydrolysates
1 1 0 0 108.35 ± 1.45a 106.85 ± 2.45
c, d 102.19 ± 1.54
a, b 119.44 ± 0.98
a
2 0 1 0 107.85 ± 3.82a 112.23 ± 1.83
a, b 104.52 ± 2.06
a 116.32 ± 1.83
b, c
3 0 0 1 89.17 ± 1.66b 107.87 ± 2.38
c, d 77.14 ± 2.34
d 116.89 ± 1.85
a, b
4 1/2 1/2 0 106.54 ± 2.19a 110.77 ± 1.68
b, c 103.62 ± 2.94
a, b 116.75 ± 1.16
a, b
5 1/2 0 1/2 93.13 ± 3.77b 106.73 ± 2.52
d 98.23 ± 2.83
b, c 113.51 ± 1.46
c, d
6 0 1/2 1/2 89.41 ± 2.53b 114.95 ± 2.51
a 71.66 ± 6.33
d 116.60 ± 1.94
a, b
7 1/3 1/3 1/3 92.87 ± 2.20b 107.62 ± 2.42
c, d 93.27 ± 1.99
c 112.92 ± 2.31
d
BB12 growth (%) TCA-soluble proteins (mg/100mg)
Non-
hydrolyzed Hydrolysates
Non-
hydrolyzed Hydrolysates
1 1 0 0 107.09 ± 7.37c, d
109.23 ± 3.38c 30.70 ± 0.71
a 62.47 ± 1.91
a, c
2 0 1 0 113.32 ± 9.12b, c
125.23 ± 5.45a 37.24 ± 1.63
b 56.70 ± 1.67
b
3 0 0 1 128.88 ± 7.15a 114.85 ± 1.89
b, c 16.42 ± 0.13
c 63.79 ± 2.78
a, c
4 1/2 1/2 0 104.14 ± 4.84c, d
117.06 ± 4.00b 36.03 ± 0.99
b 65.07 ± 1.67
a
5 1/2 0 1/2 122.85 ± 3.42a, b
100.69 ± 2.68d 17.42 ± 0.24
c 61.72 ± 0.71
a, c
6 0 1/2 1/2 119.65 ± 9.37a, b
100.12 ± 4.62d 16.99 ± 0.11
c 59.58 ± 2.06
b, c
7 1/3 1/3 1/3 124.30 ± 3.21a, b
96.89 ± 3.70d 17.65 ± 0.12
c 62.68 ± 1.41
a, c
229
It is well documented that various substances can stimulate the growth of certain bacteria
strains, among these, the protein hydrolysates have been investigated by provide a more readily
available source of peptides or amino acids needed for growth of the probiotic cultures
(McComas Jr. & Gilliland, 2003; Zhang et al., 2011; Prasanna, Grandison & Charalampopoulos,
2012). McComas Jr. & Gilliland (2003) investigated the growth of probiotic bacteria in milk
supplemented with whey protein hydrolysates. The results obtained in their research showed that
the hydrolysates had no effect on the growth of L. delbrueckii ssp. bulgaricus and S.
thermophilus; however, caused significant increases in growth of Bifidobacterium longum and L.
acidophilus. Prasanna, Grandison & Charalampopoulos (2012) studied the supplementation of
skim milk and the effects on the growth of probiotic bacteria. Their results showed that the type
of protein source had a clear effect on the cell growth of the tested strains, as the observed in our
work. The final cell concentration of B. longum subsp. infantis CCUG 52486 and B. infantis
NCIMB 702205 were higher when grown in milk supplemented with casein hydrolysates
compared with the other protein sources (lactalbumin hydrolysate, whey protein concentrate and
whey protein isolate).
3.2. Synergistic and antagonistic effects of the intact proteins and their hydrolysates on
the TCA-soluble proteins and bacteria growth (%)
The analysis of the interaction between the different protein sources and their mixtures
after enzymatic hydrolysis showed synergistic and antagonistic effects. The TCA-soluble proteins
showed a similar profile in the 7 runs of the statistical mixture design, ranging from 56.70 to
65.07 mg per 100 mg of total protein in sample. The interactions between the formulations: SPI
(1/2) plus EWP (1/2) (run 5), BWP (1/2) plus EWP (1/2) (run 6) and SPI, BWP and EWP (in
equal proportions) (run 7) were not statistically significant (p < 0.05).
In the study of the growth promotion of bifidobacteria and lactic acid bacteria strains,
the protein hydrolysates obtained as mixtures, showed antagonistic effects, resulting in a decrease
of the microorganisms growth (Table 1). The major growth reductions were observed in the
medium supplemented with the hydrolysates obtained from the ternary mixture (run 7), which
showed decreases of 11.3, 22.6 and 15.6% in BB12 growth as compared to the individual
substrates, respectively (Table 1).
230
3.3. Mixture contour plots for TCA-soluble proteins and bacteria growth (%)
The variations in the growth promotion of bifidobacteria and lactic acid bacteria strains
and TCA-soluble proteins of the hydrolysates obtained from SPI, BWP and EWP are also shown
using mixture contour plots (Fig. 1). Each factor or isolated component of the mixture is
represented on the response surface, in the corner of an equilateral triangle and the different
proportions of the components in the mixture are distributed at each point within this triangle.
The minimum concentration of each component of the mixture was located at the middle of the
opposite side of the triangle while the maximum was positioned at the corresponding corner
(Martinello et al., 2006). A contour plot provides a two-dimensional view where all points that
have the same response are connected to produce contour lines of constant responses (Rao &
Baral, 2011).
Fig. 1 - Mixture contour plots for growth of YFL 811 (a), LA5 (b) and BB12 (c) in the media
supplemented with protein hydrolysates and TCA-soluble proteins (d) of the protein
hydrolysates.
a b
> 119
< 119
< 118
< 117
< 116
< 115
< 114
< 113
0.00
0.25
0.50
0.75
1.00
EWP
0.00
0.25
0.50
0.75
1.00
SPI
0.00 0.25 0.50 0.75 1.00
BWP
> 114 < 114 < 112 < 110 < 108 < 106
0.00
0.25
0.50
0.75
1.00
EWP0.00
0.25
0.50
0.75
1.00
SPI
0.00 0.25 0.50 0.75 1.00
BWP
> 121
< 121
< 116
< 111
< 106
< 101
< 96
0.00
0.25
0.50
0.75
1.00
EWP
0.00
0.25
0.50
0.75
1.00
SPI
0.00 0.25 0.50 0.75 1.00
BWP
c
> 65
< 65
< 63
< 61
< 59
< 57
0.00
0.25
0.50
0.75
1.00
EWP
0.00
0.25
0.50
0.75
1.00
SPI
0.00 0.25 0.50 0.75 1.00
BWP
d
231
Profile changes in growth promotion were observed for each microorganism. For
YFL811, the maximum growth stimulation was observed in the medium supplemented with EWP
and BWP. However, from the contour plots for LA5 and BB12, the zones of maximum response
variables were located in the corner of triangle having BWP and SPI, respectively, as the vertices
(Fig. 1). The high levels of TCA-soluble proteins were observed in the mixtures containing SPI
and BWP. This can be verified by observing the mixture surface plots (Fig. 1).
3.4. Analysis of variance (ANOVA) and models for the TCA-soluble proteins and
bacteria growth (%)
The responses data based on the independent variables were obtained from the
experiments and recorded in Table 1. In the study of the growth promotion of bifidobacteria and
lactic acid bacteria species, the experiments were conducted with six replicates and for TCA-
soluble proteins, the experiments were performed in triplicates. In most all cases there was good
agreement between the original and replicates. All the independent and response variables were
fitted to linear, quadratic or special cubic models. The coefficient of determination R2 and the F
test (analysis of variance-ANOVA) were used to verify the quality of fit of the models. Table 2
shows the models and corresponding R2
of the regression equations for the responses, as well as
the corresponding F-ratio and p-values for each term in the predicted regression equations. Most
equations showed high coefficients of determination (R2), which were above 0.70 (Table 2),
indicate that all the response functions adequately fitted the experimental data, and the models
could be used for predictive purposes in the determination of the TCA-soluble proteins using the
different protein sources and their mixtures. Specially, in the study of the growth promotion of
probiotic and lactic acid bacteria species, some R2
obtained were below 0.70; however the models
were validated experimentally and were predictive (Table 3).
The negative quadratic (binary) and cubic (ternary) terms of fitted regression equation
showed the antagonistic effects as well the positive quadratic and cubic terms indicated
synergistic effects of the protein sources on the TCA-soluble proteins and bacteria growth (%).
