OxTalks will soon move to the new Halo platform and will become 'Oxford Events.' There will be a need for an OxTalks freeze. This was previously planned for Friday 14th November – a new date will be shared as soon as it is available (full details will be available on the Staff Gateway).
In the meantime, the OxTalks site will remain active and events will continue to be published.
If staff have any questions about the Oxford Events launch, please contact halo@digital.ox.ac.uk
Accurately communicating bacterial diversity is key, not only for classification, but also for pathogen surveillance, epidemiology, and population biology. Currently, the seven loci MLST has been successful for determining N. meningitidis population structure, further enhanced using fine typing antigens. Life Identification Number (LIN) barcodes are a novel way of describing bacterial populations through stable hierarchical clustering and nomenclature. These are based on allelic differences between core genome Sequence Types (cgSTs), assigned from representative core genome MLST (cgMLST) profiles. Neisseria meningitidis cgMLST v3 (1,329 loci), available on PubMLST, was used as the foundation for this work.
A curated dataset of 6,131 N. meningitidis isolates, encompassing up to 200 high-quality isolates from each clonal complex (CC), were used for LIN code development. The cgSTs for each isolate were subject to creation of a pairwise distance matrix and statistical analysis using Minimum Spanning Tree-based clustering. Overall, 13 LIN thresholds were chosen to represent different genetic lineages. These have been provided human-readable nicknames that represent MLST and MLEE describers. Defined N. meningitidis LIN thresholds are openly accessible for use on PubMLST. Several published outbreak datasets were used to validate the LIN codes, which illustrated high-quality and fine resolution for population analysis, emphasising the isolates at multiple-levels. Overall, LIN codes will be important for distinguishing between closely related strains for outbreak investigations, contributing to understanding of strain theory, and facilitating surveillance.