Investigating the role of whole genome sequencing in syphilis epidemiology: an English case study

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Abstract
Background: Syphilis is a sexually transmitted bacterial infection caused by Treponema pallidum subspecies pallidum , with approximately 6.3 million annual cases globally. Over the last decade, syphilis rates have risen dramatically in many high-income countries, including in England, which has seen a greater than 150% increase. Although this increase is known to be associated with high risk sexual activity in gay, bisexual and other men who have sex with men (GBMSM), cases are rising in heterosexual men and women, and congenital syphilis cases are now seen annually. The transmission dynamics within and between sexual networks of GBMSM and heterosexuals are not well understood. Methods: To determine if whole genome sequencing could be used to identify discrete patterns of transmission, we linked national patient demographic, geospatial and behavioural metadata to whole T. pallidum genome sequences previously generated from 237 patient samples collected from across England between 2012 and 2018. Findings: Phylogenomic analysis and clustering revealed two of the eight T. pallidum sublineages detected in England dominated. These dominant sublineages exhibited different spatiotemporal trends linked to demography or behaviour, suggesting they represent different sexual networks: sublineage 1 was found throughout England and across all patient groups, whereas sublineage 14 occurred predominantly in older GBMSM and was absent from samples sequenced from the North of England. By focussing on different regions of England we were able to distinguish a local heterosexual transmission cluster from a background of transmission amongst GBMSM. Interpretation: These findings demonstrate that despite extremely close genetic relationships between T. pallidum genomes globally, genomics can still be used to identify putative transmission clusters for epidemiological follow-up, and therefore has a role to play in informing public health interventions. Funding: Wellcome funding to the Sanger Institute (#206194 and 108413/A/15/D), UKRI and NIHR (COV0335; MR/V027956/1, NIHR200125), the EDCTP (RIA2018D-249), and UKHSA. Research in Context: Evidence before this study: Detailed phylogenomic analyses investigating the epidemiology and transmission dynamics of Treponema pallidum are challenging due to low bacterial loads in clinical specimens, and difficulty in culturing the bacteria. We searched PubMed until August 9 th 2022 using the search terms “Syphilis” or “ Treponema pallidum ” and “genomic” or “genome(s)” or “sequencing”, finding 23 studies describing whole genome sequencing of T. pallidum subspecies pallidum , of which two used whole genome phylogenies to investigate sexual network epidemiology, with one large study of sexual networks conducted primarily in Victoria, Australia which characterised two major circulating sublineages in that setting, as well as putative sexual transmission networks with distinct sexual behavioural characteristics and potential bridging between networks. Added value of this study: In this study, we linked national surveillance data to T. pallidum genomes, and characterised the transmission dynamics of syphilis using samples from across a whole country, in a European setting (England). Integration of national-level sociodemographic, spatiotemporal and genomic data allowed the delineation of putative sexual networks at both the national and region levels, and revealed patterns not previously detected using epidemiological or genomic data alone. Implications of all the available evidence: Our findings are consistent with findings in Australia that demonstrate genomics can identify putative sociodemographic transmission clusters. However, in that study genomic clusters included samples separated by multiple single nucleotide polymorphisms, which could represent several years of evolution. Our study explored the value of linking identical genomes, and highlights that despite technical constraints, whole genome sequencing can be used to enable outbreak exclusion and identify putative local transmission clusters for epidemiological follow-up.
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