Consequences of mRNA Transport on Stochastic Variability in Protein Levels

Singh, Abhyudai; Bokes, Pavol

doi:10.1016/j.bpj.2012.07.015

Cited by 118 publications

(164 citation statements)

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“…But whether the selective traffic of proteins and RNAs can act to increase or decrease the stochastic fluctuations in eukaryotic gene expression have only recently been studied. A theoretical study has demonstrated that mRNA transport rate can regulate noise in gene expression (Singh and Bokes, 2012). More recently, Bahar Halpern et al (2015); Battich et al (2015) have shown experimentally that nuclear retention of mRNA in single mammalian cells can reduce noise in mRNA levels.…”

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?…”

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confidence: 99%

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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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Section: Introductionmentioning

confidence: 99%

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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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“…noise levels are reduced to the Poisson limit. Thus, stochastic delays function to effectively filter out underlying bursty production [64], [65].…”

Section: One-step Conversionmentioning

confidence: 99%

Stochastic delays suppress noise in a genetic circuit with negative feedback

Smith

Singh

2019

Preprint

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We consider a mechanistic stochastic model of an autoregulatory genetic circuit with time delays. More specifically, a protein is expressed in random bursts from its corresponding gene. The synthesized protein is initially inactive and becomes active after a time delay. Rather than considering a deterministic delay, a key aspect of this work is to incorporate stochastic time delays, where delay is an independent and identically distributed random variable. The active protein inhibits its own production creating a negative feedback loop. Our analysis reveals that for an exponentially-distributed time delay, the noise in the protein levels decreases to the Poisson limit with increasing mean time delay. Interesting, for a gammadistributed time delay contrasting noise behaviors emerge based on the negative feedback strength. At low feedback strengths the protein noise levels monotonically decreases to the Poisson limit with increasing average delay. At intermediate feedback strengths, the noise levels first increase to reach a maximum, and then decease back to the Poisson limit with increasing average delay. Finally, for strong feedbacks the protein noise levels monotonically increase with the average delay. For each of these scenarios we provide approximate analytical formulas for the protein mean and noises levels, and validate these results by performing exact Monte Carlo simulations. In conclusion, our results uncover a counter intuitive feature where inclusion of stochastic delays in a negative feedback circuit can play a beneficial role in buffering deleterious fluctuations in the level of a protein.

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“…Using simulations and transcript counting, it was demonstrated that nuclear retention of mRNA can buffer cytoplasmic noise. While nuclear mRNA content can fluctuate in line with bursty transcription, the delay in the export of transcripts to the cytoplasm produces a constant “trickle” of mRNA from the nucleus, and therefore balances cytoplasmic mRNA levels between bursts (Figure A) …”

Section: Buffering Mechanisms That Reduce the Variability Generated Bmentioning

confidence: 99%

Single molecule approaches for studying gene regulation in metabolic tissues

Farack

Egozi

Itzkovitz

2018

Diabetes Obesity Metabolism

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Gene expression in metabolic tissues can be regulated at multiple levels, ranging from the control of promoter accessibilities, transcription rates, mRNA degradation rates and mRNA localization. Modulating these processes can differentially affect important performance criteria of cells. These include precision, cellular economy, rapid response and maintenance of DNA integrity. In this review we will describe how distinct strategies of gene regulation impact the trade-offs between the cells' performance criteria. We will highlight tools based on single molecule visualization of transcripts that can be used to measure promoter states, transcription rates and mRNA degradation rates in intact tissues. These approaches revealed surprising recurrent patterns in mammalian tissues, that include transcriptional bursting, nuclear retention of mRNA, and coordination of mRNA lifetimes to facilitate rapid adaptation to changing metabolic inputs. The ability to characterize gene expression at the single molecule level can uncover the design principles of gene regulation in metabolic tissues such as the liver and the pancreas.

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Consequences of mRNA Transport on Stochastic Variability in Protein Levels

Cited by 118 publications

References 54 publications

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

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

Stochastic delays suppress noise in a genetic circuit with negative feedback

Single molecule approaches for studying gene regulation in metabolic tissues

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