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PLoS One ; 7(1): e29932, 2012.
Article in English | MEDLINE | ID: mdl-22238678

ABSTRACT

During the last decades experimental studies have revealed that single cells of a growing bacterial population are significantly exposed to molecular noise. Important sources for noise are low levels of metabolites and enzymes that cause significant statistical variations in the outcome of biochemical reactions. In this way molecular noise affects biological processes such as nutrient uptake, chemotactic tumbling behavior, or gene expression of genetically identical cells. These processes give rise to significant cell-to-cell variations of many directly observable quantities such as protein levels, cell sizes or individual doubling times. In this study we theoretically explore if there are evolutionary benefits of noise for a growing population of bacteria. We analyze different situations where noise is either suppressed or where it affects single cell behavior. We consider two specific examples that have been experimentally observed in wild-type Escherichia coli cells: (i) the precision of division site placement (at which molecular noise is highly suppressed) and (ii) the occurrence of noise-induced phenotypic variations in fluctuating environments. Surprisingly, our analysis reveals that in these specific situations both regulatory schemes [i.e. suppression of noise in example (i) and allowance of noise in example (ii)] do not lead to an increased growth rate of the population. Assuming that the observed regulatory schemes are indeed caused by the presence of noise our findings indicate that the evolutionary benefits of noise are more subtle than a simple growth advantage for a bacterial population in nutrient rich conditions.


Subject(s)
Bacteria/growth & development , Cell Growth Processes/genetics , Cell Physiological Phenomena , Environment , Evolution, Molecular , Genetic Variation/physiology , Artifacts , Bacteria/cytology , Bacteria/genetics , Cell Physiological Phenomena/genetics , Cells/metabolism , Computer Simulation , Models, Biological , Models, Theoretical , Noise , Phenotype
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