Biology subjects

Wyres, K. L.

Publications and source records attributed to Wyres, K. L..

At least 19 recordsLinked to original sources

bioRxiv2026

A capsule polysaccharide synthesis locus database for the Klebsiella oxytoca Species Complex

The Klebsiella oxytoca Species Complex (SC) represents an emerging healthcare-associated group of opportunistic pathogens. The capsular polysaccharide is a virulence determinant and target for novel vaccines, monoclonal antibodies and phage therapy. In the absence of broadly accessible phenotyping techniques, prediction of capsule types from whole-genome sequence data is critical for understanding capsule diversity and epidemiology, and to prioritise capsule types as targets for novel anti-K. oxytoca SC interventions. Here we present the first comprehensive capsule synthesis locus (K locus) database targeted for the K. oxytoca SC, comprising 88 distinct loci defined by gene content and which is compatible with the rapid genome typing tool Kaptive. The database provides high coverage of publicly available K. oxytoca SC genomes (97.6% of 2,244 genomes, dereplicated from a total of 4,055), and the typing rate is significantly higher than that achieved with the pre-existing Klebsiella K locus database (97.6% vs 50.3%, p <0.0001), which primarily targets the Klebsiella pneumoniae SC. We demonstrate the utility of the novel K. oxytoca SC database by application to three diverse clinical K. oxytoca SC isolate collections (n=61 to 102 genomes each), suggesting a high diversity of K types. The novel K. oxytoca SC K locus database (github.com/klebgenomics/KoSC-surface-antigen-loci) will provide a key resource to support larger systematic studies and ongoing genomics surveillance efforts for the K. oxytoca SC. IMPACT STATEMENTMembers of the Klebsiella oxytoca Species Complex (SC) are an emerging cause of infections in humans and are frequently associated with antimicrobial resistance. Klebsiella species produce two key surface antigen sugars (capsular polysaccharide and lipopolysaccharide) that are immunogenic and are targets for novel control strategies such as vaccines and phage therapy. Phenotypic typing of these surface antigen sugars (serotyping) is costly and laborious, with genotyping (predicting the serotype from whole-genome sequence data) a useful alternative. Here, we present a curated capsule (K) locus reference database for the K. oxytoca SC, which represents a useful tool to assist in the epidemiological surveillance of this emerging pathogen. DATA SUMMARYAll Klebsiella oxytoca Species Complex genomes used in this work were publicly available, with accession details listed in Supplementary Tables 1, 2 and 3. The K. oxytoca Species Complex K locus reference database is available under GNU public license at github.com/klebgenomics/KoSC-surface-antigen-loci.

bioinformatics↗

bioRxiv2025

IS-capades of Klebsiella pneumoniae: Insertion sequences drive metabolic loss in obscure sub-lineages

IntroductionKlebsiella pneumoniae is an opportunistic pathogen which causes a wide spectrum of infections within healthcare settings and the community. Four K. pneumoniae sub-lineages defined with cgMLST/LINcodes are known to cause distinct infections of the nasal and/or upper respiratory passages: SL91 and SL10031 (also referred to as subspecies ozaenae), SL10032 (subspecies rhinoscleromatis) and SL82. These sub-lineages have also demonstrated reduced carbon source utilisation, which in other species has been linked with high loads of insertion sequences (IS). MethodsWe performed comparative genomics, analysed IS and constructed genome-scale metabolic models for available public sequences from these four sub-lineages and compared them to other sub-lineages from the wider K. pneumoniae population. ResultsThe four focal sub-lineages displayed significantly higher IS loads (median range 88 to 120 per genome) compared to other K. pneumoniae sub-lineages (median range 12 to 73). Notably, each K. pneumoniae sub-lineage had unique IS profiles, consistent with distinct evolutionary trajectories of IS acquisition and expansion. Across sub-lineages, higher IS loads were inversely associated with the number of metabolic model genes per genome (R2 = 0.16, p <0.001), as well as predicted aerobic substrate utilisation for phosphorus sources (R2 = 0.39, p<0.001) as per a second-degree polynomial regression model (n = 1,664 genomes). Additionally, the four IS-dense sub-lineages displayed a combination of convergent sub-lineage-specific substrate utilisation losses including parallel loss of 3-Phospho-D-glycerate, D-Glycerate-2-phosphate, Phosphoenolpyruvate utilisation as carbon/phosphorus sources. Finally, inspection of IS insertion sites demonstrated frequent and non-destructive insertion next to transcriptional, carbohydrate and amino acid metabolism genes. ConclusionsIS loads were significantly and inversely associated with metabolic substrate usage within K. pneumoniae, whereby sub-lineages that had higher numbers of IS also had reduced metabolic capacity. We hypothesise that an insertional tolerance model explains these findings, whereby IS can only insert into "metabolically-tolerable" sites for the individual cell and any impacts on metabolism are not detrimental for survival.

