Flexibility and sensitivity in gene regulation out of equilibrium

Cells adapt to environments and tune gene expression by controlling the concentrations of proteins and their kinetics in regulatory networks. In both eukaryotes and prokaryotes, experiments and theory increasingly attest that these networks can and do consume biochemical energy. How does this dissipation enable cellular behaviors forbidden in equilibrium? This open question demands quantitative models that transcend thermodynamic equilibrium. Here, we study the control of simple, ubiquitous gene regulatory networks to explore the consequences of departing equilibrium in transcription. Employing graph theory to model a set of especially common regulatory motifs, we find that dissipation unlocks nonmonotonicity and enhanced sensitivity of gene expression with respect to a transcription factor's concentration. These features allow a single transcription factor to act as both a repressor and activator at different concentrations or achieve outputs with multiple concentration regimes of locally enhanced sensitivity. We systematically dissect how energetically driving individual transitions within regulatory networks, or pairs of transitions, generates a wide range of more adjustable and sensitive phenotypic responses than in equilibrium. These results generalize to more complex regulatory scenarios, including combinatorial control by multiple transcription factors, which we relate and often find collapse to simple mathematical behaviors. Our findings quantify necessary conditions and detectable consequences of energy expenditure. These richer mathematical behaviors-feasibly accessed using biological energy budgets and rates-may empower cells to accomplish sophisticated regulation with simpler architectures than those required at equilibrium.

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Publication Details

Journal
Proceedings of the National Academy of Sciences
Published
2024-11-05
DOI
https://doi.org/10.1073/pnas.2411395121
Citations
20
Primary Topic
Gene Regulatory Network Analysis
Type
article
Field-Weighted Citation Impact
4.68

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article

Flexibility and sensitivity in gene regulation out of equilibrium

Patill Daghlian, Rob Phillips, Gabriel L. Salmon, Hernán G. García et al.
20 citations
Proceedings of the National Academy of Sciences
Gene Regulatory Network Analysis
4.68
article

Flexibility and sensitivity in gene regulation out of equilibrium

Patill Daghlian, Rob Phillips, Gabriel L. Salmon, Hernán G. García, Sara D. Mahdavi
article en
20 citations

Abstract

Cells adapt to environments and tune gene expression by controlling the concentrations of proteins and their kinetics in regulatory networks. In both eukaryotes and prokaryotes, experiments and theory increasingly attest that these networks can and do consume biochemical energy. How does this dissipation enable cellular behaviors forbidden in equilibrium? This open question demands quantitative models that transcend thermodynamic equilibrium. Here, we study the control of simple, ubiquitous gene regulatory networks to explore the consequences of departing equilibrium in transcription. Employing graph theory to model a set of especially common regulatory motifs, we find that dissipation unlocks nonmonotonicity and enhanced sensitivity of gene expression with respect to a transcription factor's concentration. These features allow a single transcription factor to act as both a repressor and activator at different concentrations or achieve outputs with multiple concentration regimes of locally enhanced sensitivity. We systematically dissect how energetically driving individual transitions within regulatory networks, or pairs of transitions, generates a wide range of more adjustable and sensitive phenotypic responses than in equilibrium. These results generalize to more complex regulatory scenarios, including combinatorial control by multiple transcription factors, which we relate and often find collapse to simple mathematical behaviors. Our findings quantify necessary conditions and detectable consequences of energy expenditure. These richer mathematical behaviors-feasibly accessed using biological energy budgets and rates-may empower cells to accomplish sophisticated regulation with simpler architectures than those required at equilibrium.

Proceedings of the National Academy of SciencesVol. 121(46)
QB3 (US), California Institute of Technology (US), Chan Zuckerberg Initiative (United States) (US), University of California, Berkeley (US)
National Science Foundation, Foundation for the National Institutes of Health, California Institute of Technology, Chan Zuckerberg Initiative, Tel Aviv University, National Institutes of Health, Donna and Benjamin M. Rosen Bioengineering Center, California Institute of Technology, Center for Environmental Microbial Interactions, California Institute of Technology
Affordable and clean energy
Openalex Percentile: Top 4%
Gene Regulatory Network Analysis
4.68
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