Literature DB >> 27131487

Decomposition and tunability of expression noise in the presence of coupled feedbacks.

Peijiang Liu1, Zhanjiang Yuan1, Haohua Wang1, Tianshou Zhou1.   

Abstract

Expression noise results in cell-to-cell variability in expression levels, and feedback regulation may complicate the tracing of sources of this noise. Using a representative model of gene expression with feedbacks, we analytically show that the expression noise (or the total noise) is decomposed into three parts: feedback-dependent promoter noise determined by a continuous approximation, birth-death noise determined by a simple Poisson process, and correlation noise induced by feedbacks. We clarify confused relationships between feedback and noise in previous studies, by showing that feedback-regulated noisy sources have different contributions to the total noise in different cases of promoter switching (it is an essential reason resulting in confusions). More importantly, we find that there is a tradeoff between response time and expression noise. In addition, we show that in contrast to single feedbacks, coupled positive and negative feedbacks can perform better in tuning expression noise, controlling expression levels, and maintaining response time. The overall analysis implies that living organisms would utilize coupled positive and negative feedbacks for better survival in complex and fluctuating environments.

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Year:  2016        PMID: 27131487     DOI: 10.1063/1.4947202

Source DB:  PubMed          Journal:  Chaos        ISSN: 1054-1500            Impact factor:   3.642


  2 in total

Review 1.  Stochastic Modeling of Autoregulatory Genetic Feedback Loops: A Review and Comparative Study.

Authors:  James Holehouse; Zhixing Cao; Ramon Grima
Journal:  Biophys J       Date:  2020-02-25       Impact factor: 4.033

2.  Stochastic fluctuations can reveal the feedback signs of gene regulatory networks at the single-molecule level.

Authors:  Chen Jia; Peng Xie; Min Chen; Michael Q Zhang
Journal:  Sci Rep       Date:  2017-11-22       Impact factor: 4.379

  2 in total

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