Termination factor Rho mediates transcriptional reprogramming of Bacillus subtilis stationary phase.

Transcription termination factor Rho is known for its ubiquitous role in suppression of pervasive, mostly antisense, transcription. In the model Gram-positive bacterium Bacillus subtilis, de-repression of pervasive transcription by inactivation of rho revealed the role of Rho in the regulation of post-exponential differentiation programs. To identify other aspects of the regulatory role of Rho during adaptation to starvation, we have constructed a B. subtilis strain (Rho+) that expresses rho at a relatively stable high level in order to compensate for its decrease in the wild-type cells entering stationary phase. The RNAseq analysis of Rho+, WT and Δrho strains (expression profiles can be visualized at http://genoscapist.migale.inrae.fr/seb_rho/) shows that Rho over-production enhances the termination efficiency of Rho-sensitive terminators, thus reducing transcriptional read-through and antisense transcription genome-wide. Moreover, the Rho+ strain exhibits global alterations of sense transcription with the most significant changes observed for the AbrB, CodY, and stringent response regulons, forming the pathways governing the transition to stationary phase. Subsequent physiological analyses demonstrated that maintaining rho expression at a stable elevated level modifies stationary phase-specific physiology of B. subtilis cells, weakens stringent response, and thereby negatively affects the cellular adaptation to nutrient limitations and other stresses, and blocks the development of genetic competence and sporulation. These results highlight the Rho-specific termination of transcription as a novel element controlling stationary phase. The release of this control by decreasing Rho levels during the transition to stationary phase appears crucial for the functionality of complex gene networks ensuring B. subtilis survival in stationary phase.

Greedy reduction of Bacillus subtilis genome yields emergent phenotypes of high resistance to a DNA damaging agent and low evolvability.

Genome-scale engineering enables rational removal of dispensable genes in chassis genomes. Deviating from this approach, we applied greedy accumulation of deletions of large dispensable regions in the Bacillus subtilis genome, yielding a library of 298 strains with genomes reduced up to 1.48 Mb in size. High-throughput physiological phenotyping of these strains confirmed that genome reduction is associated with substantial loss of cell fitness and accumulation of synthetic-sick interactions. Transcriptome analysis indicated that <15% of the genes conserved in our genome-reduced strains exhibited a twofold or higher differential expression and revealed a thiol-oxidative stress response. Most transcriptional changes can be explained by loss of known functions and by aberrant transcription at deletion boundaries. Genome-reduced strains exhibited striking new phenotypes relative to wild type, including a very high resistance (increased >300-fold) to the DNA-damaging agent mitomycin C and a very low spontaneous mutagenesis (reduced 100-fold). Adaptive laboratory evolution failed to restore cell fitness, except when coupled with a synthetic increase of the mutation rate, confirming low evolvability. Although mechanisms underlying this emergent phenotype are not understood, we propose that low evolvability can be leveraged in an engineering strategy coupling reductive cycles with evolutive cycles under induced mutagenesis.

Differentiation of Vegetative Cells into Spores: a Kinetic Model Applied to Bacillus subtilis.

Spore-forming bacteria are natural contaminants of food raw materials, and sporulation can occur in many environments from farm to fork. In order to characterize and to predict spore formation over time, we developed a model that describes both the kinetics of growth and the differentiation of vegetative cells into spores. The model is based on a classical growth model and enables description of the kinetics of sporulation with the addition of three parameters specific to sporulation. Two parameters are related to the probability of each vegetative cell to commit to sporulation and to form a spore, and the last one is related to the time needed to form a spore once the cell is committed to sporulation. The goodness of fit of this growth-sporulation model was assessed using growth-sporulation kinetics at various temperatures in laboratory medium or in whey for Bacillus subtilis, Bacillus cereus, and Bacillus licheniformis The model accurately describes the kinetics in these different conditions, with a mean error lower than 0.78 log10 CFU/ml for the growth and 1.08 log10 CFU/ml for the sporulation. The biological meaning of the parameters was validated with a derivative strain of Bacillus subtilis 168 which produces green fluorescent protein at the initiation of sporulation. This model provides physiological information on the spore formation and on the temporal abilities of vegetative cells to differentiate into spores and reveals the heterogeneity of spore formation during and after growth.IMPORTANCE The growth-sporulation model describes the progressive transition from vegetative cells to spores with sporulation parameters describing the sporulation potential of each vegetative cell. Consequently, the model constitutes an interesting tool to assess the sporulation potential of a bacterial population over time with accurate parameters such as the time needed to obtain one resistant spore and the probability of sporulation. Further, this model can be used to assess these data under various environmental conditions in order to better identify the conditions favorable for sporulation regarding the time to obtain the first spore and/or the concentrations of spores which could be reached during a food process.

