Importance of metabolic coupling for the dynamics of gene expression following a diauxic shift in Escherichia coli

A model explaining mRNA level fluctuations based on activity demands and RNA age

Cellular RNA levels typically fluctuate and are influenced by different transcription rates and RNA degradation rates. However, the understanding of the fundamental relationships between RNA abundance, environmental stimuli, RNA activities, and RNA age distributions is incomplete. Furthermore, the rates of RNA degradation and transcription are difficult to measure in transcriptomic experiments in living organisms, especially in studies involving humans. A model based on activity demands and RNA age was developed to explore the mechanisms of RNA level fluctuations. Using single-cell time-series gene expression experimental data, we assessed the transcription rates, RNA degradation rates, RNA life spans, RNA demand, accumulated transcription levels, and accumulated RNA degradation levels. This model could also predict RNA levels under simulation backgrounds, such as stimuli that induce regular oscillations in RNA abundance, stable RNA levels over time that result from long-term shortage of total RNA activity or from uncontrollable transcription, and relationships between RNA/protein levels and metabolic rates. This information contributes to existing knowledge.

Detected cellular RNA levels usually fluctuate. The understanding of the fundamental relationships between RNA level fluctuations, the rates of RNA degradation and transcription, environmental stimuli, RNA activities, and RNA age distributions is incomplete. In the present research, we developed a model based on the demands of RNA (related to intrinsic and/or extrinsic information), RNA age (determines the survival time and biological activity of an RNA), transcription, and RNA degradation to explain the mechanism underlying intracellular RNA level fluctuations. We also explored applicability of the model for analysing dynamic processes between interacting biomolecules, such as the relationship between RNA and protein level fluctuations. Using single-cell time-series gene expression experimental data, we assessed some biological parameters, such as transcription rates, RNA degradation rates, and RNA life spans. This model could also predict RNA levels under simulation backgrounds, such as stimuli that induce regular oscillations in RNA abundance, stable RNA levels over time that result from long-term shortage of total RNA activity or from uncontrollable transcription, and relationships between RNA/protein levels and metabolic rates. This information contributes to existing knowledge and provides a new perspective for future studies.

Genomewide Stabilization of mRNA during a "Feast-to-Famine" Growth Transition in Escherichia coli

The ability to rapidly respond to changing nutrients is crucial for E. coli to survive in many environments, including the gut. Reorganization of gene expression is the first step used by bacteria to adjust their metabolism accordingly. It involves fine-tuning of both transcription (transcriptional regulation) and mRNA stability (posttranscriptional regulation). While the forms of transcriptional regulation have been extensively studied, the role of mRNA stability during a metabolic switch is poorly understood. Investigating E. coli genomewide transcriptome and mRNA stability during metabolic transitions representative of the carbon source fluctuations in many environments, we have documented the role of mRNA stability in the response to nutrient changes. mRNAs are globally stabilized during carbon depletion. For a few genes, this leads directly to expression upregulation. As these genes are regulators of stress responses and metabolism, our work sheds new light on the likely importance of posttranscriptional regulations in response to environmental stress.

Bacteria have to continuously adjust to nutrient fluctuations from favorable to less-favorable conditions and in response to carbon starvation. The glucose-acetate transition followed by carbon starvation is representative of such carbon fluctuations observed in Escherichia coli in many environments. Regulation of gene expression through fine-tuning of mRNA pools constitutes one of the regulation levels required for such a metabolic adaptation. It results from both mRNA transcription and degradation controls. However, the contribution of transcript stability regulation in gene expression is poorly characterized. Using combined transcriptome and mRNA decay analyses, we investigated (i) how transcript stability changes in E. coli during the glucose-acetate-starvation transition and (ii) if these changes contribute to gene expression changes. Our work highlights that transcript stability increases with carbon depletion. Most of the stabilization occurs at the glucose-acetate transition when glucose is exhausted, and then stabilized mRNAs remain stable during acetate consumption and carbon starvation. Meanwhile, expression of most genes is downregulated and we observed three times less gene expression upregulation. Using control analysis theory on 375 genes, we show that most of gene expression regulation is driven by changes in transcription. Although mRNA stabilization is not the controlling phenomenon, it contributes to the emphasis or attenuation of transcriptional regulation. Moreover, upregulation of 18 genes (33% of our studied upregulated set) is governed mainly by transcript stabilization. Because these genes are associated with responses to nutrient changes and stress, this underscores a potentially important role of posttranscriptional regulation in bacterial responses to nutrient starvation.

IMPORTANCE The ability to rapidly respond to changing nutrients is crucial for E. coli to survive in many environments, including the gut. Reorganization of gene expression is the first step used by bacteria to adjust their metabolism accordingly. It involves fine-tuning of both transcription (transcriptional regulation) and mRNA stability (posttranscriptional regulation). While the forms of transcriptional regulation have been extensively studied, the role of mRNA stability during a metabolic switch is poorly understood. Investigating E. coli genomewide transcriptome and mRNA stability during metabolic transitions representative of the carbon source fluctuations in many environments, we have documented the role of mRNA stability in the response to nutrient changes. mRNAs are globally stabilized during carbon depletion. For a few genes, this leads directly to expression upregulation. As these genes are regulators of stress responses and metabolism, our work sheds new light on the likely importance of posttranscriptional regulations in response to environmental stress.

