universidade estadual de campinas instituto de...

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UNIVERSIDADE ESTADUAL DE CAMPINAS

INSTITUTO DE BIOLOGIA

ALINE GUIMARÃES SANTANA

O PAPEL DO PROTEOMA NUCLEAR DA SUBSTÂNCIA BRANCA E CINZENTA DE CÉREBROS DE PACIENTES COM ESQUIZOFRENIA

THE ROLE OF THE NUCLEAR PROTEOME FROM THE WHITE AND GRAY MATTER OF SCHIZOPHRENIA BRAINS

CAMPINAS

2017

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ALINE GUIMARÃES SANTANA

O PAPEL DO PROTEOMA NUCLEAR DA SUBSTÂNCIA BRANCA E CINZENTA DE CÉREBROS DE PACIENTES COM ESQUIZOFRENIA

THE ROLE OF THE NUCLEAR PROTEOME FROM THE WHITE AND GRAY MATTER OF SCHIZOPHRENIA BRAINS

Dissertação apresentada ao Instituto de Biologia da Universidade Estadual de Campinas como parte dos requisitos exigidos para a obtenção do título de Mestra em Biologia Funcional e Molecular na área de concentração de Bioquímica

Dissertation presented to the Biology Institute of the State University of Campinas as part of the requisites required to obtain of degree of Master in Functional and Molecular Biology in the concentration area of Biochemistry

ORIENTADOR: Prof. Dr. Daniel Martins de Souza ESTE EXEMPLAR CORRESPONDE À VERSÃO FINAL DA DISSERTAÇÃO DEFENDIDA PELA ALUNA ALINE GUIMARÃES SANTANA, E ORIENTADA PELO PROF. DR. DANIEL MARTINS-DE-SOUZA E CO-ORIENTADA PELA DRª JULIANA SILVA CASSOLI

CAMPINAS

2017

ORIENTADOR: Prof. Dr. Daniel Martins de SouzaCOORIENTADOR: Dra. Juliana Silva Cassoli

ESTE EXEMPLAR CORRESPONDE À VERSÃO FINAL DA DISSERTAÇÃO DEFENDIDA PELA ALUNA ALINE GUIMARÃES SANTANA, E ORIENTADA PELO PROF. DR. DANIEL MARTINS DE SOUZA E COORIENTADA PELA DRª JULIANA SILVA CASSOLI

Agência(s) de fomento e nº(s) de processo(s): CNPq, 132637/2015-4

Ficha catalográficaUniversidade Estadual de Campinas

Biblioteca do Instituto de BiologiaMara Janaina de Oliveira - CRB 8/6972

Santana, Aline Guimarães, 1990- Sa59p SanO papel do proteoma nuclear da substância branca e cinzenta de cérebros

de pacientes com esquizofrenia / Aline Guimarães Santana. – Campinas, SP :[s.n.], 2017.

SanOrientador: Daniel Martins de Souza. SanCoorientador: Juliana Silva Cassoli. SanDissertação (mestrado) – Universidade Estadual de Campinas, Instituto de

Biologia.

San1. Esquizofrenia. 2. Proteômica. I. Martins-de-Souza, Daniel,1979-. II.

Cassoli, Juliana Silva. III. Universidade Estadual de Campinas. Instituto deBiologia. IV. Título.

Informações para Biblioteca Digital

Título em outro idioma: The role of the nuclear proteome from the white and gray matter ofschizophrenia brainsPalavras-chave em inglês:SchizophreniaProteomicÁrea de concentração: BioquímicaTitulação: Mestra em Biologia Funcional e MolecularBanca examinadora:Daniel Martins de Souza [Orientador]César Renato SartoriLucilene Delazari dos SantosData de defesa: 22-02-2017Programa de Pós-Graduação: Biologia Funcional e Molecular

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Campinas, 22 de fevereiro de 2017

COMISSÃO EXAMINADORA

Daniel Martins de Souza

César Renato Sartori

Lucilene Delazari dos Santos

Os membros da comissão examinadora acima assinaram a Ata de Defesa que se encontra no processo de vida acadêmica do aluno.

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DEDICATÓRIA

Dedico esse trabalho aos meus familiares e amigos pelo apoio incondicional, especialmente aos meus amados pais Jandira Guimarães e Dalton Alves Santana que mesmo na distância sempre se fizeram presentes me dando forças e incentivo para seguir em frente.

Ao meu namorado Pedro Antonio Santos Flórez, pelo apoio, paciência, dedicação e carinho, tornando essa caminhada mais suave.

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AGRADECIMENTOS

Primeiramente agradeço a Deus por todas as bênçãos concedidas e por me dar

forças e condições de realizar este trabalho.

Aos meus amados pais Jandira e Dalton pelos ensinamentos, paciência, incentivo,

apoio incondicional e por se fazerem presentes mesmo na distância brindando-me com seu

carinho.

Ao meu orientador, o Prof. Dr. Daniel Martins de Souza, o qual me deu a

oportunidade de trabalhar neste grupo. Me sinto muito grata pelos ensinamentos, paciência,

dedicação e valiosa orientação.

À minha co-orientadora, Drª Juliana Silva Cassoli, por me passar um pouco do seu

conhecimento e contribuir com meu crescimento profissional. Muito obrigada pelos

ensinamentos e orientação.

À minha amiga e colega de trabalho Msc. Verônica Aparecida Saia-Cereda, por

toda a ajuda e apoio durante o desenvolvimento desse trabalho, e também pela amizade,

conselhos, dicas e ensinamentos. Meus mais sinceros agradecimentos!

Ao técnico do laboratório Paulo Baldasso pelo apoio técnico e por toda ajuda

durante o desenvolvimento deste trabalho.

Aos demais colegas de laboratório e amigos que fiz durante a realização deste

trabalho, Juliana Minardi, Sheila, Adriano, Brad, Carol, Giuliana, Guilherme, Valéria, Mariana,

Daniele, Lícia, Gabriela, Dayene, Rafael e todos que de alguma maneira contribuíram com o

desenvolvimento deste trabalho, seja contribuindo com o projeto ou alegrando-me com sua

amizade. Muito obrigada!

Ao meu namorado e amigo para todas as horas Pedro Antonio Santos Flórez, por

todo apoio e carinho, e por tornar essa caminhada muito mais suave. Te quiero mucho!

Aos meus irmãos André, Marcelo, Júlio, Clayton, Rosana, Divino, Berthaline,

Helga, Lavínia, Lilian, Dalton, Lidiane, Clautenis e Paola, aos meus cunhados Juninho, Flórida,

Alaíde, Patrick, Matheus e Roger, aos meus sobrinhos Yuri, Kevyn, Emily, Bryan, Matheus,

Rafael, Amanda, Gabriel, Laura, Leandro, Bruno e Murilo, às minhas tias Ana, Adriana, Emília,

Ilza, Lúcia, Rosalva, Thereza, Maria e a toda minha família pelo apoio incondicional, carinho,

amizade e compreensão. Apesar de muitas vezes não poder estar presente meu coração sempre

esteve com vocês!

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Aos amigos que fiz nesta cidade Fabiana, Aline, Leandro, Ju entre outros,

especialmente à Simonice pela amizade sincera e muitos momentos de descontração.

Aos meus amigos Thaís, Paula, Jéssica, dona Lúcia, Juliano, Patrícia, Suelen,

Jhonny, Yohana por mesmo na distância se fazerem presentes me alegrando com sua amizade,

carinho e apoio. Vocês são muito especiais!

A minha ex-orientadora Tatiana de Arruda Campos Brasil de Souza, pela paciência,

dedicação, ensinamentos e por sempre ter me estimulado a continuar no caminho da ciência.

Sempre serei grata por todos ensinamentos e incentivo!

Aos professores Henrique, Alessandro e Marcelo Bispo, à professora Helena e ao

Dr. Fernando pelas colaborações e ensinamentos.

Aos membros da banca examinadora que tão gentilmente aceitaram participar desse

momento tão importante.

À Unicamp e ao Instituto de Biologia

Aos órgãos de fomento CNPq, CAPES e FAPESP pelo apoio financeiro

Meu muito obrigada a todos!

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RESUMO

A esquizofrenia é um transtorno neuropsiquiátrico grave e debilitante, que afeta

uma em cada cem pessoas no mundo. Apesar de sua alta prevalência e gravidade, muito pouco

se sabe a respeito dos mecanismos moleculares que atuam no desenvolvimento da doença. O

diagnóstico é estritamente clínico e pode se subjetivo. Os tratamentos são pouco eficazes, e

apresentam uma ampla gama de efeitos adversos. A busca pela compreensão dos mecanismos

bioquímicos que atuam no desenvolvimento da doença é essencial para reverter esse cenário.

A proteômica baseada em espectrometria de massas figura como ferramenta bioquímica

essencial para tal busca, devido à suas características de alta acurácia e resolução, permitindo o

estudo de amostras proteicas complexas. Além disso, essa alta complexidade proteica pode ser

diminuída através de fracionamentos prévios às análises proteômicas, sendo a separação de

organelas um dos tipos de fracionamento mais utilizados.

Neste trabalho foi realizado análises do proteoma nuclear de amostras da subs-

tância branca (corpo caloso) e cinzenta (lobo temporal anterior) extraídas de cérebros post-

mortem de pacientes com esquizofrenia em comparação com o proteoma nuclear das mesmas

regiões cerebrais de indivíduos mentalmente sadios. Tendo como base a disfunção

glutamatérgica, fator molecular conhecido na esquizofrenia, também foi analisado o proteoma

nuclear de oligodendrócitos humanos (linhagem MO3.13) tratados com MK-801, um

antagonista de receptores NMDA. Tais análises foram efetuadas afim de verificar alterações

similares nos proteomas nucleares dessas amostras e dos pacientes com esquizofrenia.

Através das análises do tecido cerebral post-mortem foi possível verificar princi-

palmente alterações em proteínas que regulam metabolismo dos ácidos nucléicos e processos

de comunicação celular, sendo que o estudo comparativo de ambas as regiões (corpo caloso e

lobo temporal anterior) revelou uma alteração significativa em proteínas relacionadas ao

estresse celular. As análises individuais da substância cinzenta também revelaram alterações

em proteínas relacionadas ao spliceossomo, o que se mostrou bastante interessante como alvo

de estudo em função da inexistência de pesquisas a respeito.

O estudo das proteínas nucleares de MO3.13 tratadas com MK-801 foram menos

expressivos, sendo que devido à baixa identificação de proteínas nucleares alteradas, não foi

possível observar o enriquecimento de nenhuma via, contudo, analisando individualmente as

proteínas alteradas no tratamento agudo, notamos alterações pontuais interessantes que

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encontram embasamento na literatura, como a baixa abundância das proteínas Atlastina-2 e

Proteína de dedo de zinco 85 e a maior concentração da Proteína 7 contendo bromodomínio.

É importante citar, que os resultados obtidos neste trabalho são pioneiros e revelam

alterações proteômicas que se mostram interessantes para estudos mais aprofundados.

Palavras-chave: Esquizofrenia, proteômica, proteoma nuclear.

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ABSTRACT

Schizophrenia is a severe and debilitating neuropsychiatric disorder that affects one

in every hundred people in the world. Despite its high prevalence and severity, very little is

known about the molecular mechanisms involved in the development of the disease. The

diagnosis is strictly clinical and may be subjective. Treatment is based on antipsychotics and

are not effectives, presenting a wide range of side effects. The search for the understanding of

schizophrenia´s biochemical mechanisms is essential to revert the current scenario. Mass

spectrometry-based proteomics figures as an essential biochemical tool for this end, given its

high accuracy and resolution, and for allowing the study of complex protein samples. Such high

protein complexity can be reduced using pre-fractionation as the separation of organelles.

Here we analyzed the nuclear proteome of white matter (corpus callosum) and gray

matter (anterior temporal lobe) extracted post-mortem from brains of schizophrenia patients

and compared them to the nuclear proteome of the same brain regions collected from mentally

healthy individuals. Based on glutamatergic dysfunction, molecular factor known in

schizophrenia, the nuclear proteome of human oligodendrocytes (lineage MO3.13) treated with

MK-801, an NMDA receptor antagonist, were also analyzed. These analyses were carried out

in order to verify similar alterations in the nuclear proteomes of these samples and of the

patients with schizophrenia.

Analysis on post-mortem brain tissue revealed alterations in proteins that regulate

nucleic acid metabolism and cellular communication processes. A comparative study of both

regions (corpus callosum and anterior temporal lobe) revealed significant changes in proteins

associated to cellular stress. Gray matter-associated changes are about spliceosome-related

proteins, which have not been previously found.

The study of nuclear proteins of MO3.13 oligodedrocytes treated with MK-801

were less expressive, as not so many nuclear proteins were found differentially expressed.

Nevertheless, by analyzing closely the differentially expressed proteins in the acute treatment,

we noticed interesting alterations supported by literature, such as the low abundance of Atlastin-

2 proteins and zinc finger protein 85 and the highest concentration of bromodomain-containing

protein 7.

Results obtained in this thesis are novel as reveal proteomic alterations which

warrant further studies.

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ÍNDICE DE FIGURAS

Figura 1 - Biological processes related to the anterior temporal lobe (ATL) and corpus callosum (CC) differentially expressed proteins.......................................................................................46

AGRADECIMENTOS..........................................................................................................

Figura 2 - Venn diagram comparison between differentially expressed proteins in anterior temporal lobe (ATL) and corpus callosum (CC)……………………..………………………..47

LISTAABREVURAS.......................................................................................................01

Figura 3 - Analysis of the Reactome of HSF1 proteins differentially expressed found deregulated in both regions by Reactome..................................................................................48

NTRODUÇÃO.....................................................................................................................0

Figura 4 - Sliceosome of anterior temporal lobe (ATL) showing differentially expressed proteins according to program String.........................................................................................50

2 Histórico da Esquizofrenia.............................................................................................01

Figura 5 - Network deregulated related to differentially expressed proteins in corpus callosum (CC) by String………………………………………...............................................................52

1.4Dados Epidemiológicos da Esquizofrenia................................................................01

Figura 6 - Células MO3.13 crescidas em meio DEMEM-High glicose.....................................77

1.5.1 Hipótese do neurodesenvolvimento......................................................................01

Figura 7 - Representação gráfica da média da porcentagem de enriquecimento das proteínas nucleares nas amostras tratadas com MK de forma crônica (72h) e aguda (8h)..........................78


Figura 8 - Diagrama de Venn das proteínas diferencialmente abundantes encontradas no corpo colosso (cc), no lobo temporal anterior (ATL) e nas células MO3.13 após o tratamento agudo com MK-801 (MO3).................................................................................................................79

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ÍNDICE DE TABELAS

Tabela 1 - Clinical data of patients and controls........................................................................35

AGRADECIMENTOS..........................................................................................................

Tabela 2 - Proteins differentially expressed in schizophrenia anterior temporal lobe (ATL)........................................................................................................................................38

LISTAREVIATURAS.......................................................................................................01

Tabela 3 - Proteins differentially expressed in schizophrenia corpus callosum (CC)……..…..44

1. TRODUÇÃO........................................................................................................................0

Tabela 4 - Proteínas extraídas da linhagem celular MO.13 tratada com MK-801 por 8h, encontradas diferencialmente abundantes em relação ao controle e classificadas de acordo com os dados encontrados em “Human Protein Reference Database”...............................................72

1.2 Histórico dEsquizofrenia.............................................................................................01

Tabela 5 - Proteínas nucleares da linhagem celular MO.13 tratadas com MK-801 por 8h e classificadas de acordo com os dados encontrados em “Human Protein Reference Database”..................................................................................................................................75

1.4 Dados Epidemiológicos da Equizofrenia....................................................................01

Tabela supl. 1 - Vias alteradas relacionados à proteínas diferencialmente expressas no lobo temporal anterior (ATL) de acordo com o programa String.......................................................96


Tabela supl. 2 - Vias alteradas relacionados à proteínas diferencialmente expressas no corpo caloso (CC) de acordo com o programa String...........................................................................99


Tabela supl. 3 - Proteínas totais identificadas por espectrometria de massas em HMSE após tratamento crônico e agudo das células MO3.13 com MK-801 e enriquecimento nuclear.....................................................................................................................................101

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SUMÁRIO

DEDICATÓRIA.........................................................................................................................5

AGRADECIMENTOS................................................................................................................6

RESUMO....................................................................................................................................8

ABSTRACT..............................................................................................................................10

ÍNDICE DE FIGURAS.............................................................................................................11

ÍNDICE DE TABELAS............................................................................................................12

1. INTRODUÇÃO....................................................................................................................15

1.1 Aspectos Gerais da Esquizofrenia...................................................................................15

1.2 Histórico da Esquizofrenia..............................................................................................15

1.3 Sintomatologia e Diagnóstico da Esquizofrenia..............................................................17

1.4 Dados Epidemiológicos da Esquizofrenia.......................................................................17

1.5 Teorias Etiológicas da Esquizofrenia..............................................................................18

1.5.1 Hipótese do neurodesenvolvimento........................................................................18

1.5.2 Teoria sináptica.......................................................................................................19

1.5.3 Teoria Genética.......................................................................................................20

1.6 Neurotransmissão na Esquizofrenia................................................................................20

1.6.1 Hipótese dopaminérgica..........................................................................................20

1.6.2 Hipótese serotoninérgica.........................................................................................21

1.6.3 Hipótese glutamatérgica..........................................................................................22

1.7 Tratamento da Esquizofrenia..........................................................................................22

1.7.1 Antipsicóticos de Primeira Geração........................................................................22

1.7.2 Antipsicóticos de Segunda Geração........................................................................23

1.7.3 Antipsicóticos de Terceira Geração.........................................................................23

1.8 Modelos para o Estudo da Esquizofrenia........................................................................24

1.8.1 Modelos in vivo.......................................................................................................24

1.8.2 Modelos in vitro......................................................................................................25

1.9 A proteômica e a esquizofrenia.......................................................................................26

1.9.1 Espectrometria de Massas.......................................................................................27

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1.9.2 Proteômica sub-celular............................................................................................27

1.9.3 Núcleo.....................................................................................................................28

1.9.4 Proteoma nuclear.....................................................................................................29

2. OBJETIVOS..........................................................................................................................29

2.1 Objetivo geral.................................................................................................................29

2.2 Objetivos Específicos.....................................................................................................29

3. JUSTIFICATIVA..................................................................................................................30

4. METODOLOGIA, RESULTADOS E DISCUSSÕES..........................................................30

5. CAPÍTULO 1: The nuclear proteome of white and gray matter from schizophrenia.............32

6. CAPÍTULO 2: Nuclear proteomics for exploring MK-801 treated oligodendrocytes to

better understand schizophrenia................................................................................................57

7. CAPÍTULO 3: Análises do proteoma nuclear da linhagem mo3.13 tratada com MK

-801...........................................................................................................................................67

8. CONCLUSÕES.....................................................................................................................83

9. PERSPECTIVAS..................................................................................................................85

10. REFERÊNCIAS..................................................................................................................85

11. ANEXOS.............................................................................................................................96

11.1 Anexo I – Tabelas Suplementares.................................................................................96

11.2 Anexo II – Artigos Publicados....................................................................................120

11.3 Anexo III – Declaração Comitê de Ética.....................................................................145

11.4 Anexo IV – Declaração de Direitos Autorais..............................................................146

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1. INTRODUÇÃO

1.1 Aspectos Gerais da Esquizofrenia

A esquizofrenia (SCZ) é um transtorno mental grave, debilitante e incurável, que

afeta aproximadamente 1% da população mundial (Kahn et al., 2015). A doença se manifesta

entre o final da adolescência e o início da fase adulta, por meio de uma gama de disfunções

cognitivas, comportamentais e emocionais, sendo considerada a principal causa de

incapacitação psiquiátrica (Wright, 2000). Embora seja geralmente abordada como uma única

doença, a SCZ constitui um grupo de transtornos neuropsiquiátricos com etiologia,

apresentação clínica, resposta ao tratamento e desenvolvimento distintos (Sadock et al., 2007).

Devido às características complexas da doença, ainda não há compreensão de como disfunções

em vias bioquímicas se associam no desenvolvimento da doença e, por conseguinte, não existe

diagnósticos moleculares e tão pouco tratamentos específicos.

1.2 Histórico da Esquizofrenia

Na antiguidade, a SCZ e outras doenças psiquiátricas eram vistas por um prisma

sobrenatural e atribuídas à possessões por espíritos malignos. Somente no século XIX (1851,

1853), Morel fez o primeiro reconhecimento da doença descrendo-a como uma perturbação

mental que atingia indivíduos jovens, surgindo de forma aguda e progredindo até a perda das

capacidades mentais (Afonso, 2002). Alguns anos mais tarde, em 1871, Hecker descreve um

quadro clínico em pacientes jovens que se caracterizava por deterioração mental e

comportamentos regressivos, o qual foi denominado hebefrenia (Ruiloba, 2003), e três anos

depois, Kahlbaum descreve o quadro clínico da catatonia (Garrabé, 2004). Em 1986, o

psiquiatra alemão Emil Kraepelin descreve em “Tratado de Psiquiatria” os sintomas negativos

da SCZ e a denomina dementia praecox (demência precoce) (Wyatt, 2001; Silva, 2006;

Jablensky, 2010; Fatouros-Bergman et. al., 2014). E em 1899, através da observação dos

quadros clínicos anteriores, o mesmo agrupa ao conceito de Demência Precoce, as

manifestações clínicas da SCZ conhecidas como Hebefrenia, Catatonia e Paranóia (Reis, 2000;

Bleuler, 2005). Finalmente, em 1911, o psiquiatra suíço Eugene Bleuler observou a presença

de uma cisão entre pensamento, emoção e comportamento em pacientes e cunhou o termo

“esquizofrenia” (esquizo = divisão, phrenia = mente), que veio a substituir o antigo nome, sendo

utilizado até os dias atuais (Elkis, 2000; Silva, 2006; Jablensky, 2010; Moskowitz & Heim,

2011).

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Até o início do século passado, o tratamento da SCZ consistia basicamente na

internação do paciente em hospitais psiquiátricos e em práticas terapêuticas de baixíssima ou

nenhuma eficácia e fundamentação, tais como ablação parcial da tireóide, castração precoce e

imunização com vacinas estreptocócicas (Kraepelin, 1919). Na década de 30, com a inserção

de novas estratégias biológicas de tratamento, tais como leucotomia, coma insulínico e terapias

convulsivas, foi observado um aumento na eficácia terapêutica (Hegarty et. al., 1994). Todavia,

somente na década de 50, com o descobrimento da clorpromazina, é que houve uma profunda

modificação na estratégia terapêutica, inaugurando a chamada era da psicofarmacologia.

Inicialmente utilizada como anestésico, a clorpromazina apresentou um poderoso efeito

calmante frente ao estresse gerado durante períodos pré-operatórios. Diante dessas observações,

foi proposto o seu efeito tranquilizador no tratamento de transtornos psiquiátricos. Entretanto,

seu mecanismo de ação era totalmente desconhecido. Somente com a descoberta da dopamina

e seus receptores, é que se foi proposto o antagonismo dos receptores de dopamina como o

mecanismo de ação dessa droga (Stip, 2002).

Os neurolépticos (inibidores das funções psicomotoras) foram introduzidos como

medicação antipsicótica poucos anos após o início da utilização da clorpromazina, tendo como

principal protótipo o haloperidol. Curiosamente a denominação da classe como neurolépticos

surgiu, não devido aos seus efeitos terapêuticos, mas em função de seus efeitos neurológicos

adversos. Tal fato, levou a classe médica à concepção errônea de que um antipsicótico para

apresentar eficácia, deveria também levar a efeitos extrapiramidais (Moreira & Guimarães,

2007). Porém, esse paradigma foi sobrepujado na década de 70, quando um ensaio clínico

utilizando a clozapina (antipsicótico não neuroléptico) revelou a eficácia da droga no controle

dos sintomas psicóticos (Hippius, 1999). Outros fármacos foram desenvolvidos utilizando a

clozapina como modelo (os chamados antipsicóticos atípicos ou de segunda geração), e

representaram o segundo grande avanço da psiquiatria no tratamento da SCZ (Möller, 2000).

Atualmente, uma nova classe de antipsicóticos com efeitos promissores e mecanismos

diferenciados vem sendo desenvolvida, os chamados antipsicóticos de terceira geração. O único

já em comercialização é o aripiprazol, considerado o protótipo da classe (Nardi et. al., 2015).

É importante citar, que apesar da ampla gama de antipsicóticos existentes, o tratamento da

esquizofrenia permanece pouco eficaz e apresenta e uma grande variedade de efeitos adversos,

sendo esse fato atribuído à complexidade da doença e ao desconhecimento dos mecanismos

bioquímicos envolvidos em sua biopatogênese.

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1.3 Sintomatologia e Diagnóstico da Esquizofrenia

A sintomatologia neuropsiquiátrica da SCZ é bastante diversificada e não existe

nenhum sintoma que por si só seja suficiente para diagnosticar a doença. Para o diagnóstico

clínico é necessário que o paciente apresente um conjunto de sintomas característicos, sendo

que dentre estes ao menos um deve ser positivo (delírios, alucinações ou discurso

desorganizado) (Araújo & Lotufo Neto, 2014). Inicialmente, a SCZ pode apresentar sinais

pouco específicos como desinteresse, perda de iniciativa e energia, além de quadros

depressivos, isolamento social e negligência com a aparência pessoal e com a higiene (Vallada

Filho & Busatto Fillho, 1996). Os sintomas que mais caracterizam a SCZ são alucinações e

delírios, déficits cognitivos, perturbações emocionais e afetivas e falta de motivação (Pull,

2005), sendo que esses são divididos em sintomas produtivos e sintomas negativos.

Os sintomas produtivos são caracterizados por delírios, alucinações e

desorganização do pensamento. Segundo Jones (1993), esses são resultado do aumento da

atividade dopaminérgica no sistema límbico. Os sintomas negativos são caracterizados por

depressão, anedonia, afetividade superficial e pobreza do discurso. Acredita-se que que tais

sintomas podem resultar, pelo menos parcialmente, de distúrbios na atividade dopaminérgica e

serotoninérgica na região dorsolateral do córtex pré-frontal (Jones, 1993). Alguns autores

dividem a SCZ em dois tipos de síndrome, tipo I caracterizada pelos sintomas produtivos e tipo

II caracterizada pelos sintomas negativos e cognitivos. Porém, um paciente com SCZ pode

apresentar os dois tipos de sintomas, sedo que os sintomas produtivos geralmente estão

associados a quadros de SCZ aguda e os sintomas negativos aos quadros crônicos da doença.

Ainda não existe nenhum teste molecular para identificar a SCZ. O diagnóstico da

doença é puramente clínico baseado na sintomatologia (American Psychiatric

Association,1994). Atualmente, os principais critérios para o diagnóstico da SCZ estão

descritos na 10ª edição do Manual Diagnóstico e Estatístico de Transtornos Mentais (DSM-5)

proposto pela Academia Americana de Psiquiatria (APA) e 10ª edição da Classificação

Internacional de Doença (CID-10), proposta pela OMS. A diagnose se baseia na presença de

pelo menos dois sintomas característicos da doença (produtivos e/ou negativos) por pelo menos

6 meses, caso o paciente não tenha sido tratado (Andreasen, 2007).

1.4 Dados Epidemiológicos da Esquizofrenia

As primeiras manifestações clínicas da SCZ ocorrem, em geral, em jovens adultos,

entre 15-35 anos dos pacientes e estima-se que atinja 24 milhões de pessoas em todo planeta

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(entre 0,5 e 1% da população adulta) (Lambert & Kinsley, 2006). Em termos numéricos, estudos

apontam uma incidência de aproximadamente 15,2 para cada 100.000 pessoas e uma

prevalência de 7,2 a cada 1.000 pessoas (MacGrath et. al., 2004). A diferença entre incidência

e prevalência provavelmente está relacionada ao fato da doença ter um início precoce (final da

adolescência e início da idade adulta) e evolução crônica (MacGrath et. al., 2004). Esses dados

se referem a uma média da população mundial, entretanto, a esquizofrenia não tem uma

distribuição homogênea e sua prevalência e incidência variam entre países, regiões e culturas.

As menores taxas de prevalência são encontradas entre os Hurteritas e nos Estados Unidos e as

maiores situam-se na Suécia, Irlanda e antiga Iugoslávia (taxas de aproximadamente 10%) (Vaz

Serra et. al., 2010). Essa distribuição heterogênea po-de estar associada aos fatores genéticos-

ambientais da doença e/ou dados subestimados dependo da região, cultura ou religião.

Em relação à incidência da SCZ entre os gêneros, estudos apontam que o risco de

indivíduos do sexo masculino desenvolverem a doença é aproximadamente 1,42 vezes maior

que indivíduos do sexo feminino (Aleman et. al., 2003; MacGrath et. al., 2004). Os homens

tendem a desenvolver a doença mais precocemente e em formas mais graves, com mais

sintomas negativos, piores prognósticos e menores chances de remissão (Chaves, 1994;

Jablensky, 2000). As principais teorias a respeito da diferença observadas entre os sexos estão

relacionadas às diferenças existentes no desenvolvimento cerebral intrauterino dos gêneros, e

ao provável efeito protetor do estrógeno sobre o tecido cerebral feminino na vida adulta

(Chaves, 2000).

Apesar da SCZ em si não levar à danos orgânicos que culminem em morte

prematura, os pacientes acometidos por tal doença apresentam uma expectativa de vida menor

em função da alta taxa de suicídios (aproximadamente 10%) (Meltzer, 2002).

1.5 Teorias Etiológicas da Esquizofrenia

Devido à sua complexidade, as causas e mecanismos da SCZ são pouco conhecidos.

Todavia, existe um consenso de que essa doença é um transtorno multifatorial que envolve

alterações genéticas e bioquímicas combinadas a fatores ambientais (Pessoa, 1989;

Krabbendam & van Os, 2005).

1.5.1 Hipótese do neurodesenvolvimento

O conceito de que a insanidade poderia ser ocasionada por disfunções no

neurodesenvolvimento foi proposto pela primeira vez por Clouston em 1891 (Murray &

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Woodruff, 1995). Entretanto, somente na década de 1980 foi proposto, também, que desordens

no neurodesenvolvimento estão envolvidos na etiologia da SCZ (Murray & Lewis,1987). Tal

hipótese sugere que alterações ocorridas durante o neurodesenvolvimento contribuem para o

progresso da doença (Weinberger, 1987). Essa ideia vem sendo corroborada por vários achados

clínicos que dão suporte a tal hipótese.

Estudos utilizando técnicas de imagem mostraram pequenas alterações, tais como

alterações no córtex pré-frontal e hipocampo e aumento ventricular durante o desen-volvimento

do sistema nervoso central de pacientes com SCZ (Weinberger et. al., 1979). Além disso, alguns

estudos clínicos revelaram alterações comportamentais durante a infância de pacientes que

foram diagnosticados com SCZ na fase adulta.

