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Polarization of microbial communities between competitive and cooperative metabolism

Matters Arising to this article was published on 05 December 2022

Abstract

Resource competition and metabolic cross-feeding are among the main drivers of microbial community assembly. Yet the degree to which these two conflicting forces are reflected in the composition of natural communities has not been systematically investigated. Here, we use genome-scale metabolic modelling to assess the potential for resource competition and metabolic cooperation in large co-occurring groups (up to 40 members) across thousands of habitats. Our analysis reveals two distinct community types, which are clustered at opposite ends of a spectrum in a trade-off between competition and cooperation. At one end are highly cooperative communities, characterized by smaller genomes and multiple auxotrophies. At the other end are highly competitive communities, which feature larger genomes and overlapping nutritional requirements, and harbour more genes related to antimicrobial activity. The latter are mainly present in soils, whereas the former are found in both free-living and host-associated habitats. Community-scale flux simulations show that, whereas competitive communities can better resist species invasion but not nutrient shift, cooperative communities are susceptible to species invasion but resilient to nutrient change. We also show, by analysing an additional data set, that colonization by probiotic species is positively associated with the presence of cooperative species in the recipient microbiome. Together, our results highlight the bifurcation between competitive and cooperative metabolism in the assembly of natural communities and its implications for community modulation.

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Fig. 1: Co-occurring microbial communities are polarized in the competition–cooperation landscape.
Fig. 2: Members of the cooperative and competitive communities show distinct genomic and phylogenetic characteristics, and have different abundance profiles.
Fig. 3: Cooperative communities occupy more diverse habitats.
Fig. 4: Members of both competitive and cooperative communities are observed across the four main phyla.
Fig. 5: Cooperative and competitive communities show contrasting sensitivity to abiotic and biotic perturbations.

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Data availability

All of the data required to generate the results and figures presented in this article are publicly available in the following repository: https://github.com/cdanielmachado/cooccurrence.

Code availability

All of the code required to generate the results and figures presented in this article are publicly available in the following repository: https://github.com/cdanielmachado/cooccurrence.

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Acknowledgements

We acknowledge N. Zmora and E. Elinav for providing data and feedback on the probiotics study, K. Blin for assistance with the antiSMASH database, and S. Schmidt for fruitful discussions. This project has received funding from the Horizon 2020 research and innovation programme of the European Union under grant agreement no. 686070. This work was supported by the UK Medical Research Council (project no. MC_UU_00025/11).

Author information

Authors and Affiliations

Authors

Contributions

D.M. developed the co-occurrence computation method and performed the simulations and data analysis. D.M. and S.A. implemented the software for metabolic modelling. O.M.M. performed the phylogenetic analysis. Y.K. mapped the OTUs to reference genomes. P.B. supervised the phylogenetic analysis. Kaustubh R. Patil and Kiran R. Patil conceived the study. D.M. and Kiran R. Patil wrote the manuscript. All authors read and revised the final manuscript.

Corresponding author

Correspondence to Kiran R. Patil.

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The authors declare no competing interests.

Additional information

Peer review information Nature Ecology & Evolution thanks Joshua Goldford and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.

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

Extended data

Extended Data Fig. 1 Mapping of OTUs to reference genomes.

a, comparison of sample diversity in terms of OTUs (blue) and genomes (orange); b, comparison of species prevalence in terms of OTUs and genomes across samples; c, species abundance distribution; d, total abundance of each sample that is captured by the mapped genomes in comparison to the ratio of genomes to OTUs.

Extended Data Fig. 2 Summary of higher-order co-occurrence analysis.

a, Average number of samples where all species in a co-occurring community can be found together as a function of community size (computed for the threshold values used in this work); b, Principal component analysis of co-occurring communities computed using different abundance thresholds. Marker size indicates co-occurring community size (up to 30 species) and marker shapes indicates independent runs of the algorithm (3 runs for each threshold). Numbers on x and y axis indicate percentage of explained variance for the respective principle component.

Extended Data Fig. 3 Simulation results using an independent data set.

Simulation results for competition (MRO score) and cooperation potential (MIP score) for microbial communities obtained from Chaffron et al.1. Blue dots represent co-occurring communities of different sizes (up to 1000 per size) and grey dots represent randomly-assembled communities of similar size (1000 communities per size).

Extended Data Fig. 4 Summary of metabolite requirements for growth and cross-fed metabolites.

a, compounds competed for in cooperative communities; b, compounds competed for in competitive communities; c, cross-fed compounds in cooperative communities; d, cross-fed compounds in competitive communities. Compound classification according to the Human Metabolome Database (HMDB). Only the ten most frequent compound classes are colored and labeled.

Extended Data Fig. 5 Abundance of co-occurring species as a function of the total number of co-occurring partners present in a sample.

The colored line denotes the average abundance for each type of community, the shadowed area indicates standard deviation, and the dashed grey line indicates the average species abundance across all species and samples (in all cases the average is calculated as the mean value in log-space, that is representing the geometric mean of the relative abundance values).

Extended Data Fig. 6 Abundance stability in co-occurring communities.

Community stability measured in terms of: a, individual stability (lower coefficient of variation per species indicates higher stability); b, group stability (lower cosine distance indicates higher covariation of species abundance within each community).

Extended Data Fig. 7 Auxotrophy frequency is associated with amino acid production cost.

Spearman correlation between amino acid production costs and their auxotrophy frequency across species participating in cooperative communities. The data on amino acid production costs was obtained from Barton et al (ref. 45).

Extended Data Fig. 8 Acquisition of amino acid auxotrophies.

Analysis of evidence for recent acquisition of amino acid auxotrophies using two complementary approaches: taxonomy based (T), measuring the fraction of auxotrophic species at genus level; phylogeny based (P), estimating the probability of the auxotrophy existing in the most recent ancestor of the species. Green color in both columns is indicative of a consensus.

Extended Data Fig. 9 Sensitivity of co-occurring communities to different types of perturbations.

This is an extended version of Fig. 5 where the simulations are performed in aerobic and anaerobic environments separately. For abiotic perturbations we further test the effect of removal of compounds from the growth medium.

Extended Data Fig. 10 Association between the presence cooperative species and colonization of the human gut microbiome.

Presence of cooperative species in the lower gastrointestinal (LGI) tract of patients permissive to probiotic colonization (P), patients resistant to colonization (R) and control patients (C). Asterisks indicate significance of Wilcoxon signed-rank test (p < 0.05).

Supplementary information

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Supplementary Table 1

Table with all the models used in this work, including the following information: assembly accession code, strain ID, species, genus, family, order, class, phylum, genome length, number of open reading frames, number of annotated metabolic genes, number of enzymatic reactions, number of transport reactions, number of gap-filling reactions, number of internal metabolites, number of external metabolites, and frequency in cooperative and competitive communities.

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Machado, D., Maistrenko, O.M., Andrejev, S. et al. Polarization of microbial communities between competitive and cooperative metabolism. Nat Ecol Evol 5, 195–203 (2021). https://doi.org/10.1038/s41559-020-01353-4

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