dc.contributor.author | Brown, SR | |
dc.contributor.author | Staff, M | |
dc.contributor.author | Lee, R | |
dc.contributor.author | Love, J | |
dc.contributor.author | Parker, DA | |
dc.contributor.author | Aves, SJ | |
dc.contributor.author | Howard, TP | |
dc.date.accessioned | 2018-07-25T15:20:18Z | |
dc.date.issued | 2018-07-06 | |
dc.description.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 catalyze ethanol synthesis, differing in their transcriptional and post-translational regulation, subcellular localization, 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 behaviors of ADH isozymes and identified novel interactions. Importantly, the model described features of ADH metabolic behavior without explicit a priori knowledge. The method is therefore highly suited to understanding and optimizing metabolic pathways in less well-understood systems. | en_GB |
dc.description.sponsorship | We wish to thank Dr. Alex Johns for helpful discussions. S.R.B. would also like to thank Shell Biodomain for funding for this PhD research project. | en_GB |
dc.identifier.citation | Vol. 7 (7), pp 1676–1684 | en_GB |
dc.identifier.doi | 10.1021/acssynbio.8b00112 | |
dc.identifier.uri | http://hdl.handle.net/10871/33540 | |
dc.language.iso | en | en_GB |
dc.publisher | American Chemical Society | en_GB |
dc.relation.url | https://www.ncbi.nlm.nih.gov/pubmed/29976056 | en_GB |
dc.rights.embargoreason | Under embargo until 6 July 2019 in compliance with publisher policy | en_GB |
dc.rights | Copyright © 2018 American Chemical Society | en_GB |
dc.subject | Design of Experiments (DOE) | en_GB |
dc.subject | Saccharomyces cerevisiae | en_GB |
dc.subject | alcohol dehydrogenase | en_GB |
dc.subject | ethanol biosynthesis | en_GB |
dc.subject | metabolic engineering | en_GB |
dc.title | 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 | en_GB |
dc.type | Article | en_GB |
exeter.place-of-publication | United States | en_GB |
dc.description | This is the author accepted manuscript. The final version is available from the American Chemical Society via the DOI in this record | en_GB |
dc.identifier.journal | ACS Synthetic Biology | en_GB |
dcterms.dateAccepted | 2018-07-05 | |