Note on the kinetics and stochastics of induced protein synthesis as influenced by various models for messenger RNA degradation

Rigney, David R.

doi:10.1016/0022-5193(79)90250-9

Cited by 14 publications

(4 citation statements)

References 9 publications

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“…It is now well appreciated that gene expression is fundamentally stochastic: The levels of any molecule within the cell will fluctuate over time and from cell-to-cell owing to the fact that individual events are inherently probabilistic. This is both a theoretical prediction (12,20,90,91,96) and an experimental fact (8,25,71,77,88,93,98,106), as can be seen in any fluorescent micrograph. These random differences can arise from many sources.…”

Section: Noise In Gene Expressionmentioning

confidence: 57%

Stochastic Switching of Cell Fate in Microbes

Norman

Lord

Paulsson

et al. 2015

Annu. Rev. Microbiol.

164

197

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Microbes transiently differentiate into distinct, specialized cell types to generate functional diversity and cope with changing environmental conditions. Though alternate programs often entail radically different physiological and morphological states, recent single-cell studies have revealed that these crucial decisions are often left to chance. In these cases, the underlying genetic circuits leverage the intrinsic stochasticity of intracellular chemistry to drive transition between states. Understanding how these circuits transform transient gene expression fluctuations into lasting phenotypic programs will require a combination of quantitative modeling and extensive, time-resolved observation of switching events in single cells. In this article, we survey microbial cell fate decisions demonstrated to involve a random element, describe theoretical frameworks for understanding stochastic switching between states, and highlight recent advances in microfluidics that will enable characterization of key dynamic features of these circuits.

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Section: Noise In Gene Expressionmentioning

confidence: 57%

Stochastic Switching of Cell Fate in Microbes

Norman

Lord

Paulsson

et al. 2015

Annu. Rev. Microbiol.

164

197

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“…Most fall into one of two categories. Some focus on how spontaneous small-number Poisson fluctuations in mRNA levels enslave the levels of their encoded proteins, possibly through bursts of translation (Berg, 1978;McAdams and Arkin, 1997;Rigney, 1979aRigney, , 1979bSwain et al, 2002;Thattai and van Oudenaarden, 2001). Others instead focus on how mRNA fluctuations in turn are enslaved by random changes in gene activity and possible bursts of transcription (Blake et al, 2003;Kepler and Elston, 2001;Peccoud and Ycart, 1995;Raser and O'Shea, 2004;Sasai and Wolynes, 2003;Tapaswi et al, 1987).…”

Section: Introductionmentioning

confidence: 99%

Real-Time Kinetics of Gene Activity in Individual Bacteria

Golding

Paulsson

Zawilski

et al. 2005

Cell

1,392

1,648

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Protein levels have been shown to vary substantially between individual cells in clonal populations. In prokaryotes, the contribution to such fluctuations from the inherent randomness of gene expression has largely been attributed to having just a few transcripts of the corresponding mRNAs. By contrast, eukaryotic studies tend to emphasize chromatin remodeling and burst-like transcription. Here, we study single-cell transcription in Escherichia coli by measuring mRNA levels in individual living cells. The results directly demonstrate transcriptional bursting, similar to that indirectly inferred for eukaryotes. We also measure mRNA partitioning at cell division and correlate mRNA and protein levels in single cells. Partitioning is approximately binomial, and mRNA-protein correlations are weaker earlier in the cell cycle, where cell division has recently randomized the relative concentrations. Our methods further extend protein-based approaches by counting the integer-valued number of transcript with single-molecule resolution. This greatly facilitates kinetic interpretations in terms of the integer-valued random processes that produce the fluctuations.

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“…The reporter proteins in the two studies, Tsr–Venus and β-gal, were both expressed under highly repressed conditions and were monitored in real time with a resolution on the scale of minutes. The most important result in both experiments was bursts in protein production, which demonstrated that gene expression is an occasional event and that a few proteins are produced nearly simultaneously by such events, consistent with theoretical predictions . Two key parameters to describe such behavior, the burst size and frequency, correspond to how productive a single expression event is and how often such events occur.…”

mentioning

confidence: 94%