4.6 Article

Combinatorial Strategies for Improving Multiple-Stress Resistance in Industrially Relevant Escherichia coli Strains

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APPLIED AND ENVIRONMENTAL MICROBIOLOGY
卷 80, 期 19, 页码 6223-6242

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AMER SOC MICROBIOLOGY
DOI: 10.1128/AEM.01542-14

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  1. Novo Nordisk Foundation
  2. Novo Nordisk Fonden [NNF10CC1016517] Funding Source: researchfish

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High-cell-density fermentation for industrial production of chemicals can impose numerous stresses on cells due to high substrate, product, and by-product concentrations; high osmolarity; reactive oxygen species; and elevated temperatures. There is a need to develop platform strains of industrial microorganisms that are more tolerant toward these typical processing conditions. In this study, the growth of six industrially relevant strains of Escherichia coli was characterized under eight stress conditions representative of fed-batch fermentation, and strains W and BL21 (DE3) were selected as platforms for transposon (Tn) mutagenesis due to favorable resistance characteristics. Selection experiments, followed by either targeted or genome-wide nextgeneration-sequencing-based Tn insertion site determination, were performed to identify mutants with improved growth properties under a subset of three stress conditions and two combinations of individual stresses. A subset of the identified loss-of-function mutants were selected for a combinatorial approach, where strains with combinations of two and three gene deletions were systematically constructed and tested for single and multistress resistance. These approaches allowed identification of (i) strain-background-specific stress resistance phenotypes, (ii) novel gene deletion mutants in E. coli that confer single and multistress resistance in a strain-background-dependent manner, and (iii) synergistic effects of multiple gene deletions that confer improved resistance over single deletions. The results of this study underscore the suboptimality and strain-specific variability of the genetic network regulating growth under stressful conditions and suggest that further exploration of the combinatorial gene deletion space in multiple strain backgrounds is needed for optimizing strains for microbial bioprocessing applications.

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