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Engineering microbial biofuel tolerance and export using efflux pumps

Many compounds being considered as candidates for advanced biofuels are toxic to microorganisms. This introduces an undesirable trade-off when engineering metabolic pathways for biofuel production because the engineered microbes must balance production against survival. Cellular export systems, such...

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Detalles Bibliográficos
Autores principales: Dunlop, Mary J, Dossani, Zain Y, Szmidt, Heather L, Chu, Hou Cheng, Lee, Taek Soon, Keasling, Jay D, Hadi, Masood Z, Mukhopadhyay, Aindrila
Formato: Online Artículo Texto
Lenguaje:English
Publicado: European Molecular Biology Organization 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3130554/
https://www.ncbi.nlm.nih.gov/pubmed/21556065
http://dx.doi.org/10.1038/msb.2011.21
Descripción
Sumario:Many compounds being considered as candidates for advanced biofuels are toxic to microorganisms. This introduces an undesirable trade-off when engineering metabolic pathways for biofuel production because the engineered microbes must balance production against survival. Cellular export systems, such as efflux pumps, provide a direct mechanism for reducing biofuel toxicity. To identify novel biofuel pumps, we used bioinformatics to generate a list of all efflux pumps from sequenced bacterial genomes and prioritized a subset of targets for cloning. The resulting library of 43 pumps was heterologously expressed in Escherichia coli, where we tested it against seven representative biofuels. By using a competitive growth assay, we efficiently distinguished pumps that improved survival. For two of the fuels (n-butanol and isopentanol), none of the pumps improved tolerance. For all other fuels, we identified pumps that restored growth in the presence of biofuel. We then tested a beneficial pump directly in a production strain and demonstrated that it improved biofuel yields. Our findings introduce new tools for engineering production strains and utilize the increasingly large database of sequenced genomes.