Effects Of Some Single-gene Knockout Of The Central Metabolic Enzymes On The Metabolism In Escherichia Coli

The carrying out of Human Genome Project promoted the accomplishment of sequencing the Escherichia coli genome, which establishes the genetic basis for the construction of E. coli mutants and for the study on the metabolism of E. coli. In the present study, IpdA, poxB, sucA and sucC gene knockout mutants were selected. Among these four genes, the former two encode the enzymes connecting the glycolysis and the TCA cycle, and the latter two encode the TCA cycle enzymes. The effects of these four single-gene knockout mutations on the metabolism in E. coli were investigated based on the growth characteristics, gene expressions, enzyme activities, intracellular metabolite concentrations and metabolic flux analysis by ¹³C-labeling experiments.Both pyruvate dehydrogenase complex and α-ketoglutarate dehydrogenase were deficient in the IpdA gene knockout E. coli. The phenotype of IpdA mutant was significantly different from that of the wild type strain. In the LB medium, during the glucose-consuming phase, compared to the wild type strain, the glucose uptake rate and the cell growth rate of the IpdA mutant were lower. A large amount of pyruvate was produced in the IpdA mutant, which strongly reduced the biomass yield in this phase. During the pyruvate-consuming phase, D-lactate, acetate, succinate and L-glutamate were produced in the mutant. Based on the enzyme activities and intracellular metabolite concentrations, pyruvate was considered to be assimilated by the combined reactions through pyruvate oxidase and phosphoenolpyruvate synthase-phosphoenolpyruvate carboxylase. Pyruvate was converted to acetate by pyruvate oxidase, and then formed acetyl-CoA through the reactions catalyzed by acetyl-CoA synthetase and acetate kinase-phosphoacetyltransferase to support the cell growth of E. coli. The increase in the pyruvate concentration enhances the production of lactate via gene expression as well as enzyme activity in the IpdA mutant. On the other hand, the interruption of TCA cycle activates the glyoxylate shunt. The high L-glutamate production was caused by the accumulation of its precursor such asα-ketoglutarate.poxB gene knockout also reduced the glucose uptake rate, cell growth rate and the biomass yield of E. coli, while enhanced the oxygen consumption and carbon dioxide evolution rate. The deficiency of pyruvate oxidase did not cause the obvious accumulation of pyruvate, which indicated that under aerobic condition, the pyruvate metabolism mainly depends on the pyruvate dehydrogenase complex, and pyruvate oxidase does not play the key role. Enzyme results showed that the deficiency of pyruvate oxidase affected the enzyme activities in the central metabolic pathways. In the synthetic medium, although glucokinase activity increased, the flux through glycolysis was reduced due to the down-regulation of the other glycolytic enzymes such as 6-phosphofructosekinase and fructose biphosphate aldolase in the poxB mutant. In the LB medium, TCA cycle enzymes such as citrate synthase and malate dehydrogenase were repressed in the poxB mutant. The pyruvate oxidase mutation also resulted in the activation of glucose-6-phosphate dehydrogenase and acetyl-CoA synthetase. All these results suggest that pyruvate oxidase is not only a stationary-phase enzyme as previously known and that the removal of poxB gene affects the central metabolism on the enzyme level in E. coli. Especially, pyruvate oxidase is an essential enzyme in the lpdA mutant. Once pyruvate oxidase was inhibited in the ipdA mutant, cell growth stopped.sucA and sucC are located in the same operon sucABCD, and both of them encode TCA cycle enzymes. suc A encodes El subunit for α-ketoglutarate dehydrogenase and sucC encodes a subunit for succinyl-coA synthetase. Although both genes have similarities, the effects of sucA or sucC gene knockout on the metabolism in E. coli are largely different. The results showed that not all the TCA enzyme-deficiency affected the cell growth rate. sucA gene knockout significantly reduced the cell growth rate, while the sucC gene knockout almost did not affect the cell growth. The deficiency of α-ketoglutarate dehydrogenase in the sucA mutant caused the accumulation of α-ketoglutarate, which was further converted into L-glutamate. Although, succinyl-coA synthetase catalyzes