Optimality and evolutionary tuning of the expression level of a protein

Department of Molecular Cell Biology and Department of Physics of Complex Systems, The Weizmann Institute of Science, Rehovot 76100, Israel.
Nature (Impact Factor: 41.46). 08/2005; 436(7050):588-92. DOI: 10.1038/nature03842
Source: PubMed

ABSTRACT Different proteins have different expression levels. It is unclear to what extent these expression levels are optimized to their environment. Evolutionary theories suggest that protein expression levels maximize fitness, but the fitness as a function of protein level has seldom been directly measured. To address this, we studied the lac system of Escherichia coli, which allows the cell to use the sugar lactose for growth. We experimentally measured the growth burden due to production and maintenance of the Lac proteins (cost), as well as the growth advantage (benefit) conferred by the Lac proteins when lactose is present. The fitness function, given by the difference between the benefit and the cost, predicts that for each lactose environment there exists an optimal Lac expression level that maximizes growth rate. We then performed serial dilution evolution experiments at different lactose concentrations. In a few hundred generations, cells evolved to reach the predicted optimal expression levels. Thus, protein expression from the lac operon seems to be a solution of a cost-benefit optimization problem, and can be rapidly tuned by evolution to function optimally in new environments.

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Available from: Uri Alon, Sep 28, 2015
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    • "Similarly, a cost-benefit relationship has been observed in Escherichia coli, where growth in antibiotics was optimized when the multiple antibiotic resistance promoter was moderately induced [14]. Even in the absence of drugs, microorganisms have been observed to evolve optimal expression levels that maximize growth (e.g., E. coli growing in different lactose environments [15]). Natural selection may act to tune gene expression noise. "
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    ABSTRACT: Gene expression is a stochastic process that affects cellular and population fitness. Noise in gene expression can enhance fitness by increasing cell to cell variability as well as the time cells spend in favorable expression states. Using a stochastic model of gene expression together with a fitness function that incorporates the costs and benefits of gene expression in a stressful environment, we show that the fitness landscape is shaped by gene expression noise in more complex ways than previously anticipated. We find that mutations modulating the properties of expression noise enable cell populations to optimize their position on the fitness landscape. Additionally, we find that low levels of expression noise evolve under conditions where the fitness benefits of expression exceed the fitness costs, and that high levels of expression noise evolve when the expression costs exceed the fitness benefits. The results presented in this study expand our understanding of the interplay between stochastic gene expression and fitness in selective environments.
    Physical Review E 08/2015; 92(2):022713. DOI:10.1103/PhysRevE.92.022713 · 2.29 Impact Factor
    • "Growth rate () and growth yield (A) were both impaired, as would be expected if rate limiting bacterial biosynthetic resources are diverted for virulence factor expression until a critical nutrient(s) is exhausted from the medium. Protein cost is a major driving force in the shaping of regulatory systems (Dekel and Alon, 2005; Babu and Aravind, 2006; Kalisky et al., 2007; Stoebel et al., 2008; Gao and Stock, 2013). The rapid elimination of the prfA* genotype in the competition experiments in "
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    • "Generalists can access a broader range of resources but must synthesize and maintain a larger amount of biochemical machinery. For generalists or specialists, the costs of resource acquisition must be offset by the resource flux from soil substrates (Koch, 1985; Dekel and Alon, 2005). For microbes decomposing polymeric soil compounds, these costs include extracellular enzyme synthesis. "
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