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Resource–diversity relationships in bacterial communities reflect the network structure of microbial metabolism

Nature Ecology & Evolution volume 5, pages 1424–1434 (2021)Cite this article

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An Author Correction to this article was published on 15 September 2021

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Abstract

The relationship between the number of available nutrients and community diversity is a central question in ecological research that remains unanswered. Here we studied the assembly of hundreds of soil-derived microbial communities on a wide range of well-defined resource environments, from single carbon sources to combinations of up to 16. We found that, while single resources supported multispecies communities varying from 8 to 40 taxa, mean community richness increased only one-by-one with additional resources. Cross-feeding could reconcile these seemingly contrasting observations, with the metabolic network seeded by the supplied resources explaining the changes in richness due to both the identity and the number of resources, as well as the distribution of taxa across different communities. By using a consumer–resource model incorporating the inferred cross-feeding network, we provide further theoretical support to our observations and a framework to link the type and number of environmental resources to microbial community diversity.

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Fig. 1: Microbial community diversity increases slowly with the number of resources despite individual resources supporting rich communities.
Fig. 2: Experimental communities are composed of generalists and variable numbers of specialists, with the latter driving the increase in community diversity.
Fig. 3: A resource-explicit model incorporating a realistic metabolic network recapitulates our experimental results.

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Data availability

Data on 16S amplicon sequencing and metadata files have been deposited in the NCBI SRA database under NCBI BioProject ID PRJNA715195.

Code availability

Data files and analysis/simulation codes to reproduce all figures are available at https://github.com/mdalbello/Resource-diversity-relationship.

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Acknowledgements

We thank J. Grilli, M. Costantino-Lagomarsino, M. Corigliano and M. Barbier for feedback on models, the members of the Gore Lab for comments on the manuscript, and B. Stellato for help with the ensemble tree regression model. This work was supported by the Simons Collaboration: Principles of Microbial Ecosystems (PriME) award number 542395 and NIH (R01-GM102311). A.G. was supported by the Gordon and Betty Moore Foundation as a Physics of Living Systems Fellow through grant number GBMF4513.

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  1. Physics of Living Systems Group, Department of Physics, Massachusetts Institute of Technology, Cambridge, MA, USA

    Martina Dal Bello, Hyunseok Lee, Akshit Goyal & Jeff Gore

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  1. Martina Dal Bello
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Contributions

M.D.B. and J.G. conceived the study. M.D.B. performed the experiments and the sequencing analysis. H.L. performed theoretical modelling. A.G. performed metabolic and genomic analyses. All authors analysed the data and wrote the manuscript.

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Correspondence to Martina Dal Bello or Jeff Gore.

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Extended data

Extended Data Fig. 1 The majority of communities reached equilibrium before the end of the experiment.

Each panel shows the temporal trajectories of the composition of one community at the family level. The most prevalent 37 families are included. The first 16 plots depict communities grown on a single carbon source. The last four plots depict replicated communities grown on a media containing all the 16 carbon sources. The solid black line indicates the observed community richness.

Extended Data Fig. 2 Single carbon sources support microbial assemblages spanning a wide phylogenetic diversity.

The pool of ASVs found across all media supplied with single resources is phylogenetically diverse, encompassing 7 classes, indicated by colored lines on the right side of the plot (black lines indicate ASVs that could not be identified at any taxonomical level except the Domain, Bacteria). Families are indicated on the left side of the phylogenetic tree. Colored tiles indicate the media in which the ASV is found (for each carbon source, there are three replicated microcosms for a total of 48 communities.) Carbon sources are ordered based on the average richness they support.

Extended Data Fig. 3 All single resources supported multispecies communities, but richness varied with the identity of the resource.

Bars indicate, for each carbon source, the number of ASVs (mean ± s.e.m., N = 3).

