Competitive binding of transcription factors as activator-repressor in stochastic gene expression.

Das, Amit Kumar; Biswas, Debabrata · Phys Rev E · 2026

basic_science · Level V

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Abstract

In this paper, we explore the features of a genetic network where the transcription factors, namely, activators and repressors bind to the promoter in a competitive way. We have developed an analytical method to find the most probable set of parameter values that are unavailable in experiments. We study the behavior of intrinsic noise of the circuit and compare the profile with the network where the activator and the repressor bind the promoter noncompetitively. We observe that the noise found in the super-Poissonian region of the competitive genetic circuit is higher than the noise obtained in the same from a noncompetitive one. We further notice that, due to the effect of transcriptional reinitiation in the presence of the activator and repressor molecules, there exist some anomalous characteristic features in the mean expressions and noise profiles. On top of that, we find low noise in the transcriptional level and high noise in the translational level in presence of reinitiation than in absence of the same. In addition, we find out the method to reduce the noise further below the Poissonian level in competitive circuit than the noncompetitive one with the help of some noise-reducing factors. We also notice that the effect of extrinsic noise due to the environmental fluctuation on the competitive activator-repressor system is insignificant in the low noise limit.

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