Evolutionary engineering of industrially important microbial phenotypes.
The tremendous complexity of dynamic interactions in cellular systems often impedes practical applications of metabolic engineering that are largely based on available molecular or functional knowledge. In contrast, evolutionary engineering follows nature's 'engineering' principle by variation and selection. Thus, it is a complementary strategy that offers compelling scientific and applied advantages for strain development and process optimization, provided a desired phenotype is amenable to direct or indirect selection. In addition to simple empirical strain development by random mutation and direct selection on plates, evolutionary engineering also encompasses recombination and continuous evolution of large populations over many generations. Two distinct evolutionary engineering applications are likely to gain more relevance in the future: first, as an integral component in metabolic engineering of strains with improved phenotypes, and second, to elucidate the molecular basis of desired phenotypes for subsequent transfer to other hosts. The latter will profit from the broader availability of recently developed methodologies for global response analysis at the genetic and metabolic level. These methodologies facilitate identification of the molecular basis of evolved phenotypes. It is anticipated that, together with novel analytical techniques, bioinformatics, and computer modeling of cellular functions and activities, evolutionary engineering is likely to find its place in the metabolic engineer's toolbox for research and strain development. This review presents evolutionary engineering of whole cells as an emerging methodology that draws on the latest advances from a wide range of scientific and technical disciplines.
Sauer
U
U
Institute of Biotechnology, ETH Zürich, 8093 Zürich, Switzerland. sauer@biotech.biol.ethz.ch
D005075:Biological Evolution; D007218:Industrial Microbiology; D016296:Mutagenesis; D010641:Phenotype; D011995:Recombination, Genetic; D012641:Selection, Genetic