In vivo kinetics of transcription initiation of the lar promoter in Escherichia coli. Evidence for a sequential mechanism with two rate-limiting steps

<p>Abstract</p> <p>Background</p> <p>In <it>Escherichia coli </it>the mean and cell-to-cell diversity in RNA numbers of different genes vary widely. This is likely due to different kinetics of transcription initiation, a complex process with multiple rate-limiting steps that affect RNA production.</p> <p>Results</p> <p>We measured the <it>in vivo </it>kinetics of production of individual RNA molecules under the control of the lar promoter in <it>E. coli</it>. From the analysis of the distributions of intervals between transcription events in the regimes of weak and medium induction, we find that the process of transcription initiation of this promoter involves a sequential mechanism with two main rate-limiting steps, each lasting hundreds of seconds. Both steps become faster with increasing induction by IPTG and Arabinose.</p> <p>Conclusions</p> <p>The two rate-limiting steps in initiation are found to be important regulators of the dynamics of RNA production under the control of the lar promoter in the regimes of weak and medium induction. Variability in the intervals between consecutive RNA productions is much lower than if there was only one rate-limiting step with a duration following an exponential distribution. The methodology proposed here to analyze the <it>in vivo </it>dynamics of transcription may be applicable at a genome-wide scale and provide valuable insight into the dynamics of prokaryotic genetic networks.</p

Rate-limiting Steps in Transcription Initiation are Key Regulatory Mechanisms of Escherichia coli Gene Expression Dynamics

In all living organisms, the “blueprints of life” are documented in the genetic material. This material is composed of genes, which are regions of DNA coding for proteins. To produce proteins, cells read the information on the DNA with the help of molecular machines, such as RNAp holoenzymes and a factors. Proteins carry out the cellular functions required for survival and, as such, cells deal with challenging environments by adjusting their gene expression pattern. For this, cells constantly perform decision- making processes of whether or not to actively express a protein, based on intracellular and environmental cues. In Escherichia coli, gene expression is mostly regulated at the stage of transcription initiation. Although most of its regulatory molecules have been identified, the dynamics and regulation of this step remain elusive. Due to a limited number of specific regulatory molecules in the cells, the stochastic fluctuations of these molecular numbers can result in a sizeable temporal change in the numbers of transcription outputs (RNA and proteins) and have consequences on the phenotype of the cells. To understand the dynamics of this process, one should study the activity of the gene by tracking mRNA and protein production events at a detailed level. Recent advancements in single-molecule detection techniques have been used to image and track individually labeled fluorescent macromolecules of living cells. This allows investigating the intermolecular dynamics under any given condition. In this thesis, by using in vivo, single-RNA time-lapse microscopy techniques along with stochastic modelling techniques, we studied the kinetics of multi-rate limiting steps in the transcription process of multiple promoters, in various conditions. Specifically, first, we established a novel method of dissecting transcription in Escherichia coli that combines state-of-the-art microscopy measurements and model fitting techniques to construct detailed models of the rate-limiting steps governing the in vivo transcription initiation of a synthetic Lac-ara-1 promoter. After that, we estimated the duration of the closed and open complex formation, accounting for the rate of reversibility of the first step. From this, we also estimated the duration of periods of promoter inactivity, from which we were able to determine the contribution from each step to the distribution of intervals between consecutive RNA productions in individual cells. Second, using the above method, we studied the a factor selective mechanisms for indirect regulation of promoters whose transcription is primarily initiated by RNAp holoenzymes carrying a70. From the analysis, we concluded that, in E. coli, a promoter’s responsiveness to indirect regulation by a factor competition is determined by its sequence-dependent, dynamically regulated multi-step initiation kinetics. Third, we investigated the effects of extrinsic noise, arising from cell-to-cell variability in cellular components, on the single-cell distribution of RNA numbers, in the context of cell lineages. For this, first, we used stochastic models to predict the variability in the numbers of molecules involved in upstream processes. The models account for the intake of inducers from the environment, which acts as a transient source of variability in RNA production numbers, as well as for the variability in the numbers of molecular species controlling transcription of an active promoter, which acts as a constant source of variability in RNA numbers. From measurement analysis, we demonstrated the existence of lineage-to-lineage variability in gene activation times and mean transcription rates. Finally, we provided evidence that this can be explained by differences in the kinetics of the rate-limiting steps in transcription and of the induction scheme, from which it is possible to conclude that these variabilities differ between promoters and inducers used. Finally, we studied how the multi-rate limiting steps in the transcription initiation are capable of tuning the asymmetry and tailedness of the distribution of time intervals between consecutive RNA production events in individual cells. For this, first, we considered a stochastic model of transcription initiation and predicted that the asymmetry and tailedness in the distribution of intervals between consecutive RNA production events can differ by tuning the rate-limiting steps in transcription. Second, we validated the model with measurements from single-molecule RNA microscopy of transcription kinetics of multiple promoters in multiple conditions. Finally, from our results, we concluded that the skewness and kurtosis in RNA and protein production kinetics are subject to regulation by the kinetics of the steps in transcription initiation and affect the single-cell distributions of RNAs and, thus, proteins. We further showed that this regulation can significantly affect the probability of RNA and protein numbers to cross specific thresholds. Overall, the studies conducted in this thesis are expected to contribute to a better understanding of the dynamic process of bacterial gene expression. The advanced data and image analysis techniques and novel stochastic modeling approaches that we developed during the course of these studies, will allow studying in detail the in vivo regulation of multi-rate limiting steps of transcription initiation of any given promoter. In addition, by tuning the kinetics of the rate-limiting steps in the transcription initiation as executed here should allow engineering new promoters, with predefined RNA and, thus, protein production dynamics in Escherichia coli

