aletracao da microbiota gastrica em bypass yroux

7/29/2019 Aletracao Da Microbiota Gastrica Em Bypass YRoux

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DOI: 10.1126/scitranslmed.3005687, 178ra41 (2013);5Sci Transl Med

et al.Alice P. LiouHost Weight and AdiposityConserved Shifts in the Gut Microbiota Due to Gastric Bypass Reduce

Editor's Summary

the gut microbiota to influence host metabolic physiology.They suggest new approaches to the treatment of obesity and related metabolic diseases that harness the ability ofalterations in the gut microbiota contribute to the beneficial effects of bariatric surgery on energy balance and obesit

mice that received the microbiota from these operated animals. These observations demonstrate that specificwith changes in the production of short-chain fatty acids, changes that were conveyed to the previously germ-freeto nonoperated, germ-free mice resulted in weight loss and decreased body fat. Gastric bypass was also associatedto those previously observed in human gastric bypass patients. Transfer of the surgically altered microbial communitboth diet and the weight loss associated with this procedure. The observed changes in this mouse model were similabypass induced substantial, rapid, and sustained changes to the gut microbial communities that were independent ocharacterize changes in the gut microbiota, both temporally and along the length of the gastrointestinal tract. Gastric

use a mouse model of gastric bypass surgery toet al.importance of these changes is unknown. In a new study, Liouthe trillions of microorganisms that reside in the human gut is markedly altered after gastric bypass, but the functionato a large population of obese patients, prompting a search for less invasive treatments. The population structure ofeffect on weight loss and remission of diabetes, the cost and associated risk of this procedure prevents its applicatio

One of the most durably effective treatments for severe obesity is gastric bypass surgery. Despite its powerful

Getting By(pass) with Help from Our Little Friends

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O B E S I T Y

Conserved Shifts in the Gut Microbiota Due to GastricBypass Reduce Host Weight and Adiposity

Alice P. Liou,1 Melissa Paziuk,1 Jesus-Mario Luevano Jr.,2 Sriram Machineni,1

Peter J. Turnbaugh,

2

* Lee M. Kaplan

1

*

Roux-en-Y gastric bypass (RYGB) results in rapid weight loss, reduced adiposity, and improved glucose metab-

olism. These effects are not simply attributable to decreased caloric intake or absorption, but the mechanisms

linking rearrangement of the gastrointestinal tract to these metabolic outcomes are largely unknown. Studies

in humans and rats have shown that RYGB restructures the gut microbiota, prompting the hypothesis that

some of the effects of RYGB are caused by altered host-microbial interactions. To test this hypothesis, we used

a mouse model of RYGB that recapitulates many of the metabolic outcomes in humans. 16S ribosomal RNA gene

sequencing of murine fecal samples collected after RYGB surgery, sham surgery, or sham surgery coupled to caloric

restriction revealed that alterations to the gut microbiota after RYGB are conserved among humans, rats, and mice,

resulting in a rapid and sustained increase in the relative abundance of Gammaproteobacteria (Escherichia) and

Verrucomicrobia (Akkermansia). These changes were independent of weight change and caloric restriction, were

detectable throughout the length of the gastrointestinal tract, and were most evident in the distal gut, down-

stream of the surgical manipulation site. Transfer of the gut microbiota from RYGB-treated mice to nonoperated,

germ-free mice resulted in weight loss and decreased fat mass in the recipient animals relative to recipients ofmicrobiota induced by sham surgery, potentially due to altered microbial production of short-chain fatty acids.

These findings provide the first empirical support for the claim that changes in the gut microbiota contribute to

reduced host weight and adiposity after RYGB surgery.

INTRODUCTION

Roux-en-Y gastric bypass (RYGB) is a highly effective treatment forsevere obesity and type 2 diabetes, characterized by a marked and sus-tained loss of ~65 to 75% of excess body weight and fat mass (1). Ini-tially thought to be a mechanical procedure causing restriction andcalorie malabsorption, recent evidence suggests that RYGB alters the

basic physiology of energy balance and metabolism in weight-dependentand weight-independent ways (2). These changes include marked im-provement in glucose homeostasis before weight loss (3), increased se-cretion of gut hormones (4, 5), and alterations in energy expenditure(68); however, the mechanisms that drive these outcomes remain in-completely understood. It is likely that anatomical rearrangement ofthe gastrointestinal tract alters the composition of the luminal milieuand its interactions with the intestinal epithelium, which in turn af-fects downstream signaling pathways regulating host energy balanceand metabolism (9). A particular luminal factor, however, has yet tobe identified.

Of the several potential luminal components known to mediateenergy balance after gastric bypass surgery, including dietary nutrients,biliopancreatic secretions, and the gut microbiota, we focused on thepotential contribution of the microbiota to RYGB outcomes, partic-ularly due to its increasingly recognized role in regulating energybalance and metabolic function. The gut microbiota has been reportedto differ in community structure, gene content, and metabolic net-work organization between obese and lean individuals (1013). Diets

differing in fat and sugar content can also affect this structure (141favoring the growth of bacteria whose secreted factors or structucomponents contribute to the development of adiposity, insulin resiance, and other metabolic derangements (18, 19). Furthermore, conization of germ-free mice with a gut microbiota from conventionaraised mice has provided functional evidence that the gut microbio

can modulate host phenotype by decreasing food intake and increing adiposity (10, 20). These phenotypes are further enhanced in gerfree animals colonized with the cecal microbiota from obese dono(10, 17). Because the gut microbiota influences some of the same mebolic parameters as RYGB, we hypothesized that changes to the gmicrobiota after RYGB may contribute to some of the metabolic beneof this procedure.

