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

Abstract

Transhydrogenases catalyse interconversion of the redox cofactors NADH and NADPH, thereby conveying metabolic flexibility to balance catabolic NADPH formation with anabolic or stressbased 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.

Few regulatory metabolites coordinate expression of central metabolic genes in Escherichia coli

“…These findings concur with previous studies highlighting the importance of Cra in regulating the switch between glycolysis and gluconeogenesis (Ramseier, 1996;Kotte et al, 2014) and for the sensing of glycolytic flux (Kotte et al, 2010;Kochanowski et al, 2013). Similarly, our results are consistent with the demonstrated importance of Crp for regulating TCA cycle fluxes (Nanchen et al, 2008;Haverkorn van Rijsewijk et al, 2011) and carbon utilization (Kaplan et al, 2008;Aidelberg et al, 2014). Notably, F1P and FBP affected different sets of promoters more strongly through the same transcription factor Cra.…”

2 H/ 1 H variation in microbial lipids is controlled by NADPH metabolism

“…Combining these data, our model can account for the 2 H-enriched lipids only with an overproduction of NADPH in the range of ∼ 75%. Indeed, overproduction of NADPH by E. coli is suggested during growth on acetate (40,52), which is consistent with our prediction. Nevertheless, overproduction of NADPH by 75% seems to be slightly excessive and probably indicates that other 2 H-enrichment processes might be important.…”

“…Modeling lipid δ 2 H values for both carbon sources (fructose and glucose) predicts a 22‰ lower δ 2 H value for fructose, which is in excellent agreement with our culture data. Fluxes of gluconate catabolism in E. coli were found to be essentially opposite to glucose catabolism, with high ED pathway fluxes and almost exclusive production of NADPH by 6PGDH, ICDH, and PntAB due to NADPH underproduction (51,52). Zhang et al (10) measured lipid/water fractionation of −123‰ in E. coli during growth on gluconate, a 2 H/ 1 H fractionation that our model accurately predicts with an NADPH underproduction of ∼ 30%.…”

ScalaFlux: A scalable approach to quantify fluxes in metabolic subnetworks

“…Metabolic flux analysis (MFA) with stable isotope tracers, typically a 13 C-labeled carbon source, allows intracellular fluxes to be quantified in a wide range of organisms and is now a major tool in the fields of biotechnology [1][2][3], systems biology [4][5][6] and medicine [7,8]. Current approaches rely on isotopic models to simulate tracer propagation through metabolic networks in (pseudo) steady-state condition [1,[9][10][11][12][13][14].…”

“…Overall, the modeling requirement that the tracer has to be propagated right from the extracellular nutrient limits the application of flux measurements to pathways closely related to the label input. The vast majority of existing 13 C-flux studies focus indeed on central carbon metabolism, and most 15 N-flux studies focus on the nitrogen assimilation network [1,4,6,16,17]. Alternative 13 C-MFA frameworks such as metabolic flux ratio analysis [18,19] and kinetic flux profiling [16] were developed, but they are far to be generic since they are limited to the analysis of a few topological motifs based exclusively on mass spectrometry (MS) data.…”