Biomolecular characterization of Trichomonas vaginalis from Spain: evaluating genetic correlation with drug resistance and endobionts.
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2025
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MDPI
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Ibáñez-Escribano, A.; Nogal-Ruiz, J.J.; Escario, J.A.; Ponce- Gordo, F. Biomolecular Characterization of Trichomonas vaginalis from Spain: Evaluating Genetic Correlation with Drug Resistance and Endobionts. Biology 2025, 14, 618. https://doi.org/10.3390/ biology14060618
Abstract
Trichomonas vaginalis causes one of the most prevalent sexually transmitted infections (STIs). Despite extensive biomolecular research on this protozoan, no efficient molecular tool currently exists for the intraspecific classification of T. vaginalis isolates. In recent years, an incipient tendency has been observed to classify this parasite into two genotypes that correlate in a high percentage with phenotypic characteristics (such as metronidazole resistance and viral endobionts). However, this grouping method has not yet been consolidated by the scientific community. In this sense, Mycoplasma hominis has also been identified as an endobiont of T. vaginalis, but no previous studies on its presence and possible correlation with the two T. vaginalis populations detected have been executed. In the present study, several new T. vaginalis isolates of Spanish origin have been characterized using two molecular markers (microsatellites and single-copy genes), the presence of T. vaginalis virus (TVV) and Mycoplasma, and the resistance to reference drugs. On the basis of our molecular results, the isolates were classified into two groups, as proposed by other researchers. In relation to the biological determinations, the two isolates harboring Mycoplasma were sensible to the reference drugs and were included in the same genotypic group. Although the presence of TVV was more notable in one group than in the other, both groups had TTV+ and TVV− isolates. These findings indicate that genetic grouping does not strongly correlate with susceptibility to reference drugs or endobiont presence, suggesting the need for further research into alternative classification models.