crisprbact 1.3.1

Tools to design and analyse CRISPRi experiments

CRISPRbact

Tools to design and analyse CRISPRi experiments in bacteria.

CRISPRbact is a Python library and command-line tool for designing CRISPRi (CRISPR interference) experiments with the Streptococcus pyogenes dCas9 protein in bacteria.

Features

• On-target activity prediction — predicts how effectively each guide RNA will block gene expression, using a linear model trained on ~92,000 guides in E. coli
• Genome-wide library design — designs optimized CRISPRi libraries for any bacterial genome, selecting the best guides per gene while avoiding off-targets and toxic seed sequences
• Library mapping — evaluates an existing guide library against a new genome to assess coverage and predict activity
• Add-on library design — supplements an existing library (e.g. a core-genome library) with strain-specific guides to achieve full gene coverage
• Core-genome library design — designs guide libraries targeting genes conserved across multiple strains, enabling cross-strain CRISPRi screens

Installation

pip install crisprbact

Quick example

from crisprbact import on_target_predict

guides = on_target_predict("ACCACTGGCGTGCGCGTTACTCATCAGATGCTGTTCAATACCGATCAGGTTATCGAAGTGTTTGTGATTGTTTGCCGCGCGCGTGGCGAAGGCCCGTGATGAAGGAAAAGTTTTGCGCTATGTTGGCAATATTGATGAAG")

for g in guides:
    print(g["guide"], round(g["pred"], 2))

Documentation

Full documentation (guides, API reference, output formats): https://dbikard.pages.pasteur.fr/crisprbact/

References

• Calvo-Villamañán, Wong Ng et al., "On-target activity predictions enable improved CRISPR–dCas9 screens in bacteria", Nucleic Acids Research, 2020, 48(11):e64 (doi:10.1093/nar/gkaa294)
• Rousset F et al., "The impact of genetic diversity on gene essentiality within the Escherichia coli species." Nature Microbiology 6, 301–312 (2021) (doi:10.1038/s41564-020-00839-y)
• Rostain et al., "Cas9 off-target bindings as a source of far-reaching transcriptional noise", Nucleic Acids Research, 2023 (doi:10.1093/nar/gkad170)