Biology subjects

Gorrie, C. L.

Publications and source records attributed to Gorrie, C. L..

11 recordsLinked to original sources

bioRxiv2025

Ciprofloxacin resistance in Klebsiella pneumoniae: phenotype prediction from genotype and global distribution of resistance determinants

BACKGROUNDCiprofloxacin resistant Klebsiella pneumoniae is common or emerging in many geographies, and knowledge of local resistance rates is important for empirical therapy. Whilst there are known K. pneumoniae ciprofloxacin resistance determinants, there is a lack of systematic data on the effect of determinants, alone and in combination, and there are no publicly accessible tools for predicting resistance from whole genome sequence data. METHODSThe KlebNET-GSP AMR Genotype-Phenotype Group aggregated a matched genotype-phenotype dataset of n=12,167 K. pneumoniae species complex (KpSC) isolates from 27 countries between 2001-2021. We developed a rules-based classifier to predict ciprofloxacin resistance by categorizing the number of quinolone resistance determining regions mutations in gyrA and parC, the number of plasmid-mediated quinolone resistance genes, and the presence/absence of aac(6')-Ib-cr (which can acetylate ciprofloxacin). Predictive performance was assessed using the discovery dataset, for which we re-phenotyped discrepant isolates; and validated using externally contributed datasets (n=7,030 KpSC isolates). RESULTSThe rules-based classifier predicted R vs S/I with categorical agreement, sensitivity, and specificity >96%, and major/very major error rates <4%. Performance was similar across diverse KpSC sources (human, animal, other), species, and intra-species lineages. External validation of the classifier yielded overall 93.12% categorical agreement [95% confidence interval (CI), 92.50-93.74%], 8.65% major errors [95% CI, 7.34-9.97%], and 6.20% very major errors [95% CI, 5.51-6.90%]. We implemented the classifier in Kleborate, a command-line tool that is integrated into the Pathogenwatch web platform. Using this to assess the global distribution of ciprofloxacin resistance determinants in KpSC genomes available in Pathogenwatch (n=31,319, from 109 countries between years 2000-2023), we observed a significant positive association between national quinolone consumption rates and predicted ciprofloxacin resistance (R2=0.20, p=0.004). CONCLUSIONS Ciprofloxacin resistance phenotypes can be reasonably predicted from genotypes, which is sufficient for informing surveillance. However, unexplained resistance remains and accuracy is insufficient for clinical applications. We demonstrate the value of aggregating genotype-phenotype data to explore resistance mechanisms and develop predictors, but highlight complexities in combining phenotype data from different assays and standards.

genomics↗

bioRxiv2025

Benchmarking of tools for resolving plasmids from short-read assemblies for Klebsiella pneumoniae

Plasmids play a critical role in the dissemination of antimicrobial resistance genes and virulence factors in healthcare associated pathogens, such as Klebsiella pneumoniae. Surveillance of these plasmids relies on whole genome sequencing data often generated in clinical and public health settings which frequently use short-read platforms. Therefore, there is a need for robust, scalable tools that can identify and/or reconstruct plasmid sequences from short read data. A myriad of tools already exist to address this problem, however the optimum tool for plasmid identification in K. pneumoniae remains unclear. From a comprehensive search of the literature and code repositories we identified 44 plasmid identification tools, highlighting the uncertainty around best practices. Here, we sought to evaluate these 44 tools to determine which is best suited for reconstructing the plasmidome of K. pneumoniae and related species from the species complex (KpSC). We used a publicly available dataset of 568 diverse KpSC isolates that had both short-read Illumina data and closed hybrid assemblies available. This allowed us to investigate which tools perform best at recovering plasmid sequences when only short-read data is available, whilst knowing the ground truth. From the 44 tools, 34 were excluded as they: were intended for plasmid typing / characterisation (n=3), were not intended for KpSC (n=1), required metagenomic data (n=7), required long read data (n=1), could not be installed (n=13) or could not be run on the command line (n=10). The remaining nine tools had their precision and recall metrics calculated and combined into an overall F1 score. Each individual tool displayed the full range of F1 scores (0 to 1) across our collection of genomes, overall, the best performing was PlaScope followed closely by MOB-suite. Future tools developed in this crowded space should offer meaningful advancements over existing tools and be rigorously benchmarked using standardised datasets that reflect plasmid diversity.

