Genome mining for anti-CRISPR operons using machine learning.

ABSTRACT:

Motivation

Encoded by (pro-)viruses, anti-CRISPR (Acr) proteins inhibit the CRISPR-Cas immune system of their prokaryotic hosts. As a result, Acr proteins can be employed to develop more controllable CRISPR-Cas genome editing tools. Recent studies revealed that known acr genes often coexist with other acr genes and with phage structural genes within the same operon. For example, we found that 47 of 98 known acr genes (or their homologs) co-exist in the same operons. None of the current Acr prediction tools have considered this important genomic context feature. We have developed a new software tool AOminer to facilitate the improved discovery of new Acrs by fully exploiting the genomic context of known acr genes and their homologs.

Results

AOminer is the first machine learni

SUBMITTER: Yang B 

PROVIDER: S-EPMC10196667 | biostudies-literature | 2023 May

REPOSITORIES: biostudies-literature