Mycoplasmal endosymbionts of Trichomonas vaginalis are associated with reduced risk for Chlamydia trachomatis endometrial infection in asymptomatic, coinfected, women.
Sun, X.; Yount, K. S.; Batsuli, N. N.; Campbell, C.; Jeong, S.; Tollison, T. S.; Peng, X.; Darville, T.; Zheng, X.; O'Connell, C. M.
Show abstract
Trichomonas vaginalis is a protozoan parasite that causes trichomoniasis, the most common curable non-viral sexually transmitted infection, and Chlamydia trachomatis is a bacterial pathogen that can ascend to the upper genital tract and cause pelvic inflammatory disease, infertility, and ectopic pregnancy. T. vaginalis harbors bacterial endosymbionts, including Candidatus Malacoplasma girerdii, an obligate symbiont, and Metamycoplasma hominis, which can live freely or symbiotically. In a 16S rRNA sequencing study of the cervicovaginal microbiome of women at high risk for chlamydial infection, Ca. M. girerdii abundance was one of 13 features predicting lack of chlamydial spread to the endometrium, despite no direct association between T. vaginalis infection and reduced chlamydial ascension. Investigating the relationship between these microorganisms further, we found that T. vaginalis vaginal abundance correlated positively with chlamydial burden in women whose infection was confined to the cervix, while a nonsignificant inverse relationship was seen in women with endometrial spread. Among participants with high chlamydial burden, Ca. M. girerdii was detected exclusively in women without endometrial infection. Both endosymbionts trended toward more frequent detection, and higher abundance, in coinfected women without endometrial spread, while M. hominis abundance correlated strongly with T. vaginalis burden in this group. These findings suggest that mycoplasmal endosymbionts of T. vaginalis, rather than T. vaginalis itself, are microbial factors limiting chlamydial ascension, and point to a three-way interaction between parasite, endosymbiont, and bacterial pathogen that shapes upper genital tract C. trachomatis infection risk.
Matching journals
The top 6 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Cervicovaginal microbial features predict Chlamydia trachomatis spread to the upper genital tract of infected women 95%
- TLR3 Deficiency Leads to Altered Immune Responses to Chlamydia trachomatis Infection in Human Oviduct Epithelial Cells 92%
- Bacteriophage-mediated reduction of uropathogenic E. coli from the urogenital epithelium 91%
Similar papers in this journal
- Molecular Characterization of Vaginal Microbiota Using a New 22-Species qRT-PCR Test to Achieve a Relative-abundance and Species-based Diagnosis of Bacterial Vaginosis 93%
- Comparative transcriptomic profiling of human conjunctival epithelial cells and macrophages in response to Chlamydia trachomatis genovars A and B in early- and mid-infection cycles 92%
- Microbiota compositions from infertile couples seeking in vitro fertilization (IVF), using 16S rRNA gene sequencing methods: any correlation to clinical outcomes? 91%
Similar papers in this journal
Similar papers in this journal
- Circulating Chlamydia trachomatis-specific T Cell Immunity Reflects Widespread Exposure in South African Adolescents and Young Women 95%
- High Prevalence and Genotypic Diversity of Persistent Chlamydia trachomatis Infections Among South African Adolescent Girls and Young Women: A Tale of Two Cities 93%
- Seroreversion to Chlamydia trachomatis Pgp3 antigen among young children in a hyperendemic region of Amhara, Ethiopia 90%
Similar papers in this journal
- Cervicovaginal microbiota predicts Neisseria gonorrhoeae clinical presentation 96%
- Antimicrobial resistance profiling and phylogenetic analysis of Neisseria gonorrhoeae clinical isolates from Kenya in a resource-limited setting 90%
- Computational Microbiome Pharmacology Analysis Elucidates the Anti-Cancer Potential of Vaginal Microbes and Metabolites 88%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.