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MicrobiologyFrontiers in Microbiology
Peer-reviewed journal article

The LAMP-CRISPR-Cas13a technique for detecting CBASS-mechanism of phage resistance in bacteria

Concha Ortiz-CartagenaiD, Patricia Fernández-Grela, Lucía ArmániD, Lucía BlascoiD, Daniel Pablo‐MarcosiD, Inés BleriotiD, Laura Fernández-GarcíaiD, Clara Ibarguren-QuilesiD, Felipe Fernández-CuencaiD, Antonio Barrio-PujanteiD, Belén AraciliD, Jorge Calvo, María TomásiD

Abstract

Antimicrobial resistance (AMR) is an important threat to public health that has led to the development of innovative alternative treatments for bacterial infections, such as phage therapy. However, one of the greatest disadvantages of phage therapy is the generation of phage-resistant bacterial mutants via bacterial defence mechanisms, which are mainly contained in genomic islands (GIs) and controlled by the quorum sensing (QS) network. In this study, 309 pathogenic islands (PAIs) harbouring a total of 22.1 % of proteins related to anti-phage defence (APD) were detected in the genome of 48 K. pneumoniae strains. Several type I and type II CBASS systems were also detected in the genome of the 48 K. pneumoniae strains, but only 2 type II CBASS systems were located in PAIs. We constructed a knockout K. pneumoniae strain, not expressing the cyclase gene from the type II CBASS system present in PAIs, to study the regulatory role of QS in expressing the gene. As the anti-phage CBASS system is an abortive infection (Abi) system, the role of the type II CBASS system in regulating cell viability was assessed. The knockout strain was confirmed by targeting the LAMP-CRISPR-Cas13a technique specifically to the cyclase gene, and the same protocol was also used to detect the gene of the main cyclase in these type I CBASS systems, i.e. APECO1. The study findings demonstrate the regulatory role of the QS network in anti-phage defence systems. Finally, this is the first work which development an innovative biotechnological application for the LAMP-CRISPR-Cas13a rapid-technique (<2 hours) in optimizing phage therapy by detecting bacterial resistance mechanisms, by predicting the potential inefficacy of a therapeutic phage and thus improving patient prognosis.

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