The growth of probiotic and lactic acid bacteria species showed different responses
between the tested microorganisms. When the medium was supplemented with soy protein isolate
(x1), bovine whey protein (x2) and egg white protein (x3) (non-hydrolyzed), the highest positive
and significant effects on growth (%) were detected for YFL811, LA5 and BB12, respectively. In
232
the medium supplemented with hydrolysates, most all the interactions showed significant and
negative effects, except for YFL811 cultivated in medium supplemented with bovine whey
protein (x2) and egg white protein (x3), which stimulated positively the microorganism growth
(Table 2).
Table 2 – Models, R2, F-test and probability values for the final reduced models for TCA-soluble
proteins and bacterial growth.
YFL811 (Streptococcus thermophilus and Lactobacillus delbrueckii), LA5 (Lactobacillus acidophilus) and BB12
(Bifidobacterium lactis).
Validation tests were performed to determine the accuracy of the polynomial models
obtained for TCA-soluble proteins and bacterial growth of the protein hydrolysates using
different formulations with three assays (Table 3). According to the regression models (Table 2),
the experimental values agreed with the values predicted by the models within a 95% confidence
interval, thereby confirming the validity of the models for the evaluated responses (Table 3).
Responses Models Equations (non-hydrolyzed proteins) F-test R² p-value
TCA-soluble
proteins (%) Special cubic
Y = 30.70x1 + 37.24x2 + 16.42x3 + 8.25x1x2 – 24.55x1x3 – 39.35x2x3 – 115.61x1x2x3
215.30 0.99 <0.001
YFL811 growth (%) Quadratic Y = 107.71x1 + 107.21x2 + 89.34x3 –
24.41x1x3 – 38.29x2x3 35.99 0.91 <0.001
LA5 growth (%) Special cubic Y = 102.28x1 + 104.61x2 + 77.14x3 +
34.08x1x3 – 76.86x2x3 + 90.35x1x2x3 48.41 0.95 <0.001
BB12 growth (%) Special cubic Y = 108.84x1 + 112.54x2 + 129.86x3 –
26.22x1x2 – 273.72x1x2x3 6.08 0.63 <0.001
Equations (hydrolysates)
TCA-soluble
proteins (%) Quadratic Y = 62.00x1 + 56.51x2 + 63.05x3 + 22.04x1x2 5.92 0.70 <0.001
YFL811 growth (%) Special cubic Y = 107.02x1 + 112.69x2 + 107.58x3 +
19.24x2x3 – 97.76x1x2x3 6.48 0.65 <0.001
LA5 growth (%) Special cubic Y = 119.05x1 + 115.99x2 + 116.95x3 –
17.97x1x3 – 65.09x1x2x3 5.65 0.62 <0.001
BB12 growth (%) Special cubic Y = 109.17x1 + 125.17x2 + 114.85x3 –
45.27x1x3 – 79.57x2x3 – 152.33x1x2x3 21.13 0.88 <0.001
233
Table 3 - Validation tests performed to determine the adequacy of the polynomial models
obtained for bacterial growth and TCA-soluble proteins of the protein hydrolysates in different
formulations.
Results are presented as the mean (n = 3) ± SD, and those with different letters are significantly different, with p < 0.05.
Comparisons were made between the observed and predict values for each correspondent response. YFL811 (Streptococcus
thermophilus and Lactobacillus delbrueckii), LA5 (Lactobacillus acidophilus) and BB12 (Bifidobacterium lactis).
3.5. Effect of the concentration of the protein hydrolysates on cell growth
In order to study the possible effects of different concentrations of the protein
hydrolysates on the growth stimulation of the bifidobacteria and lactic acid bacteria strains, levels
ranging from 0.5 to 25 mg mL-1
were used for supplementation of the culture media. The specific
hydrolysates with the highest stimulation growth, considering the difference between the
hydrolyzed and the non-hydrolyzed samples on growth promotion, were selected for each culture;
for YFL811 and LA5 were used the medium supplemented with the mixture of EWP (1/2) and
BWP (1/2) hydrolyzed and for BB12 was used the medium supplemented with the mixture of SPI
(1/2) and BWP (1/2) hydrolyzed. Significant (p < 0.05) differences on BB12 growth were
observed when the medium was supplemented with SPI and BWP from 0.5 up to 25 mg mL-1
.
The Pearson coefficient showed a positive and significant correlation between the concentration
and the BB12 growth (%) in the presence of protein hydrolysates (Pearson coefficient = 0.95; p <
0.001), indicating that the growth increased as the concentration increased (Fig. 2). However, the
effects on LA5 growth of the medium supplemented with EWP and BWP hydrolysates at
different concentrations were less noticeable. The LA5 growth ranged from 123.3 to 129.4% at
0.5 and 25 mg mL-1
, respectively; no significant differences in the growth were observed when
the concentration ranged from 10 to 25 mg mL-1
(Fig. 2).
Responses
Independent variables Predicted
response
Experimental
response x1
(SPI)
x2
(BWP)
x3
(EWP)
TCA-soluble proteins (%) 0.33 0.34 0.33 62.95a 61.07 ± 2.85
a
YFL811 growth (%) 0.00 0.50 0.50 114.95b 117.52 ± 17.63
b
LA5 growth (%) 0.00 0.50 0.50 116.47c 123.26 ± 9.04
c
BB12 growth (%) 0.50 0.50 0.00 117.17d 118.47 ± 6.21
d
234
Fig. 3 - Influence of different concentrations of protein hydrolysates in supplemented media on
the growth of YFL811 (S. thermophilus and L. delbrueckii), LA5 (L. acidophilus) and BB12 (B.
lactis).
0
50
100
150
200
250
0 0.5 2.5 5 10 15 20 25
YF
L811 g
row
th (
%)
Concentration (mg mL-1)
0
20
40
60
80
100
120
140
0 0.5 2.5 5 10 15 20 25
LA
5 g
row
th (
%)
Concentration (mg mL-1)
0
20
40
60
80
100
120
140
160
180
200
0 0.5 2.5 5 10 15 20 25
BB
12
gro
wth
(%
)
Concentration (mg mL-1)
235
The Pearson coefficient was 0.59 (p = 0.12), indicating that there is not a linear
correlation between the LA5 growth and the concentration of the protein hydrolysates. Overall,
there was a good correlation between the YFL811 growth (%) and the EWP and BWP
concentrations (Pearson coefficient = 0.85; p = 0.008). More specifically, there was 2-fold
increase in the YFL811 growth as the EWP and BWP hydrolysates supplementation was
increased from 0 (control) to 20 mg mL-1
; no significant differences in the YFL811 growth were
observed when the medium was supplemented with EWP and BWP hydrolysates ranged from 5
to 25 mg mL-1
(Fig. 2).
4. Conclusion
The results suggest that the application of the statistical mixture designs for enzymatic
hydrolysis of different protein sources is an attractive process for improving the performance and
to find the optimum mixture formulations of proteins for growth promotion of bifidobacteria and
lactic acid bacteria strains. It was possible to observe the maximization of responses when the
mixtures were used compared to the isolated substrates. Compared with control, the cell growth
of L. bulgaricus plus S. thermophilus, L. acidophilus and B. lactis were increased with the
supplementation of the media with mixtures of BWP (1/2) plus EWP (1/2) and SPI (1/2) plus
BWP (1/2) at 25 mg mL-1
in 100.0, 29.4 and 86.2%, respectively.
Acknowledgements
The work described in this paper was substantially supported by grants from São Paulo
Research Foundation – FAPESP (Project No. 2011/10429-9), the Department of Food Science,
School of Food Engineering, University of Campinas, which are gratefully acknowledged.
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238
239
Capítulo XI: Synergistic actions of proteolytic enzymes for production of
soy protein isolate hydrolysates with antioxidant activities: an approach
based on enzymes specificities
Revista: Food Chemistry
240
Abstract
The objective of this study was investigate the enzymatic hydrolysis of soy protein isolate by
screening individual and blended commercial protease preparations using a statistical mixture
design. Information about the modulation of thermal inactivation of the enzyme by substrate or
products of hydrolysis and the determination of synergistic effects between the enzymes on
production of soy protein hydrolysates with antioxidant activities were reported. The kinetic
parameters for thermal inactivation measured under reactive and non-reactive conditions
indicated that product inhibition was not significant on soy protein hydrolysis using the
commercial proteases FlavourzymeTM
500L, AlcalaseTM
2.4L and YeastMaxTM
A. The
antioxidant activities showed different results in each method used. For DPPH radical
scavenging, the hydrolysates obtained with FlavourzymeTM
500L combined with AlcalaseTM
2.4L
showed the higher synergistic effect with increases of 10.9 and 13.2% in antioxidant activity as
compared to the hydrolysates produced with individual enzymes. The hydrolysates obtained
using the ternary mixtures of FlavourzymeTM
500L, AlcalaseTM
2.4L and YeastMaxTM
A showed
the highest power of inhibition of linoleic acid autoxidation. On the other hand, for reducing
power assay and total antioxidant activity, the most of all interactions was antagonistic with high
antioxidant activity detected for the hydrolysates produced using FlavourzymeTM
500L,
individually.
