512 Divergence of the sow vaginal microbiome based on fertility status
Bibliographic record
Abstract
Abstract The need for alternative biomarkers of reproductive potential in the pork industry is apparent as the current selection approach for sow fertility is not keeping up with the improvement of other production-related traits. To date, the vaginal microbiome has been overlooked as a source of potential biomarkers of sow fertility status. We aimed to elucidate a possible divergence of the vaginal microbiome between sows of differing fertility status and identify possible microbial biomarkers that classify the fertility potential of a sow. Microbial DNA was extracted from vaginal microbiome samples originating from highly reproductive sows (HRP, n = 41) with the number of piglets born alive ≥ 13 or infertile sows (INF, n = 22), that failed to become pregnant after two rounds of consecutive artificial insemination. Our 16S rRNA sequencing results revealed significant (P < 0.05) beta diversity divergence at the family and genus taxonomic levels between HRP and INF vaginal communities. INF vaginal communities displayed significantly greater (P < 0.05) alpha diversity at both the family and genus levels and had a significantly (P < 0.05) greater number of unique OTUs identified at the genus level. The composition of the vaginal microbiome diverges between HRP and INF sows, with INF sows experiencing a disruption of their communities via the colonization of opportunistic pathogens reducing the abundance of normal microbiota seen in HRP. The genera Streptococcus, Lachnospiraceae XPB1014 group, Staphylococcus and Treponema were selected to test as potential biomarkers due to their univariate significance, contribution to partial least squares discriminant analysis (PLS-DA) and selection in a recursive feature elimination model (RFE). The resultant support-vector machine model was diagnostic (achieving an ROC-AUC = 0.86), supporting the selected biomarkers as diagnostic markers for sow fertility status. Overall, there was an apparent shift from a normal vaginal microbiota in HRP sows to a dysbiotic vaginal microbiota in INF sows dominated by potentially pathogenic, more anaerobic and short-chain fatty acid (SCFA)-producing microbiota that may play damaging and pro-inflammatory roles in the vaginal canal. Lactobacillus, known to be the dominant genus in a majority of healthy human vaginal microbiomes, was not the dominating genus in either INF or HRP vaginal microbiomes, suggesting the uniqueness of pig vaginal microbiomes. This also emphasizes the need for pig-specific vaginal microbiome research. Investigations regarding the application of the potential vaginal microbial biomarkers identified in this study to a large, novel population of sow and gilt vaginal microbiome samples to test their on-farm accuracy are underway. In addition, the mechanistic and physiologic role of SCFAs and the bacteria that produce them in the sow vaginal microbiome should be further investigated to understand how they may influence or be a product of fertility status.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".