Machine-learning approach expands the repertoire of anti-CRISPR protein families

The CRISPR-Cas are adaptive bacterial and archaeal immunity systems that have been harnessed for the development of powerful genome editing and engineering tools. In the incessant host-parasite arms race, viruses evolved multiple anti-defense mechanisms including diverse anti-CRISPR proteins (Acrs)...

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Bibliographic Details
Published in:	Nature communications 2020-07, Vol.11 (1), p.3784-3784, Article 3784
Main Authors:	Gussow, Ayal B, Park, Allyson E, Borges, Adair L, Shmakov, Sergey A, Makarova, Kira S, Wolf, Yuri I, Bondy-Denomy, Joseph, Koonin, Eugene V
Format:	Article
Language:	eng
Subjects:	Adaptive immunity Adaptive systems Archaea - genetics Archaea - virology Bacteria - genetics Bacteria - virology Bacteriophages - genetics Computational Biology - methods CRISPR CRISPR-Associated Protein 9 - antagonists & inhibitors CRISPR-Associated Protein 9 - genetics CRISPR-Cas Systems - genetics Datasets as Topic Editing Forest management Gene Editing - methods Genomes Host-Parasite Interactions - genetics Immunity Learning algorithms Machine Learning Modulators Parasites Predictions Protein families Proteins Sequence Analysis, Protein - methods Sequence Homology, Amino Acid Viral Proteins - genetics Viruses
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Summary:	The CRISPR-Cas are adaptive bacterial and archaeal immunity systems that have been harnessed for the development of powerful genome editing and engineering tools. In the incessant host-parasite arms race, viruses evolved multiple anti-defense mechanisms including diverse anti-CRISPR proteins (Acrs) that specifically inhibit CRISPR-Cas and therefore have enormous potential for application as modulators of genome editing tools. Most Acrs are small and highly variable proteins which makes their bioinformatic prediction a formidable task. We present a machine-learning approach for comprehensive Acr prediction. The model shows high predictive power when tested against an unseen test set and was employed to predict 2,500 candidate Acr families. Experimental validation of top candidates revealed two unknown Acrs (AcrIC9, IC10) and three other top candidates were coincidentally identified and found to possess anti-CRISPR activity. These results substantially expand the repertoire of predicted Acrs and provide a resource for experimental Acr discovery.
ISSN:	2041-1723 2041-1723