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Design of Experiments Methodology to Build a Multifactorial Statistical Model Describing the Metabolic Interactions of Alcohol Dehydrogenase Isozymes in the Ethanol Biosynthetic Pathway of the Yeast Saccharomyces cerevisiae

Lookup NU author(s): Emeritus Professor David Parker, Dr Thomas Howard

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This is the authors' accepted manuscript of an article that has been published in its final definitive form by American Chemical Society, 2018.

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Abstract

Multifactorial approaches can quickly and efficiently model complex, interacting natural or engineered biological systems in a way that traditional one-factor-at-a-time experimentation can fail to do. We applied a Design of Experiments (DOE) approach to model ethanol biosynthesis in yeast, which is well-understood and genetically tractable, yet complex. Six alcohol dehydrogenase (ADH) isozymes catalyse ethanol synthesis, differing in their transcriptional and post-translational regulation, subcellular localisation, and enzyme kinetics. We generated a combinatorial library of all ADH gene deletions, and measured the impact of gene deletion(s) and environmental context on ethanol production of a subset of this library. The data were used to build a statistical model that described known behaviours of ADH isozymes and identified novel interactions. Importantly, the model described features of ADH metabolic behaviour without explicit a priori knowledge. The method is therefore highly suited to understanding and optimising metabolic pathways in less well understood systems.


Publication metadata

Author(s): Brown SR, Staff M, Lee R, Love J, Parker DA, Aves SJ, Howard TP

Publication type: Article

Publication status: Published

Journal: ACS Synthetic Biology

Year: 2018

Volume: 7

Issue: 7

Pages: 1676-1684

Print publication date: 20/07/2018

Online publication date: 06/07/2018

Acceptance date: 06/07/2018

Date deposited: 10/07/2018

ISSN (electronic): 2161-5063

Publisher: American Chemical Society

URL: https://doi.org/10.1021/acssynbio.8b00112

DOI: 10.1021/acssynbio.8b00112


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