genomics↗

bioRxiv2025

Fast and Accurate in silico Antigen Typing with Kaptive 3

Surface polysaccharides are common antigens in priority pathogens and therefore attractive targets for novel control strategies such as vaccines, monoclonal antibody and phage therapies. Distinct serotypes correspond to diverse polysaccharide structures that are encoded by distinct biosynthesis gene clusters, e.g. the Klebsiella pneumoniae species complex (KpSC) K- and O-loci encode the synthesis machinery for the capsule (K) and outer-lipopolysaccharides (O), respectively. We previously presented Kaptive and Kaptive 2, programs to identify K and O-loci directly from KpSC genome assemblies (later adapted for Acinetobacter baumannii), enabling sero-epidemiological analyses to guide vaccine and phage therapy development. However, for some KpSC genome collections, Kaptive (v[≤]2) was unable to type a high proportion of K-loci. Here we identify the cause of this issue as assembly fragmentation, and present a new version of Kaptive (v3) to circumvent this problem, reduce processing times and simplify output interpretation. We compared the performance of Kaptive v2 and Kaptive v3 for typing genome assemblies generated from subsampled Illumina read sets (decrements of 10x depth), for which a corresponding high quality completed genome was also available to determine the true loci (n=549 KpSC, n=198 A. baumannii). Both versions of Kaptive showed high rates of agreement to the matched true locus among typeable locus calls ([≥]96% for [≥]20x read depth), but Kaptive v3 was more sensitive, particularly for low depth assemblies (at <40x depth, v3 ranged 0.85-1 vs v2 0.09-0.94) and/or typing KpSC K-loci (e.g. 0.97 vs 0.82 for non-subsampled assemblies). Overall, Kaptive v3 was also associated with a higher rate of optimal outcomes i.e. loci matching those in the reference database were correctly typed and genuine novel loci were reported as untypeable (73-98% for v3 vs 7-77% for v2 for KpSC K-loci). Kaptive v3 was >1 order of magnitude faster than Kaptive v2 making it easy to analyse thousands of assemblies on a desktop computer, facilitating broadly accessible in silico serotyping that is both accurate and sensitive. The Kaptive v3 source code is freely available on GitHub (https://github.com/klebgenomics/Kaptive), and has been implemented in Kaptive Web (https://kaptive-web.erc.monash.edu).

bioinformatics↗

bioRxiv2024

Wild type domestication: loss of intrinsic metabolic traits concealed by culture in rich media

BackgroundBacteria are typically isolated on rich media to maximise isolation success, removing them from their native evolutionary context. This eliminates selection pressures, enabling otherwise deleterious genomic events to accumulate. Here we present a cautionary tale of these quiet mutations which can persist unnoticed in bacterial culture lines. MethodsWe used a combination of microbiological culture (standard and minimal media conditions), whole genome sequencing and metabolic modelling to investigate putative Klebsiella pneumoniae L-histidine auxotrophs. Additionally, we used genome-scale metabolic modelling to predict auxotrophies among completed public genomes (n=2,637). ResultsTwo sub-populations were identified within a K. pneumoniae frozen stock, differing in their ability to grow in the absence of L-histidine. These sub-populations were the same strain, separated by eight single nucleotide variants and an insertion sequence-mediated deletion of the L-histidine biosynthetic operon. The His- sub-population remained undetected for >10 years despite its in inclusion in independent laboratory experiments. Genome-scale metabolic models predicted 0.8% public genomes contained [≥]1 auxotrophy, with purine/pyrimidine biosynthesis and amino acid metabolism most frequently implicated. DiscussionWe provide a definitive example of the role of standard rich media culture conditions in obscuring biologically relevant mutations i.e. nutrient auxotrophies, and estimate the prevalence of such auxotrophies using public genome collections. While the prevalence is low, it is not insignificant given the thousands of K. pneumoniae that are isolated for global surveillance and research studies each year. Our data serve as a pertinent reminder that rich-media culturing can cause unnoticed wild type domestication.

microbiology↗

bioRxiv2024

A metabolic atlas of the Klebsiella pneumoniae species complex reveals lineage-specific metabolism that supports persistent co-existence of diverse lineages

