Comprehensive characterization of genotype to phenotype relationships in E.coli

Genome engineering has revolutionized our ability to construct diverse cell libraries opening up for the possibility of conducting comprehensive studies on the relationship between genotype and phenotype. We have used multiplex automated genome engineering (MAGE) to construct libraries for assessing the impact on specific genetic variants on the translation and transcription of genes in E.coli. Using microarray derived oligos we demonstrate that libraries can be engineered to introduce artificial promoters driving the expression of a majority of non-essential genes in E coli. Furthermore, we use these approaches to comprehensively quantify the dependence of the Shine-Dalgarno sequence on protein expression and use this information to modulate the translation rate of all transcription factors in E.coli. We show that these approaches can be used to identify causal mutations underlying improved tolerance phenotypes as well as to efficiently explore phenotypic space to accelerate cell factory development.