The biology of the meningococcus, a highly diverse ‘accidental’ pathogen with a propensity for extensive horizontal gene transfer, has presented challenges for isolate characterization for typing and phenotype studies for as long as it has been studied. Over the past 30 years or so, molecular typing methods, especially those based on nucleotide sequence determination analysis, have increasingly provided insights into meningococcal biology and its relationship to invasive disease. Whole genome sequencing is the ultimate expression of this, but the size of bacterial genomes – 2.2Mbp and around 2,200 genes in the case of the meningococcus – presents challenges for precise, reproducible, and informative typing.
PubMLST provides a repository for all types of sequence data from gene fragments to complete finished genomes and a wide range of curated sequence-based typing schemes that describe lineage structure and antigenic variants. Core genome MLST (cgMLST) provides very high levels of resolution, but to date there has been no nomenclature scheme for this. Here we describe a Life Identification Number (LIN) code system based on cgMLST which fills this gap, providing a stable, reproducible, and scalable means of cataloguing meningococcal variants, which is fully backwards compatible with existing nomenclatures.
A set of 6,131 representative publicly-available genomes from the PubMLST database (www.pubmlst.org/neisseria) was used for scheme development. Using an updated cgMLST scheme (v3), optimized for automated annotation, discontinuities in the population structure were used to designate 13 allelic mismatch thresholds. These thresholds were backwards-compatible to existing nomenclature, such as cc, and provided genome scale resolution of variants. These were implemented in the PubMLST database and where appropriate, were associated with human-readable ‘nicknames’ consistent with existing nomenclatures. The system was tested against published epidemiological scenarios and shown to provide information consistent with previous analyses, often providing deeper insights. Shortly after its development, the system was used effectively in the real-time analysis of the outbreak in Kent UK.
Meningococcal LIN codes are a stable, high-resolution tool for cataloguing, describing and comparing meningococcal variation. They are backwards-compatible and facilitate improvements in global public health through the identification and monitoring of meningococcal variants over the widest possible range of resolution.