genomics↗

bioRxiv2024

Diversity, functional classification and genotyping of SHV β-lactamases in Klebsiella pneumoniae

Interpreting phenotypes of blaSHV alleles in Klebsiella pneumoniae genomes is complex. While all strains are expected to carry a chromosomal copy conferring resistance to ampicillin, they may also carry mutations in chromosomal blaSHV alleles or additional plasmid-borne blaSHV alleles that have extended-spectrum {beta}-lactamase (ESBL) activity and/or {beta}-lactamase inhibitor (BLI) resistance activity. In addition, the role of individual mutations/amino acid changes is not completely documented or understood. This has led to confusion in the literature and in antimicrobial resistance (AMR) gene databases (e.g., NCBIs Reference Gene Catalog and the {beta}-lactamase database (BLDB)) over the specific functionality of individual SHV protein variants. Therefore, identification of ESBL-producing strains from K. pneumoniae genome data is complicated. Here, we reviewed the experimental evidence for the expansion of SHV enzyme function associated with specific amino-acid substitutions. We then systematically assigned SHV alleles to functional classes (wildtype, ESBL, BLI-resistant) based on the presence of these mutations. This resulted in the re-classification of 37 SHV alleles compared with current assignments in NCBIs Reference Gene Catalog and/or BLDB (21 to wildtype, 12 to ESBL, 4 to BLI-resistant). Phylogenetic and comparative genomic analyses support that; i) SHV-1 (encoded by blaSHV-1) is the ancestral chromosomal variant; ii) ESBL and BLI-resistant variants have evolved multiple times through parallel substitution mutations; iii) ESBL variants are mostly mobilised to plasmids; iv) BLI-resistant variants mostly result from mutations in chromosomal blaSHV. We used matched genome-phenotype data from the KlebNET-GSP Genotype-Phenotype Group to identify 3,999 K. pneumoniae isolates carrying one or more blaSHV alleles but no other acquired {beta}-lactamases, with which we assessed genotype-phenotype relationships for blaSHV. This collection includes human, animal, and environmental isolates collected between 2001 to 2021 from 24 countries across six continents. Our analysis supports that mutations at Ambler sites 238 and 179 confer ESBL activity, while most omega-loop substitutions do not. Our data also provide direct support for wildtype assignment of 67 protein variants, including eight that were noted in public databases as ESBL. We reclassified these eight variants as wildtype, because they lack ESBL-associated mutations, and our phenotype data support susceptibility to 3GCs (SHV-27, SHV-38, SHV-40, SHV-41, SHV-42, SHV-65, SHV-164, SHV-187). The approach and results outlined here have been implemented in Kleborate v2.4.1 (a software tool for genotyping K. pneumoniae from genome assemblies), whereby known and novel blaSHV alleles are classified based on causative mutations. Kleborate v2.4.1 was also updated to include ten novel protein variants from the KlebNET-GSP dataset and all alleles in public databases as of November 2023. This study demonstrates the power of sharing AMR phenotypes alongside genome data to improve understanding of resistance mechanisms. Impact statementSince every K. pneumoniae genome has an intrinsic SHV {beta}-lactamase and may also carry additional mobile forms, the correct interpretation of blaSHV genes detected in genome data can be challenging and can lead to K. pneumoniae being misclassified as ESBL-producing. Here, we use matched K. pneumoniae genome and drug susceptibility data contributed from dozens of studies, together with systematic literature review of experimental evidence, to improve our understanding of blaSHV allele variation and mapping of genotype to phenotype. This study shows the value of coordinated data sharing, in this case via the KlebNET-GSP Genotype-Phenotype Group, to improve our understanding of the evolutionary history and functionality of blaSHV genes. The results are captured in an open-source AMR dictionary utilised by the Kleborate genotyping tool, that could easily be incorporated into or used to update other tools and AMR gene databases. This work is part of the wider efforts of the KlebNET-GSP group to develop and support a unified platform tailored for the analysis and interpretation of K. pneumoniae genomes by a wide range of stakeholders. Data summaryBlaSHV allele sequences and class assignments are distributed with Kleborate, v2.4.1, DOI:10.5281/zenodo.10469001. Table S1 provides a summary of blaSHV alleles, including primary accessions, class-modifying mutations, and supporting evidence for class assignments that differ from NCBIs Reference Gene Catalog or BLDB. Whole genome sequence data are publicly available as reads and/or assemblies, individual accessions are given in Table S2; corresponding genotypes and antibiotic susceptibility phenotypes and measurements are available in Tables S3 and S4, respectively.

