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Impact of laparoscopic Roux-en-Y gastric bypass and sleeve gastrectomy on gut microbiota: a metagenomic comparative analysis

Open AccessPublished:March 20, 2020DOI:https://doi.org/10.1016/j.soard.2020.03.014

      Abstract

      Background

      Bariatric surgery is an effective therapeutic procedure for morbidly obese patients. The 2 most common interventions are sleeve gastrectomy (SG) and laparoscopic Roux-en-Y gastric bypass (LRYGB).

      Objectives

      The aim of this study was to compare microbiome long-term microbiome after SG and LRYGB surgery in obese patients.

      Setting

      University Hospital, France; University Hospital, United States; and University Hospital, Switzerland.

      Methods

      Eighty-nine and 108 patients who underwent SG and LRYGB, respectively, were recruited. Stools were collected before and 6 months after surgery. Microbial DNA was analyzed with shotgun metagenomic sequencing (SOLiD 5500 xl Wildfire). MSPminer, a novel innovative tool to characterize new in silico biological entities, was used to identify 715 Metagenomic Species Pan-genome. One hundred forty-eight functional modules were analyzed using GOmixer and KEGG database.

      Results

      Both interventions resulted in a similar increase of Shannon’s diversity index and gene richness of gut microbiota, in parallel with weight loss, but the changes of microbial composition were different. LRYGB led to higher relative abundance of aero-tolerant bacteria, such as Escherichia coli and buccal species, such as Streptococcus and Veillonella spp. In contrast, anaerobes, such as Clostridium, were more abundant after SG, suggesting better conservation of anaerobic conditions in the gut. Enrichment of Akkermansia muciniphila was also observed after both surgeries. Function-level changes included higher potential for bacterial use of supplements, such as vitamin B12, B1, and iron upon LRYGB.

      Conclusion

      Microbiota changes after bariatric surgery depend on the nature of the intervention. LRYGB induces greater taxonomic and functional changes in gut microbiota than SG. Possible long-term health consequences of these alterations remain to be established.

