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Growth rate-dependent global effects on gene expression in bacteria
Stefan Klumpp1, Zhongge Zhang, Terence Hwa
1Center for Theoretical Biological Physics, University of California, San Diego, La Jolla, CA 92093-0374, USA. klumpp@ctbp.ucsd.edu
Cell
|January 13, 2010
Summary
Bacterial growth rate significantly impacts gene expression due to changes in cellular components like RNA polymerases and ribosomes. This study models these effects, revealing a feedback mechanism that can influence antibiotic resistance and cell growth.
Area of Science:
- Microbiology
- Systems Biology
- Synthetic Biology
Background:
- Bacterial gene expression is influenced by both specific regulatory networks and global cellular parameters.
- Key cellular components, including RNA polymerases and ribosomes, exhibit growth-rate dependent abundance, affecting overall gene expression.
- Quantitative understanding of these global effects is crucial for gene regulation studies and synthetic circuit design.
Purpose of the Study:
- To model and experimentally verify the impact of bacterial growth rate on gene expression.
- To analyze complex growth dependencies in synthetic genetic circuits with regulatory elements.
- To investigate a potential feedback mechanism linking protein expression, cell growth, and physiological functions.
Main Methods:
- Development of a quantitative model incorporating measured growth-rate dependent cellular parameters.
- Experimental validation using synthetic genetic circuits with activators, repressors, and feedback loops.
- Analysis of a novel feedback mechanism mediated by general growth effects.
Main Results:
- A simple model accurately explains the growth-rate dependence of constitutive gene expression.
- Complex growth dependencies in synthetic circuits were successfully analyzed and experimentally verified.
- Evidence suggests a growth-feedback mechanism, independent of explicit gene regulation, can influence cell behavior.
Conclusions:
- Bacterial growth rate is a fundamental determinant of gene expression, predictable through cellular parameter modeling.
- Synthetic circuits exhibit complex, growth-dependent behaviors that can be engineered and understood.
- A general growth-feedback mechanism may underlie important physiological adaptations like antibiotic resistance and persistence.
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