Regulation of Single-Cell Bacterial Gene Expression at the Stage of Transcription Initiation

One of the qualities that allow bacterial cells to survive in diverse, fluctuating environments is phenotypic plasticity, which is the ability to exhibit different phenotypes depending on the environmental conditions. Phenotypic plasticity arises via coordinated work of small genetic circuits that provide the cell with the means for decision-making. The behavior of these circuits depends, among other factors, on the ability of protein numbers to cross certain thresholds for a sufficient amount of time. In bacteria, RNA numbers largely define protein numbers and thus can be used to study the decision-making processes. Previous research outlined the effects of mean and variance in RNA or protein numbers on the behavior of small genetic circuits. However, noise in gene expression is often highly asymmetric. This could impact the threshold-crossing abilities of molecular numbers in a way that is not detectable by considering only their mean and variance. The focus of this thesis is to study the regulation of multi-step kinetics of bacterial gene expression in live bacteria and its effects on the shape of the distribution of RNA or protein levels. In particular, the thesis investigates how the rate-limiting steps in bacterial transcription, such as closed and open complex formation, intermittent inactive states, and promoter escape contribute to the dynamics of RNA numbers, and how this dynamics propagates to the distribution of protein levels in a cell population. This study made use of already existing techniques such as measurements at the single-RNA level and dynamically accurate stochastic modeling, complemented by the novel methodology developed in this work. First, the thesis introduced a new method for estimating the numbers of fluorescently tagged molecules present in a cell from time series data obtained by microscopy. This method allows improving the accuracy of the estimation when fluorescently tagged molecules are absent from the cell image for time intervals comparable with cell lifetime. Second, the new methodology for dissecting in vivo kinetics of rate-limiting steps in transcription initiation was proposed. Applying this methodology to study initiation kinetics at lac/ara-1 promoter provided insights on the amount, duration, and reversibility of the rate-limiting steps in this process. Further, the thesis investigated the kinetics of transcription activation of lac/ara-1 promoter at various temperatures. The results indicate that additional rate-limiting steps emerge in inducer intake kinetics as temperature decreases from optimal (37 °C). Finally, the focus was shifted specifically to quantifying the asymmetry and tailedness in RNA and protein level distributions, since these features are relevant for determining threshold crossing propensities. Here, these features were found to depend both on promoter sequence and on regulatory molecules, thus being evolvable and adaptable. Overall, the work conducted in this thesis suggests that asymmetries in RNA and protein numbers may be crucial for decision-making in bacteria, since they can be regulated by promoter sequence, regulatory molecules levels, and temperature shifts. The thesis also contributes to the pool of existing methodology for studying in vivo bacterial gene expression using single-cell biology approach. These findings should be of use both for better understanding of natural systems and for fine-tuning behavior of synthetic gene circuits

Study of the influence of σ factors on the kinetics of RNA production

Gene expression dynamics inEscherichia coliis controlled at the transcription initiation stage, whichbeginswhen an RNA polymerase holoenzyme, composed of RNA polymerase core enzyme and the σ factor, recognizes the promoter sequence of a gene. Under different conditions, different σ factors are used. Also,some promoters require a specific σ factor, while others haveless specificity. The intracellular levels of σ factors vary between σ factorsand with the cell growth phase.It is still unknown whether different σ factors will lead to differing kinetics of transcription initiation, thereby,in this study it will be characterized the dynamicsof this processby different σ factors, under optimal growth conditionsandunder the control of either of twopromoters, PtetAandPBAD, during the exponential and stationary growth phases. Mutant cells,lacking σ54 or σ38were used and the dynamics of transcription initiation was compared with wild-type cells, for each of the two promoters and during each of the two growth phases. For this, RNA molecules are detected as soon as they are producedin each cell, using an MS2-GFP tagging method,and the distribution of time intervals between consecutive RNA productions are obtainedin each condition.From the results obtained it is concluded that: PtetAis not affected by the σ factors’ populationcompositionduring the two growth cellular phases studied, while PBADit is;the dynamics of transcription initiation is affected by the promoter used; there are 3 rate-limiting steps in transcription initiation under control of the two promoters for the 3 strains during the phases analyzed; the distribution of the intervals are not exponential-like; RNA production is sub-Poissonian; the results of the model developed are in agreement with the observations from in vivomeasurements under control of PtetA,while for PBAD there are some differences