Piecewise linear approximations to model the dynamics of adaptation to osmotic stress by food-borne pathogens

Addition of salt to food is one of the most ancient and most common methods of food preservation. However, little is known of how bacterial cells adapt to such conditions. We propose to use piecewise linear approximations to model the regulatory adaptation of Escherichiacoli to osmotic stress. We apply the method to eight selected genes representing the functions known to be at play during osmotic adaptation. The network is centred on the general stress response factor, sigma S, and also includes a module representing the catabolic repressor CRP-cAMP. Glutamate, potassium and supercoiling are combined to represent the intracellular regulatory signal during osmotic stress induced by salt. The output is a module where growth is represented by the concentration of stable RNAs and the transcription of the osmotic gene osmY. The time course of gene expression of transport of osmoprotectant represented by the symporter proP and of the osmY is successfully reproduced by the network. The behaviour of the rpoS mutant predicted by the model is in agreement with experimental data. We discuss the application of the model to food-borne pathogens such as Salmonella; although the genes considered have orthologs, it seems that supercoiling is not regulated in the same way. The model is limited to a few selected genes, but the regulatory interactions are numerous and span different time scales. In addition, they seem to be condition specific: the links that are important during the transition from exponential to stationary phase are not all needed during osmotic stress. This model is one of the first steps towards modelling adaptation to stress in food safety and has scope to be extended to other genes and pathways, other stresses relevant to the food industry, and food-borne pathogens. The method offers a good compromise between systems of ordinary differential equations, which would be unmanageable because of the size of the system and for which insufficient data are available, and the more abstract Boolean methods.

Acetate Exposure Determines the Diauxic Behavior of Escherichia coli during the Glucose-Acetate Transition

Growth of Escherichia coli on glucose in batch culture is accompanied by the excretion of acetate, which is consumed by the cells when glucose is exhausted. This glucose-acetate transition is classically described as a diauxie (two successive growth stages). Here, we investigated the physiological and metabolic properties of cells after glucose exhaustion through the analysis of growth parameters and gene expression. We found that E. coli cells grown on glucose in batch culture produce acetate and consume it after glucose exhaustion but do not grow on acetate. Acetate is catabolized, but key anabolic genes--such as the genes encoding enzymes of the glyoxylate shunt--are not upregulated, hence preventing growth. Both the induction of the latter anabolic genes and growth were observed only after prolonged exposure to low concentrations of acetate and could be accelerated by high acetate concentrations. We postulate that such decoupling between acetate catabolism and acetate anabolism might be an advantage for the survival of E. coli in the ever-changing environment of the intestine.

IMPORTANCE

The glucose-acetate transition is a valuable experimental model for comprehensive investigations of metabolic adaptation and a current paradigm for developing modeling approaches in systems microbiology. Yet, the work reported in our paper demonstrates that the metabolic behavior of Escherichia coli during the glucose-acetate transition is much more complex than what has been reported so far. A decoupling between acetate catabolism and acetate anabolism was observed after glucose exhaustion, which has not been reported previously. This phenomenon could represent a strategy for optimal utilization of carbon resources during colonization and persistence of E. coli in the gut and is also of significant interest for biotechnological applications.

Synthetic gene circuits for metabolic control: design trade-offs and constraints

A grand challenge in synthetic biology is to push the design of biomolecular circuits from purely genetic constructs towards systems that interface different levels of the cellular machinery, including signalling networks and metabolic pathways. In this paper, we focus on a genetic circuit for feedback regulation of unbranched metabolic pathways. The objective of this feedback system is to dampen the effect of flux perturbations caused by changes in cellular demands or by engineered pathways consuming metabolic intermediates. We consider a mathematical model for a control circuit with an operon architecture, whereby the expression of all pathway enzymes is transcriptionally repressed by the metabolic product. We address the existence and stability of the steady state, the dynamic response of the network under perturbations, and their dependence on common tuneable knobs such as the promoter characteristic and ribosome binding site (RBS) strengths. Our analysis reveals trade-offs between the steady state of the enzymes and the intermediates, together with a separation principle between promoter and RBS design. We show that enzymatic saturation imposes limits on the parameter design space, which must be satisfied to prevent metabolite accumulation and guarantee the stability of the network. The use of promoters with a broad dynamic range and a small leaky expression enlarges the design space. Simulation results with realistic parameter values also suggest that the control circuit can effectively upregulate enzyme production to compensate flux perturbations.

Structural and dynamical analysis of biological networks

Biological networks are currently being studied with approaches derived from the mathematical and physical sciences. Their structural analysis enables to highlight nodes with special properties that have sometimes been correlated with the biological importance of a gene or a protein. However, biological networks are dynamic both on the evolutionary time-scale, and on the much shorter time-scale of physiological processes. There is therefore no unique network for a given cellular process, but potentially many realizations, each with different properties as a consequence of regulatory mechanisms. Such realizations provide snapshots of a same network in different conditions, enabling the study of condition-dependent structural properties. True dynamical analysis can be obtained through detailed mathematical modeling techniques that are not easily scalable to full network models.