Recently, RYGB has been reported to cause marked shifts in femicrobial profiles in both humans and rats (9, 21, 22), but it remaunclear to what degree these changes are caused by alterations in tgastrointestinal tract, by the surgical process itself, or by decreasweight and/or caloric intake induced by this procedure. Furthermoit is unknown how rapidly these changes in microbial ecology occhow stable they are over time within a given individual, and if they alimited to the distal gut (for example, feces). The microbial taxonomgroups that are enriched after RYGB have been associated with decreasadiposity and leptin levels in humans (21) and with changes in feand urinary metabolites in rats (9). To date, however, there has beno empirical data to support the hypothesis that these RYGB-altermicrobial communities have a direct effect on improved metabooutcomes.

To address these questions, we turned to a recently developed mrine model of RYGB (23, 24) to (i) demonstrate that changes in the gmicrobiota after gastric bypass surgery are conserved among huma

1Obesity, Metabolism & Nutrition Institute and Gastrointestinal Unit, MassachusettsGeneral Hospital, Boston, MA 02114, USA. 2FAS Center for Systems Biology, HarvardUniversity, Cambridge, MA 02138, USA.*Corresponding author. E-mail: [email protected] (L.M.K.); [email protected] (P.J.T.)

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rats, and mice; (ii) demonstrate that the underlying cause of much ofthe microbial response to surgery is due to the reconfiguration of thegastrointestinal tract; (iii) characterize the temporal and spatial changesin the gut microbiota after this operation; and (iv) through transplan-tation of the RYGB-associated gut microbiota into germ-free mice,show that this altered gut microbiota is sufficient to trigger decreasedhost weight and adiposity (see Fig. 1, A to C, for experimental design).

RESULTS

The effect of RYGB on adiposity in the mouse modelDiet-induced obese (DIO) C57BL/6J mice fed a high-fat diet (HFD)commonly develop obesity-related metabolic derangements, includingglucose intolerance, hyperglycemia, hyperinsulinemia, and insulinresistance (25). Within 3 weeks after RYGB, male C57BL/6J mice lost29 1.9% of their initial body weight and remained at this lowerweight throughout the study period. In contrast, ad libitumfed sham-operated (SHAM) animals regained their body weight within 2 to 3 weeksafter surgery (Fig. 2A; 32.8 0.5 g versus 42.2 2.1 g after 5 weeks;P= 0.007, Students t test). Weight-matched sham-operated (WMS)animals were fed ~25% fewer calories to match the weight of the RYGB

animals. As we have seen previously (23, 24), the decreased body weigafter RYGB reflected a preferential loss of fat mass and a preservatiof lean mass compared to sham controls (Fig. 2B). Epididymal aretroperitoneal fat pad weight, the degree of hepatic steatosis, and livtriglyceride content were all reduced in both RYGB and WMS animrelative to SHAM animals (Fig. 2, C to E). Food intake was not dferent between RYGB and SHAM controls (Fig. 2F); however, taki

into account the greater energy lost in the feces of RYGB animals (F2G), the net energy intake in RYGB animals was intermediate to thof SHAM and WMS controls (Fig. 2H and table S1). This finding idicates that the weight loss in response to RYGB is due both to a dcrease in net energy intake and to an increase in total energy expendituIncreased energy expenditure after RYGB has been previously demostrated in both rat and mouse models (68).

RYGB animals maintained on HFD exhibited improved plasma gcose and insulin levels at 15 weeks after surgery, compared to SHAanimals, mirroring the metabolic phenotype of normal chow (NCfed lean mice (table S2). Although weight loss by food restriction yieldsimilar improvements in fasting plasma glucose and insulin levels, greaimprovements in glucose tolerance and insulin sensitivity were seenRYGB versus WMS animals (fig. S1), supporting human evidence thRYGB has weight-independent effects on glucose metabolism (26)

Fig. 1. Schematic of experimental design. (A) DIO C57BL/6J mice fed a60% HFD underwent either RYGB or sham operations and 2-week recov-ery on liquid diet before returning to HFD (blue bars). Sham animals thathad successfully regained body weight within 3 weeks after surgery weredivided into an ad libitumfed SHAM group or food-restricted to matchthe weight of the RYGB animals (WMS). Fresh fecal samples were col-lected preoperatively and weekly for 12 weeks after surgery for micro-biota analysis (red arrows). (B) Graphic of the RYGB anatomy and segmentscollected for luminal content and mucosal scrapings along the length of

the gastrointestinal tract. Segments representative of the RYGB anatowere also collected in SHAM and WMS animals. (C) Design of microbiotransfer experiments of the cecal contents from a representative donanimal from each group, depicted in (A), into germ-free mice (star), dicating timing of collection of fecal samples for microbiota analysis (rarrows), body weights (blue asterisks), and food intake (triangles). At tend of the colonization period, animals were fasted overnight (doulines), and final body weights, serum metabolic parameters, and adiposscores were obtained.




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RYGB rapidly alters the distal gut microbiotaTo determine how RYGB affects the distal gut microbiota, we per-formed 16S ribosomal RNA (rRNA) gene sequencing on fecal samplescollected before and weekly for 3 months after intervention in theRYGB, SHAM, and WMS groups (Fig. 1A). Overall, we analyzed

166 samples from 23 animals (109,015 5842 16S rRNA gene se-quences per sample; table S3).

RYGB markedly altered the composition of the distal gut mi-crobiota as early as 1 week after surgery, a change that progressedover time and stabilized after 5 weeks (Fig. 3 and fig. S2). The shamprocedure also affected the fecal microbial communities but to asubstantially lesser extent than RYGB; furthermore, the differences inmicrobial ecology between the SHAM and WMS groups were mini-mal (Fig. 3 and fig. S2). These observations suggest that rearrange-ment of the gastrointestinal tract by RYGB had a substantiallygreater effect on the fecal microbiota than either food restrictionmediated weight loss or the limited intestinal disruption caused bythe sham procedure.

