Program in Systems Biology; Department of Microbiology and Physiological Systems
Biochemistry, Biophysics, and Structural Biology | Systems Biology
Individual regulatory proteins are typically charged with the simultaneous regulation of a battery of different genes. As a result, when one of these proteins is limiting, competitive effects have a significant impact on the transcriptional response of the regulated genes. Here we present a general framework for the analysis of any generic regulatory architecture that accounts for the competitive effects of the regulatory environment by isolating these effects into an effective concentration parameter. These predictions are formulated using the grand-canonical ensemble of statistical mechanics and the fold-change in gene expression is predicted as a function of the number of transcription factors, the strength of interactions between the transcription factors and their DNA binding sites, and the effective concentration of the transcription factor. The effective concentration is set by the transcription factor interactions with competing binding sites within the cell and is determined self-consistently. Using this approach, we analyze regulatory architectures in the grand-canonical ensemble ranging from simple repression and simple activation to scenarios that include repression mediated by DNA looping of distal regulatory sites. It is demonstrated that all the canonical expressions previously derived in the case of an isolated, non-competing gene, can be generalised by a simple substitution to their grand canonical counterpart, which allows for simple intuitive incorporation of the influence of multiple competing transcription factor binding sites. As an example of the strength of this approach, we build on these results to present an analytical description of transcriptional regulation of the lac operon.
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Copyright: © 2017 Landman et al.
DOI of Published Version
PLoS One. 2017 Jul 7;12(7):e0179235. doi: 10.1371/journal.pone.0179235. eCollection 2017. Link to article on publisher's site
Landman J, Brewster RC, Weinert FM, Phillips R, Kegel WK. (2017). Self-consistent theory of transcriptional control in complex regulatory architectures. Program in Systems Biology Publications. https://doi.org/10.1371/journal.pone.0179235. Retrieved from https://escholarship.umassmed.edu/sysbio_pubs/108
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