P642 Whole genome sequencing of N. gonorrhoeae deconvolutes sexual behaviour, population structure and transmission in singapore. (14th July 2019) - Beale, Mathew; Sessions, Paola De; Nazri Mohamed Naim, Ahmad; Tan, Ai Ling; Chow, Angela; Yeo, Benson; Chan, Roy; Thomson, Nicholas; Chio, Martin; Hibberd, Martin
Abstract : Background: Gonorrhoea is the third most commonly notified sexually transmitted infection (STI) in Singapore. In 2012, there were 1781 notifications, with an incidence rate of 33.53 per 100, 000 population with more males than females being diagnosed. While most of the cases occur in people aged between 20 and 39 years of age, gonorrhoea is the most common STI among teenagers and among men who have sex with men (MSM) in Singapore. The aim of this study was to use whole genome sequencing to gain insights into the patterns of transmission that exist within and between different subpopulations in Singapore and internationally. Methods: We sequenced 676 samples from 544 patients infected with gonorrhoea between 2014–2016. Sequencing reads from N. gonorrhoeae genomes were mapped to a common reference and recombination masked, followed by phylogenomic, Bayesian clustering and pairwise network analyses. We correlated genetic relatedness with detailed clinical parameters. Results: N. gonorrhoeae circulating in Singapore is polyphyletic, and we defined 31 circulating sub-lineages. We detected distinct patterns of sexual behaviour associated with different genetic lineages: some lineages are strongly associated with MSM groups, whilst other lineages have increased rates of reported contact of commercial sex workers. It is likely that these associations reflect the underlying population within the transmission networks. We further correlate these genomic and behavioural subpopulations according to genetically determined antimicrobial resistance patterns. Conclusion: The analysis shows distinct transmission clustering within Singapore groups based on sexual preference and commercial sex worker use. Through the use of multiple isolates from single individuals, we established expected within patient diversity levels based on pairwise sequence differences and used this to infer both putative transmission events and also possible bridging between distinct transmission networks. Further work is required to increase the prediction accuracy of the transmission networks and relate this to predicted microbial resistance patterns. Disclosure: No significant relationships.