Keywords: proteases, enzyme specificity, antioxidant activities, mixture design
241
1. Introduction
Proteases constitute the most important category of industrial enzymes that catalyze the
hydrolysis of proteins to polypeptides and oligopeptides to amino acids (Abraham et al., 2014).
These enzymes can be classified according with their biochemical characteristics such as
mechanisms of action, catalytic sites or based on the pH for maximum activity. Proteases that
cleave peptide bonds within the polypeptide chain are called endopeptidases and those that cleave
peptides bonds at the N or C termini of polypeptide chains are classified as exopeptidases
(López-Otín & Bond, 2008; Hsiao et al., 2014). According to the catalytic sites, these enzymes
are classified in six groups: aspartic, cysteine, glutamic, serine and threonine proteases,
depending upon the amino acids present in the active site, or as metalloproteases if a metal ion is
required for catalytic activity (Li et al., 2013). They may further classified in acidic, neutral and
alkaline proteases depending on the pH at which they show the maximum activity (Ktari et al.,
2014). Through structural and functional diversity, proteases carry out a vast array of
applications, including food production (eg. baking and brewing), leather processing,
pharmaceutical manufacture, detergent formulations and protein modification (eg. protein
hydrolysis and peptide synthesis) (Anbu, 2013).
Enzymatic hydrolysis disrupts the protein tertiary structure and reduces the molecular
weight of the protein, enhancing the interaction of peptides with themselves and with the
environment, and consequently altering their functional and biological properties (Liu et al.,
2010). Notably, the nature of the protein modification is influenced by several hydrolysis
parameters, including the reaction conditions, such as pH, temperature, degree of hydrolysis, and
enzyme specificities, and intrinsic characteristics of each protein source, such as amino acids
profile (Singh, 2011; Segura-Campos et al., 2012; Fernández & Riera, 2013). The modification
of proteins based on enzymatic hydrolysis have broad potential and are likely an innovative tool
in food protein processing for optimizing the functional and biological properties of proteins
(Hiller & Lorenzen, 2009; Adjonu et al., 2013).
The combined use of proteases with different specificities and mechanisms of action can
be applied as a valuable tool to improving the functional and biological properties of protein
hydrolysates. Prior knowledge about enzyme characteristics such as purity, substrate specificity,
specific activity, single or multiple enzymatic activity have been used to obtain products
242
containing multifunctional peptides) or a mixture of different peptides with each contributing to a
specific function (Rui et al., 2012; Betancur-Ancona et al., 2014; Li-Chan, 2015).
Statistical methods have been applied for improving the performance, to find the optimum
process variables and formulations in different engineering problems (Rao & Baral, 2011).
Statistical mixture designs are an interesting class of experimental designs where the components
or factors distributed in different proportions are used to verify the interactions between the
components of a mixture and maximizing the responses studied using mixture design approach.
The general purpose of mixture design is to make possible estimates, through a contour
plots analysis of evaluated responses of a multicomponent system from a limited number of
experiments (Anarjan & Tan, 2013). In this experimental design, the total amount of material is
held constant because the response depends only on the proportions of the components present,
but not on the total amount of the mixture (Rao & Baral, 2011; Anarjan & Tan, 2013). In the
simplex centroid design, 2k
- 1 observations are taken, where k is the pure components, (k/2) is
the binary mixtures with equal proportions and (k/3) is the ternary mixtures with equal
proportions (Scheffe, 1963).
In this context, the soy protein isolate hydrolysis was investigated by screening
individual and blended commercial protease preparations using a statistical mixture design. The
study of thermal inactivation modulation of the enzyme by the substrate or products from soy
protein isolate hydrolysis using kinetic parameters was reported. The synergistic or antagonistic
effects between the different proteolytic enzymes on generation of protein hydrolysates with
antioxidant activities were further assessed.
243
2. Material and Methods
2.1. Reagents
Ammonium thiocyanate, ferrous chloride, linoleic acid, azocasein, trichloroacetic acid
(TCA), 2,2-diphenyl-1-picrylhydrazyl (DPPH) were purchased from Sigma-Aldrich (Steinheim,
Germany). All other chemicals were purchased in the grade commercially available.
2.2. Enzymes
Three commercial preparations of proteolytic enzymes were used in this study. The
proteases FlavourzymeTM
500L from Aspergillus oryzae and AlcalaseTM
2.4L from Bacillus
licheniformis were purchased from Sigma Aldrich (Steinheim, Germany). The protease
YeastMaxTM
A was kindly provided by Prozyn (Sao Paulo, Brazil).
2.3. Determination of protease activity
The protease activity was measured using azocasein as a substrate, according to Charney
and Tomarelli (1947), with modifications proposed by Castro and Sato (2013). The reaction
mixtures containing 0.5 mL 0.5% (w/v) azocasein, pH 7.0, and 0.5 mL of the enzyme solutions
were incubated for 40 min at 50 °C. The reaction was stopped by adding 0.5 mL 10% TCA and
the test tubes were centrifuged at 17,000 x g for 15 min at 25 °C. A 1.0 mL aliquot of the
supernatant was neutralized with 1.0 mL 5 M KOH. One unit of enzyme activity (U) was defined
as the amount of enzyme required to increase the absorbance at 428 nm by 0.01 under the assay
conditions described.
2.4. Kinetic parameters for thermal inactivation
The thermal stability of the commercial proteases as a function of the time was evaluated
at reactive (50 U mL-1
of protease and 100 mg mL-1
soy protein isolate solution pH 7.0) e non-
reactive (50 U mL-1
of protease and 0.2M phosphate buffer pH 7.0) conditions. For this, the
samples were incubated at 50 °C and aliquots were collected at various times for determination of
the residual protease activity. The value of the deactivation rate constant (kd) for the proteases,
expressed as an exponential decay, was found by plotting ln (A/A0) vs. time using the
experimental data as follows:
A = A0 × e-kdt
244
Where t is time, A0 is the initial enzyme activity and A is the enzyme activity at a determined
time t.
The apparent half-life of the proteases, defined as the time where the residual activity
reaches 50%, was estimated as follows:
t1/2 = ln (0.5) / kd
Decimal reduction time (D value) was defined as the time required for a one-log10
reduction or 90% reduction in the initial enzyme activity at a specific temperature. The D value is
related to the first-order deactivation rate constant (kd) and it was calculated as follows:
D = 2.303 / kd
2.5. Preparation of protein hydrolysates
The soy protein isolate was kindly provided by Bunge Foods S/A (Gaspar, Brazil). The
commercial proteases, FlavourzymeTM
500L, AlcalaseTM
2.4L and YeastMaxTM
A were used for
enzymatic hydrolysis. The enzyme concentrations were adjusted to 0 (control) or 50 U per mL of
reaction mixture according to the previously determined protease activity. The soy protein isolate
was suspended in phosphate buffer pH 7.0 to a final concentration of 100 mg mL-1
, and 50 mL
aliquots of the mixtures were distributed in 125 mL Erlenmeyer flasks. Hydrolysis was
performed at 50 °C and pH 7.0 for 120 min. After hydrolysis, the samples were incubated in a
water bath at 100 °C for 20 min for proteases inactivation. The mixtures were centrifuged at
17,000 x g at 5 °C for 20 min, and the supernatants containing the peptides were collected and
freeze-dried for the determination of their antioxidant activities and TCA soluble protein
contents.
2.6. Statistical mixture design
The experimental mixture design was used to obtain the optimum mixture compositions
of the different proteolytic enzymes for maximum antioxidant activities and to investigate the
presence of either synergistic or antagonistic effects in a blend of the components. A three
component augmented simplex centroid design was employed in which each component was
studied at six levels, namely 0 (0%), 1/6 (16.67%), 1/3 (33%), 1/2 (50%), 2/3 (66.67%) and 1
(100%) (Table 1).
