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bioRxiv · 10.1101/2023.01.10.523517

Unveiling abundance-dependent metabolic phenotypes of microbial communities

Jimenez, N. E.·Acuna, V.·Cortes, M. P.·Eveillard, D.·Maass, A. E.
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Abstract

Constraint-based modeling has risen as an alternative for characterizing the metabolism of communities. Adaptations of Flux Balance Analysis have been proposed to model metabolic interactions in most cases, considering a unique optimal flux distribution derived from the maximization of biomass production. However, these approaches do not consider the development of other potentially novel essential functions not directly related to cell growth which forces them to display suboptimal growth rates in nature. Additionally, suboptimal states allow a degree of plasticity in the metabolism, thus allowing quick shifts between alternative flux distributions as an initial response to environmental changes. In this work, we present a method to explore the abundance-growth space as a representation of metabolic flux distributions of a community. This space is defined by the composition of a community, represented by its members relative abundance and their growth rate. The analysis of this space allows us to represent the whole set of feasible fluxes without needing a complete description of the solution space unveiling abundance-dependent metabolic phenotypes displayed in a given environment. As an illustration, we consider a community composed of two bioleaching bacteria, Acidithiobacillus ferrooxidans Wenelen and Sulfobacillus thermosulfidooxidans Cutipay, finding that changes in the composition of their available resources significantly affects their metabolic plasticity. IMPORTANCEIn nature, organisms live in communities and not as isolated species. Their interactions provide a source of resilience to environmental disturbances. Despite their importance in ecology, human health, and industry, understanding how organisms interact in different environments remains an open question. In this work, we provide a novel approach which, only using genomics information, studies the metabolic phenotype exhibited by communities, where the exploration of suboptimal growth flux distributions and the composition of a community allows to unveil its capacity to respond to environmental changes, shedding the light of the degree of metabolic plasticity inherent to the community.

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Jimenez, N. E., Acuna, V., Cortes, M. P., Eveillard, D., Maass, A. E.. 2023-01-15. Unveiling abundance-dependent metabolic phenotypes of microbial communities. https://doi.org/10.1101/2023.01.10.523517

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