Extended Data Fig. 4 Richness of two-resource communities is approximately the average richness of constituent single-resource communities.

a. Observed richness of each two-resource community is best approximated by the average richness of constituent single resources, compared to the maximum and the union. Both the average error for the three predictions, calculated from the absolute values of predicted minus observed richness, and the ratio between predicted and observed richness are shown. b. Average richness of two-resource communities does not differ from the average richness of single-resource communities (boxplots with median and 95 % confidence interval; number of 1-resource media = 16, number of 2-resource media = 24; each dot is obtained from the mean of 3 replicates, s.e.m. are not shown for clarity). The color of the dots indicates the supporting resource(s).

Extended Data Fig. 5 The estimated number of metabolites for combinations of carbon sources increases fast and tends to saturate with the number of supplied resources.

The number of metabolites has been computed from KEGG and MetaCyc databases (see Methods). Large colored dots indicate the average number of metabolites for each number of supplied resources (mean ± s.e.m.) while small grey dots indicate the average richness in each media containing a combination of resources (16 for single-resource, 24 for two-resource, 12 for four-resource, six for eight-resource, 16 for 15-resource and one for 16-resource combinations). Error bars are omitted for clarity. The dotted line was obtained by fitting a spline to the points.

Extended Data Fig. 6 The observed linear trend is sufficiently robust to the exclusion of low-abundance ASVs, coarse-graining at the family level, and the index used to measure microbial community diversity.

a. Richness was calculated as the number of ASVs after the exclusion of those with relative abundance lower than 0.1%. b. Richness was calculated as the number of unique families in the media. c, d. The increase in diversity, measured as Shannon Entropy and Inverse Simpson Index, with the number of carbon sources can still be approximated by a line. These indices give progressively more weight to abundant species, accounting, in this way, for the evenness of the communities. In each panel, large colored dots indicate the mean ± s.e.m. while small grey dots indicate the average richness in each media containing a combination of resources (16 for single-resource, 24 for two-resource, 12 for four-resource, six for eight-resource, 16 for 15-resource and one for 16-resource combinations). Error bars are omitted for clarity.

Extended Data Fig. 7 The evenness of the microbial communities increases with the number of supplied carbon sources.

a. Log-linear rank abundance distributions (RADs) are shown for all the experimental microbial microcosms (48 for single-resource, 72 for two-resource, 36 for four-resource, 18 for eight-resource, 16 for 15-resource and nine for 16-resource combinations) together with the fitted regression lines (black dashed lines). Going from one to 16 resources, RADs exhibit heavier tails. b. The average absolute value of the slope (bars indicate mean ± s.e.m. across replicates with the same number of supplied resources, while jittered dots represent the slope for each individual replicate) decreases with the number of supplied resources. c. Changes in evenness are independent from changes in richness, as revealed by RADs normalized for richness (mean RADs, dashed colored lines, ± SD, shaded colored ribbon, for each number of supplied resources).

Extended Data Fig. 8 Resource occupancy of the 275 ASVs found in media containing a single carbon source.

The histogram shows the number of single resources in which each ASV is found. Bars are colored depending on whether the ASV has been classified as a generalist (pink), a specialist (teal) or an intermediate (beige). The families to which ASVs belong are reported.

Extended Data Fig. 9 The fraction of habitat generalist decreases while the fraction of habitat specialists increases with community richness.

A. Percentage fraction of habitat generalists (mean, N = 3) as a function of community richness (mean ± s.e.m., N = 3). B. Percentage fraction of habitat specialists (mean, N = 3) as a function of community richness (mean ± s.e.m., N = 3). Fitted linear regression lines (black, dashed) are shown.

Extended Data Fig. 10 Richness from simulations grows modestly with the number of resources.

Richness obtained from simulations of the consumer-resource model with cross-feeding (blue triangles, mean ± s.e.m., N = 16 for single-resource, 24 for two-resource, 12 for four-resource, six for eight-resource, 16 for 15-resource and 1 for 16-resource combinations) as a linear function of the number of available resources (solid blue line, intercept = 22.7, slope = 2). Grey jittered triangles indicate the richness of communities grown on a particular resource combination.

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Dal Bello, M., Lee, H., Goyal, A. et al. Resource–diversity relationships in bacterial communities reflect the network structure of microbial metabolism. Nat Ecol Evol 5, 1424–1434 (2021). https://doi.org/10.1038/s41559-021-01535-8

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