Abstract
Cellular hosts are widely used for the production of chemical compounds, including pharmaceutics, fuels, and specialty chemicals. However, common metabolic engineering techniques are limited in their capacity to elicit multigenic, complex phenotypes. These phenotypes can include non-pathway-based traits, such as tolerance and productivity. Global transcription machinery engineering (gTME) is a generic methodology for eliciting these complex cellular phenotypes. In gTME, dominant mutant alleles of a transcription-related protein are screened for their ability to reprogram cellular metabolism and regulation, resulting in a unique and desired phenotype. gTME has been successfully applied to both prokaryotic and eukaryotic systems, resulting in improved environmental tolerances, metabolite production, and substrate utilization. The underlying principle involves creating mutant libraries of transcription factors, screening for a desired phenotype, and iterating the process in a directed evolution fashion. The successes of this approach and details for its implementation and application are described here.
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Lanza, A.M., Alper, H.S. (2012). Using Transcription Machinery Engineering to Elicit Complex Cellular Phenotypes. In: Weber, W., Fussenegger, M. (eds) Synthetic Gene Networks. Methods in Molecular Biology, vol 813. Humana Press. https://doi.org/10.1007/978-1-61779-412-4_14
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DOI: https://doi.org/10.1007/978-1-61779-412-4_14
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