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Anti-CRISPR prediction using deep learning reveals an inhibitor of Cas13b nucleases.

Authors :
Wandera KG
Alkhnbashi OS
Bassett HVI
Mitrofanov A
Hauns S
Migur A
Backofen R
Beisel CL
Source :
Molecular cell [Mol Cell] 2022 Jul 21; Vol. 82 (14), pp. 2714-2726.e4. Date of Electronic Publication: 2022 May 31.
Publication Year :
2022

Abstract

As part of the ongoing bacterial-phage arms race, CRISPR-Cas systems in bacteria clear invading phages whereas anti-CRISPR proteins (Acrs) in phages inhibit CRISPR defenses. Known Acrs have proven extremely diverse, complicating their identification. Here, we report a deep learning algorithm for Acr identification that revealed an Acr against type VI-B CRISPR-Cas systems. The algorithm predicted numerous putative Acrs spanning almost all CRISPR-Cas types and subtypes, including over 7,000 putative type IV and VI Acrs not predicted by other algorithms. By performing a cell-free screen for Acr hits against type VI-B systems, we identified a potent inhibitor of Cas13b nucleases we named AcrVIB1. AcrVIB1 blocks Cas13b-mediated defense against a targeted plasmid and lytic phage, and its inhibitory function principally occurs upstream of ribonucleoprotein complex formation. Overall, our work helps expand the known Acr universe, aiding our understanding of the bacteria-phage arms race and the use of Acrs to control CRISPR technologies.<br />Competing Interests: Declaration of interests C.L.B. is a co-founder and member of the Scientific Advisory Board for Locus Biosciences as well as a member of the Scientific Advisory Board for Benson Hill.<br /> (Copyright © 2022 Elsevier Inc. All rights reserved.)

Details

Language :
English
ISSN :
1097-4164
Volume :
82
Issue :
14
Database :
MEDLINE
Journal :
Molecular cell
Publication Type :
Academic Journal
Accession number :
35649413
Full Text :
https://doi.org/10.1016/j.molcel.2022.05.003