Metabolic dependencies drive species co-occurrence in diverse microbial communities

Abstract

Microbial communities populate most environments on earth and play a critical role in ecology and human health. Their composition is thought to be largely shaped by interspecies competition for the available resources, but cooperative interactions, such as metabolite exchanges, have also been implicated in community assembly. The prevalence of metabolic interactions in microbial communities, however, has remained largely unknown. Here, we systematically survey, by using a genome-scale metabolic modeling approach, the extent of resource competition and metabolic exchanges in over 800 communities. We find that, despite marked resource competition at the level of whole assemblies, microbial communities harbor metabolically interdependent groups that recur across diverse habitats. By enumerating flux-balanced metabolic exchanges in these co-occurring subcommunities we also predict the likely exchanged metabolites, such as amino acids and sugars, that can promote group survival under nutritionally challenging conditions. Our results highlight metabolic dependencies as a major driver of species co-occurrence and hint at cooperative groups as recurring modules of microbial community architecture.

Keywords: community metabolism; cooperation; metabolic modeling; naturalization theory; syntrophy.

Fig. 1.

Higher-order species co-occurrence in microbial communities. (A) We consider community composition at two different levels. Sample communities are composed of all species identified by 16S ribosomal RNA in sampling sites. Co-occurring subcommunities are species groups found together more often than expected by chance (Methods), and are thus likely to be functionally dependent. (B) Inter- and intraphyla interactions in co-occurring subcommunities including 381 pairs, 3,322 triplets, and 3,518 quadruplets. (C) Species overlap and distribution of phyla among the co-occurring subcommunities of different size.

Fig. 2.

Degree of resource competition in microbial communities. (A) The concept of MRO—an intrinsic community property providing an upper limit on the degree of resource competition. The algorithm used for the MRO calculation is described in Methods. (B) Biological relevance of the MRO metric. Communities consisting of phylogenetically closely related member species show high resource overlap as expected. Red line indicates the best fit as determined by least squares linear regression analysis. (C) Resource competition is predominant in microbial communities seen as a whole. MRO values for the sample communities of different sizes and random controls are shown. P values were computed using the Wilcoxon rank sum test.

Fig. 3.

MIP of microbial communities. (A) Illustration of the concept of MIP. A community can use the biosynthetic capabilities of its members to decrease the collective dependence on nutritional availability from the environment. (B) MIP as a function of community size. For each community size, results of simulations based on 1,000 randomly assembled communities are shown. (C) Sample communities display lower than expected interaction potential in line with their high degree of resource competition.

Fig. 4.

Co-occurring subcommunities feature high metabolic interaction potential. (A) MIPs of triplet and quadruplet subcommunities (red density plots) against the background of random assemblies (gray density plots, 10,000 groups). Shown MIP values are normalized by the number of member species. (B) Co-occurring subcommunities (red density plots) show stronger metabolic coupling than non-co-occurring groups (gray density plots, 10,000 groups). (C) Distinction of co-occurring subcommunities in various cooperation (MIP and SMETANA score) and competition (resource overlap and phylogenetic distance) metrics. Error bars mark the 5th and 95th percentile of ratios between these metrics for co-occurring subcommunities and the corresponding values for 1,000 random assemblies. (D) Metabolite classes likely to be exchanged in co-occurring subcommunities as predicted by SMETANA. Numbers mark the scale of log-fold enrichment over non-co-occurring groups. P < 10⁻⁷ (amino acids), < 10⁻⁵ (carbohydrates), < 10⁻² (nucleosides), and 0.039 (organic acids). (E) Removal of mutualistic metabolite exchanges from simulated co-occurring communities diminishes the contrast to random assemblies. Error bars mark the 5th and 95th percentile of ratios between the number of edges in co-occurring communities and 1,000 random assemblies of the same size.