Two Bioinformatic Tools developed for the Identification and research of Anti-CRISPRs

As a natural adaptive immune system of prokaryotes, CRISPR-Cas systems have become popular in recent years due to their successful application in programmable genome editing. Anti-CRISPR (Acr) proteins, on the other hand, have a great potential to enable a more controllable genome editing. In the past year we developed a software tool, AcrFinder (http://bcb.unl.edu/AcrFinder/) , to help biologists retrieve putative Acr gene candidates and their genomic contexts from the vast amount of sequenced bacterial, archaeal, and viral genomes. AcrFinder combine three well-accepted ideas in one pipeline, which have been used by previous experimental papers to assist in pre-screening genomic data for Acr candidates. We tested AcrFinder on the genomes that contain 16 experimentally characterized Acr-Aca genomic loci/operons, and found that our tool had a 100% recall. We also built an online database AcrDB (http://bcb.unl.edu/AcrDB) by scanning ~19,000 genomes of prokaryotes and viruses with AcrFinder and further processed with two machine learning-based programs, AcRanker and PaCRISPR. Compared to other anti-CRISPR databases, AcrDB has the following unique features: (i) It is a genome-centric database with a much larger data; (ii) It offers a user-friendly web interface with various functions (iii) It focuses on the genomic context of Acr and Aca homologs instead of individual Acr protein family; and (iv) It collects data with three independent programs each having a unique data mining algorithm for cross validation. AcrDB and AcrFinder will be valuable resources to the anti-CRISPR research community.