genomics↗

bioRxiv2022

Bridging the gap between bioinformatics and the clinical and public health microbiology laboratory: An ISO-accredited genomics workflow for antimicrobial resistance

Realising the promise of genomics to revolutionise routine AMR diagnosis and surveillance has been a long-standing challenge in clinical and public health microbiology. We have directly addressed this issue by creating and validating abritAMR, an ISO-accredited bioinformatics platform for genomics-based bacterial AMR gene detection. abritAMR utilises the NCBI AMRFinderPlus for detection of AMR genes and mutations, with additional features to classify AMR determinants into an antibiotic class. We validated abritAMR by comparing with multiplex PCR or gold-standard reference genomes, together representing 1500 different bacteria across 29 genera and covering 415 antibiotic resistance alleles. We also assessed inference of phenotypic resistance by comparing genomic predictions with agar dilution results for 864 Salmonella spp. Performance of abritAMR was excellent, detecting AMR genes with 99.9% accuracy (95% CI 99.9-99.9%), 97.9% sensitivity (95% CI 97.5-98.4%) and 100% specificity (100-100%). Phenotypic inference of resistance for Salmonella spp. was equally impressive, with 98.9% accuracy (98.7-99.1%). Validation data were submitted to the governing authority and ISO15189 accreditation was achieved. Implementation of abritAMR resulted in streamlined bioinformatics and reporting pathways, and it was readily updated and re-verified with database revisions or changes in reporting requirements. abritAMR is publicly and freely available to assist clinical and public health microbiology laboratories everywhere harness the power of AMR genomics in their professional practice.

microbiology↗

bioRxiv2020

Systematic analysis of key parameters for genomics-based real-time detection and tracking of multidrug-resistant bacteria

BackgroundPairwise single nucleotide polymorphisms (SNPs) are a cornerstone for genomic approaches to multidrug-resistant organisms (MDROs) transmission inference in hospitals. However, the impact of key analysis parameters on these inferences has not been systematically analysed. MethodsWe conducted a multi-hospital 15-month prospective study, sequencing 1537 MDRO genomes for comparison; methicillin-resistant Staphylococcus aureus, vancomycin-resistant Enterococcus faecium, and extended-spectrum beta-lactamase-producing Escherichia coli and Klebsiella pneumoniae. We systematically assessed the impact of sample and reference genome diversity, masking of prophage and regions of recombination, cumulative genome analysis compared to a three-month sliding-window, and the comparative effects each of these had when applying a SNP threshold for inferring likely transmission ([≤]15 SNPs for S. aureus, [≤]25 for other species). FindingsAcross the species, using a reference genome of the same sequence type provided a greater degree of pairwise SNP resolution, compared to species and outgroup-reference alignments that typically resulted in inflated SNP distances and the possibility of missed transmission events. Omitting prophage regions had minimal impacts, however, omitting recombination regions a highly variable effect, often inflating the number of closely related pairs. Estimating pairwise SNP distances was more consistent using a sliding-window than a cumulative approach. InterpretationThe use of a closely-related reference genome, without masking of prophage or recombination regions, and a sliding-window for isolate inclusion is best for accurate and consistent MDRO transmission inference. The increased stability and resolution provided by these approaches means SNP thresholds for putative transmission inference can be more reliably applied among diverse MDROs. FundingThis work was supported by the Melbourne Genomics Health Alliance (funded by the State Government of Victoria, Department of Health and Human Services, and the ten member organizations); an National Health and Medical Research Council (Australia) Partnership grant (GNT1149991) and individual grants from National Health and Medical Research Council (Australia) to NLS (GNT1093468), JCK (GNT1008549) and BPH (GNT1105905).

