Developing approaches for search and analysis of CRISPR-Cas systems on the example of <i>Klebsiella pneumoniae</i> strains as a basis for creating personalized bacteriophage therapy

Abstract

This paper proposes an algorithm for searching and analyzing the structures of CRISPR-Cas systems of bacteria and screening bacteriophages through spacers in CRISPR cassettes using bioinformatic research methods in the genomes of Klebsiella pneumoniae strains. The aim was to determine and study the structure of CRISPR-Cas systems of bacteria on the example of Klebsiella pneumoniae strains using bioinformatic research methods in order to develop approaches for the selection of target bacteriophages. The research object included 150 genome-wide sequences downloaded from the GenBank database. Of these sequences, CRISPR-Cas systems were detected in 52 strains, which amounted to 34.7%. Using several search algorithms in the CRISPR-Cas systems of the studied strains, the presence of one and two CRISPR cassette was determined in 46.2 and 53.8% of cases, respectively. In all the cases, a complete set of Cas genes characteristic of Type-I Subtype-I-E systems was identified next to the cassettes. The total number of the identified spacers was 1659, of which 281 spacers were repeated in two or more CRISPR loci, while 505 spacers had no repeats. The number of spacers in the cassettes ranged from 4 to 64. The analysis of the spacer composition in CRISPR cassettes of antibiotic-resistant and hospital strains provided information on their evolutionary history and on the bacteriophages which are targeted by their CRISPR systems. The developed bioinformatic analysis algorithm enables creating a platform for the development of personalized bacteriophage therapy technologies.