Dynamic proteome allocation regulates the profile of interaction of auxotrophic bacterial consortia
Por:
Reyes-González D., De Luna-Valenciano H., Utrilla J., Sieber M., Pena-Miller R., Fuentes-Hernandez A.
Publicada:
1 ene 2022
Categoría:
Multidisciplinary
Resumen:
Microbial ecosystems are composed of multiple species in constant metabolic exchange. A pervasive interaction in microbial communities is metabolic cross-feeding and occurs when the metabolic burden of producing costly metabolites is distributed between community members, in some cases for the benefit of all interacting partners. In particular, amino acid auxotrophies generate obligate metabolic inter-dependencies in mixed populations and have been shown to produce a dynamic profile of interaction that depends upon nutrient availability. However, identifying the key components that determine the pair-wise interaction profile remains a challenging problem, partly because metabolic exchange has consequences on multiple levels, from allocating proteomic resources at a cellular level to modulating the structure, function and stability of microbial communities. To evaluate how ppGpp-mediated resource allocation drives the population-level profile of interaction, here we postulate a multi-scale mathematical model that incorporates dynamics of proteome partition into a population dynamics model. We compare our computational results with experimental data obtained from co-cultures of auxotrophic Escherichia coli K12 strains under a range of amino acid concentrations and population structures. We conclude by arguing that the stringent response promotes cooperation by inhibiting the growth of fast-growing strains and promoting the synthesis of metabolites essential for other community members. © 2022 Royal Society Publishing. All rights reserved.
Filiaciones:
Reyes-González D.:
Synthetic Biology Program, Center for Genomic Sciences, Universidad Autonoma de Mexico, Cuernavaca, 62220, Mexico
De Luna-Valenciano H.:
Synthetic Biology Program, Center for Genomic Sciences, Universidad Autonoma de Mexico, Cuernavaca, 62220, Mexico
Systems Biology Program, Center for Genomic Sciences, Universidad Nacional Autonoma de Mexico, Cuernavaca, 62210, Mexico
Utrilla J.:
Synthetic Biology Program, Center for Genomic Sciences, Universidad Autonoma de Mexico, Cuernavaca, 62220, Mexico
Sieber M.:
Max Planck Institute for Evolutionary Biology, Plon, 24306, Germany
Pena-Miller R.:
Systems Biology Program, Center for Genomic Sciences, Universidad Nacional Autonoma de Mexico, Cuernavaca, 62210, Mexico
Fuentes-Hernandez A.:
Synthetic Biology Program, Center for Genomic Sciences, Universidad Autonoma de Mexico, Cuernavaca, 62220, Mexico
Green Published, gold, Gold, Green
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