      Key words

      The last decades have seen a dramatic increase in obesity rates worldwide [
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      • Hu F.B.
      The epidemiology of obesity: a big picture.
      ]. Bariatric surgery is currently the most effective strategy for morbidly obese patients with a sustainable weight loss and a success rate at 5 years >66% [
      • Nocca D.
      • Loureiro M.
      • Skalli E.M.
      • et al.
      Five-year results of laparoscopic sleeve gastrectomy for the treatment of severe obesity.
      ]. The 2 main surgical procedures are laparoscopic Roux-en-Y gastric bypass (LRYGB) and sleeve gastrectomy (SG) [
      • Colquitt J.L.
      • Pickett K.
      • Loveman E.
      • Frampton G.K.
      Surgery for weight loss in adults.
      ].
      A recent report indicates no difference regarding the excessive body mass index loss, quality of life, improvement of co-morbidities, and fatal consequences over a period of 5 years between LRYGB and SG even if LRYGB was more efficient to treat gastroesophageal reflux disease and dyslipidemia [
      • Peterli R.
      • Wölnerhanssen B.K.
      • Peters T.
      • et al.
      Effect of laparoscopic sleeve gastrectomy vs laparoscopic Roux-en-Y gastric bypass on weight loss in patients with morbid obesity: the SM-BOSS randomized clinical trial.
      ].
      Several studies support the hypothesis that gut microbiota plays a key role in obesity [
      • Baothman O.A.
      • Zamzami M.A.
      • Taher I.
      • Abubaker J.
      • Abu-Farha M.
      The role of gut microbiota in the development of obesity and diabetes.
      ,
      • Turnbaugh P.J.
      • Ley R.E.
      • Mahowald M.A.
      • Magrini V.
      • Mardis E.R.
      • Gordon J.I.
      An obesity-associated gut microbiome with increased capacity for energy harvest.
      ,
      • Turnbaugh P.J.
      • Gordon J.I.
      The core gut microbiome, energy balance and obesity.
      ,
      • Le Chatelier E.
      • Nielsen T.
      • Qin J.
      • et al.
      Richness of human gut microbiome correlates with metabolic markers.
      ]. Energy metabolism, one of the major roles of gut microbiome, occurs through by-products, such as short-chain fatty acids, that result from microbial fermentation of carbohydrate fibers in the gut [
      • Morrison D.J.
      • Preston T.
      Formation of short chain fatty acids by the gut microbiota and their impact on human metabolism.
      ]. Individuals with lower gene richness are more prone to insulin resistance and dyslipidemia [
      • Le Chatelier E.
      • Nielsen T.
      • Qin J.
      • et al.
      Richness of human gut microbiome correlates with metabolic markers.
      ]. Akkermansia muciniphila, has been consistently reported to be negatively associated to obesity and insulin sensitivity and its ability to degrade mucin can improve metabolic health during dietary interventions [
      • Dao M.C.
      • Everard A.
      • Aron-Wisnewsky J.
      • et al.
      Akkermansia muciniphila and improved metabolic health during a dietary intervention in obesity: relationship with gut microbiome richness and ecology.
      ,
      • Everard A.
      • Belzer C.
      • Geurts L.
      • et al.
      Cross-talk between Akkermansia muciniphila and intestinal epithelium controls diet-induced obesity.
      ,
      • Plovier H.
      • Everard A.
      • Druart C.
      • et al.
      A purified membrane protein from Akkermansia muciniphila or the pasteurized bacterium improves metabolism in obese and diabetic mice.
      ]. To investigate the impact of bariatric surgeries on gut microbiota, patients who have undergone either LRYGB or SG were compared with their preoperative (baseline) microbiota [
      • Palleja A.
      • Kashani A.
      • Allin K.H.
      • et al.
      Roux-en-Y gastric bypass surgery of morbidly obese patients induces swift and persistent changes of the individual gut microbiota.
      ,
      • Liou A.P.
      • Paziuk M.
      • Luevano J.-M.
      • Machineni S.
      • Turnbaugh P.J.
      • Kaplan L.M.
      Conserved shifts in the gut microbiota due to gastric bypass reduce host weight and adiposity.
      ,
      • Kong L.-C.
      • Tap J.
      • Aron-Wisnewsky J.
      • et al.
      Gut microbiota after gastric bypass in human obesity: increased richness and associations of bacterial genera with adipose tissue genes.
      ,
      • Furet J.-P.
      • Kong L.-C.
      • Tap J.
      • et al.
      Differential adaptation of human gut microbiota to bariatric surgery-induced weight loss: links with metabolic and low-grade inflammation markers.
      ,
      • Zhang H.
      • DiBaise J.K.
      • Zuccolo A.
      • et al.
      Human gut microbiota in obesity and after gastric bypass.
      ,
      • Medina D.A.
      • Pedreros J.P.
      • Turiel D.
      • et al.
      Distinct patterns in the gut microbiota after surgical or medical therapy in obese patients.
      ,
      • Murphy R.
      • Tsai P.
      • Jüllig M.
      • Liu A.
      • Plank L.
      • Booth M.
      Differential changes in gut microbiota after gastric bypass and sleeve gastrectomy bariatric surgery vary according to diabetes remission.
      ]. A. muciniphila and Escherichia coli were both reported to be highly increased after LRYGB [
      • Palleja A.
      • Kashani A.
      • Allin K.H.
      • et al.
      Roux-en-Y gastric bypass surgery of morbidly obese patients induces swift and persistent changes of the individual gut microbiota.
      ,
      • Liou A.P.
      • Paziuk M.
      • Luevano J.-M.
      • Machineni S.
      • Turnbaugh P.J.
      • Kaplan L.M.
      Conserved shifts in the gut microbiota due to gastric bypass reduce host weight and adiposity.
      ]. Liou et al. [
      • Liou A.P.
      • Paziuk M.
      • Luevano J.-M.
      • Machineni S.
      • Turnbaugh P.J.
      • Kaplan L.M.
      Conserved shifts in the gut microbiota due to gastric bypass reduce host weight and adiposity.
      ], transplanted germ-free mice with stool from LRYGB-treated mice and observed a reduction of fat mass, suggesting the gut composition induced by surgery has a direct effect on weight loss and host metabolism [
      • Tremaroli V.
      • Karlsson F.
      • Werling M.
      • et al.
      Roux-en-Y gastric bypass and vertical banded gastroplasty induce long-term changes on the human gut microbiome contributing to fat mass regulation.
      ,
      • Li J.V.
      • Ashrafian H.
      • Bueter M.
      • et al.
      Metabolic surgery profoundly influences gut microbial-host metabolic cross-talk.
      ].
      Metagenomics shotgun sequencing surpasses the limitations and biases of 16 S gene amplicon sequencing by providing higher resolution taxonomic and functional profiling [
      • Ranjan R.
      • Rani A.
      • Metwally A.
      • McGee H.S.
      • Perkins D.L.
      Analysis of the microbiome: advantages of whole genome shotgun versus 16 S amplicon sequencing.
      ]. To our knowledge, only a few studies used a shotgun sequencing–based approach to characterize the microbiome modulation after LRYGB [
      • Palleja A.
      • Kashani A.
      • Allin K.H.
      • et al.
      Roux-en-Y gastric bypass surgery of morbidly obese patients induces swift and persistent changes of the individual gut microbiota.
      ,
      • Murphy R.
      • Tsai P.
      • Jüllig M.
      • Liu A.
      • Plank L.
      • Booth M.
      Differential changes in gut microbiota after gastric bypass and sleeve gastrectomy bariatric surgery vary according to diabetes remission.
      ,
      • Tremaroli V.
      • Karlsson F.
      • Werling M.
      • et al.
      Roux-en-Y gastric bypass and vertical banded gastroplasty induce long-term changes on the human gut microbiome contributing to fat mass regulation.
      ,
      • Graessler J.
      • Qin Y.
      • Zhong H.
      • et al.
      Metagenomic sequencing of the human gut microbiome before and after bariatric surgery in obese patients with type 2 diabetes: correlation with inflammatory and metabolic parameters.
      ,
      • Ilhan Z.E.
      • DiBaise J.K.
      • Isern N.G.
      • et al.
      Distinctive microbiomes and metabolites linked with weight loss after gastric bypass, but not gastric banding.
      ,
      • Medina D.A.
      • Li T.
      • Thomson P.
      • Artacho A.
      • Pérez-Brocal V.
      • Moya A.
      Cross-regional view of functional and taxonomic microbiota composition in obesity and post-obesity treatment shows country specific microbial contribution.
      ] and SG [
      • Murphy R.
      • Tsai P.
      • Jüllig M.
      • Liu A.
      • Plank L.
      • Booth M.
      Differential changes in gut microbiota after gastric bypass and sleeve gastrectomy bariatric surgery vary according to diabetes remission.
      ,
      • Medina D.A.
      • Li T.
      • Thomson P.
      • Artacho A.
      • Pérez-Brocal V.
      • Moya A.
      Cross-regional view of functional and taxonomic microbiota composition in obesity and post-obesity treatment shows country specific microbial contribution.
      ,
      • Damms-Machado A.
      • Mitra S.
      • Schollenberger A.E.
      • et al.
      Effects of surgical and dietary weight loss therapy for obesity on gut microbiota composition and nutrient absorption.
      ,
      • Liu R.
      • Hong J.
      • Xu X.
      • et al.
      Gut microbiome and serum metabolome alterations in obesity and after weight-loss intervention.
      ]. However, previous reports [
      • Palleja A.
      • Kashani A.
      • Allin K.H.
      • et al.
      Roux-en-Y gastric bypass surgery of morbidly obese patients induces swift and persistent changes of the individual gut microbiota.
      ,
      • Murphy R.
      • Tsai P.
      • Jüllig M.
      • Liu A.
      • Plank L.
      • Booth M.
      Differential changes in gut microbiota after gastric bypass and sleeve gastrectomy bariatric surgery vary according to diabetes remission.
      ,
      • Tremaroli V.
      • Karlsson F.
      • Werling M.
      • et al.
      Roux-en-Y gastric bypass and vertical banded gastroplasty induce long-term changes on the human gut microbiome contributing to fat mass regulation.
      ,
      • Graessler J.
      • Qin Y.
      • Zhong H.
      • et al.
      Metagenomic sequencing of the human gut microbiome before and after bariatric surgery in obese patients with type 2 diabetes: correlation with inflammatory and metabolic parameters.
      ,
      • Ilhan Z.E.
      • DiBaise J.K.
      • Isern N.G.
      • et al.
      Distinctive microbiomes and metabolites linked with weight loss after gastric bypass, but not gastric banding.
      ,
      • Damms-Machado A.
      • Mitra S.
      • Schollenberger A.E.
      • et al.
      Effects of surgical and dietary weight loss therapy for obesity on gut microbiota composition and nutrient absorption.
      ] were limited by low number of patients, varying from 6 to 23, leading to a lack of statistical power. No direct comparison between the 2 interventions involving large cohorts and their effect on the gut microbiome has been published.
      Here, we present the largest metagenomics study to date investigating the effects of LRYGB and SG on gut microbiome based on preoperative and 6-month postoperative stools. This international multicenter study is based on 89 and 108 obese patients who underwent LRYGB and SG, respectively. Our analysis depends on a recent in silico method that discovers and quantifies microbial species, including those previously unknown [
      • Plaza Oñate F.
      • Le Chatelier E.
      • Almeida M.
      • et al.
      MSPminer: abundance-based reconstitution of microbial pan-genomes from shotgun metagenomic data.
      ]. The goal was to understand taxonomic and functional changes that the 2 surgery types induce in the gut microbiome and also the differences between both interventions.

