A Tool-Box for Quantifying the Relationship Between Gene Expression, Nutrient Conditions, and Cellular Growth Rate in Bacteria

A central aspect of the genotype to phenotype problem is relating changes in gene expression to cellular division (or growth rate). The relationship between gene expression and growth rate can be complex, nonlinear, and dependent on environmental conditions, however, most high-throughput studies condense this complexity into a single discrete measurement per gene. This greatly limits the utility of high-throughput screening data in applications like rational engineering of cellular systems, modeling of cellular behavior, and genetic screening for specific phenotypes. I developed a series of techniques, based on highthroughput CRISPR interference gene knockdowns, to more continuously quantify the effects of gene expression and nutrient condition on bacterial growth rate. These techniques allow high-throughput titration of gene expression, precise modulation of environment conditions, and corresponding quantification of growth rate, epistasis, and gene-by-environment interactions all in the same experiment. Using these techniques, I have demonstrated that epistasis can explain co-evolution between a pair of enzymes, that gene by environment interactions are often specific to certain gene expression regimes, and that the sign and magnitude of epistasis can be dependent gene expression levels. In sum, these techniques are an essential step towards developing predictive models that relate gene expression, nutrient condition, and growth rate.