The ability to block gene expression in bacteria with the catalytically inactive mutant of Cas9, known as dCas9, is quickly becoming a standard methodology to probe gene function, perform high-throughput screens, and engineer cells for desired purposes. Yet, we still lack a good understanding of the design rules that determine on-target activity for dCas9. Taking advantage of high-throughput screening data, we fit a model to predict the ability of dCas9 to block the RNA polymerase based on the target sequence, and validate its performance on independently generated datasets. We further design a novel genome wide guide RNA library for E. coli MG1655, EcoWG1, using our model to choose guides with high activity while avoiding guides which might be toxic or have off-target effects. A screen performed using the EcoWG1 library during growth in rich medium improved upon previously published screens, demonstrating that very good performances can be attained using only a small number of well designed guides. Being able to design effective, smaller libraries will help make CRISPRi screens even easier to perform andmore cost-effective. Ourmodel and materials are available to the community through crispr.pasteur.fr and Addgene.
CITATION STYLE
Calvo-Villamañán, A., Ng, J. W., Planel, R., Ménager, H., Chen, A., Cui, L., & Bikard, D. (2020). On-target activity predictions enable improved CRISPR-dCas9 screens in bacteria. Nucleic Acids Research, 48(11). https://doi.org/10.1093/NAR/GKAA294
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