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1.
Mol Syst Biol ; 14(3): e7823, 2018 03 05.
Artigo em Inglês | MEDLINE | ID: mdl-29507053

RESUMO

Living systems control cell growth dynamically by processing information from their environment. Although responses to a single environmental change have been intensively studied, little is known about how cells react to fluctuating conditions. Here, we address this question at the genomic scale by measuring the relative proliferation rate (fitness) of 3,568 yeast gene deletion mutants in out-of-equilibrium conditions: periodic oscillations between two environmental conditions. In periodic salt stress, fitness and its genetic variance largely depended on the oscillating period. Surprisingly, dozens of mutants displayed pronounced hyperproliferation under short stress periods, revealing unexpected controllers of growth under fast dynamics. We validated the implication of the high-affinity cAMP phosphodiesterase and of a regulator of protein translocation to mitochondria in this group. Periodic oscillations of extracellular methionine, a factor unrelated to salinity, also altered fitness but to a lesser extent and for different genes. The results illustrate how natural selection acts on mutations in a dynamic environment, highlighting unsuspected genetic vulnerabilities to periodic stress in molecular processes that are conserved across all eukaryotes.


Assuntos
Metionina/metabolismo , Mutação , Proteínas de Saccharomyces cerevisiae/genética , Saccharomyces cerevisiae/genética , Proliferação de Células , Deleção de Genes , Perfilação da Expressão Gênica , Regulação Fúngica da Expressão Gênica , Aptidão Genética , Modelos Genéticos , Saccharomyces cerevisiae/metabolismo , Salinidade , Seleção Genética , Estresse Fisiológico
2.
Mol Syst Biol ; 14(1): e7803, 2018 01 15.
Artigo em Inglês | MEDLINE | ID: mdl-29335276

RESUMO

More and more natural DNA variants are being linked to physiological traits. Yet, understanding what differences they make on molecular regulations remains challenging. Important properties of gene regulatory networks can be captured by computational models. If model parameters can be "personalized" according to the genotype, their variation may then reveal how DNA variants operate in the network. Here, we combined experiments and computations to visualize natural alleles of the yeast GAL3 gene in a space of model parameters describing the galactose response network. Alleles altering the activation of Gal3p by galactose were discriminated from those affecting its activity (production/degradation or efficiency of the activated protein). The approach allowed us to correctly predict that a non-synonymous SNP would change the binding affinity of Gal3p with the Gal80p transcriptional repressor. Our results illustrate how personalizing gene regulatory models can be used for the mechanistic interpretation of genetic variants.


Assuntos
Polimorfismo de Nucleotídeo Único , Proteínas de Saccharomyces cerevisiae/química , Proteínas de Saccharomyces cerevisiae/genética , Saccharomyces cerevisiae/genética , Fatores de Transcrição/química , Fatores de Transcrição/genética , Alelos , Sítios de Ligação , Galactose/farmacologia , Regulação Fúngica da Expressão Gênica , Modelos Genéticos , Modelos Moleculares , Ligação Proteica , Proteínas Repressoras/metabolismo , Saccharomyces cerevisiae/metabolismo , Proteínas de Saccharomyces cerevisiae/metabolismo , Fatores de Transcrição/metabolismo , Ativação Transcricional
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