A part toolbox to tune genetic expression in Bacillus subtilis.

Libraries of well-characterised components regulating gene expression levels are essential to many synthetic biology applications. While widely available for the Gram-negative model bacterium Escherichia coli, such libraries are lacking for the Gram-positive model Bacillus subtilis, a key organism for basic research and biotechnological applications. Here, we engineered a genetic toolbox comprising libraries of promoters, Ribosome Binding Sites (RBS), and protein degradation tags to precisely tune gene expression in B. subtilis We first designed a modular Expression Operating Unit (EOU) facilitating parts assembly and modifications and providing a standard genetic context for gene circuits implementation. We then selected native, constitutive promoters of B. subtilis and efficient RBS sequences from which we engineered three promoters and three RBS sequence libraries exhibiting ∼14 000-fold dynamic range in gene expression levels. We also designed a collection of SsrA proteolysis tags of variable strength. Finally, by using fluorescence fluctuation methods coupled with two-photon microscopy, we quantified the absolute concentration of GFP in a subset of strains from the library. Our complete promoters and RBS sequences library comprising over 135 constructs enables tuning of GFP concentration over five orders of magnitude, from 0.05 to 700 µM. This toolbox of regulatory components will support many research and engineering applications in B. subtilis.

Translation elicits a growth rate-dependent, genome-wide, differential protein production in Bacillus subtilis.

Complex regulatory programs control cell adaptation to environmental changes by setting condition-specific proteomes. In balanced growth, bacterial protein abundances depend on the dilution rate, transcript abundances and transcript-specific translation efficiencies. We revisited the current theory claiming the invariance of bacterial translation efficiency. By integrating genome-wide transcriptome datasets and datasets from a library of synthetic gfp-reporter fusions, we demonstrated that translation efficiencies in Bacillus subtilis decreased up to fourfold from slow to fast growth. The translation initiation regions elicited a growth rate-dependent, differential production of proteins without regulators, hence revealing a unique, hard-coded, growth rate-dependent mode of regulation. We combined model-based data analyses of transcript and protein abundances genome-wide and revealed that this global regulation is extensively used in B. subtilis We eventually developed a knowledge-based, three-step translation initiation model, experimentally challenged the model predictions and proposed that a growth rate-dependent drop in free ribosome abundance accounted for the differential protein production.

Quantitative prediction of genome-wide resource allocation in bacteria.

Predicting resource allocation between cell processes is the primary step towards decoding the evolutionary constraints governing bacterial growth under various conditions. Quantitative prediction at genome-scale remains a computational challenge as current methods are limited by the tractability of the problem or by simplifying hypotheses. Here, we show that the constraint-based modeling method Resource Balance Analysis (RBA), calibrated using genome-wide absolute protein quantification data, accurately predicts resource allocation in the model bacterium Bacillus subtilis for a wide range of growth conditions. The regulation of most cellular processes is consistent with the objective of growth rate maximization except for a few suboptimal processes which likely integrate more complex objectives such as coping with stressful conditions and survival. As a proof of principle by using simulations, we illustrated how calibrated RBA could aid rational design of strains for maximizing protein production, offering new opportunities to investigate design principles in prokaryotes and to exploit them for biotechnological applications.

Reconciling molecular regulatory mechanisms with noise patterns of bacterial metabolic promoters in induced and repressed states.

Assessing gene expression noise in order to obtain mechanistic insights requires accurate quantification of gene expression on many individual cells over a large dynamic range. We used a unique method based on 2-photon fluorescence fluctuation microscopy to measure directly, at the single cell level and with single-molecule sensitivity, the absolute concentration of fluorescent proteins produced from the two Bacillus subtilis promoters that control the switch between glycolysis and gluconeogenesis. We quantified cell-to-cell variations in GFP concentrations in reporter strains grown on glucose or malate, including very weakly transcribed genes under strong catabolite repression. Results revealed strong transcriptional bursting, particularly for the glycolytic promoter. Noise pattern parameters of the two antagonistic promoters controlling the nutrient switch were differentially affected on glycolytic and gluconeogenic carbon sources, discriminating between the different mechanisms that control their activity. Our stochastic model for the transcription events reproduced the observed noise patterns and identified the critical parameters responsible for the differences in expression profiles of the promoters. The model also resolved apparent contradictions between in vitro operator affinity and in vivo repressor activity at these promoters. Finally, our results demonstrate that negative feedback is not noise-reducing in the case of strong transcriptional bursting.

