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 Ryan Wick, Margaret Lam and Tom Stanton.
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
Major contributors are Ryan Wick and Margaret Lam.
Kaptive and Kleborate were initially developed with Illumina data in mind, i.e. assuming ~zero nucleotide errors in the consensus nucleotide sequence of genome assemblies. Long-read nanopore sequencing generates longer reads and more complete assemblies, but with 10s-100s of basecall errors in the consensus sequence that can potentially interfere with allele-based typing (although this is improving all the time, fortunately!).
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.
Summary of results:
- K/O typing: The correct K and O loci were detected in all genomes
- Virulence: In genomes where virulence loci were present, they were detected and the correct lineage type reported
- AMR: 96% of acquired AMR genes and 92% of AMR mutations were correctly identified
- MLST: 87% of genomes yielded the correct 7-locus sequence type, the rest differed at 1-2 loci
Note that better consensus sequences can now be obtained using more recent nanopore flowcells and chemistries, so we expect even better genotyping performance on newer assembly data (we are currently testing Mk10, stay tuned).
Major contributors were Ebenezer Foster-Nyarko and Hugh Cottingham.
- 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.
Together with Sylvain Brisse at the Institut Pasteur, we coordinate the KlebNet network for Klebsiella surveillance. You can sign up here to join the email list and participate in working groups and upcoming events.
We also work in partnership with teams at the Institut Pasteur and Pathogenwatch to coordinate tools and platforms for Klebsiella genomic surveillance, under an initiative known as the KlebNet Genomic Surveillance Platform.