Outros estudos, relacionaram tais alterações no neurodesenvolvimento a eventos

ocorridos durante a gestação como a exposição pré-natal à alguns tipos de vírus que causam

neurotoxicidade ou transtornos autoimunes contra o tecido cerebral (Sadock et. al., 2007,

Vallada Filho & Samaia, 2000). A privação nutricional materna durante a gravidez também

vem sendo relacionada à desenvolvimento da SCZ. Um estudo realizado durante a 2ª guerra

mundial revelou a ocorrência duplicada de hospitalização por SCZ dos indivíduos gerados sob

essa condição (Vallada Filho & Samaia, 2000).

1.5.2 Teoria sináptica

Segundo Bleuler (1950), uma das características da SCZ é a alteração de milhares

associações neuronais responsáveis pelo pensamento, tornando-os estranhos e ilógicos. Essa

ideia apoia a teoria sináptica, sendo que a reunião dos resultados obtidos nas últimas décadas,

sugerem que alterações da transmissão sináptica e conectividade neuronal podem ser a principal

característica da SCZ (Frankle et al., 2003). Essa afirmação atualmente é corroborada por

estudos de imagem e modelos neuropsicológicos que revelaram conectividade aberrante em

diversas regiões cerebrais de pacientes com SCZ e alterações na transmissão sináptica (Friston

& Frith, 1995; Bull-more et. al., 1998, Kegeles & Laruelle, 2003), reforçando que a tese de que

alterações na transmissão sináptica e na conectividade neuronal são características centrais da

SCZ. Entretanto, a perda de conectividade sináptica na SCZ ocorre sem degeneração neural,

como acontece na doença de Alzheimer. Os déficits de conexão sináptica na SCZ estão

associados à falhas na organização precisa do circuito neural, e às suas características

neuroplásticas (Randall, 1983; Goodman, 1989). É importante ainda ressaltar, que baseado

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nessa hipótese, pode-se dirigir às falhas de conectividade presentes na SCZ, a responsabilidade

pelos déficits de memória e mau funcionamento hipocampal (Ben-Shachar & Laifenfeld, 2004).

1.5.3 Teoria Genética

A SCZ é considerada uma doença multifatorial que apresenta um caráter de

hereditariedade (Gejman et al., 2011). Estudos envolvendo irmãos gêmeos e adotivos foi o

primeiro passo para refutar a ideia que a SCZ poderia ser causada por fatores psicológicos, e

iniciar os estudos envolvendo genética molecular (Neill, 1990). Evidências atuais sugerem que

a doença envolve pequenas alterações em vários genes, que atuando de forma aditiva, tornam

cada vez maior o risco do indivíduo desenvolver a doença (Chowdari & Nimgaonkar, 1999).

Vários estudos evidenciam que possuir um parente com SCZ é o principal fator de risco para o

desenvolvimento da doença, sendo ainda que esse risco está associado ao grau de parentesco.

Para parentes de primeiro grau e gêmeos dizigóticos o risco gira em torno de 6-10%, e para

gêmeos monozigóticos é de 40-50% (Cardno et. al., 1999; Sullivan et al., 2003). Todavia, esses

dados revelam que apenas as alterações genéticas não são suficientes para desencadear a SCZ,

pois se assim fosse, gêmeos monozigóticos teriam uma concordância de 100% visto que

possuem o mesmo componente genético (Vallada Filho & Busatto Fillho, 1996). É necessário

que fatores ambientais, tais como estresse, viroses, complicações gestacionais entre outros,

atuem em conjunto à pré-disposição genética para que a doença se desenvolva (Vallada Filho

& Samaia, 2000).

1.6 Neurotransmissão na Esquizofrenia

Inúmeros estudos revelaram alterações consistentes no balanço de alguns sistemas

neurotransmissores de cérebros de pacientes com SCZ (Stevens, 1979; Lewis et al., 1999;

Aghajanian & Marek, 2000; Carlsson et al, 2004; Müller & Schwarz, 2006). Esses e outros

achados, como a descoberta dos efeitos antipsicóticos da clorpromazina e outras fenotiazinas

(Schubert et al., 1983), deram origem às hipóteses neuroquímicas que buscam explicar essa

neuropatologia.

1.6.1 Hipótese dopaminérgica

A hipótese dopaminérgica é o mais aceito e estudado modelo para explicar as causas

da SCZ (Rangel & Santos, 2013). Essa hipótese afirma que os sintomas psicóticos observados

na doença, são causados em função de uma hiperatividade dopaminérgica, que pode ser

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ocasionada tanto pelo aumento desse neurotransmissor nas fendas sinápticas, como devido ao

aumento de receptores para o mesmo (Harrison, 1999a).

As primeiras evidências que serviram de base para esta hipótese surgiram na década

de 60, quando o farmacologista sueco, Arvid Carlsson demonstrou que a clorpromazina e o

haloperidol possuem propriedades que levavam ao aumento dos níveis de metabólitos da

dopamina em algumas regiões cerebrais de ratos (Carlsson & Lindqvist, 1963). Essas

evidências foram reforçadas pela descoberta de que os receptores dopaminérgicos,

especialmente os do tipo D2, se encontram em níveis aumentados em cérebros de indivíduos

com SCZ (Roberts et. al., 1997), e pelos bons resultados observados no controle dos sintomas

produtivos. Pacientes tratados com antipsicóticos que bloqueavam ou antagonizavam os

receptores dopaminérgicos do tipo D2 apresentavam melhora significativa dos sintomas

produtivos, além do que, foi observado o surgimento de quadros psicóticos em indivíduos que

faziam uso de agentes indutores da liberação de dopamina, assim como por exemplo a

anfetamina (Rangel & Santos, 2013). Entretanto, essa hipótese ficou abalada, quando estudos

posteriores mostraram que o bloqueio dos receptores de dopamina não era o suficiente para

garantir uma resposta clínica no tratamento da SCZ, e que drogas mais eficazes, como a

quetiapina e a clozapina, atuam bloqueando o receptor D2 com menor intensidade, e também

bloqueiam o receptor de serotonina, sugerindo o envolvimento de outros sistemas neurais na

fisiopatologia da SCZ (Bressan & Pilowsky, 2003).

1.6.2 Hipótese serotoninérgica

A hipótese serotoninérgica surgiu na década de 50 com o relato de que o LSD (ácido

D-lisérgico) é um agonista do receptor 5-HT (receptor de serotonina). O uso de tal substância

produz sintomas psicoativos similares aos observados na SCZ, como alucinações visuais,

despersonalização e desrealização (Shaw & Woolley, 1956; Harrison, 1999a). Todavia, em

função dos fortes indícios a favor da hipótese dopaminérgica, a hipótese serotoninérgica foi

deixada de lado até meados dos anos 80, com a descoberta dos antipsicóticos de segunda

geração. O mecanismo de ação desses fármacos, somados a estudos que revelaram alterações

nos níveis de expressão dos receptores 5-HT1A e 5-HT2A em pacientes com SCZ, sugerem

fortemente um papel do sistema serotoninérgico no desenvolvimento da doença (Burnet et. al.,

1997; Trichard et. al., 1998; Harrison, 1999b).

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1.6.3 Hipótese glutamatérgica

A hipótese glutamatérgica foi inicialmente sugerida em função da observação dos

efeitos psicóticos muito semelhantes aos da SCZ, causados por anestésicos dissociativos como

a fenciclidina, a quetamina e o MK-801 (Javitt & Zukin, 1991; Davies et. al., 2011). Essas

substâncias atuam como antagonistas dos receptores de glutamato do tipo NMDA (N-Metil-D-

Aspartato) e dessa maneira, alguns pesquisadores concluíram que a hipofunção dos receptores

do tipo NMDA teria forte relação com o desenvolvimento da SCZ (Bressan & Pilowsky, 2003).

Mais tarde, estudos que evidenciaram a diminuição da liberação de glutamato e aumento de

algumas subunidades dos receptores NMDA na região cortical vieram a corroborar com a

hipótese glutamatérgica (Freedman, 2003). É importante ressaltar que as vias envolvidas nesta

hipótese estão fortemente interligadas às vias das hipóteses dopaminérgicas e serotoninérgicas,

desta maneira, alterações no funcionamento de uma destas vias, pode resultar em alterações nas

outras vias também (Carlson & Carlson, 1990; Aghajanian & Marek, 2000; Bressan &

Pilowsky, 2003).

1.7 Tratamento da Esquizofrenia

Atualmente, o método terapêutico utilizado no manejo da SCZ é o tratamento com

antipsicóticos e a intervenção psicossocial (Tandon et. al., 2010). Entretanto, devido à

compreensão limitada das vias bioquímicas envolvidas na SCZ, o desenvolvimento de

estratégias de medicina translacional é limitado. O tratamento com antipsicóticos, nem sempre

ser eficaz, geralmente apresenta uma ampla gama de efeitos adversos. Devido a isso, a maioria

dos pacientes desistem do tratamento (Lieberman et. al., 2005; Dieset et. al., 2012). Atualmente

existem duas classes de antipsicóticos utilizados no tratamento da SCZ, os antipsicóticos de

primeira e segunda geração. Uma terceira classe de antipsicóticos vêm sendo desenvolvida

mostrando resultados promissores.

1.7.1 Antipsicóticos de Primeira Geração

Os antipsicóticos de primeira geração ou típicos, como o haloperidol e flufenazina

foram desenvolvidos com base na estrutura química da clorpromazina, desenvolvida na década

de 50. O mecanismo de ação dessas drogas é devido ao antagonismo do receptor de dopamina

D2 (Carlsson, 1978; Lehman et. al., 2004). Embora esses fármacos ainda hoje sejam utilizados

na prática clínica, nem sempre apresentam o efeito desejado. A eficácia destes medicamentos é

exercida principalmente sobre os sintomas produtivos, apresentando baixa eficácia sobre os

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sintomas negativo (Agid et. al., 2008; Bressan et. al., 2002). Além disso, o uso prolongado

dessa classe de antipsicóticos está associado à uma vasta gama de efeitos adversos, sobretudo

sintomas extrapiramidais como acatisia (síndrome psicomotora que se manifesta pela

impossibilidade de estar parado) e discinesia tardia (movimentos repetitivos involuntários)

(Van Putten, 1974; Tarsy & Baldessarini, 2006). O desenvolvimento de tais sintomas

indesejados tem levado à redução do uso desta classe de drogas.

1.7.2 Antipsicóticos de Segunda Geração

Os antipsicóticos de segunda geração ou atípicos, surgiram a partir dos esforços

empreendidos na década de 60 pelos psiquiatras alemães para driblar os efeitos extrapiramidais,

até então considerados necessários para que os antipsicóticos fossem eficazes (Haase & Janssen,

1985). Os resultados dessas pesquisas levaram à introdução da clozapina como antipsicótico

(Haase & Janssen, 1985). Essa droga, que foi o protótipo dos antipsicóticos de segunda geração,

apresentava efeito sobre os sintomas produtivos e negativos da SCZ, e ainda possuía baixa

propensão em induzir efeitos extrapiramidais (Hippius, 1989). Em função de tais

características, o uso da clozapina se espalhou rapidamente e foi seguido do desenvolvimento

de outras drogas com características similares como a risperidona, a olanzapina, a quetiapina e

a ziprasidona, que diferem umas das outras em relação à afinidade de ligação ao receptor,

eficácia e perfil de efeitos adversos (Shen, 1999). O mecanismo de ação dos antipsicóticos de

segunda geração, também é devido ao antagonismo dos receptores D2, porém com menor

intensidade que as drogas de primeira geração, além disso também apresentam efeito

antagônico sobre os receptores 5-HT2A da serotonina, o que provavelmente é importante para

o controle dos sintomas negativos da SCZ, uma vez que o sistema serotoninérgico tem sido

associado ao humor, cognição e memória (Meltzer, 2013; Cassoli et. al., 2016a).

1.7.3 Antipsicóticos de Terceira Geração

Essa classe de antipsicóticos ainda está em desenvolvimento e possuí somente um

representante em uso clínico, o aripiprazol. Diferentemente dos outros antipsicóticos existentes,

o aripiprazol é um agonista parcial dos receptores D2 da dopamina e 5-HT1A da serotonina e

antagonista do receptor 5-HT2A (Tamminga, 2002; Lieberman, 2004). Sua eficácia sobre o

controle dos sintomas produtivos e negativos da SCZ vem sendo comprovada por vários estudos

de curto e longo prazo (Kane et. al., 2002; Miller et. al., 2007). No entanto, um relatório de

avaliação do fármaco afirmou que o aripiprazol em sua forma oral apresenta baixa eficácia, o

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que levou vários pacientes a abandonarem o tratamento durante os testes clínicos (Belgamwar

& El-Sayeh, 2011).

1.8 Modelos para o Estudo da Esquizofrenia

Os modelos experimentais para estudar os transtornos psiquiátricos foram

desenvolvidos a partir de 1984, buscando prever a ação farmacológica de drogas terapêuticas,

seguindo os critérios pré-estabelecidos por Paul Willner (validade preditiva, validade

fenomenológica e a validade por constructo) (Silva, 2006). Pode ser considerado um modelo

para estudar uma doença ou processo fisiológico, qualquer preparação experimental que

mimetize os aspectos de interesse (Geyer & Moghaddam, 2002). Um modelo pode ser

desenvolvido em seres humanos, animais de laboratório, culturas celulares e até mesmo através

de simulações matemática e computacionais (Silva, 2006; Salgado et. al., 2006). Todavia, no

caso dos transtornos psiquiátricos, assim como a SCZ, os modelos apenas lembram de maneira

distante ou indireta, o que realmente ocorre nos seres, humanos (Salgado et. al., 2006). Sendo

ainda, que um modelo que seja capaz de abranger toda a complexidade da SCZ parece ser algo

impossível, uma vez que suas múltiplas etiologias e fatores genéticos-ambientais produzem

uma alta complexidade neurológica que envolve funções superiores tais como abstração e

linguagem inerentes apenas dos seres humanos (Silva, 2006; Salgado et. al., 2006).

1.8.1 Modelos in vivo

Os modelos in vivo utilizados para o estudo da SCZ podem ser humanos, (ensaios

clínicos não invasivos e observação de melhora dos sintomas) ou animais. Entretanto os estudos

envolvendo seres humanos além de serem permitidos somente na fase final de testes de algum

medicamento, no caso da SCZ encontra mais um obstáculo, o qual caracteriza-se pelo fato dos

indivíduos afetados por tal transtorno serem pouco estáveis e propensos a participarem de

estudos longos. Dessa maneira, os modelos in vivo mais utilizados são os modelos animais. Este

tipo de modelo é largamente utilizado em grande parte das investigações pré-clínicas buscando

mimetizar mecanismos fisiológicos, patológicos ou compreender a ação de drogas (Cassoli et.

al., 2016a). Em relação às doenças somáticas esses modelos são muitas vezes bastante próximos

à forma como se desenvolvem em seres humanos. Todavia, em se tratando de doenças

psiquiátricas, especialmente a SCZ, nos deparamos com a complexidade do transtorno e a

impossibilidade de observar em modelos animais alterações à nível de abstração e pensamento

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(Kilts, 2001; Gottschalk et. al., 2013). Sendo assim, os modelos animais utilizados para o estudo

deste transtorno não preenchem todos os critérios já descritos acima (Salum et. al., 2007).

A complexidade da SCZ impõe um desafio, não somente na observação dos

sintomas em modelos animais, mas também ao seu desenvolvimento, uma vez que as alterações

genéticas, comportamentais da doença apresentam grande variação. Por tanto não existe até o

momento, um modelo que possa ser considerado definitivo e que englobe todas as

características da doença (Lipska & Weinberger, 2000), e mesmo os modelos que avaliam

apenas um único aspecto da doença, devem ser questionados levando em conta as diferenças

neuropsíquicas entre os modelos animais e os seres humanos (Lipska & Weinberger, 2000;

Jones et. al., 2011). Porém, apesar de todos esses aspectos que devem ser considerados ao se

utilizar modelos animais para o estudo da SCZ, eles foram e ainda são necessários para a

compreensão de alguns aspectos. Os modelos que fazem uso de substâncias agonistas do

sistema dopaminérgico foram de grande valia no desenvolvimento de antipsicóticos atualmente

utilizados (Lipska & Weinberger, 2000). Outros, entre os mais de 20 modelos desenvolvidos

para o estudo da SCZ (Carpenter & Koenig, 2008), também tiveram importante participação na

compreensão de outros aspectos da doença como alterações genéticas e influência de

substâncias.

Na atualidade existem várias pesquisas e grande discussões a respeito de modelos

animais para o estudo de doenças psiquiátricas, porém até o presente momento não existe um

consenso sobre o assunto e nem modelos mais específicos (Moore, 2008).

1.8.2 Modelos in vitro

Os modelos in vitro para a SCZ baseiam-se em cultura de células e organoides. A

utilização de cultura celular para a compreensão e observação de ação de drogas tem sua

eficácia comprovada como ferramenta pré-clínica desde que começou a ser empregada para tal

finalidade (Astashkina et. al., 2012). Esse tipo de modelo se torna interessante pois é possível

ter um maior controle de variáveis e pode-se obter informações mais precisas e específicas de

determinado processo, entretanto quando se busca entender processos mais complexos que

envolvam interação com outras células, tecidos e/ou moléculas, esse modelo se torna falho

(Astashkina et. al., 2012). É exatamente aí que se encontra o problema, pois a SCZ é um

transtorno de alta complexidade e estudo utilizando células em culturas isoladas é capaz de

fornecer apenas informações parciais que necessitam de validação. Uma alternativa, que pelo

menos diminui esse problema, é a utilização de organoides, como os mini brains por exemplo,

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que por serem sistemas de maior complexidade, também podem fornecer informações mais

precisas sobre alguns processos.

Todavia apesar das limitações descritas acima, as ações de antipsicóticos sobre

culturas de células vem sendo avaliadas em estudos proteômicos, fornecendo informações de

relevantes para estudos posteriores (Cassoli et. al., 2016a).

1.9 A proteômica e a esquizofrenia

A proteômica surgiu na era pós genômica, e pode ser definida como o estudo

qualitativo ou quantitativo que avalia o proteoma, sendo que este, trata-se do perfil proteico

codificado pelos genes de uma determinada célula, tecido ou organismo, incluindo alterações

pós-traducionais e estudo de interações, em determinadas condições (Wasinger et al., 1995,

Nogueira & Domont, 2014). A proteômica utiliza 3 ferramentas básicas estudos da expressão

proteica: eletroforese (uni ou bidimensional), cromatografia líquida e MS, sendo essa última

técnica a mais sensível e promissora.

Devido suas características, a proteômica é atualmente uma das principais

ferramentas para a compreensão de vias bioquímicas e, por consequência, de transtornos

multifatoriais, como por exemplo, a SCZ (Martins-de-Souza, 2012). Nas últimas duas décadas

um considerável número de trabalhos que utilizaram a proteômica para o estudo da SCZ foram

publicados. Dentre os resultados obtidos, foi possível observar, em cérebros post-mortem de

pacientes com SCZ, alterações em vias relacionadas à transmissão neuronal e função sináptica,

ao metabolismo energético, à homeostasia de cálcio, ao sistema imune e inflamação e ao

estresse oxidativo, e alterações de proteínas do citoesqueleto, (Nascimento & Martins-de-

Souza, 2015). Esses resultados são extremamente interessantes, pois a identificação de

proteínas diferencialmente expressas pode levar a indicação de biomarcadores que ajudem no

diagnósticos e/ou prognóstico da doença (Blonder et. al., 2011).

É importante destacar que em distúrbios complexos como a SCZ, muitas vezes

existem alterações importantes em inúmeras proteínas. Entretanto, apesar da sensibilidade da

técnica de MS, muitas vezes não é possível detectar proteínas que estão em concentrações muito

baixas, caso a amostra seja muito complexa e/ou contendo outras proteínas em altas

concentrações. Dessa forma, pode-se perder algum detalhe importante (Huber, 2003). Para

contornar esse problema, o estudo dos sub proteomas aparece como uma alternativa satisfatória.

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1.9.1 Espectrometria de Massas

A espectrometria de massas (MS, Mass Spectrometry), é uma técnica de análise

qualitativa e quantitativa, que consiste no estudo de íons em fase gasosa e possibilita a

identificação da composição química de compostos isolados ou de diferentes compostos em

misturas complexas (Aebersold & Mann, 2016; Van Bramer 1998). Essa identificação ocorre

pela determinação das massas moleculares dos analitos em função da movimentação destes

através de um campo elétrico, sendo ainda que, tal movimentação é determinada em função da

razão massa/carga (m/z) do analito. É importante ressaltar que não é possível analisar moléculas

ou átomos neutros por MS.

Nos anos 70 começou a surgir um grande interesse da comunidade científica na

utilização da MS para caracterização de biomoléculas (Yates III, 2011). Todavia, a limitação

dessa ideia estava na geração de íons em fase gasosa a partir de macromoléculas. Somente no

final dos anos 80, com o surgimento de técnicas de ionização suave como ESI (Eletrospray

Ionization – Fenn et. al., 1989) e MALDI (Matrix-Assisted Laser Desorption Ionization – Karas

et al., 1985; Tanaka et al., 1985), foi possível utilizar MS para o estudo de biomoléculas como

peptídeos, proteínas e ácidos nucléicos (Karas et al. 1985, Tanaka et. al., 1985; Fenn et. al.,

1989). Com o surgimento dessas novas técnicas de ionização e com a evolução dos analisadores

de massas, a MS para a análise de biomoléculas, especialmente proteínas evoluiu

extensivamente. Atualmente a MS é largamente utilizada no estudo de proteínas e complexos

proteicos, como por exemplo, na identificação, sequenciamento, determinação da massa

molecular, quantificação, etc (Taylor & Johnson, 1997; Gygi & Aebersold, 2000; Bantscheff et

al., 2007).

A análise por espectrometria de massas, em geral ocorre em cinco etapas: (1º)

injeção da amostra; (2º) ionização das moléculas (3º); separação dos íons formados em função

da razão m/z pelo analisador de massas; (4º) contagem dos íons e transformação do sinal em

corrente elétrica pelo detector; (5º) processamento e geração do espectro por meio da conversão

do sinal elétrico em dados com base na magnitude do sinal e da razão m/z (Romão, 2010;

Aebersold & Mann, 2003).

1.9.2 Proteômica subcelular

Em 1950, com o advento da microscopia eletrônica, foi observado que as células

possuem um nível de organização mais elaborada do que se pensava, compreendendo vários

subcompartimentos delimitados por membranas (Brunet et. al., 2003). Esse achado, hoje é uma

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das ferramentas utilizadas para contornar as limitações existentes na análise de amostras

complexas por MS, favorecendo a análise para vias específicas.

Estima-se que o número total de produtos gênicos, mais especificamente proteínas,

em qualquer célula seja aproximadamente 10.000. Embora possa parecer que o conteúdo

proteico celular não é tão complexo quanto outros tipos de amostras, esse número é

provavelmente subestimado cerca de 10 ordens de magnitude devido às varientes de splicing e

à grande variedade de modificações pós-traducionais. Dessa forma, proteínas de baixa

abundância, como por exemplo alguns receptores de membrana e proteínas de sinalização,

sejam mascaradas pelas proteínas que estão em maior concentração (Huber, 2003). Por tanto,

uma abordagem proteômica simples, muitas vezes pode não refletir a totalidade da dinâmica

proteica existente em uma amostra.

Além da separação de organelas, existem outras formas de fracionamento possíveis,

como por exemplo métodos cromatográficos. No entanto, a separação de organelas é uma

ferramenta valiosa para análise do proteoma celular, pois o conteúdo proteico das amostras é

reduzido representando um conjunto moléculas específicas e direcionadas. Isso proporciona a

possibilidade de cruzar os dados de proteômica com as unidades funcionais (Taylor et. al.,

2003).

1.9.3 Núcleo

O núcleo é a maior organela da célula ocupando aproximadamente 10% do volume

celular (Alberts et. al., 2010), e é o compartimento onde o material genético de células

eucarióticas fica armazenado. O núcleo é delimitado por uma dupla membrana composta por

duas bicamadas lipídicas que são sustentadas por uma rede filamentosa denominada lâmina

nuclear (Calikowski et. al., 2003). A bicamada mais externa do núcleo interage diretamente

com retículo endoplasmático e a mais interna apresenta um conjunto de proteínas que interagem

com componentes nucleares internos (Erhardt et. al., 2010). Ambas as camadas apresentam

poros proteicos que permitem o fluxo dinâmico de moléculas entre os meios interno e externo,

conferindo à esta organela o título de principal organela regulatória celular (Erhardt et. al.,

2010; Aitchison & Rout, 2012). Embora o núcleo seja uma compartimentalização celular, o

mesmo também não é homogêneo e apresenta diversos subcompartimentos com funções

específicas. Isso é um indicativo de que a relação entre função e localização também está

presente no interior do núcleo (Erhardt et. al., 2010). Dessa forma, compreendendo as

importantes funções e características nucleares, entende-se porque a análise proteômica do

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núcleo em SCZ é necessária. Existem poucos estudos a respeito das proteínas nucleares

relacionadas à SCZ mesmo sabendo-se que o núcleo contém toda a informação genética

relacionada à expressão proteica e de controle da transcrição e liberação dos produtos gênicos.

1.9.4 Proteoma nuclear

As proteínas nucleares correspondem de 10-20% do total de proteínas celulares e

exercem importantes funções para o correto funcionamento celular, entre elas o controle da

expressão gênica (Narula et. al., 2013). Dessa maneira a caracterização do proteoma nuclear é

de extrema importância para a compreensão de qualquer processo fisiológico ou patológico.

Exemplos disso podemos observar em estudos que analisam o proteoma nuclear de células

cancerígenas, infectadas por vírus, entre outros (Wu et al., 2010; DeBoer et al., 2014).

Assim, devido a importância das proteínas nucleares e os poucos estudos

envolvendo as mesmas em SCZ, fica clara a relevância de se estudar o proteoma nuclear em

busca de novos achados que possam contribuir para o entendimento dos mecanismos

moleculares deste transtorno psiquiátrico.

2. OBJETIVOS

2.1 Objetivo Geral O objetivo geral desse estudo foi analisar o proteoma nuclear da substância branca,

usando amostras do corpo caloso, e da substância cinzenta, utilizando amostras do lobo

temporal anterior, coletadas em cérebros post-mortem de pacientes com SCZ. Também foi

objetivo desse trabalho analisar o proteoma nuclear de oligodendrócitos humanos (linhagem

MO3.13) tratados com MK-801.

2.2 Objetivos Específicos

Os objetivos específicos desse trabalho foram:

- Tratar qualitativa e quantitativamente os dados obtidos pelas análises do proteoma nuclear da

substância branca e cinzenta cerebral por espectrometria de massas.

- Padronizar o cultivo da linhagem celular MO3.13 de oligodendrócitos humanos (OLs) e

montar uma biblioteca de células

- Realizar tratamento agudo (8h) e crônico (72h) das células MO3.13 com MK-801.

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- Padronizar um método eficiente de separação de núcleo a partir de células obtidas através de

cultura.

- Extrair as proteínas nucleares das células tratadas e controles e realizar análise do proteoma

nuclear por cromatografia líquida acoplada à espectrometria de massas (shotgun proteomics).

3. JUSTIFICATIVA

A SCZ é um transtorno mental grave que gera grandes onerações sociais, além de

levar a incapacitação para o trabalho de pessoas em idade ativa, levando também à danos

econômicos. A compreensão bioquímica da SCZ bem como estudos de prognóstico são

escassos, impossibilitando o desenvolvimento de estratégias de medicina translacional. O

tratamento farmacológico deste distúrbio é pouco efetivo e apresenta uma ampla gama de

efeitos colaterais (Lieberman et al., 2005; Tandon et al., 2008; Dieset et al., 2012; Tandon et

al., 2010), induzindo até 2/3 dos pacientes à abandonarem a medicação. Dessa maneira, torna-

se importante a compreensão das vias bioquímicas envolvidas na SCZ. Nosso grupo, apoiado

por dados de outras áreas do conhecimento, tem observado que os oligodendrócitos tem papel

fundamental no estabelecimento e desenvolvimento da SCZ (Hof et al., 2002; Tkachev et al.

2003; Martins-de-Souza, 2010; Cassoli et al., 2015, Vikhreva et al., 2016). Nesse trabalho, os

esforços foram direcionados em compreender e comparar as alterações que ocorrem em vias

bioquímicas e proteínas estruturais presentes em núcleos das células que compõe a substância

branca e cinzenta com as alterações observadas no proteoma nuclear de oligodendrócitos da

linhagem MO3.13 tratados com MK-801.

Esse trabalho se justifica pela importância em buscar maior compreensão a respeito

das características moleculares inerentes à SCZ, possibilitando o desenvolvimento de

tratamentos e diagnósticos mais precisos e específicos. Ademais, esse trabalho apresenta caráter

pioneiro em analisar as proteínas nucleares de um modelo farmacológico in vitro da SCZ, assim

como de tecidos obtidos de pacientes no desenvolvimento da doença.

4. METODOLOGIA, RESULTADOS E DISCUSSÕES

A metodologia empregada no desenvolvimento desse trabalho e os resultados

obtidos serão apresentados em três capítulos distintos. No primeiro capítulo, tanto a

metodologia quanto os resultados obtidos com a análise dos tecidos cerebrais de pacientes com

esquizofrenia, serão descritos na forma de um artigo, que está atualmente submetido no

periódico Molecular Neuropsychiatry. No segundo capítulo, será detalhada a metodologia

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empregada para o desenvolvimento e padronização da cultura celular da linhagem de

precursores de oligodendrócitos humanos MO3.13, o tratamento dessas células com MK-801,

o enriquecimento nuclear, e extração e preparação das proteínas nucleares para as análises por

LC-MS/MS. Este capítulo será publicado em meados de julho de 2017 como um dos capítulos

do livro “Neuromethods Series-Springer”. No terceiro capítulo, apresentaremos os resultados

proteômicos obtidos com as células tratadas com MK-801, feita de acordo com a metodologia

empregada por Saia-Cereda e colaboradores (2016). Ao final da tese, os 2 anexos apresentados

são artigos científicos já publicados, os quais participei ativamente da escrita.

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5. CAPÍTULO 1

Artigo submetido para publicação na Molecular Neuropsychiatry

THE NUCLEAR PROTEOME OF WHITE AND GRAY MATTER FROM

SCHIZOPHRENIA Aline G. Santana1,#, Verônica M. Saia-Cereda1,#, Andrea Schmitt2,3, Peter Falkai2, Daniel Martins-de-Souza1,4,*

1- Laboratory of Neuroproteomics, Department of Biochemistry and Tissue Biology, Institute of Biology, University of Campinas (UNICAMP), Campinas, São Paulo, Brazil.

