Download or read book Metabolic Modeling of Clostridia for Biofuel Production written by Satyakam Dash and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Anaerobic Clostridium spp. is an important microbial bio-production host that can producea range of solvents and utilize a broad spectrum of substrates including cellulose and syngas.Metabolic capacities of an organism can be understood and analyzed using a genome-scalemetabolic (GSM) model to develop metabolic engineering strategies for strain development. GSMmodels have been developed for various clostridial strains to explore their respective metaboliccapabilities and suitability for various bioconversions. In Chapter 1, we compare representativeGSM models for six different clostridia (Clostridium acetobutylicum, Clostridium beijerinckii,Clostridium butyricum, Clostridium cellulolyticum, Clostridium ljungdahlii, and Clostridiumthermocellum) contrasting their metabolic repertoire. We further discuss various applications ofthese GSM models to aid metabolic engineering interventions as well as assess cellular physiology.In Chapter 2, we describe the construction and validation of a GSM model for C.acetobutylicum ATCC 824 (iCac802) which can produce butanol on an industrial scale throughacetone-butanol-ethanol (ABE) fermentation. The model iCac802 spans 802 genes and includes1,137 metabolites and 1,462 reactions, along with gene-protein-reaction associations. Flux rangesallowed by the model were tested using both 13C-MFA and gene deletion data in the ABEfermentation pathway. In this Chapter, we also describe the CoreReg method which imposesregulatory constraints on the GSM model based on the fold changes in transcriptomic datasets. TheCoreReg procedure was used to differentiate the metabolic response to butanol and butyrate stress.The maximum ethanol titer achieved by C. thermocellum, a Gram-positive anaerobe withthe ability to hydrolyze and metabolize cellulose into biofuels such as ethanol, to date remainsbelow industrially required targets. Several studies have analyzed the impact of increasing ethanolconcentration on C. thermocellums membrane properties, cofactor pool ratios, and altered enzymeregulation. In Chapter 3, we explore the extent to which thermodynamic equilibrium limitsivmaximum ethanol titer. We used the max-min driving force (MDF) algorithm (Noor et al., 2014)to identify the range of allowable metabolite concentrations that maintain a negative free energychange for all reaction steps in the pathway from cellobiose to ethanol. To this end, we used a timeseriesmetabolite concentration dataset to flag five reactions (phosphofructokinase (PFK), fructosebisphosphate aldolase (FBA), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), aldehydedehydrogenase (ALDH) and alcohol dehydrogenase (ADH)) which become thermodynamicbottlenecks under high external ethanol concentrations. Thermodynamic analysis was alsodeployed in a prospective mode to evaluate genetic interventions which can improve pathwaythermodynamics by generating minimal set of reactions or elementary flux modes (EFMs) whichpossess unique genetic variations while ensuring mass and redox balance with ethanol production.MDF evaluation of all generated (336) EFMs indicated that, i) pyruvate phosphate dikinase (PPDK)has a higher pathway MDF than the malate shunt alternative due to limiting CO2 concentrationsunder physiological conditions, and ii) NADPH-dependent glyceraldehyde-3-phosphatedehydrogenase (GAPN) can alleviate thermodynamic bottlenecks at high ethanol concentrationsdue to cofactor modification and reduction in ATP generation. The combination of ATP linkedphosphofructokinase (PFK-ATP) and NADPH linked alcohol dehydrogenase (ADH-NADPH) withNADPH linked aldehyde dehydrogenase (ALDH-NADPH) or ferredoxin: NADP+ oxidoreductase(NADPH-FNOR) emerges as the best intervention strategy for ethanol production that balancesMDF improvements with ATP generation, and appears to functionally reproduce the pathwayemployed by the ethanologen Thermoanaerobacterium saccharolyticum. Expanding the list ofmeasured intracellular metabolites and improving the quantification accuracy of measurements wasfound to improve the fidelity of pathway thermodynamics analysis in C. thermocellum. This studydemonstrates even before addressing an organisms enzyme kinetics and allosteric regulations,pathway thermodynamics can flag pathway bottlenecks and identify testable strategies forenhancing pathway thermodynamic feasibility and function.vIn Chapter 4, we develop a second-generation genome-scale metabolic model (iCth446)for C. thermocellum to further investigate the organisms metabolism and engineer it. The modeliCth446 contained 446 genes, 598 metabolites and 660 reactions, along with gene-protein-reactionassociations by updating cofactor dependencies, maintenance (GAM and NGAM) values andresolving elemental and charge imbalances. The iCth446 model is next used as a scaffold to developa core kinetic model (k-ctherm118) of the C. thermocellum central metabolism using the EnsembleModeling (EM) paradigm. The kinetic model alludes to a systemic level effect of limiting nitrogensource resulting in increased yields for lactate, pyruvate and amino acids and an increase inammonia and sugar phosphates concentrations due to down-regulation of fermentation pathwaysunder ethanol stress. Robustness analysis of the kinetic model revealed the presence of secondaryactivity of ketol-acid reductoisomerase and its regulation by valine and leucine pool levels.In Chapter 5, we summarize all the work done in this dissertation and briefly highlight thefuture of metabolic modeling in clostridia which involves using a new parametrization procedureand pathway design tools.