The chemical basis of metabolic interdependence in microbial communities

Abstract

Microbial communities play a crucial role in determining the dynamics of soil and marine ecosystems. They strongly influence the physiological functioning of plants and animals, for instance, nutrient uptake, stress tolerance, immune responses in the gut, lung, skin, etc. The diverse species in such communities interact both competitively as well as cooperatively. Cross-feeding, the exchange of metabolites between a pair of microbial species for mutual benefit is a common interaction that probably explains why 99% of natural bacterial species are unculturable on their own in the laboratory. Here, we provide a theoretical, network-level understanding of the conditions under which cross-feeding between a pair of microbial species can be beneficial to both. Using the known microbial repertoire of metabolic reactions, as represented in the KEGG database, we construct a large ensemble of metabolic networks designed to synthesize a set of biomass precursors from specified nutrients. We construct both autonomous networks, that can perform this task on their own, as well as pairs of cross-feeding networks that can only perform this task together but not alone. Surprisingly, we find that there exist cross-feeding pairs that produce higher biomass or energy yields than even the best autonomous networks. We show that such "outperforming" cross-feeding pairs exist only because of certain nonlinearities in the way metabolic flux is distributed in these networks. By analyzing patterns in our ensemble of networks, we propose a set of necessary and (almost) sufficient conditions that the metabolic networks have to satisfy for cross-feeding to be beneficial. These conditions are based partly on the structure of the networks and partly on the chemical and thermodynamic properties of the underlying chemical reactions, phenomenologically quantified in terms of the effect of donating or accepting metabolites on the yield of our constructed networks. Our analysis not only provides a mechanistic understanding of why cross-feeding is prevalent in microbial communities, but also provides a theoretical basis for understanding the benefit of compartmentalization of chemical reactions in a variety of contexts, for instance with mitochondrial vs. cytoplasmic metabolism in eukaryotic cells, or multi-enzyme cascade reactions in industrial contexts.