2- Department of Psychiatry and Psychotherapy, Ludwig Maximilian University (LMU), Munich, Germany.

3- Laboratory of Neurosciences (LIM-27), Institute of Psychiatry, University of São Paulo, São Paulo, Brazil.

4- UNICAMP’s Neurobiology Center, Campinas, Brazil.

# Contributed equally

* Corresponding author:

Prof. Daniel Martins-de-Souza, PhD

Laboratory of Neuroproteomics

Department of Biochemistry and Tissue Biology

University of Campinas (UNICAMP)

Rua Monteiro Lobato, 255

13083-862 - Campinas, SP, Brazil

Tel: +55 19 3521-6129

E-mail: [email protected]

Abstract

Schizophrenia is a serious neuropsychiatric disorder that manifests through several

symptoms from young adulthood on and its treatment is among the most expensive across all

diseases. In contrast to its high prevalence and severity, little is known about the mechanisms

involved in the development and progression of the disease. However, numerous studies over

the last decades have led to significant advances in increasing our understanding of the factors

involved in schizophrenia (SCZ). For example, mass spectrometry-based proteomic analysis

has provided important insights by uncovering protein dysfunctions inherent to SCZ. Here, we

present a comprehensive analysis of the nuclear proteome of postmortem brain tissues from

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corpus callosum (white matter) and anterior temporal lobe (gray matter) collected from SCZ

patients in an attempt to characterize the role of this organelle in the disease process.

Key words: schizophrenia, proteomics, nucleus, nuclei, nuclear proteome.

5.1. Introduction

Schizophrenia (SCZ) is a serious, debilitating and incurable mental disorder that

affects approximately 1% of the world's population [1]. The disease manifests itself between

the end of adolescence and the beginning of adulthood [2] and is characterized by a range of

cognitive, behavioral and emotional dysfunctions. SCZ is the main cause of psychiatric

incapacitation [3] and, although it is usually treated as a single disease, it is likely to be a

spectrum of related disorders with distinct etiology, clinical presentation, response to treatment

and development [4]. Despite its high prevalence and severity, little is known about the

biochemical mechanisms involved in its development or progression and so there a few

established molecular diagnoses or specific treatments. Thus, there is currently a great interest

in obtaining new knowledge about the disease and, in this arena, proteomic analyses have

already yielded promising results and opened up new avenues of research.

Proteomics is a tool used to analyze the protein profile of a specific cell type, tissue

or organism, or changes in specific proteins, using mass spectrometry (MS) as its main tool.

Due to its capacity for profiling large numbers of proteins simultaneously, proteomics is

currently one of the main techniques used to understand biochemical pathways and,

consequently, multi-factorial disorders such as SCZ [5]. In the last two decades, proteomics has

contributed to a growing understanding of schizophrenia and a number of publications

involving this disorder have been published revealing alterations in several biochemical

pathways of the central nervous system [6]. However, it is important to note that in proteomic

analyses of whole tissues, it is often possible to detect proteins that are present at low

concentrations. This may occur due to the complexity of the sample and/or due to the presence

of other proteins that are present a very high concentrations which may obscure those of lower

abundance. This could lead to an inability to detect proteins which have important roles in the

disease process [7]. To circumvent this problem, the study of sub-proteomes appears as a

satisfactory alternative.

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Sub-proteomes are obtained by fractionating the proteins of a given sample into

distinct groups, taking into account some specific criteria. Although there are several ways of

fractionating the protein content of a sample, one alternative is the analysis of specific

organelles. This type of fractionation is attractive for cellular proteome analyses, since the

protein content of the organelles is less complex and represents a specific and directed set,

which provides the opportunity of investigating entire protein networks to an extent that cannot

be achieved using whole cell approaches [8].

In this study, we have used a protocol for separation of organelles in order to obtain

samples enriched in cell nuclei. The nucleus is the largest organelle of most cells and occupies

approximately 10% of its volume, although this varies according to the cell type [9]. The

nucleus is the compartment where the genetic material of eukaryotic organisms is stored and

nuclear proteins constitute 10-20% of the total cellular proteins and exert important functions

related to gene expression, transcriptional control, splicing and generation of the final gene

products [10]. Therefore, the importance of investigating the nuclear proteome for the

understanding of any physiological or pathological process is clear, and few such studies have

been carried out thus far in the field of psychiatric disorders such as schizophrenia.

As an added level of enrichment, we have analyzed nuclei obtained from the

anterior temporal lobe (ATL) and corpus callosum (CC) regions of postmortem brains from

patients and controls. Dysfunctions in theATL have been implicated previously in

schizophrenia and it consists mostly of gray matter [11]. The CC is the largest white matter

region of the brain and there are morphological, electrophysiological and neurophysiological

studies showing significant involvement of this region in patients with schizophrenia [12–14].

Because the brain works through communication with and across the different regions, we

jointly analyzed the ATL and CC nuclear proteins to provide further information on the

potential role of dysfunctions of this organelle in schizophrenia.

5.2 Materials and methods

5.2.1 Human samples

Corpus callosum and anterior temporal lobe samples were collected postmortem

from 12 patients who had suffered from chronic schizophrenia and from 8 healthy controls

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(Table 1). The patient samples were from the Nordbaden Psychiatric Center, Wiesloch,

Germany, and the controls were from the Institute of Neuropathology, Heidelberg University,

Heidelberg, Germany. Postmortem evaluations and procedures were approved by the ethics

committee of the Heidelberg University Medical School and both patients and controls gave

written consent prior to death that their brains could be used for research purposes.

Table 1 - Clinical data of patients and controls.

Case Age (years)

Gender

PMI (hours)

pH Duration of Disease (years)

Duration of Medication (years)

atyptyp valu

es SCZ 64 F 11 6,7 48 45 3

SCZ 73 M 20 6,6 43 40 1

SCZ 43 M 18 6,9 22 20 2

SCZ 77 F 32 6,5 49 48 2

SCZ 76 F 17 6,8 49 47 1

SCZ 63 F 31 6,8 40 30 3

SCZ 92 F 37 6,9 51 48 1

SCZ 71 M 28 6,4 40 35 1

SCZ 51 M 7 6,1 25 25 1

SCZ 51 M 12 6,7 28 25 2

SCZ 81 M 4 6,7 62 50 1

SCZ 64 F 23 6,6 41 40 2

Control 41 M 7 6,5

Control 91 F 16 6,7

Control 69 F 96 6,4

Control 57 M 24 6,9

Control 53 M 18 7

Control 63 M 13 6,5

Control 66 M 16 6,8

Control 79 M 24 6,4

CPE last dose

CPE last ten years Cause of Death DSM

IV Age at Onset Last Medication

1536 7,7 pulmonary insufficiency 295,6 16 Clozapine 500 mg, Haloperidol 40 mg,

Ciatyl 40 mg

507,4 1,7 heart infarction 295,6 30 Perphenazine 32 mg, Promethazine 150 mg

464 2,6 heart infarction 295,6 20 Zuclopethixol 40 mg, Valproate 1200 mg, Tiapride 300 mg

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CPE last dose

CPE last ten years

Cause of Death DSM

IV Age at Onset Last Medication

2555 8,3 lung embolism 295,6 28 Clozapine 400 mg, Benperidol 25 mg, Chlorprothixen 150 mg

300 4,9 cardio-pulmonary insufficiency 295,6 27 Perazine 300 mg

75 1,8 heart infarction 295,6 24 Olanzapine 15 mg

100 3,4 Cardio-pulmonary insufficiency 295,6 41 Prothipendyl 160 mg, Perazine 100 mg

782,4 10 heart infarction 295,6 30 Haloperidol 32 mg, Pipamperone 40 mg

147 0,6 heart infarction 295,6 19 Flupenthixol 15 mg

450 1,8 heart infarction 295,6 23 Clozapine 500 mg

92,8 1,4 Heart insufficiency 295,6 19 Haloperidol 40 mg, Prothypendyl 80 mg

54,5 4,6 heart infarction 295,6 24 Zotepine 150 mg, Olanzapine 10 mg

heart infarction

cardio-pulmonary insuffiency

lung embolism

heart infarction

heart infarction

heart infarction

heart infarction

heart infarction

Cigarettes Alcohol Hosp ECT 0 no 21 yes

30/day no 33 no

0 no 13 no

0 no 48 yes

0 no 30 yes

30/day no 30 yes

0 no 51 no

40/day no 12 no

30/day no 20 no

30/day no 17 no

20 no 48 no

20/day no 5 yes

0 no

0 no

0 no

0 no

0 no

0 no

0 no

0 no

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2.2 Nuclear Enrichment

Nuclear proteins were obtained from the ATL and CC brain tissues according to the

protocol of Cox and Emili [15]. In this protocol, Each sample (20 mg tissue) was homogenized

in 10 volumes of 250 mM sucrose (Sigma-Aldrich, St. Louis, MO, USA), 50 mM Tris-HCl, 5

mM MgCl2 (Sigma-Aldrich), 1 mM dithiothreitol (Sigma-Aldrich), 250 µg spermine and 250

µg spermidine buffer (pH=7.4), containing 1 tablet of protease cocktail inhibitor (Roche

Diagnostics, Indianapolis, IN, USA) per 25 mL buffer. The homogenate was centrifuged at

100xg for 1 min at 4°C. The supernatant was discarded. To the sediment was added 5 volumes

of 250 mM sucrose (Sigma-Aldrich, St. Louis, MO, USA), 50 mM Tris-HCl, 5 mM MgCl2

(Sigma-Aldrich), 1 mM dithiothreitol (Sigma-Aldrich), 250 µg spermine and 250 µg

spermidine buffer (pH=7.4), containing 1 tablet of protease cocktail inhibitor (Roche

Diagnostics, Indianapolis, IN, USA) per 25 mL buffer. The homogenate was centrifuged at

800xg for 15 min at 4°CThe supernatant was separated for further separation of the

mitochondria and stored at -80 as CitoI. The previous step was repeated and the supernatant

was named as CytoII. The pellet was homogenized in 4 mL of 2 M sucrose (Sigma-Aldrich, St.

Louis, MO, USA), 50 mM Tris-HCl, 5 mM MgCl2 (Sigma-Aldrich), 1 mM dithiothreitol

(Sigma-Aldrich), 250 µg spermine and 250 µg spermidine buffer (pH=7.4), containing 1 tablet

of protease cocktail inhibitor (Roche Diagnostics, Indianapolis, IN, USA) per 25 mL buffer. A

mistura foi filtrada com gaze, e o filtrado foi colocado sobre uma almofada de 4 mL do mesmo

tampão. The tube was centrifuged at 80.000xg for 35 min at 4°C. The pellet contained the pure

nuclei. The nuclear protein pellet was dissolved in 50 mM ammonium bicarbonate (pH 8.0)

prior to protein digestion.

5.2.3 Mass spectrometry

Protein extracts from nuclear enrichment of ATL and CC were digested by trypsin

at a ratio of 1:80 (trypsin: total protein). The resulting peptides were lyophilized and frozen at

-80°C before mass spectrometry analysis. Immediately prior to analysis, lyophilized peptides

were dissolved in an aqueous solution of 0.1% formic acid and injected into a 2D-nano high

performance liquid chromatography (HPLC) system (Eksigent; Dublin, CA, USA) coupled

online to a LTQ XL-Orbitrap mass spectrometer (Thermo Scientific; Bremen, Germany). The

specifics of data acquisition are described in detail in Maccarrone et al., 2013 [16].The proteins

were quantified label-free using the MASCOT Distiller program (Matrix Sciences; London,

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UK), based on the relative intensities of the extracted ion chromatograms (XICs) (for further

details, see Saia-Cereda 2015 [17]).

5. 2.4 Analysis in silico

Shotgun proteomics analysis can produce high amounts of data, especially in

studies of complex biological mixtures, such as postmortem brain samples. As an consequence,

protein-protein interaction analysis and identification of the pathways involved are fundamental

to understanding cellular phenotypes in the most complete manner possible. Due to this, we

used bioinformatics tools available online in these analyses. These were: the Search Tool for

the Retrieval of Interacting Genes/Proteins (STRING, http://string-db.org/), Kyoto

Encyclopedia Genes and Genomes (KEGG, http://www.genome.ad.jp/kegg/) and Reactome

(http://reactome.org/).

5.3 Results and discussion

In the results of the ATL nucleus enrichment, we identified a total of 4293 unique

peptides, which corresponded to 629 proteins. Of these, 224 were present at significantly

different levels between the SCZ and control samples and 76 were nuclear proteins (nuclear

enrichment of 33% - Table 2). In the CC analysis, were identified 3820 unique peptides,

corresponding to 552 proteins with 119 present at different levels and 24 of these were nuclear

proteins (nuclear enrichment of 21% - Table 3). These differentially expressed proteins were

analyzed using the online human protein reference database (http://www.hprd.org/) in order to

find the biological processes and function/molecular classes with which they are related (see

Table 2 and Table 3).

Table 2 - Proteins differentially expressed in schizophrenia anterior temporal lobe (ATL).

Gene Name Description Score Mass N° Peptides SCZ/CTRL SD

PKP2 Plakophilin-2 76 97852 2 0,05 5,154

BIN1 Myc box-dependent-interacting protein 1 175 64887 5 0,63 1,859

CADM1 Cell adhesion molecule 1 102 48935 3 0,44 4,93

CALM1 Calmodulin 759 16827 9 2,10 3,515

CDC42 Cell division control protein 42 homolog 74 21696 2 4,13 5,878

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CSRP1 Cysteine and glycine-rich protein 1 244 21409 5 0,49 2,012

CTNNB1 Catenin beta-1 71 86069 2 0,48 1,285

DPYSL2 Dihydropyrimidinase-related protein 2 1892 62711 30 2,40 2,513

PPP3CA

Serine/threonine-protein phosphatase 2B catalytic subunit alpha isoform 325 59335 5 1,92 9,805

PPP3R1 Calcineurin subunit B type 1 76 19402 2 4,30 9,98

PRKAR2B

cAMP-dependent protein kinase type II-beta regulatory subunit 157 46672 2 0,47 1,132

SEPT7 Septin-7 493 50933 11 2,16 2,939 SH3GL2 Endophilin-A1 216 40108 4 1,76 3,614

SIRT2 NAD-dependent deacetylase sirtuin-2 220 43782 5 3,94 8,747

SNCB Beta-synuclein 447 14279 6 2,05 3,512 YWHAE 14-3-3 protein epsilon 595 29326 12 0,40 4,13 YWHAG 14-3-3 protein gamma 1010 28456 18 0,56 3,229 YWHAQ 14-3-3 protein theta 400 28032 7 0,41 2,421 SEPT2 Septin-2 173 41689 3 1,86 2,96

CRMP1 Dihydropyrimidinase-related protein 1 368 62487 6 3,50 1,543

DYNLL1 Dynein light chain 1, cytoplasmic 141 10530 4 1,97 8,851

EPB41L3 Band 4.1-like protein 3 473 121458 13 0,56 7,25 FLNA Filamin-A 612 283301 8 0,36 4,413 LMNA Lamin-A/C 387 74380 7 0,11 3,386 LMNB2 Lamin-B2 173 67762 3 0,18 5,639

MAP1A Microtubule-associated protein 1A 187 306923 4 0,35 7,653

MAPRE2

Microtubule-associated protein RP/EB family member 2 338 37236 6 2,41 4,902

MYH9 Myosin-9 330 227646 4 0,23 1,904

VIM Vimentin 2238 53676 37 0,35 5,159 LGALS1 Galectin-1 79 15048 2 0,65 2,212

LDHA L-lactate dehydrogenase A chain 385 36950 8 2,48 2,252

COX4I1

Cytochrome c oxidase subunit 4 isoform 1, mitochondrial 126 19621 3 0,43 1,693

COX5B Cytochrome c oxidase subunit 5B, mitochondrial 170 13915 4 7,19 4,156

GSTP1 Glutathione S-transferase P 147 23569 2 1,64 1,268

NDUFS8

NADH dehydrogenase [ubiquinone] iron-sulfur protein 8, mitochondrial 96 24203 2 1,52 1,993

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PDE2A cGMP-dependent 3',5'-cyclic phosphodiesterase 89 107360 2 9,65 2,299

PDHA1

Pyruvate dehydrogenase E1 component subunit alpha, somatic form, mitochondrial 219 43952 7 0,35 5,372

PGK1 Phosphoglycerate kinase 1 510 44985 11 1,86 6,605 PRDX1 Peroxiredoxin-1 198 22324 4 3,30 1,57 CANX Calnexin 182 67982 5 1,85 3,216

HSPD1 60 kDa heat shock protein, mitochondrial 1089 61187 21 1,90 2,418

CALR Calreticulin 197 48283 2 0,31 1,984

CCT4 T-complex protein 1 subunit delta 105 58401 3 1,56 2,874

DNAJC5 DnaJ homolog subfamily C member 5 93 22933 2 3,89 5,26

HSPA1A Heat shock 70 kDa protein 1 390 70294 8 1,84 2,307

HSPA2 Heat shock-related 70 kDa protein 2 485 70263 13 1,91 2,814

HSPA6 Heat shock 70 kDa protein 6 328 71440 7 1,77 2,398

HSPA8 Heat shock cognate 71 kDa protein 1156 71082 22 1,84 2,293

HSPE1 10 kDa heat shock protein 130 10925 3 2,31 1,134

PSMA4 Proteasome subunit alpha type-4 71 29750 3 0,44 1,528

SNCA Alpha-synuclein 879 14451 12 1,88 3,76

EEF1A1 Elongation factor 1-alpha 1 312 50451 9 0,58 2,182 H2AFV Histone H2A.V 143 13501 2 0,17 1,264

BASP1 Brain acid soluble protein 1 1796 22680 24 0,51 1,805

CAND1 Cullin-associated NEDD8-dissociated protein 1 118 137999 2 1,81 4,005

H3F3A Histone H3.3 217 15376 5 0,50 3,531

HIST1H1C Histone H1.2 237 21352 3 0,57 4,622

HIST1H2AB Histone H2A type 1-B/E 249 14127 6 0,38 2,971

HIST1H2AD Histone H2A type 1-D 226 14099 6 0,33 1,799

HIST1H2BB Histone H2B type 1-B 190 13942 3 0,41 5,283

HIST1H2BC Histone H2B type 1-C/E/F/G/I 165 13811 3 0,43 1,266

HIST1H4A Histone H4 637 11360 11 0,46 3,406

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HNRNPA2B1 Heterogeneous nuclear ribonucleoproteins A2/B1 452 37464 7 0,16 3,769

HNRNPC Heterogeneous nuclear ribonucleoproteins C1/C2 223 33707 2 0,24 1,52

HNRNPH1 Heterogeneous nuclear ribonucleoprotein H 269 49484 4 0,18 2,678

HNRNPH2 Heterogeneous nuclear ribonucleoprotein H2 293 49517 3 0,17 2,343

HNRNPK Heterogeneous nuclear ribonucleoprotein K 225 51230 4 0,31 3,12

HNRNPU Heterogeneous nuclear ribonucleoprotein U 114 91198 3 0,41 1,193

MATR3 Matrin-3 125 95078 2 0,37 1,661

NONO

Non-POU domain-containing octamer-binding protein 116 54311 2 0,20 1,072

PURA Transcriptional activator protein Pur-alpha 157 35003 2 0,41 2,617

SFRS3 Splicing factor, arginine/serine-rich 3 81 19546 2 0,35 1,529

SSBP1

Single-stranded DNA-binding protein, mitochondrial 92 17249 2 7,35 3,86

SEPT5 Septin-5 327 43206 11 0,52 5,659 ANXA2 Annexin A2 319 38808 5 0,46 6,797

SLC1A3 Excitatory amino acid transporter 1 307 59705 6 0,22 6,411

Gene Name Biological Process Molecular Class Molecular Function

PKP2 Cell adhesion Unclassified Molecular function unknown

BIN1 Cell communication & Signaling Adapter molecule

Receptor signaling complex scaffold activity

CADM1 Cell communication & Signaling Adhesion molecule Cell adhesion molecule activity

CALM1 Cell communication & Signaling Calcium binding protein Calcium ion binding

CDC42 Cell communication & Signaling GTPase GTPase activity

CSRP1 Cell communication & Signaling Adapter molecule


CTNNB1 Cell communication & Signaling Adhesion molecule Cell adhesion molecule activity

DPYSL2 Cell communication & Signaling Cytoskeletal associated protein

Cytoskeletal protein binding

PPP3CA Cell communication & Signaling Serine/threonine phosphatase

Protein serine/threonine phosphatase activity

PPP3R1 Cell communication & Signaling Regulatory/other subunit

Phosphatase regulator activity

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PRKAR2B Cell communication & Signaling Serine/threonine kinase

Protein serine/threonine kinase activity

SEPT7 Cell communication & Signaling Cell cycle control protein Protein binding

SH3GL2 Cell communication & Signaling Unclassified Molecular function unknown

SIRT2 Cell communication & Signaling Cell cycle control protein Deacetylase activity

SNCB Cell communication & Signaling Unclassified Molecular function unknown

YWHAE Cell communication & Signaling Adapter molecule


YWHAG Cell communication & Signaling Adapter molecule


YWHAQ Cell communication & Signaling Adapter molecule


SEPT2 Cell cycle GTPase GTPase activity CRMP1 Cell growth and/or maintenance Enzyme: Hydrolase Protein binding DYNLL1 Cell growth and/or maintenance Motor protein Motor activity

EPB41L3 Cell growth and/or maintenance Structural protein Structural molecule activity

FLNA Cell growth and/or maintenance Anchor protein Cytoskeletal anchoring activity

LMNA Cell growth and/or maintenance Structural protein Structural molecule activity

LMNB2 Cell growth and/or maintenance Structural protein Structural molecule activity

MAP1A Cell growth and/or maintenance Cytoskeletal associated protein


MAPRE2 Cell growth and/or maintenance Cytoskeletal associated protein


MYH9 Cell growth and/or maintenance Structural protein Structural molecule activity

VIM Cell growth and/or maintenance Cytoskeletal protein Structural constituent of cytoskeleton

LGALS1 Immune response Ligand Receptor binding

LDHA Metabolism ; Energy pathways Enzyme: Dehydrogenase Catalytic activity

COX4I1 Metabolism ; Energy pathways Enzyme: Oxidoreductase Oxidoreductase activity

COX5B Metabolism ; Energy pathways Enzyme: Oxidoreductase Oxidoreductase activity

GSTP1 Metabolism ; Energy pathways Enzyme: Glutathione transferase

Glutathione transferase activity

NDUFS8 Metabolism ; Energy pathways Enzyme: Oxidoreductase Oxidoreductase activity

PDE2A Metabolism ; Energy pathways Enzyme: Phosphodiesterase

Phosphoric diester hydrolase activity

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PDHA1 Metabolism ; Energy pathways Enzyme: Dehydrogenase Catalytic activity

PGK1 Metabolism ; Energy pathways Enzyme: Phosphotransferase Catalytic activity

PRDX1 Metabolism ; Energy pathways Enzyme: Peroxidase Peroxidase activity CANX Protein folding Chaperone Chaperone activity

HSPD1 Protein folding ; Apoptosis ; Regulation of immune response ; Signal transduction Heat shock protein

Heat shock protein activity

CALR Protein metabolism Chaperone Chaperone activity CCT4 Protein metabolism Chaperone Chaperone activity DNAJC5 Protein metabolism Chaperone Chaperone activity HSPA1A Protein metabolism Chaperone Chaperone activity

HSPA2 Protein metabolism Heat shock protein Heat shock protein activity



HSPE1 Protein metabolism Heat shock protein Heat shock protein activity

PSMA4 Protein metabolism Ubiquitin proteasome system protein

Ubiquitin-specific protease activity

SNCA Protein metabolism Chaperone Chaperone activity

EEF1A1 Regulation of cell cycle Transcription regulatory protein

Transcription regulator activity

H2AFV Regulation of gene expression, epigenetic DNA binding protein DNA binding

BASP1 Regulation of nucleobase, nucleoside, nucleotide and nucleic acid metabolism

Transcription regulatory protein


CAND1 Regulation of nucleobase, nucleoside, nucleotide and nucleic acid metabolism



H3F3A Regulation of nucleobase, nucleoside, nucleotide and nucleic acid metabolism DNA binding protein DNA binding

HIST1H1C Regulation of nucleobase, nucleoside, nucleotide and nucleic acid metabolism DNA binding protein DNA binding

HIST1H2AB Regulation of nucleobase, nucleoside, nucleotide and nucleic acid metabolism DNA binding protein DNA binding

HIST1H2AD Regulation of nucleobase, nucleoside, nucleotide and nucleic acid metabolism DNA binding protein DNA binding

HIST1H2BB Regulation of nucleobase, nucleoside, nucleotide and nucleic acid metabolism DNA binding protein DNA binding

HIST1H2BC Regulation of nucleobase, nucleoside, nucleotide and nucleic acid metabolism DNA binding protein DNA binding

HIST1H4A Regulation of nucleobase, nucleoside, nucleotide and nucleic acid metabolism DNA binding protein DNA binding

HNRNPA2B1 Regulation of nucleobase, nucleoside, nucleotide and nucleic acid metabolism Ribonucleoprotein

Transcription factor binding

HNRNPC Regulation of nucleobase, nucleoside, nucleotide and nucleic acid metabolism RNA binding protein RNA binding

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HNRNPH1 Regulation of nucleobase, nucleoside, nucleotide and nucleic acid metabolism Ribonucleoprotein Ribonucleoprotein

HNRNPH2 Regulation of nucleobase, nucleoside, nucleotide and nucleic acid metabolism Ribonucleoprotein RNA binding

HNRNPK Regulation of nucleobase, nucleoside, nucleotide and nucleic acid metabolism Ribonucleoprotein Ribonucleoprotein

HNRNPU Regulation of nucleobase, nucleoside, nucleotide and nucleic acid metabolism Ribonucleoprotein RNA binding

MATR3 Regulation of nucleobase, nucleoside, nucleotide and nucleic acid metabolism RNA binding protein RNA binding

NONO Regulation of nucleobase, nucleoside, nucleotide and nucleic acid metabolism RNA binding protein RNA binding

PURA Regulation of nucleobase, nucleoside, nucleotide and nucleic acid metabolism Transcription factor

Transcription factor activity

SFRS3 Regulation of nucleobase, nucleoside, nucleotide and nucleic acid metabolism RNA binding protein RNA binding

SSBP1 Regulation of nucleobase, nucleoside, nucleotide and nucleic acid metabolism DNA binding protein DNA binding

SEPT5 Signal transduction GTPase GTP binding

ANXA2 Signal transduction ; Cell communication Calcium binding protein Calcium ion binding

SLC1A3 Transport Transport/cargo protein Transporter activity

Table 3 - Proteins differentially expressed in schizophrenia corpus callosum (CC).

Gene name Protein name Score Mass N° Peptides SCZ/CTRL SD

ARF1 ADP-ribosylation factor 1 298 20741 7 4,26 5,333

BASP1 Brain acid soluble protein 1 766 22680 14 5,96 3,633

CALM1 Calmodulin 349 16827 7 2,63 1,817

CAMK2A

Calcium/calmodulin-dependent protein kinase type II subunit alpha 469 54566 10 3,08 8,707

CAMK2B

Calcium/calmodulin-dependent protein kinase type II subunit beta 180 73593 4 5,90 5,656

CAMK2G

Calcium/calmodulin-dependent protein kinase type II subunit gamma 195 63311 4 7,19 4,726

CDC42 Cell division control protein 42 homolog 85 21696 2 2,09 3,534

CFL1 Cofilin-1 192 18719 6 5,54 4,899

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Gene name Protein name Score Mass N° Peptides SCZ/CTRL SD

CSRP1 Cysteine and glycine-rich protein 1 458 21409 7 4,07 5,108

DPYSL2 Dihydropyrimidinase-related protein 2 1679 62711 25 7,07 5,889

H2AFV Histone H2A.V 422 13501 5 0,42 2,387 HIST1H1E Histone H1.4 513 21852 11 0,12 3,04

HIST1H3A Histone H3.1 353 15509 7 0,17 8,548

HIST1H4A Histone H4 979 11360 13 0,19 3,693

HMGB1 High mobility group protein B1 315 25049 3 0,01 5,9

HNRNPA2B1

Heterogeneous nuclear ribonucleoproteins A2/B1 325 37464 6 0,43 5,195

HNRNPR

Heterogeneous nuclear ribonucleoprotein R 106 71184 2 0,03 1,653

HNRNPU

Heterogeneous nuclear ribonucleoprotein U 373 91198 8 0,19 5,492

HP1BP3

Heterochromatin protein 1-binding protein 3 78 61454 2 3,40 5,984

HSPA1A Heat shock 70 kDa protein 1A/1B 310 70294 5 1,58 1,484

LMNA Prelamin-A/C 1140 74380 24 0,41 7,189 LMNB2 Lamin-B2 207 67762 2 0,05 2,067 NPM1 Nucleophosmin 172 32726 2 6,64 1,167 PTMA Prothymosin alpha 177 12196 3 10,62 2,334 S100B Protein S100-B 290 10820 3 0,30 1,203

Gene name Biological Process Molecular Class Molecular Function ARF1 Cell communication & Signaling GTPase GTPase activity

BASP1 Reg. nucleic acid metabolism Transcription regulatory protein Transcription regulator activity

CALM1 Cell communication & Signaling Calcium binding protein Calcium ion binding

CAMK2A Cell communication & Signaling Serine/threonine kinase Protein serine/threonine kinase activity

CAMK2B Cell communication & Signaling Serine/threonine kinase Protein serine/threonine kinase activity

CAMK2G Cell communication & Signaling Serine/threonine kinase Protein serine/threonine kinase activity

CDC42 Cell communication & Signaling GTPase GTPase activity

CFL1 Cell growth & maintenance Cytoskeletal associated protein Cytoskeletal protein binding

CSRP1 Cell communication & Signaling Adapter molecule Receptor signaling complex scaffold activity

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Gene name Biological Process Molecular Class Molecular Function

DPYSL2 Cell communication & Signaling Cytoskeletal associated protein Cytoskeletal protein binding

H2AFV Reg. nucleic acid metabolism DNA binding protein DNA binding HIST1H1E Reg. nucleic acid metabolism DNA binding protein DNA binding HIST1H3A Reg. nucleic acid metabolism DNA binding protein DNA binding HIST1H4A Reg. nucleic acid metabolism DNA binding protein DNA binding HMGB1 Reg. nucleic acid metabolism DNA binding protein DNA binding HNRNPA2B1 Reg. nucleic acid metabolism Ribonucleoprotein Transcription factor binding HNRNPR Reg. nucleic acid metabolism RNA binding protein RNA binding HNRNPU Reg. nucleic acid metabolism Ribonucleoprotein RNA binding HP1BP3 Reg. nucleic acid metabolism DNA binding protein DNA binding HSPA1A Protein metabolism Chaperone Chaperone activity LMNA Cell growth & maintenance Structural protein Structural molecule activity LMNB2 Cell growth & maintenance Structural protein Structural molecule activity NPM1 Protein metabolism Chaperone Chaperone activity PTMA Cell growth & maintenance Unclassified Molecular function unknown S100B Cell communication & Signaling Calcium binding protein Calcium ion binding

The differentially expressed proteins related to both the nuclei of the ATL region

cells and the CC participated in biological processes related mainly to processes such as

regulation of nucleobase, nucleoside, nucleotide and nucleic acid metabolism (27% ATL, 40%

CC) and cell communication and signaling (23% ATL, 36%CC) (Figure 1). These processes

are related to the main functions of the nucleus, such as gene expression, transcriptional control,

splicing and release of gene products [10].