      Methods

      Study population

      In total, 275 patients diagnosed with obesity scheduled for LRYGB or SG have been recruited in 4 clinical centers in the following 3 countries: France, Switzerland, and the United States. For the present investigation, inclusion criteria were age ≥18 years and body mass index ≥35. Exclusion criteria were use of antibiotics and bowel cleansing for colonoscopy during the last 2 months before fecal sampling. The study was approved by the Ethical Committee of Basel in Switzerland (reference 272/05), the French Ethical Committee “Comité de Protection des Personnes” Ile de France VI (reference 2604-2012), and the Geisinger institutional review board in the United States (2004-0255).

      Data collection

      Fecal samples were self-collected 1 month before and 6 months after the surgery and stored essentially as described by the International Human Microbiome Standards consortium standard operating protocol 5 [
      SOPs05 [homepage on the Internet]. International Human Microbiome Standards; c2015 [cited 2018 Jan 9].
      ]. The medical records of participants were reviewed for demographic data, co-morbidities, and medications. In total, 531 fecal samples were collected before and 6 months after surgery from 275 patients. Patients with only 1 collected stool sample were excluded. Consequently, 197 patients were analyzed with their respective 197 preoperative and 197 postoperative stools that were collected and sequenced.

      DNA extraction and sequencing

      Fecal DNA extraction was carried out according to the International Human Microbiome Standards consortium standard operating protocol 7 [
      SOPs07 [homepage on the Internet]. International Human Microbiome Standards; c2015 [cited 2018 Jan 9].
      ]. Shotgun metagenomic sequencing was performed using SOLiD 5500 xl Wildfire sequencing system (Life Technologies [Life Technologies, Carlsbad, CA, USA] then ThermoFisher [ThermoFisher, Waltham, MA, USA]). Five hundred thirty-one samples were sequenced yielding an average of 81.782 million (±33.261 million) 35 base-long single reads.

      Reads mapping

      Reads were cleaned using an in-house procedure included in METEOR software [

      Pons N, Batto J-M, Kennedy S, et al. A platform for quantitative metagenomic profiling of complex system. Poster presented at: JOBIM; September 7-9, 2010; Montpellier, France.

      ] to remove (1) those containing resilient sequencing adapters/barcodes, and (2) those with average quality <20. Cleaned reads were subsequently filtered from human and other possible food contaminant DNA (using Human genome RCh37-p10, Bos taurus and Arabidopsis thaliana) using Bowtie 1 [
      • Langmead B.
      • Trapnell C.
      • Pop M.
      • Salzberg S.L.
      Ultrafast and memory-efficient alignment of short DNA sequences to the human genome.
      ] (2 mismatches permitted) included in METEOR software. The gene abundance profiling was based on the integrated catalogue of reference genes in the human gut microbiome [
      • Li J.
      • Jia H.
      • Cai X.
      • et al.
      An integrated catalog of reference genes in the human gut microbiome.
      ]. Filtered high-quality reads were mapped to the 9.9 M gene catalogue using Bowtie 1 (3 mismatches permitted) included in METEOR software. Using METEOR, the gene abundance profiling table was generated using a 2-step procedure. First, the unique mapped reads (reads mapped to a unique gene in the catalogue) were attributed to their corresponding genes. Second, the shared reads (reads that mapped with the same alignment score to multiple genes in the catalogue) were attributed according to the ratio of their unique mapping counts. The counts were then normalized according to the reads per kilobase of exon model per million mapped reads strategy (normalization by the gene size and the number of total mapped reads reported in frequency) to give the final gene relative abundance profile table.

      Taxonomic annotation

      The genes were annotated using BLASTN alignment method against KEGG and RefSeq genomic databases [
      • Kanehisa M.
      • Goto S.
      • Sato Y.
      • Kawashima M.
      • Furumichi M.
      • Tanabe M.
      Data, information, knowledge and principle: back to metabolism in KEGG.
      ,
      • Tatusova T.
      • Ciufo S.
      • Fedorov B.
      • O’Neill K.
      • Tolstoy I.
      RefSeq microbial genomes database: new representation and annotation strategy.
      ]. The gene annotation method was adapted from Li et al [
      • Li J.
      • Jia H.
      • Cai X.
      • et al.
      An integrated catalog of reference genes in the human gut microbiome.
      ]. Only the hits with a minimum of 80% of query sequence length and 65% nucleotide identity were considered in the annotation process. The similarity thresholds for the phylum, genus, and species taxonomic ranges were 65%, 80%, and 95%, respectively. Genes with multiple hits deprived of any consensus (a consensus was defined as 10% of hits having the same annotation) for their taxonomic associations were annotated at a higher taxonomic range until a consensus was established.