genomics↗

bioRxiv2019

Genomic interrogation of the burden and transmission of multidrug-resistant pathogens within and across hospital networks

BackgroundMultidrug-resistant organisms (MDROs) disproportionately affect hospitalized patients due to the combination of comorbidities, frequent antimicrobial use, and in-hospital MDRO transmission. Identification of MDRO transmission by hospital microbiology laboratories is difficult due to limitations of existing typing methods.\n\nMethodsWe conducted a prospective multicenter genomics implementation study (8 hospitals, 2800 beds) from 24th April to 18th June 2017 in Melbourne, Australia. Clinical and screening isolates from hospital inpatients were collected for six MDROs (vanA VRE, MRSA, ESBL E. coli [ESBL-Ec] and Klebsiella pneumoniae [ESBL-Kp], and carbapenem-resistant Pseudomonas aeruginosa [CRPa] and Acinetobacter baumannii [CRAb]), sequenced (Illumina NextSeq) and analyzed using open-source tools. MDRO transmission was assessed by genomics (core SNP phylogeny, grouped by species and ST) and compared to epidemiologic data.\n\nResults408 isolates were collected from 358 patients; 47.5% were screening isolates. ESBL-Ec was most common (52.5%), then MRSA (21.6%), vanA VRE (15.7%) and ESBL-Kp (7.6%).\n\nWe define the transmission rate for each MDRO by genomics and epidemiology; 31.6% of all study patients had potential genomic links to other study isolates; 86% of these were confirmed by epidemiologic links (probable or possible transmission). The highest transmission rates occurred with vanA VRE (88.4% of patients).\n\nConclusionsCombining genomics with high-quality epidemiologic data gives substantial insights into the burden and distribution of critical MDROs in hospitals, including in-hospital transmission. By defining transmission rates by genomics, we hope to enable comparisons over time and between sites, and introduce this as a new outcome measure to assess the efficacy of infection control interventions.

genomics↗

bioRxiv2018

Distinct evolutionary dynamics of horizontal gene transfer in drug resistant and virulent clones of Klebsiella pneumoniae

Klebsiella pneumoniae (Kp) has emerged as an important cause of two distinct public health threats: multidrug resistant (MDR) healthcare-associated infections1 and community-acquired invasive infections, particularly pyogenic liver abscess2. The majority of MDR hospital outbreaks are caused by a subset of Kp clones with a high prevalence of acquired antimicrobial resistance (AMR) genes, while the majority of community-acquired invasive infections are caused by hypervirulent clones that rarely harbour acquired AMR genes but have high prevalence of key virulence loci3-5. Worryingly, the last few years have seen increasing reports of convergence of MDR and the key virulence genes within individual Kp strains6, but it is not yet clear whether these represent a transient phenomenon or a significant ongoing threat. Here we perform comparative genomic analyses for 28 distinct Kp clones, including 6 hypervirulent and 8 MDR, to better understand their evolutionary histories and the risks of convergence. We show that MDR clones are highly diverse with frequent chromosomal recombination and gene content variability that far exceeds that of the hypervirulent clones. Consequently, we predict a much greater risk of virulence gene acquisition by MDR Kp clones than of resistance gene acquisition by hypervirulent clones.

microbiology↗

bioRxiv2017

Antimicrobial resistant Klebsiella pneumoniae carriage and infection in specialized geriatric care wards linked to acquisition in the referring hospital