245
Table 1 – Matrix of the simplex centroid mixture design for soy protein isolate hydrolysis using
different sources of commercial proteases and their mixtures and study of the antioxidant
properties of the hydrolysates.
Quadratic or special cubic regression models were fitted for the variations of all the
responses studied as a function of significant (p < 0.05) interaction effects between the
proportions, thereby obtaining acceptable determination coefficients (R² > 0.75). Equation 1
represents these models as follows:
where ‘Yi’ is the predicted response; ‘q’ represents the number of components in the system; ‘Xi,
Xj, Xk’ are the coded independent variables; ‘βi’ is the regression coefficient for each linear effect
term; and ‘βij’ and ‘βijk’ are the binary and ternary interaction effect terms, respectively.
StatisticaTM
10 software from Statsoft Inc. (Tulsa, Oklahoma, USA) was employed for the
experimental design, data analysis and model building.
𝑌𝑖 = 𝛽𝑖𝑋𝑖 + 𝛽𝑖𝑗
𝑞
𝑖<𝑗
𝑞
𝑖=1
𝑋𝑖𝑋𝑗 + 𝛽𝑖𝑗𝑘𝑋𝑖𝑋𝑗𝑋𝑘
𝑞
𝑖<𝑗<𝑘
Run
Independent variables
FlavourzymeTM
500L AlcalaseTM
2.4L YeastMaxTM
A
x1 x2 x3
1 1 0 0
2 0 1 0
3 0 0 1
4 1/2 1/2 0
5 1/2 0 1/2
6 0 1/2 1/2
7 2/3 1/6 1/6
8 1/6 2/3 1/6
9 1/6 1/6 2/3
10 1/3 1/3 1/3
246
2.7. Determination of TCA soluble protein content
The TCA soluble protein content of the hydrolysates was determined using a modified
version of the method described by Pericˇin et al. (2009). A 1.0 mL aliquot of the hydrolysate
was added to an equal volume of 0.44 mol L-1
trichloroacetic acid (TCA). The mixture was
incubated for 30 min at room temperature and then centrifuged at 17,000 x g for 15 min. The
protein content of the supernatant (0.22 mol L-1
TCA soluble protein fraction) and the supernatant
of the hydrolysate mixture (without the addition of TCA) was analyzed by the Lowry method
(1951), using bovine serum albumin as the standard protein. The results were expressed as a
percentage and were calculated as the ratio of the 0.22 mol L-1
TCA soluble protein content to the
total protein content in the supernatant of the hydrolysate mixture.
2.8. Determination of antioxidant activities
2.8.1. DPPH radical-scavenging activity
The DPPH radical-scavenging activity of the protein hydrolysates was determined as
described by Bougatef et al. (2009). An aliquot (500 µL) of each sample (5 mg mL-1
) was mixed
with 500 µL of 99.5% ethanol and 125 µL of DPPH (0.2 mg mL-1
) in 99.5% ethanol. The
mixture was then kept at room temperature in the dark for 60 min, and the reduction of the DPPH
radical was measured at 517 nm using a UV-Visible spectrophotometer. The DPPH radical-
scavenging activity was calculated as follows:
Radical scavenging activity (%) = [(Absorbance of control - Absorbance of sample) / (Absorbance of
control)] * 100.
2.8.2. Inhibition of linoleic acid autoxidation
The lipid peroxidation inhibition activity was measured in a linoleic acid emulsion system
according to the method described by Nazeer & Kulandai (2012) with slight modifications. A 20
mg aliquot of each hydrolysate was dissolved in 10 mL of 50 mM phosphate buffer (pH 7.0) and
was later added to 130 µL of a linoleic acid solution and 10 mL of 99.5% ethanol. The total
volume was then adjusted to 25 mL with distilled water. The mixture was incubated in a 50-mL
assay tube with a screw cap at 42 ± 1 °C for 24 h in a dark room. The degree of oxidation of
linoleic acid was measured using the ferric thiocyanate method of Sakanaka et al. (2004) with
slight modifications. An aliquot of 0.1 mL of the reaction mixture was mixed with 4.7 mL of
247
75% ethanol, 0.1 mL of 30% ammonium thiocyanate and 0.1 mL of 20 mM ferrous chloride
solution in 3.5% HCl and after a 3-min incubation at room temperature, the color development,
which represents the linoleic acid oxidation, was measured at 500 nm. The antioxidant capacity
of inhibiting peroxide formation in the linoleic acid system was expressed as follows:
Inhibition (%) = [(Absorbance of control - Absorbance of sample) / (Absorbance of control)] * 100.
2.8.3. Reducing power assay
The capacity of the protein hydrolysates to reduce iron (III) was determined according to
the method described by Yildirim et al., (2001) with slight modifications. A 0.2 mL aliquot of
each protein hydrolysate at 10 mg mL-1
was mixed with 0.5 mL of 0.2 M phosphate buffer (pH
6.6) and 0.5 mL of 1% potassium ferricyanide. The reaction mixtures were incubated at 50 °C in
the dark and after 30 min, 0.5 mL of 10% (w/v) trichloroacetic acid was added. The reaction
mixtures were centrifuged at 8000 x g for 10 min at 5 °C and 0.75 mL of the supernatant
solutions were collected and mixed with 0.75 mL of distilled water and 0.15 mL of 0.1% (w/v)
ferric chloride. The absorbance of the final solution was measured after 10 min reaction at 700
nm. The results were expressed in function of the absorbance considering that the absorbance was
directly proportional to the reducing power.
2.8.4. Total antioxidant capacity
Total antioxidant capacity of the hydrolysates was performed according to the method
described by Prieto et al., (1999). An aliquot of 0.1 mL of the protein hydrolysates solutions at 10
mg mL-1
was mixed with 1.0 mL of the reagent solution containing 0.6 M sulphuric acid, 28 mM
sodium phosphate and 4 mM ammonium molybdate. The reaction mixtures were then incubated
at 90 °C and kept in the dark for 90 min. The samples were cooled to room temperature and the
absorbance was measured at 695 nm. An appropriate control was prepared with 1.0 mL of the
reagent solution and 0.1 mL distilled water. The results were expressed in function of the
absorbance considering that the absorbance was directly proportional to the total antioxidant
capacity.
248
2.9. Calculations and statistics
The statistical analyzes were performed using the MinitabTM
16.1.1 software package
from Minitab Inc. (USA). Values are expressed as the arithmetic mean. The Tukey test was used
to test for significant differences between the groups analyzed. The differences were considered
significant at p < 0.05.
Pearson correlation coefficient was used to measure the strength of linear dependence
between two responses. The correlation coefficient ranges from – 1 to 1. A value of 1 implies that
a linear equation describes the relationship between the responses was perfectly and positive,
while a value of -1 indicate a perfectly and negative correlation. A value of 0 implies that there is
no linear correlation between the responses. The correlations between analyzed parameters were
considered significant at p-value < 0.10.
3. Results and Discussion
3.1. Investigation of thermal inactivation modulation of the enzyme by the substrate or
products from soy protein isolate hydrolysis using kinetic parameters
The commercial enzymes FlavourzymeTM
500L, AlcalaseTM
2.4L and YeastMaxTM
A
showed 5,489.33 U mL-1
, 327,760.00 U mL-1
and 10,900.67 U g-1
of protease activity,
respectively.
In order to assess the modulation of the thermal inactivation of the enzyme by the
substrate or products during enzymatic hydrolysis, experiments were carried out at reactive
conditions, in which the residual protease activities were measured in the presence of soy protein
isolate at 100 mg mL-1
pH 7.0, and non-reactive conditions, performed in 0.2 M phosphate buffer
solution pH 7.0. The protease activities were determined as a function of time at 50 °C and the
results were presented in Figure 1. The protease activities decreased with increasing reaction
times, retaining approximately 21.43, 26.37 and 18.59% of the initial activity after 180 min under
reactive conditions and residual activities of 9.10, 20.83 and 10.69% after the same time under
non-reactive conditions for FlavourzymeTM
500L, AlcalaseTM
2.4L and YeastMaxTM
A,
respectively (Figure 1). These data were used to estimate the kinetic parameters for thermal
inactivation of the proteases using Arrhenius plots (Figure 2).
