Improving the genetic stability of bacterial growth control for long-term bioproduction.

Using microorganisms for bioproduction requires the reorientation of metabolic fluxes from biomass synthesis to the production of compounds of interest. We previously engineered a synthetic growth switch in Escherichia coli based on inducible expression of the β- and β'-subunits of RNA polymerase. Depending on the level of induction, the cells stop growing or grow at a rate close to that of the wild-type strain.

Maturation models of fluorescent proteins are necessary for unbiased estimates of promoter activity.

Fluorescent proteins (FPs) are a powerful tool to quantitatively monitor gene expression. The dynamics of a promoter and its regulation can be inferred from fluorescence data. The interpretation of fluorescent data, however, is strongly dependent on the maturation of FPs since different proteins mature in distinct ways.

Multiomics Study of Bacterial Growth Arrest in a Synthetic Biology Application.

We investigated the scalability of a previously developed growth switch based on external control of RNA polymerase expression. Our results indicate that, in liter-scale bioreactors operating in fed-batch mode, growth-arrested cells are able to convert glucose to glycerol at an increased yield. A multiomics quantification of the physiology of the cells shows that, apart from acetate production, few metabolic side effects occur.

Acetate Metabolism and the Inhibition of Bacterial Growth by Acetate.

During aerobic growth on glucose, excretes acetate, a mechanism called "overflow metabolism." At high concentrations, the secreted acetate inhibits growth. Several mechanisms have been proposed for explaining this phenomenon, but a thorough analysis is hampered by the diversity of experimental conditions and strains used in these studies.

An ensemble of mathematical models showing diauxic growth behaviour.

Background: Carbon catabolite repression (CCR) controls the order in which different carbon sources are metabolised. Although this system is one of the paradigms of regulation in bacteria, the underlying mechanisms remain controversial. CCR involves the coordination of different subsystems of the cell - responsible for the uptake of carbon sources, their breakdown for the production of energy and precursors, and the conversion of the latter to biomass.

Mathematical modelling of microbes: metabolism, gene expression and growth.

The growth of microorganisms involves the conversion of nutrients in the environment into biomass, mostly proteins and other macromolecules. This conversion is accomplished by networks of biochemical reactions cutting across cellular functions, such as metabolism, gene expression, transport and signalling. Mathematical modelling is a powerful tool for gaining an understanding of the functioning of this large and complex system and the role played by individual constituents and mechanisms.

Resource Reallocation in Bacteria by Reengineering the Gene Expression Machinery.

Bacteria have evolved complex regulatory networks to control the activity of transcription and translation, and thus the growth rate, over a range of environmental conditions. Reengineering RNA polymerase and ribosomes allows modifying naturally evolved regulatory networks and thereby profoundly reorganizing the manner in which bacteria allocate resources to different cellular functions. This opens new opportunities for our fundamental understanding of microbial physiology and for a variety of applications.

Dynamical Allocation of Cellular Resources as an Optimal Control Problem: Novel Insights into Microbial Growth Strategies.

Microbial physiology exhibits growth laws that relate the macromolecular composition of the cell to the growth rate. Recent work has shown that these empirical regularities can be derived from coarse-grained models of resource allocation. While these studies focus on steady-state growth, such conditions are rarely found in natural habitats, where microorganisms are continually challenged by environmental fluctuations.

A synthetic growth switch based on controlled expression of RNA polymerase.

The ability to control growth is essential for fundamental studies of bacterial physiology and biotechnological applications. We have engineered an Escherichia coli strain in which the transcription of a key component of the gene expression machinery, RNA polymerase, is under the control of an inducible promoter. By changing the inducer concentration in the medium, we can adjust the RNA polymerase concentration and thereby switch bacterial growth between zero and the maximal growth rate supported by the medium.

Robust reconstruction of gene expression profiles from reporter gene data using linear inversion.

Motivation: Time-series observations from reporter gene experiments are commonly used for inferring and analyzing dynamical models of regulatory networks. The robust estimation of promoter activities and protein concentrations from primary data is a difficult problem due to measurement noise and the indirect relation between the measurements and quantities of biological interest.

Results: We propose a general approach based on regularized linear inversion to solve a range of estimation problems in the analysis of reporter gene data, notably the inference of growth rate, promoter activity, and protein concentration profiles.

Characterization of the Escherichia coli σ(S) core regulon by Chromatin Immunoprecipitation-sequencing (ChIP-seq) analysis.

In bacteria, selective promoter recognition by RNA polymerase is achieved by its association with σ factors, accessory subunits able to direct RNA polymerase "core enzyme" (E) to different promoter sequences. Using Chromatin Immunoprecipitation-sequencing (ChIP-seq), we searched for promoters bound by the σ(S)-associated RNA polymerase form (Eσ(S)) during transition from exponential to stationary phase. We identified 63 binding sites for Eσ(S) overlapping known or putative promoters, often located upstream of genes (encoding either ORFs or non-coding RNAs) showing at least some degree of dependence on the σ(S)-encoding rpoS gene.

Inference of quantitative models of bacterial promoters from time-series reporter gene data.

The inference of regulatory interactions and quantitative models of gene regulation from time-series transcriptomics data has been extensively studied and applied to a range of problems in drug discovery, cancer research, and biotechnology. The application of existing methods is commonly based on implicit assumptions on the biological processes under study. First, the measurements of mRNA abundance obtained in transcriptomics experiments are taken to be representative of protein concentrations.

