Unveiling abundance-dependent metabolic phenotypes of microbial communities

Author:

Jiménez Natalia E.12ORCID,Acuña Vicente12,Cortés María Paz1,Eveillard Damien3,Maass Alejandro Eduardo124ORCID

Affiliation:

1. Center for Mathematical Modeling, University of Chile , Santiago, Chile

2. Center for Genome Regulation, Millennium Institute, University of Chile , Santiago, Chile

3. Nantes Université, Ecole Centrale Nantes, CNRS , Nantes, France

4. Department of Mathematical Engineering, University of Chile , Santiago, Chile

Abstract

ABSTRACT Constraint-based modeling has risen as an alternative for characterizing metabolism of communities. Adaptations of flux balance analysis have been proposed to model metabolic interactions, which in most cases consider the maximization of biomass production as their objective. In nature, novel essential functions are not directly related to cell growth force communities to display suboptimal growth rates. These suboptimal states allow a degree of plasticity in their metabolism, thus allowing quick shifts between alternative flux distributions as an initial response to environmental changes. In this work, we introduce the abundance-growth space as a representation of metabolic phenotypes of a community. This space is defined by the composition of a community, represented by its members’ relative abundances, and their growth rate. The analysis of this space allows us to pinpoint how critical reactions respond to shifts of the environment, showing where changes in community plasticity occur. Interestingly, it highlights the relevance of the relative abundance of its members in the lost or gain of plasticity. This method is applied to two simple communities that exchange metabolites. A synthetic community of two mutant Escherichia coli strains and an environmental bioleaching community composed by Acidithiobacillus ferrooxidans Wenelen and Sulfobacillus thermosulfidooxidans Cutipay, where only Cutipay consumes organic matter disposed of by the community. IMPORTANCE In nature, organisms live in communities and not as isolated species, and 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 that, only using genomic 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 light of the degrees of metabolic plasticity inherent to the community.

Funder

Agencia Nacional de Investigación y Desarrollo

Ministerio de Economía, Fomento y Turismo, Chile

Publisher

American Society for Microbiology

Subject

Computer Science Applications,Genetics,Molecular Biology,Modeling and Simulation,Ecology, Evolution, Behavior and Systematics,Biochemistry,Physiology,Microbiology

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