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Infections caused by metallo-beta-lactamase-producing organisms (MBLs) are a global health threat. Our understanding of transmission dynamics and how MBLs establish endemicity remains limited. We analysed two decades of bla IMP-4 evolution in a hospital using sequence data from 270 clinical and environmental isolates (including 169 completed genomes) and identified the bla IMP-4 gene across 7 Gram-negative genera, 68 bacterial strains and 7 distinct plasmid types. We showed how an initial multi-species outbreak of conserved IncC plasmids (95 genomes across 37 strains) allowed endemicity to be established through the ability of bla IMP-4 to disseminate in successful strain-genetic setting pairs we termed propagators, in particular Serratia marcescens and Enterobacter hormaechei . From this reservoir, bla IMP-4 persisted through diversification of genetic settings that resulted from transfer of bla IMP-4 plasmids between bacterial hosts and of the integron carrying bla IMP-4 between plasmids. Our findings provide a framework for understanding endemicity and spread of MBLs and may have broader applicability to other carbapenemase-producing organisms. Resistance to carbapenems, a class of last-line antibiotics, is a global health threat. This study analysed a two-decade history of carbapenem resistance and identified complex, multi-level (bacterial strain, plasmid, gene) transmission dynamics.

Background Resistance to third-generation cephalosporins, often mediated by extended-spectrum beta-lactamases (ESBLs), is a considerable issue in hospital-associated infections as few drugs remain for treatment. ESBL genes are often located on large plasmids that transfer horizontally between strains and species of Enterobacteriaceae and frequently confer resistance to additional drug classes. Whilst plasmid transmission is recognised to occur in the hospital setting, the frequency and impact of plasmid transmission on infection burden, compared to ESBL + strain transmission, is not well understood. Methods We sequenced the genomes of clinical and carriage isolates of Klebsiella pneumoniae species complex from a year-long hospital surveillance study to investigate ESBL burden and plasmid transmission in an Australian hospital. Long-term persistence of a key transmitted ESBL + plasmid was investigated via sequencing of ceftriaxone-resistant isolates during 4 years of follow-up, beginning 3 years after the initial study. Results We found 25 distinct ESBL plasmids. We identified one plasmid, which we called Plasmid A, that carried bla CTX-M-15 in an IncF backbone similar to pKPN-307. Plasmid A was transmitted at least four times into different Klebsiella species/lineages and was responsible for half of all ESBL episodes during the initial 1-year study period. Three of the Plasmid A-positive strains persisted locally 3–6 years later, and Plasmid A was detected in two additional strain backgrounds. Overall Plasmid A accounted for 21% of ESBL + infections in the follow-up period. Conclusions Here, we systematically surveyed ESBL strain and plasmid transmission over 1 year in a single hospital network. Whilst ESBL plasmid transmission events were rare in this setting, they had a significant and sustained impact on the burden of ceftriaxone-resistant and multidrug-resistant infections. If onward transmission of Plasmid A-carrying strains could have been prevented, this may have reduced the number of opportunities for Plasmid A to transmit and create novel ESBL + strains, as well as reducing overall ESBL infection burden.

Objectives:New Delhi metallo-β-lactamases (NDMs) are major contributors to the spread of carbapenem resistance globally. In Australia, NDMs were previously associated with international travel, but from 2019 we noted increasing incidence of NDM-positive clinical isolates. We investigated the clinical and genomic epidemiology of NDM carriage at a tertiary-care Australian hospital from 2016 to 2021.Methods:We identified 49 patients with 84 NDM-carrying isolates in an institutional database, and we collected clinical data from electronic medical record. Short- and long-read whole genome sequencing was performed on all isolates. Completed genome assemblies were used to assess the genetic setting of blaNDM genes and to compare NDM plasmids.Results:Of 49 patients, 38 (78%) were identified in 2019–2021 and only 11 (29%) of 38 reported prior travel, compared with 9 (82%) of 11 in 2016–2018 (P = .037). In patients with NDM infection, the crude 7-day mortality rate was 0% and the 30-day mortality rate was 14% (2 of 14 patients). NDMs were noted in 41 bacterial strains (ie, species and sequence type combinations). Across 13 plasmid groups, 4 NDM variants were detected: blaNDM-1, blaNDM-4, blaNDM-5, and blaNDM-7. We noted a change from a diverse NDM plasmid repertoire in 2016–2018 to the emergence of conserved blaNDM-1 IncN and blaNDM-7 IncX3 epidemic plasmids, with interstrain spread in 2019–2021. These plasmids were noted in 19 (50%) of 38 patients and 35 (51%) of 68 genomes in 2019–2021.Conclusions:Increased NDM case numbers were due to local circulation of 2 epidemic plasmids with extensive interstrain transfer. Our findings underscore the challenges of outbreak detection when horizontal transmission of plasmids is the primary mode of spread.

