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Evolutionary engineering of E. coli MG1655 for tolerance against isoprenol

BACKGROUND: Isoprenol is the basis for industrial flavor and vitamin synthesis and also a promising biofuel. Biotechnological production of isoprenol with E. coli is currently limited by the high toxicity of the final product. Adaptive laboratory evolution (ALE) is a promising method to address comp...

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Detalles Bibliográficos
Autores principales: Babel, Heiko, Krömer, Jens O.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7653855/
https://www.ncbi.nlm.nih.gov/pubmed/33292484
http://dx.doi.org/10.1186/s13068-020-01825-6
Descripción
Sumario:BACKGROUND: Isoprenol is the basis for industrial flavor and vitamin synthesis and also a promising biofuel. Biotechnological production of isoprenol with E. coli is currently limited by the high toxicity of the final product. Adaptive laboratory evolution (ALE) is a promising method to address complex biological problems such as toxicity. RESULTS: Here we applied this method successfully to evolve E. coli towards higher tolerance against isoprenol, increasing growth at the half-maximal inhibitory concentration by 47%. Whole-genome re-sequencing of strains isolated from three replicate evolutions at seven time-points identified four major target genes for isoprenol tolerance: fabF, marC, yghB, and rob. We could show that knock-out of marC and expression of mutated Rob H(48) → frameshift increased tolerance against isoprenol and butanol. RNA-sequencing showed that the deletion identified upstream of yghB correlated with a strong overexpression of the gene. The knock-out of yghB demonstrated that it was essential for isoprenol tolerance. The mutated Rob protein and yghB deletion also lead to increased vanillin tolerance. CONCLUSION: Through ALE, novel targets for strain optimization in isoprenol production and also the production of other fuels, such as butanol, could be obtained. Their effectiveness could be shown through re-engineering. This paves the way for further optimization of E. coli for biofuel production.