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Optimality and evolution of transcriptionally regulated gene expression.
Frank J Poelwijk1, Philip D Heyning, Marjon G J de Vos
1AMOLF Institute, Science Park 104, 1098 XG, Amsterdam, The Netherlands.
BMC Systems Biology
|August 18, 2011
Summary
Gene expression evolution was studied by decoupling regulatory and metabolic functions. Cells evolved to optimal expression levels in constant environments, demonstrating the power of natural selection on gene regulation.
Area of Science:
- Evolutionary biology
- Molecular biology
- Systems biology
Background:
- Understanding how natural selection shapes gene expression is crucial.
- Quantifying the costs and benefits of gene expression is challenging.
Purpose of the Study:
- To directly measure the costs and benefits of gene expression.
- To investigate the evolution of transcriptional regulation under natural selection.
Main Methods:
- Decoupled regulatory and metabolic functions of the Escherichia coli lac system.
- Used a non-metabolizable inducer and a non-inducing carbon source.
- Measured growth rates to determine optimal expression levels and conducted serial transfer experiments for evolutionary response.
Main Results:
- Identified expression levels maximizing benefits minus costs without models.
- Observed evolution towards predicted optima in constant environments.
- Found increased expression phenotypes were more genetically accessible than decreased ones.
- Alternating environments led to overall expression changes, limited by tradeoff curves.
Conclusions:
- Directly measuring costs and benefits enables study of gene regulation evolution.
- Regulated gene expression evolves to predicted optima within hundreds of generations.
- Provides quantitative insights into the adaptive origins of regulatory systems.
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