Repression of flagellar genes in exponential phase by CsgD and CpxR, two crucial modulators of Escherichia coli biofilm formation.

Escherichia coli adapts its lifestyle to the variations of environmental growth conditions, swapping between swimming motility or biofilm formation. The stationary-phase sigma factor RpoS is an important regulator of this switch, since it stimulates adhesion and represses flagellar biosynthesis. By measuring the dynamics of gene expression, we show that RpoS inhibits the transcription of the flagellar sigma factor, FliA, in exponential growth phase.

A genome-wide screen for identifying all regulators of a target gene.

We have developed a new screening methodology for identifying all genes that control the expression of a target gene through genetic or metabolic interactions. The screen combines mutant libraries with luciferase reporter constructs, whose expression can be monitored in vivo and over time in different environmental conditions. We apply the method to identify the genes that control the expression of the gene acs, encoding the acetyl coenzyme A synthetase, in Escherichia coli.

Expression dynamics of RpoS/Crl-dependent genes in Escherichia coli.

The alternative sigma factor RpoS is a central regulator of the stress response in many Proteobacteria, acting both during exponential growth and in stationary phase. The small protein Crl increases the interaction between RpoS and RNA polymerase and thereby activates certain RpoS-dependent promoters. However, the growth-phase dependence of the interaction of Crl with different forms of polymerase remains unknown.

Shared control of gene expression in bacteria by transcription factors and global physiology of the cell.

Gene expression is controlled by the joint effect of (i) the global physiological state of the cell, in particular the activity of the gene expression machinery, and (ii) DNA-binding transcription factors and other specific regulators. We present a model-based approach to distinguish between these two effects using time-resolved measurements of promoter activities. We demonstrate the strength of the approach by analyzing a circuit involved in the regulation of carbon metabolism in E.

Genetic network analyzer: a tool for the qualitative modeling and simulation of bacterial regulatory networks.

Genetic Network Analyzer (GNA) is a tool for the qualitative modeling and simulation of gene regulatory networks, based on so-called piecewise-linear differential equation models. We describe the use of this tool in the context of the modeling of bacterial regulatory networks, notably the network of global regulators controlling the adaptation of Escherichia coli to carbon starvation conditions. We show how the modeler, by means of GNA, can define a regulatory network, build a model of the network, determine the steady states of the system, perform a qualitative simulation of the network dynamics, and analyze the simulation results using model-checking tools.

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

Gene regulatory networks consist of direct interactions, but also include indirect interactions mediated by metabolism. We investigate to which extent these indirect interactions arising from metabolic coupling influence the dynamics of the system. To this end, we build a qualitative model of the gene regulatory network controlling carbon assimilation in Escherichia coli, and use this model to study the changes in gene expression following a diauxic shift from glucose to acetate.

The carbon assimilation network in Escherichia coli is densely connected and largely sign-determined by directions of metabolic fluxes.

Gene regulatory networks consist of direct interactions but also include indirect interactions mediated by metabolites and signaling molecules. We describe how these indirect interactions can be derived from a model of the underlying biochemical reaction network, using weak time-scale assumptions in combination with sensitivity criteria from metabolic control analysis. We apply this approach to a model of the carbon assimilation network in Escherichia coli.

Experimental and computational validation of models of fluorescent and luminescent reporter genes in bacteria.

Background: Fluorescent and luminescent reporter genes have become popular tools for the real-time monitoring of gene expression in living cells. However, mathematical models are necessary for extracting biologically meaningful quantities from the primary data.

Results: We present a rigorous method for deriving relative protein synthesis rates (mRNA concentrations) and protein concentrations by means of kinetic models of gene expression.

WellReader: a MATLAB program for the analysis of fluorescence and luminescence reporter gene data.

Motivation: Fluorescent and luminescent reporter gene systems in combination with automated microplate readers allow real-time monitoring of gene expression on the population level at high precision and sampling density. This generates large amounts of data for the analysis of which computer tools are missing to date.

Results: We have developed WellReader, a MATLAB program for the analysis of fluorescent and luminescent reporter gene data.

The Crl-RpoS regulon of Escherichia coli.

The RpoS subunit of RNA polymerase controls the expression of numerous genes involved in stationary phase and in response to different stress conditions. The regulatory protein Crl increases the activity of RpoS by direct interaction with the RpoS holoenzyme. To define the extent of the Crl regulon, we used two-dimensional SDS-PAGE to measure the role of Crl in regulating the expression of the Escherichia coliproteome in stationary phase at 30 degrees C.

Mutual regulation of Crl and Fur in Escherichia coli W3110.

The small regulatory protein Crl controls the expression of curli. Recently we have shown that Crl interacts directly with one of the most global regulators of Escherichia coli, the stress-related sigma factor RpoS, suggesting a more global role for Crl. We show here by a proteomics analysis that the expression of at least nine cellular proteins was considerably modified when Crl was overexpressed.

Parallel changes in global protein profiles during long-term experimental evolution in Escherichia coli.

Twelve populations of Escherichia coli evolved in and adapted to a glucose-limited environment from a common ancestor. We used two-dimensional protein electrophoresis to compare two evolved clones, isolated from independently derived populations after 20,000 generations. Exceptional parallelism was detected.

Qualitative simulation of the carbon starvation response in Escherichia coli.

In case of nutritional stress, like carbon starvation, Escherichia coli cells abandon their exponential-growth state to enter a more resistant, non-growth state called stationary phase. This growth-phase transition is controlled by a genetic regulatory network integrating various environmental signals. Although E.