Temperature-dependence of the single-cell variability in the kinetics of transcription activation in Escherichia coli (original) (raw)
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PLoS computational biology, 2016
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...
General properties of transcriptional time series in Escherichia coli
Nature Genetics, 2011
A gene's activity can be described by the discrete time series of mRNA production events 1,2 . This transcriptional time series is stochastic rather than deterministic 2-4 . Furthermore, it generally cannot be described as a simple Poisson process. In other words, mRNA molecules are not produced with a constant probability per unit time; instead, mRNA production is often bursty (pulsatile) in both bacteria 2 and higher organisms 4-8 . A suitable mathematical framework for describing gene activity data is the two-state model 8-10 , where a gene stochastically fluctuates between 'off ' and 'on' states, and mRNA is produced stochastically only in the on state. This scenario can lead to the occurrence of transcription 'bursts' , periods of intense activity separated by periods of quiescence. Measured mRNA kinetics 2,5 and copy-number statistics have been shown to be consistent with the two-state picture in a variety of model systems. However, despite considerable theoretical attention 2,13-17 , we do not have a biophysical understanding of the nature of the on and off states and what governs the transitions between them.
FEBS Letters, 2012
The kinetics of transcription initiation in Escherichia coli depend on the duration of two rate-limiting steps, the closed and the open complex formation. In a lac promoter variant, P lac/ara-1 , the kinetics of these steps is controlled by IPTG and arabinose. From in vivo single-RNA measurements, we find that induction affects the mean and normalized variance of the intervals between consecutive RNA productions. Transcript production is sub-Poissonian in all conditions tested. The kinetics of each step is independently controlled by a different inducer. We conclude that the regulatory mechanism of P lac/ara-1 allows the stochasticity of gene expression to be environment-dependent.
Nucleic Acids Research, 2012
In Escherichia coli, tetracycline prevents translation. When subject to tetracycline, E. coli express TetA to pump it out by a mechanism that is sensitive, while fairly independent of cellular metabolism. We constructed a target gene, P tetA -mRFP1-96BS, with a 96 MS2-GFP binding site array in a single-copy BAC vector, whose expression is controlled by the tetA promoter. We measured the in vivo kinetics of production of individual RNA molecules of the target gene as a function of inducer concentration and temperature. From the distributions of intervals between transcription events, we find that RNA production by P tetA is a sub-Poissonian process. Next, we infer the number and duration of the prominent sequential steps in transcription initiation by maximum likelihood estimation. Under full induction and at optimal temperature, we observe three major steps. We find that the kinetics of RNA production under the control of P tetA , including number and duration of the steps, varies with induction strength and temperature. The results are supported by a set of logical pairwise Kolmogorov-Smirnov tests. We conclude that the expression of TetA is controlled by a sequential mechanism that is robust, whereas sensitive to external signals.
Thermodynamic analysis of the transcription cycle in E. coli
Biophysical Chemistry, 1990
The E. coli RNA transcription cycle can be divided into three major phases, which are generafly called initiation, elongation, and termiuation. In this paper, we review recent biophysical studies of the interactions of the transcriptional regulatory proteins, sigma7o and NusA, with tbemsefves and with core RNA polymerase in solution, as well as with core polymerase within the transcription complex. The different affinities of sigma70 and NusA for core RNA polymerase at various stages in the transcription cycle, together with other quantitative data, are then used to construct a partial free energy diagram for the overall transcription process. 'Ibis thermodynamic framework, which is interrupted by at least two irreversible steps, can be used to rationalize physiological aspects of the transcription cycle and its regulation, as well as to identify crucial points at which our knowledge is still incomplete.
2017
Transcription is the dominant point of control of gene expression. Biochemical studies have revealed key molecular components of transcription and their interactions, but the dynamics of transcription initiation in cells is still poorly understood. This state of affairs is being remedied with experiments that observe transcriptional dynamics in single cells using fluorescent reporters. Quantitative information about transcription initiation dynamics can also be extracted from experiments that use electron micrographs of RNA polymerases caught in the act of transcribing a gene (Miller spreads). Inspired by these data we analyze a general stochastic model of transcription initiation and elongation, and compute the distribution of transcription initiation times. We show that different mechanisms of initiation leave distinct signatures in the distribution of initiation times that can be compared to experiments. We analyze published micrographs of RNA polymerases transcribing ribosomal R...
Real-Time Kinetics of Gene Activity in Individual Bacteria
Cell, 2005
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 mRNAprotein 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.
Transcriptional Response of Escherichia coli to Temperature Shift
Biotechnology Progress, 2008
Temperature shift is often practiced in the cultivation of Escherichia coli to reduce undesired metabolite formation and to maximize synthesis of correctly folded heterologous protein. As the culture temperature is decreased below the optimal 37°C, growth rate decreases and many physiological changes occur. In this study, we investigated the gene expression dynamics of E. coli on switching its cultivation temperature from 37 to 33 and 28°C using whole genome DNA microarrays. Approximately 9% of the genome altered expression level on temperature shift. Overall, the alteration of transcription upon the downshift of temperature is rapid and globally distributed over a wide range of gene classes. The general trends of transcriptional changes at 28 and 33°C were similar. The largest functional class among the differentially expressed genes was energy metabolism. About 12% of genes in energy metabolism show a decrease in their level of expression, and ∼6% show an increase. Consistent with the decrease in the glucose uptake rate, many genes involved in glycolysis and the PTS sugar transport systems show decreased expression. Genes encoding enzymes related to amino acid biosynthesis and transport also have reduced expression levels. Such decrease in expression probably reflects the reduced growth rate and the accompanying reduction in energy and amino acid demand at lower temperatures. However, nearly all genes encoding enzymes in the TCA cycle have increased expression levels, which may well be compensating the reduction of the activity of TCA cycle enzymes at lower temperatures. Temperature shift also results in shift of the cytochromes from the high affinity cytochrome o system to the low affinity cytochrome d system. There is no evidence that protein processing genes are selectively altered to create favorable conditions for heterologous protein synthesis. Our results indicate that the beneficial effect of temperature shift in many biotechnological processes is likely to be attributed to the general effect of reduced growth and metabolism.
Spatiotemporal patterns and transcription kinetics of induced RNA in single bacterial cells
Proceedings of the National Academy of Sciences, 2009
Bacteria have a complex internal organization with specific localization of many proteins and DNA, which dynamically move during the cell cycle and in response to changing environmental stimuli. Much less is known, however, about the localization and movements of RNA molecules. By modifying our previous RNA labeling system, we monitor the expression and localization of a model RNA transcript in live Escherichia coli cells. Our results reveal that the target RNA is not evenly distributed within the cell and localizes laterally along the long cell axis, in a pattern suggesting the existence of ordered helical RNA structures reminiscent of known bacterial cytoskeletal cellular elements. fluorescent protein ͉ live E. coli cells ͉ protein complementation ͉ RNA visualization D espite their relatively small dimensions, bacterial cells show a remarkable, rich internal subcellular organization that has captured the interest of researchers over the past decade (1-4). Many cytoplasmic and membrane proteins, particularly those involved in cell division, DNA replication, and chromosome segregation, have specific subcellular localizations that can change quickly over time in response to cell cycle progression, motility, and environmental cues. This dynamic and organized behavior is also true for bacterial chromosomal DNA. The use of GFP fusions and in situ fluorescence hybridization (FISH) have shown that every chromosomal locus has a defined subcellular address and is replicated and segregated into the new cell as part of an active and directed process (4, 5). Bacterial plasmids, both low and high copy, also have specific cellular addresses and segregate in a fashion that is unique for a given plasmid (6-8).