BackgroundKlebsiella pneumoniae is a leading cause of extended-spectrum beta-lactamase (ESBL) producing hospital-associated infections, for which elderly patients are at increased risk.\n\nMethodsWe conducted a 1-year prospective cohort study, in which a third of patients admitted to two geriatric wards in a specialized hospital were recruited and screened for carriage of K. pneumoniae by microbiological culture. Clinical isolates were monitored via the hospital laboratory. Colonizing and clinical isolates were subjected to whole genome sequencing and antimicrobial susceptibility testing.\n\nResultsK. pneumoniae throat carriage prevalence was 4.1%, rectal carriage 10.8% and ESBL carriage 1.7%. K. pneumoniae infection incidence was 1.2%. The isolates were diverse, and most patients were colonized or infected with a unique phylogenetic lineage, with no evidence of transmission in the wards. ESBL strains carried blaCTX-M-15 and belonged to clones associated with hospital-acquired ESBL infections in other countries (ST29, ST323, ST340).\n\nOne also carried the carbapenemase blaIMP-26. Genomic and epidemiological data provided evidence that ESBL strains were acquired in the referring hospital. Nanopore sequencing also identified strain-to-strain transmission of a blaCTX-M-15 FIBK/FIIK plasmid in the referring hospital.\n\nConclusionsThe data suggest the major source of K. pneumoniae was the patients own gut microbiome, but ESBL strains were acquired in the referring hospital. This highlights the importance of the wider hospital network to understanding K. pneumoniae risk and infection control. Rectal screening for ESBL organisms upon admission to geriatric wards could help inform patient management and infection control in such facilities.\n\nSummaryPatients own gut microbiota were the major source of K. pneumoniae, but extended-spectrum beta-lactamase strains were acquired in the referring hospital. This highlights the potential for rectal screening, and the importance of the wider hospital network, for local risk management.

microbiology↗

bioRxiv2017

Completing bacterial genome assemblies with multiplex MinION sequencing

Illumina sequencing platforms have enabled widespread bacterial whole genome sequencing. While Illumina data is appropriate for many analyses, its short read length limits its ability to resolve genomic structure. This has major implications for tracking the spread of mobile genetic elements, including those which carry antimicrobial resistance determinants. Fully resolving a bacterial genome requires long-read sequencing such as those generated by Oxford Nanopore Technologies (ONT) platforms. Here we describe our use of the ONT MinION to sequence 12 isolates of Klebsiella pneumoniae on a single flow cell. We assembled each genome using a combination of ONT reads and previously available Illumina reads, and little to no manual intervention was needed to achieve fully resolved assemblies using the Unicycler hybrid assembler. Assembling only ONT reads with Canu was less effective, resulting in fewer resolved genomes and higher error rates even following error correction with Nanopolish. We demonstrate that multiplexed ONT sequencing is a valuable tool for high-throughput bacterial genome finishing. Specifically, we advocate the use of Illumina sequencing as a first analysis step, followed by ONT reads as needed to resolve genomic structure.\n\nData summaryO_LISequence read files for all 12 isolates have been deposited in SRA, accessible through these NCBI BioSample accession numbers: SAMEA3357010, SAMEA3357043, SAMN07211279, SAMN07211280, SAMEA3357223, SAMEA3357193, SAMEA3357346, SAMEA3357374, SAMEA3357320, SAMN07211281, SAMN07211282, SAMEA3357405.\nC_LIO_LIA full list of SRA run accession numbers (both Illumina reads and ONT reads) for these samples are available in Table S1.\nC_LIO_LIAssemblies and sequencing reads corresponding to each stage of processing and analysis are provided in the following figshare project: https://figshare.com/projects/Completing_bacterial_genome_assemblies_with_multiplex_MinION_sequencing/23068\nC_LIO_LISource code is provided in the following public GitHub repositories: https://github.com/rrwick/Bacterial-genome-assemblies-with-multiplex-MinION-sequencing https://github.com/rrwick/Porechop https://github.com/rrwick/Fast5-to-Fastq\nC_LI\n\nImpact StatementLike many research and public health laboratories, we frequently perform large-scale bacterial comparative genomics studies using Illumina sequencing, which assays gene content and provides the high-confidence variant calls needed for phylogenomics and transmission studies. However, problems often arise with resolving genome assemblies, particularly around regions that matter most to our research, such as mobile genetic elements encoding antibiotic resistance or virulence genes. These complexities can often be resolved by long sequence reads generated with PacBio or Oxford Nanopore Technologies (ONT) platforms. While effective, this has proven difficult to scale, due to the relatively high costs of generating long reads and the manual intervention required for assembly. Here we demonstrate the use of barcoded ONT libraries sequenced in multiplex on a single ONT MinION flow cell, coupled with hybrid assembly using Unicycler, to resolve 12 large bacterial genomes. Minor manual intervention was required to fully resolve small plasmids in five isolates, which we found to be underrepresented in ONT data. Cost per sample for the ONT sequencing was equivalent to Illumina sequencing, and there is potential for significant savings by multiplexing more samples on the ONT run. This approach paves the way for high-throughput and cost-effective generation of completely resolved bacterial genomes to become widely accessible.