Environment-sensing Mechanisms of Gene Expression and their Effects on the Dynamics of Genetic Circuits across Cell Generations

In genetic circuits, the constituent genes do not interact only between themselves, they are also affected by regulatory molecules of the host cells that support the circuits’ operation and by the environmental conditions. These factors, along with the intrinsic noise in gene expression, affect the functioning of the circuits. As such, to understand the structure of natural circuits and to engineer functional synthetic circuits, one needs to characterize thoroughly how external factors and perturbations from the environment may affect their behavior.This thesis focused on two cellular mechanisms through which the dynamics of gene expression becomes environment dependent: the intake of gene expression regulatory molecules from the media and the σ factor competition. The first mechanism determines the dynamics by which inducer molecules in the media enter the cell cytoplasm and trigger or repress the expression of the target gene. The second mechanism allows cells to change its gene expression profile to adapt to specific stress conditions.Following the characterization of the effects of these mechanisms on the expression dynamics of individual genes from live, single cell measurements, we then performed in silico assessments on how these effects at the single gene level propagate to the circuit level. Here, the dynamics of genetic circuits was observed in both non-dividing and dividing cell populations, where errors in the partitioning of molecules in cell division occur and introduce significant variance between sister cells.From these studies, with the knowledge on the factors of the host cells and their environment sensing mechanisms, more predictive models of the circuits’ dynamics are expected to emerge. The models would further help in identifying what circuit composition, properties of the host strains and environmental conditions are needed for the circuits to exhibit the desired behavior

Studies of the plasticity of transcription in Escherichia coli using single-molecule, in vivo detection techniques

The phenotypic characteristics of living organisms are shaped by the interactions of the genotype with the environment. In their lifetime, organisms are subject to various environmental changes, some of which are stressful. They cope up with these by means of phenotypic plasticity. In prokaryotes, this plasticity is achieved mostly by rapid adaptations of the gene expression profile. To better understand this, it is critical to study the mechanisms by which these adaptations are implemented. In Escherichia coli, transcription initiation is the first and most regulated step in gene expression. In vitro studies suggest that this is a complex, sequential process. Its rate-limiting steps regulate both the rate and the fluctuations of RNA production. These then determine the protein numbers and, thus, the cellular phenotype. In this work, we make use of state-of-the-art techniques in microscopy imaging, image processing and molecular probing to perform a quantitative analysis of the in vivo dynamics of transcription initiation in different environments in the prokaryotic model organism, E. coli. From the measurements, we characterize the plasticity of this process. For this, we used MS2-GFP fluorescent tagging of mRNA that allows detection of single mRNA molecules with confocal microscopy, shortly after their production. We also developed a tool to automatically track cell lineages in a time-lapse movie, and extract the spatiotemporal distribution of fluorescently tagged molecules in individual cells. From the analysis of the results, we show that, in vivo, the process of transcription initiation in E. coli is multi-stepped, as in vitro measurements had previously suggested. Also, the kinetics of each step can be independently controlled by different regulatory molecules. Further, the number and timing of the rate-limiting steps are affected by physiological changes that occur in cells when subject to changing environmental conditions. We conclude that the phenotypic plasticity of E. coli arises, partially, from the plasticity of the kinetics of the rate-limiting steps in transcription initiation

Deciphering transcriptional dynamics in vivo by counting nascent RNA molecules

Transcription of genes is the focus of most forms of regulation of gene expression. Even though careful biochemical experimentation has revealed the molecular mechanisms of transcription initiation for a number of different promoters in vitro, the dynamics of this process in cells is still poorly understood. One approach has been to measure the transcriptional output (fluorescently labeled messenger RNAs or proteins) from single cells in a genetically identical population, which could then be compared to predictions from models that incorporate different molecular mechanisms of transcription initiation. However, this approach suffers from the problem, that processes downstream from transcription can affect the measured output and therefore mask the signature of stochastic transcription initiation on the cell-to-cell variability of the transcriptional outputs. Here we show theoretically that measurements of the cell-to-cell variability in the number of nascent RNAs provide a more direct test of the mechanism of transcription initiation. We derive exact expressions for the first two moments of the distribution of nascent RNA molecules and apply our theory to published data for a collection of constitutively expressed yeast genes. We find that the measured nascent RNA distributions are inconsistent with transcription initiation proceeding via one rate-limiting step, which has been generally inferred from measurements of cytoplasmic messenger RNA. Instead, we propose a two-step mechanism of initiation, which is consistent with the available data. These findings for the yeast promoters highlight the utility of our theory for deciphering transcriptional dynamics in vivo from experiments that count nascent RNA molecules in single cells.Comment: 28 pages including S

