Back to Search Start Over

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

Authors :
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
Source :
Nature Communications, Vol 14, Iss 1, Pp 1-13 (2023)
Publication Year :
2023
Publisher :
Nature Portfolio, 2023.

Abstract

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.

Subjects

Subjects :
Science

Details

Language :
English
ISSN :
20411723
Volume :
14
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Nature Communications
Publication Type :
Academic Journal
Accession number :
edsdoj.b12ff695ad9d4f259cdb44c85b6ab4f5
Document Type :
article
Full Text :
https://doi.org/10.1038/s41467-023-43528-0