Computational design of guide RNAs and vector to knockout LasR gene of Pseudomonas aeruginosa

CRISPR-cas9 genome editing has received much attention in recent years due to its wide applications to treat various genetic disorders, cancer, and infectious diseases caused by harmful pathogens. Pseudomonas aeruginosa is one of the most prominent opportunistic pathogens that cause major concern in health care due to its antibiotic resistance. Quorum sensing inhibition is an effective means of treating this multidrug-resistant bacterial infection. In the present work, an in silico gene editing strategy was performed to knock out the LasR gene, responsible for regulating the expression of virulence-associated genes and biofilm formation in P. aeruginosa. To design appropriate guide RNA (gRNA) hits, the study explores four computational tools: ChopChop, Cas-Designer, Crispor, and Benchling which determine 18 gRNA hits out of 102 gRNAs, 39 hits out of 115, 6 hits out of 115, and 15 hits out of 115, respectively. About 19 hits that satisfy all the parameters mentioned in more than one tool were selected for further analysis. Thereafter, analysis of the 19 hits recommends gRNAs 1, 8, 14, 16, 17, and 19 as the top hits and subsequently, secondary structure analysis of the top hits using the RNAfold server ascertained gRNAs 1 and 16 as the best lead gRNAs. In addition, target-specific oligos and single guide RNAs (sgRNAs) for the selected leads were designed using the NEBiocalculator, followed by the in silico construction of the guide RNA expression vector using SnapGene software. However, the guide RNAs designed by computational methods need to be tested in vitro to determine their efficiency in knocking out the LasR gene.