bioRxivMicrobiologyPreprint
The inter-continental population dynamics of Neisseria gonorrhoeae
M. N. Osnes, O. B. Brynildsrud, K. Alfsnes, L. van Dorp, S. A. McKeand, J. Ross, K. Town, J. De Korne-Elenbaas, A. van Dam, S. Bruisten, B. F. de Blasio, D. A. Caugant, Y. H. Grad, D. A. Williamson, F. Balloux, X. Didelot, V. Eldholm
Abstract
Neisseria gonorrhoeae is a globally distributed sexually transmitted bacterial pathogen. Recent studies have revealed that its evolution has been shaped by antibiotic use, while molecular surveillance efforts have demonstrated large changes in lineage composition over relatively short time-spans. However, the global population dynamics of N. gonorrhoeae remain unsatisfyingly characterized. To reconstruct recent large-scale population dynamics, we generated a dated phylogeny from 9,732 N. gonorrhoeae genomes and found the effective population size of the species to have expanded gradually over the past two centuries. While the effective population size of clades with reduced susceptibility to extended-spectrum cephalosporins started declining around 2010, a major clade containing a mosaic mtr operon associated with cephalosporin susceptibility and decreased azithromycin did not display any reduction in population size. Using ancestral trait reconstruction analyses, we delineated transmission lineages, defined as groups of sequences in which all the samples can be traced back to the same import event to a given location. Import, export and local transmission dynamics across two densely sampled locations (Norway and Victoria, Australia) were investigated in detail. Norway exhibited substantially higher rates of strain import and export compared to Victoria, where incidence was to a larger extent fuelled by locally transmitted lineages. Taken together, our work highlights the power of large-scale phylogenomic analyses to uncover the complex dynamics of lineage transmission in N. gonorrhoeae.
- organism: human
- assay: whole-genome sequencing
- research focus: phylogenetics / evolution
- approach: statistical model
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