bioRxivMicrobiology
Kaptive Web: user-friendly capsule and lipopolysaccharide serotype prediction for Klebsiella genomes
Abstract
As whole genome sequencing becomes an established component of the microbiologists toolbox, it is imperative that researchers, clinical microbiologists and public health professionals have access to genomic analysis tools for rapid extraction of epidemiologically and clinically relevant information. For the gram-negative hospital pathogens such as Klebsiella pneumoniae, initial efforts have focused on detection and surveillance of antimicrobial resistance genes and clones. However, with the resurgence of interest in alternative infection control strategies targeting Klebsiella surface polysaccharides, the ability to extract information about these antigens is increasingly important.\n\nHere we present Kaptive Web, an online tool for rapid typing of Klebsiella K and O loci, which encode the polysaccharide capsule and lipopolysaccharide O antigen, respectively. Kaptive Web enables users to upload and analyse genome assemblies in a web browser. Results can be downloaded in tabular format or explored in detail via the graphical interface, making it accessible for users at all levels of computational expertise.\n\nWe demonstrate Kaptive Webs utility by analysis of >500 K. pneumoniae genomes. We identify extensive K and O locus diversity among 201 genomes belonging to the carbapenemase- associated clonal group 258 (25 K and six O loci). Characterisation of a further 309 genomes indicates that such diversity is common among the multi-drug resistant clones and that these loci represent useful epidemiological markers for strain subtyping. These findings reinforce the need for rapid, reliable and accessible typing methods such as Kaptive Web.\n\nKaptive Web is available for use at kaptive.holtlab.net and source code is available at github.com/kelwyres/Kaptive-Web.
- organism: bacteria (other)
- assay: whole-genome sequencing
- research focus: cell type annotation
- research focus: clustering
- research focus: differential expression
- research focus: gene regulatory network inference
- approach: experimental assay
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