Genomic dissection of the bacterial population underlyingKlebsiella pneumoniaeinfections in hospital patients: insights into an opportunistic pathogen

Abstract

Klebsiella pneumoniae is a major cause of opportunistic healthcare-associated infections, which are increasingly complicated by the presence of extended-spectrum beta-lactamases (ESBLs) and carbapenem resistance. We conducted a year-long prospective surveillance study of K. pneumoniae clinical isolates identified in a hospital microbiological diagnostic laboratory. Disease burden was two-thirds urinary tract infections (UTI; associated with female sex and age), followed by pneumonia (15%), wound (10%) and disseminated infections/sepsis (10%). Whole-genome sequencing (WGS) revealed a diverse pathogen population, including other species within the K. pneumoniae complex (18%). Several infections were caused by K. variicola/K. pneumoniae species hybrids, one of which showed evidence of nosocomial transmission, indicating fitness to transmit and cause disease despite a lack of acquired antimicrobial resistance (AMR). A wide range of AMR phenotypes were observed and, in most cases, corresponding mechanisms were identified in the genomes, mainly in the form of plasmid-borne genes. ESBLs were correlated with presence of other acquired AMR genes (median 10). Bacterial genomic features associated with nosocomial onset of disease were ESBL genes (OR 2.34, p=0.015) and rhamnose-positive capsules (OR 3.12, p<0.001). Virulence plasmid-encoded features (aerobactin, hypermucoidy) were rare (<3%), and mostly present in community-onset cases. WGS-confirmed nosocomial transmission was rare (10% of cases) but strongly associated with ESBLs (OR 21, p<1x10-11). We estimate 28% risk of onward nosocomial transmission for ESBL-positive strains vs 1.7% for ESBL-negative strains. These data indicate the underlying burden of K. pneumoniae disease in hospitalised patients is due largely to opportunistic infections with diverse strains. However, we also identified several successful lineages that were overrepresented but not due to nosocomial transmission. These lineages were associated with ESBL, yersiniabactin, mannose+ K loci and rhamnose- K loci; most are also common in public clinical genome collections, suggesting enhanced propensity for colonisation and spread in the human population.

Epidemiology and genomic analysis of Klebsiella oxytoca from a single hospital network in Australia

“…To our knowledge, this is the first description of the population structure of a non-outbreak collection of isolates identified as K. oxytoca from a single hospital network. Isolates from urine were most common, followed by isolates from respiratory and wound specimens, similar to what has been observed for a collection of KpSC infections from the same hospital across a similar time period (38).…”

Nanopore-only assemblies for genomic surveillance of the global priority drug-resistant pathogen, Klebsiella pneumoniae

“…However, as Pathogenwatch calls SNPs only in 1,972 core genes and not genome-wide, we compared the SNP distances calculated by Pathogenwatch with genome-wide SNP counts obtained by mapping short reads to a reference genome to determine the equivalent cut-off for clustering analysis using Pathogenwatch distances. To do this, we used the genome- wide SNP alignment generated previously for n=270 K. pneumoniae isolated at Alfred Health, based on mapping of Illumina reads to the K. pneumoniae NTUH-K2044 reference genome using the RedDog pipeline [68] (see full details in [41]). Pairwise SNP counts were extracted using snp-dist [69].…”

“…Pairwise SNP counts were extracted using snp-dist [69]. Assemblies for these 270 genomes (assembled from Illumina reads de novo using SPAdes optimised with Unicycler v0.4.74, see full details in [41]) were uploaded to Pathogenwatch, and the pairwise distance matrix was downloaded and compared against that generated from RedDog. We then used R to fit a linear regression model for Pathogenwatch distances as a function of genome-wide mapping-based SNP distances (see Supplementary Figure 1 ).…”

“…We utilised 54 K. pneumoniae that were previously isolated at the Alfred Health Clinical Microbiological Diagnostic Laboratory in Melbourne, Australia, as part of a year-long prospective study of isolates from clinical infections (hospital-wide) and screening swabs (in intensive care and geriatric wards) in the Alfred Health network [41,[46][47][48]. The accession numbers for all genome data analysed in this study are provided in Supplementary Table 1.…”

“…Here, we use a collection of 54 clinical isolates of K. pneumoniae with matched Illumina and ONT data [41] to assess the performance of ONT-only data when used for the prediction of AMR determinants, virulence factors, K/O typing and phylogenetic clustering analysis. Current read-based genotyping tools for Illumina data (such as ARIBA [42] or SRST2 [43]) are not optimised to be used efficiently on noisy long reads like those produced by ONT.…”