Fluctuations in intracellular molecule abundance can lead to distinct, coexisting phenotypes in isogenic populations. Although metabolism continuously adapts to unpredictable environmental changes, and although bistability was found in certain substrate-uptake pathways, central carbon metabolism is thought to operate deterministically. Here, we combine experiment and theory to demonstrate that a clonal Escherichia coli population splits into two stochastically generated phenotypic subpopulations after glucose-gluconeogenic substrate shifts. Most cells refrain from growth, entering a dormant persister state that manifests as a lag phase in the population growth curve. The subpopulation-generating mechanism resides at the metabolic core, overarches the metabolic and transcriptional networks, and only allows the growth of cells initially achieving sufficiently high gluconeogenic flux. Thus, central metabolism does not ensure the gluconeogenic growth of individual cells, but uses a population-level adaptation resulting in responsive diversification upon nutrient changes.

We present a large-scale differential equation model of E. coli's central metabolism and its enzymatic, transcriptional, and posttranslational regulation. This model reproduces E. coli's known physiological behavior.We found that the interplay of known interactions in E. coli's central metabolism can indirectly recognize the presence of extracellular carbon sources through measuring intracellular metabolic flux patterns.We found that E. coli's system-level adaptations between glycolytic and gluconeogenic carbon sources are realized on the molecular level by global feedback architectures that overarch the enzymatic and transcriptional regulatory layers.We found that the capability for closed-loop self-regulation can emerge within metabolism itself and therefore, metabolic operation may adapt itself autonomously to changing carbon sources (not requiring upstream sensing and signaling).

In this study, full-genome DNA microarrays based on the sequence of Staphylococcus aureus N315 were used to compare the transcriptome of a clinical S. aureus strain with a normal phenotype to that of its isogenic mutant with a stable small-colony-variant (SCV) phenotype (hemB::ermB). In addition to standard statistical analyses, systems biology advances were applied to identify reporter metabolites and to achieve a more detailed survey of genome-wide expression differences between the hemB mutant and its parental strain. Genes of enzymes involved in glycolytic and fermentative pathways were found to be up-regulated in the hemB mutant. Furthermore, our analyses allowed identification of additional differences between the normal-phenotype S. aureus and the SCV, most of which were related to metabolism. Profound differences were identified especially in purine biosynthesis as well as in arginine and proline metabolism. Of particular interest, a hypothetical gene of the Crp/Fnr family (SA2424) that is part of the arginine-deiminase (AD) pathway, whose homologue in Streptococcus suis is assumed to be involved in intracellular persistence, showed significantly increased transcription in the hemB mutant. The hemB mutant potentially uses the up-regulated AD pathway to produce ATP or (through ammonia production) to counteract the acidic environment that prevails intracellularly. Moreover, genes involved in capsular polysaccharide and cell wall synthesis were found to be significantly up-regulated in the hemB mutant and therefore potentially responsible for the changed cell morphology of SCVs. In conclusion, the identified differences may be responsible for the SCV phenotype and its association with chronic and persistent infections.

Background: Synthesis of the Staphylococcus aureus peptidoglycan pentaglycine interpeptide bridge is catalyzed by the nonribosomal peptidyl transferases FemX, FemA and FemB. Inactivation of the femAB operon reduces the interpeptide to a monoglycine, leading to a poorly crosslinked peptidoglycan. femAB mutants show a reduced growth rate and are hypersusceptible to virtually all antibiotics, including methicillin, making FemAB a potential target to restore β-lactam susceptibility in methicillin-resistant S. aureus (MRSA). Cis-complementation with wild type femAB only restores synthesis of the pentaglycine interpeptide and methicillin resistance, but the growth rate remains low. This study characterizes the adaptations that ensured survival of the cells after femAB inactivation.

Here, we present the so-called divide-and-conquer approach--a strategy to analyze underdetermined biochemical models. The approach draws on steady state omics measurement data and exploits a decomposition of the global estimation problem into independent subproblems. The solutions to these subproblems are joined to the complete space of global optima, which can be easily analyzed. We derive the conditions at which the decomposition occurs, outline strategies to fulfill these conditions and--using an example model--illustrate how the approach uncovers the most important parameters and suggests targeted experiments without knowing the exact parameter values.