Letter

Quantitative microbiome profiling links gut community variation to microbial load

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Accepted:
Published online:

Abstract

Current sequencing-based analyses of faecal microbiota quantify microbial taxa and metabolic pathways as fractions of the sample sequence library generated by each analysis1,2. Although these relative approaches permit detection of disease-associated microbiome variation, they are limited in their ability to reveal the interplay between microbiota and host health3,4. Comparative analyses of relative microbiome data cannot provide information about the extent or directionality of changes in taxa abundance or metabolic potential5. If microbial load varies substantially between samples, relative profiling will hamper attempts to link microbiome features to quantitative data such as physiological parameters or metabolite concentrations5,6. Saliently, relative approaches ignore the possibility that altered overall microbiota abundance itself could be a key identifier of a disease-associated ecosystem configuration7. To enable genuine characterization of host–microbiota interactions, microbiome research must exchange ratios for counts4,8,9. Here we build a workflow for the quantitative microbiome profiling of faecal material, through parallelization of amplicon sequencing and flow cytometric enumeration of microbial cells. We observe up to tenfold differences in the microbial loads of healthy individuals and relate this variation to enterotype differentiation. We show how microbial abundances underpin both microbiota variation between individuals and covariation with host phenotype. Quantitative profiling bypasses compositionality effects in the reconstruction of gut microbiota interaction networks and reveals that the taxonomic trade-off between Bacteroides and Prevotella is an artefact of relative microbiome analyses. Finally, we identify microbial load as a key driver of observed microbiota alterations in a cohort of patients with Crohn’s disease10, here associated with a low-cell-count Bacteroides enterotype (as defined through relative profiling)11,12.

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Accessions

Primary accessions

European Nucleotide Archive

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Acknowledgements

We thank all study participants, F. Giraldo for enabling sample collection at the PXL Hasselt, L. Rymenans and C. Verspecht for faecal DNA extraction and library preparation, K. Verbeke for facilitating moisture content determinations, and P. Goncalves for advice on simulating microbial data for benchmarking the QMP and RMP approach. The main funding for this study comes from a KU Leuven CREA grant. D.V. is supported by the Agency for Innovation by Science and Technology (IWT). G.K., K.D., M.V.-C., S.V.-S., and J.W. are funded by the Research Foundation Flanders (FWO-Vlaanderen). This work is further supported through funding by VIB, the Rega Institute for Medical Research, KU Leuven, FP7 METACARDIS (HEALTH-F4-2012-305312), and H2020 SYSCID (grant agreement 733100).

Author information

Author notes

    • Doris Vandeputte
    • , Gunter Kathagen
    • , Kevin D’hoe
    •  & Sara Vieira-Silva

    These authors contributed equally to this work.

    • Gwen Falony
    •  & Jeroen Raes

    These authors jointly supervised this work.

Affiliations

  1. KU Leuven – University of Leuven, Department of Microbiology and Immunology, Rega Institute, Herestraat 49, B-3000 Leuven, Belgium

    • Doris Vandeputte
    • , Gunter Kathagen
    • , Kevin D’hoe
    • , Sara Vieira-Silva
    • , Mireia Valles-Colomer
    • , Jun Wang
    • , Raul Y. Tito
    • , Lindsey De Commer
    • , Youssef Darzi
    • , Gwen Falony
    •  & Jeroen Raes
  2. VIB, Center for Microbiology, Kasteelpark Arenberg 31, B-3000 Leuven, Belgium

    • Doris Vandeputte
    • , Gunter Kathagen
    • , Kevin D’hoe
    • , Sara Vieira-Silva
    • , Mireia Valles-Colomer
    • , Jun Wang
    • , Raul Y. Tito
    • , Youssef Darzi
    • , Gwen Falony
    •  & Jeroen Raes
  3. Research Group of Microbiology, Department of Bioengineering Sciences, Vrije Universiteit Brussel, Pleinlaan 2, B-1050 Brussels, Belgium

    • Doris Vandeputte
    • , Kevin D’hoe
    •  & Raul Y. Tito
  4. Translational Research Center for Gastrointestinal Disorders (TARGID), KU Leuven, B-3000 Leuven, Belgium

    • João Sabino
    •  & Séverine Vermeire

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Contributions

This study was conceived by G.F. Experiments were designed by D.V., S.V., G.F., and J.R. Sampling of cohorts was set up and carried out by D.V., G.K., K.D., S.V.-S., M.V.-C., J.S., J.W., R.Y.T., L.D.C., and G.F. Optimization of sequencing protocols was performed by R.Y.T.; data pre-processing by D.V., M.V.-C., J.S., J.W., and Y.D.; flow cytometry analyses by G.K. and K.D.; statistical analyses by D.V., G.K., K.D., S.V.-S., M.V.-C., J.S., J.W., and G.F.; network analyses by S.V.-S.; and simulation experiments by D.V. and S.V.-S. G.F. developed the QMP protocol. S.V.-S., G.F., and J.R. drafted the manuscript. All authors revised the article and approved the final version for publication.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to Jeroen Raes.

Reviewer Information Nature thanks W. M. de Vos and the other anonymous reviewer(s) for their contribution to the peer review of this work.

Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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