      Functional annotation

      Translated genes were aligned using BLASP version 2.6.0 against KEGG Release 81.0 (April 2017). Hits with a bitscore inferior to 60 or with an e-value superior to .01 were discarded. Each gene was finally assigned to the functional group (KEGG Ortholog or Enzyme Commission) associated with the most significant hit.

      Metagenomic species Pan-genomes processing

      The integrated reference catalogue of the human gut microbiome [
      • Li J.
      • Jia H.
      • Cai X.
      • et al.
      An integrated catalog of reference genes in the human gut microbiome.
      ] was organized into 1696 Metagenomic Species Pan-genomes (MSPs) with MSPminer [
      • Plaza Oñate F.
      • Le Chatelier E.
      • Almeida M.
      • et al.
      MSPminer: abundance-based reconstitution of microbial pan-genomes from shotgun metagenomic data.
      ] by grouping coabundant genes across 1267 stool samples coming from cohorts distinct of the one used in this study. For each MSP, the median vector of the square-root transformed counts of its core genes was computed by using the 531 samples of this study. MSPs detected in <5 samples were discarded. Then, the relationship between this median vector and the core genes was assessed with the concordance correlation coefficient by Lin [
      • Lin L.I.
      A concordance correlation coefficient to evaluate reproducibility.
      ]. Finally, the abundance of the MSP was estimated from its 30 core genes with the highest concordance.

      Relative abundance estimation and feature selection

      Of 531 samples, 394 from 197 patients with 2 timepoints were used for further analysis. The relative abundances at phylum level, based on the National Center for Biotechnology Information taxonomy, were computed by summing the relative abundances of all the genes belonging to the same phylum. The relative abundances of functional modules, which were based on the KEGG annotation, were computed by summing the relative abundances of all the genes belonging to the KEGG Orthologous (KO) groups. Abundances of 130 modules from GOmixer [
      • Darzi Y.
      • Falony G.
      • Vieira-Silva S.
      • Raes J.
      Towards biome-specific analysis of meta-omics data.
      ] were calculated by summing the abundances of each KO that belonged to the same module. This set of metabolic modules was selected because it was manually curated based on rigorous literature specific to gut bacterial functions. To increase important functional units that were lacking, 20 modules from KEGG were added to the GOmixer modules (Supplementary Table 1). The relative abundances of MSP were calculated by estimating the median of the 30 top genes belonging to its core genes. Microbial features that were present in <70% of all the samples were removed. After filtering, statistical analysis was performed with the abundances of 15 phyla, 302 MSP, and 5348 KO groups. The values were log10 transformed, to approach normal distributions; a pseudo count equal to the lowest relative abundance value in the cohort was added to all relative abundances, to deal with zeros.

      Gene richness and taxonomic diversity

      The gene richness is a measure of how many unique genes are present in a sample. It was computed from the raw abundance genes table after downsizing based on 5 million–simulated sequencing depth (5 million reads are randomly selected from the original pool of reads) and then computing the mean number of unique genes over 30 repeats (https://github.com/fplaza/CountMatrixDownsizer). To compare with the original work introducing the concept of gene richness with a downsizing at 11 M of reads [
      • Le Chatelier E.
      • Nielsen T.
      • Qin J.
      • et al.
      Richness of human gut microbiome correlates with metabolic markers.
      ], it was then recalculated using an in-house predictive model (linear regression). The Shannon index was computed to assess taxonomic diversity species level [
      • Hugerth L.W.
      • Andersson A.F.
      Analysing microbial community composition through amplicon sequencing: from sampling to hypothesis testing.
      ].

      Statistical test analysis

      All statistical analyses were performed with R, version 3.3.2 (The R Project for Statistical Computing, Vienna, Austria). Clinical variables were summarized as medians with interquartile ranges or as frequencies with percentages. The Fisher’s exact test was used to compare categoric variables between patients who underwent SG and LRYGB surgery. Adonis tests were used from the R package vegan for differential analysis according to groups [

      Oksanen J, Blanchet F-G, Friendly M, et al. Vegan: Community Ecology Package. R package version 2.5-6. 2019. Available from: https://CRAN.R-project.org/package=vegan. Accessed September 1, 2019.

      ]. Dissimilarity matrices were calculated using Bray-Curtis dissimilarity on relative abundance values of MSP.

      Statistical analysis to assess the effect of surgery on microbiota

      First, we performed 2 independent analyses for LRYGB and for SG. To test the normality assumption of metagenomic variables, all 302 MSPs and 150 modules distributions were tested with Shapiro-Wilk test. Normality was rejected for all of these metagenomic features (Shapiro-Wilk test, P < 2 × 10−11). Microbiome data are also known to be sparse and overdispersed [
      • Xia Y.
      • Sun J.
      • Chen D.-G.
      Statistical analysis of microbiome data with R.
      ]. Wilcoxon signed-rank test was used because it does not require the assumption of normal distribution. Because this is a prospective study and the samples are not independent, 2-sided Wilcoxon signed-rank test was used. Multiple testing was controlled by Benjamini-Hochberg false-discovery rate [
      • Haynes W.
      Benjamini–Hochberg Method.
      ]. To ensure the MSP were significant, an additional filter based on the median fold change of relative abundance was applied. The median log2 fold change (FC_log2) is the ratio of the median of this feature in all patients after surgery divided by the median of this feature in all patients before the gastric surgery.
      FClog2=log2(medianPostoperativestoolmedianPreoperativestools)


      To summarize, a P value < .05 and a (2-fold) FC ≥ 1 or FC ≤ −1 were considered statistically significant.

      Statistical analysis to compare the 2 types of surgery

      To evaluate the change of microbiome composition induced by the gastric surgery, the relative abundances from the postoperative stool were normalized by dividing them with relative abundances from preoperative stools for each patient and then log2 transformed. The abundance ratios were then used to compare the surgery types by performing Wilcoxon rank-sum test on the microbial features that were significant at least in 1 surgery group. Multiple testing was controlled by Benjamini-Hochberg.

