| Literature DB >> 29537074 |
Katia Tarasava1, Rongming Liu2, Andrew Garst3, Ryan T Gill1,2.
Abstract
Optimization of metabolic flux is a difficult and time-consuming process that often involves changing the expression levels of multiple genes simultaneously. While some pathways have a known rate limiting step, more complex metabolic networks can require a trial-and-error approach of tuning the expression of multiple genes to achieve a desired distribution of metabolic resources. Here we present an efficient method for generating expression diversity on a combinatorial scale using CRISPR interference. We use a modified native Escherichia coli Type I-E CRISPR-Cas system and an iterative cloning strategy for construction of guide RNA arrays. This approach allowed us to build a combinatorial gene expression library three orders of magnitude larger than previous studies. In less than 1 month, we generated ∼12,000 combinatorial gene expression variants that target six different genes and screened these variants for increased malonyl-CoA flux and 3-hydroxypropionate (3HP) production. We were able to identify a set of variants that exhibited a significant increase in malonyl-CoA flux and up to a 98% increase in 3HP production. This approach provides a fast and easy-to-implement strategy for engineering metabolic pathway flux for development of industrially relevant strains, as well as investigation of fundamental biological questions.Entities:
Keywords: 3-hydroxypropionic acid; CRISPR interference; combinatorial gene expression; malonyl-coA; metabolic flux engineering
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Year: 2018 PMID: 29537074 DOI: 10.1002/bit.26589
Source DB: PubMed Journal: Biotechnol Bioeng ISSN: 0006-3592 Impact factor: 4.530