Abstract
CRISPR/Cas9 is a promising tool in prokaryotic genome engineering, but its success is limited by the widely varying on-target activity of single guide RNAs (sgRNAs). Based on the association of CRISPR/Cas9-induced DNA cleavage with cellular lethality, we systematically profiled sgRNA activity by co-expressing a genome-scale library (∼70 000 sgRNAs) with Cas9 or its specificity-improved mutant in Escherichia coli. Based on this large-scale dataset, we constructed a comprehensive and high-density sgRNA activity map, which enables selecting highly active sgRNAs for any locus across the genome in this model organism. We also identified 'resistant' genomic loci with respect to CRISPR/Cas9 activity, notwithstanding the highly accessible DNA in bacterial cells. Moreover, we found that previous sgRNA activity prediction models that were trained on mammalian cell datasets were inadequate when coping with our results, highlighting the key limitations and biases of previous models. We hence developed an integrated algorithm to accurately predict highly effective sgRNAs, aiming to facilitate CRISPR/Cas9-based genome engineering, screenings and antimicrobials design in bacteria. We also isolated the important sgRNA features that contribute to DNA cleavage and characterized their key differences among wild type Cas9 and its mutant, shedding light on the biophysical mechanisms of the CRISPR/Cas9 system.