Additionally, we analyzed fecal samples at a single time point fromunoperated DIO, unoperated lean NC-fed mice, and RYGB-operatedmice maintained on NC (NC-RYGB). As expected, the abundance ofspecies-level operational taxonomic units (OTUs) in samples from DIOand lean animals was significantly different (Fig. 3A; Spearman corre-lation range was 0.58 to 0.84 and 0.16 to 0.24 for within-group versusbetween-group comparisons, respectively; P< 107, Students t test).However, the effect of RYGB on the gut microbiota was similar re-gardless of whether mice were fed NC or HFD (Fig. 3), suggesting thatthe impact of surgery can overwhelm even the well-recognized effectof dietary composition on the gut microbiota (14).

Weight loss after dietary restriction or RYGB was accompanby similar changes in the abundance of taxonomic groups within tFirmicutes phylum as a proportion of the total sequences observedthe phylum. Compared to preoperative levels, both the RYGB aWMS microbiota were dominated by the order Clostridiales (78.9

2.7% and 72.9 2.7% of Firmicutes 16S rRNA gene sequences, resptively), whereas the SHAM microbiota had a significantly greatabundance of the orders Lactobacillales and Erysipelotricha[42.5 4.0% (SHAM), 27.1 3.8% (WMS), and 21.1 2.7% (RYGP< 0.01, SHAM versus WMS and SHAM versus RYGB, Studenttest; Fig. 4A and table S4]. In contrast, the relative abundanceBacteroidales remained stable when comparing pre- and postoperatabundances across all treatment groups over time (Fig. 4A).

RYGB induced several specific changes in the gut microbial ecogy including an increased abundance in the Enterobacteriales withthe first 2 weeks after surgery; there was no change in the Enterbacteriales in either the SHAM or WMS groups (Fig. 4A and fig. S3AThere was also a significantly greater increase in Verrucomicrobiawithin the first 2 weeks after RYGB (10,000-fold on average; P< 0.Students ttest) compared to preoperative levels that was more markthan that observed after either SHAM or WMS treatment (3-fold, P0.05 for both; Fig. 4A). Using the linear discriminant analysis (LDeffect size (LEfSe) (27) method, we identified more specific bactertaxa and species-level phylotypes whose relative abundance varied snificantly among fecal samples taken from the RYGB, SHAM, aWMS treatment groups. This analysis revealed 50 discriminative ftures (LDA score >2; Fig. 4B and table S4). RYGB microbiotas weenriched for three distinct taxonomic groups, evident from phylulevelBacteroidetes, Verrucomicrobia, and Proteobacteriato gen

Fig. 2. Phenotypic data from the RYGB mouse model. Character-istics of DIO C57BL/6J mice undergoing either RYGB (n = 11 to 17),sham operation (SHAM; n = 4 to 6), or sham operation with weight

matching to the RYGB group by food restriction (WMS; n = 5 to 6). (A) Bodyweight curves after surgery. (B) Body composition analysis. (C) Adiposityindex calculated from epididymal and retroperitoneal fat pad weights. (D)Liver triglyceride content. (E) Liver histology (20). (F to H) One-weekcumulative (F) food intake, (G) fecal energy output, and (H) net energy intake

in RYGB (n = 14), SHAM (n = 11), and WMS (n = 6) animals. Measurements(B) to (E) were taken at the end of study, 15 weeks after surgery. Food intaand energy output studies were performed 4 to 6 weeks after surgery. * P0.05, **P< 0.01, ***P< 0.001, one-way analysis of variance (ANOVA) and phoc Tukey test. Values represent means SEM.




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levelAlistipes, Akkermansia, and Escherichia, respectively (Fig. 4B).The relative abundance of Archaea in fecal samples, as determinedby quantitative polymerase chain reaction (PCR), was also found tobe greater in RYGB animals relative to SHAM animals (fig. S4, Aand B). However, we were unable to detect the presence of methanogensusing two previously validated primers targeting methyl coenzyme Mreductase subunit A, a conserved enzyme in the methanogenesis path-way (fig. S4, C and D) (28, 29).

To determine how gastric bypass affects the spatial structure of thegut microbiota, we sampled the luminal and mucosal adherent micro-bial communities at eight sites spanning the stomach, small intestine,cecum, and colon of mice 15 weeks after RYGB, SHAM, or WMS treat-ments (n = 3 to 6 samples per site per treatment; 207 samples; 84,758 3873 sequences per sample; Fig. 1B and table S5). Comparisons of mi-

crobial community membership using tunweighted UniFrac metric revealed ththe distal stomach, ileal, cecal, and colonmicrobiota were all strongly affected RYGB (Fig. 5). As in the fecal samples, taggregate RYGB microbiota had a snificantly higher abundance of Enter

bacteriales (16.7 1.3%), Bacteroida(28.7 1.9%), and Verrucomicrobia(17.6 1.4%) compared to SHAM contr(5.0 0.6%, 16.7 1.8%, and 6.0 1.0respectively; P< 105 for each, Studenttest). The observed changes were qualitively consistent throughout the gastintestinal tract, with some notable exceptio(Fig. 5B). For example, the relative abudance of the Enterobacteriales increasto thegreatestextentin theluminal conteof the distal gut, as well as in the intestisegments not excluded from nutrient fland in the mucosal adherent communitof the colon, ileum, and Roux limb (fS3B). Microbial communities in the mcosal and luminal content samples wsimilar across segments within both RYGand SHAM animals (Fig. 5A); howevthe luminal and mucosal adherent poplations of WMS animals diverged througout the small intestinal segments, includthe biliopancreatic, Roux, and commlimbs (Fig. 5). The latter result suggethat bacteria localized at the mucosal suface in the small intestine may be moresponsive to food-restricted weight lo

than to RYGB, where the effects are seprimarily in the distal intestine, cecuand colon.