Figure 1 - Biological processes related to the anterior temporal lobe (ATL) and corpus callosum (CC) differentially expressed proteins.

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5.3.1 Proteomic similarities between regions

The ATL is enriched in gray matter while the cerebral region of the CC corresponds

to the largest portion of white matter in the brain. This results from the preponderance of

neurons in the ATL [18] whereas glial cells and neuronal axons are more predominant in the

CC [19]. It is important to compare proteomic profiles of these two regions of the brain mainly

because this gives a more integrated view of brain function and not only what happens only

with the neurons, as is typical of most other brain proteomic studies. In the comparison of these

two regions, 64 of these were specific to the ATL, 13 to the CC and 12 were common to both

regions, i.e. 13.5% of the proteins are shared for the regions, as it can be seen in the Venn

diagram (figure 2). According to analysis carried out using the Reactome software, these latter

proteins were related to cellular stress response, with a chain of reactions related to heat-shock

proteins (HSPs) (p-value- 3.18E-11) (Figure 3). This type of reaction is triggered by cellular

stressors such as exposure to high temperatures, hypoxia and free radicals, and these factors

can cause damage to cellular proteins and induce this type of response [20–23].

Figure 2 - Venn diagram comparison between differentially expressed proteins in anterior temporal lobe (ATL) and corpus callosum (CC).

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Figure 3 - Analysis of the Reactome of HSF1 proteins differentially expressed found deregulated in both regions by Reactome.

Since maintaining homeostasis is important for the proper functioning of cellular

metabolism, this type of stress response must be effective and coordinated [24]. For this to

occurn, the main molecule responsible for transcription-mediated stress response, the heat

shock transcription factor HSF1, must be present at optimal functional levels [25, 26]. Under

normal physiological conditions, this molecule is present in its inactive form, mediated by a

series of protein-protein interactions. However, in the presence of stressors, this molecule

becomes actived by a series of reactions, including its phosphorylation and interaction with

DNA, promoting the cellular responses to stress (Figure 3) [27–32].

The protein that mediates most of these reactions, the heat shock 70 kDa protein

1A/1B (HSPA1A), was found to be increased in the nuclear compartments of both the ATL and

CC. This protein belongs to the family of heat shock protein 70 (HSP70), which has been

implicated previously in schizophrenia [33]. A recent study showed that a polymorphism in the

HSPA1A protein gene is associated with increased risk of developing paranoid schizophrenia

[34], and another study found increased mRNA expression of this gene in postmortem samples

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from the prefrontal cortex of patients with schizophrenia [35]. The analysis of differentially

expressed proteins in the ATL nuclei showed additional changes in 4 more heat shock proteins,

with 3 of these belonging to the HSP70 family (heat shock-related 70 kDa protein 2 [HSPA2],

heat shock 70 kDa protein 6 [HSPA6], heat shock cognate 71 kDa protein [HSPA8] and 10 kDa

heat shock protein [HSPE1]). All these proteins were found at higher levels in the patients

compared to controls, indicating a large response to cellular stress in the former. There is a

debate about the effects displayed in the analysis of postmortem brains in studies of psychiatric

disorders. One of the main disputed points is whether or not such effects are a cause or

consequence of the disease, or a consequence of prolonged treatment of these patients with

different antipsychotic medications throughout their lives and through different stages of

disease development. However, such data have appeared recurrently in proteomic data of

postmortem brain of patients with schizophrenia and cannot be ignored. Nevertheless,

corroborative studies of some format involving first onset antipsychotic naïve patients may help

to resolve some of these issues.

5.3.2 Nuclear proteins altered in the ATL

In silico analysis of the proteins found at different levels in cell nuclei of the gray

matter region, showed that these proteins are mainly associated with spliceosome complex (p-

value 5.9 E-6; String) (Supplementary Table 1). The spliceosome is a complex of five multi-

megadalton ribonucleoproteins (snRNPs), which are abundant RNA-binding proteins that carry

out processing of pre-mRNA transcripts. This complex removes introns of these molecules and

rearranges exons so that these conform and can give rise to the correctly configured mRNA

transcripts [36]. Due to the exon rearrangement, a single pre-mRNA can give rise to different

functioning mRNAs and any perturbations of this process may lead to disease development or

contribute to the severity of preexisting diseases [37].

The proteins related to this pathway that were found at altered levels in this study

were heterogeneous nuclear ribonucleoproteins C1/C2 (HNRNPC), heterogeneous nuclear

ribonucleoprotein K (HNRNPK), heterogeneous nuclear ribonucleoprotein U (HNRNPU),

splicing factor, arginine/serine-rich 3 (SRSF3) and HSPA1A, HSPA2, HSPA6 and HSPA8, as

described above. These proteins are the main constituents of the snRNP complex, which is the

main component of the splicing operation (Figure 4; KEGG).

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Eight of the proteins belonging to the hnRNP family were found deregulated in a

study of oligodendrocyte cells treated with clozapine, an antipsychotic used in the treatment of

schizophrenia [38]. Moreover, studies of silencing and super-expression of proteins showed a

crucial role of hnRNP proteins in the myelination of neurons by oligodendrocytes,

independently of the indirect regulation of quaking proteins as previously proposed [39, 40].

This dysfunction in myelination was related to dysregulation of the synaptic connection [17,

41, 42]., One of these proteins was HNRNPC, which was found at decreased levels in SCZ

patients compared to controls in this study. It is known that the regulation process of

myelination undergoes a precise control dependent on the alternative splicing [39] and if the

hnRNP protein complex is deregulated, this may cause aberrant alternative splicing as reported

in neurodegenerative and neuropsychiatric diseases such as frontotemporal dementia with

Parkinsonism, amyotrophic lateral sclerosis and schizophrenia [43–45].

Figure 4 - Sliceosome of anterior temporal lobe (ATL) showing differentially expressed proteins according to program String.

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The deregulation of hnRNP proteins, in addition to being related to oligodendrocyte

cells, are also related to dysfunction of the neurotransmitter system. In a study performed using

polymerase chain reaction (PCR) analysis of schizophrenia prefrontal cortex tissue, alterations

in splicing of mRNA molecules related to the Gabaergic system were found [44]. Another study

has shown that proteins related to dopamine receptors are also regulated by alternative splicing

and that perturbed splicing of these proteins can cause dysfunctions in the dopaminergic system

[46]. These systems are known to be altered in patients with schizophrenia [47]. Thus far, there

are only a few recent studies that correlate perturbations in splicing and schizophrenia.

However, the coverging evidence suggests that this could play a major role in the disease

process and therefore warrants further study, particularly accounting for effects on both

neuronal and oligodendrocyte cells.

3.3 Nuclear proteins of white matter (CC)

After enriching the pathways of the 24 proteins found differentially expressed in

the nucleus of the CC region, only 4 proteins were present in all of the enriched pathways

(Supplementary Table 2) and were present in the same interaction network (Figure 5). These

four proteins were calmodulin (CALM1), calcium/calmodulin-dependent protein kinase type II

subunit alpha (CAMK2A), calcium/calmodulin-dependent protein kinase type II subunit beta

(CAMK2B), and calcium/calmodulin-dependent protein kinase type II subunit gamma

(CAMK2G) which are all calcium dependent for their activation and response, as well as being

constituents of the serine/threonine protein kinase family, which has been widely associated

with metabolic events such as muscle contraction, cellular metabolism/proliferation, gene

expression and neurotransmitter release (reviewed in Naz, 2016 [48]).

The correlation between deregulation of calcium and schizophrenia began in the

1970s [49] and several studies confirming and discussing various aspects of this correlation

have been performed. Among the many hypotheses that correlate calcium signaling to

schizophrenia, there is the deregulation of the dopaminergic system, which is one of the

hypotheses of SCZ development of the disease [50]. Calcium participates in the uptake of

dopamine by synaptic vesicles and, in this process, calcium is associated with CaMKII proteins

[27]. In this study, we found increased levels of the alpha, beta and gamma CAMK2 proteins,

suggesting that there may be a high uptake of dopamine by synaptic vesicles and, consequently,

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a greater release of the neurotransmitter in the synaptic cleft [47]. The major focus in most

studies in schizophrenia has been on the proteins of neuronal cells, as can be seen in the results

presented above. However, one study quantified the calmodulin proteins in nuclei of neuronal

and glial cells and showed that the abundance of these molecules is greater in the latter cell type

[51]. Even so, little research has been done investigating the role of the deregulation of

calmodulin proteins in glial cells.

Figure 5 - Network deregulated related to differentially expressed proteins in corpus callosum (CC) by String.

A few recent studies have associated calcium/calmodulin-dependent protein with

glial cells in functions such as actin cytoskeleton remodeling, glutamate and glycine transport

and regulation of neurotrophic factors [52–55]. This involves the activation of the PI3K protein

which, according to Pérez-Garcia et al. [55], is regulated by calmodulin proteins associated with

calcium. The process of activation of the PI3K protein involve its auto phosphorylation, which

was found to be reduced in a recent study of postmortem CC from patients with schizophrenia

performed by our group [56]. Given that neurotrophic factors are decreased in patients [57], we

can associate the increased amount of CAMK found in this study to a form of cellular

compensation which aims to normalize the activation of the neurotrophic factors. Another

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possible association is that the high concentration of CaMK proteins may desensitize the P13K

activation process, causing the observed disruption in this pathway.

Also, present in the network identified above, is the nucleic acid metabolism related

proteins, which are proteins of the heat-shock proteins family, and proteins linked to the genetic

transcription, which belong to the family of hnRNPs. These results are related to those found

in the ATL region, showing a possible relationship between the deregulation of the white and

gray matter, with changes in cell stress and regulation of genetic expression.

5.4 Conclusion

The results found in this study provide an overview of the participation of nuclear

proteins in the pathophysiology of the disease. When it comes to the gray matter, the results

point to the dysregulation of the sliceosome, an area which has not been investigated previously.

In the case of the white matter, the role of calcium/calmodulin protein deregulation in glial cells

has only been partly explored in previous studies, and may be related to altered production of

neurotrophic factors. These results represent the first in depth study comparing effects on gray

and white matter in schizophrenia and lay the groundwork for further studies in this area to help

increase our understanding of this complex disease. This could lead to identification of novel

biomarkers and drug targets which, in turn, may result in development of newer and better

treatment options for people suffering from this disease for improved therapeutic outcomes.

Acknowledgements

Verônica M. Saia-Cereda and Prof. Daniel Martins-de-Souza are funded by FAPESP (São

Paulo Research Foundation), grants 2016/07332-7 and 13/08711-3.

Conflict of Interest

Authors declare no conflict of interest.

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6. CAPÍTULO 2

Capítulo aceito para publicação no Neuromethods (Springer)

Nuclear proteomics for exploring MK-801 treated oligodendrocytes to better understand schizophrenia

Aline G. Santana1, Giuliana S. Zuccoli1, Verônica Saia-Cereda1, Juliana S. Cassoli1, Daniel Martins-de-Souza1,2

1 Department of Biochemistry and Tissue Biology, Institute of Biology, University of Campinas (UNICAMP) 2 UNICAMP´s Neurobiology Center, Campinas, SP, Brazil.

Abstract

Proteomics is currently one of the main techniques used to understand the

biochemical mechanisms inherent to physiological and pathological processes, especially those

with a multifactorial characteristic such as schizophrenia. The main tool used in proteomics is

mass spectrometry (MS), given its high sensitivity and preciseness. Despite their qualities, MS

presents limitations as the coverage of samples highly complex in terms of proteome such as

brain cells, including oligodendrocytes, which have been largely involved in the pathogenesis

of neurodegenerative and psychiatric disorders. One strategy to overcome this is sample

fractionation in subproteomes. In the case of cellular extracts, the separation of organelles

presents great advantages, since in addition to simplifying the sample, directs the analysis of a

specific set of proteins. This work focuses on nuclear enrichment to perform proteomic analysis

of nuclear proteins extracted from an in vitro pharmacological model of schizophrenia.

Key words: Oligodendrocytes, schizophrenia, subproteome and nucleus.

6. 1. Introduction

Oligodendrocytes (OLDs) are neuroglia cells that, along with axons and astrocytes,

constitute the white matter, which is responsible for cerebral connectivity (Graça 1988). OLDs

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correspond to 51% of the cells that surround neurons (Polak et al., 1982) and can be

distinguished by their characteristic nuclear morphology. They are essential for the survival and

functioning of neurons, since they are involved in trophic signaling, synthesis of growth factors,

myelinization of axons and formation of the myelin sheath of neurons (Du & Dreyfus, 2002;

Martins-de-Souza, 2010). Studies have associated dysfunctions in OLDs to neurological

disorders, such as multiple sclerosis, and psychiatric disorders such as schizophrenia

(schizophrenia) (Vostrikov & Uranova, 2011; Cassoli et al., 2015).

Schizophrenia is a severe, debilitating, incurable, and highly complex mental

disorder that affects approximately 1% of the world's population (Kahn et al. 2015). The disease

manifests itself between late adolescence and early adulthood, affecting the central nervous

system and leading to numerous neuropsychic changes. Due to the central nervous system’s

inaccessibility, one of the main challenges of studying the mechanisms of schizophrenia is the

acquisition of samples from individuals affected by the disease. An alternative that has been

widely chosen is the use of models that mimic some aspects of the disease, such as the treatment

of animals and cells with MK-801 (NMDA receptor inhibitor). Despite current efforts to

improve the better understanding of schizophrenia, little is still known about the biochemical

pathways involved and, consequently, there are no molecular diagnoses and just a few specific

treatments for the disease., In order to overcome this situation, studies aiming the

comprehension of the molecular basis of schizophrenia have become of great interest, with

proteomics studies contributing strongly in this scenario.

Proteomics is currently one of the main tools for understanding biochemical

pathways and, consequently, multifactorial disorders, such as schizophrenia (Martins-de-

Souza, 2012). Over the last two decades, a substantial number of works involving this disorder

and proteomics studies have been published (Nascimento & Martins-de-Souza, 2015). Among

the results obtained through this technique on postmortem brain samples of patients with

schizophrenia it was possible to observe changes in pathways related to neuronal transmission

and synaptic function, energy metabolism, calcium homeostasis, cytoskeleton, immune system

and inflammation, and oxidative stress, which corroborates the multifactorial characteristic of

the disease. These results are of extreme value, since the identification of differentially

expressed proteins may be important in finding biomarkers that could aid in the diagnosis and/or

prognosis of a particular disorder (Blonder et. al., 2011). However, it is important to note that

in complex disorders, such as schizophrenia, there are often significant changes in numerous

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components that are not detected by mass spectrometry (MS). Despite the high sensitivity of

the technique, if the sample is very complex and/or present some proteins in high

concentrations, the signals referring to the components present in very low concentrations may

not be detected or be mixed with the noise. To circumvent this problem, the study of sub-

proteomes emerges as a satisfactory alternative.

It may seem that cellular protein content is not as complex as other types of samples,

but in reality, the total number of gene products in any cell is estimated at approximately 10.000

and this number is probably underestimated by about 10 orders of magnitude when we speak

of proteins, due to splicing variants and the wide variety of post-translational modifications that

may occur inside the cell. Thus, it becomes clear that low abundance proteins, such as signaling

proteins and transcription factors, may be masked by proteins that are in a higher concentration

(Huber, 2003). Therefore, a simple proteomic approach may often not reflect the totality of the

existing protein dynamics.

There is more than one way to fractionate the cellular content and reduce sample

complexity. In some cases, the separation of organelles is the best alternative because, in

addition to reducing the complexity of the sample, it still acts in the sense of enriching the

sample, directing to the analysis of specific proteins (Taylor et. al., 2003). This work focuses

on obtaining nuclear proteins from oligodendrocytes, making it essential to separate the

organelle.

It is important to mention that the study of nuclear proteins in schizophrenia is of

extreme value, since in addition to very few studies linking the nuclear proteome to the disease,

nuclear proteins correspond to 10-20% of the total cellular proteins and perform important

functions regarding proper cellular functioning, such as the control of gene expression (Narula

et. al., 2013). Thus, the characterization of the nuclear proteome is of extreme importance for

the understanding of any physiological or pathological process inherent to schizophrenia.

6.2 Recipies

- Culture medium: Dulbecco’s Modified Eagle’s Medium (DMEM) high glucose

supplemented with 10% fetal bovine serum (FBS), 0.5% glutamine and 1% penicillin-

streptomycin (5,000 U/mL)

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- Freezing medium: 60% culture medium, 30% FBS supplemented with 10% sterile dimethyl

sulfoxide (DMSO)

- Osmotic buffer: 10 mM NaCl, 1.5 mM MgCl2, 10 mM Tris-HCl (pH 7.5)

- Homogenization buffer (1x): 210 mM Mannitol, 70 mM Sucrose, 5 mM Tris-HCl, 1 mM

EDTA (pH 7.5)

- Homogenization buffer (2.5x): 525 mM Mannitol, 175 mM Sucrose, 12.5 mM Tris-HCl, 2.5

mM EDTA (pH 7.5)

- Lysis and reduction buffer: 6 M urea, 2 M thiourea, 10 mM dithiothreitol, 0.1 mM sodium

pervanadate and protease inhibitor (cOmplete ULTRA Roche).

- Alkylation solution: 200 mM iodoacetamide in 20mM TEAB.

- Digestion solution: 2% trypsin.

- Stop digestion solution: 100% Formic acid.

6.3 Materials (See Note 1)

6.3.1 Cell culture

• Human Oligodendroglia Cell Line MO3.13 (Cedarlane, cat. no. CLU301) • Culture medium • Trypsin/EDTA solution 0.25% • Flask Nunclon Delta-treated Vent/Close T75 • Pipette tips, 100–1,000 μL

• Serological pipet 25 mL • Conical centrifuge tube 15 mL • Water bath • Laminar Flow Cabinet

• CO2 incubator • Bench centrifuge with mobile angle rotor for 15 mL tubes

6.3.2 Freezing

• Freezing medium • Pipette tips 100–1,000 μL • Cryogenic vials • Laminar Flow Cabinet • Bench centrifuge with mobile angle rotor for 15 mL tubes

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6.3.3. Cell treatment

• 5-10 M MK-801 hydrogen maleate solution (Sigma) (See note 2) • Pipette tips, 20–200 μL • Laminar Flow Cabinet • CO2 incubator

6.3.4 Collecting the cells • Sterile phosphate buffered saline 0.1 M (PBS) (See note 3) • Cell Scraper • Conical centrifuge tube 15 mL • Conical centrifuge tube 50 mL • Pipette tips, 100–1,000 μL • Serological pipet 5 mL • Syringe filter unit, 0.22μm polyethersulfone (PES) membrane • Syringe 10 mL • Laminar Flow Cabinet • Bench centrifuge with mobile angle rotor for 15 mL tubes

6.3.5 Nuclei separation

• Osmotic buffer • Homogenization buffer (1x) • Homogenization buffer (2.5x) • Conical centrifuge tube 15 mL • Pipette tips, 100–1,000 μL • Dounce tissue grinder 5-10 mL • Bench centrifuge with fixed angle rotor for 15 mL tubes

6.3.6 Lysis, reduction, alkylation, and protein digestion

• Lysis and reduction buffer • Triethylammonium bicarbonate buffer (TEAB) 20 mM • Alkylation solution • Digestion solution • Stop digestion solution • Qubit® Protein Assay Kit • Qubit® Assay Tubes • Pipette tips 100–1,000 μL • Ultrasonic Homogenizer • Vortex Genie 2 • Thermoblock • Qubit® 3.0 Fluorometer

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6.4 Methods

6.4.1 Cell culture (See note 4)

1. Take from liquid nitrogen a cryogenic vial containing approximately 5 x 106 MO3.13 cells

and thaw in a water bath at 37ºC (See note 5).

2. Transfer the cells to a conical centrifuge tube of 15 mL containing 10 mL of culture medium.

3. Centrifuge at 250 g for 5 minutes.

4. Discard the supernatant and resuspend the cell pellet in 2 mL of culture medium.

5. Distribute cell suspension equally in four T75 flaks containing 25 mL of culture medium

(See note 6)

6. Keep the cells in proper incubator at 37ºC and 5% CO2 and split the cells after 3 days of

growth.

7. Remove culture medium from the flasks and wash them gently with 4 mL of culture medium

without FBS.

8. Discard the medium and add 2 mL of trypsin / EDTA to each flask and incubate the cells for

3 min at 37oC.

9. Add 5 mL of culture medium containing FBS, and transfer the content to a 15 mL conical

centrifuge tube.

10. Wash the flasks with 4 mL of culture medium and transfer to the same tube.

11. Centrifuge at 250 g for 5 minutes.

12. Discard the supernatant and resuspend cell pellet from one tube in 3 mL of culture

medium.

13. Distribute the resuspension in 6 new T75 flasks containing 25 ml of culture medium, keep

the flasks in proper cell incubator at 37ºC and 5% CO2 until reach 100% confluence.

6.4.2 Freezing

1. Resuspend cell pellets from other 3 tubes in 2 mL of freezing medium and divide equally

the content in 6 cryotubes (See note 7)

2. Store the cryotubes at -20 ° C for 2 hours, then transfer them to -80 ° C for 12-16 hours and

finally in liquid nitrogen.

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6.4.3 Cell treatment (See note 8)

1. Acute treatment: after the cells reached 90% confluency, change culture medium to a new

one containing 50 μM MK-801 and incubate at 37ºC and 5% CO2. Collect the cells after 8h.

2. Chronic treatment: after the cells reached 70% confluency, change culture medium to a new

one containing 10 μM MK-801 and incubate at 37ºC and 5% CO2. Refresh the medium

containing 10 μM MK-801 every 24 hours of incubation. Collect the cells after 72h.

6.4.4 Collecting the cells

1. Remove culture medium from flasks leaving around 2mL and store them at 4ºC.

2. Harvest cells by scraping them off the flask and collect the cells in centrifuge tube 15 mL.

3. Wash the flasks with 5 mL of stored medium and put the content in the same centrifuge tube.

4. Centrifuge at 250 g for 5 minutes and discard the supernatant.

5. Wash cell pellet using 1 mL PBS and centrifuge at 250 g for 5 minutes.

6. Proceed with nuclei separation or store the cells at -80ºC until further analyses.

6.4.5 Nuclei separation (See note 9)

1. Add 5 mL osmotic buffer to the cell pellet (≈ 3 x 107 cells). Homogenize and leave the cells

to swell for 10 min.

2. Transfer the content to a dounce tissue grinder and perform controlled strokes during 3-4

min.

3. Transfer the lysate back to the centrifuge tube 15 mL.

4. Wash the homogenizer with 3.6 mL homogenisation buffer 2.5 x and add the content to the

same centrifuge tube 15 mL.

5. Complete the volume to 13 mL using homogenisation buffer 1 x and centrifuge at 2100 g for

7 min 4ºC.

6. Transfer the supernatant to a new conical centrifuge tube of 15 mL (See note 10) and save

the pellet containing the nuclei.

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7. Proceed with lysis and protein digestion or store the pellet at -80ºC until further analyses.

6.4.6 Lysis, Reduction, Alkylation and Protein Digestion

1. Add 200 μL lysis buffer to the nuclei pellet. Vortex well and incubate for 2 h at 37oC.

2. Dilute the sample ten times with 20 mM TEAB, pH 7.5 and sonicate on ice.

3. Take an 10 μL aliquot and perform the protein quantification using Qubit System.

4. Add 200 μL of 200 mM iodoacetamide in 20 mM TEAB and incubate the sample for 20 min

in the dark at room temperature (RT).

5. After incubation, digest the sample using trypsin (enzyme to substrate ratio 1:100) overnight

(12–16 h) at 37ºC.

6. Add 100 % Formic Acid to a final concentration of 5% to stop the reaction and leave for 5 min at RT.

7. Centrifuge for 30 min at 14,000 g in order to pellet lipids and save the supernatant containing

peptides from nuclear proteins. Store them at -20oC until further analyzes.

6.5 Notes

1. All solutions used in this protocol must be prepared with high purity chemical reagents and

sterile ultra pure water. When sterile reagents are not available, the solutions must be filtered

using a 0.22 μm polyethersulfone (PES) membrane. Heat sterilization processes are not

recommended. Organic solutions can undergo rapid reduction-oxidation processes prior to

perform this protocol.

2. MK-801 solution can be prepared using ultra pure water to a final concentration between 5-

10 M and its aliquots should be stored at -20ºC.

3. It is recommended to sterilize the solution using syringe filter units with 0.22 μm PES

membrane.

4. All procedures are made in order to maintain complete sterility and whenever possible using

a laminar flow cabinet. The cell media should be at 37ºC prior to use.

5. This step should be done quickly because DMSO is toxic to cells.

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6. It is suggested to shake gently the flasks to ensure the cell distribution will cover the proper

space of the flasks.

7. This step should be done as quick as possible to minimize cell death caused by DMSO from

freezing medium.

8. Treatments were performed in two stages: acute (8 hours) and chronic (72 hours) with three

biological replicates in each condition. Control group are the cells that growth in the same

condition as treated group, without addition of MK-801. Concentrations of MK-801 were

based on those of previous studies (Kondziella et al., 2006, Paulson et al., 2004, Paulson et

al., 2007).

8. All buffers should be ice-cold before use.

9. The supernatant may go through another centrifugation step in order to separate the

mitochondrial fraction.

6.6 References

1. Blonder J et al (2011) Proteomic biomarker discovery: it's more than just mass spectrometry. Electrophoresis 32 (13):1541-1548 2. Cassoli JS et al (2015) Distrbed macro-connectivity in schizophrenia linked to oligodendrocyte dysfunction: from structural findings to molecules. npj Schizophrenia, a:15034, doi: 10.1038/npjschz.2015.34. 3. Cassoli JS et al (2016). Effect of MK-801 and clozapine on the proteome of cultured human oligodendrocytes. Front. Cell. Neurosci 10 (52):1-14 4. Du Y, Dreyfus CF (2002) Oligodendrocytes as Providers of Growth Factors. Journal of Neuroscience Research 68:647–654 5. Graça DL (1988) Mielinização, desmielinização e remielinização no sistema nervoso central. ArqNeuro-Psiquiat 46 (3): 292-297 6. Guest PC et al (2015) MK-801 treatment affects glycolysis in oligodendrocytes more than in astrocytes and neuronal cells: insights for schizophrenia. Front. Cell. Neurosci 9 (180): 1–10 7. Huber LA (2003) Is proteomics heading in the wrong direction? Nature Reviews: Mol Cell Biol London 4: 74–80 8. Kahn SR et al (2015) Schizophrenia Nat Rev Dis Primers aa: 15069 9. Kondziella D et al (2006) Glial-neuronal interactions are impaired in the schizophrenia model of repeated MK801 exposure. Neuropsychopharmacol 31 (9): 1880–1887 10. Martins-de-souza D (2012) Proteomics Tackling Schizophrenia as a Pathway Disorder. Schizophr Bull

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11. Martins-de-souza D (2010) Proteome and transcriptome analysis suggests oligodendrocyte dysfunction in schizophrenia. Journal of Psychiatric Research 44:149–156 12. Narula K et al (2013) Comparative analyses of nuclear proteome: extending its function. Front Plant Sci 4: 100 13. Nascimento JM & Martins-de-Souza D (2015) The proteome of schizophrenia Nature, 14003: 1-11 14. Paulson L et al (2004) Comparative proteome\ analysis of thalamus in MK-801-treated rats Proteomics 4 (3): 819–825 15. Paulson L et al (2007) Proteome analysis after co-administration of clozapine or haloperidol to MK-801-treated rats. J Neural Transm 114 (7): 885–891 16. Polak M et al (1982) Neuroglia and their reactions. In: Haymaker W, Adams RD, editors, Histology and histopathology of the nervous system. Springfield: Charles C. Thomas 17. Taylor sw et al (2003) Global organellar proteomics. Trends in Biotechnol 21: 82–88

18. Vostrikov V & Uranova N (2011) Age-Related Increase in the Number of Oligodendrocytes Is Dysregulated in Schizophrenia and Mood Disorders. Schizophr Res Treatment 2011: 1-10

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7. CAPÍTULO 3

ANÁLISES DO PROTEOMA NUCLEAR DA LINHAGEM MO3.13 TRATADA COM

MK-801

7.1 Introdução

Os oligodendrócitos (OLDs) são as células responsáveis pelo envolvimento dos

axônios no sistema nervoso central (SNC), permitindo a condução rápida e saltatória do impulso

nervoso e provendo suporte metabólico aos neurônios (Funfschilling et al., 2012, Saab et al.,

2016, Ono & Ikenaka, 2012). A gênese e maturação dessas células são processos essenciais

para mielinização e desenvolvimento do SNC. Os oligodendrócitos são gerados na zona

germinal a partir de seus precursores (OPCs) migratórios e, ao longo do seu desenvolvimento,

expressam marcadores de superfície celular que regulam sua proliferação, migração,

diferenciação e sobrevivência (Ono & Ikenaka, 2012).

Com o intuito de se estudar essas células e suas funções, muitos métodos de

extração de OPCs de tecidos cerebrais tem sido descritos (O'Meara et al., 2011, Emery et al.,

2013). Esses métodos quase sempre requerem tempo elevado de cultura celular e demandam

diversos reagentes e equipamentos, apesar de serem bem sucedidos. Devido à dificuldade de

obtenção de OPCs e proliferação limitada dos oligodendrócitos em cultura, pesquisadores

desenvolveram uma linhagem celular de oligodendrócitos, chamada MO3.13 para contornar

tais limitações.

