Large-scale 13C-flux analysis reveals distinct transcriptional control of respiratory and fermentative metabolism in Escherichia coli

The authors analyze the role transcription plays in regulating bacterial metabolic flux. Of 91 transcriptional regulators studied, 2/3 affect absolute fluxes, but only a small number of regulators control the partitioning of flux between different metabolic pathways

Distinct transcriptional regulation of the two Escherichia coli transhydrogenases PntAB and UdhA

Transhydrogenases catalyse interconversion of the redox cofactors NADH and NADPH, thereby conveying metabolic flexibility to balance catabolic NADPH formation with anabolic or stress-based consumption of NADPH. Escherichia coli is one of the very few microbes that possesses two isoforms: the membrane-bound, proton-translocating transhydrogenase PntAB and the cytosolic, energy-independent transhydrogenase UdhA. Despite their physiological relevance, we have only fragmented information on their regulation and the signals coordinating their counteracting activities. Here we investigated PntAB and UdhA regulation by studying transcriptional responses to environmental and genetic perturbations. By testing pntAB and udhA GFP reporter constructs in the background of WT E. coli and 62 transcription factor mutants during growth on different carbon sources, we show distinct transcriptional regulation of the two transhydrogenase promoters. Surprisingly, transhydrogenase regulation was independent of the actual catabolic overproduction or underproduction of NADPH but responded to nutrient levels and growth rate in a fashion that matches the cellular need for the redox cofactors NADPH and/or NADH. Specifically, the identified transcription factors Lrp, ArgP and Crp link transhydrogenase expression to particular amino acids and intracellular concentrations of cAMP. The overall identified set of regulators establishes a primarily biosynthetic role for PntAB and link UdhA to respiration

Unraveling the inhibitory effects of acetate on ethanol production in CEN.PK

In this study, we used the ORACLE (Optimization and Risk Analysis of Complex Living Entities)[1] framework to study the impact of extracellular acetic acid on the S. cerevisiae metabolism with the aim to improve ethanol production in the presence of this inhibitor found in significant concentrations in lignocellulosic hydrolysates. First, we derived a consistently reduced core model (279 metabolites and 382 reactions) of S. cerevisiae from the iMM904 genome scale reconstruction. We integrated thermodynamic and experimentally measured information about the metabolite concentrations and reaction fluxes, to identify thermodynamically feasible operational configurations of the network under different experimental conditions using the novel Flux Directionality Profile Analysis (FDPA) technique[2,3]. We then computed a population of stoichiometrically, thermodynamically, kinetically and physiologically consistent log-linear kinetics models. These models were used to (i) explore the flexibility and robustness of the operational states; (ii) identify the differences of the flux profiles for different doses of acetate during ethanol production; and (iii) derive optimal strategies for improvement of the ethanol production under these physiological conditions