To elucidate potential selection prsures that could be responsible for tobserved changes in microbial ecoloafter RYGB, we analyzed fecal sampfrom RYGB, SHAM, and WMS animfor fecal fat and nitrogen content and p(table S1). Fecal samples from RYG

mice had significantly lower pH and higher fat content than fecsamples from SHAM and WMS mice. In contrast, fecal nitrogen cotent was lower in both RYGB and WMS samples relative to SHAFurthermore, pH within the distal stomach was significantly increasin RYGB mice (3.8 0.6; n = 8) relative to SHAM mice (1.9 0.7; n5; P< 0.05, Mann-Whitney test), potentially due to the loss of dirstimulation of acid secretion by food. These changes underscore tpresence of an altered luminal milieu after RYGB that could influengut microbial ecology (14, 30).

Decreased host adiposity is transmissiblethrough the microbiotaGiven that previous studies have shown that host adiposity and gcose homeostasis can be affected by the gut microbiota (20, 31),

Fig. 3. RYGB causes marked, rapid, and sustained changesin gut microbial ecology that are independent of weightand diet. (A) Heat map of pairwise Spearman rank corre-lations between species-level OTUs from fecal samples,ordered by treatment, individual, and time. Within-individual rank correlations in RYGB, SHAM, and WMSmice (n = 4 to 5 animals per group) compare weeklypostoperative samples to a preoperative sample. Rank

correlations between endpoint samples taken from unop-erated DIO, unoperated NC-fed (NC), and RYGB-operatedmice maintained on NC (NC-RYGB) are also included

(n = 2 to 4 per group). Each correlation is colored from dark blue (no correlation) to dark red (perfectpositive correlation). (B) Temporal effects of gastric bypass on overall community membership amongfecal samples from RYGB (pink circles), SHAM (orange squares), and WMS (olive triangles) animals [firstprincipal coordinate from an unweighted UniFrac-based analysis over time]. Includes endpoint fecalsamples from age-matched DIO (purple circle), NC (green triangle), and NC-RYGB (blue diamond) mice.Values represent means SEM.




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sought to determine whether any of the metabolic changes associatedwith RYGB could be directly influenced by RYGB-induced modula-tion of the gut microbiota. We tested this possibility by inoculatinglean, germ-free mice with cecal contents from RYGB donors (RYGBrecipient or RYGB-R mice) and comparing basal phenotypic outcomesto those of uninoculated germ-free mice and germ-free mice inoculatedwith cecal contents from SHAM or WMS donors (SHAM-R and WMS-Ranimals, respectively; Fig. 1C). During a 2-week colonization period,RYGB-R animals exhibited a significant decrease in body weight (5.0 1.8%; P< 0.05, one-sample ttest), whereas both SHAM-R and germ-free control animals exhibited no significant weight change (0.2 1.1%

and 2.5 1.4%, respectively; Fig. 6, A and B). Food intake in SHAManimals was significantly decreased compared to germ-free controsimilar to what has been seen previously [P< 0.01, SHAM-R versgerm-free, Students t test (20)], whereas food intake in RYGBanimals was not affected (P= 0.39, RYGB-R versus germ-free, Studenttest; Fig. 6C). A similar trend toward increased food intake in RYGBmice relative to SHAM-R mice (Fig. 6C) was also seen relative to WMSmice (fig. S5A). Both SHAM-R and WMS-R animals exhibited a similar increase in overall adiposity (fig. S6), including relative fat pweights, at the end of the colonization period. Consolidating bosham groups together, the recipients of cecal transfer from sham dnors had a significantly greater fat mass than either RYGB-R or uinoculated germ-free controls [P< 0.01 (germ-free versus SHAM-and P< 0.05 (RYGB-R versus SHAM-R), Students ttest; Fig. 6D afig. S5B], a difference that was also reflected in plasma leptin lev(P< 0.05, RYGB-R versus SHAM-R, Students t test; Fig. 6E and f5C). Fat pad weight did not increase in the RYGB-R animals relatito the uninoculated germ-free controls (Fig. 6D). Liver weights we

Fig. 4. Bacterial taxonomic groups that discriminate among RYGB-, SHAM-,and WMS-derived samples. (A) Average relative abundance of bacterialorders in RYGB, SHAM, and WMS mice before and up to 12 weeks aftersurgery. (B) LEfSe-derived (27) phylogenetic tree depicting nodes withinthe bacterial taxonomic hierarchy that are significantly enriched in fecalsamples from RYGB (red), SHAM (green), and WMS (blue) mice. Significantphyla are labeled, with the genera in parentheses. LEfSe was used with thedefault parameters (n = 5000 sequences per sample; OTUs with


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no different among groups, but there was a trended increase in livertriglyceride levels in the SHAM-R animals (Table 1).

Although marked changes in serum glucose, insulin, and triglyceridesin lean recipient mice fed a standard chow diet were not expected, therewas a trend toward improved insulin sensitivity, estimated by homeosta-sis model assessment of insulin resistance (HOMA-IR), and significantlyreduced fasting triglyceride levels in RYGB-R mice relative to SHAM-Rmice (Table 1). Glucose tolerance and insulin tolerance in the recipientswere not measured.

In an attempt to find potential microbiota-derived signals thatcould be directing the loss of body weight and adiposity in recipientanimals, we examined both ileal fasting-induced adiposity factor (FIAF)gene expression and cecal short-chain fatty acid (SCFA) composition.