As células MO3.13 apresentam características fenotípicas de oligodendrócitos

primários (McLaurin et al., 1995). Tais células foram criadas através da hibridização de

oligodendrócitos humanos maduros com células mutantes de rabdomiossarcoma humano

resistentes à 6-tioguanina (McLaurin et al., 1995). Em contraste com as células tumorais

precursoras, e corroborando sua similaridade aos oligodendrócitos, a linhagem MO3.13

apresenta imunorreatividade superficial para galactosilcerebrosideos (GS) e intracelular para

proteína básica de mielina (MBP), proteína proteolipídica (PLP), proteína ácida fibrilar glial

(GFAP). Outros trabalhos também relatam a presença de imunomarcadores de oligodendrócitos

imaturos como a galactosilceramidase (GalC) e a 2',3'-nucleotídeo cíclico 3'-fosfodiesterase

(CNPase) (CEDARLANE CELLutions BIOSYSTEMS, 2017). Devido às suas características,

a linhagem MO3.13 é bastante utilizada em estudos que buscam analisar alterações em

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oligodendrócitos, como é caso deste trabalho, onde buscamos avaliar alterações na expressão

de proteínas nucleares de oligodendrócitos tratados com a droga MK-801 (ou dizocilpina).

O MK-801 é um composto análogo à fenciclidina (PCP), que atua como antagonista

não competitivo do receptor de glutamato N-metil-D-aspartato (NMDA) no SNC (Homayoun

& Moghaddam, 2007; Kovacic & Somanathan, 2010; Saletti et al., 2015; Cassoli et al., 2016b).

O MK-801 antagoniza o receptor NMDA através da ligação à dois sítios de ligação, os mesmos

do PCP, impedindo a passagem dos íons Ca2+ através do canal. Estudos mostram que a

administração de MK-801 em animais induz mudanças comportamentais, tais como ataxia,

estereotipias, hiperlocomoção, diminuição da consciência e perda de capacidade de responder

à estímulos auditivos e luminosos (Javitt & Zukin, 1991; Bickel & Javitt, 2009; Kovacic &

Somanathan, 2010; Yu et al., 2011), sendo que essas características são muito semelhantes aos

sintomas observados em pacientes com SCZ (Yu et al., 2011). Assim, a administração de MK-

801 em animais de experimentação consiste em um dos modelos farmacológicos para o estudo

SCZ.

Além do uso em animais, o MK-801 vem sendo utilizando no tratamento de culturas

celulares como neurônios, astrócitos e oligodendrócitos (Martins-de-Souza et al., 2011, Guest

et al., 2015) Segundo Cassoli e col. (2016b), o tratamento com MK-801 também leva à

alterações no perfil proteico de oligodendrócitos humanos que foram semelhantes às alterações

observadas em pacientes com SCZ. Ademais, algumas dessas alterações foram revertidas pela

clozapina (um dos antipsicóticos mais utilizados no tratamento da SCZ).

O propósito dessa parte do trabalho foi analisar o proteoma nuclear de

oligodendrócitos tratados com MK-801, buscando por alterações no perfil proteico similares às

alterações descritas em tecido cerebral coletados post-mortem de pacientes com SCZ, relatadas

no capítulo 1.

7.2 Materiais e Métodos

7.2.1 Cultura celular e tratamento com MK801

Células MO3.13 (Cedarlane, cat. no. CLU301) foram cultivadas em meio DMEM

high glicose (Life/Thermo) suplementado com 2 mM de L-glutamina, 1% de

penicilina/estreptomicina (SigmaAldrich, St. Louis, MO, EUA) e 10% de soro fetal bovino

(FBS) (Life Technologies, Darmstadt, Alemanha), e mantidas em incubadora apropriada à 37

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°C e em atmosfera humidificada contendo 5% de CO2. As células foram crescidas e

transferidas, quando atingiam a confluência, até a 8a passagem. Para o congelamento as células

foram coletadas utilizando 2 mL da solução de tripsina/EDTA e diluídas em 6 mL DMEM

suplementado com 10% de FBS. As células foram centrifugadas em centrífuga de ângulo móvel

à 250 g por 5 minutos e o sobrenadante foi descartado. Cada pellet foi ressuspendido em 2 mL

de meio de congelamento (60% de DEMEM high glicose suplementado, 30% FBS e 10% de

dimetil sulfóxido). Finalmente, as células foram congeladas gradativamente e posteriormente

armazenadas em nitrogênio líquido.

Após obter uma biblioteca de células, foi realizado o tratamento das células

MO3.13 usando o MK-801. Para o tratamento agudo, 50 μM de MK-801 (concentração final)

foi adicionado às células e as mesmas foram mantidas por 8 horas na presença do MK-801.

Para o tratamento crônico, 10 μM de MK-801 (concentração final) a cada 24h durante 72h. O

grupo controle foi submetido aos mesmos procedimentos, todavia não foi adicionado o MK-

801.

Após os tratamentos, as células foram removidas com ajuda de um scraper,

centrifugadas à 250 g por 5 minutos, lavadas com PBS e centrifugadas novamente. Os pellets

foram armazenados à -80ºC para a etapa de enriquecimento nuclear.

7.2.2 Enriquecimento nuclear e extração do proteoma

Para realizar o procedimento de enriquecimento nuclear, foi adicionado ao pellet

congelado 5 mL de tampão osmótico (10 mM NaCl, 1.5 mM MgCl2, 10 mM Tris-HCl (pH

7.5)). Após 10 minutos de repouso o conteúdo celular foi lisado em um homogeinizador de

tecidos manual. O lisado foi transferido para um tubo de centrífuga, e o homogeinizador foi

lavado com 3.6 mL de tampão de homogeinização 2.5x (525 mM de manitol, 175 mM de

sacarose, 12.5 mM de Tris-HCl, 2.5 mM de EDTA (pH 7.5)), sendo que o conteúdo da lavagem

também foi adicionado ao mesmo tubo de centrífuga. O volume do lisado presente no tubo de

centrifuga foi completado para 13 mL com tampão de homogeinização 1x (210 mM de manitol,

70 mM de sacarose, 5 mM de Tris-HCl, 1 mM de EDTA (pH 7.5)). Em seguida o lisado foi

centrifugado à 2100 g por 7 min à 4ºC. O sobrenadante foi transferido para um novo tubo e

armazenado à -80 ºC para posterior separação das mitocôndrias e o pellet contendo os núcleos

foi utilizado para etapa de extração proteica.

Para extração e redução das proteínas nucleares, 200 µL de tampão de lise (6 M de

uréia, 2 M de tiouréia, 10 mM de ditiotreitol, 0.1 mM de pervanadato de sódio e inibidor de

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protease (cOmplete ULTRA Roche) foram adicionados aos pellets nucleares, seguido de

agitação em vórtex por 15s e incubação por 2 horas à 37ºC. Posteriormente, o conteúdo foi

diluído 10x com bicarbonado de trietilamônio (TEAB) 20 mM pH 7.5 e sonicado por 2x por 15

segundos em gelo. As proteínas foram alquiladas utilizando 200 μL de uma solução de 200 mM

de iodoacetamida em 20 mM TEAB e incubando o conteúdo por 20 minutos em temperatura

ambiente em ambiente isento de luz. Após as proteínas estarem reduzidas e alquiladas, as

mesmas foram digeridas com tripsina para serem analisadas por MS. Para tal, foi adicionado à

solução de proteínas, tripsina (Sequencing Grade Modified Trypsin, Promega) na concentração

de 1:100 em relação ao substrato, seguido de incubação entre 12-16 horas à 37ºC. A reação foi

parada pela adição de 5% de concentração final (v/v) de ácido fórmico. Os peptídeos foram

quantificados por fluorimetria utilizando o sistema Qubit® 3.0.

7.2.3 Análises em micro cromatografia líquida acoplada à espectrometria de

massas

As análises foram realizadas em sistema Acquity UPLC M-Class (Waters

Corporation) bidimensional acoplado ao espectrômetro Synapt G2-Si HDMS (Waters

Corporation) controlados pelo software MassLynx 4.1 (Waters Corporation).

As amostras de 0,5 μg de peptídeos foram injetadas e fracionadas em coluna de fase

reversa ACQUITY M-Class HSS T3 (100 Å, 1,8 μm, 75 μm × 150 mm, Waters Corporation,

Milford, MA). A coluna foi equilibrada com ácido fórmico 0,1% e os peptídeos foram eluídos

por meio de um gradiente de 7% à 40% (v/v) de acetonitrila durante 54 minutos diretamente no

espectrômetro de massas. O fluxo utilizado foi de 400 nL/min.

As análises de MS foram realizadas em instrumento híbrido do tipo ESI-Q-IMS-

TOF, o Synapt G2Si HDMS, cuja configuração se resume basicamente a uma interface (ou

fonte de íons) do tipo Electrospray, acoplada a um analizador Quadrupolo (Q), seguido da

câmara de mobilidade iônica (IMS) e outro analizador do tipo Time-of-Flight (TOF). Os

espectros de massa foram adquiridos no modo ion positivo e dado-independente utilizando

mobilidade iônica dos íons precursores (HDMSE). Os íons precursores foram analisados por

MS no TOF (ciclo de baixa energia) através do rastreamento de massas entre 50-2000 m/z em

alta resolução (40.000 FWHM) e fragmentados por colisão induzida (CID). Os íons fragmentos

também foram resolvidos no TOF (ciclo de alta energia) com a mesma faixa de massa dos íons

precursores. O espectrômetro foi calibrado usando espectros de MS/MS do peptide [Glu1]-

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Fibrinopeptide B human (Glu-Fib) em solução que foi usado como sprayer de referência da

fonte NanoLock Spray.

7.2.4 Processamento e busca em banco de dados

Os espectros de MS e MS/MS foram processados usando o software Progenesis®

QI for Proteomics versão 2.1 (Waters Corporation) e as buscas por identificações foram

realizadas contra a base de dados do proteoma humano Uniprot versão 2016/04 (registros),

utilizando o mesmo software. Para as análises quantitativas foram utilizados algoritmos

específicos (Apex3D, Peptide 3D e Ion Accounting) também do Progenesis® QI for Proteomics,

baseados nos parâmetros padrões para contabilidade iónica e quantificação descritos em Li et

al., (2009). Este software utilizada os dados de LC-MS, executa o alinhamento das corridas e a

detecção dos picos, criando uma lista de íons peptídicos de interesse que são então explorados

dentro do Peptide Ion Stats por meio métodos estatísticos multivariados, sendo que a etapa final

é a identificação dos peptídeos e proteínas. Os seguintes parâmetros foram considerados para

identificação:

1) Tripsina foi escolhida como a enzima do processo de digestão, permitindo-se até

uma clivagem errônea. 2) Cisteína-carbamidometilação foi definida como modificação fixa. 3)

Oxidação da metionina (M) foi escolhida como modificações dinâmica. 4). As identificações

foram consideradas positivas somente para peptídeos de alta-confiança (high confidence),

contendo uma taxa de falso positivo (FDR) menor do que 4%. 5). Foram consideradas somente

as proteinnas identificadas com 2 ou mais peptídeos, sendo pelo menos 1 peptídeo único.

7.2.5 Análises de correlação funcional

Nessa etapa as proteínas provenientes das células MO3.13 após o tratamento agudo

e crônico com MK-801 identificadas por MS, foram analisadas em relação às suas

características funcionais, localização celular e processos biológicos dos quais participam.

Sendo que as proteínas provenientes dessa análise que se localizam no núcleo celular e se

encontram diferencialmente abundantes em relação ao controle, foram comparadas com as

proteínas encontradas diferencialmente abundantes nos tecidos cerebrais de pacientes com SCZ

(corpo caloso - CC e lobo temporal anterior - ATL) e também analisadas em relação às vias das

quais participam.

Primeiramente a lista das proteínas totais identificadas por MS foram analisadas

utilizando os bancos de dados presentes nos softwares online String 10.0 disponível em

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(http://string-db.org/cgi/network.pl). Utilizando a ferramenta “Analysis” indetificamos através

dos dados encontrados em “Cellular Component” a porcentagem de enriquecimento nuclear

obtido através do procedimento de enriquecimento nuclear.

Posteriormente as proteínas presentes nas amostras tratadas com MK-801 que se

mostraram mais ou menos abundantes em relação ao controle foram devidamente classificadas

de acordo com o banco de dados encontrado em “Human Protein Reference Database”

disponível em (http://hprd.org) (tabela 4), sendo que das proteínas diferencialmente abundantes,

utilizamos aquelas que se localizam no núcleo (tabela 5) para realizar análises comparativas

com as proteínas nucleares encontradas diferencialmente abundantes nos tecidos cerebrais de

pacientes com SCZ (corpo caloso - CC e lobo temporal anterior - ATL). Para tal utilizamos a

um algoritmo de bioinformática online capaz de realizar análises comparativas produzindo um

diagrama de Venn, que está disponível em

(http://bioinformatics.psb.ugent.be/webtools/Venn/).

Análises posteriores foram realizadas utilizando os bancos de dados presentes nos

softwares online String 10.0 disponível em (http://string-db.org/cgi/network.pl) e Reactome

Pathway Database disponível em (http://www.reactome.org/). Essas análises também foram

feitas utilizando somente as proteínas nucleares diferencialmente abundantes em relação ao

controle, encontradas nas células MO3.13 agudamente tratadas com MK-801, visando

identificar vias alteradas nessas células pela presença da droga, uma vez que como e será

descrito nos resultados, as células MO3.13 cronicamente tradas com MK-801 não revelaram

diferenças significativas em relação ao controle.

Tabela 4 – Proteínas extraídas da linhagem celular MO.13 tratada com MK-801 por 8h, encontradas diferencialmente abundantes em relação ao controle e classificadas de acordo com os dados encontrados em “Human Protein Reference Database”

Gene name MK/control TAG Cell local

Biological process

Molecular class

Molecular function

PODNL1 -5,54187377 DOWN

-- Biological process unknown

Unclassified Molecular function unknown

TP53I11 -1,57130474 DOWN

Cytoplasm; Integral to membrane

Apoptosis Unclassified Molecular function unknown

SPIDR -2,20408374 DOWN -- -- -- --

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Biological process

Molecular class

Molecular function

GRM8 -1,53471079 DOWN

Plasma membrane

Cell communication ; Signal transduction

G protein coupled receptor

G-protein coupled receptor activity

UPK1A -2,39889931 DOWN

Plasma membrane; Endoplasmic reticulum


Cell surface receptor

Receptor activity

CTDNEP1 -2,11493954 DOWN

KRT2 -1,86868808 DOWN

Cytoplasm; Cytoskeleton

Cell growth and/or maintenance

Cytoskeletal associated protein


ZNF85 -1,79161764 DOWN

Nucleus

Regulation of nucleobase, nucleoside, nucleotide and nucleic acid metabolism

DNA binding protein DNA binding

ZMYM3 -1,57116908 DOWN

Nucleus; Cytoplasm



QSER1 -2,0161897 DOWN --

Biological process unknown


TRPC7 -1,63534856 DOWN Plasma membrane Transport Ion channel Ion channel

activity

TAF8 -1,7272122 DOWN

Nucleus


Transcription factor


ATL2 -1,78691426 DOWN Nucleus



C7orf26 -1,76989044 DOWN --



POTEKP -1,62652296 DOWN --



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Biological process

Molecular class

Molecular function

TMEM161A -1,51863588 DOWN

Plasma membrane



EHD2 -1,73091285 DOWN

Cytoplasm; Nucleus; Plasma membrane



RPS10-NUDT3 -1,58171817 DOWN -- -- -- --

RPL23 1,76161646 UP

Ribosome Protein metabolism

Ribosomal subunit

Structural constituent of ribosome

RPAP1 5,12718882 UP



INTS8 4,21947456 UP



CHD2 1,53511439 UP

Nucleus



GLRX3 1,9907664 UP

Cytoplasm Biological process unknown


BRCA2 3,44377879 UP

Cytoplasm; Extracellular




PDE7A 1,71362563 UP

Cytoplasm


Enzyme: Phosphodiesterase

Phosphoric diester hydrolase activity

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Biological process

Molecular class

Molecular function

NBPF9 2,27248485 UP



TMCO3 1,96530865 UP

Integral to membrane


Integral membrane protein

Molecular function unknown

SPC24 2,21457281 UP

Nucleus; Kinetochore


Cell cycle control protein Protein binding

ESAM 1,92787972 UP Integral to membrane

Immune response

Immunoglobulin

Antigen binding

BRD7 1,55865342 UP

Nucleus; Cytoplasm

Regulation of cell cycle ; Signal transduction



HPS5 2,86112022 UP

Cytoplasm

Cell organization and biogenesis


Tabela 5 – Proteínas nucleares da linhagem celular MO.13 tratadas com MK-801 por 8h e classificadas de acordo com os dados encontrados em “Human Protein Reference Database”


Biological process

Molecular class

Molecular function

ZNF85 -1,79161764 DOWN

Nucleus



ZMYM3 -1,57116908 DOWN

Nucleus; Cytoplasm



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Biological process

Molecular class

Molecular function

TAF8 -1,7272122 DOWN

Nucleus




ATL2 -1,78691426 DOWN Nucleus Biological process

unknown Unclassified Molecular function unknown

EHD2 -1,73091285 DOWN

Cytoplasm; Nucleus; Plasma membrane



CHD2 1,53511439 UP

Nucleus



SPC24 2,21457281 UP

Nucleus; Kinetochore


Cell cycle control protein Protein binding

BRD7 1,55865342 UP

Nucleus; Cytoplasm

Regulation of cell cycle ; Signal transduction



7.3 Resultados e Discussões

7.3.1 Cultura celular

Utilizando o protocolo descrito acima, o êxito nessa etapa foi alcançado, sendo que

a taxa de crescimento celular foi satisfatória e a morfologia das células assumiu um caráter

poligonal com vários processos curtos como continuação do corpo celular (figura 6). Esse tipo

de morfologia é característica para essas células e já foi descrita em outros estudos, assim como

no trabalho realizado por Buntinx e col. (2003). A biblioteca de MO3.13 foi construída e a

quantidade de células necessária para realização dos experimentos foi atingida. É importante

citar que as células se mostraram bastante resistentes ao congelamento.

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Figura 6 - Células MO3.13 crescidas em meio DEMEM-High glicose. Morfologia poligonal com vários processos curtos como continuação do corpo celular.

7.3.2 Cromatografia líquida acoplada à MS e identificação e quantificação de

proteínas e análises in silico

Foram identificados um total de 6849 peptídeos que correspondem à 838 proteínas

no proteoma de MO3.13 após tratamento crônico com MK-801 (tabela suplementar 3) e 8385

peptídeos que correspondem à 869 proteínas no proteoma de MO3.13 após tratamento agudo

com MK-801 (tabela suplementar 3). Em relação ao tratamento crônico não foram encontradas

alterações significativas em comparação ao controle. Em relação ao tratamento agudo foram

encontrados 111 peptídeos que correspondem à 31 proteínas que foram encontradas

diferencialmente abundantes em relação ao controle. O processo de separação nuclear foi

satisfatório, os espectros foram de boa qualidade e as análises realizadas com as proteínas

identificadas no software online String 10.1 mostraram uma alta taxa de enriquecimento como

mostra a figura 7.

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Figura 7 - Representação gráfica da média da porcentagem de enriquecimento das proteínas nucleares nas amostras tratadas com MK de forma crônica (72h) e aguda (8h). Banda rosa – proteínas nucleares. Banda azul – demais proteínas.

A análise comparativa entre as proteínas nucleares diferencialmente abundantes nos

tecidos cerebrais de pacientes com SCZ (corpo caloso - CC e lobo temporal anterior - ATL) e

as proteínas nucleares de MO3.13 após tratamento agudo com MK-801, não apresentou

nenhuma identificação em comum, como mostra a figura 8.

Esse resultado pode ser explicado devido: o fato das células MO3.13 não estarem

no mesmo estágio de maturação que os oligodendrócitos encontrados nos tecidos cerebrais

adultos, o tipo de medicação utilizada pelos pacientes durante o tratamento contra SCZ, o MK-

801 atuar principalmente sobre outros tipos celulares, as proteínas diferencialmente expressas

encontradas nos tecidos estarem presentes em outro tipo celular que não os oligodendrócitos,

as proteínas alteradas no núcleo serem de muito baixa abundancia, entre outros.

Enriquecimento - Proteínas nucleares

Outras proteínas Proteínas núcleares

52% 48%

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Figura 8 - Diagrama de Venn das proteínas diferencialmente abundantes encontradas no corpo colosso (cc), no lobo temporal anterior (ATL) e nas células MO3.13 após o tratamento agudo com MK-801 (MO3).

Através das análises realizadas usando softwares online String 10.0 e Reactome

Pathway Database, com a finalidade de identificar vias alteradas nessas células pela presença

da droga, também não foi possível identificar nenhuma via alterada. Entretanto, observando

individualmente as proteínas encontradas diferencialmente abundantes em células MO3.13

tratadas agudamente com MK-801, encontramos alterações pontuais bastante interessantes e

que corroboram com achados previamente publicados. É o caso da Proteína de dedo de zinco

85 (gene name = ZNF85) que foi encontrada menos abundante nas células MO3.13 agudamente

tratadas com MK-801. Essa proteína trata-se de um importante regulador transcricional

contendo domínios de dedo de zinco (Pieler & Bellefroid, 1994; Berg & Shi, 1996). Dados

encontrados na literatura revelam que outras proteínas da mesma família também apresentam

um papel no desenvolvimento da SCZ. Como por exemplo, a Proteína de dedo de zinco 365

(gene name = ZNF365) que foi encontrada como um importante parceiro de DISC1 (Disrupted-

In-Schizophrenia 1), sendo que esta última é conhecidamente associada à fisiopatologia das

principais psicoses (Anitha et al., 2009). Além disso, outros estudos também revelaram a

associação da Proteína de dedo de zinco 804A (gene name = ZNF804A) com o

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desenvolvimento da SCZ, sendo que essa também trata-se de um regulador transcricional

pertencente à mesma família de ZNF85 e ZNF365 (Walters et al., 2010; Tao et al., 2014).

A proteína Atlastina-2 (gene name = ATL2) também foi encontrada em menor

abundância nas células MO3.13 tratadas agudamente com MK-801. Dados da literatura

mostram que proteínas pertencentes à família das atlastinas são GTPases importantes para a

fusão homotípica dos túbulos do retículo endoplasmático e que sua falta, está associada à danos

neurológicos e processos neurodegenarativos (Chiurchiù et al., 2014).

A Proteína 7 contendo bromodomínio (gene name = BRD7) também foi encontrada

alterada em relação ao controle, porém ao contrário das outras, esta proteína está presente em

maior abundância. Estudos realizados por Christensen e col. (2012) e Fryland e col. (2016)

revelam que um outro membro da mesma família, a Proteína 1 contendo bromodomíno atua

regulando a expressão de inúmeros genes envolvidos no desenvolvimento cerebral e

susceptibilidade à distúrbios mentais, apresentando grande importância no desenvolvimento de

desordens mentais, tais como SCZ e transtorno bipolar.

Dessa maneira, apesar dos resultados obtidos nessa parte do trabalho não

apresentarem co-relação com os resultados obtidos pela análise do tecido cerebral, e de não ter

sido possível observar a alteração em nenhuma via ao analisar as proteínas nucleares de

MO3.13 tratadas com MK-801, foi possível observar alterações em proteínas importantes

relacionadas ao desenvolvimento de neuropatologias, como por exemplo, proteínas

relacionadas à regulação da expressão gênica e à processos de sinalização, e que podem

futuramente servir como alvo para estudos mais específicos e aprofundados.

7.4 Referências

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4 BUNTINX M, VANDERLOCHT J, HELLINGS N, VANDENABEELE F, LAMBRICHTS I, RAUS J, AMELOOT M, STINISSEN P, STEELS P. (2003. Characterization of three human oligodendroglial cell lines as a model to study oligodendrocyte injury: Morphology and oligodendrocyte-specific gene expression. J. Neurocytol., 32(1): 25-38.

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5 CASSOLI JS, IWATA K, STEINER J, GUEST PC, TURCK CW, NASCIMENTO JM, MARTINS-DE-SOUZA D. (2016b). Effect of MK-801 and Clozapine on the Proteome of Cultured Human Oligodendrocytes. Front Cell Neurosci., 10(52), doi: 10.3389/fncel.2016.00052.

6 CEDARLANE CELLutions BIOSYSTEMS. Human Oligodendrocytic (Glial) (MO3.13) Cell Line Maintenance. Disponível em: <http://search.cosmobio.co.jp/cosmo_search_p/search_gate2/docs/CEB_/CLU301.20140127.pdf>. Acesso em 20 de jan. de 2017.

7 CHIURCHIÙ V, MACCARRONE M, ORLACCHIO A. (2014). The Role of Reticulons in Neurodegenerative Diseases. Neuromol Med., 16: 3–15.

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9 EMERY B, DUGAS JC. (2013). Purification of oligodendrocyte lineage cells from mouse cortices by immunopanning. Cold Spring Harb Protoc., 2013(9): 854-868.

10 FRYLAND T, CHRISTENSEN JH, PALLESEN J, MATTHEISEN M, PALMFELDT J, BAK M, GROVE J, DEMONTIS D, BLECHINGBERG J, OOI HS, NYEGAARD M, HAUBERG ME, TOMMERUP N, GREGERSEN N, MORS O, CORYDON TJ, NIELSEN AL, BØRGLUM AD. (2016). Identification of the BRD1 interaction network and its impact on mental disorder risk. Gen Med., doi: 10.1186/s13073-016-0308-x.

11 FUNFSCHILLING U, SUPPLIE LM, MAHAD D, BORETIUS S, SAAB AS, EDGAR J, BRINKMANN BG, KASSMANN CM, TZVETANOVA ID, MOBIUS W, DIAZ F, MEIJER D, SUTER U, HAMPRECHT B, SEREDA MW, MORAES CT, FRAHM J, GOEBBELS S, NAVE KA. (2012). Glycolytic oligodendrocytes maintain myelin and long-term axonal integrity. Nature, 485(7399): 517-521.

12 GUEST PC, IWATA K, KATO TA, STEINER J, SCHMITT A, TURCK CW, MARTINS-DE-SOUZA D. (2015). MK-801 treatment affects glycolysis in oligodendrocytes more than in astrocytes and neuronal cells: insights for schizophrenia. Front Cell Neurosci., 9:180, doi: 10.3389/fncel.2015.00180. 13 HOMAYOUN H, MOGHADDAM B. (2007). NMDA receptor hypofunction produces opposite effects on prefrontal cortex interneurons and pyramidal neurons. J. Neurosci., 27: 11496–11500.

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16 LI GZ, VISSERS JPC, SILVA JC, GOLICK D, GORENSTEIN MV, GEROMANOS SJ. (2009). Database searching and accounting of multiplexed precursor and product ion spectra from the data independent analysis of simple and complex peptide mixtures. Proteomics, 9(6): 1696–1719.

17 MARTINS-DE-SOUZA D, LEBAR M, TURCK CW. (2011). Proteome analyses of cultured astrocytes treated with MK-801 and clozapine: similarities with schizophrenia. Eur Arch Psychiatry Clin Neurosci., 261 (3):217-228.

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18 MCLAURIN J, TRUDEL GC, SHAW IT, ANTEL JP, CASHMAN NR. (1995). A human glial hybrid cell line differentially expressing genes subserving oligodendrocyte and astrocyte phenotype. J Neurobiol., 26(2): 283-293. 19 O'MEARA RW, RYAN SD, COLOGNATO H, KOTHARY R. (2011). Derivation of enriched oligodendrocyte cultures and oligodendrocyte/neuron myelinating co-cultures from post-natal murine tissues. Journal of visualized experiments. JoVE, 54, doi:10.3791/3324

20 ONO K, IKENAKA K. (2012). Lineage and development: Oligodendrocytes. In: Kettenmann H, Ransom BR (eds) Neuroglia. Oxford University Press, New York

21 PIELER T, BELLEFROID E. (1994). Perspectives on zinc finger protein function and evolution — an update. Mol. Biol. Rep. 20: 1-8.

22 SAAB AS, TZVETAVONA ID, TREVISIOL A, BALTAN S, DIBAJ P, KUSCH K, MOBIUS W, GOETZE B, JAHN HM, HUANG W, STEFFENS H, SCHOMBURG ED, PEREZ-SAMARTIN A, PEREZ-CERDA F, BAKHTIARI D, MATUTE C, LOWEL S, GRIESINGER C, HIRRLINGER J, KIRCHHOFF F, NAVE KA. (2016). Oligodendroglial NMDA Receptors Regulate Glucose Import and Axonal Energy Metabolism. Neuron, 91(1): 119-132. 23 SALETTI PG, MAIOR RS, HORI E, NISHIJO H, TOMAZ C. (2015). Sensorimotor gating impairments induced by MK-801 treatment may be reduced by tolerance effect and by familiarization in monkeys. Front. Pharmacol., v. 6, n. 204, doi: 10.3389/fphar.2015.00204, 2015

24 TAO R, COUSIJN H, JAFFE AE, BURNET PW, EDWARDS F, EASTWOOD SL, SHIN JH, LANE TA, WALKER MA, MAHER BJ, WEINBERGER DR, HARRISON PJ, HYDE TM, KLEINMAN JE. (2014). Expression of ZNF804A in human brain and alterations in schizophrenia, bipolar disorder, and major depressive disorder: a novel transcript fetally regulated by the psychosis risk variant rs1344706. JAMA Psychiatry., 71(10): 1112-1120.

25 WALTERS JT, CORVIN A, OWEN MJ, WILLIAMS H, DRAGOVIC M, QUINN EM, JUDGE R, SMITH DJ, NORTON N, GIEGLING I, HARTMANN AM, MÖLLER HJ, MUGLIA P, MOSKVINA V, DWYER S, O'DONOGHUE T, MORAR B, COOPER M, CHANDLER D, JABLENSKY A, GILL M, KALADJIEVA L, MORRIS DW, O'DONOVAN MC, RUJESCU D, DONOHOE G. (2010). Psychosis susceptibility gene ZNF804A and cognitive performance in schizophrenia. JAMA Psychiatry., 67(7): 692-700.

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8. CONCLUSÕES GERAIS

Este trabalho teve um caráter pioneiro ao buscar as alterações no proteoma nuclear

que estão envolvidas no desenvolvimento da SCZ. Acredita-se que os dados obtidos neste

estudo são importantes, pois além de revelarem interessantes alterações ajudando a montar o

quebra-cabeças do complexo mecanismo envolvido no desenvolvimento da SCZ abrindo novas

perspectivas de estudos mais aprofundados e específicos.

O primeiro desafio enfrentado nesse trabalho foi a otimização de um protocolo que

permitisse um enriquecimento das proteínas nucleares nas amostras utilizadas para as análises

por espectrometria de massas. No caso das amostras de tecido cerebral humano, o protocolo de

desenvolvido por Cox & Emili (2006) se mostrou eficaz permitindo um enriquecimento

bastante satisfatório. Entretanto, para o enriquecimento nuclear das amostras obtidas a partir

cultura celular de MO3.13, foi necessário otimizar um novo protocolo, no qual os volumes e

tampões se ajustassem as condições celulares. Esse protocolo encontra-se descrito no capítulo

2 desta dissertação, sendo que o mesmo já foi aceito para publicação como um capítulo de livro

no Neuromethods (Springer). O enriquecimento nuclear realizado a partir deste último também

se mostrou bastante satisfatório, sendo que como já foi apresentado acima a proporção de

proteínas nucleares obtidas em relação às outras foi superior aos 50%.

