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Competition for fluctuating resources reproduces statistics of species abundance over time across wide-ranging microbiotas.
Ho, Po-Yi; Good, Benjamin H; Huang, Kerwyn Casey.
Afiliación
  • Ho PY; Department of Bioengineering, Stanford University, Stanford, United States.
  • Good BH; Department of Applied Physics, Stanford University, Stanford, United States.
  • Huang KC; Chan Zuckerberg Biohub, San Francisco, United States.
Elife ; 112022 04 11.
Article en En | MEDLINE | ID: mdl-35404785
ABSTRACT
Across diverse microbiotas, species abundances vary in time with distinctive statistical behaviors that appear to generalize across hosts, but the origins and implications of these patterns remain unclear. Here, we show that many of these macroecological patterns can be quantitatively recapitulated by a simple class of consumer-resource models, in which the metabolic capabilities of different species are randomly drawn from a common statistical distribution. Our model parametrizes the consumer-resource properties of a community using only a small number of global parameters, including the total number of resources, typical resource fluctuations over time, and the average overlap in resource-consumption profiles across species. We show that variation in these macroscopic parameters strongly affects the time series statistics generated by the model, and we identify specific sets of global parameters that can recapitulate macroecological patterns across wide-ranging microbiotas, including the human gut, saliva, and vagina, as well as mouse gut and rice, without needing to specify microscopic details of resource consumption. These findings suggest that resource competition may be a dominant driver of community dynamics. Our work unifies numerous time series patterns under a simple model, and provides an accessible framework to infer macroscopic parameters of effective resource competition from longitudinal studies of microbial communities.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Microbiota / Modelos Biológicos Tipo de estudio: Observational_studies / Prognostic_studies Límite: Animals Idioma: En Revista: Elife Año: 2022 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Microbiota / Modelos Biológicos Tipo de estudio: Observational_studies / Prognostic_studies Límite: Animals Idioma: En Revista: Elife Año: 2022 Tipo del documento: Article País de afiliación: Estados Unidos
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