Colonization with either SHAM-R or RYGB-R microbiota into germfree animals caused a similar decrease in ileal FIAF expression (fS7), consistent with previously published results (20). Cecal SCFAhowever, differed among the germ-free, RYGB-R, and SHAM-R grou(Fig. 7, C and D). Microbial colonization of germ-free mice increasSCFA production, as indicated by the increase in cecal SCFA levewith SHAM-R animals producing significantly more SCFAs relativegerm-free animals (P< 0.05, Students t test) and RYGB-R animproducing an intermediate quantity of cecal SCFAs (Fig. 7C). This dference is not as apparent in the operated donor groups (Fig. 7Ahowever, the relative proportion of acetate, propionate, and butyrlevels were maintained in both donor and recipient animals. Tacetate/propionate/butyrate ratios in SHAM and WMS animals w

Fig. 6. Decreased weight and adiposity is transmissible via the gut micro-biota. (A) Body weight curves for SHAM-R (n = 6) and RYGB-R (n = 10) mice,represented as change from initial body weight. (B) Change in body weights(BW) among the groups relative to baseline. (C) Cumulative food intake overthe 13-day colonization period. (D and E) Visceral fat pad weights (D) andplasma leptin levels (E) in the RYGB-R (n = 10), uninoculated germ-free

(n = 7), and consolidated SHAM-R (n = 10) groups. Values in (A) to (E) ameans SEM. *P< 0.05, **P< 0.01, ANOVA post hoc test. Representativethree experiments. (F) Relative abundance of bacterial taxa in recipieanimals after gavage with cecal contents from RYGB, SHAM, and WMS dnors. Mean values across each time point (1 to 13 days after gavage) ashown (n = 3 to 15 samples per time point; 10,000 sequences per samp




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75:12:13, similar to those seen in SHAM-R animals (74:11:15); in con-trast, the acetate/propionate/butyrate ratios in RYGB and RYGB-Ranimals were in the same range at 62:27:11 and 54:30:16, respectively(Fig. 7, B and D).

To identify RYGB-specific microbial biomarkers that may contrib-ute to the recipient phenotype, we collected fecal samples from RYGB-R,SHAM-R, and WMS-R animals at 1, 2, 3, 7, and 13 days after colo-

nization with their respective donor microbiota and searched for bac-terial taxonomic groups shared between the donor and recipientanimals. 16S rRNA gene sequencing was performed on 91 total sam-ples from 26 recipient animals (n = 5 to 6 mice per treatment group

per experiment; 53,739 2740 sequences per sample; table S6). Athree treatment groups had high levels of Enterobacteriales durithe first 2 days after colonization, whereas the Bacteroidales consistenbecame the dominant taxa by day 13. The levels of Verrucomicrobialhowever, remained significantly higher in RYGB-R samples (30.11.6% of 16S rRNA gene sequences) than in either SHAM-R (9.31.7%; P< 104) or WMS-R (14.6 2.8%; P< 104, Students t te

controls (Fig. 6F). Analysis with LEfSe confirmed the enrichment fAkkermansia as well as Alistipes (Bacteroidetes phylum) in RYGBfecal samples, similar to what we observed in the donor anim(table S7).

DISCUSSION

Rodent models of RYGB assist in identifying potential mechanismsweight loss, fat loss, and metabolic improvements in ways that wouotherwise be limited in clinical studies. Here, we show that changesmicrobial ecology after RYGB are due to gastrointestinal reconfigration and not merely due to the associated changes in weight lodiet, or intestinal transection. Furthermore, we demonstrate that taltered microbiota is sufficient to trigger a reduction in host boweight and adiposity.

Our study was designed to minimize potential interindividual vaiation by assessing within-individual changes in gut microbial ecolobefore and after surgery. Marked changes in this ecology were observwithin 1 week after RYGB, with a pronounced increase in the abundanof the Verrucomicrobia (genus: Akkermansia) and Gammaproteobacte(order: Enterobacteriales). These changes were similar to those oserved in the fecal microbiota of human patients (21, 22) and in no

obese, NC-fed rats (9) that had undergoRYGB, and were observed in RYGB mfed either a high-fat or standard chow dSeveral studies have demonstrated the r

of dietary composition in modulating mcrobial ecology and diversity (1416, 3however, it is clear that RYGB produunique selective pressures to modulcommunity structure that is not merelyreversion to a community seen in the leNC-fed state (14, 17). Together, many pects of the microbial response to gastbypass surgery are conserved among hmans, rats, and mice, despite significadifferences in the specific microbial straand species found within their gastrintestinal tracts (13, 33).

Given the increase in Gammaprotebacteria in humans (21, 22), rats (9), anow our mouse model of RYGB, we rsoned that this population could be a kcontributor to regulating host metabooutcomes after surgery. Escherichia, tgenus most highly enriched after RYGin the mouse, includes several pathogenstrains associated with metabolic syndromobesity, and insulin resistance (19, 3as well as nonpathogenic commen

Table 1. Fasting blood parameters of germ-free (GF) recipient animals re-ceiving cecal contents from RYGB-R, SHAM-R, and GF mice. Values repre-sent means SEM. Data annotated by different letters are significantlydifferent (P < 0.05, ANOVA).

RYGB-R SHAM-R GF

n 15 10 7

Blood glucose (mg/dl) 148 5.5A 147 7.4A 120 3.9B

Insulin (ng/ml) 0.46 0.10A 0.99 0.19A 0.73 0.19A

HOMA-IR 4.4 0.98A 9.8 4.1A 5.5 1.5A

Serum triglyceride (mg/dl) 77.8 9.7A 113 8.5B 73.5 16.8A

Serum NEFA (meQ/liter) 0.58 0.06A 0.65 0.06A 0.62 0.05A

Liver weight (% body weight) 4.9 0.10A 4.8 0.20A 4.8 0.18A

Liver triglyceride (mg/g liver) 22.9 4.2A 36.2 9.1A 21.6 6.0A

Fig. 7. SCFA levels are consistent between donor and recipient animals. (A and B) Total cecal SCFAs (A)and percentage of total SCFAs (B) of acetate, propionate, and butyrate in RYGB-operated (n = 6), SHAM-operated (n = 4), and WMS-operated (n = 5) animals. (C) Total cecal SCFAs of RYGB-R (n = 5), SHAM-R (n =6), and germ-free (GF; n = 4) mice 2 weeks after colonization of their respective operated donor cecalmicrobiota. (D) Percentage of total SCFA of acetate, propionate, and butyrate in RYGB-R and SHAM-R mice.Values represent means SEM. *P< 0.05, **P< 0.01, ****P< 0.001, one-way ANOVA post hoc Tukey test orStudents t test.




