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Concentration fluctuations in growing and dividing cells: Insights into the emergence of concentration homeostasis.
Jia, Chen; Singh, Abhyudai; Grima, Ramon.
Afiliação
  • Jia C; Applied and Computational Mathematics Division, Beijing Computational Science Research Center, Beijing, China.
  • Singh A; Department of Electrical and Computer Engineering, University of Delaware, Newark, Delaware, United States of America.
  • Grima R; School of Biological Sciences, University of Edinburgh, Edinburgh, United Kingdom.
PLoS Comput Biol ; 18(10): e1010574, 2022 10.
Article em En | MEDLINE | ID: mdl-36194626
ABSTRACT
Intracellular reaction rates depend on concentrations and hence their levels are often regulated. However classical models of stochastic gene expression lack a cell size description and cannot be used to predict noise in concentrations. Here, we construct a model of gene product dynamics that includes a description of cell growth, cell division, size-dependent gene expression, gene dosage compensation, and size control mechanisms that can vary with the cell cycle phase. We obtain expressions for the approximate distributions and power spectra of concentration fluctuations which lead to insight into the emergence of concentration homeostasis. We find that (i) the conditions necessary to suppress cell division-induced concentration oscillations are difficult to achieve; (ii) mRNA concentration and number distributions can have different number of modes; (iii) two-layer size control strategies such as sizer-timer or adder-timer are ideal because they maintain constant mean concentrations whilst minimising concentration noise; (iv) accurate concentration homeostasis requires a fine tuning of dosage compensation, replication timing, and size-dependent gene expression; (v) deviations from perfect concentration homeostasis show up as deviations of the concentration distribution from a gamma distribution. Some of these predictions are confirmed using data for E. coli, fission yeast, and budding yeast.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Schizosaccharomyces / Escherichia coli Tipo de estudo: Prognostic_studies Idioma: En Revista: PLoS Comput Biol Assunto da revista: BIOLOGIA / INFORMATICA MEDICA Ano de publicação: 2022 Tipo de documento: Article País de afiliação: China

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Schizosaccharomyces / Escherichia coli Tipo de estudo: Prognostic_studies Idioma: En Revista: PLoS Comput Biol Assunto da revista: BIOLOGIA / INFORMATICA MEDICA Ano de publicação: 2022 Tipo de documento: Article País de afiliação: China