Transcriptional regulation is insufficient to explain substrate-induced flux changes in Bacillus subtilis.

One of the key ways in which microbes are thought to regulate their metabolism is by modulating the availability of enzymes through transcriptional regulation. However, the limited success of efforts to manipulate metabolic fluxes by rewiring the transcriptional network has cast doubt on the idea that transcript abundance controls metabolic fluxes. In this study, we investigate control of metabolic flux in the model bacterium Bacillus subtilis by quantifying fluxes, transcripts, and metabolites in eight metabolic states enforced by different environmental conditions. We find that most enzymes whose flux switches between on and off states, such as those involved in substrate uptake, exhibit large corresponding transcriptional changes. However, for the majority of enzymes in central metabolism, enzyme concentrations were insufficient to explain the observed fluxes--only for a number of reactions in the tricarboxylic acid cycle were enzyme changes approximately proportional to flux changes. Surprisingly, substrate changes revealed by metabolomics were also insufficient to explain observed fluxes, leaving a large role for allosteric regulation and enzyme modification in the control of metabolic fluxes.

Nicotinic acid modulates Legionella pneumophila gene expression and induces virulence traits.

In response to environmental fluctuations or stresses, bacteria can activate transcriptional and phenotypic programs to coordinate an adaptive response. The intracellular pathogen Legionella pneumophila converts from a noninfectious replicative form to an infectious transmissive form when the bacterium encounters alterations in either amino acid concentrations or fatty acid biosynthesis. Here, we report that L. pneumophila differentiation is also triggered by nicotinic acid, a precursor of the central metabolite NAD(+). In particular, when replicative L. pneumophila are treated with 5 mM nicotinic acid, the bacteria induce numerous transmissive-phase phenotypes, including motility, cytotoxicity toward macrophages, sodium sensitivity, and lysosome avoidance. Transcriptional profile analysis determined that nicotinic acid induces the expression of a panel of genes characteristic of transmissive-phase L. pneumophila. Moreover, an additional 213 genes specific to nicotinic acid treatment were altered. Although nearly 25% of these genes lack an assigned function, the gene most highly induced by nicotinic acid treatment encodes a putative major facilitator superfamily transporter, Lpg0273. Indeed, lpg0273 protects L. pneumophila from toxic concentrations of nicotinic acid as judged by analyzing the growth of the corresponding mutant. The broad utility of the nicotinic acid pathway to couple central metabolism and cell fate is underscored by this small metabolite's modulation of gene expression by diverse microbes, including Candida glabrata, Bordetella pertussis, Escherichia coli, and L. pneumophila.

BasyLiCA: a tool for automatic processing of a Bacterial Live Cell Array.

UNLABELLED: Live Cell Array (LCA) technology allows the acquisition of high-resolution time-course profiles of bacterial gene expression by the systematic assessment of fluorescence in living cells carrying either transcriptional or translational fluorescent protein fusion. However, the direct estimation of promoter activities by time-dependent derivation of the fluorescence datasets generates high levels of noise. Here, we present BasyLiCA, a user-friendly open-source interface and database dedicated to the automatic storage and standardized treatment of LCA data. Data quality reports are generated automatically. Growth rates and promoter activities are calculated by tunable discrete Kalman filters that can be set to incorporate data from biological replicates, significantly reducing the impact of noise measurement in activity estimations. AVAILABILITY: The BasyLiCA software and the related documentation are available at http://genome.jouy.inra.fr/basylica.

What remains from living cells in bacterial lysate-based cell-free systems.