Sequence-dependent noise filtering in small genetic motifs

The rates of intracellular processes are, in general, in constant change in response to environmental signals and other internal processes. To deal with noise in the input signals, filtering and decision-making circuits are needed. Motivated by recent evidences from in vivo measurements that the rate limiting steps in transcription initiation are critical in determine RNA and protein numbers, we study the effects of these steps on the behavior of three genetic circuits: a toggle switch, a genetic amplitude filter and a genetic frequency filter. We model these circuits, and from stochastic simulations, we study the performance of the filters and the stability of the switch. We find that these features degrade as the transcript levels are lowered. These effects can be alleviated by adding rate limiting steps to the transcription initiation process. In addition, we show that some features of the filters, such as cutoff levels, are affected by changes in mRNA production dynamics as well. In conclusion, our study shows that the kinetics of transcription initiation of the genes composing these circuits, which are largely determined by the promoter sequence, can be varied within realistic parameter ranges of values to alter considerably their behaviors

Temperature Dependence of the Transcription Dynamics of Synthetic Genes in Escherichia coli

One of the major current goals in synthetic biology is the design of genetic components with more predictable functions. This predictability, however, does not depend solely on these components, but also on the environment where they will be inserted in.Escherichia coli is one of the most studied microorganisms in Microbiology, and it is commonly used in Synthetic Biology as a host strain to test the functioning of the components of genetic systems. These components are typically well characterized under controlled laboratory conditions. However, it is unclear how unfavorable environmental conditions, such as temperature fluctuations, can affect their functionality and robustness.In this thesis, we investigated how temperature affects the kinetics of transcription activation and subsequent dynamics of RNA production of synthetic genes in E. coli. For this, we made use of state-of-the-art in vivo single RNA-detection techniques and image analysis tools, to dissect, at the single-cell and single-RNA level, the kinetics of the rate-limiting steps in transcription, as well as the intake kinetics of inducer molecules. In addition, we analyzed how the temperature dependency is affected by the promoter structure.Specifically, first, we characterized the intake kinetics of inducer molecules, from the media to the cell periplasm and then cytoplasm, at optimal and suboptimal temperatures. We found that, for a wide range of extracellular inducer concentrations, and in the absence of a transporter protein, the intake process is diffusive-like. The results also show that, the mean intake time increases nonlinearly with decreasing temperature, likely due to the emergence of additional rate-limiting steps at low temperatures. Finally, our results indicate that the dynamics of this intake process affects significantly the expected RNA numbers in individual cells for a significant amount of time following induction and, thus, the overall distribution of RNA numbers of the cell population.Next, we studied the temperature dependence of the dynamics of transcription initiation of a synthetic gene, engineered from a viral promoter. This dependency is shown to occur at the level of the underlying kinetics of the rate limiting steps in initiation. From the analysis of the empirical data, we found that, first, similarly to E. coli promoters, the T7 phage Phi 10 promoter exhibits more than one rate-limiting step during initiation. Also, the mean time-length of these steps is temperature dependent. However, contrary to E. coli promoters, the noise in RNA production increases with increasing temperature within the range of temperatures tested.Finally, we investigated a key mechanism of transcription, namely, the robustness of a transcription repression mechanism by analyzing the rate of ‘leaky’ transcription events, i.e., RNA production events when under full repression. Using the LacO3O1 as a model promoter, from the analysis of the empirical data on single RNA production kinetics, we found that this promoter exhibits a leakiness rate that is higher at low temperatures, suggesting that its repression mechanism is less efficient under these conditions.We believe that the studies presented here contribute to a better understanding of how temperature affects the transcription dynamics of synthetic genes in environments where temperature fluctuations occur. Since the acquired knowledge is of use to better understand the behavior of synthetic promoters, we expect our main contribution to be in the area of Synthetic Biology, namely, to be of value in predicting the robustness of future synthetic genetic circuits to temperature shifts. In particular, our results show that, in the genes studied, the repression mechanism is the most affected by temperature. This strong temperature dependence translates into the hindering of the promoter responsiveness to induction at sub-optimal temperature conditions. Additionally, our results suggest that this temperature-dependence of the robustness and responsiveness can be tuned, which indicates that it is possible to engineer synthetic promoters of higher response accuracy for a wider range of environmental conditions than those studied here. This knowledge can be used in the construction of synthetic genetic circuits with a more predictable, robust behavior