Frequency selectivity, multistability, and oscillations emerge from models of genetic regulatory systems
Abstract
To examine the capability of genetic regulatory systems for complex dynamic activity, we developed simple kinetic models that incorporate known features of these systems. These include autoregulation and stimulus-dependent phosphorylation of transcription factors (TFs), dimerization of TFs, crosstalk, and feedback. The simplest model manifested multiple stable steady states, and brief perturbations could switch the model between these states. Such transitions might explain, for example, how a brief pulse of hormone or neurotransmitter could elicit a long-lasting cellular response. In slightly more complex models, oscillatory regimes were identified. The addition of competition between activating and repressing TFs provided a plausible explanation for optimal stimulus frequencies that give maximal transcription. Such optimal frequencies are suggested by recent experiments comparing training paradigms for long-term memory formation and examining changes in mRNA levels in repetitively stimulated cultured cells. In general, the computational approach illustrated here, combined with appropriate experiments, provides a conceptual framework for investigating the function of genetic regulatory systems.
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Computational simulations have supported the plausibility of a mechanism based on differential phosphorylation of dCREB2 isoforms, but it has not been validated empirically.
“Computational simulations have supported the plausibility of this mechanism65, but it has not been validated empirically.”
From The right time to learn: Mechanisms and optimization of spaced learning (2016) · cites this paper as [65]
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- Authors
- Smolen, P., Baxter, D. A., & Byrne, J. H.
- Affiliations
- The University of Texas Health Science Center at Houston (US)
- Venue
- American Journal of Physiology-Cell Physiology
- Publisher
- American Physiological Society
- Published
- 1998-02-01
- Volume
- 274
- Issue
- 2
- Pages
- C531-C542
- ISSN
- 0363-6143 (ISSN-L)
- 1522-1563
- OpenAlex
- W2167176119
- Cited by
- 185
- References
- 46
- Citations by year
- 2026: 3 · 2025: 3 · 2024: 5 · 2023: 1 · 2022: 8 · 2021: 4 · 2020: 6 · 2019: 9 · 2018: 14 · 2017: 7 · 2016: 11 · 2015: 4 · 2014: 7 · 2013: 5 · 2012: 7
- FWCI
- 0.28
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- American Journal of Physiology-Cell Physiology (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institutes of Health (5k05mh000649-09)
- National Institute of Mental Health (K05 MH00649)
- National Institute of Neurological Disorders and Stroke (T32 NS 07373, T32NS007373)
- National Center for Research Resources (R01RR11626, R01RR011626)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene Regulatory Network Analysis
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Physical Sciences › Mathematics › Geometry and Topology › Advanced Differential Equations and Dynamical Systems
- Keywords
- frequency selectivity, multistability, oscillations, autoregulation, transcription factor phosphorylation, transcription factor dimerization, crosstalk, feedback, long-term memory formation, kinetic model
- MeSH terms
- Animals, Gene Expression Regulation, Genes, Regulator, Homeostasis, Humans, Models, Genetic, Transcription Factors, Dimerization
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