Flux balance analysis of microbial communities from metabolic strategies: composition, cross-feeding and ecological service

Microorganisms interact through the exchange of metabolites and competition for shared substrates, and this metabolic coupling shapes the composition and function of microbial communities. Community flux balance analysis (cFBA) can predict such behaviour - the maximum community growth rate, the metabolic fluxes and the relative abundances of the species - from stoichiometric models of their metabolism, but existing formulations are either complex and hard to scale as communities grow or cannot predict optimal growth rates. Here we present a physiology-based formulation of cFBA in which each species' metabolism is reduced to a few macrochemical equations, one for each 'metabolic mode' the species can use, and the whole community is then solved as a single linear program. From this, the method predicts the optimal composition of the community, its maximum growth rate, the metabolites exchanged between the species, and the net conversion the community carries out as a whole; its ecological service. This reduction makes it far simpler to build and solve models of larger communities. We illustrate the approach on a two-species synergistic community that can be verified by hand, apply it to a five-member anaerobic digestion community, and use it to predict the metabolic interactions of a genome-scale syngas-fermenting coculture. Characterising these communities at their optimal steady states, we show that each species is driven to a distinct metabolic strategy. We discuss the method both as a practical tool for larger microbial communities and as a means of uncovering the ecological principles that govern them.