Using Neisseria meningitidis genomic diversity to inform outbreak strain identification.
PLoS Pathog
; 17(5): e1009586, 2021 05.
Article
em En
| MEDLINE
| ID: mdl-34003852
ABSTRACT
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.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Variação Genética
/
Surtos de Doenças
/
Infecções Meningocócicas
/
Neisseria meningitidis
Tipo de estudo:
Diagnostic_studies
/
Screening_studies
Limite:
Humans
País/Região como assunto:
America do norte
Idioma:
En
Revista:
PLoS Pathog
Ano de publicação:
2021
Tipo de documento:
Article
País de afiliação:
Estados Unidos