Literature DB >> 20441737

Counter-intuitive stochastic behavior of simple gene circuits with negative feedback.

Tatiana T Marquez-Lago1, Jörg Stelling.   

Abstract

It has often been taken for granted that negative feedback loops in gene regulation work as homeostatic control mechanisms. If one increases the regulation strength a less noisy signal is to be expected. However, recent theoretical studies have reported the exact contrary, counter-intuitive observation, which has left a question mark over the relationship between negative feedback loops and noise. We explore and systematically analyze several minimal models of gene regulation, where a transcriptional repressor negatively regulates its own expression. For models including a quasi-steady-state assumption, we identify processes that buffer noise change (RNA polymerase binding) or accentuate it (repressor dimerization) alongside increasing feedback strength. Moreover, we show that lumping together transcription and translation in simplified models clearly underestimates the impact of negative feedback strength on the system's noise. In contrast, in systems without a quasi-steady-state assumption, noise always increases with negative feedback strength. Hence, subtle mathematical properties and model assumptions yield different types of noise profiles and, by consequence, previous studies have simultaneously reported decrease, increase or persistence of noise levels with increasing feedback. We discuss our findings in terms of separation of timescales and time correlations between molecular species distributions, extending current theoretical findings on the topic and allowing us to propose what we believe new ways to better characterize noise. Copyright (c) 2010 Biophysical Society. Published by Elsevier Inc. All rights reserved.

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Year:  2010        PMID: 20441737      PMCID: PMC2862162          DOI: 10.1016/j.bpj.2010.01.018

Source DB:  PubMed          Journal:  Biophys J        ISSN: 0006-3495            Impact factor:   4.033


  30 in total

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8.  Stochasticity of gene products from transcriptional pulsing.

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10.  Stochastic mRNA synthesis in mammalian cells.

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  18 in total

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2.  Systems biology: The cost of feedback control.

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3.  Quantifying negative feedback regulation by micro-RNAs.

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4.  Deciphering noise amplification and reduction in open chemical reaction networks.

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Journal:  J R Soc Interface       Date:  2018-12-21       Impact factor: 4.118

5.  Delays induce novel stochastic effects in negative feedback gene circuits.

Authors:  Eder Zavala; Tatiana T Marquez-Lago
Journal:  Biophys J       Date:  2014-01-21       Impact factor: 4.033

6.  A moment-convergence method for stochastic analysis of biochemical reaction networks.

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Review 7.  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

8.  Type of noise defines global attractors in bistable molecular regulatory systems.

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9.  Modeling and simulation of biological systems from image data.

Authors:  Ivo F Sbalzarini
Journal:  Bioessays       Date:  2013-03-27       Impact factor: 4.345

10.  The magnitude and colour of noise in genetic negative feedback systems.

Authors:  Margaritis Voliotis; Clive G Bowsher
Journal:  Nucleic Acids Res       Date:  2012-05-11       Impact factor: 16.971

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