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A library of human gut bacterial isolates paired with longitudinal multiomics data enables mechanistic microbiome research

September 2019
Nature Medicine 25(9):1-11

DOI:10.1038/s41591-019-0559-3

Authors:

Mathilde Poyet

Kiel University

Mathieu Groussin

Massachusetts Institute of Technology

Sean Gibbons

Institute for Systems Biology

Julian Avila

Broad Institute of MIT and Harvard

Show all 24 authorsHide

Our understanding of how the gut microbiome interacts with its human host has been restrained by limited access to longitudinal datasets to examine stability and dynamics, and by having only a few isolates to test mechanistic hypotheses. Here, we present the Broad Institute-OpenBiome Microbiome Library (BIO-ML), a comprehensive collection of 7,758 gut bacterial isolates paired with 3,632 genome sequences and longitudinal multi-omics data. We show that microbial species maintain stable population sizes within and across humans and that commonly used ‘omics’ survey methods are more reliable when using averages over multiple days of sampling. Variation of gut metabolites within people over time is associated with amino acid levels, and differences across people are associated with differences in bile acids. Finally, we show that genomic diversification can be used to infer eco-evolutionary dynamics and in vivo selection pressures for strains within individuals. The BIO-ML is a unique resource designed to enable hypothesis-driven microbiome research.

Description of the BIO-ML a, 16S phylogenetic tree of the 7,758 isolates in the BIO-ML. Lineages are colored by phylum. b, Depiction of the distribution of 1,347 isolates across 24 bacterial species (y axis) over time (x axis) that were whole-genome sequenced. c, Depiction of the distribution of 1,168 samples across individuals (y axis) and over time (x axis) that were processed for 16S amplicon sequencing. d, Depiction of the distribution of 563 samples across individuals and over time that were processed for shotgun metagenomic sequencing. e, Depiction of the distribution of 179 samples across individuals and over time that were processed for metabolomic study.

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Taxonomic coverage and composition of the BIO-ML of isolates and genomes a, Abundance-weighted taxonomic coverage of the library of bacterial isolates (7,758 isolates) (y axis), compared to the diversity observed through culture-independent 16S amplicon sequencing (x axis). Eleven donors were used to build the library of isolates. The phylogenetic diversity of isolates was measured with 16S sanger sequencing, and this was compared to the total diversity observed in the 16S sequence data obtained from 1,168 samples from 90 individual donors of the BIO-ML. Taxonomic coverage was evaluated using different 16S OTU clustering thresholds, from 90% to 100% (ASV) similarity. b, Phylogenomic tree of the 3,632 genomes of the BIO-ML. Branches are colored by phylum.

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The library of genomes contain multiple species within the Faecalibacterium and Akkermansia genera Phylogenetic trees of Faecalibacterium (a) and Akkermansia (b) genomes were reconstructed using the concatenate alignment of ribosomal proteins (see Methods). We used RAxML to reconstruct the tree, using the PROTGAMMALGF substitution model. Pairwise Mash distances are represented on the right of each tree. Within each major clade, pairwise Mash distances were lower than 0.05, the threshold used to define species taxonomic units. Between clades, pairwise distances were higher than 0.05. Genomes in the F. prausnitzii and A. muciniphila clades have Mash distances with corresponding NCBI reference genomes that were lower than 0.05. Two different Akkermansia species are present in our genome library. At least two different Faecalibacterium species are present in the genome library.

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Stability and conservation of microbiome species over time within and across people a, Non-metric multidimensional scaling (NMDS) plot showing 16S community structure (Bray–Curtis distances) across long-term time series from ten stool donors. Samples are colored by donors (right). Donors maintain unique microbial signatures over many months to years (ANOSIM, P < 0.0001). b, The black points show the median abundance comparisons, and the red points show the results for a single, randomly drawn sample. Species abundances are conserved across donor pairs. The spread in the red points is larger than for the black points, indicating the median abundances show a tighter correlation across donors (black points Pearson’s R² = 0.25; red points Pearson’s R² = 0.19).

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Stability and conservation of microbiome functions over time within and across people a, NMDS plot showing functional structure (Bray–Curtis distances) across long-term time series from four stool donors. Donors maintain unique functional signatures over many months-to-years. b, COG abundances are conserved across donor pairs. The black points show the median abundance comparisons, and the red points show the results for a single, randomly drawn sample. The spread in the red points is larger than that for the black points, indicating the median abundances show a tighter correlation across donors (black points Pearson’s R² = 0.88; red points Pearson’s R² = 0.77).

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https://doi.org/10.1038/s41591-019-0559-3

1Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA. 2Center for Microbiome Informatics and

Therapeutics, Massachusetts Institute of Technology, Cambridge, MA, USA. 3The Broad Institute of MIT and Harvard, Cambridge, MA, USA. 4Institute for

Systems Biology, Seattle, WA, USA. 5Finch Therapeutics, Somerville, MA, USA. 6OpenBiome, Somerville, MA, USA. 7Gastrointestinal Unit and Center for

Computational and Integrative Biology, Massachusetts General Hospital, Boston, MA, USA. 8These authors contributed equally: M. Poyet, M. Groussin,

S. M. Gibbons. *e-mail: xavier@molbio.mgh.harvard.edu; ejalm@mit.edu

Engineering the gut microbiome to treat disease is an exciting

new direction in medical science1–3. Fecal microbiota trans-

plant (FMT) from a healthy donor into patients with recurrent

Clostridium difficile infections is the first widely adopted microbi-

ome-related therapy and has a ~90% success rate4,5. Investigational

trials are underway in new disease areas, such as inflammatory

bowel disease, liver disease, Parkinson’s disease, severe acute malnu-

trition and infection by antibiotic-resistant pathogens6–9 (see ongo-

ing clinical trials at https://clinicaltrials.gov/). OpenBiome is a stool

bank that has provided material for over 48,000 fecal transplants.

