Population-based metagenomics analysis reveals markers for gut microbiome composition and diversity
“Normal” for the gut microbiota
For the benefit of future clinical studies, it is critical to establish what constitutes a “normal” gut microbiome, if it exists at all. Through fecal samples and questionnaires, Falony et al. and Zhernakova et al. targeted general populations in Belgium and the Netherlands, respectively. Gut microbiota composition correlated with a range of factors including diet, use of medication, red blood cell counts, fecal chromogranin A, and stool consistency. The data give some hints for possible biomarkers of normal gut communities.
Abstract
Deep sequencing of the gut microbiomes of 1135 participants from a Dutch population-based cohort shows relations between the microbiome and 126 exogenous and intrinsic host factors, including 31 intrinsic factors, 12 diseases, 19 drug groups, 4 smoking categories, and 60 dietary factors. These factors collectively explain 18.7% of the variation seen in the interindividual distance of microbial composition. We could associate 110 factors to 125 species and observed that fecal chromogranin A (CgA), a protein secreted by enteroendocrine cells, was exclusively associated with 61 microbial species whose abundance collectively accounted for 53% of microbial composition. Low CgA concentrations were seen in individuals with a more diverse microbiome. These results are an important step toward a better understanding of environment-diet-microbe-host interactions.
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Supplementary Material
Summary
Materials and Methods
Figs. S1 to S13
Tables S1 to S19
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References and Notes
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Volume 352 | Issue 6285
29 April 2016
29 April 2016
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Copyright © 2016, American Association for the Advancement of Science.
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Received: 1 September 2015
Accepted: 11 March 2016
Published in print: 29 April 2016
Acknowledgments
We thank the LifeLines-DEEP participants and the Groningen LifeLines staff for their collaboration. We thank J. Dekens, M. Platteel, and A. Maatman for management and technical support. We thank J. Senior and K. McIntyre for editing the manuscript. This project was funded by grants from the Top Institute Food and Nutrition, Wageningen, to C.W. (TiFN GH001); the Netherlands Organization for Scientific Research to J.F. (NWO-VIDI 864.13.013), L.F. (ZonMW-VIDI 917.14.374), and R.K.W. (ZonMW-VIDI 016.136.308); and CardioVasculair Onderzoek Nederland to M.H.H. and A.Z. (CVON 2012-03). A.Z. holds a Rosalind Franklin Fellowship (University of Groningen), and M.C.C. holds a postdoctoral fellowship from the Fundación Alfonso Martín Escudero. This research received funding from the European Research Council (ERC) under the European Union’s Seventh Framework Program: C.W. is supported by FP7/2007-2013)/ERC advanced Grant Agreement no. 2012-322698. M.G.N. is supported by an ERC Consolidator Grant (no. 310372). L.F. is supported by FP7/2007–2013, grant agreement 259867, and by an ERC Starting Grant, grant agreement 637640 (ImmRisk). J.R. and G.F. are supported by FP7 METACARDIS HEALTH-F4-2012-305312, VIB, FWO, IWT (Agency for Innovation by Science and Technology), the Rega institute for Medical Research, and KU Leuven. S.V.-S. and M.J. are supported by postdoctoral fellowships from FWO. T.V., M.S., and R.J.X. are supported by NIH, JDRF, and CCFA. A.Z., C.W., and J.F. designed the study. A.Z., E.F.T., L.F., and C.W. initiated the cohort and collected cohort data. A.Z., E.F.T., Z.M., S.A.J., M.C.C., and D.G. generated data. A.Z., A.K., M.J.B., E.F.T., M.S., T.V., A.V.V., G.F., S.V.-S, J.W., F.I., P.D., M.A.S., C.H., R.J.X., and J.F. analyzed data. G.F, S.V.-S., J.W., E.B., M.J., R.K.W., E.J.M.F., M.G.N., D.G., D.J., L.F., Y.S.A., C.H., J.R., R.J.X., and M.H.H. participated in integral discussions. A.Z., A.K., M.J.B., R.J.X., C.W., and J.F. wrote the manuscript. The authors have no conflicts of interest to report. The raw sequence data for both MGS and 16S rRNA gene sequencing data sets, and age and gender information per sample are available from the European genome-phenome archive (https://www.ebi.ac.uk/ega/) at accession number EGAS00001001704. Other phenotypic data can be requested from the LifeLines cohort study (https://lifelines.nl/lifelines-research/access-to-lifelines) following the standard protocol for data access. All data access to the Lifelines population cohort must follow the informed consent regulations of the Medical Ethics Review Board of the University Medical Center Groningen, which are clearly described at https://lifelines.nl/upload/file/lifelines+data+access+policy_%5B1%5D.pdf. The study was approved by the institutional review board of UMCG, ref.M12.113965. D.J. has additional funding from EU FP7/ no. 305564 and EU FP7/ no. 305479. C.H. is on the Scientific Advisory Board for Seres Therapeutics. Y.S.A. is a director and co-owner of PolyOmica, which provides services in statistical (gen)omics.
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