Because they mimic cells while offering an accessible and controllable environment, lysate-based cell-free systems (CFS) have emerged as valuable biotechnology tools for synthetic biology. Historically used to uncover fundamental mechanisms of life, CFS are nowadays used for a multitude of purposes, including protein production and prototyping of synthetic circuits. Despite the conservation of fundamental functions in CFS like transcription and translation, RNAs and certain membrane-embedded or membrane-bound proteins of the host cell are lost when preparing the lysate. As a result, CFS largely lack some essential properties of living cells, such as the ability to adapt to changing conditions, to maintain homeostasis and spatial organization. Regardless of the application, shedding light on the black-box of the bacterial lysate is necessary to fully exploit the potential of CFS. Most measurements of the activity of synthetic circuits in CFS and in vivo show significant correlations because these only require processes that are preserved in CFS, like transcription and translation. However, prototyping circuits of higher complexity that require functions that are lost in CFS (cell adaptation, homeostasis, spatial organization) will not show such a good correlation with in vivo conditions. Both for prototyping circuits of higher complexity and for building artificial cells, the cell-free community has developed devices to reconstruct cellular functions. This mini-review compares bacterial CFS to living cells, focusing on functional and cellular process differences and the latest developments in restoring lost functions through complementation of the lysate or device engineering.

Combining Fusion of Cells with CRISPR-Cas9 Editing for the Cloning of Large DNA Fragments or Complete Bacterial Genomes in Yeast.

The genetic engineering of genome fragments larger than 100 kbp is challenging and requires both specific methods and cloning hosts. The yeast Saccharomyces cerevisiae is considered as a host of choice for cloning and engineering whole or partial genomes from viruses, bacteria, and algae. Several methods are now available to perform these manipulations, each with its own limitations. In order to extend the range of yeast cloning strategies, a new approach combining two already described methods, Fusion cloning and CReasPy-Cloning, was developed. The CReasPy-Fusion method allows the simultaneous cloning and engineering of megabase-sized genomes in yeast by the fusion of bacterial cells with yeast spheroplasts carrying the CRISPR-Cas9 system. With this new approach, we demonstrate the feasibility of cloning and editing whole genomes from several Mycoplasma species belonging to different phylogenetic groups. We also show that CReasPy-Fusion allows the capture of large genome fragments with high efficacy, resulting in the successful cloning of selected loci in yeast. We finally identify bacterial nuclease encoding genes as barriers for CReasPy-Fusion by showing that their removal from the donor genome improves the cloning efficacy.

Malate-mediated carbon catabolite repression in Bacillus subtilis involves the HPrK/CcpA pathway.

Most organisms can choose their preferred carbon source from a mixture of nutrients. This process is called carbon catabolite repression. The Gram-positive bacterium Bacillus subtilis uses glucose as the preferred source of carbon and energy. Glucose-mediated catabolite repression is caused by binding of the CcpA transcription factor to the promoter regions of catabolic operons. CcpA binds DNA upon interaction with its cofactors HPr(Ser-P) and Crh(Ser-P). The formation of the cofactors is catalyzed by the metabolite-activated HPr kinase/phosphorylase. Recently, it has been shown that malate is a second preferred carbon source for B. subtilis that also causes catabolite repression. In this work, we addressed the mechanism by which malate causes catabolite repression. Genetic analyses revealed that malate-dependent catabolite repression requires CcpA and its cofactors. Moreover, we demonstrate that HPr(Ser-P) is present in malate-grown cells and that CcpA and HPr interact in vivo in the presence of glucose or malate but not in the absence of a repressing carbon source. The formation of the cofactor HPr(Ser-P) could be attributed to the concentrations of ATP and fructose 1,6-bisphosphate in cells growing with malate. Both metabolites are available at concentrations that are sufficient to stimulate HPr kinase activity. The adaptation of cells to environmental changes requires dynamic metabolic and regulatory adjustments. The repression strength of target promoters was similar to that observed in steady-state growth conditions, although it took somewhat longer to reach the second steady-state of expression when cells were shifted to malate.

Metabolic fluxes during strong carbon catabolite repression by malate in Bacillus subtilis.

