Distinct cervical tissue-adherent and luminal microbiome communities correlate with mucosal host gene expression and protein levels in Kenyan sex workers
Bibliographic record
Abstract
BACKGROUND: The majority of studies characterizing female genital tract microbiota have focused on luminal organisms, while the presence and impact of tissue-adherent ectocervical microbiota remain incompletely understood. Studies of luminal and tissue-associated bacteria in the gastrointestinal tract suggest that these communities may have distinct roles in health and disease. Here, we performed a multi-omics characterization of paired luminal and tissue samples collected from a cohort of Kenyan female sex workers. RESULTS: We identified a tissue-adherent bacterial microbiome, with a higher alpha diversity than the luminal microbiome, in which dominant genera overall included Gardnerella and Lactobacillus, followed by Prevotella, Atopobium, and Sneathia. About half of the L. iners-dominated luminal samples had a corresponding Gardnerella-dominated tissue microbiome. Broadly, the tissue-adherent microbiome was associated with fewer differentially expressed host genes than the luminal microbiome. Gene set enrichment analysis revealed that L. crispatus-dominated tissue-adherent communities were associated with protein translation and antimicrobial activity, whereas a highly diverse microbial community was associated with epithelial remodeling and pro-inflammatory pathways. Tissue-adherent communities dominated by L. iners and Gardnerella were associated with lower host transcriptional activity. Tissue-adherent microbiomes dominated by Lactobacillus and Gardnerella correlated with host protein profiles associated with epithelial barrier stability, although with a more pro-inflammatory profile for the Gardnerella-dominated microbiome group. Tissue samples with a highly diverse composition had a protein profile representing cell proliferation and pro-inflammatory activity. CONCLUSION: We identified ectocervical tissue-adherent bacterial communities in all study participants of a female sex worker cohort. These communities were distinct from cervicovaginal luminal microbiota in a significant proportion of individuals. We further revealed that bacterial communities at both sites correlated with distinct host gene expression and protein levels. The tissue-adherent bacterial community could possibly act as a reservoir that seed the lumen with less optimal, non-Lactobacillus, bacteria. Video Abstract.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".