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Comparison of genome‐wide selection strategies to identify furfural tolerance genes in Escherichia coli
Author(s) -
Glebes Tirzah Y.,
Sandoval Nicholas R.,
Gillis Jacob H.,
Gill Ryan T.
Publication year - 2015
Publication title -
biotechnology and bioengineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.136
H-Index - 189
eISSN - 1097-0290
pISSN - 0006-3592
DOI - 10.1002/bit.25325
Subject(s) - recombineering , biology , gene , genome , plasmid , escherichia coli , genetics , computational biology , selection (genetic algorithm) , computer science , artificial intelligence
Engineering both feedstock and product tolerance is important for transitioning towards next‐generation biofuels derived from renewable sources. Tolerance to chemical inhibitors typically results in complex phenotypes, for which multiple genetic changes must often be made to confer tolerance. Here, we performed a genome‐wide search for furfural‐tolerant alleles using the TRackable Multiplex Recombineering (TRMR) method (Warner et al. (2010), Nature Biotechnology ), which uses chromosomally integrated mutations directed towards increased or decreased expression of virtually every gene in Escherichia coli . We employed various growth selection strategies to assess the role of selection design towards growth enrichments. We also compared genes with increased fitness from our TRMR selection to those from a previously reported genome‐wide identification study of furfural tolerance genes using a plasmid‐based genomic library approach (Glebes et al. (2014) PLOS ONE ). In several cases, growth improvements were observed for the chromosomally integrated promoter/RBS mutations but not for the plasmid‐based overexpression constructs. Through this assessment, four novel tolerance genes, ahpC, yhjH, rna , and dicA , were identified and confirmed for their effect on improving growth in the presence of furfural. Biotechnol. Bioeng. 2015;112: 129–140. © 2014 Wiley Periodicals, Inc.