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species that have been used as probiotic agents to prevent gastro-intestinal inflammatory conditions (35). It is possible that the specificEscherichia population enriched after RYGB may have some beneficialrole in driving host metabolic improvements after surgery.

The Verrucomicrobium Akkermansia was also substantially in-creased in RYGB mice and was maintained after transfer to germ-freerecipients. Given this observation, it is possible that Akkermansia may

have a substantial role in regulating host adiposity and weight loss.Akkermansia can use mucus as a sole source of carbon and nitrogenin times of health and particularly in times of caloric restriction (36).This observation likely explains why Akkermansia is selectively in-creased in the mucus layer of WMS mice. The physiological relevanceof the overall increase in Akkermansia throughout the RYGB-alteredgastrointestinal tract, and how this may differ from the site-specificincreases seen in WMS animals, remains to be determined. Additionalstudies are needed to elucidate whether increased foraging on hostmucins or altered inflammation and insulin sensitivity in responseto Akkermansia (37, 38) contribute to the metabolic outcomes afterRYGB. In addition, we cannot discount the potential interactionsamong Enterobacteriales, Akkermansia, and other enriched bacterialgroups (such as Alistipes) in the RYGB model and how they maywork independently or interdependently to influence host metabol-ic improvements.

Microbial community structure is likely altered after RYGB throughrerouting of nutrients and biliopancreatic secretions. Although we didsee changes in fecal fat and pH profiles in the RYGB animal, thesechanges would be expected to promote the growth of Firmicutes(17, 30) rather than the observed decrease in Firmicutes after surgery.Therefore, the precise factors responsible for modulating microbialcommunities have yet to be defined.

Phenotypic characterization of germ-free recipient mice receiving amicrobiota transplant from RYGB-operated donors highlights the po-tential functional and metabolic contributions of the RYGB micro-biota. We found that RYGB-R animals had reduced body weight and

decreased fat deposition compared to SHAM-R and uninoculatedgerm-free controls. WMS-R animals shared similar body weight andadiposity phenotypes as the SHAM-R animals (fig. S5), likely due tothe similar cecal microbial profiles between the WMS and SHAM do-nors (Fig. 3C and fig. S3), suggesting that the effects of the RYGBmicrobiota on germ-free recipients are unique to this particular mi-crobial profile. This was a surprising observation because inoculationof the entire complex microbial communities (14, 19, 20) or specificmicroorganisms (39) from either lean or obese mice has previouslybeen shown to cause an increase in epididymal fat pad weight andoverall adiposity in the face of decreased food intake (10, 20). Al-though the degree of weight loss by the RYGB microbiota into leanrecipient mice is not as profound as the effect of RYGB in obese mice(5% versus 29% weight loss, respectively), these findings are consistentwith the hypothesis that alterations in the gut microbiota after RYGBat least partially modulate body weight and adiposity.

A decrease in adiposity and body weight without a change in foodintake suggests that the RYGB-associated microbiota may either re-duce the ability to harvest energy from the diet or produce signalsregulating energy expenditure and/or lipid metabolism. Previousstudies had identified ileal FIAF as a microbiota-influenced mecha-nism promoting lipid uptake into adipose tissue (20, 31). Colonizationof germ-free recipients with either a RYGB or SHAM microbiota re-sulted in equally reduced ileal FIAF expression despite the differences

in fat pad weight, suggesting that the effect of the RYGB microbioon metabolic outcomes is independent of FIAF.

SCFAs are by-products of microbial fermentation that affect hphysiology in several ways, including serving as a primary enersource for colonocytes, substrates for lipid storage in adipose tissuimmune cell modulators, and molecules regulating lipid and glucometabolism and appetitive drives via G protein (heterotrimeric guan

nucleotidebinding protein)coupled receptor (GPR41 and GPR4activation and signaling (40, 41). Increased adiposity has been demostrated in previously germ-free recipients of gut microbiota contenlikely due to increased availability of SCFAs (10, 17). Indeed, an creased production of SCFAs in SHAM-R animals relative to RYGBand germ-free animals may explain the differences in adiposity amothe groups. However, these observations do not explain the physiologidifferences among the RYGB, SHAM, and WMS groups, which do nexhibit significant differences in total cecal SCFA content.

It is possible that the different SCFAs affect host metabolic phyiology in different ways. Both RYGB and RYGB-R animals had retively greater propionate and lower acetate production than the WMSHAM, and SHAM-R groups, likely a consequence of the differemicrobial profiles seen in the RYGB and RYGB-R animals (tabS4 and S7) (42). The decreased adiposity in RYGB-R animals relatto SHAM-R animals could be due to the reduced level of acetate avaable for lipogenesis by adipose tissue and peripheral tissues (43). Futhermore, propionate is known to inhibit acetate conversion into lipin the liver (44) and adipose tissue (45), and may contribute to tlowered adiposity and serum triglyceride levels and a trend toward dcreased hepatic triglyceride content. Propionate is also thought to hibit food intake through GPR41- and GPR43-induced secretionsatiety-regulating gastrointestinal hormones (46), although this is llikely given the lack of change in food intake in the RYGB-R anima

Given the well-established effect of RYGB to increase energy ependiture (7, 8), we cannot discount the possibility that a reductiin body weight without a change in food intake is due to altered m

crobial signaling that up-regulates host energy expenditure. Male mlacking GPR41 have reduced energy expenditure and increased adposity (47), suggesting that SCFAs regulate energy expenditure vGPR41. Among the known SCFAs, propionate has the highest affinfor GPR41, and its administration has been shown to increase sympthetic activity, resulting in elevated energy expenditure (48). Therefothe increase in energy expenditure after RYGB could be mediated,part, through enhanced propionate activation of the GPR41 pathwAnother potential mechanism is differential microbial modificationbile acids, which are also signaling molecules that can influence enerexpenditure (49). Additional studies are necessary to further clarify tspecific contributions of these various microbially influenced metablites on changes in host energy balance and metabolism after RYG