Commonly glucose is considered to be the only preferred substrate in Bacillus subtilis whose presence represses utilization of other alternative substrates. Because recent data indicate that malate might be an exception, we quantify here the carbon source utilization hierarchy. Based on physiology and transcriptional data during co-utilization experiments with eight carbon substrates, we demonstrate that malate is a second preferred carbon source for B. subtilis, which is rapidly co-utilized with glucose and strongly represses the uptake of alternative substrates. From the different hierarchy and degree of catabolite repression exerted by glucose and malate, we conclude that both substrates might act through different molecular mechanisms. To obtain a quantitative and functional network view of how malate is (co)metabolized, we developed a novel approach to metabolic flux analysis that avoids error-prone, intuitive, and ad hoc decisions on (13)C rearrangements. In particular, we developed a rigorous approach for deriving reaction reversibilities by combining in vivo intracellular metabolite concentrations with a thermodynamic feasibility analysis. The thus-obtained analytical model of metabolism was then used for network-wide isotopologue balancing to estimate the intracellular fluxes. These (13)C-flux data revealed an extraordinarily high malate influx that is primarily catabolized via the gluconeogenic reactions and toward overflow metabolism. Furthermore, a considerable NADPH-producing malic enzyme flux is required to supply the biosynthetically required NADPH in the presence of malate. Co-utilization of glucose and malate resulted in a synergistic decrease of the respiratory tricarboxylic acid cycle flux.

Isotopologue profiling of Legionella pneumophila: role of serine and glucose as carbon substrates.

Legionella pneumophila (Lp) is commonly found in freshwater habitats but is also the causative agent of Legionnaires' disease when infecting humans. Although various virulence factors have been reported, little is known about the nutrition and the metabolism of the bacterium. Here, we report the application of isotopologue profiling for analyzing the metabolism of L. pneumophila. Cultures of Lp were supplied with [U-(13)C(3)]serine, [U-(13)C(6)]glucose, or [1,2-(13)C(2)]glucose. After growth, (13)C enrichments and isotopologue patterns of protein-derived amino acids and poly-3-hydroxybutyrate were determined by mass spectrometry and/or NMR spectroscopy. The labeling patterns detected in the experiment with [U-(13)C(3)]serine showed major carbon flux from serine to pyruvate and from pyruvate to acetyl-CoA, which serves as a precursor of poly-3-hydroxybutyrate or as a substrate of a complete citrate cycle with Si specificity of the citrate synthase. Minor carbon flux was observed between pyruvate and oxaloacetate/malate by carboxylation and decarboxylation, respectively. The apparent lack of label in Val, Ile, Leu, Pro, Phe, Met, Arg, and Tyr confirmed that L. pneumophila is auxotrophic for these amino acids. Experiments with [(13)C]glucose showed that the carbohydrate is also used as a substrate to feed the central metabolism. The specific labeling patterns due to [1,2-(13)C(2)]glucose identified the Entner-Doudoroff pathway as the predominant route for glucose utilization. In line with these observations, a mutant lacking glucose-6-phosphate dehydrogenase (Delta zwf) did not incorporate label from glucose at significant levels and was slowly outcompeted by the wild type strain in successive rounds of infection in Acanthamoeba castellanii, indicating the importance of this enzyme and of carbohydrate usage in general for the life cycle of Lp.

GamA is a eukaryotic-like glucoamylase responsible for glycogen- and starch-degrading activity of Legionella pneumophila.

Legionella pneumophila (Lp) is the causative agent of Legionnaires' disease, an atypical pneumonia. Lp is found in freshwater habitats and replicates within different protozoa (amoebae). It is known that Lp uses amino acids as primary energy and carbon sources for replication. However, very recently it was reported that Lp is able to metabolize also carbohydrates (glucose). Here, we present for the first time experimental evidence that the lpp0489 [gamA] gene encodes a eukaryotic-like glucoamylase (GamA) responsible for the glycogen- and starch-degrading activities of Lp. Although not essential for intra- and extracellular growth, we showed that GamA is expressed and active during intracellular replication in Acanthamoeba castellanii, suggesting that Lp is degrading glycogen during intracellular replication. Altogether, these findings indicate that Lp is indeed able to degrade exogenous polysaccharides and to utilize carbohydrates (glucose).

Absolute quantification of gene expression in individual bacterial cells using two-photon fluctuation microscopy.

Quantification of promoter activity or protein expression in gene regulatory networks is generally achieved via measurement of fluorescent protein (FP) intensity, which is related to the true FP concentration by an unknown scaling factor, thereby limiting analysis and interpretation. Here, using approaches originally developed for eukaryotic cells, we show that two-photon (2p) fluorescence fluctuation microscopy, specifically scanning number and brightness (sN&B) analysis, can be applied to determine the absolute concentrations of diffusing FPs in live bacterial cells. First, we demonstrate the validity of the approach, despite the small size of the bacteria, using the central pixels and spatial averaging. We established the lower detection limit at or below 75 nM (~3 molecules of FP/vol(ex)) and the upper detection limit at approximately 10 µM, which can be extended using intensity measurements. We found that the uncertainty inherent in our measurements (<5%) was smaller than the high cell-cell variations observed for stochastic leakage from FP fusions of the lac promoter in the repressed state or the 10 to 25% variation observed on induction. This demonstrates that a reliable and absolute measure of transcriptional noise can be made using our approach, which should make it particularly appropriate for the investigation of stochasticity in gene expression networks.

