UMass Chan Medical School Faculty Publications
UMMS Affiliation
Program in Systems Biology; Department of Microbiology and Physiological Systems
Publication Date
2019-12-05
Document Type
Article Preprint
Disciplines
Systems Biology
Abstract
The single-input module (SIM) is a regulatory motif capable of coordinating gene expression across functionally related genes. We explore the relationship between regulation of the central autoregulated TF in a negatively regulated SIM and the target genes using a synthetic biology approach paired with stochastic simulations. Surprisingly, we find a fundamental asymmetry in the level of regulation experienced by the TF gene and its targets, even if they have identical regulatory DNA; the TF gene experiences stronger repression than its targets. This asymmetry is not predicted from deterministic modeling of the system but is revealed from corresponding stochastic simulations. The magnitude of asymmetry depends on factors such as the number of targets in the SIM, TF degradation rate (or growth rate) and TF binding affinity. Beyond implications for SIM motifs, the influence of network connectivity on regulatory levels highlights an interesting challenge for predictive models of gene regulation.
Keywords
regulatory asymmetry, single-input module, gene expression, synthetic biology, stochastic simulations, Systems Biology
Rights and Permissions
The copyright holder for this preprint (which was not peer-reviewed) is the author/funder. It is made available under a CC-BY-NC-ND 4.0 International license.
DOI of Published Version
10.1101/865527
Source
bioRxiv 865527; doi: https://doi.org/10.1101/865527. Link to preprint on bioRxiv service.
Journal/Book/Conference Title
bioRxiv
Repository Citation
Ali Z, Parisutham V, Choubey S, Brewster RC. (2019). Regulatory asymmetry in the negative single-input module network motif: Role of network size, growth rate and binding affinity [preprint]. UMass Chan Medical School Faculty Publications. https://doi.org/10.1101/865527. Retrieved from https://escholarship.umassmed.edu/faculty_pubs/1659
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.