Broad, CE; Llangari-Arizo, LM; Laing, KG; Romero-Sandoval, NC; Cooper, PJ; Sadiq, ST
(2026)
Trichomonas vaginalis strain diversity among female sex workers in Ecuador using DNA sequence-based typing.
BMC Infectious Diseases, 28.
p. 18.
ISSN 1471-2334
https://doi.org/10.1186/s12879-025-12185-7
SGUL Authors: Laing, Kenneth
|
PDF
Published Version
Available under License Creative Commons Attribution. Download (1MB) |
|
|
PDF (Supplementary Material 1)
Supporting information
Download (1MB) |
|
|
Microsoft Word (.docx) (Supplementary Material 2)
Supporting information
Download (52kB) |
|
|
Microsoft Word (.docx) (Supplementary Material 3)
Supporting information
Download (121kB) |
Abstract
Background Molecular methods to track the spread of Trichomonas vaginalis (TV) infection, the most common curable non-viral sexually transmitted infection globally, associated with poor reproductive health outcomes and low socio-economic status are challenging, as ultra-long repetitive DNA sequences in TV make whole genome sequencing difficult. We undertook multilocus sequence typing (MLST) of TV using nested-PCR from clinical samples, to describe strain diversity among at-risk female sex-workers (FSWs) in Ecuador. Methods Sociodemographic data and vulvo-vaginal swabs were collected from two groups of FSWs, street-based workers (SBWs) and brothel-based workers (BBWs). DNA extracts, positive for TV by real-time PCR, were amplified by two-step nested-PCR for seven TV genes and MLST-amplicon libraries sequenced using Illumina MiSeq. Sequence types (STs) were clustered into clonal complexes using goeBURST and population structure investigated using STRUCTURE. Results Of 250 FSWs, 58 were positive for TV by real-time PCR. Subsets of TV positive vaginal DNA extracts were sequence-typed from 15 SBWs and 17 BBWs, alongside a non-sex worker sample collected from the same region, and a positive control. Compared with BBWs, SBWs were older (p < 0.001) and earnt less for sex work. TV-MLST revealed new STs and two major population subtypes. No associations were found between ST and behaviouralcharacteristics. goeBURST analysis of study samples identified four clonal complexes in which the largest complex comprised primarily of BBWs. When combined with a larger international dataset, goeBURST revealed 9 clonal complexes and 24 separate STs or nodes. FSWs with the same ancestral TV population structure were not displaced by the added STs. Conclusion TV-MLST revealed high strain diversity among Ecuadorian FSWs and a two-type sub-population. The preservation of links between STs associated with some FSWs when adding a larger set of archived STs, suggests potential for use as an aid to TV associated sexual network identification.
| Item Type: | Article | ||||||||
|---|---|---|---|---|---|---|---|---|---|
| Additional Information: | © The Author(s) 2025. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. | ||||||||
| Keywords: | Ecuador, Sequence-typing, Sex workers, Sexual networks, Trichomonas vaginalis | ||||||||
| SGUL Research Institute / Research Centre: | Academic Structure > Infection and Immunity Research Institute (INII) | ||||||||
| Journal or Publication Title: | BMC Infectious Diseases | ||||||||
| ISSN: | 1471-2334 | ||||||||
| Language: | en | ||||||||
| Media of Output: | Print-Electronic | ||||||||
| Related URLs: | |||||||||
| Publisher License: | Creative Commons: Attribution 4.0 | ||||||||
| PubMed ID: | 41345568 | ||||||||
| Dates: |
|
||||||||
| Go to PubMed abstract | |||||||||
| URI: | https://openaccess.sgul.ac.uk/id/eprint/118160 | ||||||||
| Publisher's version: | https://doi.org/10.1186/s12879-025-12185-7 |
Statistics
Actions (login required)
![]() |
Edit Item |

