A sustainable economy will depend, if only partly, on efficient renewable-feedstock conversion to chemicals and fuels, and advances in that direction have relied and will continue to rely on strain engineering. Traditional methods comprising directed genetic modifications (i.e. targeting specific genes) have been quite successful in improving several phenotypes of industrial interest. Evolutionary approaches have also contributed much to these efforts and are gaining attention in particular for addressing complex phenotypes. Most commonly, mutagenesis and selection has been the method of choice, but many other random search-based approaches for phenotypic alteration have been developed in recent years. One such method, transcriptional engineering, relies on transcriptome-wide modifications that can be exploited to better complex traits. The initial aim of this work was to build upon the idea of transcriptional engineering in bacteria, which had been tried in our laboratory through mutagenesis of the principal sigma factor, sigma D. Initially, we explored new targets for transcriptional engineering. Using error-prone PCR, we constructed libraries of several stress-related sigma factors in Escherichia coli (sigma S, sigma E, and sigma H) and screened them for phenotypes of interest. We also considered the alpha subunit of the RNA polymerase as a tool for phenotypic alteration, and fruitfully used it to improve butanol and solvent tolerance, accumulation of hyaluronic acid, and L-tyrosine production.
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