Antimicrobial Susceptibility and Molecular Features of Colonizing Isolates of Pseudomonas aeruginosa and the Report of a Novel Sequence Type (ST) 3910 from Thailand.
Arnon ChukamnerdRattanaruji PomwisedSarunyou ChusriKamonnut SingkhamananSanicha ChumtongKongpop JeenkeawpiamChanida SakunrangKuwanhusna SaroengPhanvasri SaengsuwanMonwadee WonglapsuwanSiriporn LalakornPublished in: Antibiotics (Basel, Switzerland) (2023)
Pseudomonas aeruginosa is an important pathogen as it can cause hospital-acquired infections. Additionally, it can also colonize in patients and in other various environments. Hence, this study aimed to investigate the antimicrobial susceptibility, and to study the molecular features, of colonizing isolates of P. aeruginosa from Songklanagarind Hospital, Thailand. Genomic DNA extraction, whole-genome sequencing (WGS), and bioinformatics analysis were performed in all studied isolates. The findings demonstrated that the majority of isolates were non-susceptible to colistin and carbapenem. For in silico study, multilocus sequence typing (MLST) revealed one novel sequence type (ST) 3910 and multiple defined STs. The isolates carried several antimicrobial resistance genes ( bla OXA-50 , aph(3')-IIb , etc.) and virulence-associated genes ( fleN , waaA , etc.). CRISPR-Cas sequences with different spacers and integrated bacteriophage sequences were also identified in these isolates. Very high SNPs were found in the alignments of the novel ST-3910 isolate with other isolates. A comparative genomic analysis exhibited phylogenetic clustering of our colonizing isolates with clinical isolates from many countries. Interestingly, ST-3981, ST-3982, ST-3983, ST-3984, ST-3985, ST-3986, ST-3986, ST-3986, ST-3987, and ST-3988, the new STs from published genomes, were assigned in this study. In conclusion, this WGS data might be useful for tracking the spread of P. aeruginosa colonizing isolates.
Keyphrases
- pseudomonas aeruginosa
- genetic diversity
- antimicrobial resistance
- crispr cas
- healthcare
- cystic fibrosis
- genome wide
- bioinformatics analysis
- end stage renal disease
- emergency department
- single cell
- randomized controlled trial
- systematic review
- machine learning
- newly diagnosed
- biofilm formation
- ejection fraction
- deep learning
- molecular docking
- genome editing
- artificial intelligence
- peritoneal dialysis
- transcription factor
- molecular dynamics simulations
- gram negative
- circulating tumor
- big data