Title Deletion of genes encoding cytochrome oxidases and quinol monooxygenase blocks the aerobic-anaerobic shift in Escherichia coli K-12 MG1655.
Year of Publication 2010
Authors V.A. Portnoy; D.A. Scott; N.E. Lewis; Y. Tarasova; A.L. Osterman; B.Ø. Palsson
Journal PLoS Comput Biol
Abstract The constitutive activation of the anoxic redox control transcriptional regulator (ArcA) in Escherichia coli during aerobic growth, with the consequent production of a strain that exhibits anaerobic physiology even in the presence of air, is reported in this work. Removal of three terminal cytochrome oxidase genes (cydAB, cyoABCD, and cbdAB) and a quinol monooxygenase gene (ygiN) from the E. coli K-12 MG1655 genome resulted in the activation of ArcA aerobically. These mutations resulted in reduction of the oxygen uptake rate by nearly 98% and production of d-lactate as a sole by-product under oxic and anoxic conditions. The knockout strain exhibited nearly identical physiological behaviors under both conditions, suggesting that the mutations resulted in significant metabolic and regulatory perturbations. In order to fully understand the physiology of this mutant and to identify underlying metabolic and regulatory reasons that prevent the transition from an aerobic to an anaerobic phenotype, we utilized whole-genome transcriptome analysis, (13)C tracing experiments, and physiological characterization. Our analysis showed that the deletions resulted in the activation of anaerobic respiration under oxic conditions and a consequential shift in the content of the quinone pool from ubiquinones to menaquinones. An increase in menaquinone concentration resulted in the activation of ArcA. The activation of the ArcB/ArcA regulatory system led to a major shift in the metabolic flux distribution through the central metabolism of the mutant strain. Flux analysis indicated that the mutant strain had undetectable fluxes around the tricarboxylic acid (TCA) cycle and elevated flux through glycolysis and anaplerotic input to oxaloacetate. Flux and transcriptomics data were highly correlated and showed similar patterns.
URL PubMed