RNAseq data can be used to infer genetic variants, yet its use for estimating genetic population structure remains underexplored. Here, we construct a freely available computational tool (RGStraP) to estimate RNAseq-based genetic principal components (RG-PCs) and assess whether RG-PCs can be used to control for population structure in gene expression analyses. Using whole blood samples from understudied Nepalese populations and the Geuvadis study, we show that RG-PCs had comparable results to paired array-based genotypes, with high genotype concordance and high correlations of genetic principal components, capturing subpopulations within the dataset. In differential gene expression analysis, we found that inclusion of RG-PCs as covariates reduced test statistic inflation. Our paper demonstrates that genetic population structure can be directly inferred and controlled for using RNAseq data, thus facilitating improved retrospective and future analyses of transcriptomic data. RGStraP is a computational pipeline to estimate RNA-seq-based genetic principal components and assess whether these can be used to control for population structure in gene expression analyses.

New Delhi metallo-β-lactamases (NDMs) are major contributors to the spread of carbapenem resistance globally. In Australia, NDMs were previously associated with international travel, but from 2019 we noted increasing incidence of NDM-positive clinical isolates. We investigated the clinical and genomic epidemiology of NDM carriage at a tertiary-care Australian hospital from 2016 to 2021. We identified 49 patients with 84 NDM-carrying isolates in an institutional database, and we collected clinical data from electronic medical record. Short- and long-read whole genome sequencing was performed on all isolates. Completed genome assemblies were used to assess the genetic setting of genes and to compare NDM plasmids. Of 49 patients, 38 (78%) were identified in 2019-2021 and only 11 (29%) of 38 reported prior travel, compared with 9 (82%) of 11 in 2016-2018 ( .037). In patients with NDM infection, the crude 7-day mortality rate was 0% and the 30-day mortality rate was 14% (2 of 14 patients). NDMs were noted in 41 bacterial strains (ie, species and sequence type combinations). Across 13 plasmid groups, 4 NDM variants were detected: , , , and . We noted a change from a diverse NDM plasmid repertoire in 2016-2018 to the emergence of conserved IncN and IncX3 epidemic plasmids, with interstrain spread in 2019-2021. These plasmids were noted in 19 (50%) of 38 patients and 35 (51%) of 68 genomes in 2019-2021. Increased NDM case numbers were due to local circulation of 2 epidemic plasmids with extensive interstrain transfer. Our findings underscore the challenges of outbreak detection when horizontal transmission of plasmids is the primary mode of spread.

Abstract Objectives Antimicrobial resistance (AMR) is a global health threat, with third-generation cephalosporin–resistant (3GCR) and carbapenem-resistant infections of particular concern. There is currently a lack of genomic data on AMR organisms in the Pacific region. Methods We aimed to address this gap by examining the genetic diversity of a collection of 788 Gram-negative and Gram-positive clinical isolates collected between July 2020 and October 2022 from a single hospital in Suva, Fiji. We sampled sensitive and resistant isolates, focusing on 3GCR and carbapenem-resistant Gram-negatives, and methicillin-resistant Staphylococcus and vancomycin-resistant Enterococcus. Results We detected 29 distinct species across 12 different genera. Amongst Gram-negative genomes, Klebsiella pneumoniae, Escherichia coli, Acinetobacter baumannii and Pseudomonas aeruginosa were the most common. Carbapenem resistance was mostly detected in A. baumannii ST2 and P. aeruginosa ST773, with both STs carrying NDM-1 and showing evidence of transmission within Fiji. Carbapenem resistance was relatively rare amongst the Enterobacterales; however, we observed evidence of transmission of OXA-232–carrying K. pneumoniae ST395 and NDM-7 E. coli ST410. For Gram-positive bacteria, Staphylococcus aureus ST1 was the dominant clone, and phylogenetic analysis revealed a single clade harbouring the majority of Fijian genomes, with close relationships to genomes from neighbouring Samoa. Enterococcus was relatively rare, with only 22 genomes detected. Conclusions This study provides crucial genomic data on AMR organisms in Fiji, highlighting the diversity of resistant species in the region. Local transmission of four carbapenem-resistant clones within Fiji was observed, underscoring the importance of local spread of these resistant strains.