The Klebsiella pneumoniae species complex inhabits a wide variety of hosts and environments, and is a major cause of antimicrobial resistant infections. Genomics has revealed the population comprises multiple species/subspecies and hundreds of distinct co-circulating sub-lineages that are associated with distinct gene complements. A substantial fraction of the pan-genome is predicted to be involved in metabolic functions and hence these data are consistent with metabolic differentiation as a driver of population structure. However, this has so far remained unsubstantiated because in the past it was not possible to explore metabolic variation at scale. Here we used a combination of comparative genomics and high-throughput genome-scale metabolic modelling to systematically explore metabolic diversity across the K. pneumoniae species complex (n=7,835 genomes). We simulated growth outcomes for each isolate using carbon, nitrogen, phosphorus and sulfur sources under aerobic and anaerobic conditions (n=1,278 conditions per isolate). We showed that the distributions of metabolic genes and growth capabilities are structured in the population, and confirmed that sub-lineages exhibit unique metabolic profiles. In vitro co-culture experiments demonstrated reciprocal commensalistic cross-feeding between sub-lineages, effectively extending the range of conditions supporting individual growth. We propose that these substrate specialisations promote the existence and persistence of co-circulating sub-lineages by reducing nutrient competition and facilitating commensal interactions via negative frequency-dependent selection. Our findings have implications for understanding the eco-evolutionary dynamics of K. pneumoniae and for the design of novel strategies to prevent opportunistic infections caused by this World Health Organization priority antimicrobial resistant pathogen.

microbiology↗

bioRxiv2024

Genomic and functional analysis of rmp locus variants in Klebsiella pneumoniae

AbstractO_ST_ABSBackgroundC_ST_ABSKlebsiella pneumoniae is an opportunistic pathogen and a leading cause of healthcare-associated infections in hospitals, which are frequently antimicrobial resistant (AMR). Exacerbating the public health threat posed by K. pneumoniae, some strains also harbor additional hypervirulence determinants typically acquired via mobile genetic elements such as the well-characterised large virulence plasmid KpVP-1. The rmpADC locus is considered a key virulence feature of K. pneumoniae and is associated with upregulated capsule expression and the hypermucoid phenotype, which can enhance virulence by contributing to serum resistance. Typically such strains have been susceptible to all antimicrobials besides ampicillin, however the recent emergence of AMR hypermucoid strains is concerning. MethodsHere, we investigate the genetic diversity, evolution, mobilisation and prevalence of rmpADC, in a dataset of 14000 genomes from isolates of the Klebsiella pneumoniae species complex, and describe the RmST virulence typing scheme for tracking rmpADC variants for the purposes of genomic surveillance. Additionally, we examine the functionality of representatives for variants of rmpADC introduced into a mutant strain lacking its native rmpADC locus. ResultsThe rmpADC locus was detected in 7% of the dataset, mostly from genomes of K. pneumoniae and a very small number of K. variicola and K. quasipneumoniae. Sequence variants of rmpADC grouped into five distinct lineages (rmp1, rmp2, rmp2A, rmp3 and rmp4) that corresponded to unique mobile elements, and were differentially distributed across different populations (i.e. clonal groups) of K. pneumoniae. All variants were demonstrated to produce enhanced capsule production and hypermucoviscosity. ConclusionThese results provide an overview of the diversity and evolution of a prominent K. pneumoniae virulence factor and support the idea that screening for rmpADC in K. pneumoniae isolates and genomes is valuable to monitor the emergence and spread of hypermucoid K. pneumoniae, including AMR strains.

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↗

bioRxiv2024

Bacterial strain nomenclature in the genomic era: Life Identification Numbers using a gene-by-gene approach

