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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 HowardORCiD



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

For re-use rights please refer to the publisher's terms and conditions.


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


DOI: 10.1021/acssynbio.8b00112


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