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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

The Pharmacogenomics Journal volume 13, pages 514–522 (2013)Cite this article

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Abstract

Roux-en-Y gastric bypass (RYGB) has become a prominent therapeutic option for long-term treatment of morbid obesity and type 2 diabetes mellitus (T2D). Cross talk and pathogenetic consequences of RYGB-induced profound effects on metabolism and gut microbiome are poorly understood. The aim of the present study therefore was to characterize intra-individual changes of gut microbial composition before and 3 months after RYGB by metagenomic sequencing in morbidly obese patients (body mass index (BMI)>40 kg m−2) with T2D. Subsequently, metagenomic data were correlated with clinical indices. Based on gene relative abundance profile, 1061 species, 729 genera, 44 phyla and 5127 KO (KEGG Orthology) were identified. Despite high diversity, bacteria could mostly be assigned to seven bacterial divisions. The overall metagenomic RYGB-induced shift was characterized by a reduction of Firmicutes and Bacteroidetes and an increase of Proteobacteria. Twenty-two microbial species and 11 genera were significantly altered by RYGB. Using principal component analysis, highly correlated species were assembled into two common components. Component 1 consisted of species that were mainly associated with BMI and C-reactive protein. This component was characterized by increased numbers of Proteobacterium Enterobacter cancerogenus and decreased Firmicutes Faecalibacterium prausnitzii and Coprococcus comes. Functional analysis of carbohydrate metabolism by KO revealed significant effects in 13 KOs assigned to phosphotransferase system. Spearmen’s Rank correlation indicated an association of 10 species with plasma total- or low-density lipoprotein cholesterol, and 5 species with triglycerides. F. prausnitzii was directly correlated to fasting blood glucose. This is the first clinical demonstration of a profound and specific intra-individual modification of gut microbial composition by full metagenomic sequencing. A clear correlation exists of microbiome composition and gene function with an improvement in metabolic and inflammatory parameters. This will allow to develop new diagnostic and therapeutic strategies based on metagenomic sequencing of the human gut microbiome.

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Acknowledgements

We thank Sigrid Nitzsche for the excellent technical support, Dr Dongqian Shen and Dr Liang Xiao who helped us for the functional analysis and gave us some useful advises. This work was supported by grants of the Deutsche Forschungsgemeinschaft to SRB, ME-B, VL-Z, TC (KFO 252/1), of the German Federal Ministry for Education and Research (BMBF) to the German Centre for Diabetes Research (DZD e.V.) to SRB and of the Federal Ministry for Education and Research Germany to SRB and JL (01DR12065).

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  1. J Graessler, Y Qin, H Zhong, J Zhang and S R Bornstein: These authors equally contributed to this work.

Authors and Affiliations

  1. Department of Internal Medicine III, Carl Gustav Carus Medical School, Technical University Dresden, Dresden, Germany

    J Graessler, T Chavakis, A B Bornstein, M Ehrhart-Bornstein, V Lamounier-Zepter & S R Bornstein

  2. Research and Cooperation Division, BGI-Shenzhen, Shenzhen, China

    Y Qin, H Zhong & J Zhang

  3. Department of Translational Medicine, John Curtin School of Medical Research, Australian National University, Canberra, ACT, Australia

    J Licinio & M-L Wong

  4. Department of Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China

    A Xu

  5. Department of Internal Medicine, Dresden Interdisciplinary Adiposity Center, Community Hospital Dresden-Neustadt, Dresden, Germany

    T Lohmann & T Wolf

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  1. J Graessler
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Correspondence to S R Bornstein.

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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. Pharmacogenomics J 13, 514–522 (2013). https://doi.org/10.1038/tpj.2012.43

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