249
Figure 1 - Residual protease activities for commercial enzymes FlavourzymeTM
500L (a), AlcalaseTM
2.4L (b) and YeastMaxTM
A (c) under non-reactive and reactive conditions.
a
b
c
0
20
40
60
80
100
0 30 60 90 120 150 180
Res
idu
al a
ctiv
ity (
%)
Time (min)
Non-reactive Reactive
0
20
40
60
80
100
0 30 60 90 120 150 180
Res
idu
al a
ctiv
ity (
%)
Time (min)
Non-reactive Reactive
0
20
40
60
80
100
0 30 60 90 120 150 180
Res
idu
al a
ctiv
ity (
%)
Time (min)
Non-reactive Reactive
250
Figure 2 – Arrhenius plots for FlavourzymeTM
500L (a, A), AlcalaseTM
2.4L (b, B) and
YeastMaxTM
A (c, C) inactivation under non-reactive and reactive conditions, respectively.
0 30 60 90 120 150 180
Time (min)
-2.0
-1.6
-1.2
-0.8
-0.4
0.0
ln (
A/A
0)
0 30 60 90 120 150 180
Time (min)
-2.5
-2.0
-1.5
-1.0
-0.5
0.0ln
(A
/A0)
0 30 60 90 120 150 180
Time (min)
-1.8
-1.5
-1.2
-0.9
-0.6
-0.3
0.0
ln (
A/A
0)
0 30 60 90 120 150 180
Time (min)
-1.5
-1.2
-0.9
-0.6
-0.3
0.0
ln (
A/A
0)
0 30 60 90 120 150 180
Time (min)
-2.4
-2.0
-1.6
-1.2
-0.8
-0.4
0.0
ln (
A/A
0)
0 30 60 90 120 150 180
Time (min)
-1.8
-1.5
-1.2
-0.9
-0.6
-0.3
0.0
ln (
A/A
0)
y = -0.0124x – 0.2314
R² = 0.98
y = -0.0083x – 0.0825
R² = 0.98
y = -0.0084x – 0.1806
R² = 0.94 y = -0.0066x – 0.2076
R² = 0.92
y = -0.0115x – 0.4521
R² = 0.91
y = -0.0086x – 0.2162
R² = 0.95
a A
b B
c C
251
The half-life (t1/2) of an enzyme, at a given temperature, is the time it takes for the activity
to reduce to a half of its original/initial activity. The decimal reduction time (D value) is defined
as the time required for a 90% reduction in the initial enzyme activity. Higher values of these
parameters at the specific operating temperature are important and desirable for industrial
applications since indicate the resistance of the enzyme to thermal inactivation. AlcalaseTM
2.4L
showed the highest thermal resistance when compared to the other proteases, reaching D value of
348.88 min and t1/2 of 105.02 min at 50 °C under reactive conditions. There is a clear indicative
that in the presence of soy protein isolate, the commercial proteases showed higher thermal
stability. FlavourzymeTM
500L, AlcalaseTM
2.4L and YeastMaxTM
A presented an increase in the
half-life from 55.90 min to 83.51 min, 82.52 to 105.02 min and 60.27 to 80.60 min, respectively,
in the presence of substrate protein (Table 2).
Table 2 - Kinetic parameters for thermal deactivation of commercial preparations of proteases
under non-reactive and reactive conditions.
It was observed that residual protease activities of AlcalaseTM
2.4L under non-reactive
conditions were higher than reactive conditions during the first 45 min reaction at 50 °C. After
this time, a positive modulation increased progressively with the soy protein isolate hydrolysis
(reactive conditions), suggesting that smaller protein/peptides had a greater stabilizing effect for
this enzyme. The loss of protease activity for FlavourzymeTM
500L and YeastMaxTM
A presented
lower rates when considering the same reaction times under reactive and non-reactive conditions
until 120 min, indicating that the presence of smaller protein molecules was also important to
stabilize these enzymes (Table 2). These results evidenced that the product inhibition phenomena
was not significant on soy protein hydrolysis using these commercial preparations.
Protease Non-reactive conditions
kd (min-1
) t1/2 (min) D (min) R²
FlavourzymeTM
500L 0.0124 55.90 185.69 0.98
AlcalaseTM
2.4L 0.0084 82.52 274.12 0.94
YeastMaxTM
A 0.0115 60.27 200.23 0.91
Reactive conditions
FlavourzymeTM
500L 0.0083 83.51 277.42 0.98
AlcalaseTM
2.4L 0.0066 105.02 348.88 0.92
YeastMaxTM
A 0.0086 80.60 267.74 0.95
252
3.2. Synergistic and antagonistic effects of the proteases on production of soy protein
isolate hydrolysates with antioxidant activities
The interactions amongst the three commercial proteases on production of soy protein
isolate hydrolysates and study of their antioxidant properties were studied in the 10 assays using a
simplex centroid mixture design (Table 3). The antioxidant activities of the hydrolysates were
evaluated using a DPPH radical-scavenging, inhibition of linoleic acid autoxidation, reducing
power assay and total antioxidant capacity.
The variations in the antioxidant activities of the hydrolysates obtained from different
proteases were depicted using mixture contour plots (Figure 3 and Figure 4). On the response
surfaces, each factor (pure mixture component) is represented in the corner of an equilateral
triangle, and each point within this triangle refers to a different proportion of the components in
the mixture. The maximum percentage of each ingredient considered by the regression is placed
at the corresponding corner, and the minimum percentage is positioned at the middle of the
opposite side of the triangle (Martinello et al., 2006). A contour plot provides a two-dimensional
view where all points that have the same response are connected to produce contour lines of
constant responses (Rao & Baral, 2011).
The correlation analysis between the antioxidant activities measured by different methods
showed the following results: DPPH vs. inhibition of linoleic acid autoxidation (Pearson
coefficient = 0.41; p-value = 0.02), DPPH vs. total antioxidant capacity (Pearson coefficient =
0.07; p-value = 0.71), DPPH vs. reducing power (Pearson coefficient = 0.31; p-value = 0.09),
inhibition of linoleic acid autoxidation vs. total antioxidant capacity (Pearson coefficient = -0.09;
p-value = 0.61), inhibition of linoleic acid autoxidation vs. reducing power (Pearson coefficient =
0.03; p-value = 0.88) and total antioxidant capacity vs. reducing power (Pearson coefficient =
0.91; p-value < 0.01). It can be observed that no significant correlations were detected for most of
the analyzed responses, because the antioxidant methods have different reaction mechanisms and
consequently measure particular antioxidant capacities. Methods based on the same reaction
mechanism, as total antioxidant capacity and reducing power that measure the electron donation
capacity of antioxidant molecules, showed a positive and significant correlation.
DPPH is a relatively stable organic radical that is characterized by a deep purple color and
a maximum absorbance at 515–520 nm. When DPPH encounters a hydrogen-donating substance,
253
the radical is scavenged, and the absorbance is reduced. Therefore, DPPH is widely used as a
substrate to evaluate the efficacy of antioxidants (Gao et al., 2010). DPPH-radical scavenging
showed synergistic effects for all assays performed using binary mixtures of proteases (runs 4-6).
The hydrolysates obtained with FlavourzymeTM
500L (0.5) combined with AlcalaseTM
2.4L (0.5)
(run 4) showed the higher synergistic effect with increases of 10.9 and 13.2% in antioxidant
activity as compared to the hydrolysates produced with individual enzymes (runs 1-2),
respectively, and reaching a maximum DPPH radical scavenging of 70.84% at 5 mg mL-1
(Table
3). From the contour plots for DPPH assay, the zones of maximum response variables were
located towards the side of triangle having mixtures of FlavourzymeTM
500L and AlcalaseTM
2.4L as the vertices (Figure 3a). This indicates that to certain extent, these enzyme proportions
may be added to improve the antioxidant activities of the soy protein hydrolysates.
A complex process that involves formation and propagation of free radicals in the
presence of oxygen is the lipid peroxidation. Antioxidant peptides can inhibit this process afford
their protective actions in lipid peroxidation by scavenging the lipid-derived radicals (R•, RO• or
ROO•) (Nazeer et al., 2012). For the inhibition of linoleic acid autoxidation, the ternary mixtures
of proteases presented important synergistic effects, while the binary mixtures showed no
significant effects. The contour plot analysis indicated that the soy protein isolate hydrolysis
using the ternary mixtures of the proteases in equal proportions resulted in the highest inhibition
of linoleic acid autoxidation (Figure 3b). This can also be confirmed in run 10 that showed
increase of approximately 3-fold in the ability to inhibit the linoleic acid autoxidation as
compared to the hydrolysates obtained using individual enzymes, and reached maximum values
about 60% inhibition at 0.8 mg mL-1
(Table 3).
