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Dynamic resource allocation drives growth under nitrogen starvation in eukaryotes.
Tibocha-Bonilla, Juan D; Kumar, Manish; Richelle, Anne; Godoy-Silva, Rubén D; Zengler, Karsten; Zuñiga, Cristal.
Afiliación
  • Tibocha-Bonilla JD; Bioinformatics and Systems Biology Graduate Program, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA, 92093-0760, USA.
  • Kumar M; Department of Pediatrics, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA, 92093-0760, USA.
  • Richelle A; Grupo de Investigación en Procesos Químicos y Bioquímicos, Departamento de Ingeniería Química y Ambiental, Universidad Nacional de Colombia, Bogotá, DC, Colombia.
  • Godoy-Silva RD; Department of Pediatrics, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA, 92093-0760, USA.
  • Zengler K; Department of Pediatrics, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA, 92093-0760, USA.
  • Zuñiga C; Grupo de Investigación en Procesos Químicos y Bioquímicos, Departamento de Ingeniería Química y Ambiental, Universidad Nacional de Colombia, Bogotá, DC, Colombia.
NPJ Syst Biol Appl ; 6(1): 14, 2020 05 15.
Article en En | MEDLINE | ID: mdl-32415097
Cells can sense changes in their extracellular environment and subsequently adapt their biomass composition. Nutrient abundance defines the capability of the cell to produce biomass components. Under nutrient-limited conditions, resource allocation dramatically shifts to carbon-rich molecules. Here, we used dynamic biomass composition data to predict changes in growth and reaction flux distributions using the available genome-scale metabolic models of five eukaryotic organisms (three heterotrophs and two phototrophs). We identified temporal profiles of metabolic fluxes that indicate long-term trends in pathway and organelle function in response to nitrogen depletion. Surprisingly, our calculations of model sensitivity and biosynthetic cost showed that free energy of biomass metabolites is the main driver of biosynthetic cost and not molecular weight, thus explaining the high costs of arginine and histidine. We demonstrated how metabolic models can accurately predict the complexity of interwoven mechanisms in response to stress over the course of growth.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Eucariontes / Nitrógeno Límite: Animals Idioma: En Revista: NPJ Syst Biol Appl Año: 2020 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Reino Unido

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Eucariontes / Nitrógeno Límite: Animals Idioma: En Revista: NPJ Syst Biol Appl Año: 2020 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Reino Unido