On-target activity predictions enable improved CRISPR–dCas9 screens in bacteria. Issue 11 (30th April 2020)

• Record Type: Journal Article
• Authors: Calvo-Villamañán, Alicia; Ng, Jérome Wong; Planel, Rémi; Ménager, Hervé; Chen, Arthur; Cui, Lun; Bikard, David
• Is Part Of: Nucleic acids research. Volume 48:Issue 11(2020)
• Page Start: e64
• Page End: e64
• Publication Date: 2020-04-30
• Subjects: Nucleic acids -- Periodicals; Molecular biology -- Periodicals; 572.805
• DOI: 10.1093/nar/gkaa294
• Languages: English
• ISSNs: 0305-1048

Abstract

Abstract: 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 and more cost-effective. Our model and materials are available to the community through crispr.pasteur.fr and Addgene.