Soy protein hydrolysates demonstrated electron-donating capacity and thus they may act
as radical chain terminators, transforming reactive free radical species into more stable non-
reactive products (Dorman et al., 2003; Arabshahi-Delouee & Urooj, 2007). This mechanism is
the basis for total antioxidant capacity and reducing power methods. For the reducing power
assay, the presence of antioxidant in tested samples results in the reduction of Fe3+
/ferricyanide
complex to ferrous form (Yildirim et al., 2000; Bougatef et al., 2009). Whereas, total antioxidant
capacity is based on the reduction of Mo (VI) to Mo (V) by the antioxidant agent and the
subsequent formation of a green phosphate/Mo (V) complex at acidic pH (Prieto et al., 1999;
254
Bougatef et al., 2009). The results for both assays were similar and showed maximum responses
for the hydrolysates obtained using FlavourzymeTM
500L (run 1) (Figure 3c and 3d). Since the
values obtained for run 1 in these assays were too high compared to the other runs, most of the
observed interaction effects were antagonistic, resulting in decreased of the antioxidant capacity
of the hydrolysates (Table 3).
Table 3 - Matrix of the simplex centroid mixture design used to study the antioxidant activities of
soy protein isolate hydrolysates obtained different proteases and their mixtures.
a, b, c...The results are presented as the mean (n = 3) ± SD, and those with different letters are significantly different, with p < 0.05.
Tukey tests were applied between the runs for each response (not between different responses). 1The non-hydrolyzed sample was
used as the control. 2Results presented as the absorbance at 700 nm. 3Results presented as the absorbance at 695 nm.
Runs DPPH radical
scavenging (%)
Inhibition of linoleic
acid autoxidation (%)
Reducing power
assay2
Total antioxidant
capacity3
Control1 51.14 ± 1.30
f 17.48 ± 6.23
a 0.1287 ± 0.01
h 0.2186 ± 0.01
g
1 63.83 ± 1.03c, d, e
15.39 ± 4.95a 0.3993 ± 0.03
a 0.7032 ± 0.01
a
2 62.57 ± 2.42d, e
15.59 ± 4.77a 0.1761 ± 0.01
f, g 0.3060 ± 0.01
f
3 59.91 ± 1.56e 15.00 ± 4.16
a 0.1653 ± 0.01
g 0.3215 ± 0.02
e, f
4 70.84 ± 1.55a 16.07 ± 4.91
a 0.2804 ± 0.01
b, c 0.3924 ± 0.03
b, c, d
5 64.53 ± 1.36c, d, e
16.28 ± 5.95a 0.2398 ± 0.02
c, d 0.3780 ± 0.01
b, c, d
6 65.23 ± 0.95c, d
15.91 ± 3.98a 0.1914 ± 0.01
e, f, g 0.3506 ± 0.01
d, e, f
7 67.76 ± 1.14a, b, c
59.80 ± 1.76b 0.3044 ± 0.02
b 0.4177 ± 0.01
b
8 65.21 ± 2.11c, d
60.50 ± 2.58b 0.2247 ± 0.01
d, e 0.3699 ± 0.02
c, d
9 65.54 ± 1.28b, c, d
60.19 ± 2.32b 0.2179 ± 0.01
d, e, f 0.3540 ± 0.02
d, e
10 69.92 ± 2.07a, b
60.21 ± 2.72b 0.2504 ± 0.01
c, d 0.4117 ± 0.03
b, c
255
Figure 3 - Mixture contour plots for antioxidant activities of soy protein isolate hydrolysates as
function of significant (p < 0.05) interaction effects of different commercial proteases
proportions: DPPH radical scavenging (a), inhibition of linoleic acid autoxidation (b), reducing
power assay (c) and total antioxidant capacity (d).
The size of the peptides is known to be a significant factor in the overall antioxidant
activity and functional properties of protein hydrolysates. Proteolysis levels are often assessed by
global quantification of the soluble peptides in certain concentrations of trichloroacetic acid
(TCA). This parameter has been used as an indication of the amount of small peptides in protein
hydrolysates and has a positive correlation with the degree of hydrolysis (DH) (Zhou et al.,
2012).
> 70 < 70 < 60 < 50 < 40 < 30 < 20
0.00
0.25
0.50
0.75
1.00
YeastMax A0.00
0.25
0.50
0.75
1.00
Flavourzyme®
500L
0.00 0.25 0.50 0.75 1.00
Alcalase®
2.4L
> 70 < 70 < 67 < 65 < 63 < 61
0.00
0.25
0.50
0.75
1.00
YeastMax A0.00
0.25
0.50
0.75
1.00
Flavourzyme®
500L
0.00 0.25 0.50 0.75 1.00
Alcalase®
2.4L
> 0.38 < 0.38 < 0.33 < 0.29 < 0.25 < 0.21 < 0.17
0.00
0.25
0.50
0.75
1.00
YeastMax A0.00
0.25
0.50
0.75
1.00
Flavourzyme®
500L
0.00 0.25 0.50 0.75 1.00
Alcalase®
2.4L
> 0.65 < 0.65 < 0.56 < 0.51 < 0.46 < 0.41 < 0.36 < 0.31
0.00
0.25
0.50
0.75
1.00
YeastMax A0.00
0.25
0.50
0.75
1.00
Flavourzyme®
500L
0.00 0.25 0.50 0.75 1.00
Alcalase®
2.4L
a b
c d
256
Figure 4 shows the distribution profile of TCA soluble protein for the assays performed
using the statistical mixture design as well as the contour plot for this response as function of
significant interaction effects of different proteases proportions. The results showed that the
hydrolysis performed using the protease YeastMaxTM
A (run 3) resulted in highest TCA soluble
protein value, reaching 90.5%, while the hydrolysates obtained with the binary mixture of
FlavourzymeTM
500L (0.50) and YeastMaxTM
A (0.50) (run 5) presented the lowest value
(69.9%). In some studies, an increase in the TCA soluble protein content of the protein
hydrolysates increases the antioxidant activity. However, other studies have reported a decrease
in antioxidant activity with an increase in TCA soluble protein content. For our study, the
correlation analysis indicated no significant relationship between the antioxidant activities and
TCA soluble protein. This can be justified by the complexity involved when the different
protease sources were combined in binary or ternary mixtures.
Figure 4 – Variation of TCA soluble protein content in the runs 1-10 performed using statistical
mixture design (a) and contour plot for TCA soluble protein of the hydrolysates as function of
significant (p < 0.05) interaction effects of different proteases proportions (b).
The response data based on the independent variables was obtained from the experiments
and recorded in Table 3. The experiments were conducted with triplicates. In almost all cases, a
good agreement existed between the original and triplicates. All the independent and response
variables were fitted to quadratic or special cubic models. The coefficient of determination (R2)
and the F-test (analysis of variance; ANOVA) were used to verify the quality of fit of the models.
> 90 < 90 < 86 < 82 < 78 < 74 < 70
0.00
0.25
0.50
0.75
1.00
YeastMax A0.00
0.25
0.50
0.75
1.00
Flavourzyme®
500L
0.00 0.25 0.50 0.75 1.00
Alcalase®
2.4L
0
20
40
60
80
100
1 2 3 4 5 6 7 8 9 10
TC
A s
olu
ble
pro
tein
(%
)
Runs
a b
257
Table 4 shows the models, corresponding R2, F-ratio and p-values of the regression
equations for antioxidant activities. The high coefficients of determination (R2), which were
greater than 0.75 (Table 4), indicated that all the response functions adequately fitted the
experimental data and that the models could be used for predictive purposes in the determination
of the antioxidant activities of soy protein isolate hydrolysates using the different proteases
sources and their mixtures.
Table 4 - Analysis of variance (ANOVA) including models, R2 and probability values for the
final reduced models for antioxidant activities of soy protein isolate hydrolysates.
