Title of article :
Genome-scale identification and characterization of ethanol tolerance genes in Escherichia coli
Author/Authors :
Woodruff، نويسنده , , Lauren B.A. and Pandhal، نويسنده , , Jagroop and Ow، نويسنده , , Saw Y. and Karimpour-Fard، نويسنده , , Anis and Weiss، نويسنده , , Sophie J. and Wright، نويسنده , , Phillip C. and Gill، نويسنده , , Ryan T.، نويسنده ,
Issue Information :
دوماهنامه با شماره پیاپی سال 2013
Pages :
10
From page :
124
To page :
133
Abstract :
The identification of relevant gene targets for engineering a desired trait is a key step in combinatorial strain engineering. Here, we applied the multi-Scalar Analysis of Library Enrichments (SCALEs) approach to map ethanol tolerance onto 1,000,000 genomic-library clones in Escherichia coli. We assigned fitness scores to each of the ∼4,300 genes in E. coli, and through follow-up confirmatory studies identified 9 novel genetic targets (12 genes total) that increase E. coli ethanol tolerance (up to 6-fold improved growth). These genetic targets are involved in the processes related to cell membrane composition, translation, serine biosynthesis, and transcription regulation. Transcriptional profiling of the ethanol stress response in 5 of these ethanol-tolerant clones revealed a total of 700 genes with significantly altered expression (mapped to 615 significantly enriched gene ontology terms) across all five clones, with similar overall changes in global gene expression between two clone clusters. All ethanol-tolerant clones analyzed shared 6% of the overexpressed genes and showed enrichment for transcription regulation-related GO terms. iTRAQ-based proteomic analysis of ethanol-tolerant strains identified upregulation of proteins related to ROS mitigation, fatty acid biosynthesis, and vitamin biosynthesis as compared to the parent strainʹs ethanol response. The approach we outline here will be useful for engineering a variety of other traits and further improvements in alcohol tolerance.
Keywords :
Metabolic engineering , Ethanol , TOLERANCE , Selections , E. coli , Strain engineering
Journal title :
Metabolic Engineering
Serial Year :
2013
Journal title :
Metabolic Engineering
Record number :
1429477
Link To Document :
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