Here, we provide a case study by engineering isopropanol production in gas-fermenting Clostridium ljungdahlii. To date, the rational redesign of gas-fermenting bacteria is still in its infancy, due in part to the lack of quantitative and precise metabolic knowledge that can direct strain engineering. IMPORTANCE Highly efficient bioproduction from gaseous substrates (e.g., hydrogen and carbon oxides) will require systematic optimization of the host microbes. Our work highlighted that the gas-fermenting chasses can be fine-tuned for high-yield bioproduction by directed and elaborative pathway engineering. In a bioreactor environment sparging with CO, CO2, and H2 only, the strain produced 2.4 g/L isopropanol. The engineered strain was further tested under gas-fermenting mixotrophic conditions, where more than 4 g/L isopropanol was produced when CO, CO2, and fructose were provided as the substrates. Our predictions directed iterative pathway construction, which enabled a 2.8-fold increase in isopropanol production compared to the initial version. Based on in silico thermodynamic optimization, minimal protein requirement analysis, and ensemble modeling-based robustness analysis, we identified the top two significant flux control sites, i.e., acetoacetyl-coenzyme A (CoA) transferase (AACT) and acetoacetate decarboxylase (AADC), overexpression of which could lead to increased isopropanol production. To this extent, we integrated a metabolic model in comparison with proteomics measurements and quantified the uncertainty for a variety of pathway targets needed to improve the bioproduction of isopropanol. Based on recent advances in constraint-based thermodynamic and kinetic models, we identify key enzymes in the gas-fermenting acetogen Clostridium ljungdahlii that correlate with the production of isopropanol. To date, rational design of gas-fermenting bacteria such as changing the expression levels of individual enzymes to obtain the desired pathway flux is challenging, because pathway design must follow a verifiable metabolic blueprint indicating where interventions should be executed. It will allow the microbial chassis to renewably valorize natural resources from carbon oxides, hydrogen, and/or lignocellulosic feedstocks more efficiently. Rational engineering of gas-fermenting bacteria for high yields of bioproducts is vital for a sustainable bioeconomy. Here we describe the database characteristics and implementation and demonstrate its use. The eQuilibrator code is open-source and all thermodynamic source data are freely downloadable in standardįormats. () enables easy calculation of Gibbs energies of compounds and reactions given arbitrary pH, ionic strength and metaboliteĬoncentrations. To address this problem, eQuilibrator couples a comprehensive and accurate database of thermodynamic properties of biochemicalĬompounds and reactions with a simple and powerful online search and calculation interface. ‘how much Gibbs energy is released by ATP hydrolysis at pH 5?’ are complicated excessively by the search for accurate data. However, thermodynamic data on biochemical compoundsĬan be difficult to find and is cumbersome to perform calculations with manually. This relationship is described by the equation above.The laws of thermodynamics constrain the action of biochemical systems. Newton’s law of cooling states the relationship between heat transfer when conduction, radiation, and convection are the dominating factors in a heat transfer problem. The following equation can be used to calculate the temperature of a substance after a certain time and cooling rate.
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