bioinformatics↗

bioRxiv2016

Gastrointestinal carriage is a major reservoir of K. pneumoniae infection in intensive care patients

BackgroundKlebsiella pneumoniae is an opportunistic pathogen and a leading cause of hospital-associated (HA) infections. Patients in intensive care units (ICUs) are particularly at risk, and outbreaks are frequently reported in ICUs. K. pneumoniae is also part of the healthy human microbiome, providing a potential reservoir for HA infection. However, the frequency of K. pneumoniae gut colonization and its contribution to HA infections are not well characterized.\n\nMethodsWe conducted one-year prospective cohort study of ICU patients. Participants (n=498) were screened for rectal and throat carriage of K. pneumoniae shortly after admission, and clinical information was extracted from hospital records.K. pneumoniae isolated from screening swabs and clinical diagnostic samples were characterized using whole genome sequencing. Genomic and epidemiological data were combined to identify likely transmission events.\n\nResults and ConclusionsK. pneumoniae carriage frequencies were estimated at 6% (95% CI, 3%-8%) amongst ICU patients admitted direct from the community, and 19% (95% CI, 14% - 51%) amongst those who had recent contact with healthcare. Gut colonisation on admission was significantly associated with subsequent K. pneumoniae infection (infection risk 16% vs 3%, OR=6.9, p<0.001), and genome data indicated a match between carriage and infection isolates in most patients. Five likely transmission chains were identified, resulting in six infections (12% of K. pneumoniae infections in ICU). In contrast, 49% of K. pneumoniae infections were caused by a strain that was unique to the patient, and 48% of patients with K. pneumoniae infections who participated in screening were positive for prior colonisation. These data confirm K. pneumoniae colonisation is a significant risk factor for subsequent infection in ICU, and indicate that half of all K. pneumoniae infections result from patients own microbiota. Screening for colonisation on admission could limit risk of infection in the colonised patient and others.

microbiology↗

bioRxiv2016

Unicycler: resolving bacterial genome assemblies from short and long sequencing reads

1.The Illumina DNA sequencing platform generates accurate but short reads, which can be used to produce accurate but fragmented genome assemblies. Pacific Biosciences and Oxford Nanopore Technologies DNA sequencing platforms generate long reads that can produce more complete genome assemblies, but the sequencing is more expensive and error prone. There is significant interest in combining data from these complementary sequencing technologies to generate more accurate \"hybrid\" assemblies. However, few tools exist that truly leverage the benefits of both types of data, namely the accuracy of short reads and the structural resolving power of long reads. Here we present Unicycler, a new tool for assembling bacterial genomes from a combination of short and long reads, which produces assemblies that are accurate, complete and cost-effective. Unicycler builds an initial assembly graph from short reads using the de novo assembler SPAdes and then simplifies the graph using information from short and long reads. Unicycler utilises a novel semi-global aligner, which is used to align long reads to the assembly graph. Tests on both synthetic and real reads show Unicycler can assemble larger contigs with fewer misassemblies than other hybrid assemblers, even when long read depth and accuracy are low. Unicycler is open source (GPLv3) and available at github.com/rrwick/Unicycler.

bioinformatics↗