It is clear from studies in our laboratory and others that RYGB improves glucose metabolism in animals and in people (50). However, tdegree to which the RYGB-altered microbiota mediates those improvments when administered to germ-free mice remains uncertain. In thexperiments, recipient mice were lean and maintained on NC. Althouthere were no changes in fasting glucose levels between RYGB-R aSHAM-R mice, the RYGB-R group exhibited a trend toward lower fastinsulin levels than either SHAM-R or germ-free mice. It is possible thin this model system, the effect of the microbial community on host gcose metabolism is diet-dependent. Therefore, future microbiota tranplantation studies in germ-free recipients fed a HFD are warranted




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In summary, these studies have given us preliminary insights to thepotential contributions of the RYGB-associated gut microbiota, andparticularly SCFAs, in regulating host physiology, energy balance,and metabolism (fig. S8). Future studies incorporating surgery, meta-genomics, gnotobiotics, and genetic deletions for key metabolic sign-aling pathways promise to expand our understanding of the gutmicrobiota in shaping host energy balance and the metabolic response

to surgical intervention.

MATERIALS AND METHODS

AnimalsMale C57BL/6J DIO mice were purchased at 22 to 26 weeks of age(Jackson Laboratories) and maintained on a 60% HFD (ResearchDiets, D12492) until they reached a preoperative weight of 40 to 50 g.All surgically operated animals were individually housed in cageswith wire floor throughout the study period. Male, age-matched (7 to10 weeks old), germ-free Swiss Webster mice were obtained fromTaconic. All animal studies were performed under protocols approvedby the Massachusetts General Hospital and Harvard Medical SchoolInstitutional Animal Care and Use Committees.

Surgery, postoperative care, and dietThe surgical approach for RYGB mice is a modified version of thatpreviously described (8, 23), the only difference being that the glandularand nonglandular portions of the stomach were double-sutured andtransected to form the distal stomach and gastric pouch, respectively(Fig. 1B). With this approach, we achieved less than 20% mortalityover the course of the experiment. Sham animals were treated in amanner similar to the RYGB animals, with a single transection justdistal to the ligament of Treitz followed by reanastomosis to restorethe preoperative intestinal anatomy.

Operated animals did not receive postoperative antibiotics or anti-

inflammatory drugs, but were given buprenorphine (0.05 mg/kg, in-tramuscularly) for pain. Animals were maintained on a liquid diet(Vital HN, Abbott Laboratories) for 2 weeks until weaned back ontosolid HFD. Body weights were monitored weekly. Three weeks aftersurgery, a group of weight-stabilized SHAM animals was randomlychosen and maintained on a restricted diet of about 75% of the caloriesconsumed daily by RYGB-treated mice so as to match the weight of theRYGB animals (WMS). With constant adjustment of the daily foodintake of these animals, weight matching with the RYGB group was sta-bilized by 6 weeks after surgery (3 weeks after start of food restriction).

Food intake and fecal analysisA subgroup of animals was housed singly on wire floors, and food inthe hopper and food spilled were weighed every 3 to 4 days. All fecalpellets were collected, weighed, and submitted to the University of Ar-kansas Central Analytical Laboratory (http://www.uark.edu/ua/cal/)for measurements of fecal calorie, crude fat, and protein (nitrogen)and pH. The net intake for each component (energy, fat, or protein)was calculated by subtracting the energy expelled in the stool from thetotal amount consumed during a 1-week period.

Fecal sampling, processing, and analysisFecal samples were collected weekly and stored at 80C until process-ing. DNA was extracted with the PowerSoil bacterial DNA extraction

kit (MO-BIO) and PCR-amplified with universal bacterial primers tgeting variable region 4 of the 16S rRNA gene as described previou(51). Amplicons were sequenced with the Illumina HiSeq platfor(52). Multivariable statistical analysis was used to compare microbcomposition among the treatment groups. 16S rRNA gene sequences wanalyzed with the QIIME [Quantitative Insights Into Microbial Ecogy (53)] software package along with custom Perl scripts to analyze

(within-sample) and b (between-sample) diversity. The LEfSe packawas used to identify taxonomic groups significantly associated weach treatment (27). Spearman rank correlations were calculated bason the number of sequences assigned to abundant species-level phytypes in each fecal microbiota (phylotypes with 100 sequences acra combined data set were included; 10,000 randomly subsampled quences were included per sample).

Tissue harvest and intestinal axis samplingMice were sacrificed between 12 and 15 weeks after surgery. Befosacrifice, animals were fasted for 2 hours and blood glucose was mesured from the tail tip with a handheld glucometer (AlphaTRAK, AbbLaboratories). The animals were then anesthetized with sodiupentobarbital (100 mg/kg, intraperitoneally) and euthanized by cardexsanguination. Plasma was isolated and stored at 80C. The flowing intestinal sections were collected for bacterial DNA analysgastric pouch, distal stomach remnant, biliopancreatic limb, Roux limcommon limb, ileum, cecum, and colon. Sections representative of tintestinal segments comprising each limb were also collected in SHAanimals (Fig. 1B). Each segment was flushed with extraction buf(200 mM NaCl, 200 mM tris, 20 mM EDTA, pH 8.0) to retrieve lumibacterial contents. Each section was then cut longitudinally, and tmucosa was scraped off with slides for assessment of mucosal adherebacterial populations. All contents and mucosal adherent samples wflash-frozen in liquid nitrogen and stored at 80C until DNA extrtion. In a separate group of animals, pH was measured in different sements of the gastrointestinal tract with a micro-pH electrode (Therm

Scientific). Epididymal and retroperitoneal fat pads were collected aweighed as a biomarker for visceral adiposity. Whole-body lean and masses were determined by time-domain nuclear magnetic resonan(Bruker TD Minispec).

