Endemic High-Risk Clone ST277 Is Related to the Spread of SPM-1-Producing Pseudomonas aeruginosa during the COVID-19 Pandemic Period in Northern Brazil.
Pabllo Antonny Silva Dos SantosYan Corrêa RodriguesDavi Josué MarconAmália Raiana Fonseca LobatoThalyta Braga CazuzaMaria Isabel Montoril GouveiaMarcos Jessé Abrahão SilvaAlex Brito SouzaLuana Nepomuceno Gondim Costa LimaAna Judith Pires Garcia QuaresmaDanielle Murici BrasilienseKarla Valéria Batista LimaPublished in: Microorganisms (2023)
Pseudomonas aeruginosa is a high-priority bacterial agent that causes healthcare-acquired infections (HAIs), which often leads to serious infections and poor prognosis in vulnerable patients. Its increasing resistance to antimicrobials, associated with SPM production, is a case of public health concern. Therefore, this study aims to determine the antimicrobial resistance, virulence, and genotyping features of P. aeruginosa strains producing SPM-1 in the Northern region of Brazil. To determine the presence of virulence and resistance genes, the PCR technique was used. For the susceptibility profile of antimicrobials, the Kirby-Bauer disk diffusion method was performed on Mueller-Hinton agar. The MLST technique was used to define the ST of the isolates. The exoS + /exoU - virulotype was standard for all strains, with the aprA , lasA , toxA , exoS , exoT, and exoY genes as the most prevalent. All the isolates showed an MDR or XDR profile against the six classes of antimicrobials tested. HRC ST277 played a major role in spreading the SPM-1-producing P. aeruginosa strains.
Keyphrases
- pseudomonas aeruginosa
- antimicrobial resistance
- poor prognosis
- escherichia coli
- biofilm formation
- public health
- cystic fibrosis
- genome wide
- healthcare
- long non coding rna
- end stage renal disease
- acinetobacter baumannii
- ejection fraction
- chronic kidney disease
- staphylococcus aureus
- newly diagnosed
- drug resistant
- multidrug resistant
- genome wide identification
- gene expression
- dna methylation
- patient reported outcomes
- high throughput
- bioinformatics analysis
- transcription factor
- single cell
- genome wide analysis