the downstream reaction of α-ketoglutarate dehydrogenase, the accumulation of neither α-ketoglutarate nor L-glutamate was foundin the sucC mutant.The glucose uptake rate and the acetate production were decreased in the sucA mutant, and the acetate was utilized by the suc A mutant. The down-regulation of acetate kinase was consistent with the reduction of acetate production, and the down-regulation of glycolytic enzymes revealed that the decreased glycolytic flux led to the lower acetate production. The activation of the glyoxylate shunt enabled the suc A mutant to utilize the acetate. In contrast, the glucose uptake rate was not much affected in the sucC mutant. A significantly higher amount of acetate was produced, and it was not utilized in sucC mutant. The enzyme results showed that the glycolytic enzyme activities were down-regulated, and the increased acetate kinase activity catalyzed the acetate over-production. A large amount of acetate did not induce the glyoxylate shunt, which explained why the acetate was not utilized in the sucC mutant. In continuous cultivation, the gene expression results indicated that the global regulatory genes such as fadR and iclR were slightly down-regulated in the sucA mutant, which enhanced the expression of ace A gene and caused the up-regulation of the isocitrate lyase activity in the sucA mutant, while fadR and iclR of sucC mutant changed little and no isocitrate lyase activation was observed for sucC mutant. Some other global regulatory genes such as arcA and fnr- genes were down-regulated in both mutants, which caused some of the TCA cycle genes to be up-regulated.The interruption of the TCA cycle affected the redox balance in the sucA and sucC mutants. The concentrations of oxidative NAD⁺ and NADP⁺ were increased. The accumulations of energetic substance ATP in both mutants were detected. For the sucC mutant, the acetate production pathway is also a main ATP production pathway, so the production of the large amount acetate was accompanied by the ATP production. For the sucA mutant, the ATP production pathway is obviously not the acetate production reaction due to the lower acetate production. Oxidative pentose phosphate pathway was activated in the sucA mutant, and the NADPH produced in the pathway could be converted into ATP through the electron transport chain. Therefore, the phenotypes of the ATP accumulation were similar in both sucA and sucC mutants, but the metabolic mechanisms were totally different.The effect of the gene knockout on the intracellular metabolic flux distributions was investigated based on ¹H-¹³C NMR spectra and GC-MS signals obtained from ¹³C-labeling experiments using the mixture of [U-¹³C] glucose, [1-¹³C] glucose, and naturally labeled glucose. The main idea of the labeling experiments is to perform isotopomer balance on carbon atoms in order to track the fate of labeled carbon atoms from the substrate. Isotopomer balance based on a set of metabolic flux distributions enables us to determine the isotopomer distributions of the intracellular metabolites in the central metabolic network. Since the isotopomer distributions of amino acids can be inferred from the isotopomer distributions of their corresponding precursors, the NMR spectra and GC-MS signals for the amino acids can then be simulated. During the simulation of NMR spectra and GC-MS signals using isotopomer balance, three types of correction were made to take into account the effects of natural abundance, non-steady state condition, and skewing effect. The fluxes were obtained by minimizing the weighted residuals between the simulated and measured NMR spectra and GC-MS signals. Two-stage optimization strategy was implemented, where the first stage is a global search using a constrained-based genetic algorithm, and the second stage is a local search using local optimization function in the MATLAB toolbox or the Powell's quadratically convergent method. A total of 100 data sets were generated by addition of normally distributed to the measurement data for the statistical analysis.In the present study, in the continuous cultivation, the calculation method of the metabolic flux distributions for the IpdA and sucA mutants was developed as a model, and the metabolic flux distribution results were consistent with the results of growth characteristics, gene expressions, enzyme activities and intracellular metabolite concentrations.