Unified strain taxonomies are needed for the epidemiological surveillance of bacterial pathogens and international communication in microbiological research. Core genome multilocus sequence typing (cgMLST) holds great promise for standardized high-resolution strain genotyping. However, this approach faces challenges including classification instability and disconnection of new nomenclature from widely adopted classical MLST identifiers. This essay discusses the cgMLST-based Life Identification Number (LIN) method, recently proposed as a stable multilevel strain taxonomy system applicable to most bacterial pathogens. We describe how LIN codes are implemented and used in practice for precise strain definitions and epidemiological tracking. Glossary Multilocus sequence typing (MLST)A genotyping method applied mostly to microbial strains to study population structure and epidemiology, based on comparing the nucleotide sequences of a small number (typically seven) of housekeeping protein-coding genes. In MLST, allele numbers are assigned to each sequence variant (allele) of a given gene. The MLST genotype of a bacterial strain is defined by the combination of the allele numbers observed at the genes that are included in the genotyping scheme. A sequence type (ST) is assigned to each unique combination of alleles, called an MLST profile. MLST was invented in 1998 and became a de-facto standard taxonomy of bacterial strains, albeit at low resolution. Core genome MLSTAn extension of MLST that analyzes sequence variation across hundreds to thousands of conserved (core) genes, shared by all strains of a species, providing higher resolution typing for genomic epidemiology and evolutionary studies. cgMLST schemes typically comprise 2000 to 4000 genes, depending on the genome size and genetic variation (in terms of presence/absence of genes) within bacterial species. A core genome sequence type (cgST) can be assigned to unique cgMLST profiles, i.e., a unique combination of cgMLST allelic numbers. Whole Genome Sequencing (WGS)A method that determines the complete DNA sequence of an organisms genome in a single process, providing comprehensive information for comparative genetic analyses based on cgMLST or other analytic methods. Single Nucleotide Polymorphisms (SNPs)Variations at a single base position in the DNA sequence among individuals isolates, strains or species, used as genetic markers for studying for example, evolutionary relationships or strain identity. Average nucleotide identity (ANI)A measure of genomic similarity between two organisms, calculated as the average percentage of identical nucleotides in orthologous genomic regions; commonly used to assess species-level relatedness in prokaryotes. TaxonomyHere, we apply the word taxonomy to bacterial strains as a system of classifying, naming and identifying strains based on shared genetic characteristics as defined by e.g., cgMLST.

microbiology↗

bioRxiv2023

A validated pangenome-scale metabolic model for the Klebsiella pneumoniae species complex

The Klebsiella pneumoniae Species Complex (KpSC) is a major source of nosocomial infections globally with high rates of resistance to antimicrobials. Consequently, there is growing interest in understanding virulence factors and their association with cellular metabolic processes for developing novel anti-KpSC therapeutics. Phenotypic assays have revealed metabolic diversity within the KpSC, but metabolism research has been neglected due to experiments being difficult and cost-intensive. Genome-scale metabolic models (GSMMs) represent a rapid and scalable in silico approach for exploring metabolic diversity, which compiles genomic and biochemical data to reconstruct the metabolic network of an organism. Here we use a diverse collection of 507 KpSC isolates, including representatives of globally distributed clinically-relevant lineages, to construct the most comprehensive KpSC pan-metabolic model to-date, KpSC pan v2. Candidate metabolic reactions were identified using gene orthology to known metabolic genes, prior to manual curation via extensive literature and database searches. The final model comprised a total of 3,550 reactions, 2,403 genes and can simulate growth on 360 unique substrates. We used KpSC pan v2 as a reference to derive strain-specific GSMMs for all 507 KpSC isolates, and compared these to GSMMs generated using a prior KpSC pan-reference (KpSC pan v1) and two single-strain references. We show that KpSC pan v2 includes a greater proportion of accessory reactions (8.8%) than KpSC pan v1 (2.5%). GSMMs derived from KpSC pan v2 also result in more accuracy growth predictions than those derived from other references in both aerobic (median accuracy = 95.4%) and anaerobic (median accuracy = 78.8%). KpSC pan v2 also generates more accurate growth predictions, with high median accuracies of 95.4% (aerobic, n=37 isolates) and 78.8% (anaerobic, n=36 isolates) for 124 matched carbon substrates. KpSC pan v2 is freely available at https://github.com/kelwyres/KpSC-pan-metabolic-model, representing a valuable resource for the scientific community, both as a source of curated metabolic information and as a reference to derive accurate strain-specific GSMMs. The latter can be used to investigate the relationship between KpSC metabolism and traits of interest, such as reservoirs, epidemiology, drug resistance or virulence, and ultimately to inform novel KpSC control strategies. Significance as a BioResource to the communityKlebsiella pneumoniae and its close relatives in the K. pneumoniae Species Complex (KpSC) are priority antimicrobial resistant pathogens that exhibit extensive genomic diversity. There is growing interest in understanding KpSC metabolism, and genome scale metabolic models (GSMMs) provide a rapid, scalable option for exploration of whole cell metabolism plus phenotype prediction. Here we present a KpSC pan-metabolic model representing the cellular metabolism of 507 diverse KpSC isolates. Our model is the largest and most comprehensive of its kind, comprising >2,400 genes associated with >3,500 metabolic reactions, plus manually curated evidence annotations. These data alone represent a key knowledge resource for the Klebsiella research community; however, our models greatest impact lies in its potential for use as a reference from which highly accurate strain-specific GSMMs can be derived to inform in depth strain-specific and/or large-scale comparative analyses. Data summaryO_LIKlebsiella pneumoniae species complex (KpSC) pan v2 metabolic model available at https://github.com/kelwyres/KpSC-pan-metabolic-model. C_LIO_LIAll KpSC isolate whole genome sequences used in this work were reported previously and are available under Bioprojects PRJEB6891, PRJNA351909, PRJNA493667, PRJNA768294, PRJNA253462, PRJNA292902 and PRJNA391323. Individual accessions listed in Table S1. C_LIO_LIStrain-specific GSMMs used for comparative analyses (deposited in Figshare - 10.6084/m9.figshare.24871914), plus their associated MEMOTE reports (indicates completeness and annotation quality), reaction and gene presence-absence matrices across all isolates. C_LIO_LIGrowth phenotype predictions derived from strain-specific GSMMs are available in Table S4. C_LIO_LIBinarised Biolog growth phenotype data for n=37 isolates (plates PM1 and PM2, aerobic and anaerobic conditions) are available in Tables S6 & S7. C_LIO_LIAdditional growth assay data for six substrates not included on Biolog plates PM1 and PM2 (deposited in Figshare - 10.6084/m9.figshare.24871914). C_LI

