Detection and Analysis of CRISPR-Cas-System Structures in Genome of Plasmid pYC-1 of <i>Bacillus thuringiensis </i>Strain YC-10
The aim of this work was to search and analyze the structures of the CRISPR-Cas system in the genome of the plasmid pYC-1 from the strain Bacillus thuringiensis YC-10 using a selected algorithm of bioinformatics software. A search and analysis of the structures of the CRISPR-Cas-system in the genome of the plasmid pYC-1, which is a megaplasmid of thestrain Bacillus thuringiensis YC-10, was carried out. The bioinformatical search for CRISPR-Cas-system structures included three stages: identification of cas-genes, detection of CRISPR- cassettes and analysis of their structures. Identification of cas-genes was carried out through their amino acid profile using the MacSyFinder program. The detection and analysis of CRISPR cassettes was performed using four applications: 1) CRISPRFinder; 2) CRISPRDetect; 3) PILER-CR; 4) CRISPR Recognition Tool (CRT). A consensus structure for multiple alignment of inter-spacer repeats was obtained and visualized in WebLogo 3. The position of the consensus sequence in the classification of CRISPR-associated repeats was determined through the CRISPRmap web service (v1.3.0). The analysis of the structure of the CRISPR locus was performed using the software platform Artemis (ver. 17.0.1). The type of CRISPR-Cas system was determined in accordance with the latest version of the classification [Koonin et.al. 2017]. As a result of a software search in megaplasmid pYC-1, one CRISPR locus was found, classified as Class I, type I, subtype C. Two CRISPR cassettes and four CRISPR-associated genes were identified. The analysis of the structure of CRISPR-cassettes. The decoded spacer sequences provide information about bacteriophages and foreign plasmids to which this bacterial strain may be resistant. The presence of a CRISPR-Cas system in the plasmid genome may indicate a possible transfer of a given locus from the bacterial chromosome to the plasmid. It can also be assumed that these systems can be transmitted by conjugation in bacterial communities. The bioinformatics algorithm used in this work showed a high efficiency of its use for the detection of CRISPR-Cas-system structures in extrachromosomal elements of the genome.