Kinetic modelling of the Zymomonas mobilis Entner–Doudoroff pathway: insights into control and functionality

Abstract

Zymomonas mobilis, an ethanol-producing bacterium, possesses the Entner-Doudoroff (E-D) pathway, pyruvate decarboxylase and two alcohol dehydrogenase isoenzymes for the fermentative production of ethanol and carbon dioxide from glucose. Using available kinetic parameters, we have developed a kinetic model that incorporates the enzymic reactions of the E-D pathway, both alcohol dehydrogenases, transport reactions and reactions related to ATP metabolism. After optimizing the reaction parameters within likely physiological limits, the resulting kinetic model was capable of simulating glycolysis in vivo and in cell-free extracts with good agreement with the fluxes and steady-state intermediate concentrations reported in previous experimental studies. In addition, the model is shown to be consistent with experimental results for the coupled response of ATP concentration and glycolytic flux to ATPase inhibition. Metabolic control analysis of the model revealed that the majority of flux control resides not inside, but outside the E-D pathway itself, predominantly in ATP consumption, demonstrating why past attempts to increase the glycolytic flux through overexpression of glycolytic enzymes have been unsuccessful. Co-response analysis indicates how homeostasis of ATP concentrations starts to deteriorate markedly at the highest glycolytic rates. This kinetic model has potential for application in Z. mobilis metabolic engineering and, since there are currently no E-D pathway models available in public databases, it can serve as a basis for the development of models for other micro-organisms possessing this type of glycolytic pathway.

Modeling of Zymomonas mobilis central metabolism for novel metabolic engineering strategies

“…Since the ED pathway itself is a major player in ANP and NAD(P)(H) turnover, this might lead to erroneous conclusions on the pathway kinetics and restrict the range of model application. The recent kinetic model by Rutkis et al (2013): (i) treated the cofactor levels as variables, making the interplay between adenylate cofactor levels and the pathway kinetics explicit, and (ii) introduced equilibrium constants in the kinetic equations to account for the reversibility of reactions more correctly. Metabolic control analysis (MCA) carried out with the model pointed to the ATP turnover as a major bottleneck, showing that the ATP consumption (dissipation) exerts a high level of control over glycolytic flux under various conditions (Rutkis et al, 2013).…”

“…The negative effects of overexpression apparently did not result from intrinsically negative flux control coefficients of the ED enzymes, but were attributable to the protein burden effect (Snoep et al, 1995), whereby overexpression of an enzyme with a small flux control coefficient caused reductions in the expression of other enzymes that have a greater influence on the flux. These results together with MCA studies on the kinetic model suggested that, due to the negligible flux control coefficients for the majority of reactions, single enzymes of the ED pathway should not be considered as prime targets for overexpression to increase the glycolytic flux in Z. mobilis (Rutkis et al, 2013). The calculated effects of several glycolytic enzyme ( gap, pgk, pgm ) and both alcohol dehydrogenase isoenzyme( adhA and adhB ) overexpression, in accordance with previous experimental observations, predicted little or no increase of glycolytic flux (Arfman et al, 1992; Snoep et al, 1995).…”

“…The calculated effects of several glycolytic enzyme ( gap, pgk, pgm ) and both alcohol dehydrogenase isoenzyme( adhA and adhB ) overexpression, in accordance with previous experimental observations, predicted little or no increase of glycolytic flux (Arfman et al, 1992; Snoep et al, 1995). The somewhat higher flux control coefficient for the pyruvate decarboxylase ( pdc ) reaction suggested that overexpression of this enzyme by more than 3-fold, might lead to an increase of glycolytic flux of almost 23% (Rutkis et al, 2013). However, quite the opposite was observed experimentally: approximately 10-fold increase of pdc was shown to slow down glycolysis by up to 25%, thereby implying that the protein burden might be a serious side effect of catabolic enzyme overexpression in Z. mobilis .…”

Elucidation of Zymomonas mobilis physiology and stress responses by quantitative proteomics and transcriptomics

“…The genome sequences for strains ZM4, NCIMB 11163, 10988, 29291 and 29292 have been determined (Seo et al, 2005; Kouvelis et al, 2009, 2011; Pappas et al, 2011; Desiniotis et al, 2012), and the ZM4 genome annotation was improved recently (Yang et al, 2009a). Genome-scale in silico metabolic modeling analysis have been reported (Lee et al, 2010; Widiastuti et al, 2011; Rutkis et al, 2013) and recombinant strains have been engineered to express and secret cellulase (Linger et al, 2010) or ferment hexoses and pentose sugars such as xylose and arabinose (Zhang et al, 1995; Deanda et al, 1996). …”

Studies on The Hungate technique for ethanol fermentation of algae Spirogyra hyalina using Saccharomyces cerevisiae

“…S. cerevisiae uses carbon sources through the Embden-Meyerhof pathway, in which 2 moles of ATP are produced per mole of glucose [28,29]. Meanwhile, Z. mobilis can use glucose, fructose or sucrose as the carbon source via the Entner-Doudoroff metabolic pathway [11,30,31], which produces only 1 mole of ATP per mole of glucose or fructose, so Z. mobilis uses sugar at a higher rate in order to produce enough energy for growth. Because only 1 mole of ATP is produced per mole of sugar, Z. mobilis transforms glucose quickly to provide ATP.…”