Nature Communications (Nov 2023)

Distributed genotyping and clustering of Neisseria strains reveal continual emergence of epidemic meningococcus over a century

  • Ling Zhong,
  • Menghan Zhang,
  • Libing Sun,
  • Yu Yang,
  • Bo Wang,
  • Haibing Yang,
  • Qiang Shen,
  • Yu Xia,
  • Jiarui Cui,
  • Hui Hang,
  • Yi Ren,
  • Bo Pang,
  • Xiangyu Deng,
  • Yahui Zhan,
  • Heng Li,
  • Zhemin Zhou

DOI
https://doi.org/10.1038/s41467-023-43528-0
Journal volume & issue
Vol. 14, no. 1
pp. 1 – 13

Abstract

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Abstract Core genome multilocus sequence typing (cgMLST) is commonly used to classify bacterial strains into different types, for taxonomical and epidemiological applications. However, cgMLST schemes require central databases for the nomenclature of new alleles and sequence types, which must be synchronized worldwide and involve increasingly intensive calculation and storage demands. Here, we describe a distributed cgMLST (dcgMLST) scheme that does not require a central database of allelic sequences and apply it to study evolutionary patterns of epidemic and endemic strains of the genus Neisseria. We classify 69,994 worldwide Neisseria strains into multi-level clusters that assign species, lineages, and local disease outbreaks. We divide Neisseria meningitidis into 168 endemic lineages and three epidemic lineages responsible for at least 9 epidemics in the past century. According to our analyses, the epidemic and endemic lineages experienced very different population dynamics in the past 100 years. Epidemic lineages repetitively emerged from endemic lineages, disseminated worldwide, and apparently disappeared rapidly afterward. We propose a stepwise model for the evolutionary trajectory of epidemic lineages in Neisseria, and expect that the development of similar dcgMLST schemes will facilitate epidemiological studies of other bacterial pathogens.