This is the home for Klebsiella genomics tools and resources developed collaboratively by the teams of Kat Holt and Kelly Wyres, at (LSHTM) and (Monash University).
Kaptive is commandline software for identifying surface polysaccharide loci (capsule and O antigen) from genome assemblies. The software was initially developed for the Klebsiella pneumoniae species complex, but there are now typing databases for several other organisms (each with their own repository).
You can also run a graphical version of Kaptive via the Kaptive-Web online interface developed by Tom Stanton.
Code and resources:
- Kaptive code
- Kaptive docs, including instructions and info on Kaptive logic
- Kaptive v3 Tutorial, illustrating how to use Kaptive and interpret the data
- Kaptive-Web, an online version of Kaptive where you can upload genomes and visualise results
Kaptive databases:
- Klebsiella pneumoniae Species Complex K and O
- Klebsiella oxytoca Species Complex K and O
- For details on all databases supported by Kaptive, including third-party databases for Acinetobacter baumanii and Escherchia coli, see the docs here
Major contributors are Kelly Wyres and Tom Stanton. Earlier versions were developed by Ryan Wick, with contributions from Margaret Lam and Kat Holt.
Kleborate was initially developed to type genome assemblies of Klebsiella pneumoniae and its species complex (KpSC), but now also includes modules for typing Klebsiella oxytoca species complex (KoSC) and Escherichia coli/Shigella.
Code and resources:
- Kleborate code
- Kleborate docs (in English and French)
- Kleborate Tutorial, illustrating how to use Kleborate and interpret the data
This paper explores the accuracy of Kaptive & Kleborate genotyping on genomes assembled solely from Oxford Nanopore data (generated using Mk9.4.1 flowcells). We benchmark performance against genotypes called from Illumina-based assemblies, and hybrid Illumina+nanopore assemblies, using 55 Klebsiella pneumoniae genomes.
Major contributors are Kat Holt, Mary Maranga, Margaret Lam, Ebenezer Foster-Nyarko and Kara Tsang. Earlier versions were developed by Ryan Wick, with contributions from Kelly Wyres.
The KlebNET-GSP Epidemiology Consortium collates publicly available K. pneumoniae species complex (KpSC) whole genome sequences with matched isolate source and sampling information, to support:
- KlebNET Clone Reviews – collaborative genomic epidemiology reviews of globally distributed clones (e.g multi-drug resistant or hypervirulent clones);
- KlebNET Clone Risk Framework – a systematic risk framework to support global genomic surveillance of K. pneumoniae;
- KlebNET Metadata Repository – a comprehensive open-access repository of enhanced contextual meta-data, facilitating use and reuse of publicly available data by the global research community by enabling robust epidemiology and genomic meta-analyses.
The Consortium is coordinated by Kelly Wyres and Hina Salimuddin (Monash University, Australia) on behalf of the KlebNet-GSP and operates according to its Terms of Reference.
Participation in the consortium is contingent on contributing contextual metadata for Klebsiella genome sequences that have been deposited in public databases, for inclusion in the metadata repository and consortium analyses.
To join, please complete the registration form.
Relevant repositories:
- Metadata Template
- Metadata Repository
- Clone Risk Framework
K and O serotype distributions and coverage, from Klebsiella pneumoniae neonatal sepsis in African and South Asian countries
We recently published a paper presenting collaborative meta-analysis of K and O serotypes amongst neonatal sepsis isolates from 35 sites across 13 studies.
- Data, R code for modelling and visualisation, and all tables/figures from the paper are in this repository: https://github.com/klebgenomics/KlebNNSsero (developed by Kat Holt and Shaun Keegan)
- An R shiny app to explore the data is available here, app code is here (developed by Tom Stanton)
Transmission estimator
The transmission_estimator Shiny app is designed to identify transmission clusters among neonatal sepsis bacterial isolates using genomic (genetic distance) and epidemiological (spatiotemporal) data was developed for this paper, and can be used to undertake cluster analysis with your own data. The app allows users to explore the impact of temoporal and distance thresholds on clustering estimates, and to visualise cluster fractions and timelines stratified by other variables such as location or sequence type. (developed by Erkison Odih)
We used the app in a recently published paper presenting collaborative meta-analysis of transmission cluster rates amongst neonatal sepsis isolates from 27 hospitals across 13 countries.
- Data, R code for analysis and visualisation, and all tables/figures from the paper are in this repository: https://github.com/klebgenomics/KlebNNS_transmission (developed by Erkison Odih)
- KlebRef - Database of genomic data and typing information for Klebsiella reference isolates available in public repositories
- KleborateR - developed by Tom Stanton, for analysing Kaptive and Kleborate output
- Kleborate Workshop Data - used in the Kleborate Tutorial
- Klebs Genome Assemblies from the paper "Genomic analysis of diversity, population structure, virulence, and antimicrobial resistance in Klebsiella pneumoniae, an urgent threat to public health" (Holt et al, 2015 PNAS)
- KpSC-pan-metabolic-model - a pan genome-scale metabolic model for the K. pneumoniae species complex developed for use as a reference with Bactabolize - a pipeline for high-throughput generation of strain-specific metabolic models and growth phenotype predictions. Developed by Kelly Wyres, Ben Vezina and Helena Cooper with major contributions from Jane Hawkey and Stephen Watts.
- Data and code for the paper reporting the ciprofloxacin resistance prediction module included in Kleborate https://github.com/klebgenomics/cipropaper, "Ciprofloxacin resistance in Klebsiella pneumoniae: phenotype prediction from genotype and global distribution of resistance determinants" Tsang et al, 2025 BioRxiv, by the KlebNET-GSP AMR Genotype-Phenotype Group
- Slides from the "Klebsiella pneumoniae Genomic Epidemiology and Antimicrobial Resistance" training lectures delivered by members of the KlebNET Genomic Surveillance Platform in September 2025. https://github.com/klebgenomics/KlebNetTrainingSep2025