Stool banks like OpenBiome represent an attractive opportunity

for building a well-characterized culture collection because living

biomass is preserved, allowing cultivation of isolated strains, and

because dense longitudinal sampling (that is, several samples being

collected per week) enables analysis of within-host dynamics. In

addition, a resource of isolate genomes together with longitudinal

dynamics can be useful in designing and analyzing future clinical

trials. Finally, a comprehensive culture collection from successful

donors could ultimately be used to replace FMT, which is a blunt

tool for engineering the gut microbiome and may have long-term

consequences due to the introduction of a wide variety of exoge-

nous strains with unknown function10–12.

While comprehensive strain collections are essential for mecha-

nistic studies, culturing a diverse representation of gut bacteria has

been challenging. Seminal work by several groups13–17 has addressed

many of the technological challenges of growing wide arrays of

gut bacterial lineages, and two recent studies reported isolate and

genome collections with broad phylogenetic representation18,19.

However, existing isolate and genome collections are still limited,

especially in strain-level diversity, for most of the bacterial species in

the human gut. In addition, current collections are limited in exam-

ples of coexisting strain-level diversity from the same human host

because the majority of strains were cultured from a large number of

individuals or were targeted for maximizing phylogenetic diversity.

Recent work has shown that this within-host strain diver-

sity is extensive in the human population20 and within individual

people21–23. New studies increasingly point to functional differ-

ences between strains of the same species that can impact human

health21,24,25. For instance, strain-level differences can influence the

metabolism of dietary compounds, such as galacto-oligosaccha-

rides26 or nondigestible fibers27,28. Bacteria-mediated metabolism of

drugs can also differ across strains, influencing drug efficacy and

toxicity29,30. In addition, genomic variation in virulence genes can

alter pathogenicity among strains31–33. Finally, distinct strains can

elicit different immune responses, such as cytokine production25.

For these reasons, a large collection of isolates of multiple strains

from many gut bacterial species, sampled both within and across

people, is needed to better understand host–microbe interactions

and to efficiently screen for candidate features that could ultimately

be leveraged in rationally designed microbiome-based therapeutics.

Here, we introduce a comprehensive biobank of human gut bac-

teria: a library of 7,758 bacterial isolates obtained from healthy FMT

donors recruited in the Boston area. This library covers most of the

phylogenetic diversity found in the human gut, contains extensive

A library of human gut bacterial isolates paired

with longitudinal multiomics data enables

mechanistic microbiome research

M. Poyet1,2,3,8, M. Groussin1,2,3,8, S. M. Gibbons 1,2,3,4,8, J. Avila-Pacheco3, X. Jiang1,2,3, S. M. Kearney1,2,3,

A. R. Perrotta1,2, B. Berdy 1,2,3, S. Zhao1,2, T. D. Lieberman1,2,3, P. K. Swanson1,5, M. Smith5,6,

S. Roesemann 3, J. E. Alexander3, S. A. Rich3, J. Livny3, H. Vlamakis3, C. Clish 3, K. Bullock3, A. Deik3,

J. Scott3, K. A. Pierce3, R. J. Xavier2,3,7* and E. J. Alm 1,2,3,5,6*

Our understanding of how the gut microbiome interacts with its human host has been restrained by limited access to longitu-

dinal datasets to examine stability and dynamics, and by having only a few isolates to test mechanistic hypotheses. Here, we

present the Broad Institute-OpenBiome Microbiome Library (BIO-ML), a comprehensive collection of 7,758 gut bacterial iso-

lates paired with 3,632 genome sequences and longitudinal multi-omics data. We show that microbial species maintain stable

population sizes within and across humans and that commonly used ‘omics’ survey methods are more reliable when using aver-

ages over multiple days of sampling. Variation of gut metabolites within people over time is associated with amino acid levels,

and differences across people are associated with differences in bile acids. Finally, we show that genomic diversification can be

used to infer eco-evolutionary dynamics and invivo selection pressures for strains within individuals. The BIO-ML is a unique

resource designed to enable hypothesis-driven microbiome research.

NATURE MEDICINE | VOL 25 | SEPTEMBER 2019 | 1442–1452 | www.nature.com/naturemedicine

1442

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Temporal dynamics and metagenomics of phosphorothioate epigenomes in the human gut microbiome

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Evolutionary dynamics of bacteria in the gut microbiome within and across hosts

Preprint

Sep 2018

Gut microbiota are shaped by a combination of ecological and evolutionary forces. While the ecological dynamics have been extensively studied, much less is known about how species of gut bacteria evolve over time. Here we introduce a model-based framework for quantifying evolutionary dynamics within and across hosts using a panel of metagenomic samples. We use this approach to study evolution in ∼30 prevalent species in the human gut. Although the patterns of between-host diversity are consistent with quasi-sexual evolution and purifying selection on long timescales, we identify new genealogical signatures that challenge standard population genetic models of these processes. Within hosts, we find that genetic differences that accumulate over ∼6 month timescales are only rarely attributable to replacement by distantly related strains. Instead, the resident strains more commonly acquire a smaller number of putative evolutionary changes, in which nucleotide variants or gene gains or losses rapidly sweep to high frequency. By comparing these mutations with the typical between-host differences, we find evidence that some sweeps are seeded by recombination, in addition to new mutations. However, comparisons of adult twins suggest that replacement eventually overwhelms evolution over multi-decade timescales, hinting at fundamental limits to the extent of local adaptation. Together, our results suggest that gut bacteria can evolve on human-relevant timescales, and they highlight the connections between these short-term evolutionary dynamics and longer-term evolution across hosts.