*F-ratio = Fcalculated/Ftabulated
DPPH radical scavenging
Source of variation Sum of
squares
Degrees of
freedom
Mean of
squares F-ratio
* R² p-value
Regression 265.75 5 53.15 7.85 0.77 <0.01
Residual 77.26 24 3.22
Total 343.01
Quadratic model: Y = 63.79x1 + 61.89x2 + 60.14x3 + 30.32x1x2 + 12.22x1x3 + 16.25x2x3
Inhibition of linoleic acid autoxidation
Source of variation Sum of
squares
Degrees of
freedom
Mean of
squares F-ratio
* R² p-value
Regression 1,1870.77 3 3,956.92 16.54 0.81 <0.01
Residual 2,695.65 26 103.68
Total 14,566.42
Special cubic model: Y = 18.64x1 + 18.89x2 + 18.47x3 + 1,601.25x1x2x3
Reducing power assay
Source of variation Sum of
squares
Degrees of
freedom
Mean of
squares F-ratio
* R² p-value
Regression 0.1300 4 0.0325 60.20 0.95 <0.01
Residual 0.0062 25 0.0002
Total 0.1362
Quadratic model: Y = 0.39x1 + 0.17x2 + 0.17x3 – 0.14x1x3 + 0.12x2x3
Total antioxidant capacity
Source of variation Sum of
squares
Degrees of
freedom
Mean of
squares F-ratio
* R² p-value
Regression 0.320 5 0.064 29.14 0.93 <0.01
Residual 0.025 24 0.001
Total 0.345
258
The specificity of each enzyme on protein hydrolysis could be attributable to the
differences observed in antioxidant activities and TCA soluble protein, releasing peptides with
different sizes, amino acid sequences and amounts. The enzyme specificities can be used to
predict the type of peptides produced and therefore their application.
The protease FlavourzymeTM
500L is a fungal protease/peptidase complex obtained from
A. oryzae that contains endoprotease and exopeptidase activities and cleaves amino acids on the
C-terminal side (Luna-Vital et al., 2014). On the other hand, AlcalaseTM
2.4L is an endoprotease
of the serine type obtained from B. licheniformis that has a high specificity for aromatic (Phe,
Trp, Tyr), acidic (Glu), sulfur containing (Met), aliphatic (Leu, Ala), hydroxyl (Ser) and basic
(Lys) residues (Doucet et al., 2003). Information about the source, mechanisms of action and
specificities for YeastMaxTM
A were not found in the literature and not provided by the enzyme
supplier. This commercial preparation is described as a mixture of proteases indicated for yeast
hydrolysis with maximum activity at pH 6-10 and temperature ranging from 50 to 60 °C. Based
on the results obtained in our study, YeastMaxTM
A probably has a broad specificity, hydrolyzing
most peptide bonds, which was characterized by the high TCA soluble protein content of the
hydrolysates (Figure 4a).
Studies about specificities of proteolytic enzymes as well as the application of systems
based on combination of proteases from different sources have been used for production of
bioactive peptides.
Adjonu et al., (2013) studied the enzymatic hydrolysis of whey protein isolate using α-
chymotrypsin, pepsin and trypsin with a focus on enzyme specificities in order to obtain peptides
with antioxidant activities. The results showed maximum DH for all samples ranging from 11.8
to 14.1%, with high values for the no heat treated protein hydrolyzed by chymotrypsin, followed
by pepsin and trypsin. Regarding to antioxidant activities, protein hydrolysates obtained using
pepsin were less effective in scavenging peroxyl radicals (ORAC assay) compared to the ABTS˙+
free radicals (FRSA assay). The ORAC and the FRSA values suggested that high DH values may
not be suitable for generating antioxidant peptides, since may result in release of high proportions
of free amino acids, which can negatively affect the antioxidant activity by acting as prooxidants
(Pihlanto, 2006; Adjonu et al., 2013). The profile changes in antioxidant activities and DH were
associated to the enzyme-peptide bond specificity. Both chymotrypsin and trypsin are alkaline
259
endoproteases with specificity by peptide bonds at the C-terminal side containing aromatic amino
acids (Trp, Tyr and Phe) and at the C-terminal side with Arg and Lys residues, respectively. On
the other hand, pepsin is an acidic endoprotease that act on peptide bonds at the N-terminal side
containing aromatic and hydrophobic amino acids (Adjonu et al., 2013).
Betancur-Ancona et al., (2014) reported that the enzymatic treatment of protein
concentrate of beans using mixture of proteases increased DH and had a positive impact on
antioxidant properties of the hydrolysates. The protein concentrate of beans reached DH values
ranging from 10 to 20% using AlcalaseTM
and FlavourzymeTM
after 120 min hydrolysis,
respectively, while the combination of them resulted in DH value of 33.29%. The combined use
of pepsin and pancreatin also increased DH of the protein, reaching a maximum value of 28.47%.
The hydrolysates obtained with AlcalaseTM
-FlavourzymeTM
system showed higher antioxidant
activity compared to Pepsin-Pancreatin hydrolysates. According these authors, intestinal enzymes
such as pepsin and pancreatin generate a large amount of proteins and oligopeptides, while
enzymes from bacterial and fungal such as AlcalaseTM
and FlavourzymeTM
generate a large
amount of small peptides and free amino acids, which exhibit greater activity.
4. Conclusion
The enzymatic hydrolysis of proteins based on their specificities and mechanisms of
action can be used as a valuable tool to improve the antioxidant properties of soy protein isolate
hydrolysates. Kinetic parameters obtained for thermal inactivation showed that the commercial
preparations of proteases were not inhibited by the products from soy protein isolate hydrolysis.
The use a binary mixture of FlavourzymeTM
500L and AlcalaseTM
2.4L increased the capacity of
DPPH radical scavenging reaching a maximum value of 70.84% at 5 mg mL-1
. Strong and
significant synergistic effects were observed in the hydrolysates obtained using the ternary
mixtures of FlavourzymeTM
500L, AlcalaseTM
2.4L and YeastMaxTM
A, reaching about 60%
inhibition of linoleic acid autoxidation against values of approximately 15% inhibition for the soy
protein hydrolysates obtained using individual enzymes. The results obtained in our study suggest
that the combined use of proteases with broad enzymatic specificities will release different
peptides and thus increase the number of cleavage sites in the protein and hydrolysates, resulting
in high antioxidant activities.
260
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265
Conclusões gerais
Os resultados obtidos mostraram que a aplicação da técnica de planejamento experimental
de misturas é um método atrativo para o aumento da produção de proteases e obtenção de
preparações com diferentes propriedades bioquímicas. Esse tipo de planejamento também
mostrou-se como uma importante ferramenta para o estudo da hidrólise simultânea de misturas de
proteínas em um processo simplificado assim como a utilização de composições contendo
proteases de diferentes fontes, permitindo a maximização de diversas atividades biológicas e
propriedades funcionais das proteínas.
O estudo da produção de proteases por A. niger LBA02 em fermentação semissólida
utilizando diferentes resíduos agroindustriais como substratos e a utilização de formulações
contendo misturas binárias, ternárias ou quaternárias dos substratos mostrou-se um processo
atrativo para maximização da produção. Os resultados obtidos mostraram que a utilização de uma
mistura contendo farelo de trigo, farelo de soja, farelo de algodão e casca de laranja em iguais
proporções resultou em aumentos de 33,7, 7,6, 30,8 e 581,7% na produção de proteases, quando
os valores são comparados aos obtidos utilizando cada substrato de forma isolada. As maiores
atividades de protease foram detectadas quando utilizada a mistura quaternária dos substratos e a
mistura binária de farelo de trigo (1/2) e farelo de soja (1/2), atingindo 245,97 e 262,78 U g-1
após
48h de fermentação.
O estudo de aspectos físico-químicos dos resíduos agroindustriais revelou que parâmetros
como a capacidade de retenção de água, distribuição granulométrica, densidade aparente e
composição química apresentaram forte influência sobre a produção de proteases por A. niger
LBA02 em fermentação semissólida. A composição química dos resíduos agroindustriais exerceu
um dos efeitos mais notórios, onde a produção de proteases foi induzida nas primeiras 48h de
fermentação nos substratos que continham maior quantidade de proteína e inibida pelos
substratos com alto teor de carboidratos.
A caracterização bioquímica das preparações enzimáticas obtidas a partir de A. niger
LBA02 por fermentação semissólida utilizando farelo de trigo, farelo de soja, farelo de algodão,
casca de laranja e a mistura quaternária destes substratos permitiu avaliar os aspectos de
produção sob um novo ponto de vista, permitindo a seleção de uma formulação ou substrato que
266
permita a produção de enzimas com características mais atrativas, como maior estabilidade
térmica. O micro-organismo apresentou a capacidade de secretar diferentes tipos de protease
quando cultivado nos diferentes substratos. Parâmetros cinéticos e termodinâmicos para
inativação térmica incluindo valores de t1/2, D, Ead, ΔH, ΔG e ΔS mostraram que as proteases
produzidas em farelo de trigo foram as mais estáveis termicamente ao passo que as proteases
produzidas em farelo de algodão foram as mais sensíveis. Para ativação térmica, as proteases
produzidas em casca de laranja apresentaram o menor valor para energia de ativação, atingindo
16,32 kJ mol-1
, enquanto o maior valor foi detectado para as proteases produzidas utilizando a
mistura quaternária dos substratos (19,48 kJ mol-1
). As preparações enzimáticas também
apresentaram diferentes perfis quando a especificidade de substrato foi determinada frente a
diferentes substratos proteicos. A maior atividade relativa (496,4%), considerando o substrato
caseína como padrão (100%) foi observada para hemoglobina de sangue bovino hidrolisada com
a preparação enzimática de proteases de A. niger LBA02 obtida a partir da fermentação
utilizando a mistura quaternária dos resíduos agroindustriais.
