Modulating the frequency and bias of stochastic switching to control phenotypic variation

Hung, Michelle E.; Chang, Emily A; Hussein, Razika; Frazier, Katya; Shin, Jung-Eun; Sagawa, Shiori; Lim, Hyunseob

doi:10.1038/ncomms5574

Cited by 21 publications

(21 citation statements)

References 72 publications

(90 reference statements)

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“…Several examples have shown that the noise in gene expression is a potential mechanism to generate phenotypic heterogeneity [ 27 , 49 , 58 ]. The phenotypic diversity has been a focus of attention in biology, since the amount of phenotypic variation (also known as gene expression noise) in a cell population can determine fitness by affecting growth rate, robustness and adaptation [ 28 - 31 ]. Population diversity offers an alternate way that cells adapt to randomly fluctuating environments [ 30 ].…”

Section: Resultsmentioning

confidence: 99%

“…Increasing phenotypic variation is particularly beneficial to organisms that need to adapt efficiently to sudden changes in chemical composition, local temperature, or illumination [ 30 ]. In contrast, decreasing phenotypic variation is usually advantageous in constant environments [ 28 , 37 , 38 ]. The peaks of gene product distribution are a cause of generating phenotypic diversity in genetically identical cell populations [ 27 ], and the gene product noise always decreases with the increase of the leakage rate as shown above, so we naturally consider the relationship between promoter leakage and phenotypic selection.…”

Section: Resultsmentioning

confidence: 99%

“…It is particularly beneficial to microbial cells that need to adapt efficiently to sudden changes in environmental conditions [ 35 , 36 ]. And decreased phenotypic variation, where every gene product is as close as possible to an optimal level of gene expression that maximizes fitness, is usually advantageous to cells in constant environments [ 28 , 37 , 38 ]. Given the above facts or results, an unsolved question is how promoter leakage influences probability distribution and phenotypic heterogeneity.…”

Section: Introductionmentioning

confidence: 99%

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Effects of promoter leakage on dynamics of gene expression

et al. 2015

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BackgroundQuantitative analysis of simple molecular networks is an important step forward understanding fundamental intracellular processes. As network motifs occurring recurrently in complex biological networks, gene auto-regulatory circuits have been extensively studied but gene expression dynamics remain to be fully understood, e.g., how promoter leakage affects expression noise is unclear.ResultsIn this work, we analyze a gene model with auto regulation, where the promoter is assumed to have one active state with highly efficient transcription and one inactive state with very lowly efficient transcription (termed as promoter leakage). We first derive the analytical distribution of gene product, and then analyze effects of promoter leakage on expression dynamics including bursting kinetics. Interestingly, we find that promoter leakage always reduces expression noise and that increasing the leakage rate tends to simplify phenotypes. In addition, higher leakage results in fewer bursts.ConclusionsOur results reveal the essential role of promoter leakage in controlling expression dynamics and further phenotype. Specifically, promoter leakage is a universal mechanism of reducing expression noise, controlling phenotypes in different environments and making the gene produce generate fewer bursts.Electronic supplementary materialThe online version of this article (doi:10.1186/s12918-015-0157-z) contains supplementary material, which is available to authorized users.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Effects of promoter leakage on dynamics of gene expression

et al. 2015

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“…Besides allowing the quantification of intrinsic and extrinsic variation, our experimental platform can be used to study the phenotypic consequences of gene expression variability by artificially altering the endogenous variation levels of genes of interest 36,37 . Moreover, by regulating all cellular outputs to the same target levels, our integral feedback controllers effectively "cancel out" the effect of slowly-varying sources of extrinsic variation.…”

Section: Discussionmentioning

confidence: 99%

Optogenetic single-cell control of transcription achieves mRNA tunability and reduced variability

Rullan

Benzinger

et al. 2017

Preprint

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The study of gene expression at the single-cell level has exposed the importance of stochasticity for the behavior of cellular systems. Research on cellular variability has mostly relied on observing expression either in response to natural stimuli or to constant gene regulators. However, the ability to probe cells individually can lead to a deeper understanding of the underlying process. Here, we propose an experimental platform for optogenetic feedback control of individual cells. It consists of a digital micromirror device that, coupled to a microscope, can target light-responsive cells with individualized illumination profiles, thereby exploiting the good spatial resolution of optogenetic induction. Together with an automated software pipeline for segmentation, quantification and tracking of single cells, the platform enables independent and real-time control of numerous cells. We demonstrate our platform by regulating transcription in over a hundred yeast cells simultaneously, while achieving tunability of mRNA abundance. Using a novel technique to measure extrinsic variation, we further show that single cell feedback regulation of this highly stochastic process achieves a 10-fold reduction of extrinsic variation in nascent mRNA over population control, with superior control loop properties. Our platform establishes a new, flexible method for studying transcriptional dynamics in single cells.

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“…A system with such properties has only been described in bacteria by modulating bias and frequency of a genetic switch. 29 …”

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confidence: 99%

Robust Synthetic Circuits for Two-Dimensional Control of Gene Expression in Yeast

et al. 2016

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Cellular phenotypes are the result of complex interactions between many components. Understanding and predicting the system level properties of the resulting networks requires the development of perturbation tools that can simultaneously and independently modulate multiple cellular variables. Here, we develop synthetic modules that use different arrangements of two transcriptional regulators to achieve either concurrent and independent control of the expression of two genes, or decoupled control of the mean and variance of a single gene. These modules constitute powerful tools to probe the quantitative attributes of network wiring and function.

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Modulating the frequency and bias of stochastic switching to control phenotypic variation

Cited by 21 publications

References 72 publications

Effects of promoter leakage on dynamics of gene expression

Effects of promoter leakage on dynamics of gene expression

Optogenetic single-cell control of transcription achieves mRNA tunability and reduced variability

Robust Synthetic Circuits for Two-Dimensional Control of Gene Expression in Yeast

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