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Multiple nutrient transporters enable cells to mitigate a rate-affinity tradeoff.
Montaño-Gutierrez, Luis Fernando; Correia, Kevin; Swain, Peter S.
Afiliación
  • Montaño-Gutierrez LF; School of Biological Sciences, University of Edinburgh, Edinburgh, United Kingdom.
  • Correia K; School of Biological Sciences, University of Edinburgh, Edinburgh, United Kingdom.
  • Swain PS; School of Biological Sciences, University of Edinburgh, Edinburgh, United Kingdom.
PLoS Comput Biol ; 18(4): e1010060, 2022 04.
Article en En | MEDLINE | ID: mdl-35468136
ABSTRACT
Eukaryotic genomes often encode multiple transporters for the same nutrient. For example, budding yeast has 17 hexose transporters (HXTs), all of which potentially transport glucose. Using mathematical modelling, we show that transporters that use either facilitated diffusion or symport can have a rate-affinity tradeoff, where an increase in the maximal rate of transport decreases the transporter's apparent affinity. These changes affect the import flux non-monotonically, and for a given concentration of extracellular nutrient there is one transporter, characterised by its affinity, that has a higher import flux than any other. Through encoding multiple transporters, cells can therefore mitigate the tradeoff by expressing those transporters with higher affinities in lower concentrations of nutrients. We verify our predictions using fluorescent tagging of seven HXT genes in budding yeast and follow their expression over time in batch culture. Using the known affinities of the corresponding transporters, we show that their regulation in glucose is broadly consistent with a rate-affinity tradeoff as glucose falls, the levels of the different transporters peak in an order that mostly follows their affinity for glucose. More generally, evolution is constrained by tradeoffs. Our findings indicate that one such tradeoff often occurs in the cellular transport of nutrients.
Asunto(s)

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Proteínas de Saccharomyces cerevisiae Tipo de estudio: Prognostic_studies Idioma: En Revista: PLoS Comput Biol Asunto de la revista: BIOLOGIA / INFORMATICA MEDICA Año: 2022 Tipo del documento: Article País de afiliación: Reino Unido

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Proteínas de Saccharomyces cerevisiae Tipo de estudio: Prognostic_studies Idioma: En Revista: PLoS Comput Biol Asunto de la revista: BIOLOGIA / INFORMATICA MEDICA Año: 2022 Tipo del documento: Article País de afiliación: Reino Unido