Genomic diversity and antimicrobial resistance in clinical Klebsiella pneumoniae isolates from tertiary hospitals in Southern Ghana.

OBJECTIVES: Comprehensive data on the genomic epidemiology of hospital-associated Klebsiella pneumoniae in Ghana are scarce. This study investigated the genomic diversity, antimicrobial resistance patterns, and clonal relationships of 103 clinical K. pneumoniae isolates from five tertiary hospitals in Southern Ghana-predominantly from paediatric patients aged under 5 years (67/103; 65%), with the majority collected from urine (32/103; 31%) and blood (25/103; 24%) cultures. METHODS: We generated hybrid Nanopore-Illumina assemblies and employed Pathogenwatch for genotyping via Kaptive [capsular (K) locus and lipopolysaccharide (O) antigens] and Kleborate (antimicrobial resistance and hypervirulence) and determined clonal relationships using core-genome MLST (cgMLST). RESULTS: Of 44 distinct STs detected, ST133 was the most common, comprising 23% of isolates (n = 23/103). KL116 (28/103; 27%) and O1 (66/103; 64%) were the most prevalent K-locus and O-antigen types. Single-linkage clustering highlighted the global spread of MDR clones such as ST15, ST307, ST17, ST11, ST101 and ST48, with minimal allele differences (1-5) from publicly available genomes worldwide. Conversely, 17 isolates constituted novel clonal groups and lacked close relatives among publicly available genomes, displaying unique genetic diversity within our study population. A significant proportion of isolates (88/103; 85%) carried resistance genes for ≥3 antibiotic classes, with the blaCTX-M-15 gene present in 78% (n = 80/103). Carbapenem resistance, predominantly due to blaOXA-181 and blaNDM-1 genes, was found in 10% (n = 10/103) of the isolates. CONCLUSIONS: Our findings reveal a complex genomic landscape of K. pneumoniae in Southern Ghana, underscoring the critical need for ongoing genomic surveillance to manage the substantial burden of antimicrobial resistance.

Detection of hidden antibiotic resistance through real-time genomics.

Real-time genomics through nanopore sequencing holds the promise of fast antibiotic resistance prediction directly in the clinical setting. However, concerns about the accuracy of genomics-based resistance predictions persist, particularly when compared to traditional, clinically established diagnostic methods. Here, we leverage the case of a multi-drug resistant Klebsiella pneumoniae infection to demonstrate how real-time genomics can enhance the accuracy of antibiotic resistance profiling in complex infection scenarios. Our results show that unlike established diagnostics, nanopore sequencing data analysis can accurately detect low-abundance plasmid-mediated resistance, which often remains undetected by conventional methods. This capability has direct implications for clinical practice, where such "hidden" resistance profiles can critically influence treatment decisions. Consequently, the rapid, in situ application of real-time genomics holds significant promise for improving clinical decision-making and patient outcomes.