      Correlation between functional modules and MSPs

      We performed 2 independent analyses for LRYGB and for SG groups. In this context, Spearman correlation coefficients were calculated for every MSP that was found significantly impacted by gastric surgery and 150 functional modules. Relative abundances before and after surgery were used for the correlation and only correlation coefficients superior to .7 were retained for subsequent analysis.

      Results

      Demographic description

      One hundred ninety-seven patients have been included in 3 different countries (France, the United States, and Switzerland) before they underwent bariatric surgery (89 LRYGB and 108 SG). Of these, 86 patients were included by 2 French clinical centers, 73 patients from the United States, and 38 patients from Switzerland. We checked if the presurgery characteristics of the cohort were homogeneous depending on the type of surgery performed (Supplementary Table 2). Significant differences were found only for the country of origin (Fisher exact test, P < .001) and diabetes prevalence (Fisher exact test, P < .05). Important decrease of body mass index was important after both surgical procedures (Supplementary Tables 3 and 4).

      Analysis of gut microbiota before surgery

      Because the surgery type was confounded with the country of origin, we first analyzed the differences in microbial gut composition at MSP level between the patients before surgery, using a principal component analysis of log-transformed relative abundances of MSPs (Fig. 1). Patients from Europe (France and Switzerland) were clearly separated from the U.S. cohort (Fig. 1A, Adonis P value = .001) and by the type of surgery performed (Fig. 1B, Adonis P = .001). However, in the Swiss cohort, no difference (Fig. 1C, Adonis P = .074) was observed between the patients who underwent LRYGB (n = 20) and SG (n = 18). To overcome this limitation, Wilcoxon rank-sum test on ratio was used to normalize the microbiome profile at baseline to reduce variability induced by country of origin.
      Figure thumbnail gr1
      Fig. 1Principal component analysis based on log transformed Metagenomic Species Pan-genome abundances. Adonis tests were performed to assess the variance in preoperative microbiota profiles. Associated P values are shown for each analysis and a P value < .05 was considered as significant. Separation between patients from the United States and Europe before surgery (A). Separation of patients who underwent laparoscopic Roux-en-Y gastric bypass (LRYGB) and sleeve gastrectomy (SG) before surgery (B). No separation for Swiss patients before surgery (C).

      Surgery effects on gut microbial diversity and phylum-level composition

      We estimated Shannon microbial diversity and gene richness in each sample. Compared with baseline, the Shannon index (Fig. 2) was significantly increased by surgery after 6 months (Wilcoxon signed-rank test, LRYGB: P = 7.5 × 10−6 and SG: P = 7.3 × 10−11). Similarly, gene richness was increased very significantly (∼15%) by both procedures (LRYGB: P = 3.8 × 10−5, SG: P = 5.9 × 10−10). As expected, the following 5 phyla were the most abundant in human intestinal gut: Bacteroidetes, Firmicutes, Proteobacteria, Actinobacteria, and Verrucomicrobia (Supplementary Fig. 1). Before surgery, phylum composition was comparable between the 2 groups. Proteobacteria was significantly increased by LRYGB (Wilcoxon signed-rank test, P = 1.9 × 10−12) and SG (Wilcoxon signed-rank test, P = 5.4 × 10−6). Verrucomicrobia was enriched by LRYGB (Wilcoxon signed-rank test, P = 2.1 × 10−10) and SG (Wilcoxon signed-rank test, P = 3.0 × 10−10). Firmicutes showed a slight decrease after both surgeries.
      Figure thumbnail gr2
      Fig. 2Shannon microbial diversity and gene richness. Compared with baseline, the Shannon index (left side) was significantly increased by surgery after 6 months (Wilcoxon signed-rank test, laparoscopic Roux-en-Y gastric bypass [LRYGB]: P = 7.5 × 10−6 and sleeve gastrectomy [SG]: P = 7.3 × 10−11). Gene richness (right side) was also significantly higher 6 months after LRYGB (Wilcoxon signed-rank test, LRYGB: P = 3.8 × 10−5 and after SG: P = 5.9 × 10−10).