genomics↗

bioRxiv2023

Bactabolize: A tool for high-throughput generation of bacterial strain-specific metabolic models

Metabolic capacity can vary substantially within a bacterial species, leading to ecological niche separation, as well as differences in virulence and antimicrobial susceptibility. Genome-scale metabolic models are useful tools for studying the metabolic potential of individuals, and with the rapid expansion of genomic sequencing there is a wealth of data that can be leveraged for comparative analysis. However, there exist few tools to construct strain-specific metabolic models at scale. Here we describe Bactabolize (github.com/kelwyres/Bactabolize), a reference-based tool which rapidly produces strain-specific metabolic models and growth phenotype predictions. We describe a pan reference model for the priority antimicrobial-resistant pathogen, Klebsiella pneumoniae (github.com/kelwyres/KpSC-pan-metabolic-model), and a quality control framework for using draft genome assemblies as input for Bactabolize. The Bactabolize-derived model for K. pneumoniae reference strain KPPR1 performed comparatively or better than currently available automated approaches CarveMe and gapseq across 507 substrate and 2317 knockout mutant growth predictions. Novel draft genomes passing our systematically-defined quality control criteria resulted in models with a high degree of completeness ([≥]99% genes and reactions captured compared to models derived from matched complete genomes) and high accuracy (mean 0.97, n=10). We anticipate the tools and framework described herein will facilitate large-scale metabolic modelling analyses that broaden our understanding of diversity within bacterial species and inform novel control strategies for priority pathogens.

bioinformatics↗

bioRxiv2022

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

BackgroundOxford Nanopore Technologies (ONT) sequencing has rich potential for genomic epidemiology and public health investigations of bacterial pathogens, particularly in low-resource settings and at the point of care, due to its portability and affordability. However, low base-call accuracy has limited the reliability of ONT data for critical tasks such as antimicrobial resistance (AMR) and virulence gene detection and typing, serotype prediction and cluster identification. Thus, Illumina sequencing remains the standard for genomic surveillance despite higher capital and running costs. MethodsWe tested the accuracy of ONT-only assemblies for common applied bacterial genomics tasks (genotyping and cluster detection, implemented via Kleborate, Kaptive and Pathogenwatch), using data from 54 unique Klebsiella pneumoniae isolates. ONT reads generated via MinION with R9.4 flowcells were basecalled using three alternative models (Fast, High-accuracy (HAC) and Super-accuracy (SUP), available within ONTs Guppy software), assembled with Flye and polished using Medaka. Accuracy of typing using ONT-only assemblies was compared with that of Illumina-only and hybrid ONT+Illumina assemblies, constructed from the same isolates as reference standards. ResultsThe most resource-intensive ONT-assembly approach (SUP basecalling, with or without Medaka polishing) performed best, yielding reliable capsule (K) type calls for all strains (100% exact or best matching locus), reliable multi-locus sequence type (MLST) assignment (98.3% exact match or single-locus variants), and good detection of acquired AMR genes and mutations (88% - 100% correct identification across the various drug classes). Distance-based trees generated from SUP+Medaka assemblies accurately reflected overall genetic relationships between isolates; however, the definition of outbreak clusters from ONT-only assemblies was problematic. HAC basecalling + Medaka polishing performed similarly to SUP basecalling without polishing, and polishing introduced errors into HAC- or Fast-basecalled assemblies. Therefore, we recommend investing compute resources into basecalling (SUP model) over polishing, where compute resources and/or time are limiting. ConclusionsOverall, our results show that MLST, K type and AMR determinants can be reliably identified with ONT-only data. However, cluster detection remains challenging with this technology.