Abstract Motivation Klebsiella species are increasingly multidrug resistant pathogens affecting human and animal health and are widely distributed in the environment. Among these, the Klebsiella pneumoniae species complex (KpSC), which includes seven phylogroups, is an important cause of community and hospital infections. In addition, the Klebsiella oxytoca species complex (KoSC) also causes hospital infections and antibiotic-associated haemorrhagic colitis. The unsuitability of widely used clinical microbiology methods to distinguish species within each of these species complexes leads to high rates of misidentifications that are masking the true clinical significance and potential epidemiological specificities of individual species. Results We developed a web-based tool, Klebsiella MALDI TypeR, a platform-independent and user-friendly application that enables uploading raw data from MALDI-TOF mass spectrometer to identify Klebsiella isolates at the species complex and phylogroup levels. The tool is based on a database of previously identified biomarkers that are specific for either the species complex, individual phylogroups, or related phylogroups, and is available at https://maldityper.pasteur.fr. Competing Interest Statement The authors have declared no competing interest. Footnotes * http://hub05.hosting.pasteur.fr/sbridel/klebsiellatyper/

Infections caused by metallo-beta-lactamase-producing organisms (MBLs) are a global health threat. Our understanding of transmission dynamics and how MBLs establish endemicity remains limited. We analysed two decades of blaIMP-4 evolution in a hospital using sequence data from 270 clinical and environmental isolates (including 169 completed genomes) and identified extreme gene promiscuity across 7 Gram-negative genera, 68 bacterial strains and 7 distinct plasmid types. An initial multi-species outbreak of conserved IncC plasmids (95 genomes across 37 strains) allowed endemicity to be established through the ability of blaIMP-4 to disseminate in successful strain-genetic setting pairs we termed ‘propagators’, in particular Serratia marcescens and Enterobacter hormaechei. From this reservoir, blaIMP-4 persisted through diversification of genetic settings that resulted from transfer of blaIMP-4 plasmids between bacterial hosts and of the integron carrying blaIMP-4 between plasmids. Our findings provide a framework for understanding endemicity and spread of MBLs and may have broader applicability to other carbapenemase-producing organisms.

The Klebsiella pneumoniae species complex (KpSC) is a set of seven Klebsiella taxa which are found in a variety of niches, and are an important cause of opportunistic healthcare-associated infections in humans. Due to increasing rates of multi-drug resistance within the KpSC, there is a growing interest in better understanding the biology and metabolism of these organisms to inform novel control strategies. We collated 37 sequenced KpSC isolates isolated from a variety of niches, representing all seven taxa. We generated strain-specific genome scale metabolic models (GEMs) for all 37 isolates and simulated growth phenotypes on 511 distinct carbon, nitrogen, sulphur and phosphorus substrates. Models were curated and their accuracy assessed using matched phenotypic growth data for 94 substrates (median accuracy of 96%). We explored species-specific growth capabilities and examined the impact of all possible single gene deletions on growth in 145 core carbon substrates. These analyses revealed multiple strain-specific differences, within and between species and highlight the importance of selecting a diverse range of strains when exploring KpSC metabolism. This diverse set of highly accurate GEMs could be used to inform novel drug design, enhance genomic analyses, and identify novel virulence and resistance determinants. We envisage that these 37 curated strain-specific GEMs, covering all seven taxa of the KpSC, provide a valuable resource to the Klebsiella research community.

RNAseq data can be used to infer genetic variants, yet its use for estimating genetic population structure remains underexplored. Here, we construct a freely available computational tool (RGStraP) to estimate RNAseq-based genetic principal components (RG-PCs) and assess whether RG-PCs can be used to control for population structure in gene expression analyses. Using whole blood samples from understudied Nepalese populations and the Geuvadis study, we show that RG-PCs had comparable results to paired array-based genotypes, with high genotype concordance and high correlations of genetic principal components, capturing subpopulations within the dataset. In differential gene expression analysis, we found that inclusion of RG-PCs as covariates reduced test statistic inflation. Our paper demonstrates that genetic population structure can be directly inferred and controlled for using RNAseq data, thus facilitating improved retrospective and future analyses of transcriptomic data.