Abstract | ||
---|---|---|
Anti-CRISPR (Acr) proteins encoded by (pro)phages/(pro)viruses have a great potential to enable a more controllable genome editing. However, genome mining new Acr proteins is challenging due to the lack of a conserved functional domain and the low sequence similarity among experimentally characterized Acr proteins. We introduce here AcrFinder, a web server (http://bcb.unl.edu/AcrFinder) that combines three well-accepted ideas used by previous experimental studies to pre-screen genomic data for Acr candidates. These ideas include homology search, guilt-by-association (GBA), and CRISPR-Cas self-targeting spacers. Compared to existing bioinformatics tools, AcrFinder has the following unique functions: (i) it is the first online server specifically mining genomes for Acr-Aca operons; (ii) it provides a most comprehensive Acr and Aca (Acr-associated regulator) database (populated by GBA-based Acr and Aca datasets); (iii) it combines homology-based, GBA-based, and self-targeting approaches in one software package; and (iv) it provides a user-friendly web interface to take both nucleotide and protein sequence files as inputs, and output a result page with graphic representation of the genomic contexts of Acr-Aca operons. The leave-one-out cross-validation on experimentally characterized Acr-Aca operons showed that AcrFinder had a 100% recall. AcrFinder will be a valuable web resource to help experimental microbiologists discover new Anti-CRISPRs. |
Year | DOI | Venue |
---|---|---|
2020 | 10.1093/nar/gkaa351 | NUCLEIC ACIDS RESEARCH |
DocType | Volume | Issue |
Journal | 48 | W1 |
ISSN | Citations | PageRank |
0305-1048 | 0 | 0.34 |
References | Authors | |
0 | 6 |
Name | Order | Citations | PageRank |
---|---|---|---|
Haidong Yi | 1 | 3 | 3.17 |
Le Huang | 2 | 2 | 1.73 |
Bowen Yang | 3 | 0 | 0.34 |
Javi Gomez | 4 | 0 | 0.34 |
Han Zhang | 5 | 0 | 0.68 |
Yanbin Yin | 6 | 31 | 7.75 |