Using Neisseria meningitidis genomic diversity to inform outbreak strain identification

• Published in: PLoS pathogens Vol. 17; no. 5; p. e1009586
• Main Authors: Retchless, Adam C., Chen, Alex, Chang, How-Yi, Blain, Amy E., McNamara, Lucy A., Mustapha, Mustapha M., Harrison, Lee H., Wang, Xin
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 18.05.2021; Public Library of Science (PLoS)
• Subjects: Alleles; Biology and Life Sciences; Causes of; Clusters; Computer and Information Sciences; Epidemics; Genetic aspects; Genomes; Genomics; Genotype; Health aspects; Identification and classification; Medicine and Health Sciences; Meningococcal disease; Neisseria meningitidis; Outbreaks; Phylogenetics; Phylogeny; Population; Public health; United States; United States; Oregon; California; United Kingdom > UK; United States > US; Ireland
• ISSN: 1553-7374; 1553-7366; 1553-7374
• DOI: 10.1371/journal.ppat.1009586

Meningococcal disease is a life-threatening illness caused by the human-restricted bacterium Neisseria meningitidis . Outbreaks in the USA involve at least two cases in an organization or community caused by the same serogroup within three months. Genome comparisons, including phylogenetic analysis and quantification of genome distances can provide confirmatory evidence of pathogen transmission during an outbreak. Interpreting genome distances depends on understanding their distribution both among isolates from outbreaks and among those not from outbreaks. Here, we identify outbreak strains based on phylogenetic relationships among 141 N . meningitidis isolates collected from 28 outbreaks in the USA during 2010–2017 and 1516 non-outbreak isolates collected through contemporaneous meningococcal surveillance. We show that genome distance thresholds based on the maximum SNPs and allele distances among isolates in the phylogenetically defined outbreak strains are sufficient to separate most pairs of non-outbreak isolates into separate strains. Non-outbreak isolate pairs that could not be distinguished from each other based on genetic distances were concentrated in the clonal complexes CC11, CC103, and CC32. Within each of these clonal complexes, phylodynamic analysis identified a group of isolates with extremely low diversity, collected over several years and multiple states. Clusters of isolates with low genetic diversity could indicate increased pathogen transmission, potentially resulting in local outbreaks or nationwide clonal expansions.