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DOE OSTI · 2466236

Bayesian Framework for Predicting and Controlling Metabolic Phenotypes in Microbial System

McNaughton, Andrew D.·Pino, James C.·Mahserejian, Shant M.·George, August D.·Johnson, Connah G.·Bohutskyi, Pavlo·Petyuk, Vladislav A.·Zucker, Jeremy D.
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Abstract

To improve titers, rates and yields for sucrose production in an engineered strain of Synechococcus elongatus PCC7942, we employed Bayesian metabolic control analysis to transcriptomics and external metabolomics data generated for various phases during the circadian clock. Top overexpression candidates included sodium-dependent bicarbonate transporter (H2cO3_Nat_syn), and UTP—glucose-1-phosphate uridylyltransferase (GALUi). Top repression candidates included Glycogen/starch synthetases, ADP-glucose type (GLCS3), Glutamate racemase (GLUR), and ribonucleoside diphosphate reductase (RNDR1).

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60 APPLIED LIFE SCIENCESBayesian Metabolic Control Analysis

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BibTeXRIS

McNaughton, Andrew D., Pino, James C., Mahserejian, Shant M., George, August D., Johnson, Connah G., Bohutskyi, Pavlo, Petyuk, Vladislav A., Zucker, Jeremy D.. 2024-09-01. Bayesian Framework for Predicting and Controlling Metabolic Phenotypes in Microbial System. https://doi.org/10.2172/2466236

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