Dekel E, Alon U.. Optimality and evolutionary tuning of the expression level of a protein. Nature 436: 588-592

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


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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    • "Expression is a metabolically costly process requiring energy for transcription, translation, and mobilization of the translational machinery (Dekel and Alon 2005; Gout et al. 2010). The expression level of a protein is predicted to be a tradeoff between the beneficial effects of its function and the energetic costs of its expression (Cherry 2010; Gout et al. 2010), and selection should drive the expression level of all proteins close to values that maximize fitness (Dekel and Alon 2005; Nabholz et al. 2013). Although most proteins will be expressed near their optimal levels, abundantly expressed proteins should be highly optimized owing to the increased energetic cost of production (Gout et al. 2010; Vishnoi et al. 2010). "
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    ABSTRACT: Protein expression level is one of the strongest predictors of protein sequence evolutionary rate, with high-expression protein sequences evolving at slower rates than low-expression protein sequences, largely because of constraints on protein folding and function. Expression evolutionary rates have also been shown to be negatively correlated with expression level across human and mouse orthologs over relatively long divergence times (i.e., approximately 100 million years). Long-term evolutionary patterns, however, often cannot be extrapolated to microevolutionary processes (and vice versa), and whether this relationship holds for traits evolving under directional selection within a single species over ecological timescales (i.e., <5,000 years) is unknown and not necessarily expected. Expression is a metabolically costly process, and the expression level of a particular protein is predicted to be a trade-off between the benefit of its function and the costs of its expression. Selection should drive the expression level of all proteins close to values that maximize fitness, particularly for high-expression proteins because of the increased energetic cost of production. Therefore, stabilizing selection may reduce the amount of standing expression variation for high-expression proteins and, in combination with physiological constraints that may place an upper-bound on the range of beneficial expression variation, these constraints could severely limit the availability of beneficial expression variants. To determine whether rapid expression evolution was restricted to low-expression proteins due to these constraints on highly expressed proteins over ecological timescales, we compared venom protein expression levels across mainland and island populations for three species of pit vipers. We detected significant differentiation in protein expression levels in two of the three species and found that rapid expression differentiation was restricted to low-expression proteins. Our results suggest that various constraints on high-expression proteins reduce the availability of beneficial expression variants relative to low-expression proteins, enabling low-expression proteins to evolve, and potentially lead to adaptation, more rapidly.
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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.
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    • "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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    ABSTRACT: Virulence traits are essential for pathogen fitness but whether they affect microbial performance in the environment, where they are not needed, remains experimentally unconfirmed. We investigated this question with the facultative pathogen Listeria monocytogenes and its PrfA virulence regulon. PrfA-regulated genes are activated intracellularly (PrfA "ON") but shut down outside the host (PrfA "OFF"). Using a mutant PrfA locked ON (PrfA*) and thus causing the PrfA regulon to be constitutively activated, we show that virulence gene expression significantly impairs the listerial growth rate (μ) and maximum growth (A) in rich medium. Deletion analysis of the PrfA regulon and expression of PrfA* in a mutant lacking all PrfA-regulated genes indicated that the growth reduction was specifically due to the unneeded virulence determinants and not to pleiotropic regulatory effects of PrfA ON. No PrfA*-associated fitness disadvantage was observed in infected eukaryotic cells, where PrfA-regulated virulence gene expression is critical for survival. Microcosm experiments demonstrated that the constitutively virulent state strongly impaired L. monocytogenes performance in soil, the natural habitat of these bacteria. Our findings provide empirical proof that virulence carries a significant cost to the pathogen. They also experimentally substantiate the assumed, though not proven, key role of virulence gene regulation systems in offsetting the cost of bacterial virulence outside the host. This article is protected by copyright. All rights reserved.
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