Germ-free mouse experimentsCecal contents from a donor animal representing each group (RYGWMS, and SHAM) were saved in reduced anaerobic phosphate-buffersaline and homogenized within an anaerobic chamber. The resultaslurry was administered by oral gavage to germ-free mice (five to six amals per group). Animals were housed one to two per cage on wfloors and fed autoclaved rodent breeder chow. Uninoculated germ-fmice were used as controls. Body weight and cumulative food intawere measured and recorded weekly. Fecal pellets were collecteddays 1, 1, 2, 3, 7, and 13 days after gavage. On day 13, food was witheld from animals overnight. The next morning, fasting blood glucowas measured in blood collected from the tail tip. After euthanasiaterminal blood collection was taken, tissue was harvested, the liver a

visceral (retroperitoneal and epididymal) fat pads were weighed, acecal contents were obtained for SCFA analysis.

Biochemical assaysPlasma insulin was measured with the mouse ultrasensitive insuenzyme-linked immunosorbent assay (ELISA) (Alpco). Fasting triglycer




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and nonesterified fatty acids (NEFAs) were assayed in serum with kitsfor these analytes (Wako Chemicals). Liver triglycerides were mea-sured with free glycerol reagent (Sigma) after ethanolic KOH extrac-tion. Plasma leptin was measured by ELISA (Crystal Chem). HOMA-IR,an estimate of insulin resistance, was calculated as follows: [fasting glu-cose (mg/dl) fasting insulin (mU/ml)]/405. Cecal SCFA content wasdetermined by gas chromatography.

Gene expressionTotal RNA was extracted with TRIzol reagent (Invitrogen), and com-plementary DNA was produced with the SuperScript III First-StrandSynthesis System (Invitrogen). TaqMan quantitative PCR was performedwith primers for FIAF (Mm00480431_m1, Applied Biosystems). Geneexpression was normalized to the housekeeping gene b-actin.

Statistical analysisFor in vivo physiology experiments, all data are expressed as means SEM. Statistical analyses were performed with GraphPad Prism (v. 5).The threshold of statistical significance was set at P< 0.05.

SUPPLEMENTARY MATERIALS

www.sciencetranslationalmedicine.org/cgi/content/full/5/178/178ra41/DC1

Materials and Methods

Fig. S1. Effect of RYGB on glucose metabolism.

Fig. S2. RYGB alters the gut microbiota independently of weight loss.

Fig. S3. Relative abundance of Enterobacteriales over time and space.

Fig. S4. Determination and quantification of Archaea and methanogens in fecal DNA samples

in RYGB, SHAM, and WMS animals.

Fig. S5. Phenotypic changes between germ-free mice colonized with microbiota from either

RYGB or WMS donors.

Fig. S6. Comparisons of body weight and adiposity markers in SHAM-R and WMS-R mice.

Fig. S7. Ileal FIAF gene expression in germ-free recipient mice.

Fig. S8. Potential mechanisms by which altered microbiota after RYGB affect host metabolic

function.

Table S1. One-week food i ntake and fecal calorimetry analysis of a cohort of RYGB, SHAM, andWMS animals.

Table S2. Two-hour fasted blood concentrations of glucose, insulin, calculated HOMA-IR, tri-

glycerides, and NEFAs in mice maintained on HFD.

Table S3. 16S rRNA gene sequencing metadata from fecal time series.

Table S4. Taxonomic groups with differential relative abundance between treatments.

Table S5. 16S rRNA gene sequencing metadata from intestinal axis sampling.

Table S6. 16S rRNA gene sequencing metadata from fecal transplants.

Table S7. Taxonomic groups with relative abundance between transplant recipients.

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Acknowledgments: We thank C. Maurice for helpful advice; D. Gootenberg, S. Lajoie, a

A. Pfalzer for technical assistance; N. Stylopoulos for contributions to surgical model deve

ment; C. Reardon and C. Daly of the Bauer Core Facility for sequencing; L. Kirby (Universit

Arkansas Central Analytical Laboratory) for fecal analysis; and V. Yeliseyev, M. Delaney, and L

of the Harvard Digestive Diseases Center Gnotobiotic Core Facility for technical assistance,

vice with the microbiota transfer studies, and SCFA analysis of cecal samples. Funding:

DK088661 (L.M.K.), NIH P50 GM068763 (P.J.T.), F32 DK095561 (A.P.L.), P30DK034854 (Harv

Digestive Diseases Center), and Ethicon Surgical Care (L.M.K.). Author contributions: A.P.L., P

and L.M.K. designed the experiments and wrote the paper; M.P. produced surgical mouse mod

J.-M.L. performed 16Ssequencing of samples; P.J.T. analyzed 16Ssequencing data; A.P.L. collec

and processed the samples, performed metabolic phenotyping experiments, and analyzed rela

data; S.M. provided technical assistance and critical reading and editing of the manusc

Competing interests: L.M.K. receives funding as a consultant for Ethicon Surgical Care. A.

L.M.K., and P.J.T. are named inventors on a patent related to this work (serial 13/780,284). M

J.-M.L., and S.M. declare no competing financial interests. Data and materials availabi

16S rRNA gene sequencing reads are deposited in MG-RAST (accession no. 1331).

Submitted 11 January 2013

Accepted 5 March 2013

Published 27 March 2013

10.1126/scitranslmed.3005687

Citation: A. P. Liou, M. Paziuk, J.-M. Luevano Jr., S. Machineni, P. J. Turnbaugh, L. M. Kap

Conserved shifts in the gut microbiota due to gastric bypass reduce host weight and adipo

Sci. Transl. Med. 5, 178ra41 (2013).



aletracao da microbiota gastrica em bypass yroux

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