Referente às análises do proteoma nuclear propriamente dito dos tecidos cerebrais

de pacientes com SCZ e das células MO3.13 tratadas com MK-801, os resultados obtidos foram

bastante distintos e dessa maneira serão apresentados separadamente. No capítulo 1 dessa

dissertação nós discutimos em forma de artigo as alterações observadas no proteoma nuclear

dos tecidos cerebrais de pacientes com SCZ. De acordo com os resultados apresentados, é

possível concluir que tanto o tecido cerebral que corresponde a substância branca (CC), como

o tecido cerebral que corresponde à substância cinzenta (ATL) apresentam alterações em vias

relacionadas à resposta ao estresse celular. O aumento da concentração de proteínas nucleares

relacionadas as respostas ao choque térmico (HSPs) é um achado bastante interessante, pois

corrobora os inúmeros estudos que ligam o desenvolvimento da SCZ com a exposição do tecido

cerebral à fatores estressantes, como hipóxia (durante o nascimento ou desenvolvimento fetal)

ou processos imuno-inflatórios. No entanto, alguns autores também discutam a possibilidade

desses efeitos serem resultantes dos tratamentos utilizados no controle da doença.

Individualmente, o tecido cerebral correspondente a região ATL de pacientes com SCZ

apresentou alterações não somente em proteínas relacionadas às respostas ao estresse celular,

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mas também em proteínas relacionadas ao spliceossomo, como podemos observar ao analisar

os resultados expostos no capítulo 1 dessa dissertação. Sabendo que o spliceossomo é essencial

para o processamento do mRNA, podemos concluir que essas proteínas se figuram alvos

bastante promissores para estudos mais aprofundados, uma vez que essas alterações se

relacionam à um processo chave, que pode influenciar diversas vias ao mesmo tempo,

apresentando um efeito prolongado e pleiotrópico característico de doenças neuropsiquiátricas

como a SCZ.

Análises de enriquecimento de vias realizadas com as proteínas encontradas

diferentemente abundantes, proporcionou uma visão mais ampla dos mecanismos celulares que

se mostraram afetados e também das proteínas que indiretamente sofrem modificações em sua

atividade devido a alterações em vias das quais participa. As vias que se mostraram alteradas

nos tecidos cerebrais de pacientes com SCZ estão principalmente relacionadas à sinalização e

comunicação celular, metabolismo de ácidos nucleicos e transcrição gênica. Dessa maneira é

possível concluir, que apesar de não terem sido observadas grandes quantidades de alterações

nas proteínas nucleares de indivíduos com SCZ, as poucas alterações observadas se relacionam

à processos chaves e abrangentes que podem influenciar todos os outros mecanismos celulares.

Relativo ao estudo do proteoma nuclear das células MO3.13 tratadas com MK-801,

os resultados observados e apresentados no capítulo 3 dessa dissertação são bastante distintos

dos resultados obtidos com as análises dos tecidos cerebrais. Não foi possível observar uma

conexão entre as proteínas alteradas nas células tratadas com MK-801 com as proteínas

alteradas nos tecidos. Muitas hipóteses podem ser apresentadas para justificar esse resultado: o

fato do tecido analisado apresentar um conjunto de diferentes células que interagem, os tipos

de tratamento utilizados pelos pacientes, o fato das células estarem em um estágio de maturação

anterior às células presentes no tecido analisado.

As células MO3.13 tratadas de forma crônica apresentaram alterações

principalmente em proteínas relacionadas ao estresse e morte celular. O mesmo não foi

observado nas células tratadas de forma aguda. Essas alterações observadas nas células tratadas

cronicamente com MK801 provavelmente são fruto do estresse provocado pelo longo tempo

em que as células foram cultivadas no mesmo meio de cultura. No fim do tratamento, o meio

já se encontrava com baixo pH e provavelmente com todos os nutrientes consumidos. Nas

células tratadas de forma aguda também não foi possível observar grandes alterações. Poucas

proteínas nucleares se mostraram diferencialmente abundantes em relação ao controle e não foi

possível observar alteração em nenhuma via através das análises de bioinformática. Entretanto,

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analisando individualmente as proteínas alteradas foi possível observar resultados interessantes,

como alteração em proteínas relacionadas à transcrição e regulação gênica e também ao

citoesqueleto. Essas alterações pontuais podem apresentar grande abrangência, mas podem se

configuram como importantes alvos de estudos mais aprofundados.

Finalmente, considerando o que foi discutido neste trabalho pode-se concluir que

os resultados encontrados fornecem uma visão mais abrangente com relação a atuação das

proteínas nucleares no desenvolvimento da SCZ.

9. PERSPECTIVAS

Este trabalho apresentou uma proposta pioneira ao buscar as alterações proteicas à

nível nuclear que ocorrem em pacientes com SCZ, sendo que o estudo do compartimento

nuclear se mostrou extremamente interessante, pois nesta região celular se desenvolvem

importantes processos, os quais atuam na célula como um todo. Sendo assim, temos como

perspectiva estudar mais profundamente as vias e proteínas encontradas alteradas, buscando a

compreender mais claramente seus mecanismos, e como as mesmas se relacionam ao

desenvolvimento da SCZ.

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11. ANEXOS

11. 1 Anexo I – Tabelas Suplementares

Tabela suplementar 1 – Vias alteradas relacionados à proteínas diferencialmente expressas no lobo temporal anterior (ATL) de acordo com o programa String.

pathway description

observed gene count

false discovery rate

matching proteins in your network (IDs)

matching proteins in your network (labels)

Spliceosome 8 5,56E-06

ENSP00000227378,ENSP00000247207,ENSP00000283179,ENSP00000310219,ENSP00000319690,ENSP00000362820,ENSP00000364802,ENSP00000365439

HNRNPC,HNRNPK,HNRNPU,HSPA1A,HSPA2,HSPA6,HSPA8,SRSF3

97

97

athway description

observed gene count




Legionellosis 6 6,17E-06

ENSP00000227378,ENSP00000247207,ENSP00000310219,ENSP00000330054,ENSP00000340019,ENSP00000364802

EEF1A1,HSPA1A,HSPA2,HSPA6,HSPA8,HSPD1

Antigen processing and presentation 6 1,22E-05


CALR,CANX,HSPA1A,HSPA2,HSPA6,HSPA8

Alzheimer s disease 8 1,22E-05


CALM1,COX4I1,COX5B,NDUFS8,PPP3CA,PPP3R1,SNCA,UQCRH

Epstein-Barr virus infection 8 2,90E-05


HSPA1A,HSPA2,HSPA6,HSPA8,VIM,YWHAE,YWHAG,YWHAQ

Oocyte meiosis 6 0,000106


CALM1,PPP3CA,PPP3R1,YWHAE,YWHAG,YWHAQ

Protein processing in endoplasmic reticulum 7 0,000106

ENSP00000227378,ENSP00000247207,ENSP00000247461,ENSP00000310219,ENSP00000320866,ENSP00000354111,ENSP00000364802

CALR,CANX,DNAJC5,HSPA1A,HSPA2,HSPA6,HSPA8

MAPK signaling pathway 8 0,000151


CDC42,FLNA,HSPA1A,HSPA2,HSPA6,HSPA8,PPP3CA,PPP3R1

Estrogen signaling pathway 5 0,000796

ENSP00000227378,ENSP00000247207,ENSP00000310219,ENSP00000349467,ENSP00000364802

CALM1,HSPA1A,HSPA2,HSPA6,HSPA8

Viral carcinogenesis 6 0,00166


CDC42,HIST1H2BB,HNRNPK,YWHAE,YWHAG,YWHAQ

Endocytosis 6 0,00209


CDC42,HSPA1A,HSPA2,HSPA6,HSPA8,SH3GL2

98

98

pathway description

observed gene count




Parkinson s disease 5 0,00373


COX4I1,COX5B,NDUFS8,SNCA,UQCRH

Alcoholism 5 0,00373


CALM1,H2AFV,H3F3A,HIST1H2AD,HIST1H2BB

Non-alcoholic fatty liver disease (NAFLD) 5 0,0045


CDC42,COX4I1,COX5B,NDUFS8,UQCRH

Systemic lupus erythematosus 4 0,00797

ENSP00000308405,ENSP00000341094,ENSP00000350580,ENSP00000355778

H2AFV,H3F3A,HIST1H2AD,HIST1H2BB

Toxoplasmosis 4 0,0145


HSPA1A,HSPA2,HSPA6,HSPA8

Pathogenic Escherichia coli infection 3 0,0161

ENSP00000238081,ENSP00000314458,ENSP00000344456

CDC42,CTNNB1,YWHAQ

Axon guidance 4 0,0182


CDC42,DPYSL2,PPP3CA,PPP3R1

Oxidative phosphorylation 4 0,0183


COX4I1,COX5B,NDUFS8,UQCRH

VEGF signaling pathway 3 0,0183

ENSP00000234310,ENSP00000314458,ENSP00000378323

CDC42,PPP3CA,PPP3R1

Tight junction 4 0,0183


CDC42,CTNNB1,EPB41L3,MYH9

Measles 4 0,0183



Long-term potentiation 3 0,0208

ENSP00000234310,ENSP00000349467,ENSP00000378323

CALM1,PPP3CA,PPP3R1

Amphetamine addiction 3 0,0218

ENSP00000234310,ENSP00000349467,ENSP00000378323

CALM1,PPP3CA,PPP3R1

Hippo signaling pathway 4 0,0246


CTNNB1,YWHAE,YWHAG,YWHAQ

Bacterial invasion of epithelial cells 3 0,0261

ENSP00000314458,ENSP00000344456,ENSP00000353157

CDC42,CTNNB1,SEPT2

HTLV-I infection 5 0,0261


CALR,CANX,CTNNB1,PPP3CA,PPP3R1

99

99

pathway description

observed gene count




Arrhythmogenic right ventricular cardiomyopathy (ARVC) 3 0,0261

ENSP00000070846,ENSP00000344456,ENSP00000357283

CTNNB1,LMNA,PKP2

cGMP-PKG signaling pathway 4 0,0267


CALM1,PDE2A,PPP3CA,PPP3R1

Cardiac muscle contraction 3 0,0267

ENSP00000253452,ENSP00000258424,ENSP00000309565

COX4I1,COX5B,UQCRH

Salmonella infection 3 0,0306

ENSP00000216181,ENSP00000314458,ENSP00000358866

CDC42,FLNA,MYH9

Influenza A 4 0,0306



Apoptosis 3 0,0319 ENSP00000234310,ENSP00000265717,ENSP00000378323

PPP3CA,PPP3R1,PRKAR2B

Tuberculosis 4 0,0319


CALM1,HSPD1,PPP3CA,PPP3R1

Huntington s disease 4 0,038


COX4I1,COX5B,NDUFS8,UQCRH

T cell receptor signaling pathway 3 0,0464

ENSP00000234310,ENSP00000314458,ENSP00000378323

CDC42,PPP3CA,PPP3R1

Tabela suplementar 2 – Vias alteradas relacionados à proteínas diferencialmente expressas no corpo caloso (CC) de acordo com o programa String.

pathway description

observed gene count




GnRH signaling pathway 5 1,42E-05


CALM1,CAMK2A,CAMK2B,CAMK2G,CDC42

Neurotrophin signaling pathway 5 2,88E-05


CALM1,CAMK2A,CAMK2B,CAMK2G,CDC42

Long-term potentiation 4 5,40E-05


CALM1,CAMK2A,CAMK2B,CAMK2G

100

100

pathway description

observed gene count




Amphetamine addiction 4 5,40E-05



Glioma 4 5,40E-05 ENSP00000319060,ENSP00000349467,ENSP00000379098,ENSP00000381412


Gastric acid secretion 4 6,07E-05



Circadian entrainment 4 0,000143



Inflammatory mediator regulation of TRP channels

4 0,000144 ENSP00000319060,ENSP00000349467,ENSP00000379098,ENSP00000381412


Melanogenesis 4 0,000144 ENSP00000319060,ENSP00000349467,ENSP00000379098,ENSP00000381412


Oocyte meiosis 4 0,000185 ENSP00000319060,ENSP00000349467,ENSP00000379098,ENSP00000381412


Dopaminergic synapse 4 0,000325



Adrenergic signaling in cardiomyocytes

4 0,000494 ENSP00000319060,ENSP00000349467,ENSP00000379098,ENSP00000381412


Oxytocin signaling pathway 4 0,000612



Tuberculosis 4 0,000881 ENSP00000319060,ENSP00000349467,ENSP00000379098,ENSP00000381412


Calcium signaling pathway 4 0,0009



Insulin secretion 3 0,00192 ENSP00000319060,ENSP00000379098,ENSP00000381412

CAMK2A,CAMK2B,CAMK2G

Proteoglycans in cancer 4 0,00192


CAMK2A,CAMK2B,CAMK2G,CDC42

101

101

pathway description

observed gene count




ErbB signaling pathway 3 0,00195 ENSP00000319060,ENSP000003

79098,ENSP00000381412 CAMK2A,CAMK2B,CAMK2G

HIF-1 signaling pathway 3 0,00351 ENSP00000319060,ENSP000003


Cholinergic synapse 3 0,00373 ENSP00000319060,ENSP000003


Axon guidance 3 0,00535 ENSP00000309539,ENSP00000309629,ENSP00000314458

CDC42,CFL1,DPYSL2

Wnt signaling pathway 3 0,0067 ENSP00000319060,ENSP000003


Olfactory transduction 4 0,0129



Pertussis 2 0,0353 ENSP00000309629,ENSP00000349467 CALM1,CFL1

Tabela suplementar 3 – Proteínas totais identificadas por espectrometria de massas em HMSE após tratamento crônico e agudo das células MO3.13 com MK-801 e enriquecimento nuclear.

102

102

103

103

104

104

105

105

106

106

107

107

108

108

109

109

110

110

111

111

112

112

113

113

114

114

115

115

116

116

117

117

118

118

119

119

442 Proteomics Clin. Appl. 2016, 10, 442–455DOI 10.1002/prca.201500109

REVIEW

Employing proteomics to unravel the molecular effectsof antipsychotics and their role in schizophreniaJuliana S. Cassoli1, Paul C. Guest1, Aline G. Santana1 and Daniel Martins-de-Souza1,2

1 Laboratory of Neuroproteomics, Department of Biochemistry and Tissue Biology, Institute of Biology, Universityof Campinas (UNICAMP), Campinas, Sao Paulo, Brazil

2 UNICAMP Neurobiology Center, Campinas, Sao Paulo, Brazil

Received: August 31, 2015Revised: November 15, 2015Accepted: December 9, 2015

Schizophrenia is an incurable neuropsychiatric disorder managed mostly by treatment of thepatients with antipsychotics. However, the efficacy of these drugs has remained only low tomoderate despite intensive research efforts since the early 1950s when chlorpromazine, thefirst antipsychotic, was synthesized. In addition, antipsychotic treatment can produce often un-desired severe side effects in the patients and addressing these remains a large unmet clinicalneed. One of the reasons for the low effectiveness of these drugs is the limited knowledge aboutthe molecular mechanisms of schizophrenia, which impairs the development of new and moreeffective treatments. Recently, proteomic studies of clinical and preclinical samples have iden-tified changes in the levels of specific proteins in response to antipsychotic treatment, whichhave converged on molecular pathways such as cell communication and signaling, inflamma-tion and cellular growth, and maintenance. The findings of these studies are summarized anddiscussed in this review and we suggest that this provides validation of proteomics as a usefultool for mining drug mechanisms of action and potentially for pinpointing novel moleculartargets that may enable development of more effective medications.

Keywords:Antipsychotics / Proteomics / Psychiatric disorders / Schizophrenia

! Additional supporting information may be found in the online version of this article atthe publisher’s web-site

1 Introduction

Schizophrenia is a serious, debilitating, incurable mentaldisorder with an unknown etiology, which affects around1% of world population [1]. There is a broad spectrumof symptoms that usually manifest in young adults [2–4]which are divided basically into three categories: (i) posi-tive symptoms (delusions and hallucinations); (ii) negative

Correspondence: Professor Daniel Martins-de-Souza, Laboratoryof Neuroproteomics, Department of Biochemistry and Tissue Bi-ology, Institute of Biology, University of Campinas, Rua MonteiroLobato 255, Cidade Universitaria Zeferino Vaz, 13083–862 Camp-inas, SP, BrazilE-mail: [email protected]

Abbreviations: ALDOC, aldolase C; ApoA-I, apolipoprotein A-I; ATP, adenosine triphosphate; CNS, central nervous system;CRMP, collapsin response mediator protein; DLPFC, dorsolat-eral prefrontal cortex; EPS, extrapyramidal symptoms; HSP, heatshock protein; MDH, malate dehydrogenase; NSC, neural stemcell; PMBC, peripheral mononuclear blood cell

symptoms (depression, unsociability, anhedonia, and lack ofmotivation), and (iii) cognitive impairments (difficulties inworking and long-term memory, attention and executivefunctioning) [5, 6]. Although monozygotic twin studies haveproven that schizophrenia has a genetic component, otherstudies have shown that this is not always sufficient to triggerthe disorder [2,6,7]. It is now believed that the pathogenesis ofschizophrenia involves genetic predisposition associated withenvironmental factors such as viral infections, inflammatorydiseases, stress, drug abuse, pregnancy complications, as wellas physical and emotional stress [2, 4, 8].

The complexity of schizophrenia has led to many theoriesabout its causes [9], such as the neurodevelopmental hypoth-esis [2, 10, 11] and neurotransmitter hypotheses which havemainly focused on perturbations in dopaminergic [12, 13],glutamatergic [2,14] and gabaergic [2,15] pathways. Recently,an immune hypothesis of schizophrenia emerged from clin-ical and epidemiological studies which revealed abnormal-ities in immune and inflammatory systems [9, 16]. Despitethe numerous publications defending each hypothesis, nonecan address all aspects associated with schizophrenia. Several

C⃝ 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim www.clinical.proteomics-journal.com

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reports have now converged on the idea that schizophrenia isa multifactorial disorder which can involve perturbations ofdifferent signaling pathways in the brain and periphery, suchas inflammation and hormonal networks [17].

The lack of a consensus on the biochemical pathways af-fected in schizophrenia has hampered development of newand more effective drugs. Antipsychotics, also known as neu-roleptics, are still the main class of drug used in the pharmaco-logical treatment of schizophrenia [18]. These drugs basicallytarget neurotransmitter receptors in the CNS, and this cancontrol some of schizophrenia symptoms. However, thesedrugs can have off-target effects on multiple body systemsleading to a wide range of side effects [19], causing manypatients to pause or abandon treatment [20, 21].

In the face of these problems, many research projects havebeen undertaken to increase our knowledge concerning thebiochemical bases of schizophrenia and the effects of existingantipsychotic treatments. In this aspect, proteomic methodshave emerged as the method of choice as they allow analysisof multiple protein networks simultaneously, in a dynamicmanner [17]. This review provides an outline of studies involv-ing the use of antipsychotics in both preclinical and clinicalscenarios and the use of proteomics to unravel the associatedmolecular pathways.

2 Antipsychotics

2.1 First-generation drugs

Prior to the early twentieth century, the treatment ofschizophrenia was based on maintaining patients in psychi-atric hospitals and applying rudimentary therapeutic tech-niques with little or no evidence of effectiveness [22]. Onlyin the 1950s, with the development of chlorpromazine, treat-ment of patients with antipsychotics began [23–25]. Chlor-promazine is a phenothiazine derivate and its mechanism ofaction is mainly based on the antagonism of D2 dopaminereceptors (type 2 dopamine receptor) [23, 26–28]. Becauseof clinical success of chlorpromazine, other D2 antagonistswere synthesized based on its chemical structure, such ashaloperidol and fluphenazine [25, 29]. The first-generationantipsychotics are still used in the clinic to treat schizophre-nia, although these do not always benefit the patients [30].The effectiveness of these drugs is mainly exerted over posi-tive symptoms, with lower efficacy on the negative or deficitsymptoms [25, 31]. In addition, prolonged use of typical an-tipsychotics is associated with a wide range of side effects,particularly the extrapyramidal symptoms (EPSs), akathisia,and tardive dyskinesia in least 25% of the patients [32, 33].These effects have led to reduced use of this class of drugs.

2.2 Second-generation drugs

In the early 1960s, German psychiatrists worked on a drugto circumvent the link that was created between EPS and

antipsychotic efficacy. These efforts led to the introduction ofclozapine, an antipsychotic with low propensity to induce EPS[34, 35]. The initial use of this drug showed its usefulness onrelief of both positive and negative schizophrenia symptoms[36]. Because of this, the news of clozapine spread quickly inthe field of psychiatry and this lead to the emergence of theconcept of “atypical” antipsychotic drugs. Consequently, thefirst generation of antipsychotics was named “typical antipsy-chotics” [37]. Following the development of clozapine, otheratypical medications such as risperidone, olanzapine, queti-apine, and ziprasidone came out for clinical use in 1990s, dif-fering from each other in terms of receptor binding, efficacy,and side-effect profiles [38]. In addition to effects on dopamin-ergic neurotransmission, the second-generation drugs alsoantagonize 5-hydroxytryptamine receptor 2A receptors withat least equal (or higher) affinity compared to their blockadeof dopamine D2 receptors [39]. This may be important as theserotonergic system has been associated with the control ofmood, cognition, and memory [40].

2.3 Third-generation drugs

The term “third generation” of antipsychotics came intouse due to introduction of the drug aripiprazole [41]. Op-posite to the other antipsychotics, aripiprazole is actu-ally a partial agonist of the dopamine D2 and serotonin5-hydroxytryptamine receptor 1A receptors, and an antago-nist of 5-hydroxytryptamine receptor 2A receptors [42, 43].Several short- [44–46] and long-term [47,48] studies have nowreported the success of this medication in relief of both thepositive and negative symptoms of schizophrenia patients.Although a report in a systematic database review stated thataripiprazole is not very effective in its oral form, leading sev-eral patients to discontinue treatment during clinical trials[49].

3 Proteomics toolbox applied toantipsychotic research

One of the most useful features of proteomics comes fromthe myriad of techniques employed to study protein levelchanges, mostly in a large scale and multiplex fashion. Thisprovides versatility, which has been applied in investigationsabout the antipsychotic effects in several preclinical modelsand clinical studies, including analysis of cells and other bio-logical samples. Shotgun MS has been the method of choicein studying the mechanism of action of antipsychotics intissue samples, in which different configurations of instru-ments (MALDI-TOF [50–57], quadrupole-TOF [58, 59], Orbi-trap [60–62], etc.) have been employed. Prior to shotgun-MSapproaches, several studies used either 1D [60] or 2D elec-trophoresis [50–55,57,58,63] techniques to study proteomes.Although these had some advantages such as the ability to de-tect changes in different isoforms and PTMs of proteins, theytended to be limited by the relatively low number of total pro-


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444 J. S. Cassoli et al. Proteomics Clin. Appl. 2016, 10, 442–455

teins detected and lower throughput. Recently, quantitativeproteomics procedures have been applied in some studies forrelative quantification by means of label-free [61, 62, 64] andstable isotope labeling [60] methods. In addition, MS-basedproteomics studies of PTMs have been facilitated by use ofimmobilized metal affinity chromatography (IMAC) and hy-drophilic interaction LC in order to verify whether phospho-proteins and glycoproteins are also changed in response totreatment with antipsychotics [64, 65].

4 What does proteomics tell us aboutantipsychotic mechanisms of action?

4.1 Findings in cell cultures

Cellular cultures have a proven record as preclinical tools fordrug screening and testing for mode of action and toxicityassessments [66]. In vitro cell culture systems can reliablyyield better-quality, more accurate, and tissue-specific infor-mation than could be achieved using whole organisms andcould also significantly improve the technical output, pre-dictive value, and translation efficiencies between in vitro,animal, and human clinical studies [66]. However, as in anymedical or biological field of study, cell cultures are only asgood as their ability to outline in vivo physiological and patho-logical processes as it relates to specific isolated cell types [66].This could be a limitation as most cells of the body do notact alone and require feed-forward and feedback control fromother cell types and body fluids. Thus, the findings of all suchstudies will ultimately require validation testing using moreintact physiological systems.

The actions of antipsychotics drugs on cell cultures havebeen in assessed in several MS-based proteomic studies. Ina recent report, the action of haloperidol was evaluated us-ing primary cortical neurons from rodents in order to de-tect short-term changes in neuronal function and associatedchanges in protein levels using a SILAC proteomic profil-ing method on an LTQ-Orbitrap mass spectrometer [60]. Theauthors found that the haloperidol treatment led to markedchanges in protein synthesis networks (Supporting Informa-tion Table 1). This included the finding of increased levels ofcytoskeletal proteins and proteins associated with the transla-tional machinery as well as the molecular target of rapamycinC1 signaling pathway [60]. The molecular target of rapamycinC1 pathway is also involved in regulation of protein synthesisas well as cell growth and proliferation [67]. From these find-ings, the authors suggested that haloperidol, considered tobe an old antipsychotic, can increase the synthesis of compo-nents of the translational machinery in cultured striatal neu-rons and this may be involved in its mechanism of action [60].This is consistent with the findings that protein synthesis andthe mTOR pathway appear to be disrupted in schizophreniapatients [68]. However, changes in both of these pathwayshave also been linked to the extrapyramidal side effects ofsome antipsychotics [69].

Aripiprazole was one of latest antipsychotics developed foruse in clinical practice. Already, new insights concerning itstherapeutic mechanism have been reported by proteomics.A differential 2DE and MALDI-TOF MS showed that thisdrug increased significantly the levels of the HSP Hsp90!(Table 1) in cultured PC12 cells, a model often used to studyneural and endocrine functions [51]. In this case, the in-creased abundance of Hsp90! was associated with neuriteoutgrowth. This may be relevant as other studies have re-ported that the same protein is downregulated in the dor-solateral prefrontal cortex (DLPFC) of schizophrenia patients[70]. Hsp90 is an essential molecular chaperone, ubiquitouslyactive in many signaling and other cellular pathways, and isresponsible for the assembly of a number of protein com-plexes [71] which may include those involved in the aripipra-zole mechanism of action.

Using similar proteomic approaches and cellular models,two other research groups described the actions of haloperi-dol and risperidone on neural stem cells (NSCs) during 24 h(short-term treatment) and 96 h (long-term treatment), re-spectively [52, 72]. Although the short-term treatment witheither drug had no detectable effects on the morphology ofNSCs, both produced significant changes in the levels ofspecific proteins [72]. Haloperidol altered mainly the lev-els of secreted acidic cysteine rich glycoprotein (SPARC),leu-enkephalin, activator of G protein signaling 3, and N-ethylmaleimide-sensitive factor (NSF)-L cofactor (p97–p47factor), indicating that this drug may alter Ca2+ mobiliza-tion processes and G protein signaling in those cells [72].This may indicate a reversal of the effects seen in the dis-ease as both Ca2+ and G protein signaling are well knownto be disrupted in schizophrenia [73]. NSFL is an ATPase(where ATP is adenosine triphosphate) known to be involvedin transport vesicle/target membrane fusion between mem-brane compartments in cellular trafficking processes. Treat-ment of the cells with risperidone resulted in altered levelsof 17 proteins (Supporting Information Table 1) with dis-tinct functional activities, which were associated with severalbiochemical pathways [72]. Haloperidol and risperidone in-hibited and promoted, respectively, the growth of NSCs inthe long-term treatment study [52]. Moreover, this led to dif-ferential levels of 12 proteins altered by the haloperidol treat-ment and 14 proteins changed in response to risperidone.Comparing the different treatment groups showed that twoproteins were changed in common. [52] From this finding,the authors suggested that at early stages the mechanism ofboth drugs display a common mode of action but as the treat-ment progresses their actions become opposite to each other.While haloperidol promoted growth and induced changes inproteins associated with oxidative stress and apoptosis cas-cades, risperidone treatment led to activation of growth andmetabolism pathways [52]. Again, both of these pathwaysare known to be disrupted in schizophrenia [74]. Neverthe-less, further studies should investigate whether or not suchchanges are favorable with respect to these pathways, whichcould pave the way for future studies aimed at co-targeting


122


Tabl

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Sum

mar

ized

diff

eren

tially

expr

esse

dpr

otei

nsm

ore

exte

nsiv

ely

veri

fied

inin

vitr

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r,in

vivo

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alm

odel

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hum

ansa

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sych

otic

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t

Acc

essi

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nipr

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n(d

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lar

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tion

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logi

calp

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atio

n↑

Up-

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lture

s

P079

00H

SP

HS

P90

-alp

haC

ytop

lasm

Prot

ein

met

abol

ism

↑A

ripi

praz

ole

[51]

Q91

ZN1

Cor

onin

-1A

Cyt

opla

smC

ellg

row

than

dm

aint

enan

ce↑

Hal

oper

idol

[60]

P237

85G

ranu

lins

Sec

rete

dC

ellc

omm

unic

atio

nan

dsi

gnal

ing

↑H

alop

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ol[6

0]O

7044

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sin-

3C

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icat

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g↑

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[60]

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876

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↑H

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0]Q

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in(S

PAR

C)

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row

than

dm

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ce↑

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[72]

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090

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ing

3C

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mun

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Hal

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[72]

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987

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ctor

p47

Cyt

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nm

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m↑

Hal

oper

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[72]

P478

19G

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ary

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FAP)

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row

than

dm

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ce↑!

↑H

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[72]

↓H

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2]P4

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synt

hase

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e[7

2]

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d-de

rive

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fact

orS

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ted

Cel

lgro

wth

and

mai

nten

ance

↑!↑

Hal

oper

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/ri

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e[5

2]

P041

77Ty

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eC

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mun

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sign

alin

g↑

Hal

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[52]

P115

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Mem

bran

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row

than

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aint

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ce↓

Hal

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[52]

P164

46Ph

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nal

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Cyt

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ellg

row

than

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aint

enan

ce↓!

↓H

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ol/

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one

[52]

P115

05C

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e1

Mem

bran

eC

ellg

row

than

dm

aint

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ce↓

Hal

oper

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[52]

Inan

imal

mod

els

P047

97G

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phos

phat

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hydr

ogen

ase

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sman

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ucle

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ergy

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ated

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Mem

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9]Q

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in-1

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cell

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mun

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lanz

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e[5

9]

P108

60G

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mat

ede

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1,m

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ial

Mito

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Prot

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met

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ism

↑O

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l[6

2]

P146

69A

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3M

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[62]

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[62]

P026

88M

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and

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5146

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and

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0517

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ble

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m↑

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and

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[62]

(Con

tinue

d)


123


Tabl

e1.

