Optimizing complex phenotypes through model-guided multiplex genome engineering
Optimizing complex phenotypes through model-guided multiplex genome engineering
We present a method for identifying genomic modifications that optimize a complex phenotype through multiplex genome engineering and predictive modeling. We apply our method to identify six single nucleotide mutations that recover 59% of the fitness defect exhibited by the 63-codon E. coli strain C321.ΔA.