In VivoThermodynamic Analysis of Glycolysis in Clostridium thermocellum and Thermoanaerobacterium saccharolyticum Using¹³C and²H Tracers

Abstract

Clostridium thermocellum and Thermoanaerobacterium saccharolyticum are thermophilic anaerobic bacteria with complementary metabolic capabilities that utilize distinct glycolytic pathways for the conversion of cellulosic sugars to biofuels. We integrated quantitative metabolomics with 2H and 13C metabolic flux analysis to investigate the in vivo reversibility and thermodynamics of the central metabolic networks of these two microbes. We found that the glycolytic pathway in C. thermocellum operates remarkably close to thermodynamic equilibrium, with an overall drop in Gibbs free energy 5-fold lower than that of T. saccharolyticum or anaerobically grown Escherichia coli. The limited thermodynamic driving force of glycolysis in C. thermocellum could be attributed in large part to the small free energy of the phosphofructokinase reaction producing fructose bisphosphate. The ethanol fermentation pathway was also substantially more reversible in C. thermocellum than in T. saccharolyticum. These observations help explain the comparatively low ethanol titers of C. thermocellum and suggest engineering interventions that can be used to increase its ethanol productivity and glycolytic rate. In addition to thermodynamic analysis, we used our isotope tracer data to reconstruct the T. saccharolyticum central metabolic network, revealing exclusive use of the Embden-Meyerhof-Parnas (EMP) pathway for glycolysis, a bifurcated tricarboxylic acid (TCA) cycle, and a sedoheptulose bisphosphate bypass active within the pentose phosphate pathway. IMPORTANCE Thermodynamics constitutes a key determinant of flux and enzyme efficiency in metabolic networks. Here, we provide new insights into the divergent thermodynamics of the glycolytic pathways of C. thermocellum and T. saccharolyticum, two industrially relevant thermophilic bacteria whose metabolism still is not well understood. We report that while the glycolytic pathway in T. saccharolyticum is as thermodynamically favorable as that found in model organisms, such as E. coli or Saccharomyces cerevisiae, the glycolytic pathway of C. thermocellum operates near equilibrium. The use of a near-equilibrium glycolytic pathway, with potentially increased ATP yield, by this cellulolytic microbe may represent an evolutionary adaptation to growth on cellulose, but it has the drawback of being highly susceptible to product feedback inhibition. The results of this study will facilitate future engineering of high-performance strains capable of transforming cellulosic biomass to biofuels at high yields and titers.

A moonlighting role for enzymes of glycolysis in the co-localization of mitochondria and chloroplasts

“…The metabolic intermediates are not believed to be toxic or unstable and their leakage impacting the cell is also unlikely. Moreover, looking at the in vivo thermodynamics of these reactions in other systems 49 , data are not available to estimate these in plants, suggesting that there is likely no thermodynamic advantage to metabolon formation. Thus, despite careful consideration, the exact purpose of the metabolite channel currently remains opaque and will require further study to clarify.…”

Metabolic Fluxes of Nitrogen and Pyrophosphate in Chemostat Cultures of Clostridium thermocellum and Thermoanaerobacterium saccharolyticum

“…In C. thermocellum the conversion of glucose-6-phosphate to pyruvate is fully reversible ( 28 ) due to the presence of PP i -PFK and PPDK ( Table 1 ). The malate shunt ( Fig.…”

“…The reversibility of the PPi-linked glycolysis in C. thermocellum, as proven by labeling studies (28) combined with the absence of irreversible PPi hydrolysis results in a reversible charging of transfer RNA (Fig. 5).…”

Modular Dynamic Biomolecular Modelling with Bond Graphs: The Unification of Stoichiometry, Thermodynamics, Kinetics and Data

“…In recent times, such data are becoming more readily available; species concentrations can be obtained from metabolomics data, and tracer experiments involving 13 C and 2 H have been used to infer both fluxomics data for reaction flows [70,71] and thermodynamic data for reaction potentials [70,72,73]. In the following examples, we make use of the dataset obtained by Park et al [70] to infer the thermodynamic parameters using a relatively fast quadratic programming (QP) algorithm.…”