genomics↗

bioRxiv2021

Linear plasmids in Klebsiella and other Enterobacteriaceae

Linear plasmids are extrachromosomal DNA that have been found in a small number of bacterial species. To date, the only linear plasmids described in the Enterobacteriaceae family belong to Salmonella, first found in Salmonella Typhi. Here, we describe a collection of 12 isolates of the Klebsiella pneumoniae species complex in which we identified linear plasmids. We used this collection to search public sequence databases and discovered an additional 74 linear plasmid sequences in a variety of Enterobacteriaceae species. Gene content analysis divided these plasmids into five distinct phylogroups, with very few genes shared across more than two phylogroups. The majority of linear plasmid-encoded genes are of unknown function, however each phylogroup carried its own unique toxin-antitoxin system and genes with homology to those encoding the ParAB plasmid stability system. Passage in vitro of the 12 linear plasmid-carrying Klebsiella isolates in our collection (which include representatives of all five phylogroups) indicated that these linear plasmids can be stably maintained, and our data suggest they can transmit between K. pneumoniae strains (including members of globally disseminated multidrug resistant clones) and also between diverse Enterobacteriaceae species. The linear plasmid sequences, and representative isolates harbouring them, are made available as a resource to facilitate future studies on the evolution and function of these novel plasmids. Significance as a BioResource to the communityThis study provides the first report of linear plasmids identified within the Klebsiella pneumoniae species complex and the first report in Enterobacteriaceae besides Salmonella.We present the first comparative analysis of linear plasmid sequences in Enterobacteriaceae, however whilst this family is highly clinically significant, the functional and/or evolutionary importance of these plasmids is not yet clear. To facilitate future studies to address these questions, we have publicly deposited (i) the collection of linear plasmid sequence data; (ii) isolates representative of each of the distinct linear plasmid phylogroups. Data SummaryThe authors confirm all supporting data, code and protocols have been provided within the article or through supplementary information O_LIWhole genome sequence reads from Klebsiella pneumoniae isolates sequenced in this study have been deposited in NCBI SRA under the accession numbers listed in Table S1. C_LIO_LIRepresentative annotated sequences of one linear plasmid per phylogroup have been deposited in FigShare, doi 10.26180/16729126. C_LIO_LIA copy of all linear plasmid sequences that we assembled from publicly available genome sequence reads are available in FigShare, doi 10.26180/16531365. Read accessions for these are given in Table S1. C_LIO_LIEleven representative K. pneumoniae isolates harbouring linear plasmids described in this study have been deposited with the National Collection of Type Cultures (NCTC) and are available for purchase under the NCTC accession numbers listed in Table S1.K. pneumoniae 1194/11 (representative of phylogroup B) has been deposited in the Microorganisms Collection Center, Adolfo Lutz Institute, Sao Paulo, Brazil. To request strain 1194/11 (IAL 3063, SISGEN ABBF09B), contact: Microorganisms Collection Center Culture Collection Laboratory Instituto Adolfo Lutz, Sao Paulo State Department of Health Address: Av Dr Arnaldo, 351, 10 floor, room 1020 Phone number: +55 11 3068-2884 Zip code 01246-000, Sao Paulo, Brazil E-mail: colecaoial@ial.sp.gov.br C_LIO_LIAlignments of terminal inverted repeat sequences for each phylogroup can be found in Data S1, available on FigShare, doi 10.26180/16531371. C_LI

microbiology↗

bioRxiv2021

Kaptive 2.0: updated capsule and LPS locus typing for the Klebsiella pneumoniae species complex

