PLoS ONEGenomicsPeer-reviewed journal article
Tracking a Serial Killer: Integrating Phylogenetic Relationships, Epidemiology, and Geography for Two Invasive Meningococcal Disease Outbreaks
Ifeoma Ezeoke, Madeline R. Galac, Ying Linda LiniD, Alvin T. Liem, Pierce A. Roth, Andy KilianskiiD, Henry S. GibbonsiD, Danielle BlochiD, John S. Kornblum, Paula Del Rosso, Daniel A. JaniesiD, Don WeissiD
Abstract
BackgroundWhile overall rates of meningococcal disease have been declining in the United States for the past several decades, New York City (NYC) has experienced two serogroup C meningococcal disease outbreaks in 2005-2006 and in 2010-2013. The outbreaks were centered within drug use and sexual networks, were difficult to control, and required vaccine campaigns.\n\nMethodsWhole Genome Sequencing (WGS) was used to analyze preserved meningococcal isolates collected before and during the two outbreaks. We integrated and analyzed epidemiologic, geographic, and genomic data to better understand transmission networks among patients. Betweenness centrality was used as a metric to understand the most important geographic nodes in the transmission networks. Comparative genomics was used to identify genes associated with the outbreaks.\n\nResultsNeisseria meningitidis serogroup C (ST11/ET-37) was responsible for both outbreaks with each outbreak having distinct phylogenetic clusters. WGS did identify some misclassifications of isolates that were more distant from the rest of the outbreak, as well as those that should have been included based on high genomic similarity. Genomes for the second outbreak were more similar than the first and no mutation was found to either be unique or specific to either outbreak lineage. Betweenness centrality as applied to transmission networks based on phylogenetic analysis demonstrated that the outbreaks were transmitted within focal communities in NYC with few transmission events to other locations.\n\nConclusionsNeisseria meningitidis is an ever changing pathogen and comparative genomic analyses can help elucidate how it spreads geographically to facilitate targeted interventions to interrupt transmission.
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