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A Life Identification Number Barcoding (LIN Code) System for Neisseria meningitidis: High resolution multi-level typing of meningococci
Please note: for navigation to the department, google maps will still show OX1 3PS for the Life and Mind Building; however, the new and correct post code is OX1 3EL
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.
Date:
17 November 2025, 13:30
Venue:
Life and Mind Building, South Parks Road, OX1 3EL, seminar rooms 7 & 8, Lower Ground Floor
Speaker:
Dr Kasia Parfitt (University of Oxford)
Organising department:
Department of Biology
Organiser contact email address:
andrea.kastner@biology.ox.ac.uk
Host:
Professor Sam Sheppard (INEOS Oxford Institute and Department of Biology, University of Oxford)
Booking required?:
Not required
Audience:
Members of the University only
Editor:
Andrea Kastner
