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Resource Balance Analysis (RBA) is a computational method based on resource allocation, which performs accurate quantitative predictions of whole-cell states (i.e. growth rate, metabolic fluxes, abundances of molecular machines including enzymes) across growth conditions. We present an integrated workflow of RBA together with the Python package RBApy. RBApy builds bacterial RBA models from annotated genome-scale metabolic models by adding descriptions of cellular processes relevant for growth and maintenance. The package includes functions for model simulation and calibration and for interfacing to Escher maps and Proteomaps for visualization. We demonstrate that RBApy faithfully reproduces results obtained by a hand-curated and experimentally validated RBA model for Bacillus subtilis. We also present a calibrated RBA model of Escherichia coli generated from scratch, which obtained excellent fits to measured flux values and enzyme abundances. RBApy makes whole-cell modelling accessible for a wide range of bacterial wild-type and engineered strains, as illustrated with a CO 2 -fixing Escherichia coli strain. AVAILABILITY: RBApy is available at /https://github.com/SysBioInra/RBApy, under the licence GNU GPL version 3, and runs on Linux, Mac and Windows distributions., (Copyright © 2019 International Metabolic Engineering Society. Published by Elsevier Inc. All rights reserved.)

Central to the functioning of any living cell, the metabolic network is a complex network of biochemical reactions. It may also be viewed as an elaborate production system, integrating a diversity of internal and external signals in order to efficiently produce the energy and the biochemical precursors to ensure all cellular functions. Even in simple organisms like bacteria, it shows a striking level of coordination, adapting to very different growth media. Constraint-based models constitute an efficient mathematical framework to compute optimal metabolic configurations, at the scale of a whole genome. Combining the constraint-based approach "Resource Balance Analysis" with combinatorial optimization techniques, we propose a general method to explore these configurations, based on the inference of logical rules governing the activation of metabolic fluxes in response to diverse extracellular media. Using the concept of partial Boolean functions, we notably introduce a novel tractable algorithm to infer monotone Boolean functions on a minimal support. Monotonicity seems particularly relevant in this context, since the orderliness exhibited by the metabolic network's dynamical behavior is expected to give rise to relatively simple rules. First results are promising, as the application of the method on Bacillus subtilis central carbon metabolism allows to recover known regulations as well as to investigate lesser known parts of the global regulatory network.

How cells control their shape and size is a long-standing question in cell biology. Many rod-shaped bacteria elongate their sidewalls by the action of cell wall synthesizing machineries that are associated to actin-like MreB cortical patches. However, little is known about how elongation is regulated to enable varied growth rates and sizes. Here we use total internal reflection fluorescence microscopy and single-particle tracking to visualize MreB isoforms, as a proxy for cell wall synthesis, in Bacillus subtilis and Escherichia coli cells growing in different media and during nutrient upshift. We find that these two model organisms appear to use orthogonal strategies to adapt to growth regime variations: B. subtilis regulates MreB patch speed, while E. coli may mainly regulate the production capacity of MreB-associated cell wall machineries. We present numerical models that link MreB-mediated sidewall synthesis and cell elongation, and argue that the distinct regulatory mechanism employed might reflect the different cell wall integrity constraints in Gram-positive and Gram-negative bacteria.

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., (© 2016 The Authors. Published under the terms of the CC BY 4.0 license.)

Systems biology based on high quality absolute quantification data, which are mandatory for the simulation of biological processes, successively becomes important for life sciences. We provide protein concentrations on the level of molecules per cell for more than 700 cytosolic proteins of the Gram-positive model bacterium Bacillus subtilis during adaptation to changing growth conditions. As glucose starvation and heat stress are typical challenges in B. subtilis' natural environment and induce both, specific and general stress and starvation proteins, these conditions were selected as models for starvation and stress responses. Analyzing samples from numerous time points along the bacterial growth curve yielded reliable and physiologically relevant data suitable for modeling of cellular regulation under altered growth conditions. The analysis of the adaptational processes based on protein molecules per cell revealed stress-specific modulation of general adaptive responses in terms of protein amount and proteome composition. Furthermore, analysis of protein repartition during glucose starvation showed that biomass seems to be redistributed from proteins involved in amino acid biosynthesis to enzymes of the central carbon metabolism. In contrast, during heat stress most resources of the cell, namely those from amino acid synthetic pathways, are used to increase the amount of chaperones and proteases. Analysis of dynamical aspects of protein synthesis during heat stress adaptation revealed, that these proteins make up almost 30% of the protein mass accumulated during early phases of this stress., (© 2014 by The American Society for Biochemistry and Molecular Biology, Inc.)

