Jilai Zhou

Atypical Glycolysis in Clostridium thermocellum

ABSTRACT Cofactor specificities of glycolytic enzymes in Clostridium thermocellum were studied with cellobiose-grown cells from batch cultures. Intracellular glucose was phosphorylated by glucokinase using GTP rather than ATP. Although phosphofructokinase typically uses ATP as a phosphoryl donor, we found only pyrophosphate (PPi)-linked activity. Phosphoglycerate kinase used both GDP and ADP as phosphoryl acceptors. In agreement with the absence of a pyruvate kinase sequence in the C. thermocellum genome, no activity of this enzyme could be detected. Also, the annotated pyruvate phosphate dikinase (ppdk) is not crucial for the generation of pyruvate from phosphoenolpyruvate (PEP), as deletion of the ppdk gene did not substantially change cellobiose fermentation. Instead pyruvate formation is likely to proceed via a malate shunt with GDP-linked PEP carboxykinase, NADH-linked malate dehydrogenase, and NADP-linked malic enzyme. High activities of these enzymes were detected in extracts of cellobiose-grown cells. Our results thus show that GTP is consumed while both GTP and ATP are produced in glycolysis of C. thermocellum. The requirement for PPi in this pathway can be satisfied only to a small extent by biosynthetic reactions, in contrast to what is generally assumed for a PPi-dependent glycolysis in anaerobic heterotrophs. Metabolic network analysis showed that most of the required PPi must be generated via ATP or GTP hydrolysis exclusive of that which happens during biosynthesis. Experimental proof for the necessity of an alternative mechanism of PPi generation was obtained by studying the glycolysis in washed-cell suspensions in which biosynthesis was absent. Under these conditions, cells still fermented cellobiose to ethanol.

Glycolysis without pyruvate kinase in Clostridium thermocellum

The metabolism of Clostridium thermocellum is notable in that it assimilates sugar via the EMP pathway but does not possess a pyruvate kinase enzyme. In the wild type organism, there are three proposed pathways for conversion of phosphoenolpyruvate (PEP) to pyruvate, which differ in their cofactor usage. One path uses pyruvate phosphate dikinase (PPDK), another pathway uses the combined activities of PEP carboxykinase (PEPCK) and oxaloacetate decarboxylase (ODC). Yet another pathway, the malate shunt, uses the combined activities of PEPCK, malate dehydrogenase and malic enzyme. First we showed that there is no flux through the ODC pathway by enzyme assay. Flux through the remaining two pathways (PPDK and malate shunt) was determined by dynamic 13C labeling. In the wild-type strain, the malate shunt accounts for about 33±2% of the flux to pyruvate, with the remainder via the PPDK pathway. Deletion of the ppdk gene resulted in a redirection of all pyruvate flux through the malate shunt. This provides the first direct evidence of the in-vivo function of the malate shunt.

Development of a core Clostridium thermocellum kinetic metabolic model consistent with multiple genetic perturbations

BackgroundClostridium thermocellum is a Gram-positive anaerobe with the ability to hydrolyze and metabolize cellulose into biofuels such as ethanol, making it an attractive candidate for consolidated bioprocessing (CBP). At present, metabolic engineering in C. thermocellum is hindered due to the incomplete description of its metabolic repertoire and regulation within a predictive metabolic model. Genome-scale metabolic (GSM) models augmented with kinetic models of metabolism have been shown to be effective at recapitulating perturbed metabolic phenotypes.ResultsIn this effort, we first update a second-generation genome-scale metabolic model (iCth446) for C. thermocellum by correcting cofactor dependencies, restoring elemental and charge balances, and updating GAM and NGAM values to improve phenotype predictions. The iCth446 model is next used as a scaffold to develop a core kinetic model (k-ctherm118) of the C. thermocellum central metabolism using the Ensemble Modeling (EM) paradigm. Model parameterization is carried out by simultaneously imposing fermentation yield data in lactate, malate, acetate, and hydrogen production pathways for 19 measured metabolites spanning a library of 19 distinct single and multiple gene knockout mutants along with 18 intracellular metabolite concentration data for a Δgldh mutant and ten experimentally measured Michaelis–Menten kinetic parameters.ConclusionsThe k-ctherm118 model captures significant metabolic changes caused by (1) nitrogen limitation leading to increased yields for lactate, pyruvate, and amino acids, and (2) ethanol stress causing an increase in intracellular sugar phosphate concentrations (~1.5-fold) due to upregulation of cofactor pools. Robustness analysis of k-ctherm118 alludes to the presence of a secondary activity of ketol-acid reductoisomerase and possible regulation by valine and/or leucine pool levels. In addition, cross-validation and robustness analysis allude to missing elements in k-ctherm118 and suggest additional experiments to improve kinetic model prediction fidelity. Overall, the study quantitatively assesses the advantages of EM-based kinetic modeling towards improved prediction of C. thermocellum metabolism and develops a predictive kinetic model which can be used to design biofuel-overproducing strains.

Determining the roles of the three alcohol dehydrogenases (AdhA, AdhB and AdhE) in Thermoanaerobacter ethanolicus during ethanol formation

Thermoanaerobacter ethanolicus is a promising candidate for biofuel production due to the broad range of substrates it can utilize and its high ethanol yield compared to other thermophilic bacteria, such as Clostridium thermocellum. Three alcohol dehydrogenases, AdhA, AdhB and AdhE, play key roles in ethanol formation. To study their physiological roles during ethanol formation, we deleted them separately and in combination. Previously, it has been thought that both AdhB and AdhE were bifunctional alcohol dehydrogenases. Here we show that AdhE has primarily acetyl-CoA reduction activity (ALDH) and almost no acetaldehyde reduction (ADH) activity, whereas AdhB has no ALDH activity and but high ADH activity. We found that AdhA and AdhB have similar patterns of activity. Interestingly, although deletion of both adhA and adhB reduced ethanol production, a single deletion of either one actually increased ethanol yields by 60–70%.