Con

tinue

d

Acc

essi

onU

nipr

otPr

otei

n(d

escr

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n)C

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lar

loca

tion

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logi

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n↑

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regu

latio

n↓

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n-re

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tion

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efer

ence

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BU

2Pr

otei

nN

DR

G2

Cyt

opla

smC

ellg

row

than

dm

aint

enan

cean

dce

llco

mm

unic

atio

nan

dsi

gnal

ing

↑O

lanz

apin

e[6

2]

P050

65Fr

ucto

se-b

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osph

ate

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lase

AC

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gyM

etab

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m↑

Ola

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and

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[62]

Q9Z

0W5

Prot

ein

kina

seC

and

case

inki

nase

subs

trat

ein

neur

ons

prot

ein

1C

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lasm

Cel

lgro

wth

and

mai

nten

ance

↑O

lanz

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ean

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lope

rido

l[6

2]

P057

08H

exok

inas

e-1

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gyM

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olis

m↑

Hal

oper

idol

[62]

Q5P

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0N

euro

calc

in-d

elta

Cyt

opla

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dse

cret

edC

ellc

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unic

atio

nan

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gnal

ing

↑C

loza

pine

[61]

O08

838

Am

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nC

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lcom

mun

icat

ion

and

sign

alin

g↑

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and

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dol

[62]

P107

19A

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ial

Mito

chon

dria

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gym

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olis

m↑

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nzap

ine

and

halo

peri

dol

[62]

P215

75D

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in-1

Cyt

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smTr

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ort

↑O

lanz

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e[6

2]

Inhu

man

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ples

P495

88A

lani

ne–t

RN

Alig

ase,

cyto

plas

mic

Cyt

opla

smPr

otei

nm

etab

olis

m↑

Ola

nzap

ine

[64]

O00

499

Am

phip

hysi

nII

Mem

bran

eS

igna

ltra

nsdu

ctio

n↑

Flup

hena

zin

equi

vale

nts

[122

]

P026

47A

polip

opro

tein

A-I

Sec

rete

dLi

pid

met

abol

ism

and

tran

spor

t↓

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orpr

omaz

ine/

cloz

apin

e[1

12]

↑R

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ne[5

0]Q

8IV

L8C

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xype

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ase

OC

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lasm

Prot

ein

met

abol

ism

↑O

lanz

apin

e[6

4]P2

8290

Cle

avag

esi

gnal

-1pr

otei

nC

ytop

lasm

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lgro

wth

and

mai

nten

ance

↑O

lanz

apin

e[6

4]Q

1401

9C

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-like

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smPr

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nm

etab

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m↓

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desc

ribe

d[1

20]

P490

05D

NA

poly

mer

ase

delta

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nit2

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leus

Prot

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met

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ism

↑O

lanz

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e[6

4]Q

9UG

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in-B

Sec

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than

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ce↑

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ine

[64]

P231

42Fi

bulin

-1S

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ted

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mai

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ance

and

cell

com

mun

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[64]

P099

72Fr

ucto

sebi

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ergy

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↑Fl

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22]

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794

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tone

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m↑

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peat

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tain

ing

prot

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and

mai

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ance

↑O

lanz

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e[6

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0467

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ecifi

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embr

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Cel

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and

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and

tran

spor

t↑

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[64]

Q9H

720

PGA

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Cel

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and

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↑O

lanz

apin

e[6

4]


124


such pathways in personalized medicine strategies. For ex-ample, those patients who present an inflammatory profile[75] may respond better to haloperidol, while those who have aperturbed energy metabolism profile [76] may respond betterto risperidone.

Clozapine is one of the most used antipsychotics inclinical practice. Even though use of this drug is asso-ciated with fewer EPS, it is known to cause other se-vere side effects such as alterations in lipid and glucosemetabolism, oxidative stress, postural hypotension and tachy-cardia, sedation, seizures, weight gain, and agranulocytosis[77, 78].

Despite these advancements in knowledge on clozapine´smechanisms of action, there is still considerable researchto be carried out if we are to explain the biological mech-anisms underlying the side effects. One proteomic studyusing a 6-iodoacetamide fluorescein label showed that cloza-pine treatment in SKNSH neuroblastoma cells induced ox-idation of proteins involved in energy metabolism [79]. Alltogether, five proteins were identified which were mitochon-drial ribosomal protein S22, mitochondrial malate dehydro-genase (MDH), calumenin, pyruvate kinase, and 3-oxoacidCoA transferase [79]. The authors suggested that protein oxi-dation could be a mechanism by which atypical antipsychoticsas clozapine increased the risk for metabolic alterations [79].The same group also used a similar proteomic approach inorder to identify specific proteins oxidized after clozapinetreatment in lymphoblastoid cell lines obtained from patientswith schizophrenia and normal controls [80]. This resulted inidentification of seven proteins with increased oxidation inresponse to the clozapine treatment and these were enolase,triosephosphate isomerase, glyceraldehyde-3-phosphate de-hydrogenase (GAPD), Rho GDP dissociation inhibitor (GDI),cofilin (CFL), uridine monophosphate/cytidine monophos-phate (UMP-CMP) kinase, and translation elongation factor(EEF) [80]. Baig and collaborators also discussed the pointthat several of these proteins play important roles in energymetabolism and mitochondrial function, and suggested thatthe results could support the oxidative stress hypothesis asthe mechanism by which antipsychotics increase the risk ofpatients developing metabolic syndrome or type 2 diabetesmellitus [80]. In a different proteomics approach, Martins-de-Souza and collaborators reported the action of clozapineon astrocyte cells following treatment with MK-801, an N-methyl-D-aspartate glutamate receptor antagonist [81]. Thisshowed that clozapine treatment caused differential levels ofeight proteins, most of them associated to cell growth and/ormaintenance [81]. Two of the identified proteins were theactin subunits beta and gamma. Both were found to be dif-ferentially expressed in previous proteomic studies which an-alyzed postmortem human brain tissue from schizophreniapatients [82, 83]. These changes could indicate the effects ofmedication on schizophrenia patients treated chronically withantipsychotics. Moreover, clozapine treatment was found toreverse the protein changes induced by MK-801 treatment[81].

Many of the studies described above indicate that it ispossible to develop relevant cell models of schizophrenia. Inaddition, the combination of these models with protein-basedbiomarker readouts of drug efficacy should allow testing ofnovel drug candidates. It is interesting that most of the mod-els showed changes in the levels of glycolytic enzymes andthese signatures were at least partly normalized after applica-tion of currently used antipsychotic drugs. However, success-ful models will most likely require incorporation of additionmarkers such as those involved in synaptic strengthening.Thus, further studies are warranted to select the most ro-bust models and biomarker profiles for up-scaling into high-throughput formats to support drug discovery efforts.

4.2 Findings in animal models

Animals are employed largely in preclinical research to modelthe pathogenic mechanisms of the disease in question andfor initial drug trials. When dealing with psychiatric disor-ders, the translation of animal model findings to humans iscomplicated by the fact that these are multifaceted diseasesand there are no existing models capable of recapitulating allof these aspects [84,85]. Also, most models for psychiatric dis-orders rely on changes in behavior and none can recapitulateall behaviors. For example, there are no techniques that canbe used to determine the emotional state of an animal andthis is something that will probably never happen with anycertainty. Thus, use of these models should be undertakenwith a degree of caution.

Proteomic studies of rodent brain tissues after exposureto antipsychotics have led to identification of differentiallyexpressed proteins associated mainly with presynaptic func-tion [59], the cytoskeleton, calcium regulation, signal trans-duction [52] and mitochondrial energy production and ox-idative stress pathways (Supporting Information Table 2;Fig. 1) [52, 54]. All of these pathways have been found tobe disrupted in schizophrenia and antipsychotics appear tohit the same pathways, in some cases appearing to have anormalizing effect on the component proteins. Proteomicanalysis of the hippocampus from chlorpromazine-treatedmice revealed the downregulation of dual specificity mitogen-activated protein kinase kinase 1 (MP2K1) and the mito-chondrial proteins MDH, peroxiredoxin 3 [56]. While MDHacts on energy metabolism through facilitating conversionof malate into oxaloacetate, peroxiredoxin 3 acts on path-ways involved in protection against oxidative damage [56,86].The same study reported several proteins changes associatedwith chronic clozapine treatment, such as the downregula-tion of MDH and V-ATPase subunit B 2 (VATB2) from theV1 complex of vacuolar ATPase [56]. Chronic treatment ofrats with risperidone also had an impact on mitochondrialprotein levels [53, 61]. For example, the levels of mitochon-drial creatine kinase (uMiCK), mitochondrial ATP synthase! chain (MiATPase !), and cytochrome c oxidase were alldecreased [55]. The uMiCK protein is a reversible catalyst of


125


Figure 1. Biological process associated with protein differentialexpression following antipsychotic treatment. The percentagesof differentially expressed proteins were based on the numberof proteins belonging to each biological process in relation tototal number of proteins described in literature (see SupportingInformation tables for detailed lists of proteins and the associatedbiological classes).

transport system creatine/phosphocreatine, responsible forthe fast regeneration of ATP, which has been correlated withthe energy requirement and synaptic density [87]. Further-more, this enzyme is important in maintaining the functionand structural integrity of mitochondria [88]. The MiATPase-! and cytochrome c oxidase proteins are part of the elec-tron transport system and the downregulation of these en-zymes is associated with induction of oxidative damage, asseen in Alzheimer disease [89]. Treatment with other drugssuch as clozapine, chlorpromazine, and quetiapine also ledto changes in abundance of mitochondrial proteins associ-ated with cell respiration and oxidative damage, as shownby Ji and collaborators [54]. Proteomic analyzes revealed thatchronic treatment of rats with these drugs led to quantitativechanges in the levels of NADH dehydrogenase [ubiquinone]1 alpha subcomplex subunit 10 (NDUFA10), NADH dehy-drogenase (ubiquinone) flavoprotein 2 (NDUFV2), NADHdehydrogenase (ubiquinone) Fe-S protein 3 (NDUFS3), ATPsynthase beta subunit (ATP5B), V-type proton ATPase sub-unit B, brain isoform (ATP6V1B2), and V-type proton AT-Pase catalytic subunit A (ATP6V1A1), which are involved inmitochondrial oxidative phosphorylation [54]. In addition tothe mitochondria proteins, studies have shown that treat-ment with antipsychotics alters the abundance of enzymesinvolved in glycolysis and gluconeogenesis [53, 55]. O’Brienand collaborators [53] showed that chronic treatment of ratswith risperidone led to decreased levels of the three glycolyticenzymes triosephosphate isomerase, phosphoglycerate mu-tase 1 and aldolase C (ALDOC). These findings were con-sistent with those observed by Ji and collaborators [53]. Theauthors found that chronic treatment of rats with clozapine,chlorpromazine, and quetiapine led to alterations in the levelsof the glycolysis/gluconeogenesis enzymes phosphoglyceratemutase 1, pyruvate kinase M2, and alcohol dehydrogenase[NADP(+)] (AKR1A1). The finding that enzymes associatedwith these pathways have also been implicated in the pathobi-

ology of schizophrenia provides confirmation that the abovetreatments may at least partially target disease relevant path-ways [15, 74, 82, 90–92].

Despite the conclusions of some proteomic reports sug-gesting that glycolysis is the main altered pathway inschizophrenia [93], antipsychotic treatment seems to affectmitochondrial processes to a greater extent, as describedabove [94–96]. This is seen by the large number of effectson mitochondrial proteins such as those involved in oxidativephosphorylation. Further studies will be required to confirmwhether or not some or all of these are part of the therapeu-tic mechanism or if they are associated with the metabolicside-effect profiles of antipsychotic drugs.

Proteomic studies of cerebral cortex from rats treated withclozapine and risperidone revealed changes in abundance ofproteins associated with the cytoskeleton and cellular orga-nization [58]. The main changes were found in collapsin re-sponse mediator protein (CRMP) family, and the risperidoneand clozapine treatment led to downregulation of the phos-phorylated form of CRMP2 and CRMP4 and upregulationof the CRMP2 dephosphorylated form, which has been as-sociated previously with schizophrenia [97]. These proteinsare essential for stabilization of microtubules as well as foraxon and dendrite development, besides acting on several ex-tracellular signaling processes. The phosphorylation of theseproteins has an important regulatory function, besides pre-venting the association CRMP2 with tubulin [58]. Differenceson the levels of proteins associated with cellular organizationwere also found in the CNS of rats treated chronically withhaloperidol and olanzapine. Microtubule-associated protein2 and microtubule-associated protein tau were found to beupregulated in haloperidol-treated rats and tubulin beta-2Cchain (TBB2C) was increased in olanzapine-treated rats. Cy-toskeleton proteins are pivotal for the structural maintenanceof the CNS [59]. Changes in the expression levels of theseproteins might be consistent with the neurodevelopmentalhypothesis of schizophrenia that suggests the abnormal de-velopment of neuronal structure in schizophrenia brains, par-ticularly in the hippocampus and prefrontal cortex [98]. Fur-thermore, the effects of antipsychotics on cytoskeletal andsynapse-related proteins are consistent with the fact thesedrugs are known to target neurotransmitter systems. Thus,many of the effects on the individual proteins could be used asbiomarkers of changes in neurotransmitter-related synapticremodeling in future drug discovery studies.

Chronic clozapine treatment may also act on calcium fluxsignaling according to a study in the cerebral cortex of rats.Visinin-like protein-1 and neurocalcin delta, which act ascalcium sensors in regulating neuronal signal transduction,were found to be upregulated in rats treated chronically withclozapine [58]. The mechanism of action of risperidone ap-pears to be similar as chronic treatment with this drug led toupregulation of the annexin V protein in the striatal tissue,and this protein forms voltage-dependent calcium channelsin all membranes of the body [53]. Again, these effects couldrepresent a reversal of disrupted Ca2+ signaling pathways in


126


schizophrenia, as indicated above in the cellular models sec-tion. Synaptic vesicle associated proteins are also affected bytreatment with clozapine and risperidone as suggested by thefact that both drugs resulted in a downregulation of vesicle-associated membrane protein 2 [58], which has a key rolein vesicle fusion and exocytosis [99]. Furthermore, clozapinetreatment led to downregulation of septin 8 [58], which par-ticipates in the formation of the SNARE complex and subse-quently in the reuptake of neurotransmitters [100]. Treatmentwith other antipsychotic drugs such as paliperidone have beenfound to alter the abundance of the serine/threonine-proteinphosphatase PP1-alpha catalytic subunit (PPP1CA), tubu-lin beta-2B chain (TUBB4B), and glyceraldehyde-3-phosphate(GAPDH) [101].

It should also be considered that antipsychotic treatmentcan influence the PTM of synaptic proteins, which may affecttheir regulation. With this in mind, Ma and collaborators ana-lyzed the cerebral cortex of haloperidol and olanzapine chron-ically treated rats and found lower levels of synapsin-1 (SYN1)in the membrane of synaptic vesicles with a concomitant in-crease of this protein in soluble fraction [59]. From this, theauthors hypothesized that the antipsychotic treatments mayhave altered SYN1 PTM, resulting in its translocation acrossthe membrane and soluble compartments [59]. SYN1 is regu-lated by phosphorylation (Swiss-Prot), and other studies haveshown that its translocation is regulated by phosphorylationof other protein partners [102, 103].

Studies performed by Ji and collaborators showed thatchronic treatment with clozapine, chlorpromazine and que-tiapine, altered the expression levels of proteins related toG protein signal transduction in rats. Guanine nucleotide-binding protein G(i), alpha-1 subunit (GNAI1), alpha-2 sub-unit (GNAI2), septin 4, septin 5, syntaxin-binding protein 1and GTP-binding nuclear protein Ran (RAN) were the mostsignificantly affected [54]. Again, this may represent a reversalof the known effects on G-protein receptor signaling whichappears to be disrupted in schizophrenia. Chronic treatmentwith risperidone also leads to changes in proteins associatedwith cell proliferation and communication, such as upreg-ulation of fatty acid-binding protein (FABP7) and translin-associated protein X and downregulation of thy-1 membraneglycoprotein (THY-1) [58]. FABP7 acts on the migration andproliferation of astrocytes [104] and translin-associated pro-tein X is involved in normal cell proliferation, while THY-1is important in communicating neuron/astrocyte, inhibitingneurite outgrowth and promoting retraction of neuronal pro-cesses [105, 106]. Moreover, proteomic analysis of the hip-pocampus of rats treated with clozapine and olanzapine re-vealed increased levels of other proteins such as transthyretin[63]. This protein has been associated with the transport ofthyroxine and retinol to brain cells [107], and the sequestra-tion of !-amyloid proteins in cerebrospinal fluid inhibitingthe formation of amyloid fibrils in the brain and blood vessels[108]. These data indicate that the retinoid signaling pathwaymay be involved in the therapeutic mechanism of atypicalantipsychotics (Fig. 1) [63].

Research also shows that chronic treatment of rats withrisperidone may influence glutamate metabolism in the CNSby upregulation of glutamate transporter 1 in the cerebralcortex [58] and downregulation of hippocalcin in the stria-tum [53]. The glutamate transporter 1 located in membranecatalyzes the entry of glutamate into astrocytes, playing animportant role in the metabolism of this amino acid [109],and the hypocalcin acts in controlling the release this neu-rotransmitter by exocytosis [53]. It should be noted that bothprocesses are important for maintaining the concentration ofextracellular glutamate below neurotoxic levels and enablingcell communication through its neurotransmitter activities.Risperidone treatment has also been found to increase abun-dance of the protein dystrophin-related protein 2 in rat stria-tum. The dystrophin-related protein 2 protein is involved inthe repair of damaged neurons and in the maintenance ofneural networks [110]. Thus, these data are consistent withthe downregulation of hypocalcin, as the absence or repres-sion of this protein can lead to excessive glutamate releasecausing oxidative stress and neurodegeneration [53].

The proteomic studies described above indicate that thesame drugs can affect proteins which are involved in manydifferent biological pathways. However, we suggest that thisis an expected result of proteomic analyses on brain tis-sues considering that both the disease and treatment inducechanges in neuronal tissue. This means that proteins involvedin synaptic remodeling and structure, and those involved inenergy metabolism are likely to be affected on a global scale.Furthermore, all of these pathways are actually connectedin a systems biology manner to support synaptic function-ing. It is not possible to determine whether or not all ofthe antipsychotic-induced changes are therapeutic responsesor side-effect related. This may be particularly true for themetabolism-related changes considering the strong link ofantipsychotics to metabolic side effects.

4.3 Findings in human studies

In contrast with the section on animal models, there havebeen no studies carried out to investigate the effects of an-tipsychotics using proteomics to analyze brain tissues fromliving human subjects. This is mainly due to the impracti-cal nature of such studies and argues for the use of cell- oranimal-based testing systems. Thus, most of the proteomicstudies looking at the effects of antipsychotic treatment havebeen carried out using either blood serum or plasma samples.With the emergence of experimental medical techniques inthe mid-1800s, studies of blood from patients with psychiatricillnesses were conducted in order to identify any chemical orphysical characteristics that could be useful for distinguish-ing sick people from healthy ones. Also, these investigationsproposed the searching of any natural disease entities thatcould classify such patients into clinical categories [111].

Proteomic reports about the action of antipsychoticson protein expression levels (Table 1) using blood sam-


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ples began to emerge around the year 2007, when La andcolleagues demonstrated that apolipoprotein A-I (ApoA-I)had significantly decreased levels [112] in blood samplesfrom schizophrenia patients treated separately with chlor-promazine or clozapine. The authors of the study suggestedthat reduced abundance of ApoA-I may be associated withthe pathology of schizophrenia and not necessarily with thetreatment. This was consistent with a reverse effect follow-ing the application of antipsychotics as healthy rats treatedwith chlorpromazine and clozapine displayed increased lev-els of ApoA-I [112]. This protein was suggested by Song andcolleagues to be a novel biomarker related to metabolic sideeffects in first episode schizophrenia treated with risperidone[50]. They found that ApoA-I was significantly increased inplasma samples from antipsychotic-treated schizophrenia pa-tients and this was correlated with increased plasma levels ofcholesterols and potentially other metabolic disturbances [50].ApoA-I is the major protein component of the high-densitylipoprotein complex in plasma and plays a role in the reversetransport of cholesterol from tissues to the liver for excretionby promoting cholesterol efflux from tissues and by acting asa cofactor for lecithin cholesterol acyltransferase [113].

Other investigations using blood samples investigated thepotential effects of antipsychotics on PTMs of serum proteins.A glycoproteomic study found that olanzapine treatment re-sulted in increased levels of a disialylated biantennary glycanand reduced levels of a number of disialylated bi- and tri-antennary glycans on whole serum glycoproteins, especiallyon !1 acid glycoprotein, from schizophrenia patients [65].However, the source of the olanzapine-induced glycan al-terations in the above study remains unclear. One possiblesource could be related to olanzapine-induced changes in theCNS although it is more likely the source of the glycan al-terations occurs from olanzapine’s actions in the periphery,altering the activity of liver enzymes which, in turn, resultsin altered glycosylation of proteins prior to their exocytoticsecretion by the actions of glycosyltransferases and glycosi-dases. In addition, potential changes in phosphorylation havebeen addressed in studies of schizophrenia blood samples.A number of studies have shown that blood serum phos-phoproteins are altered in schizophrenia patients [114, 115]although Jaros and collaborators investigated if serum phos-phoproteins were also changed in response to treatment witholanzapine. They found that the levels of 11 proteins were sig-nificantly changed in terms of overall abundance and therewere specific changes in phosphorylation of 45 proteins after6 weeks of antipsychotic treatment. The altered phosphopro-teins were mainly related to inflammatory response (acutephase), lipid and glucose homeostasis, retinoic acid signal-ing, and complement pathways. Again, it is not clear whetheror not these changes occur before or after secretion of theseproteins into the bloodstream.

Some studies have described that the brain and somewhite blood cells display a number of parallel responses inpsychiatric illnesses [116, 117]. Specifically, peripheral bloodmononuclear cells have been proposed as potential pre-

clinical models and as useful sources of disease or treat-ment biomarkers [118, 119]. Interestingly, peripheral bloodmononuclear cells express most of the functional neurotrans-mitter and ion channel receptors that are found in the brainas well as the intracellular signaling pathways which couplereceptor binding to cellular responses. This allows the use ofthese cells as a potential novel screening tool for drug profil-ing, using reporter systems linked to the activation of receptorsignaling cascades. Herberth and colleagues reported manydifferentially expressed proteins from PMBCs of first-onset,antipsychotic-naive and antipsychotic-treated patients [120].However, comparison of the chronically ill antipsychotic-treated patients with controls did not lead to identificationof any significant change in those proteomes suggesting thatprotein levels may be normalized by treatment with antipsy-chotic medications [120].

As appropriate, most of the MS-based proteomic studieshave focused on analysis of postmortem brain samplesfor understanding the pathophysiology of severe mentalillnesses, including schizophrenia [121]. With the aim ofcharacterizing the differential protein expression levels inthe DLPFC from 35 schizophrenia treated by antipsychotics,English and colleagues used 2D DIGE to profile proteinlevel changes in the brain. They found 70 protein spots tobe significantly altered between disease and control subjects,of which 46 were subsequently identified by LC-MS/MS[122]. Of these 46 proteins, fructose bisphosphate ALDOC,immunoglobulin superfamily, member 8 (IGSF8), andamphiphysin II (AMPHL) were significantly correlatedwith antipsychotic dose [122]. ALDOC has been shown tobe the most reproducibly altered protein in multiple brainregions from schizophrenia patients. Increased expression ofALDOC was detected in frontopolar region of frontal cortex(BA10) and in DLPFC (BA46), whereas decreased levels ofthis protein were observed in areas such as ventral anteriorcingulate cortex (BA24), anterior temporal lobe (BA38) andin posterior superior temporal gyrus (BA22) [74].

Finally, one study carried out an analysis of postmortembrain tissue from schizophrenia patients and controls whichpartially addressed the effects of antipsychotics. Chan andcolleagues found that many proteins were differentially ex-pressed in DLPFC from schizophrenia patients using alabel-free LC-MS-based proteomics approach and the au-thors suggested that some of these could be present be-fore and then normalized with the drug treatment [123].Overall, this study showed that the differentially expressedproteins in low-cumulative-medication subjects were asso-ciated with synaptogenesis, neuritic dynamics, presynapticvesicle cycling, amino acid and energy metabolism systems(Table 1; Fig. 1) [123].

5 Final remarks

In summary, we have reviewed the results of many pro-teomic studies that have been used to elucidate the effects of


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antipsychotic drugs on cells, tissues, and human samples.Many of these drugs are limited in their clinical potentialas they are associated with debilitating side effects. This is aconsequence of our incomplete understanding of their phar-macology and the signaling pathways regulated by them. Be-cause of the limited range of tools available to resolve theseissues, integrated approaches are required to fully understandthe pharmacological action of such drugs and the biochem-ical repertoire regulated their targets. Recently, a cohort ofschizophrenia patients had blood plasma collected before andafter 6 weeks of antipsychotic treatment and these have beenanalyzed by shotgun mass spectrometry. Results showed thatalthough all patients had essentially the same biochemicalpathways triggered by antipsychotic treatment, these wereregulated in different directions in patients who respondedwell to antipsychotics, compared with those who had a pooreroutcome [124].

Taken together, studies presented here and evaluated byCarboni and Domenici [125] have revealed the range of an-tipsychotic action upon many cellular processes includingthe therapeutic and nontherapeutic ones. For the proteomicanalyses of the antipsychotic-treated cellular and animal mod-els, there was an overlap of changes in synaptic, cytoskele-tal, Ca2+ flux, second messenger signaling, oxidation, andmetabolism-related proteins, and these pathways appeared tobe affected oppositely in the human schizophrenia studies.The cellular models showed changes in protein synthesis andthe mTOR pathways, which have also been reported in hu-man schizophrenia. Therefore, this finding should be inves-tigated further in the other model systems and tested furtherfor its relevance to the human disease state. The human stud-ies focused on analyses of serum or plasma in investigatingthe actions of antipsychotics. These showed increased levelsof ApoA-I in response to antipsychotic treatment and effectson glycosylation and phosphorylation of other proteins. Inthe case of phosphorylation changes, these mainly involvedproteins involved in the acute phase inflammation response,energy metabolism, retinoic acid signaling, and the comple-ment cascade.

There are proteomic techniques still to be explored inmolecular psychiatry research using different models of study(cellular or animal models), which may help to fill in the gapsin the current knowledge (Fig. 1). Subproteome analyses canbe employed to investigate different cell compartments. Inaddition, a particular pathway can be investigated for particu-lar posttranslational changes as a means of yielding potentialinsights into functional activation or deactivation using MS-based methods such as selected-reaction monitoring (SRM).This technique can be used to monitor quantitative changesin a given proteome or subproteome by using internal stan-dards for each targeted analyte. Integrating these methodsshould allow us to validate signaling pathways and to identifynew ones. Furthermore, these integrated approaches will con-tinue to provide valuable additional insights into the mech-anisms of antipsychotic action at therapeutic and nonthera-peutic targets, providing more complete understanding and

for revealing biomarkers of desirable and undesirable effectsof such drugs. We believe that these techniques, in combi-nation with others, are critical in the development of noveltherapies that are more pathway specific and efficacious withminimal off-target effects.

The ultimate aim is to translate the findings of proteomic-based biomarker studies into clinical practice. This will help toimprove the response of patients to antipsychotic treatmentsand will facilitate clinical development of novel treatment ap-proaches. A number of small-scale studies have now beencarried out showing that it is possible to stratify early onsetand even preonset patients with schizophrenia [126,127], ma-jor depression [128], and bipolar disorder [129]. Furthermore,other studies in schizophrenia have shown that it is possibleto predict which patients will respond favorably [130] or expe-rience metabolic side effects [131] to antipsychotic treatmentusing a biomarker readouts in baseline blood samples. In allcases, these require further validation using larger cohorts inmultiple clinical centers before they can be adopted in clinicalpractice.

J.S.C. and D.M.S. are funded by FAPESP (Sao Paulo Re-search Foundation, grants 2014/14881-1 and 2013/08711-3)and CNPq (The Brazilian National Council for Scientific andTechnological Development, grant 460289/2014-4).

The authors declare no conflict of interest.

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Proteomics Clin. Appl. 2016, 00, 1–11 1DOI 10.1002/prca.201600021

REVIEW

Proteomics and molecular tools for unveiling missinglinks in the biochemical understanding of schizophreniaJuliana M. Nascimento, Sheila Garcia, Veronica M. Saia-Cereda, Aline G. Santana,Caroline Brandao-Teles, Giuliana S. Zuccoli, Danielle G. Junqueira,Guilherme Reis-de-Oliveira, Paulo A. Baldasso, Juliana S. Cassoliand Daniel Martins-de-Souza

Department of Biochemistry and Tissue Biology, Laboratory of Neuroproteomics, Institute of Biology, University ofCampinas (UNICAMP), Campinas, Sao Paulo, Brazil

Received: April 18, 2016Revised: June 21, 2016

Accepted: July 14, 2016

Psychiatric disorders are one of the biggest burdens to society, with significant personal andeconomical costs. Schizophrenia (SCZ), among them, is still poorly understood, and its molec-ular characterization is crucial to improve patients’ diagnosis and treatment. The combinationof genetic, biochemical, and environmental factors leads to systemic alterations, which areyet to be fully comprehended. Thus, understanding those missing links by connecting somemolecular reports of SCZ is essential. From postmortem brain to animal models and cell cul-ture, new tools are emerging, including recent advances in proteomics, and there is a need toapply them to solve these problems. Here, we review some of those features, mainly related towhere proteomics could help, and discuss whether those new technologies could and shouldbe applied to psychiatric disorder studies.

Keywords:Biomarkers / CRISPR / iPSCs / MS / Schizophrenia / SRM

1 The molecular and biochemical basis ofschizophrenia

Psychiatric disorders are one of the biggest burdens to society,with significant personal and economical costs, being suchdebilitating illnesses [1]. These are responsible for almost30 years of life disability [2], which is more than double ofcardiovascular disorders burden. Understanding the molecu-lar complexity of these diseases is currently one of the majorchallenges faced in medicine. Despite all recent progresses ingenetic and environmental causes [3], schizophrenia (SCZ)is still poorly understood, mainly due to its complexity, com-posed of a combination of genetic, biochemical, and environ-mental factors.