The outer polysaccharide capsule and lipopolysaccharide antigens are key targets for novel control strategies targeting Klebsiella pneumoniae and related taxa from the K. pneumoniae species complex (KpSC), including vaccines, phage and monoclonal antibody therapies. Given the importance and growing interest in these highly diverse surface antigens, we had previously developed Kaptive, a tool for rapidly identifying and typing capsule (K) and outer lipopolysaccharide (O) loci from whole genome sequence data. Here, we report two significant updates, now freely available in Kaptive 2.0 (github.com/katholt/kaptive); i) the addition of 16 novel K locus sequences to the K locus reference database following an extensive search of >17,000 KpSC genomes; and ii) enhanced O locus typing to enable prediction of the clinically relevant O2 antigen (sub)types, for which the genetic determinants have been recently described. We applied Kaptive 2.0 to a curated dataset of >12,000 public KpSC genomes to explore for the first time the distribution of predicted O (sub)types across species, sampling niches and clones, which highlighted key differences in the distributions that warrant further investigation. As the uptake of genomic surveillance approaches continues to expand globally, the application of Kaptive 2.0 will generate novel insights essential for the design of effective KpSC control strategies. Significance as a BioResource to the communityKlebsiella pneumoniae is a major cause of bacterial healthcare associated infections globally, with increasing rates of antimicrobial resistance, including strains with resistance to the drugs of last resort. The latter have therefore been flagged as priority pathogens for the development of novel control strategies. K. pneumoniae produce two key surface antigen sugars (capsular polysaccharide and lipopolysaccharide (LPS)) that are immunogenic and targets for novel controls such as a vaccines and phage therapy. However, there is substantial antigenic diversity in the population and relatively little is understood about the distribution of antigen types geographically and among strains causing different types of infections. Whereas laboratory-based antigen typing is difficult and rarely performed, information about the relevant synthesis loci can be readily extracted from whole genome sequence data. We have previously developed Kaptive, a freely available tool for rapid typing of Klebsiella capsule and LPS loci from genome sequences. Kaptive is now used widely in the global research community and has facilitated new insights into Klebsiella capsule and LPS diversity. Here we present an update to Kaptive facilitating i) the identification of 16 additional novel capsule loci, and ii) the prediction of immunologically relevant LPS O2 antigen subtypes. These updates will enable enhanced sero-epidemiological surveillance for K. pneumoniae, to inform the design of vaccines and other novel Klebsiella control strategies. Data summaryO_LIThe updated code and reference databases for Kaptive are available at https://github.com/katholt/Kaptive C_LIO_LIGenome accessions from which reference sequences of novel K loci were defined are listed in Supplementary Table 1, and genomes from which these loci were detected (along with the corresponding Kaptive output) are listed in Supplementary Table 2. C_LIO_LIAccessions for the genomes screened for O types/subtypes (along with the corresponding Kaptive output) are listed in Supplementary Table 3. C_LI The authors confirm all supporting data, code and protocols have been provided within the article or through supplementary data files. Repositories1.1 RepositoriesGenome sequence from which the novel K locus KL182 was defined has been deposited under the accession JAJHNT000000000.

genomics↗

bioRxiv2021

Transmission of Klebsiella strains and plasmids within and between Grey-headed flying fox colonies

The Grey-headed flying fox (Pteropus poliocephalus) is an endemic Australian fruit bat, known to carry pathogens with zoonotic potential. We recently showed these bats harbour the bacterial pathogens Klebsiella pneumoniae and closely related species in the K. pneumoniae species complex (KpSC). However, the dynamics of Klebsiella transmission and gene flow within flying fox colonies were not explored and remain poorly understood. Here we report a high-resolution genomic comparison of 39 KpSC isolates from Greyheaded flying foxes. Illumina whole genome sequences (n=39) were assembled de novo and the Kleborate genotyping tool was used to infer sequence types (STs). Oxford Nanopore sequences were generated for 13 isolates (one for each distinct ST) in order to generate high-quality completed reference genomes. Read mapping and variant calling was used to identify single nucleotide variants (SNVs) within each ST, using the relevant reference genome. In silico genome-scale metabolic models were generated to predict and compare substrate usage to 59 previously published KpSC models for isolates from human and environmental sources, which indicated no distinction on the basis of metabolic capabilities. High-resolution genome comparisons identified five putative strain transmission clusters (four intra- and one inter-colony, n=2-15 isolates each, [≤]25 pairwise SNVs). Inter-colony transmission of Klebsiella africana was found between two flying fox populations located within flying distance. The 13 completed genomes harboured 11 plasmids, all of which showed 37-98% coverage (mean 73%) and [≥]95% identity to those previously reported from human-associated KpSC. Comparison of plasmids from different flying fox associated KpSC indicated an interspecies horizontal plasmid transmission between K. pneumoniae and K. africana for a 98 kbp plasmid, pFF1003. These data indicate that KpSC are able to transmit directly via flying fox populations or indirectly via a common source, and that these isolates can harbour plasmids with similarity to those found in human derived KpSC, indicating gene flow is occurring between isolates from Grey-headed flying fox KpSC and human clinical isolates.

microbiology↗

bioRxiv2021

A curated collection of Klebsiella metabolic models reveals variable substrate usage and gene essentiality

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.

microbiology↗

bioRxiv2021

A nationwide genomic study of clinical Klebsiella pneumoniae in Norway 2001-2015: Introduction and spread of ESBL facilitated by CG15 and CG307