A determinação do pH e temperatura ótima para atividade e estabilidade utilizando
delineamento composto central rotacional (DCCR), mostrou que as proteases de A. niger LBA02
foram mais ativas na faixa de pH 3 a 4 e temperaturas de 45 a 50 °C. As proteases mostraram-se
estáveis na faixa de pH de 2,5 a 4,5 e na faixa de 40 a 50 °C após 1h de incubação.
As preparações de proteases produzidas em farelo de trigo, farelo de soja e farelo de
algodão apresentaram diferentes valores para atividade coagulante do leite atingindo 22,22, 0,56
e 5,80 U mL-1
, respectivamente. Hidrolisados de proteínas do soro de leite obtidos a partir destas
preparações, também apresentaram diferentes perfis de atividade antioxidante, sendo as proteases
produzidas em farelo de trigo e farelo de algodão as mais adequadas para obtenção de
hidrolisados com forte capacidade de inibição de radicais DPPH, atingindo 82,8 e 84,5% de
inbição, respectivamente, na concentração de 10 mg mL-1
.
O estudo da hidrólise enzimática simultânea utilizando diferentes fontes de proteínas de
forma isolada ou em combinadas em misturas e a protease comercial Flavourzyme® 500L
mostrou diversos efeitos sinérgicos para propriedades funcionais, atividade antioxidante, anti-
adipogênica e na indução do crescimento de bactérias lácticas e probióticas.
267
Dentre as propriedades funcionais avaliadas, a atividade emulsificante foi a que
apresentou o maior efeito sinérgico entre as diferentes fontes de proteínas. A hidrólise enzimática
da mistura ternária contendo proteína isolada de soja, proteínas do soro de leite e da clara de ovo
em iguais proporções aumentou o índice de atividade emulsionante de 2 a 12 vezes comparado
aos índices obtidos para os hidrolisados produzidos de forma isolada.
Para atividade antioxidante, o maior destaque foi para a capacidade de inibição de radicais
DPPH, onde a mistura hidrolisada de proteínas do soro de leite e da clara de ovo, resultaram em
aumentos de 45,1 e 37,3%, respectivamente, em comparação aos hidrolisados obtidos utilizando
as fontes isoladas.
Para atividade anti-adipogênica, os resultados obtidos mostraram que após a hidrólise
enzimática, a mistura contendo proteínas do soro de leite (1/2) e proteínas da clara de ovo (1/2)
mostrou o maior aumento na supressão do acúmulo relativo de lipídeos (ARL) nas células pré-
adipócitas 3T3-L1. A mistura hidrolisada contendo proteínas do soro de leite (1/2) e proteínas da
clara de ovo (1/2) na concentração de 800 ppm mostraram aumentos de 220 e 27% na supressão
do ARL, respectivamente, quando comparadas aos substratos isolados, atingindo uma supressão
máxima de ARL de 15,5%. Na avaliação de diferentes concentrações dos hidrolisados, o maior
nível de supressão do ARL (%) foi de 47,9% quando as células 3T3-L1 foram tratadas com os
hidrolisdos contendo a mistura de proteínas do soro de leite (1/2) e da clara de ovo (1/2) na
concentração de 1200 ppm. A ultrafiltração mostrou que frações de massas moleculares inferiores
a 30 kDa exercem forte influência sobre a supressão do ARL.
Para atividade antimicrobiana, os resultados obtidos mostraram que na maior parte dos
ensaios, a suplementação dos meios de cultivo com fontes de proteínas estimulou o crescimento
das bactérias patogênicas. A linhagem de S. aureus ATCC 6538 foi a única que apresentou
inibição significativa do crescimento quando cultivada em meio suplementado com uma mistura
binária de proteína isolada de soja (1/2) e proteínas da clara de ovo (1/2) não hidrolisadas,
resultando em inibição de 16,82%. As linhagens de leveduras não apresentaram mudanças nos
perfis de inibição do crescimento quando comparadas as amostras hidrolisadas e não hidrolisadas.
A maior inibição observada foi detectada para a linhagem de S. cerevisiae KL 88 cultivada em
meio suplementado com a mistura ternária de proteínas hidrolisadas em proporções iguais,
resultando em inibição de 15,42%.
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Os hidrolisados proteicos também apresentaram um efeito positivo sobre o estímulo do
crescimento de linhagens de bactérias lácticas e probióticas. A suplementação do meio de cultivo
com a mistura binária de hidrolisados de proteínas do soro de leite (1/2) e da clara de ovo (1/2) na
concentração de 25 mg mL-1
resultou em aumentos de 100,0 e 29,4% no crescimento celular de
uma cultura mista de Streptococcus thermophilus e Lactobacillus delbrueckii e de Lactobacillus
acidophilus, respectivamente. Para a linhagem de Bifidobacterium lactis, um crescimento 86,2%
superior ao controle foi observado quando os meios foram suplementados com 25 mg mL-1
dos
hidrolisados contendo a mistura binária de proteína isolada (1/2) e proteínas do soro de leite
(1/2).
O estudo da obtenção de hidrolisados de proteína isolada de soja utilizando proteases de
diferentes fontes de forma isolada ou em uso combinado permitiu uma interessante discussão
sobre os mecanismos de ação e especificidades de enzimas proteolíticas e os seus efeitos sobre a
atividade antioxidante dos hidrolisados. Os resultados obtidos mostraram que a atividade
antioxidante apresentou respostas variáveis quando avaliada por diferentes métodos. Para
inibição de radicais DPPH, os hidrolisados obtidos com a protease Flavourzyme® 500L
combinada com Alcalase® 2.4L mostrou o maior efeito sinérgico, atingindo aumentos de 10,9 e
13,2% na atividade antioxidante, em comparação com os hidrolisados produzidos com enzimas
isoladas. Os hidrolisados obtidos utilizando as misturas ternárias de Flavourzyme® 500L,
Alcalase® 2.4L e YeastMax
® A apresentaram o maior poder de inibição da auto-oxidação do
ácido linoleico. Já para os ensaios baseados no poder redutor das moléculas antioxidantes, que
incluíram o poder de redução de Fe3+
e a capacidade antioxidante total (redução de Mo (VI) a Mo
(V)), os hidrolisados produzidos usando Flavourzyme® 500L apresentaram maior atividade.
269
Sugestões para trabalhos futuros
- Caracterizar os resíduos agroindustriais de forma mais aprofundada e propor mecanismos de
indução da produção de proteases baseados na presença de fontes de proteínas com diferentes
massas moleculares, digestibilidade e composição de aminoácidos, assim como verificar a
correlação entre a presença de diferentes fontes de carbono (glicose, sacarose, amido, celulose,
hemicelulose, pectina, etc.) e/ou o balanço entre elas e a produção de diversas enzimas;
- Caracterizar os extratos enzimáticos obtidos por fermentação semissólida utilizando meios de
cultivo baseados na mistura de diferentes resíduos, quanto à presença de outros grupos de
enzimas e propor formulações para a produção simultânea de enzimas ou produção preferencial
de uma determinada enzima;
- Verificar a produção simultânea de enzimas com perfis bioquímicos complementares utilizando
culturas mistas de micro-organismos, como por exemplo, para atuação em uma ampla faixa de
pH e temperatura;
- Realizar um estudo mais aprofundado de caracterização das matrizes proteicas utilizadas para a
hidrólise enzimática, e propor formulações para a produção de hidrolisados com propriedades
multifuncionais, englobando aspectos tecnológicos e biológicos;
- Purificar os peptídeos com atividade biológica por cromatografia de troca iônica e filtração em
gel;
- Identificar as sequências peptídicas responsáveis pelas bioatividades utilizando cromatografia
líquida de alta eficiência e espectrometria de massas;
- Verificar as alterações no perfil de peptídeos após a hidrólise enzimática correlacionando com
as atividades biológicas;
- Avaliar outras atividades biológicas, incluindo atividade antitumoral, antitrombótica e anti-
hipertensiva, dos hidrolisados proteicos.
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