Influence of gastrectomy for gastric cancer treatment on faecal microbiome and metabolome profiles

Abstract

Objective: Recent evidence points to the gut microbiome's involvement in postoperative outcomes, including after gastrectomy. Here, we investigated the influence of gastrectomy for gastric cancer on the gut microbiome and metabolome, and how it related to postgastrectomy conditions.

Design: We performed shotgun metagenomics sequencing and capillary electrophoresis time-of-flight mass spectrometry-based metabolomics analyses on faecal samples collected from participants with a history of gastrectomy for gastric cancer (n=50) and compared them with control participants (n=56).

Results: The gut microbiota in the gastrectomy group showed higher species diversity and richness (p<0.05), together with greater abundance of aerobes, facultative anaerobes and oral microbes. Moreover, bile acids such as genotoxic deoxycholic acid and branched-chain amino acids were differentially abundant between the two groups (linear discriminant analysis (LDA) effect size (LEfSe): p<0.05, q<0.1, LDA>2.0), as were also Kyoto Encyclopedia of Genes and Genomes modules involved in nutrient transport and organic compounds biosynthesis (LEfSe: p<0.05, q<0.1, LDA>2.0).

Conclusion: Our results reveal alterations of gut microbiota after gastrectomy, suggesting its association with postoperative comorbidities. The multi-omic approach applied in this study could complement the follow-up of patients after gastrectomy.

Keywords: gastrectomy; gastric cancer; gutmicrobiome; metabolome; metagenome.

Conflict of interest statement

Competing interests: SF and TY are founders of Metabologenomics. The company is focused on the design and control of the gut environment for human health. The company had no control over the interpretation, writing or publication of this work. The terms of these arrangements are being managed by Keio University and Tokyo Institute of Technology in accordance with its conflict of interest policies.

© Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.

Figures

Figure 1

Community structure of the faecal microbiome and metabolome in postgastrectomy and control participants. Principal coordinates analysis (PCoA) with Bray-Curtis distance was performed to assess the community structure of species’ relative abundance obtained by mOTU (A) and MetaPhlAn2 (B) in the gastrectomy group (n=50) (orange) and in the control group (n=56) (blue). The PCoA trend was confirmed by significantly lower microbial structure dissimilarity (Bray-Curtis) within groups (p=5.53×10−7) (C). PCoA was performed also on faecal metabolite concentrations in the gastrectomy group (n=44) (orange) and the control group (n=54) (blue) (D).

Figure 2

Microbiome diversity in gastrectomy and control groups. Species richness was measured using the Chao1 index calculated from the species annotated by mOTU (A) and MetaPhlAn2 (B). Species alpha-diversity was measured using the Shannon-Wiener index based on mOTU (C) and MetaPhlAn2 (D) annotation. Species alpha-diversity was measured for each major phylum using mOTU (E) and MetaPhlAn2 (F) annotation.

Figure 3

Differential enrichment of microbes in gastrectomy and control groups. Cladogram of species annotated by mOTU (A) and MetaPhlAn2 (B). Each dot represents a taxonomic hierarchy. Dots are marked for significant (LEfSe: p3.0 are highlighted and labelled accordingly. The summed relative abundances of oral microbes were compared between the gastrectomy (n=50) and control (n=56) groups based on the species annotated by mOTU (C) and MetaPhlAn2 (D). The summed relative abundances of aerobes (E) and facultative anaerobes (F) were compared between the two groups.

Figure 4

Different trends of functional modules and metabolites from the faecal microbiomes of gastrectomy and control groups. Relative abundance and linear discriminant analysis (LDA) score (log10) of Kyoto Encyclopedia of Genes and Genomes (KEGG) modules annotated by the Human Microbiome Project Unified Metabolic Analysis Network 2 (HUMAnN2) and overlapping with those annotated by our in-house pipeline (linear discriminant analysis effect size (LEfSe): p<0.05, q<0.1, LDA>2.0) (A). Richness (Chao1) and alpha-diversity (Shannon-Wiener) of contributor species were estimated. Three modules (marked by an asterisk (*) in A) contributed by significantly more diverse and richer microbes (two-sided Mann-Whitney U test (MWU): p<0.001) in the gastrectomy group, in spite of their enrichment in the control group (B). The modules were M00196, M00535 and M00122 (two-sided MWU: p=5.31×10−4, 3.17×10−5, 7.14×10−6, for richness, respectively, and p=1.12×10−4, 2.22×10−4, 6.10×10−4, for alpha-diversity, respectively). KEGG modules’ relative abundance is represented by the top value of each stack of bars. Samples were subsequently sorted according to the dominant contributor to a module and then grouped as either gastrectomy or control (sample order differs between panels). Different trends in metabolites were also observed between the two groups (LEfSe: p<0.05, q<0.1, LDA>3.0) (C). Bile acid reaction consisted of deconjugation of conjugated bile acids (glycocholate and taurocholate) into their primary form (cholate) and amino acids (glycine and taurine) followed by 7-α/β-dehydroxylation to form secondary bile acids (deoxycholic acid (DCA)). The colours highlight enrichment in the control (blue) and gastrectomy (orange) groups (D).

Figure 5

Genus-genus and genus-metabolite correlations. Co-occurrence (red) and co-excluding (green) relationships between genera (SparCC: −0.22.0) and metabolites (LEfSe: p3.0) from gastrectomy (n=44) and control (n=54) participants (C). The matrices were derived from Euclidean distance-based bi-clustering of Spearman’s RANK correlation matrices. Correlation coefficients in each square represent positive (red) and negative (blue) relationships. Colours are proportional to the absolute value of Spearman’s RANK correlations (see legend in the figure). Statistically significant correlations (p

Figure 6

Data integration-derived schematic hypothesis. Schematic hypothesis of gut microbiome and metabolite alterations after gastrectomy. The scheme is divided into three parts denoting physiological changes (grey), findings from our study (blue) and the possible consequences (red). Solid lines show the links confirmed by previous studies. Dashed lines show possible connections that can be inferred from our findings. The higher or lower levels observed in postgastrectomy patients are shown in comparison with those of control participants. BCAA, branched-chain amino acids.