This is the home for Klebsiella genomics tools and resources developed collaboratively by the teams of Kat Holt (LSHTM) and Kelly Wyres (Monash University).

Kaptive is commandline software for identifying surface polysaccharide loci (capsule and O antigen) from genome assemblies. It was initially developed for the Klebsiella pneumoniae species complex, but also includes reference databases for Acinetobacter baumannii and Vibrio paramaemolyticus.

You can also run a graphical version of Kaptive via this web interface (which hosts Kaptive-Web source code).

Code and resources:

• Kaptive code
• Kaptive docs, including instructions and info on Kaptive logic
• Kaptive-Web, an online version of Kaptive where you can upload genomes and visualise results
• Kaptive Tutorial, illustrating how to use Kaptive and interpret the data

Major contributors are Kelly Wyres and Tom Stanton. Earlier versions were developed by Ryan Wick, with contributions from Margaret Lam and Kat Holt.

Kleborate is a tool to screen genome assemblies of Klebsiella pneumoniae and the Klebsiella pneumoniae species complex (KpSC) for:

• MLST sequence type
• species (e.g. K. pneumoniae, K. quasipneumoniae, K. variicola, etc.)
• ICEKp associated virulence loci: yersiniabactin (ybt), colibactin (clb), salmochelin (iro), hypermucoidy (rmpA)
• virulence plasmid associated loci: salmochelin (iro), aerobactin (iuc), hypermucoidy (rmpA, rmpA2)
• antimicrobial resistance determinants: acquired genes, SNPs, gene truncations and intrinsic β-lactamases
• K (capsule) and O antigen (LPS) serotype prediction, via wzi alleles and Kaptive

Code and resources:

• Kleborate code
• Kleborate docs, including instructions and info on Kleborate logic
• Kleborate-viz, a ShinyR app for visualising Kleborate output (which hosts the Kleborate-viz source code)
• Kleborate Tutorial, illustrating how to use Kleborate and interpret the data
• Details of Kleb specific AMR typing including SHV alleles and ciprofloxacin resistance prediction
• This paper explores the accuracy of Kaptive & Kleborate genotyping on genomes assembled solely from 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.

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 preprint 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

Shiny app designed to identify transmission clusters among neonatal sepsis bacterial isolates using genomic (genetic distance) and epidemiological (spatiotemporal) data.

• Code
• App

(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 Workshop
• 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.