Background: Mapping the local etiology and susceptibility of common pathogens causing complicated urinary tract infection (cUTI) is important for promoting evidence-based antimicrobial prescribing. Evaluating the prevalence of extended-spectrum beta-lactamase (ESBL), AmpC beta-lactamase (AmpC), and carbapenemase-producing
Enterobacterales (CPEs) is equally important as it informs treatment guidelines and empiric management. Whole genome sequencing (WGS) enhances antimicrobial resistance (AMR) surveillance by complementing phenotypic antimicrobial susceptibility testing, offering deeper insights into resistance mechanisms, transmissions, and evolutions. Integrating it into routine AMR monitoring can significantly improve global efforts to combat antimicrobial resistance.
Methods: Antimicrobial susceptibility profiles of isolates from cUTI were collected from patients presenting with Sultan Qaboos University Hospital, Muscat and Suhar Hospital, Suhar, Oman. Automated systems as well as manual methods were used for detection of ESBL, AmpC, and CPE. ESBLs, AmpC β-lactamases, and CPEs were further detected by manual methods: double-disk synergy test for ESBL; disk approximation assay and D69C AmpC detection set for AmpC, and mCIM and
KPC/IMP/NDM/VIM/OXA-48 Combo test kit for CPE. WGS was carried out in 11 FOX-resistant
E. coli and (22 carbapenem-resistant
K. pneumoniae) isolates with varying susceptibilities to identify circulating clades, AMR genes, and plasmids. Bioinformatic analysis was performed using online tools.
Results: The susceptibility patterns of
E. coli from cUTI were as follows: nitrofurantoin (96%), fosfomycin (100%), fluoroquinolones (44%), aminoglycosides (93%), piperacillin-tazobactam (95%), and carbapenems (98%). In comparison, susceptibility rates of
K. pneumoniae were far lower: nitrofurantoin (38%), fosfomycin (89%), aminoglycosides (82%), piperacillin-tazobactam (72%), and carbapenems (83%).
K. pneumoniae, however, was more susceptible to fluoroquinolones at 47% in comparison to
E. coli. The prevalence of ESBL among
E. coli and
K. pneumoniae was 37.2% and CRE was 6.2% while the estimated prevalence of AmpC was 5.4%. It was observed that
E. coli was the predominant ESBL and AmpC producer, while
K. pneumoniae was the major carbapenem-resistant
Enterobacterales (CREs) producer. No predominant multi-locus sequence typing (MLST) lineage was observed in AmpC-producing
E. coli with nine
E. coli MLST lineages being identified from eleven isolates:
ST-10,
ST-69,
ST-77,
ST-131,
ST-156,
ST-167,
ST-361,
ST-1125, and
ST-2520. On the other hand, a less diverse MLST spectrum (
ST-2096,
ST-231,
ST-147,
ST-1770, and
ST-111) was observed in the CRE
K. pneumoniae. Among the five MLST lineages,
ST-2096 (twelve isolates) and
ST-147 (seven isolates) predominated. WGS revealed that
DHA-1 was the predominant plasmid-mediated
AmpC gene in
E. coli, while
OXA-232 and
NDM-5 were the most common carbapenemase genes in
K. pneumoniae. All
E. coli DHA-1-positive isolates co-harbored the quinolone resistance gene
qnrB4 and the sulfonamide resistance gene
sul1 while no aminoglycoside resistance genes were detected. The majority of CPE CRE
K. pneumoniae carried other β-lactamase genes, such as
blaCTX-M-15,
blaSHV, and
blaTEM; all co-harbored the quinolone resistance gene
OqxAB; and 77% carried the aminoglycoside resistance gene
armA.
Conclusions: Our results suggest that fosfomycin is an excellent empiric choice for treating complicated cystitis caused by both
E. coli and
K. pneumoniae, while nitrofurantoin is an appropriate choice for
E. coli cystitis but not for
K. pneumoniae. Aminoglycosides and piperacillin-tazobactam are excellent intravenous alternatives that spare carbapenems.
DHA-1 was the predominant AmpC in
E. coli, while
OXA-232 and
NDM-5 were the predominant carbapenemases in
K. pneumoniae. In AmpC-producing
E. coli, no MLST predominated, suggesting a significant flux in
E. coli with lack of stable clades in this region. In contrast,
ST-2096 and
ST-147 predominated in CRE
Klebsiella pneumoniae, suggesting a stable circulation of these in Oman. WGS profiling provides a deeper understanding of the genetic basis of resistance and enhances surveillance and offers comprehensive insights into pathogen evolution and transmission patterns.
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