High diversity amongst African Treponema pallidum genomes provides a window into global transmission dynamics of syphilis: A genomic epidemiology study
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Abstract
Background
Global syphilis rates have risen dramatically since the early 2000s. Genomes can be used to inform rational control and intervention strategies by enhancing surveillance and ensuring vaccines have broad global utility. However, although >1000 Treponema pallidum genomes are now available from high-income countries, genomic data from Africa remain limited.
Methods
We combined samples from 1198 participants recruited into a genital ulcer aetiology study in Botswana, Ghana, Uganda and Zimbabwe (collected 2022-2023) with 276 samples from national syphilis surveillance in South Africa to generate 147 novel African T. pallidum genomes (collected 2006-2023). Combining these with 167 publicly available African genomes and 1062 genomes from 24 non-African countries, we performed contextual population genomic analyses to understand the T. pallidum genomic diversity and transmission within and between African countries and the rest of the world.
Findings
Contrasting with previous studies showing global circulation of highly similar T. pallidum , we found remarkable diversity amongst African T. pallidum . Of 56 sublineages, 20 were exclusively found amongst 6 African countries, 31 were found amongst 24 non-African countries, and 5 were found in both. Sublineage sharing between Africa and the rest of the world was rare, with 83.8% of African syphilis caused by locally circulating sublineages. Only 20.1% of African syphilis was resistant to macrolides (global average = 68.6%); where resistance occurred, this was strongly linked to introduction of global sublineages into Africa.
Interpretation
African T. pallidum is characterised by locally circulating strains not found globally. Since sublineage sharing between countries is low, cataloguing African T. pallidum diversity will require intense local sampling in many countries. These findings will inform ongoing strategies for genomic surveillance and vaccine design, whilst contributing to our understanding of the spread of antimicrobial resistance in Africa, enabling refined treatment guidelines based on local data.
Funding
Wellcome and the Gates Foundation.
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This Zenodo record is a permanently preserved version of a PREreview. You can view the complete PREreview at https://prereview.org/reviews/19587072.
This study addresses a relevant research question by examining how the genomic diversity, antimicrobial resistance patterns, and transmission dynamics of Treponema pallidum in Africa differ from those observed globally. The authors use an observational genomic epidemiology approach, combining cross-sectional and retrospective data with whole genome sequencing, which is appropriate for capturing both spatial and temporal patterns of variation.
The findings indicate that T. pallidum in Africa has considerable genomic diversity, with most infections (83.8%) driven by locally circulating sublineages, suggesting strong geographic structuring. Additionally, macrolide resistance is notably lower …
This Zenodo record is a permanently preserved version of a PREreview. You can view the complete PREreview at https://prereview.org/reviews/19587072.
This study addresses a relevant research question by examining how the genomic diversity, antimicrobial resistance patterns, and transmission dynamics of Treponema pallidum in Africa differ from those observed globally. The authors use an observational genomic epidemiology approach, combining cross-sectional and retrospective data with whole genome sequencing, which is appropriate for capturing both spatial and temporal patterns of variation.
The findings indicate that T. pallidum in Africa has considerable genomic diversity, with most infections (83.8%) driven by locally circulating sublineages, suggesting strong geographic structuring. Additionally, macrolide resistance is notably lower than global estimates and appears to be primarily associated with imported strains. Overall, the results support the authors' conclusions, as the data and interpretations are well aligned and follow a coherent analytical progression from genomic analysis to epidemiological inference. These findings contribute valuable new knowledge to a field that has historically been limited by underrepresentation of African genomic data.
Among the main strengths, the study contributes valuable genomic data from an underrepresented region, helping to fill an important gap in global surveillance. The integration of African and global datasets allows meaningful comparisons, while the use of whole genome sequencing and phylogenetic analysis provides high-resolution insights into transmission dynamics and antimicrobial resistance patterns. This methodological approach strengthens the validity of the findings and enhances their relevance for public health.
However, some limitations should be considered. The most important is the limited and uneven geographic sampling, with most data coming from a small number of countries, which may affect the representativeness of the findings. This is particularly relevant when interpreting conclusions about predominantly local transmission, as the observed patterns may partly reflect the geographic concentration of samples and the reliance on clinical populations rather than fully capturing transmission dynamics across the region. Additionally, the use of samples obtained from clinical settings, primarily individuals presenting with symptomatic disease, introduces potential selection bias and may exclude asymptomatic or underserved populations that could play a role in transmission. Similarly, the finding of lower macrolide resistance should be interpreted with caution, since resistance patterns are known to vary across regions and over time, often influenced by local antibiotic use practices.
In conclusion, this is a well-conducted study that provides important insights into the genomic epidemiology of T. pallidum in Africa. While certain limitations related to sampling and representativeness should be more explicitly considered when interpreting the findings, the conclusions are supported by the data and the study offers a meaningful contribution to the field.
Competing interests
The authors declare that they have no competing interests.
Use of Artificial Intelligence (AI)
The authors declare that they did not use generative AI to come up with new ideas for their review.
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