In the growing field of systems biology, the knowledge of protein concentrations is highly required to truly understand metabolic and adaptational networks within the cells. Therefore we established a workflow relying on long chromatographic separation and mass spectrometric analysis by data independent, parallel fragmentation of all precursor ions at the same time (LC/MS(E)). By prevention of discrimination of co-eluting low and high abundant peptides a high average sequence coverage of 40% could be achieved, resulting in identification of almost half of the predicted cytosolic proteome of the Gram-positive model organism Bacillus subtilis (>1,050 proteins). Absolute quantification was achieved by correlation of average MS signal intensities of the three most intense peptides of a protein to the signal intensity of a spiked standard protein digest. Comparative analysis with heavily labeled peptides (AQUA approach) showed the use of only one standard digest is sufficient for global quantification. The quantification results covered almost four orders of magnitude, ranging roughly from 10 to 150,000 copies per cell. To prove this method for its biological relevance selected physiological aspects of B. subtilis cells grown under conditions requiring either amino acid synthesis or alternatively amino acid degradation were analyzed. This allowed both in particular the validation of the adjustment of protein levels by known regulatory events and in general a perspective of new insights into bacterial physiology. Within new findings the analysis of "protein costs" of cellular processes is extremely important. Such a comprehensive and detailed characterization of cellular protein concentrations based on data independent, parallel fragmentation in liquid chromatography/mass spectrometry (LC/MS(E)) data has been performed for the first time and should pave the way for future comprehensive quantitative characterization of microorganisms as physiological entities.

Bacteria adapt to environmental stimuli by adjusting their transcriptomes in a complex manner, the full potential of which has yet to be established for any individual bacterial species. Here, we report the transcriptomes of Bacillus subtilis exposed to a wide range of environmental and nutritional conditions that the organism might encounter in nature. We comprehensively mapped transcription units (TUs) and grouped 2935 promoters into regulons controlled by various RNA polymerase sigma factors, accounting for ~66% of the observed variance in transcriptional activity. This global classification of promoters and detailed description of TUs revealed that a large proportion of the detected antisense RNAs arose from potentially spurious transcription initiation by alternative sigma factors and from imperfect control of transcription termination.

We have generated a protein-protein interaction network in Bacillus subtilis focused on several essential cellular processes such as cell division, cell responses to various stresses, the bacterial cytoskeleton, DNA replication and chromosome maintenance by careful application of the yeast two-hybrid approach. This network, composed of 793 interactions linking 287 proteins with an average connectivity of five interactions per protein, represents a valuable resource for future functional analyses. A striking feature of the network is a group of highly connected hubs (GoH) linking many different cellular processes. Most of the proteins of the GoH have unknown functions and are associated to the membrane. By the integration of available knowledge, in particular of transcriptome data sets, the GoH was decomposed into subgroups of party hubs corresponding to protein complexes or regulatory pathways expressed under different conditions. At a global level, the GoH might function as a very robust group of date hubs having partially redundant functions to integrate information from the different cellular pathways. Our analyses also provide a rational way to study the highly redundant functions of the GoH by a genetic approach., (Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

The peptidoglycan cell wall and the actin-like MreB cytoskeleton are major determinants of cell shape in rod-shaped bacteria. The prevailing model postulates that helical, membrane-associated MreB filaments organize elongation-specific peptidoglycan-synthesizing complexes along sidewalls. We used total internal reflection fluorescence microscopy to visualize the dynamic relation between MreB isoforms and cell wall synthesis in live Bacillus subtilis cells. During exponential growth, MreB proteins did not form helical structures. Instead, together with other morphogenetic factors, they assembled into discrete patches that moved processively along peripheral tracks perpendicular to the cell axis. Patch motility was largely powered by cell wall synthesis, and MreB polymers restricted diffusion of patch components in the membrane and oriented patch motion.

Background: Few genome-scale models of organisms focus on the regulatory networks and none of them integrates all known levels of regulation. In particular, the regulations involving metabolite pools are often neglected. However, metabolite pools link the metabolic to the genetic network through genetic regulations, including those involving effectors of transcription factors or riboswitches. Consequently, they play pivotal roles in the global organization of the genetic and metabolic regulatory networks., Results: We report the manually curated reconstruction of the genetic and metabolic regulatory networks of the central metabolism of Bacillus subtilis (transcriptional, translational and post-translational regulations and modulation of enzymatic activities). We provide a systematic graphic representation of regulations of each metabolic pathway based on the central role of metabolites in regulation. We show that the complex regulatory network of B. subtilis can be decomposed as sets of locally regulated modules, which are coordinated by global regulators., Conclusion: This work reveals the strong involvement of metabolite pools in the general regulation of the metabolic network. Breaking the metabolic network down into modules based on the control of metabolite pools reveals the functional organization of the genetic and metabolic regulatory networks of B. subtilis.