Using design of experiments to guide genetic optimization of engineered metabolic pathways

Abstract   Design of experiments (DoE) is a term used to describe the application of statistical approaches to interrogate the impact of many variables on the performance of a multivariate system. It is commonly used for process optimization in fields such as chemical engineering and material scienc...

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Bibliographic Details
Published inJournal of industrial microbiology & biotechnology Vol. 51
Main Authors Moon, Seonyun, Saboe, Anna, Smanski, Michael J
Format Journal Article
LanguageEnglish
Published Germany Oxford University Press 09.01.2024
Subjects
Genetic Engineering
Metabolic Engineering
Metabolic Networks and Pathways - genetics
Gene expression
Metabolic engineering
Design of experiments
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Summary:Abstract   Design of experiments (DoE) is a term used to describe the application of statistical approaches to interrogate the impact of many variables on the performance of a multivariate system. It is commonly used for process optimization in fields such as chemical engineering and material science. Recent advances in the ability to quantitatively control the expression of genes in biological systems open up the possibility to apply DoE for genetic optimization. In this review targeted to genetic and metabolic engineers, we introduce several approaches in DoE at a high level and describe instances wherein these were applied to interrogate or optimize engineered genetic systems. We discuss the challenges of applying DoE and propose strategies to mitigate these challenges. One-Sentence Summary This is a review of literature related to applying Design of Experiments for genetic optimization. Graphical Abstract Graphical Abstract
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ISSN:1367-5435
1476-5535
DOI:10.1093/jimb/kuae010