Regulation of mean and noise of the in vivo kinetics of transcription under the control of the <i>lac/ara‐1</i> promoter

Kandhavelu, Meenakshisundaram; Lloyd-Price, Jason; Gupta, Abhishekh; Muthukrishnan, Anantha-Barathi; Yli‐Harja, Olli; Ribeiro, André S.

doi:10.1016/j.febslet.2012.09.014

Cited by 22 publications

(52 citation statements)

References 37 publications

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“…This production is a sub-Poissonian process, as the normalized variance (σ 2 /µ 2 ) of the distribution is 0.37. Similar conclusions were obtained from measurements of the in vivo kinetics of RNA production under the control of P lac/ara- 1 and P tetA (9,10). …”

Section: Resultssupporting

confidence: 83%

In vivo single-molecule kinetics of activation and subsequent activity of the arabinose promoter

Mäkelä

Kandhavelu

Oliveira

et al. 2013

Nucleic Acids Research

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Using a single-RNA detection technique in live Escherichia coli cells, we measure, for each cell, the waiting time for the production of the first RNA under the control of PBAD promoter after induction by arabinose, and subsequent intervals between transcription events. We find that the kinetics of the arabinose intake system affect mean and diversity in RNA numbers, long after induction. We observed the same effect on Plac/ara-1 promoter, which is inducible by arabinose or by IPTG. Importantly, the distribution of waiting times of Plac/ara-1 is indistinguishable from that of PBAD, if and only if induced by arabinose alone. Finally, RNA production under the control of PBAD is found to be a sub-Poissonian process. We conclude that inducer-dependent waiting times affect mean and cell-to-cell diversity in RNA numbers long after induction, suggesting that intake mechanisms have non-negligible effects on the phenotypic diversity of cell populations in natural, fluctuating environments.

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Section: Resultssupporting

confidence: 83%

In vivo single-molecule kinetics of activation and subsequent activity of the arabinose promoter

Mäkelä

Kandhavelu

Oliveira

et al. 2013

Nucleic Acids Research

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“…This situation can be modeled by stochastic switching between the two states with rates k on and k off (left panel in Fig 1A and Materials and Methods). However, as was previously observed in both eukaryotic and prokaryotic cell cultures [11, 12, 14, 15], once the gene is switched off the system may have to progress through a series of OFF states before the gene can be reactivated. Recently these kinds of cycle models have been discussed for the hunchback promoter [22].…”

Section: Resultsmentioning

confidence: 80%

“…To understand the details of the regulatory process that controls mRNA expression we need to quantify the statistics of the activation and inactivation times, as has been performed in cell cultures [11, 12, 14, 15]. However the very short duration of the cell cycles (6-15 minutes for cell cycles 11-13) in early fly development prevents accumulation of statistics about the inactivation events and interpretation of these distributions.…”

Section: Introductionmentioning

confidence: 99%

Precision of Readout at the hunchback Gene: Analyzing Short Transcription Time Traces in Living Fly Embryos

et al. 2016

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The simultaneous expression of the hunchback gene in the numerous nuclei of the developing fly embryo gives us a unique opportunity to study how transcription is regulated in living organisms. A recently developed MS2-MCP technique for imaging nascent messenger RNA in living Drosophila embryos allows us to quantify the dynamics of the developmental transcription process. The initial measurement of the morphogens by the hunchback promoter takes place during very short cell cycles, not only giving each nucleus little time for a precise readout, but also resulting in short time traces of transcription. Additionally, the relationship between the measured signal and the promoter state depends on the molecular design of the reporting probe. We develop an analysis approach based on tailor made autocorrelation functions that overcomes the short trace problems and quantifies the dynamics of transcription initiation. Based on live imaging data, we identify signatures of bursty transcription initiation from the hunchback promoter. We show that the precision of the expression of the hunchback gene to measure its position along the anterior-posterior axis is low both at the boundary and in the anterior even at cycle 13, suggesting additional post-transcriptional averaging mechanisms to provide the precision observed in fixed embryos.

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“…Which and how many steps most contribute to the observed transcription dynamics appears to depend on the promoter and intra- and extracellular conditions [10, 11, 13, 22, 23]. In what concerns modeling this process, for example, if the promoter’s visit to the off-state or a sequential step are fast, these can be eliminated from the model, as they do not contribute significantly to the transcription dynamics.…”

Section: Methodsmentioning

confidence: 99%

Temperature-Dependent Model of Multi-step Transcription Initiation in Escherichia coli Based on Live Single-Cell Measurements

et al. 2016

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Transcription kinetics is limited by its initiation steps, which differ between promoters and with intra- and extracellular conditions. Regulation of these steps allows tuning both the rate and stochasticity of RNA production. We used time-lapse, single-RNA microscopy measurements in live Escherichia coli to study how the rate-limiting steps in initiation of the Plac/ara-1 promoter change with temperature and induction scheme. For this, we compared detailed stochastic models fit to the empirical data in maximum likelihood sense using statistical methods. Using this analysis, we found that temperature affects the rate limiting steps unequally, as nonlinear changes in the closed complex formation suffice to explain the differences in transcription dynamics between conditions. Meanwhile, a similar analysis of the PtetA promoter revealed that it has a different rate limiting step configuration, with temperature regulating different steps. Finally, we used the derived models to explore a possible cause for why the identified steps are preferred as the main cause for behavior modifications with temperature: we find that transcription dynamics is either insensitive or responds reciprocally to changes in the other steps. Our results suggests that different promoters employ different rate limiting step patterns that control not only their rate and variability, but also their sensitivity to environmental changes.

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Regulation of mean and noise of the in vivo kinetics of transcription under the control of the lac/ara‐1 promoter

Cited by 22 publications

References 37 publications

In vivo single-molecule kinetics of activation and subsequent activity of the arabinose promoter

In vivo single-molecule kinetics of activation and subsequent activity of the arabinose promoter

Precision of Readout at the hunchback Gene: Analyzing Short Transcription Time Traces in Living Fly Embryos

Temperature-Dependent Model of Multi-step Transcription Initiation in Escherichia coli Based on Live Single-Cell Measurements

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