Key aspects of papillomavirus infection influence the host cervicovaginal microbiome in a preclinical murine papillomavirus (MmuPV1) infection model
Bibliographic record
Abstract
ABSTRACT Human papillomaviruses (HPVs) are the most common sexually transmitted infection in the United States and are a major etiological agent of cancers in the anogenital tract and oral cavity. Growing evidence suggests changes in the host microbiome are associated with the natural history and ultimate outcome of HPV infection. We sought to define changes in the host cervicovaginal microbiome during papillomavirus infection, persistence, and pathogenesis using the murine papillomavirus (MmuPV1) cervicovaginal infection model. Cervicovaginal lavages were performed over a time course of MmuPV1 infection in immunocompetent female FVB/N mice and extracted DNA was analyzed by qPCR to track MmuPV1 viral copy number. 16S ribosomal RNA (rRNA) gene sequencing was used to determine the composition and diversity of microbial communities throughout this time course. We also sought to determine whether specific microbial communities exist across the spectrum of MmuPV1-induced neoplastic disease. We, therefore, performed laser-capture microdissection to isolate regions of disease representing all stages of neoplastic disease progression (normal, low- and high-grade dysplasia, and cancer) from female reproductive tract tissue sections from MmuPV1-infected mice and performed 16S rRNA sequencing. Consistent with other studies, we found that the natural murine cervicovaginal microbiome is highly variable across different experiments. Despite these differences in initial microbiome composition between experiments, we observed that MmuPV1 persistence, viral load, and severity of disease influenced the composition of the cervicovaginal microbiome. These studies demonstrate that papillomavirus infection can alter the cervicovaginal microbiome. IMPORTANCE Human papillomaviruses (HPVs) are the most common sexually transmitted infection in the United States. A subset of HPVs that infect the anogenital tract (cervix, vagina, anus) and oral cavity cause at least 5% of cancers worldwide. Recent evidence indicates that the community of microbial organisms present in the human cervix and vagina, known as the cervicovaginal microbiome, plays a role in HPV-induced cervical cancer. However, the mechanisms underlying this interplay are not well-defined. In this study, we infected the female reproductive tract of mice with a murine papillomavirus (MmuPV1) and found that key aspects of papillomavirus infection and disease influence the host cervicovaginal microbiome. This is the first study to define changes in the host microbiome associated with MmuPV1 infection in a preclinical animal model of HPV-induced cervical cancer. These results pave the way for using MmuPV1 infection models to further investigate the interactions between papillomaviruses and the host microbiome.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".