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• W3134873996 abstract "Abstract The development of a culture medium is an essential step in any bioprocess involving microorganisms for the bioconversion of by‐products to valuable chemicals, making industries like the biofuel industry more competitive. Optimization of the bioconversion process to minimize cost while maximizing yield underscores the importance of using computational methods to identify cellular requirements under specific growth conditions. In this study, a computational approach was proposed as an alternative to optimizing glycerol consumption in one of the most common production chassis, Escherichia coli , specifically strain ATCC 8739. Nineteen compounds were identified as essential for E. coli growth in glycerol. Of these, three reactions associated with nitrogen, phosphorous, and oxygen availability were determined as crucial to reaching high growth and glycerol uptake rates. Based on computational results, a glycerol‐based medium was supplemented with reported common chemical compounds that contain nitrogen or phosphorous (NH 4 Cl, Na 2 HPO 4 , and K 2 HPO 4 ) for further experimental validation. When comparing the supplemented culture medium experimentally with LB medium (Luria Bertani), a two‐fold increment in the glycerol consumption was observed. Transcriptomic analysis of the most promising culture medium reveals that high glycerol utilization under aerobic conditions is dependent on phosphorus to avoid toxicity within the cell because of glycerol‐3‐phosphate generation. The result of this study is a resource to determine nutritional requirements that allow the improvement of the use of raw material for the production of compounds that are attractive to the bio‐based industry. © 2021 Society of Chemical Industry and John Wiley & Sons, Ltd" @default.
• W3134873996 created "2021-03-15" @default.
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• W3134873996 date "2021-03-04" @default.
• W3134873996 modified "2023-10-16" @default.
• W3134873996 title "Optimization of glycerol consumption in wild‐type <i>Escherichia coli</i> using central carbon modeling as an alternative approach" @default.
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• W3134873996 doi "https://doi.org/10.1002/bbb.2205" @default.
• W3134873996 hasPublicationYear "2021" @default.
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