Correspondence: Prof. Daniel Martins-de-Souza, Department ofBiochemistry and Tissue Biology, Laboratory of Neuropro-teomics, Institute of Biology, University of Campinas (UNICAMP),Rua Monteiro Lobato, 255, Campinas, SP 13083-862, BrazilE-mail: [email protected]

Abbreviations: CRISPR, Clustered Regularly Interspaced ShortPalindromic Repeats; hESC, human embryonic stem cell; hiPSC,human-induced pluripotent stem cells; NMDA, N-methyl-D-aspartate glutamate; NPC, neural progenitor cell; PCP, phency-clidine; SCZ, schizophrenia

SCZ is a severe, debilitating, and incurable mental disor-der, which affects 21 million people worldwide. Generally, itstrikes individuals in their late adolescence/early adulthood,even though its roots are in the neurodevelopment [4]. Thenonspecific symptoms of SCZ are as diverse as the multifac-torial characteristic of the disease itself, basically classified aspositive (hallucinations, delusions, and psychosis), negative(anhedonia and social retreat), and cognitive (disorganizedthinking and cognition impairment). SCZ diagnosis is stillstrictly clinical, with no molecular validation, often leading tosubjectivity and misdiagnosis. For instance, a clinical studyshowed that about 30% of bipolar disorder patients were ini-tially diagnosed with SCZ [5]. In addition, there is correlationof abnormalities in brain volume of patients with SCZ corre-lated with positive symptoms and it is responsible for corticalgray matter loss. It is in the first year of the disease that thelargest decrease in brain volume is observed. This is due to theuse of antipsychotics at the beginning of the treatment, whichprobably provide a neuroprotective role [6, 7]. This urges forthe identification of diagnostic biomarkers [8]. Those predic-tive biomarkers may also be significant in the early detec-tion and intervention of the disease, reducing severity. As

Colour Online: See the article online to view Fig. 1 in colour.


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2 J. M. Nascimento et al. Proteomics Clin. Appl. 2016, 00, 1–11

Figure 1. How can proteomicsaddress possible missing linksin schizophrenia puzzle?

important as those, biomarkers that could indicate a positiveresponse to medication are also needed [9].

Understanding SCZ from a molecular perspective is help-ful for the identification of biomarkers and the developmentof innovative and effective treatment strategies. In the past,the development of new medication was a rather empiricalscience. Nowadays, more effective medication target causesand symptoms based on the knowledge of the molecularmechanisms involved in a given disorder. Medications fortreating SCZ—and psychiatric disorders in general—are farfrom being effective, despite being the primary method ofdisease management. SCZ treatment is ineffective for about40% of the patients in a first moment. As a consequence,around 60% of the patients end up abandoning treatmentdue to severe side effects [10]. And this is due to the fact thatwe still lack in understanding this disorder from the molecu-lar point of view. The challenges listed above can be addressedby proteomics and other complementary techniques (Fig. 1)[11], as we discuss in detail below.

2 The relation genomics/proteomics

Within the “molecular comprehension of schizophrenia,” wemust consider the role of genetics, which is pivotal in causing

the illness. Lately, several common and rare variants, includ-ing risk loci, rare copy-number variants, and de novo muta-tions, have been identified using diverse genetic and genomictools [12]. In 2014, 108 genetic loci—83 novel ones—werefound to contribute to disease susceptibility [13], confirm-ing genetics as a major cause of SCZ. The identification ofrisk variants, and the products of genes involved, opened anew door for the understanding of SCZ [14]. These findingsconfirmed commonly targeted molecules, as dopamine re-ceptor D2 association, and other several genes involved inglutamatergic neurotransmission were found, in addition togenes involved in immunity [13]. More recently, component4 (C4) has been found to play a pivotal role in the braindevelopment and SCZ risk, due to its role in synaptic prun-ing, beyond its well-known role in the immune system. Thehigh variability of C4 explains its multitasking. After examin-ing the genome data from 65 000 individuals between healthycontrols and SCZ patients, researchers observed that a par-ticular structural form of the C4 gene drive its upregulationand consequently its higher risk of developing SCZ [15].

Although genetic and genomic studies have marchedsteadily toward the comprehension of the molecular basisof SCZ, there is still much to be done in the biochemical sce-nario. This is necessary, as genetics alone does not explainthe whole complexity of the disease in molecular terms.


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Using equally sensitive and accurate tools, although notas automated, proteomics has also contributed to looking atSCZ from a molecular point of view. All sorts of humantissues have been investigated, including postmortem brains[16,17] and liver [18], as well as blood cells and serum/plasma[19]. The proteome of SCZ have been also investigated usinganimal models [20], but despite some useful findings, giventhe complexity of the disease, these preclinical models presentmajor limitations [21]. Similarly limited are in vitro modelsusing cell lines. Those models can answer some questions[22–24], but techniques closer to the patient reality are stillessential.

3 Advances using stem cells

As previously noted, most of the molecular studies on psychi-atric disorders have been performed on postmortem tissues.However, the downside is that even if well preserved, thisapproach does not allow the observation of disease’s mecha-nisms on living cells, and oftentimes represents the tissueafter prolonged use of medication [25]. Furthermore, dis-orders such as SCZ and autism are considered to have aneurodevelopmental origin; this approach may not reveal thefundamental disease-related characteristics, and since post-mortem tissue represents the end stage of the disease [26].Therefore, stem cell technology is particularly significant forthe study of not accessible tissues as biopsies from livingpatients, making human embryonic stem cells (hESCs) andhuman-induced pluripotent stem cells (hiPSCs) importanttools for studying complex brain disorders [27].

Regarding hESCs, human embryos carrying specific mu-tations or chromosomal aberrations can be used as a sourceof ES cell models for monogenic or chromosomal disorders.Therefore, only a small range of disorders could generatedisease models in human ESC cells [28]. Advantageously,Yamanaka et al. discovered that differentiated cells could bereprogrammed back to a pluripotent state by the transduc-tion of four defined transcription factors (Oct3/4, Sox2, Klf4,and c-Myc), the resulting cells are known as iPSCs [29, 30].Therefore, iPSCs reprogrammed from human somatic cells(hiPSCs) were used to generate models of human multifac-torial disorders [31, 32]. This breakthrough opened new per-spectives for modeling and understanding human psychiatricdisorders, since they can differentiate into disease-affectedcell type and recapitulate the early steps of neuronal develop-ment, allowing the study of the cellular and molecular causesof neurodevelopmental disorders [25, 28].

Several concomitant studies generated hiPSC from SCZpatients and observed that there was no difference betweenfibroblasts and iPSCs of SCZ and control [33]. Nevertheless,neural progenitor cells (NPCs) and neurons from SCZ pa-tients showed features previously associated with the disor-der, such as diminished neuronal connectivity, together withdecreased neurite number, PSD95-protein levels, and gluta-mate receptor expression, relative to controls [33–35]. Gene

expression data indicated effects on pathways that have notbeen previously associated with SCZ, including notch sig-naling, cell adhesion, and Slit-Robo-mediated axon guidance[34]. In other studies of complex psychiatric disorder, such asbipolar disorder, hiPSCs were generated from members ofthe same family, two affected brothers and their unaffectedparents [36]. No significant difference was observed betweenthose hiPSCs, as previously observed in SCZ hiPSC [37, 38].Nevertheless, upon neural differentiation, bipolar disorder-derived NPCs exhibited phenotypic differences at the neuro-genesis level and expression of neuroplasticity genes, such asWNT pathway components and ion channel subunits [36].

Proteomic studies of brain tissues from patients have in-creased the understanding of the molecular pathways affectedin psychiatric disorders. While the use of brain tissue haslimitations, as stated before, it is important to also conductproteomic studies using hiPSCs, as an alternative to studybrain cells and their altered connections in psychiatric dis-eases. Likewise, as psychiatric disorders are considered tohave neurodevelopmental origin, the use of iPSCs could leadto new insights regarding the etiologies [39]. Microarray geneexpression and stable isotope labeling by amino acids in cellculture (SILAC) in quantitative proteomic MS analyses havebeen employed to compare control and SCZ hiPSC NPCs[40]. Changes in cellular adhesion and oxidative stress path-ways were identified [40], in addition to increased extramito-chondrial oxygen consumption and elevated levels of reactiveoxygen species, when compared to controls [33]. Suggestingthose SCZ hiPSC NPCs could help elucidate developmentalpathways potentially contributing to SCZ pathogenesis [40].

Another interesting model, which could address someof the questions on SCZ and other disorders, are cerebralorganoids [41, 42]. Those so-called minibrains are stem cellderived tissues that are cultured in conditions that stimu-late spontaneous differentiation of different neural cell types,including nonneuronal such as glial cells, and recapitulatesome human brain development features [43].

The use of iPSCs combined with proteomics techniquesmakes it possible to investigate protein content at a givenstage of cellular differentiation and at a subcellular level [39].Some reports show that alterations in mitochondrial phys-iology contribute to the onset of psychiatric disorder, suchas SCZ and bipolar disorder [44–46]. The relation betweenthe disorders and mitochondrial dysfunction has not beenidentified [47]. Therefore, the possibility of studying proteindistribution in the organelle, as the cell differentiates, couldshed light on disorder’s mechanisms and bring new insightsconcerning drug response and potential biomarkers [39].

The use of hiPSCs to model psychiatric disorders is recent.Therefore, due to sample size, findings are still preliminaryand phenotypes described may not be observed across allpatients [40]. This model presented promising results andit is important that new studies aim on larger samples toachieve statistical robustness. In addition, it could bring abetter translation of proteomic findings to clinical applica-tions. An important ambition regarding this approach is to


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be able to find, develop, and validate diagnostic biomarkers.Hence, allowing the possibility to develop a test to diagnosepsychiatric disorders in the future [48]. Also, as these cells canbe obtained directly from patients, proteomic profiling of thecell in disease or in response to drug treatment could lead to abetter understanding of disease mechanisms. Future studiescould lead to the development of new therapeutic drugs andto a more personalized medicine, increasing the chance ofpositive treatment outcomes [28, 39]. Additionally, by havingthese hiPSCs in culture, technologies to modify them genet-ically can be helpful to test new hypotheses and medication.

4 Gene editing: Use of ClusteredRegularly Interspaced ShortPalindromic Repeats

Gene editing mechanisms have been employed in recentdecades in order to modify specific genes and provide newperspectives in the modeling of syndromes and diseasesassociated with genetic alterations [49]. Clustered RegularlyInterspaced Short Palindromic Repeats (CRISPR) is a geneediting mechanism based on an immune mechanism used bymany bacteria in the protection against infections by exoge-nous nucleic acids, which was first identified in Escherichiacoli in 1987 [50, 51]. This system consists of the repetitionof small noncontiguous DNA palindromic sequences gen-erally close to the gene of a caspase (Cas 9 in CRISPR II)[52, 53]. And between these sequences is possible to incorpo-rate small sequences of exogenous DNA [53]. The transcriptsstarting these sequences, crRNAs can hybridize to a secondRNA called transactivation RNA CRISPR (tracrRNA). Thesetwo hybridized RNA can form a complex with the nucleaseCas 9, which guided by crRNA can recognize a target DNAsequence and cleave it [53].

It is important to highlight that genetic control systemshave been a major breakthrough in the study of gene func-tion and understanding of pathophysiological mechanismsof several diseases. Thus allowing, in addition to phenotypicanalysis, the study on the molecular level of organisms andcells that have undergone genetic edition. Hence, this type oftool has been very useful in understanding complex diseasessuch as neuropsychiatric disorders.

Although animal models are being used for decades in thestudy of psychiatric disorders [54], with undeniable contri-bution to clinical research trials and psychopharmacologicalstudies [55], there is a major criticism regarding the applicabil-ity of these models on human diseases [56], especially in mul-tifaceted diseases, such as psychiatric disorders [21]. Thus,lacking biological support correlating neurological changesobserved in animals with the complex mechanisms of thehuman brain [54]. In this scenario, genetic edition modelsare gaining space and reliability. Beyond allowing specificmolecular analysis, when applied to human cell models, itmay render important information in terms of cellular com-

munication. This information can be collected from both thecellular body and the culture media.

5 Exosomes

Exosomes are nanovesicles of approximately 50 nm diameterthat are released from different cell types, such as neural,epithelial, and muscle cells [57]. They are found in many bio-logical fluids, such as plasma, urine, malignant effusions,breast milk, saliva, and synovial fluid [58]. These vesiclescan be originated from the fusion of multivesicular bodieswith the plasma membrane or can be released directly fromthe plasma membrane [59]. Cells secret exosomes in physio-logical and pathological conditions [60]. They can be distin-guished from other vesicles by their density, size, high levelsof sphingomyelin, cholesterol, and GM3 glycolipid [58].

Despite different possible cells origins, exosomes havea conserved set of proteins that can be identified by pro-teomic analysis [58]. These vesicles have in common tubulinand actin, which are proteins from the cytoskeleton; Hsp70and Hsp90, which are heat-shock proteins; kinases and het-erotrimeric G proteins, proteins related with signal transduc-tion; Flottilin-1, Rab, involved in cell migration [61]. In ad-dition, exosomes contain specific compounds related to thecells they are derived [61].

Exosomes play many roles, such as elimination of un-wanted proteins, cell signaling, and communication, trans-port, and transfer molecules [61]. It had been proposed thatthese vesicles can execute their functions by internalizationby target cells, binding to the cell surface, and triggeringsecond messenger pathways, releasing components withinthe extracellular matrix [57]. Ligands in the exosomal mem-brane are associated with the target cells [60].

Cells in the CNS, such as neurons, astrocytes, and oligo-dendrocytes, release microvesicles as exosomes. These vesi-cles can be associated with pathogenic proteins and thedevelopment of neurological disorders [61]. The content ofthese nanovesicles can change in response to different exter-nal stimuli and stages of development of the nervous system.So, identification of its cargo is essential to determine theroles of exosomes in the CNS, as the loading, release, andformation of the exosomes may also vary in the apical andbasal sides of polarized cells such as neurons [62].

In brain diseases, such as Alzheimer’s and SCZ, vesiclescan transport molecules related to the development of thedisease. These include exosomes, which may carry mutatedor misfolded proteins related to the disease pathology [59],and other molecules, such as miRNA. Indeed, differentiallyexpressed miR-497 in prefrontal cortex exosomes of patientswith SCZ and bipolar disorder is related to neurodegenerativeand heart diseases [63].

Exosomes are potential biomarkers and diagnostic tools,because these vesicles can carry molecules related to the de-velopment of pathologies. Also, they may be used as a way fordelivering molecules to determined tissues [58]. However, it is


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necessary to improve and standardize isolation and purifica-tion protocols to allow comparison between different studies.In the last few years, the number of articles published on exo-somes increased considerably, showing the crescent interestof understanding and exploring the potential of these vesi-cles [57]. The information carried by exosomes may unveilinformation on neurotransmitter systems, which are majorlyinvolved in SCZ pathogenesis, and the physiological stateof cells that release them. Integrating exosome isolation andproteomics should allow signaling pathways validation, in ad-dition to identifying new altered pathways in SCZ. Further-more, these integrated approaches will continue to providevaluable additional insights into the mechanisms of such dis-order, providing more complete understanding and revealingpossible biomarkers.

6 Exploring the glutamatergictransmission

Glutamate is the most abundant amino acid in the brainand plays a key role as a major excitatory neurotransmitter.Dysfunction of its major receptor subtype, ligand-gated ionchannel N-methyl-D-aspartate glutamate (NMDA) is the basisof the glutamatergic hypothesis of SCZ [64, 65]. Evidencesincreased due to chronic and excessive use of phencyclidine(PCP), an antagonist of the NMDA receptor [66]. The firststudies on the effects of PCP compared other psychogenicdrugs, such as lysergic acid diethylamide and mescaline, aswell as sleep deprivation and sensory isolation. However, thesymptoms produced were similar to those seen in SCZ, suchas positive, negative, and electrophysiological symptoms [67].

PCP-like drugs, which act as NMDA receptor antagonists,are known as psychotomimetic. There are different struc-tural PCP classes, such as benz(f)Isoquinolines, 2-methyl-3,3-diphenyl-3-propanolamine , and dizocilpine (MK-801), whichshare the same properties and binding site as PCP. Amongthe above-mentioned classes, MK-801 represents the mostpowerful antagonist of the NMDA receptor [67]. MK-801 gen-erally binds to NMDA receptor, preventing the flow of ions,such as calcium (Ca2+), and has been used to stimulate SCZ-like symptoms and effects in preclinical models [22].

NMDA antagonists, such as MK-801, are able to induceon animal models cognitive deficits and negative symptomssimilar to SCZ [68]. Adult rats treated with MK-801 had amemory deficit in the test of recognition of objects, in whichthe animals were assessed for their ability to discriminatebetween an old, familiar object, and a new one [69]. However,NMDA antagonists can not only be applied to animal models,but also to cell culture, as study models for SCZ.

Proteomic studies of postmortem brain tissue from SCZpatients demonstrated that changes in the activation of theglycolytic metabolism and energy are common [70]. The treat-ment of neuronal cell lines, astrocytes and oligodendrocyteswith MK-801 [22], resulted in changes in all analyzed gly-colytic enzymes in all cell types. Albeit NMDA antagonist

model does not contain genetic approaches to the disease,animal models and cell culture treated with neurotransmitterantagonists may contribute to elucidate the pathophysiologyof SCZ and assist in the discovery of new drugs and theirmechanisms of action.

Studies involving the glutamatergic system in SCZ havesuggested this system should be targeted by new and moreeffective medication. The antipsychotics of first generationare effective in reducing positive symptoms, such as hallu-cinations. However, they are less effective in patients withnegative and cognitive symptoms, which contribute to mostof the deficiency associated with SCZ. Furthermore, they arealso less effective when compared to the second generation,being often associated with recurrence and poorer qualityof life of SCZ patients [71]. The second generation of an-tipsychotic drugs is more effective regarding the reductionof negative symptoms, but also exhibits extrapyramidal sideeffects, weight gain, and sedation when compared to the firstgeneration of antipsychotic drugs [71, 72].

Recent studies demonstrated that addition of a second-generation antipsychotic in oligodendrocytes treated withMK-801 reversed the differential expression of proteins foundon MK-801-treated oligodendrocytes [24]. This reversal sug-gests proteins possibly associated with medication response.Since SCZ is a multifactorial disease with uncertain onset,the study of this disorder requires methods to investigate andelucidate its molecular mechanisms, involved in its patho-physiology. Thus, exploring glutamatergic inhibition throughproteomics allows gaining some insight into possible SCZbiomarkers and provides extra tools to investigate the molec-ular mechanisms of the disorder.

7 Biomarkers for an effective medication

Despite the efforts of scientists, there are still no biomark-ers for SCZ [19]. Researchers have been demonstrating theintrinsic correlation between blood stream and brain due todynamic change in compounds from plasma to tissues andcontrariwise. Evidence shows that cholesterol levels and pro-teins associated with transport, such as apolipoproteins, areunregulated in patients with psychiatric disorders [73]. Inaddition, hormones, inflammatory cytokines, and growth fac-tors altered in SCZ patients are found in both blood and brain,strengthening the hypothesis that blood samples are goodtools to discover potential prognostic and predictive biomark-ers [19, 74, 75].

Although many studies are focusing on elucidating thepathophysiology of SCZ, little has been done about the ef-fectiveness of treatment response of this disease [76–78]. Onthe other hand, the current framework of SCZ treatmentdemonstrates that a significant proportion of patients do notrespond to treatment, which causes strong side effects andabandonment of treatment [79]. Therefore, finding biomark-ers for drug effectiveness is essential to avoid trial and errorin treatment choice.


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Molecular biomarkers for good response to treatmentare strongly studied within the field of pharmacogenomics.Nonetheless, this is still symbolic in SCZ research, despitegenomics showing promising results, mostly regarding vari-ations in drug-metabolizing (polymorphisms in cytochromeP450) and mitochondrial genes (NFS-1 and TYPE) [80, 81].

There are few studies in proteomics searching forbiomarkers in SCZ, and fewer are those distinguishing re-sponders to medication. An important study regarding theeffects of treatment with antipsychotics in human samplesassessed the cumulative effects of continued use of medica-tion in brain tissues of chronically treated patients, revealinga small group of candidate proteins that could be associatedwith medication [82].

Recently, using shotgun proteomics, a cohort of 116 bloodsamples of SCZ patients were collected before and after6 weeks of treatment and showed the same biological path-ways altered, in opposite directions, between good and badresponders [9]. These data are unprecedented and providenew insights regarding the response to treatment of patientswith SCZ.

8 Proteomic tools yet to be moreexplored in SCZ research

8.1 Protein “modificomics” and phosphoproteomics

Primary sequence variations are mainly studied, indirectly,by deep RNA sequencing. Nevertheless, in the last decade,with the great advance of MS instrumentation, proteomicanalyses can provide more direct and quantitative results.Many reports on how to perform fast and accurate proteomicworkflows have been released in the literature. Global PTManalysis is still very challenging and resource costly. Combi-nations of different and substoichiometric PTMs give rise tothe heterogeneity of the protein population. These turn PTMproteomic studies into a highly demanding task in order toachieve complete characterization and accurate quantitationof protein PTMs [83]. In addition, the difficulty to get clinicalsamples, such as brain tissues and blood samples of SCZpatients, further contributes to the scarcity of PTM studiesin neuropsychiatry. However, despite these barriers, morestudies about PTMs in proteomics must be performed.

Phosphorylation is the primary signaling used in animalcells. Few reports have focused in describing thoroughly dis-turbs in protein phosphorylation of SCZ samples. However,many phosphoproteins are involved in the pathophysiologyof psychiatric disorders, participating in the mechanism ofaction of currently used antipsychotics [70].

Although research employing phosphoproteomics in psy-chiatry is scarce, it was already demonstrated that SCZ pa-tients have abnormalities in serum protein phosphorylationpathways involved in coagulation and acute response [84].More recently, 68 differentially phosphorylated proteins werefound in corpus callosum of patient with SCZ [85]. This brain

region is responsible for communication between the twohemispheres [86], and according to morphological, electro-physiological, and neurophysiological studies, it is altered inSCZ patients [87–89]. Most phosphoproteins found altered inSCZ are related to pathways of communication and cell sig-naling, including ciliary neurotrophic factor signaling, mainlycomposed of cytokines [90]. The PI3K and mTOR proteins arealso associated with this pathway [91, 92], which is related tothe dysregulated function of synaptic plasticity in patientswith SCZ [93]. Synaptic plasticity is dependent on the con-nection between axons of neurons and astrocytes [94], thusevidences the role of phosphorylated proteins in the molecu-lar basis of the disease. In this way, further investigation ofthese specific phosphorylation changes may lead to a betterunderstanding of the molecular etiology of SCZ.

8.2 Protein interactomics

The modification of only one protein can drive a widespreadeffect of disturbances in the whole brain. This happens be-cause the brain consists of innumerous protein connectionswithin the billions of neurons we have. Considering that pro-teomics investigations revealed dozens of proteins differen-tially expressed, from studying postmortem brains of SCZpatients, may give an idea of the complexity of SCZ. Thus,understanding the interconnections proteins is a way to tracenew hypothesis to understand the disease from a molecularpoint of view.

The protein interactome can be defined as the completeset of molecular interactions of a given protein in a biolog-ical environment. This leads to a network, which promotesand regulates protein activity or expression. Protein interac-tomics can be performed using yeast two-hybrid screening,tandem affinity purification, as well as a combination of coim-munoprecipitation and shotgun MS. The large-scale charac-teristics of the latter allow the use of sophisticated compu-tational network analysis, and in combination with a strongand improved bioinformatics it could greatly contribute tonew understandings of functional interactions.

Gene and drug interactomes have been shortly explored,as well as protein interactomes in SCZ research [95, 96].The interactome of the disrupted in SCZ 1 (DISC1) pro-tein has been investigated, suggesting the importance ofthe coordinated expression of DISC1 and its interactors forthe normal functioning of prefrontal cortex-dependent cog-nitive functions [97]. A protein consistently found differen-tially expressed in SCZ, collapsin response mediator protein-2(CRMP2), is involved in several functions, as neuronal de-velopment, axonal growth, cell migration, and protein traf-ficking. By using a combination of coimmunoprecipitationand shotgun proteomics, 78 protein interactors of CRMP2were identified, unraveling its connections and involvementin SCZ [98].

Protein interactomics may suggest critical proteins andpathways associated with SCZ. Their analysis in a targeted


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manner could render novel biomarkers and drug targets foruse in drug discovery.

8.3 SRM or MRM

In proteomic analysis, a high accurate and precise quantifi-cation is important to ask a range of questions. These ques-tions can be about relative changes in protein expression insamples or absolute quantification, when the protein concen-tration is a key to solve the problem [99].

One of the main useful methodologies in these casesis the SRM, also called MRM. The SRM is a targeted MStechnique, which is used to detect and quantify a set ofinterest proteins, providing high accuracy, sensibility, andthroughput [100–102]. Differently of other techniques, asELISA and other immunoassays, SRM is not antibody de-pendent and has internal standards [103]. Due to such char-acteristics, the assay is able to avoid nonspecific interfer-ences, routinely multiplexed [104], and has synthesized stan-dard readily, allowing high interlaboratory reproducibility[105].

In general, a SRM analysis is performed using an HPLCsystem connected to a triple quadrupole mass spectrometer.The first quadrupole works as a mass filter and selects theprecursor ion of given m/z value. The second quadrupoleis a collision cell and induces the fragmentation of the pre-cursor ion to specific product ions (fragments). The thirdquadrupole is used as a second mass filter, selecting the spe-cific fragment. These selected product ions are received by adetector that counts their number over time, resulting in anMS peak associated with a specific chromatographic retentiontime and an intensity value [99, 102, 106].

Employing SRM on a preclinical model of SCZ, sevenglycolysis enzymes were compared under NMDA receptorblocking, PCP, in brain tissue of rats. Results have indicateddecreasing expression of triosephosphate isomerase (TPI1)and phosphoglycerate mutase 1 (PGAM1) in treatment, al-tering metabolic pathways in these brain tissues [107]. Al-terations of glutamate signaling protein expression in theauditory cortex of SCZ patients was also studied by SRM[108]. Quantifying 155 synaptic proteins in gray matter haveshown 17 differentially expressed proteins. Some of themwere connected to glutamate signaling pathway, which mayindicate a possible explanation to some positive symptomsof SCZ, as auditory hallucinations and cognitive impairmentphenotypes.

In addition, SRM was employed to search for biomarkercandidates in the sweat fluid of schizophrenic patients [109],which yield a specific set of proteins, and can be obtainedmore readily than other fluids. Among protein findings werecaspase 14, an apoptosis-related cysteine peptidase, whichmay be connected to neuronal apoptosis, also shown onpostmortem brain tissue studies. Caspase 14 alteration inthe pathophysiology of SCZ may be considered a potentialbiomarker for the disease.

Integrating SRM with other methods can offer new pos-sibilities of biomarker candidates for psychiatric disorders[110]. New biomarkers would improve the development ofnovel therapies, which could become more effective and spe-cific, decreasing side effects. Additionally, they could alsopredict desirable and adverse effects of such drugs, offeringpossible diagnosis and prognosis to the disease [111]. Finally,SRM MS is a technology that increasingly has become es-sential to quantitative proteomics due to its high accuracy,sensibility, and throughput. Besides, parallel reaction moni-toring analysis has received a great improvement due to thecombination of higher resolution and mass accuracy analyz-ers. In this approach, the quadrupole is first used to select arestricted m/z range. Then, MS/MS mode provides furtherselectivity and accuracy using the Orbitrap or TOF mass an-alyzer to achieve higher resolution and mass accuracy in allscanning modes [112]. With this, it is possible to detect allproduct ions of a peptide in parallel, rather than just fewtransitions per peptide. This allows an increased number ofpeptides to be quantitated in one experiment.

Consequently, the use of SRM or parallel reaction moni-toring approaches is essential to offer novel highlights aboutpsychiatric disorders mechanisms and novel biomarkers can-didates to clinical applications.

9 Conclusions

Classically, psychiatry is a discipline centered strongly onclinical outcomes. Nevertheless, in the past decades, psychi-atrists have assumed that psychiatric disorders, such as SCZ,are caused by molecular defects in the brain. More recently,it has been even accepted that peripheral tissues may reflectsuch defects in the precipitation and progression of theseconditions.

Genetics and environmental factors play an important rolein the establishment of SCZ, leading to differences in geneand protein expression. These have been rigorously studied,but there still are missing links as we discussed above thatmust be considered. Here, we shed light into some combina-tion of methods in different fields, in which interplay couldadvance and improve knowledge in SCZ.

Besides the fact that proteomics is not on the same level asgenetic/genomics technologies, this tool can back up the ap-proaches we proposed here toward the understanding of themolecular mechanisms of SCZ. Moreover, MS-based pro-teomics is capable of analyzing hundreds of samples andanalytes, which could be useful in biomarker candidate stud-ies. Targeted multiplex MS may be a reality using SRM, forinstance, and has still been poorly explored in SCZ studies inbiomarker candidate studies.

J.M.N., C.B.T., G.S.Z., J.S.C., and D.M.S. are sup-ported by Sao Paulo Research Foundation (FAPESP) grants2014/21035-0, 2015/23049-0, 2016/04912-2, 2014/14881-1,and 2013/08711-3. D.M.S. is also supported by the Brazilian


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National Council for Scientific and Technological Development(CNPq) grant 460289/2014-4.

The authors have declared no conflict of interest.

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DECLARAÇÃO

Eu, Aline Guimarães Santana, portadora do RG nº 48.173.711-x – SSP/SP, e do

CPF nº 394.327.688-05, solteira, residente na cidade de Campinas no endereço Rua

Plínio Aveniente, 148 – Bairro Jd. Stª Genebra II – Distrito de Barão Geraldo. Venho

por meio desta declarar que a pesquisa que desenvolvi durante o mestrado, a qual

resultou na dissertação intitulada “O papel do proteoma nuclear da substância

branca e cinzenta de cérebros de pacientes com esquizofrenia”, não versou sobre

pesquisa envolvendo seres humanos, animais, patrimônio genético ou temas afetos a

biossegurança.

Sem mais, por ser expressão da verdade, firmo a presente

Assinatura _____________________________

Autora: Aline Guimarães Santana

RG: 48.173.711-x

Assinatura _____________________________

Orientador: Daniel Martins-de-Souza

RG: 32.431.379-2

Campinas

20 de abril de 2017

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11.3 Anexo III - Declaração Comitê de Ética

Declaração

As cópias de artigos de minha autoria ou de minha co-autoria, já publicados ou submetidos para publicação em revistas científicas ou anais de congressos sujeitos a arbitragem, que constam da minha Dissertação/Tese de Mestrado/Doutorado, intitulada O papel do proteoma nuclear da substância branca e cinzenta de cérebros de pacientes com esquizofrenia, não infringem os dispositivos da Lei n.° 9.610/98, nem o direito autoral de qualquer editora. Campinas, 20/04/2017 Assinatura : __________________________________ Nome do(a) autor(a): Aline Guimarães Santana RG n.° 48.173.711-x Assinatura : __________________________________ Nome do(a) orientador(a): Daniel Martins-de-Souza RG n.° 32.431.379-2

146

11.4 Anexo IV - Declaração de Direitos Autorais

universidade estadual de campinas instituto de...

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