      Surgery effects on microbiome species composition

      Fifty-one MSP were significantly impacted by LRYGB (P < .05 and FC_log2 ≥1 or FC_log2 ≤ −1, Wilcoxon signed-rank tests) and 48 after SG (Figs. 3A and 4A ; detailed view in Supplementary Figs. 2 and 3, numeric values in Supplementary Tables 5 and 6). Of these, 20 were common to both procedures and were overwhelmingly (18 of 20) enriched upon surgery. Notably, the beneficial Verrucomicrobia A. muciniphila was enriched (LRYGB: FC_log2 = 1.61, SG: FC_log2 = 1.82), but also the potentially proinflammatory Proteobacteria like E. coli (LRYGB: FC_log2 = 5.22, SG: FC_log2 = 1.04), Klebsiella pneumoniae (LRYGB: FC_log2 = 4.03, SG: FC_log2 = 2.09), and Haemophilus parainfluenzae (LRYGB: FC_log2 = 1.61, SG: FC_log2 = 1.4). Faecalibacterium prausnitzii was less abundant only after LRYGB (FC_log2 = −1.43). Five oral species were enriched by both procedures, of which most strongly Veillonela parvula (LRYGB: FC_log2 = 2.65, SG: FC_log2 = 1.92) and Streptococcus salivarius (LRYGB: FC_log2 = 4.07, SG: FC_log2 = 1.98) but also Streptococcus gordonii, Streptococcus mutans, and Streptococcus parasanguinis. Additional 6 oral species (Fusobacteria nucleatum, Streptococcus anginosus, Streptococcus oralis, Streptococcus vestibularis, Veillonela atypica, and Veillonela sp oral) were enriched by LRYGB but not SG. Interestingly, 2 oral Bifidobacteria were depleted by interventions, 1 by LRYGB (Bifidobacteria bifidum) and 1 by SG (Bifidobacteria dentium). Four MSPs with no species-level annotation were enriched by both surgery procedures (msp_0868, msp_0344, msp_0582, and msp_0355).
      Figure thumbnail gr3
      Fig. 3Microbial changes (MSP) after LRYGB. Median fold changes (Log2) of relative abundances (postsurgery/baseline) for 51 MSP that were significantly impacted by laparoscopic Roux-en-Y gastric bypass compared with baseline. MSP were regrouped by phylum and ordered according their fold change within the phylum (A). Eleven modules were significantly increased after laparoscopic Roux-en-Y gastric bypass and were regrouped by functional category (B).
      Figure thumbnail gr4
      Fig. 4Microbial changes (MSP) after sleeve gastrectomy. Median fold changes (Log2) of relative abundances (postsurgery/baseline) for 49 MSP that were significantly impacted by laparoscopic Roux-en-Y gastric bypass compared with baseline. MSP were regrouped by phylum and ordered according their fold change within the phylum (A). Four modules were significantly increased after laparoscopic Roux-en-Y gastric bypass and were regrouped by functional category (B).
      Of 78 MSPs impacted by LRYGB and/or SG 24 had abundance ratios significantly different between LRYGB and SG groups (P < .05, Wilcoxon rank-sum tests; Fig. 5A; Supplementary Table 7). Two Proteobacteria (E. coli and K. pneumonia), and 7 oral MSPs (2 S. oralis, S. parasanguinis, S. salivarius, V. atypica, V. parvula, and V. sp. oral) were more enriched by LRYGB than SG surgery. One oral species, B. bifidum, was more depleted. Two Roseburia (R. faecis and R. hominis) were also more enriched by LRYGB, as was E. faecalis. The 5 MSPs more enriched by SG and annotated at the species level (A. hadrus, C. sp KLE, F. plautii, O. sp. KLE, and R. gnavus) all belonged to Firmicutes order Clostridiales.
      Figure thumbnail gr5
      Fig. 5Differences of changes induced by laparoscopic Roux-en-Y gastric bypass (LRYGB) and sleeve gastrectomy (SG) at microbial changes level. Log2 transformed relative abundance ratios (postsurgery/baseline) of 24 microbial changes that were significantly different regarding the surgery type (A). Log2 transformed relative abundance ratios (postsurgery/baseline) of 11 modules that were significantly different regarding the surgery type (B).

      Effect of LRYGB and SG on microbiome functions

      Thirteen functional modules were significantly more abundant after LRYGB and 6 after SG; 5 were common to both surgical interventions (Figs. 3B and 4B, Supplementary Tables 8 and 9, Supplementary Figs. 4 and 5). Five common modules were ABC transporters implied in vitamin B12 (LRYGB: FC_log2 = 5.23, SG: FC_log2 = 1.49), histidine (LRYGB: FC_log2 = 5.51, SG: FC_log2 = 1.18), lysine/arginine (LRYGB: FC_log2 = 5.16, SG: FC_log2 = 1.16), putrescin (LRYGB: FC_log2 = 4.95, SG: FC_log2 = 1.6), and manganese/zinc (LRYGB: FC_log2 = 3.30, SG: FC_log2 = 2.04) transport. Another manganese/zinc transport system was increased only after LYRGB (M00319; FC_log2 = 3.39), as were Thiamine and Urea transport systems. Glutamate degradation module (FC_log2 = 1.39) was more abundant after SG while significant increase of nitrate reduction (FC_log2 = 1.00) and propionate production (FC_log2 = 2.53) modules were enriched after LRYGB.
      Of 14 functional modules affected by LRYGB and/or SG 13 were found to be significantly different between LRYGB and SG groups (P < .05, Wilcoxon rank-sum tests; Fig. 5B, Supplementary Table 10). Notably, 8 functional modules involved in ABC transporters were more enriched in patients after LRYGB compared with the SG surgery (histidine and lysine, putrescin, vitamin B12, manganese/zinc, urea, and thiamine transport system). Modules involved in nitrate respiration and propionate production via kinase were more increased by LRYGB.

      Correlations of functional modules and MSPs

      Spearman correlations between relative abundances of 78 MSP and 150 modules were computed independently for 2 groups of patients, LRYGB and SG. Regarding the former, 8 modules were correlated to a set of 5 MSP annotated to V. parvula, S. vestibularis, S. salivarius, and S. parasanguinis, and E. coli (Spearman’s rho ≥ .7, Supplementary Table 11).

