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A dynamic kinetic model captures cell-free metabolism for improved butanol production.

Authors :
Martin JP
Rasor BJ
DeBonis J
Karim AS
Jewett MC
Tyo KEJ
Broadbelt LJ
Source :
Metabolic engineering [Metab Eng] 2023 Mar; Vol. 76, pp. 133-145. Date of Electronic Publication: 2023 Jan 29.
Publication Year :
2023

Abstract

Cell-free systems are useful tools for prototyping metabolic pathways and optimizing the production of various bioproducts. Mechanistically-based kinetic models are uniquely suited to analyze dynamic experimental data collected from cell-free systems and provide vital qualitative insight. However, to date, dynamic kinetic models have not been applied with rigorous biological constraints or trained on adequate experimental data to the degree that they would give high confidence in predictions and broadly demonstrate the potential for widespread use of such kinetic models. In this work, we construct a large-scale dynamic model of cell-free metabolism with the goal of understanding and optimizing butanol production in a cell-free system. Using a combination of parameterization methods, the resultant model captures experimental metabolite measurements across two experimental conditions for nine metabolites at timepoints between 0 and 24 h. We present analysis of the model predictions, provide recommendations for butanol optimization, and identify the aldehyde/alcohol dehydrogenase as the primary bottleneck in butanol production. Sensitivity analysis further reveals the extent to which various parameters are constrained, and our approach for probing valid parameter ranges can be applied to other modeling efforts.<br />Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.<br /> (Copyright © 2023 International Metabolic Engineering Society. Published by Elsevier Inc. All rights reserved.)

Details

Language :
English
ISSN :
1096-7184
Volume :
76
Database :
MEDLINE
Journal :
Metabolic engineering
Publication Type :
Academic Journal
Accession number :
36724840
Full Text :
https://doi.org/10.1016/j.ymben.2023.01.009