SynopsisO_ST_ABSObjectiveC_ST_ABSWe have used the nationwide Norwegian surveillance program on resistant microbes in humans (NORM) to address longitudinal changes in the population structure K. pneumoniae isolates during 2001-15, encompassing the emergence and spread of ESBL-producing Enterobacterales (ESBL-E) in Norway. Material and methodsAmong blood (n= 6124) and urinary tract (n=5496) surveillance isolates from 2001-15, we used Illumina technology to whole genome sequence 201 ESBL-producing isolates from blood (n=130) and urine (n=71), and 667 non-ESBL isolates from blood. Complete genomes for four isolates were resolved with Oxford Nanopore sequencing. ResultsIn a highly diverse collection, Klebsiella variicola ssp. variicola caused a quarter of Klebsiella pneumoniae species complex bacteraemias. ESBL-production was limited to K. pneumoniae sensu stricto (98.5 %). A diverse ESBL population of 57 clonal groups (CGs) were dominated by multidrug resistant CG307 (17%), CG15 (12%), CG70 (6%), CG258 (5%) and CG45 (5%) carrying blaCTX-M-15. Yersiniabactin was significantly more common in ESBL-positive (37.8%) compared to non-ESBL K. pneumoniae sensu stricto isolates (12.7%), indicating convergence of virulence and resistance determinants Moreover, we found a significant lower prevalence of yersinabactin (3.0 %, 37.8 % and 17.3 %), IncFIB (58.7 %, 87.9 % and 79.4 %) and IncFII plasmid replicons (40.5 %, 82.8 % and 54.2%) in K. variicola ssp. variicola compared to ESBL- and non-ESBL K. pneumoniae sensu stricto, respectively. ConclusionThe increase in Norwegian KpSC ESBLs during 2010-15 was driven by blaCTX-M-15 carrying CG307 and CG15. K. variicola ssp. variicola was a frequent cause of invasive KpSC infection, but rarely carried ESBL.

microbiology↗

bioRxiv2021

Novel strains of Klebsiella africana and Klebsiella pneumoniae in Australian Fruit Bats (Pteropus poliocephalus)

Over the past decade human associated multidrug resistant (MDR) and hypervirulent Klebsiella pneumoniae lineages have been increasingly detected in wildlife. This study investigated the occurrence of K. pneumoniae species complex (KpSC) in grey-headed flying foxes (GHFF), an Australian fruit bat. Thirty-nine KpSC isolates were cultured from 275 GHFF faecal samples (14.2%), comprising K. pneumoniae (sensu stricto) (n=30), Klebsiella africana (n=8) and Klebsiella variicola subsp. variicola (n=1). The majority (79.5%) of isolates belonged to novel sequence types (ST), including two novel K. africana STs. This is the first report of K. africana outside of Africa and in a non-human host. A minority (15.4%) of GHFF KpSC isolates shared STs with human clinical K. pneumoniae strains, of which, none belonged to MDR clonal lineages that cause frequent nosocomial outbreaks, and no isolates were characterised as hypervirulent. The occurrence of KpSC isolates carrying acquired antimicrobial resistance genes in GHFF was low (1.1%), with three K. pneumoniae isolates harbouring both fluoroquinolone and trimethoprim resistance genes. This study indicates that GHFF are not reservoirs for MDR and hypervirulent KpSC strains, but they do carry novel K. africana lineages. The health risks associated with KpSC carriage by GHFF are deemed low for the public and GHFF.

microbiology↗

bioRxiv2021

Trycycler: consensus long-read assemblies for bacterial genomes

Assembly of bacterial genomes from long-read data (generated by Oxford Nanopore or Pacific Biosciences platforms) can often be complete: a single contig for each chromosome or plasmid in the genome. However, even complete bacterial genome assemblies constructed solely from long reads still contain a variety of errors, and different assemblies of the same genome often contain different errors. Here, we present Trycycler, a tool which produces a consensus assembly from multiple input assemblies of the same genome. Benchmarking using both simulated and real sequencing reads showed that Trycycler consensus assemblies contained fewer errors than any of those constructed with a single long-read assembler. Post-assembly polishing with Medaka and Pilon further reduced errors and yielded the most accurate genome assemblies in our study. As Trycycler can require human judgement and manual intervention, its output is not deterministic, and different users can produce different Trycycler assemblies from the same input data. However, we demonstrated that multiple users with minimal training converge on similar assemblies that are consistently more accurate than those produced by automated assembly tools. We therefore recommend Trycycler+Medaka+Pilon as an ideal approach for generating high-quality bacterial reference genomes. Data availabilitySupplementary figures, tables and code can be found at: github.com/rrwick/Trycycler-paper Reads, assemblies and reference sequences can be found at: bridges.monash.edu/articles/dataset/Trycycler_paper_dataset/14890734

bioinformatics↗