      Discussion

      Microbiome composition is differentially altered by LRYGB and SG

      Physiologic and anatomic changes of the gastrointestinal tract after bariatric surgery modify gut motility, gastric acid secretion, bile acid processing, and gut hormone secretion [
      • Quercia I.
      • Dutia R.
      • Kotler D.P.
      • Belsley S.
      • Laferrère B.
      Gastrointestinal changes after bariatric surgery.
      ]. Using whole metagenome shotgun sequencing with the largest cohort of patients to date, we confirmed gut microbiota was strongly modulated after SG and LRYGB with notable similarities and differences. Gene richness was increased for most of the patients after both surgical interventions. However, the most important divergence was the extent of the increase of Proteobacteria species. E. coli and K. pneumoniae were both increased by surgery but the increase was significantly stronger after LRYGB confirming results from other studies [
      • Palleja A.
      • Kashani A.
      • Allin K.H.
      • et al.
      Roux-en-Y gastric bypass surgery of morbidly obese patients induces swift and persistent changes of the individual gut microbiota.
      ,
      • Graessler J.
      • Qin Y.
      • Zhong H.
      • et al.
      Metagenomic sequencing of the human gut microbiome before and after bariatric surgery in obese patients with type 2 diabetes: correlation with inflammatory and metabolic parameters.
      ]. Increase of E. coli may reflect host and gut adaptation to maximize energy harvest in starvation-like conditions after bariatric surgery [
      • Furet J.-P.
      • Kong L.-C.
      • Tap J.
      • et al.
      Differential adaptation of human gut microbiota to bariatric surgery-induced weight loss: links with metabolic and low-grade inflammation markers.
      ]. A. muciniphila, known to be negatively correlated to inflammation, was increased in patients after SG or LRYGB in similar proportion in our study confirming results from other studies [
      • Palleja A.
      • Kashani A.
      • Allin K.H.
      • et al.
      Roux-en-Y gastric bypass surgery of morbidly obese patients induces swift and persistent changes of the individual gut microbiota.
      ,
      • Medina D.A.
      • Pedreros J.P.
      • Turiel D.
      • et al.
      Distinct patterns in the gut microbiota after surgical or medical therapy in obese patients.
      ,
      • Graessler J.
      • Qin Y.
      • Zhong H.
      • et al.
      Metagenomic sequencing of the human gut microbiome before and after bariatric surgery in obese patients with type 2 diabetes: correlation with inflammatory and metabolic parameters.
      ]. This species has been found to reverse obesity and increase mucus layer thickness in mice fed a high-fat diet [
      • Everard A.
      • Belzer C.
      • Geurts L.
      • et al.
      Cross-talk between Akkermansia muciniphila and intestinal epithelium controls diet-induced obesity.
      ]. Our study allows us to make the assumption that LRYGB has a higher impact on microbiome than SG in contradiction with a recent study reporting both interventions appeared to have the same impact on gut [
      • Paganelli F.L.
      • Luyer M.
      • Hazelbag C.M.
      • et al.
      Roux-Y gastric bypass and sleeve gastrectomy directly change gut microbiota composition independent of surgery type.
      ].
      In contrast, the number of MSP being negatively affected by bariatric surgery was lower. F. prausnitzii, which is a butyrate-producer, decreased 6 months after surgery in LRYGB while SG had no effect on its presence in feces. The decrease of F. prausnitzii in LYRGB patients was reported in 2 previous studies as well [
      • Palleja A.
      • Kashani A.
      • Allin K.H.
      • et al.
      Roux-en-Y gastric bypass surgery of morbidly obese patients induces swift and persistent changes of the individual gut microbiota.
      ,
      • Medina D.A.
      • Pedreros J.P.
      • Turiel D.
      • et al.
      Distinct patterns in the gut microbiota after surgical or medical therapy in obese patients.
      ,
      • Graessler J.
      • Qin Y.
      • Zhong H.
      • et al.
      Metagenomic sequencing of the human gut microbiome before and after bariatric surgery in obese patients with type 2 diabetes: correlation with inflammatory and metabolic parameters.
      ]. Similarly, R. gnavus and R. torques were also reportedly decreased in LRYGB. This species is well known to produce trans-scialidase to degrade mucin [
      • Crost E.H.
      • Tailford L.E.
      • Monestier M.
      • et al.
      The mucin-degradation strategy of Ruminococcus gnavus: the importance of intramolecular trans-sialidases.
      ] and to be associated with inflammatory bowel diseases and metabolic disorders [
      • Le Chatelier E.
      • Nielsen T.
      • Qin J.
      • et al.
      Richness of human gut microbiome correlates with metabolic markers.
      ]. Some MSPs not annotated at species-level were also detected to be affected by both interventions. These observations were possible because MSPminer does not rely on reference genomes and can reveal new biological entities of interest.

      LRYGB promotes aerotolerant colonization more than SG

      We observed that LRYGB led to a higher increase of oral colonizers (Veillonela and Streptococcus genus) than SG. Possibly, less exposure to the acidic stomach compartment favors access of oral bacteria to the gut. However, facilitated access appears to be insufficient for implementation in the gut and other factors may be needed, as oral Bifidobacteria were depleted after surgery. Moreover, bypassing the duodenum might introduce some oxygen to the gastrointestinal tract [
      • Celiker H.
      A new proposed mechanism of action for gastric bypass surgery: air hypothesis.
      ], which is usually anaerobic, inhibiting growth of obligate anaerobes, such as the Clostridium genus, and promote domination of aerobes [
      • Hartman A.L.
      • Lough D.M.
      • Barupal D.K.
      • et al.
      Human gut microbiome adopts an alternative state following small bowel transplantation.
      ]. According to our results, Clostridium species were negatively impacted by LRYGB while they were enriched after SG suggesting the gut is still largely in anaerobic after SG. Along the same lines, a higher relative abundance of ferredoxin oxidoreductase, which is usually associated with aerobic respiration, was observed after LRYGB relative to SG. Evidence of oxidative stress was also reported with enrichment of functional modules involved in glutathione metabolism in LRYGB patients in concordance with others studies [
      • Palleja A.
      • Kashani A.
      • Allin K.H.
      • et al.
      Roux-en-Y gastric bypass surgery of morbidly obese patients induces swift and persistent changes of the individual gut microbiota.
      ,
      • Tremaroli V.
      • Karlsson F.
      • Werling M.
      • et al.
      Roux-en-Y gastric bypass and vertical banded gastroplasty induce long-term changes on the human gut microbiome contributing to fat mass regulation.
      ].

      Nitrates respiration may favor E. coli expansion after LRYGB

      After LRYGB, signs of nitrate reduction as an alternative form of respiration were observed. Interestingly, it has been recently observed that nitrate can boost growth of E. coli to outcompete species that rely on fermentation only [
      • Tiso M.
      • Schechter A.N.
      Nitrate reduction to nitrite, nitric oxide and ammonia by gut bacteria under physiological conditions.
      ,
      • Winter S.E.
      • Winter M.G.
      • Xavier M.N.
      • et al.
      Host-derived nitrate boosts growth of E. coli in the inflamed gut.
      ]. LRYGB led also to enrichment of a functional module involved in urea transport system. After LRYGB, we also observed an increased potential for trimethylamine oxidized (TMAO) utilization via pathways found in Proteobacteria (torYZ and torC, Supplementary Table 12). These results are in agreement with previous observations showing higher level of plasma circulating plasma TMAO levels in patients after LRYGB compared with SG. A retroconversion model of trimethylamine produced in gut by Enterobacteriaceae from TMAO reduction by gut bacteria has been reported [
      • Hoyles L.
      • Jiménez-Pranteda M.L.
      • Chilloux J.
      • et al.
      Metabolic retroconversion of trimethylamine N-oxide and the gut microbiota.
      ].

