Comparison of classical and autogenous systems of regulation in inducible operons

Savageau, Michael A.

doi:10.1038/252546a0

Cited by 205 publications

(191 citation statements)

References 13 publications

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“…Strong supporting evidence suggested in ref. 19 and verified in ref. 20 indicates that the rise time in the level of a protein, following a step induction in an open-loop transcription unit, can be dramatically improved by adding a negative feedback loop.…”

Section: Discussionsupporting

confidence: 68%

Surviving heat shock: Control strategies for robustness and performance

El-Samad

Kurata²,

Doyle³

et al. 2005

Proc. Natl. Acad. Sci. U.S.A.

250

263

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Molecular biology studies the cause-and-effect relationships among microscopic processes initiated by individual molecules within a cell and observes their macroscopic phenotypic effects on cells and organisms. These studies provide a wealth of information about the underlying networks and pathways responsible for the basic functionality and robustness of biological systems. At the same time, these studies create exciting opportunities for the development of quantitative and predictive models that connect the mechanism to its phenotype then examine various modular structures and the range of their dynamical behavior. The use of such models enables a deeper understanding of the design principles underlying biological organization and makes their reverse engineering and manipulation both possible and tractable The heat shock response presents an interesting mechanism where such an endeavor is possible. Using a model of heat shock, we extract the design motifs in the system and justify their existence in terms of various performance objectives. We also offer a modular decomposition that parallels that of traditional engineering control architectures.control theory ͉ heat shock stress response ͉ mathematical modeling A systems approach is a promising venue for studying biological complexity. The hallmark of this approach is an analysis of the dynamics of the biological network and the protocols used for their interactions. Experiences from fields like engineering, where model-based analysis and design have been the central paradigm, provide a glimpse of what is achievable (1). Biology and engineering share many similarities at the system level (2), including the use of complexity to achieve robustness and performance rather than for minimal functionality. We define robustness as the capability of a system to operate reliably when its physical parameters vary within their expected ranges; conversely, fragility is defined as hypersensitivity to such parametric variations. We suspect that the comparative study of genetic networks will confirm that robustness and the ability to achieve prompt adaptation in the presence of environmental challenges impose severe constraints on the underlying architecture of a system and are the source of the general design motifs repeated in many cellular networks.Here, we study the heat shock response (hsr) in Escherichia coli. The hsr is universally conserved among organisms and serves to remedy protein damage induced by heat and other stresses (reviewed in ref.3). We build a model for the E. coli hsr system, analyze its layers of regulation, and argue that its complexity is a necessary outcome of design requirements such as robustness, speed of response, noise rejection, and efficiency. This model provides useful insight into the heat shock system design architecture. It also suggests a mathematical and conceptual modular decomposition that defines the functional blocks or submodules of the heat shock system. This decomposition is drawn by analogy to manmade control systems and is foun...

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Section: Discussionsupporting

confidence: 68%

Surviving heat shock: Control strategies for robustness and performance

El-Samad

Kurata²,

Doyle³

et al. 2005

Proc. Natl. Acad. Sci. U.S.A.

250

263

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“…Approximately 40% of known transcription factors in Escherichia coli are subject to negative transcriptional autoregulation (Thieffry et al, 1998;Rosenfeld et al, 2002). Negative feedback control is typically considered as an important means of repressing the noise level in gene expression by suppressing the variability of the protein level across cells (Savageau, 1974;Becskei and Serrano, 2000;Simpson et al, 2003;Swain, 2004;Boyer et al, 2005;Tao et al, 2007). However, introducing negative feedback without increasing transcription or translation rates can amplify the intrinsic noise level, as negative feedback causes a decrease in the average number of mRNAs and proteins, which results in an increase in the protein variability (Shahrezaei et al, 2008;Singh and Hespanha, 2009).…”

Section: Introductionmentioning

confidence: 99%

“…It is known that both negative feedback and compartmentalisation can reduce gene expression noise (Savageau, 1974;Becskei and Serrano, 2000;Simpson et al, 2003;Swain, 2004;Boyer et al, 2005;Tao et al, 2007;Singh and Bokes, 2012;Bahar Halpern et al, 2015;Battich et al, 2015). The central question we sought to address in this paper was: what effect does the combination of both negative feedback and compartmentalisation have on gene expression noise?…”

mentioning

confidence: 99%

The influence of nuclear compartmentalisation on stochastic dynamics of self-repressing gene expression

Sturrock

Shahrezaei

2017

Journal of Theoretical Biology

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Gene expression is an inherently noisy process. This noise is generally thought to be deleterious as precise internal regulation of biochemical reactions is essential for cell growth and survival. Selfrepression of gene expression, which is the simplest form of a negative feedback loop, is commonly believed to be employed by cellular systems to decrease the stochastic fluctuations in gene expression. When there is some delay in autoregulation, it is also believed that this system can generate oscillations. In eukaryotic cells, mRNAs that are synthesised in the nucleus must be exported to the cytoplasm to function in protein synthesis, whereas proteins must be transported into the nucleus from the cytoplasm to regulate the expression levels of genes. Nuclear transport thus plays a critical role in eukaryotic gene expression and regulation. Some recent studies have suggested that nuclear retention of mRNAs can control noise in mRNA expression. However, the effect of nuclear transport on protein noise and its interplay with negative feedback regulation is not completely understood. In this paper, we systematically compare four different simple models of gene expression. By using simulations and applying the linear noise approximation to the corresponding chemical master equations, we investigate the influence of nuclear import and export on noise in gene expression in a negative autoregulatory feedback loop. We first present results consistent with the literature, i.e., that negative feedback can effectively buffer the variability in protein levels, and nuclear retention can decrease mRNA noise levels. Interestingly we find that when negative feedback is combined with nuclear retention, an amplification in gene expression noise can be observed and is dependant on nuclear translocation rates. Finally, we investigate the effect of nuclear compartmentalisation on the ability of self-repressing genes to exhibit stochastic oscillatory dynamics.

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“…Negative feedback is therefore commonly used to maintain homeostasis and to reduce the fluctuations in intracellular processes such as gene expression [3][4][5] . For example, nearly half of the B300 transcription factors (TFs) in Escherichia coli make use of negative feedback on their own expression 6,7 .…”

mentioning

confidence: 99%

Transcription factor binding kinetics constrain noise suppression via negative feedback

2013

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Negative autoregulation, where a transcription factor regulates its own expression by preventing transcription, is commonly used to suppress fluctuations in gene expression. Recent single molecule in vivo imaging has shown that it takes significant time for a transcription factor molecule to bind its chromosomal binding site. Given the slow association kinetics, transcription factor mediated feedback cannot at the same time be fast and strong. Here we show that with a limited association rate follows an optimal transcription factor binding strength where noise is maximally suppressed. At the optimal binding strength the binding site is free a fixed fraction of the time independent of the transcription factor concentration. One consequence is that high-copy number transcription factors should bind weakly to their operators, which is observed for transcription factors in Escherichia coli. The results demonstrate that a binding site's strength may be uncorrelated to its functional importance.

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Comparison of classical and autogenous systems of regulation in inducible operons

Cited by 205 publications

References 13 publications

Surviving heat shock: Control strategies for robustness and performance

Surviving heat shock: Control strategies for robustness and performance

The influence of nuclear compartmentalisation on stochastic dynamics of self-repressing gene expression

Transcription factor binding kinetics constrain noise suppression via negative feedback

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