The Legionella pneumophila LetA/LetS two-component system exhibits rheostat-like behavior.

When confronted with metabolic stress, replicative Legionella pneumophila bacteria convert to resilient, infectious cells equipped for transmission. Differentiation is promoted by the LetA/LetS two-component system, which belongs to a family of signal-transducing proteins that employ a four-step phosphorelay to regulate gene expression. Histidine 307 of LetS was essential to switch on the transmission profile, but a threonine substitution at position 311 (T311M) suggested a rheostat-like function. The letS(T311M) bacteria resembled the wild type (WT) for some traits and letS null mutants for others, whereas they displayed intermediate levels of infectivity, cytotoxicity, and lysosome evasion. Although only 30 to 50% of letS(T311M) mutants became motile, flow cytometry determined that every cell eventually activated the flagellin promoter to WT levels, but expression was delayed. Likewise, letS(T311M) mutants exhibited delayed induction of RsmY and RsmZ, regulatory RNAs that relieve CsrA repression of transmission traits. Transcriptional profile analysis revealed that letS(T311M) mutants expressed the flagellar regulon and multiple other transmissive-phase loci at a higher cell density than the WT. Accordingly, we postulate that the letS(T311M) mutant may relay phosphate less efficiently than the WT LetS sensor protein, leading to sluggish gene expression and a variety of phenotypic profiles. Thus, as first described for BvgA/BvgS, rather than acting as on/off switches, this family of two-component systems exhibit rheostat activity that likely confers versatility as microbes adapt to fluctuating environments.

Two small ncRNAs jointly govern virulence and transmission in Legionella pneumophila.

To transit from intra- to extracellular environments, Legionella pneumophila differentiates from a replicative/non-virulent to a transmissive/virulent form using the two-component system LetA/LetS and the global repressor protein CsrA. While investigating how both regulators act co-ordinately we characterized two ncRNAs, RsmY and RsmZ, that link the LetA/LetS and CsrA regulatory networks. We demonstrate that LetA directly regulates their expression and show that RsmY and RsmZ are functional in Escherichia coli and are able to bind CsrA in vitro. Single mutants have no (ΔrsmY) or a little (ΔrsmZ) impact on virulence, but the ΔrsmYZ strain shows a drastic defect in intracellular growth in Acanthamoeba castellanii and THP-1 monocyte-derived macrophages. Analysis of the transcriptional programmes of the ΔletA, ΔletS and ΔrsmYZ strains revealed that the switch to the transmissive phase is partially blocked. One major difference between the ΔletA, ΔletS and ΔrsmYZ strains was that the latter synthesizes flagella. Taken together, LetA activates transcription of RsmY and RsmZ, which sequester CsrA and abolish its post-transcriptional repressive activity. However, the RsmYZ-CsrA pathway appears not to be the main or only regulatory circuit governing flagella synthesis. We suggest that rather RpoS and LetA, by influencing LetE and probably cyclic-di-GMP levels, regulate motility in L. pneumophila.

pBaSysBioII: an integrative plasmid generating gfp transcriptional fusions for high-throughput analysis of gene expression in Bacillus subtilis.

Plasmid pBaSysBioII was constructed for high-throughput analysis of gene expression in Bacillus subtilis. It is an integrative plasmid with a ligation-independent cloning (LIC) site, allowing the generation of transcriptional gfpmut3 fusions with desired promoters. Integration is by a Campbell-type event and is non-mutagenic, placing the fusion at the homologous chromosomal locus. Using phoA, murAA, gapB, ptsG and cggR promoters that are responsive to phosphate availability, growth rate and carbon source, we show that detailed profiles of promoter activity can be established, with responses to changing conditions being measurable within 1 min of the stimulus. This makes pBaSysBioII a highly versatile tool for real-time gene expression analysis in growing cells of B. subtilis.