Short Residence Times of DNA-Bound Transcription Factors Can Reduce Gene Expression Noise and Increase the Transmission of Information in a Gene Regulation System
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Abstract
Gene expression noise is not just ubiquitous but also variable, and we still do not understand some of the most elementary factors that affect it. Among them is the residence time of a transcription factor (TF) on DNA, the mean time that a DNA-bound TF remains bound. Here, we use a stochastic model of transcriptional regulation to study how residence time affects the gene expression noise that arises when a TF induces gene expression. We find that the effect of residence time on gene expression noise depends on the TF's concentration and its affinity to DNA, which determine the level of induction of the gene. At high levels of induction, residence time has no effect on gene expression noise. However, as the level of induction decreases, short residence times reduce gene expression noise. The reason is that fast on-off TF binding dynamics prevent long periods where proteins are predominantly synthesized or degraded, which can cause excessive fluctuations in gene expression. As a consequence, short residence times can help a gene regulation system acquire information about the cellular environment it operates in. Our predictions are consistent with the observation that experimentally measured residence times are usually modest and lie between seconds to minutes.
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- Authors
- Azpeitia, E., & Wagner, A.
- Affiliations
- SIB Swiss Institute of Bioinformatics (CH)
- Corresponding author
- Wagner, Andreas
- Venue
- Frontiers in Molecular Biosciences
- Publisher
- Frontiers Media SA
- Published
- 2020-04-28
- Volume
- 7
- Pages
- 67-67
- ISSN
- 2296-889X (ISSN-L)
- PMC
- PMC7198700
- OpenAlex
- W3023727038
- Cited by
- 17
- References
- 6
- Citations by year
- 2026: 1 · 2024: 2 · 2023: 4 · 2022: 4 · 2021: 3 · 2020: 3
- FWCI
- 1.14
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Frontiers in Molecular Biosciences (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Zurich Open Repository and Archive (University of Zurich) (acceptedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Zurich Open Repository and Archive (University of Zurich) (submittedVersion, cc-by)
- Zurich Open Repository and Archive (University of Zurich)
- Funders
- National Science Foundation (31003A_172887)
- Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (739874, 172887)
- H2020 European Research Council (739874)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene Regulatory Network Analysis
- Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › stochastic dynamics and bifurcation
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Bacterial Genetics and Biotechnology
- Keywords
- stochastic gene expression, transcriptional regulation, stochastic gene expression models, information transmission, gene expression regulation
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