Origin of Neisseria meningitidis clonal complex 4821

Zhizhou Tan1, Lin Xu2, Jie Che1

  • 1National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, People's Republic of China.

PubMed

Insights

The study traced the origins of the Neisseria meningitidis CC4821 cluster in China, revealing its evolution over 60 years, not just the last two decades. This finding reshapes our understanding of invasive meningococcal disease dynamics.

Area of Science:

  • Microbiology
  • Genomics
  • Epidemiology

Background:

  • Neisseria meningitidis causes invasive meningococcal disease (IMD).
  • Clonal complex (CC) 4821 is a dominant N. meningitidis genetic cluster in China, emerging ~20 years ago.
  • The evolutionary history of CC4821 remains largely unknown.

Purpose of the Study:

  • To elucidate the evolutionary origin and timeline of the N. meningitidis CC4821 clade.
  • To identify the ancestral lineages and diversification patterns within CC4821.

Main Methods:

  • Comprehensive core genome multilocus sequence typing (cgMLST) analysis of 26,801 N. meningitidis genomes.
  • Phylogenetic analysis to reconstruct evolutionary relationships and estimate divergence times.

Main Results:

  • A distinct CC4821 clade was identified, comprising 388 N. meningitidis isolates.
  • Phylogenetic analysis indicated CC4821 originated in the 1960s, with basal isolates dating back to 1966.
  • Eight subclades were identified, with clades 1-4 present since the 1970s and clades 5-8 emerging post-2000s.
  • Clade 5, a hyperinvasive lineage, likely originated from an isolate from 1985.

Conclusions:

  • N. meningitidis CC4821 has a 60-year evolutionary history in China, predating its recent emergence as a predominant cluster.
  • The findings highlight continuous evolution and diversification within N. meningitidis in China.
  • Understanding the deep evolutionary roots of CC4821 is crucial for predicting and controlling future IMD outbreaks.

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