Optimality and evolution of transcriptionally regulated gene expression

Frank J. Poelwijk, Philip D. Heyning, Marjon G J de Vos, Daniel J. Kiviet, Sander J. Tans

Research output: Contribution to journalArticle

17 Citations (Scopus)

Abstract

Background: How transcriptionally regulated gene expression evolves under natural selection is an open question. The cost and benefit of gene expression are the driving factors. While the former can be determined by gratuitous induction, the latter is difficult to measure directly.Results: We addressed this problem by decoupling the regulatory and metabolic function of the Escherichia coli lac system, using an inducer that cannot be metabolized and a carbon source that does not induce. Growth rate measurements directly identified the induced expression level that maximizes the metabolism benefits minus the protein production costs, without relying on models. Using these results, we established a controlled mismatch between sensing and metabolism, resulting in sub-optimal transcriptional regulation with the potential to improve by evolution. Next, we tested the evolutionary response by serial transfer. Constant environments showed cells evolving to the predicted expression optimum. Phenotypes with decreased expression emerged several hundred generations later than phenotypes with increased expression, indicating a higher genetic accessibility of the latter. Environments alternating between low and high expression demands resulted in overall rather than differential changes in expression, which is explained by the concave shape of the cross-environmental tradeoff curve that limits the selective advantage of altering the regulatory response.Conclusions: This work indicates that the decoupling of regulatory and metabolic functions allows one to directly measure the costs and benefits that underlie the natural selection of gene regulation. Regulated gene expression is shown to evolve within several hundreds of generations to optima that are predicted by these costs and benefits. The results provide a step towards a quantitative understanding of the adaptive origins of regulatory systems.

Original languageEnglish (US)
Article number128
JournalBMC Systems Biology
Volume5
DOIs
StatePublished - Aug 16 2011

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Gene expression
Gene Expression
Cost-Benefit Analysis
Optimality
Genetic Selection
Metabolism
Phenotype
Costs
Natural Selection
Decoupling
Carbon
Escherichia coli
Costs and Cost Analysis
Transcriptional Regulation
Gene Regulation
Growth
Proteins
Accessibility
Escherichia Coli
Genes

ASJC Scopus subject areas

  • Molecular Biology
  • Structural Biology
  • Applied Mathematics
  • Modeling and Simulation
  • Computer Science Applications

Cite this

Poelwijk, F. J., Heyning, P. D., de Vos, M. G. J., Kiviet, D. J., & Tans, S. J. (2011). Optimality and evolution of transcriptionally regulated gene expression. BMC Systems Biology, 5, [128]. https://doi.org/10.1186/1752-0509-5-128

Optimality and evolution of transcriptionally regulated gene expression. / Poelwijk, Frank J.; Heyning, Philip D.; de Vos, Marjon G J; Kiviet, Daniel J.; Tans, Sander J.

In: BMC Systems Biology, Vol. 5, 128, 16.08.2011.

Research output: Contribution to journalArticle

Poelwijk, FJ, Heyning, PD, de Vos, MGJ, Kiviet, DJ & Tans, SJ 2011, 'Optimality and evolution of transcriptionally regulated gene expression', BMC Systems Biology, vol. 5, 128. https://doi.org/10.1186/1752-0509-5-128
Poelwijk, Frank J. ; Heyning, Philip D. ; de Vos, Marjon G J ; Kiviet, Daniel J. ; Tans, Sander J. / Optimality and evolution of transcriptionally regulated gene expression. In: BMC Systems Biology. 2011 ; Vol. 5.
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