      Microbial transportation of supplements is stimulated by bariatric surgery

      The strong increase of ABC transporters, especially Vitamin B12, B1, and manganese/iron transport systems was more pronounced in LRYGB, confirming previous findings [
      • Palleja A.
      • Kashani A.
      • Allin K.H.
      • et al.
      Roux-en-Y gastric bypass surgery of morbidly obese patients induces swift and persistent changes of the individual gut microbiota.
      ]. After surgery, multivitamin, iron, and calcium supplements are provided to compensate for deficiencies caused by food intake reduction and malabsorption [
      • Ilhan Z.E.
      • DiBaise J.K.
      • Isern N.G.
      • et al.
      Distinctive microbiomes and metabolites linked with weight loss after gastric bypass, but not gastric banding.
      ]. Of note, in supplement tablets, vitamin B12, not bound to protein, is subsequently available to bacteria in the intestine. High levels of transport potential of vitamin B12, B1, and iron, particularly in LRYGB, suggest opportunist use of these nutrients by microbes. Transport of vitamin B12 was highly correlated with E. coli while iron transporter was associated with S. salivarius and V. parvula (Supplementary Table 11); these functions may have facilitated enrichment of the cognate species, acting synergistically with the decrease of exposure to acidic stomach compartment.

      Short chain fatty acids are altered by LRYGB and may impact weight loss via a glucagon-like peptide-1–dependent mechanism

      Short-chain fatty acids, metabolites formed by gut microbiota from carbohydrate substrates, can have several beneficial effects on the host. Butyrate and propionate were reported to be associated with weight loss and to have protective properties against diet-induced obesity in mice [
      • Lin H.V.
      • Frassetto A.
      • Kowalik Jr., E.J.
      • et al.
      Butyrate and propionate protect against diet-induced obesity and regulate gut hormones via free fatty acid receptor 3-independent mechanisms.
      ]. More precisely, the study indicated butyrate and propionate impact on gut hormones (by stimulating glucagon-like peptide-1) and food intake reduction. In parallel, postprandial glucagon-like peptide-1 was observed to be significantly increased after LRYGB [
      • Jirapinyo P.
      • Jin D.X.
      • Qazi T.
      • Mishra N.
      • Thompson C.C.
      A Meta-analysis of GLP-1 after Roux-en-Y gastric bypass: impact of surgical technique and measurement strategy.
      ]. Abundance of propionate production module was higher after LRYGB and was also correlated with E. coli (Spearman's rho = .76). In concordance to this observation, Ilhan et al. [
      • Ilhan Z.E.
      • DiBaise J.K.
      • Isern N.G.
      • et al.
      Distinctive microbiomes and metabolites linked with weight loss after gastric bypass, but not gastric banding.
      ] has reported an increase of propionate after LRYGB. Visceral and liver fat were also reduced after propionate delivery in humans [
      • Chambers E.S.
      • Viardot A.
      • Psichas A.
      • et al.
      Effects of targeted delivery of propionate to the human colon on appetite regulation, body weight maintenance and adiposity in overweight adults.
      ]. General glycemic improvement was more pronounced after LRYGB and could be related to higher gut propionate production. Breton et al. [
      • Breton J.
      • Tennoune N.
      • Lucas N.
      • et al.
      Gut commensal E. coli proteins activate host satiety pathways following nutrient-induced bacterial growth.
      ] identified ClpB, a bacterial protein produced by E. coli, as an antigen-mimetic of a neuropeptide involved in the satietogenic system by stimulating GLP-1. The gene coding ClpB was found to be increased by 100 after LRYGB (P < .05, Wilcoxon signed-rank test; not shown), in parallel with the increase of E. coli that encodes it. Taken together, the data from literature and our results support that E. coli may potentially influence both host appetite and metabolism via a complex activation cascade.

      Conclusions

      A direct comparison of microbiome changes after SG and LRYGB procedures, assessed via large cohorts and shotgun metagenomic indicated a profound modification of bacterial gut composition 6 months after bariatric surgery in parallel with weight loss. Similar taxonomic and functional changes were observed after both intervention (Proteobacteria, oral colonizers, nitrate, and TMAO oxidation and vitamin B12 use increase) but less important after SG. The main limitations of our study are the lack of measure of metabolites as short-chain fatty acids to validate what we observed at KO level. Long-terms observations from surgery, possibly 3 to 5 years, are necessary to highlight the clinical relevance of these findings. We infer from these data that LRYGB had greater impact on microbiome composition than SG. This could be considered when advising the patient on the type of bariatric surgery or postoperative diet.

      Disclosures

      The authors have no commercial associations that might be a conflict of interest in relation to this article.

      Acknowledgments

      The authors thank Professor Ralph Peterli to have performed the operations and recruiting for the Swiss cohort and Dr. Anne Christin Meyer-Gerspach who was very helpful to collect all stool samples. They thank Rodolphe Anty who recruited patients from CHU Nice and also Craig Wood from Geisinger Health Center in the United States. They also thank Karine Roger and Rachel Morra who have monitored the clinical study and regrouped the clinical data. They finally thank Pierre Rimbaud for his thoughtful comments and suggestions to improve the manuscript.

      Supplementary materials

      Figure thumbnail figs1
      Supplementary Figure 1Phylum-level composition of patients (median of relative abundance) before surgery and after LRYGB and SG. The phyla with abundances superior to 0.1% were represented.
      Figure thumbnail figs2
      Supplementary Figure 2Relative abundances of 51 MSPs that were significantly impacted by LRYGB. MSPs were grouped by phylum and ordered according their fold change within the phylum.
      Figure thumbnail figs3
      Supplementary Figure 3Relative abundances of 49 MSPs that were significantly impacted by SG. MSPs were grouped by phylum and ordered according their fold change within the phylum.
      Figure thumbnail figs4
      Supplementary Figure 4Relative abundances of 13 modules that were significantly impacted by LRYGB. Modules were grouped by functional category and ordered according their fold change values.
      Figure thumbnail figs5
      Supplementary Figure 5Relative abundances of 6 modules that were significantly impacted by SG. Modules were grouped by functional category and ordered according their fold change values.

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