Screening and modular design for metabolic pathway optimization
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Prather_Screening and.pdf
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1.9 MB
Format
Adobe PDF
Checksum (MD5)
a70a66e0b2945c34d104a3c0785d28ff
Author(s)
Boock, Jason
Gupta, Apoorv
Jones, Kristala L.
Date Issued
October 2015
Journal
Current Opinion in Biotechnology
Publisher
Elsevier
Citation
Boock, Jason T, Gupta, Apoorv, and Prather, Kristala L J. “Screening and Modular Design for Metabolic Pathway Optimization.” Current Opinion in Biotechnology 36 (December 2015): 189–198. © 2015 Elsevier Ltd
Version
Author's final manuscript
Abstract
Biological conversion of substrate sugars to a variety of products is an increasingly popular option for chemical transformation due to its high specificity and because of significant interest in the use of renewable feedstocks. However, pathway optimization through metabolic engineering is often needed to make such molecules economically at a relevant scale. Employing effective methods to search and narrow the immense pathway parameter space is essential to meet performance metrics such as high titer, yield and productivity with efficiency. This review focuses on two practices that increase the likelihood of finding a more advantageous pathway solution: implementing a screen to identify high producers and utilizing modular pathway design to streamline engineering efforts. While screens seek to couple product titer with a high-throughput measurement output, modular design aims to rationally construct pathways to allow parallel optimization of various units. Both of these methodologies have proven widely successful in metabolic engineering, with combinations of them resulting in synergistic enhancements to pathway optimization. This review will particularly highlight their utility for microbially derived acid and alcohol products, which are of interest as fuels and value added products.
MIT Department
Massachusetts Institute of Technology. Department of Biological Engineering
Massachusetts Institute of Technology. Department of Chemical Engineering
Terms of Use
Creative Commons Attribution-NonCommercial-NoDerivs License
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DOI of Published Version
https://doi.org/10.1016/j.copbio.2015.08.013
