Sequencing and culture-based characterization of the vaginal and uterine microbiota in beef cattle that became pregnant or remained open following artificial insemination
Bibliographic record
Abstract
ABSTRACT In this study, we evaluated the vaginal and uterine microbiota between beef cattle that became pregnant via artificial insemination (AI) and those that remained open to identify microbial signatures associated with fertility. We also characterized the culturable fraction of these microbiota and screened certain vaginal and uterine bacterial isolates for antimicrobial resistance. For this, vaginal and uterine swabs were collected before AI from two cohorts of Angus-crossbred cattle: mature cows (vaginal and uterine: 27 open and 31 pregnant) and heifers (vaginal: 26 open and 33 pregnant). The microbiota of these samples were assessed using 16S rRNA gene sequencing and culturing. Twenty-nine vaginal and uterine bacterial isolates were screened for resistance against 41 antibiotics. Within the vaginal microbiota, 11 amplicon sequence variants (ASVs) were more relatively abundant in the open heifers compared with the pregnant heifers. No differentially abundant ASVs were detected in the vaginal samples from pregnant versus open cows. Pregnant cows had a distinct uterine microbiota community structure ( P = 0.008) and interaction network structure compared with open cows. Twenty-eight differentially abundant uterine ASVs were observed between the pregnant and open cows. Community structure and diversity were different between the cow’s vagina and uterus. A total of 733 bacterial isolates were recovered from vaginal (512) and uterine (221) swabs under aerobic (83 different species) and anaerobic (69 species) culturing. Among these isolates were pathogenic species and those mostly susceptible to tested antibiotics. Overall, our results indicate that fertility-associated taxonomic signatures are present in the bovine uterine and vaginal microbiota. IMPORTANCE Emerging evidence suggests that microbiome-targeted approaches may provide a novel opportunity to reduce the incidence of reproductive failures in cattle. To develop such microbiome-based strategies, one of the first logical steps is to identify reproductive microbiome features related to fertility and to isolate the fertility-associated microbial species for developing a future bacterial consortium that could be administered before breeding to enhance pregnancy outcomes. Here, we characterized the vaginal and uterine microbiota in beef cattle that became pregnant or remained open via artificial insemination and identified microbiota features associated with fertility. We compared similarities between vaginal and uterine microbiota and between heifers and cows. Using culturing, we provided new insights into the culturable fraction of the vaginal and uterine microbiota and their antimicrobial resistance. Overall, our findings will serve as an important basis for future research aimed at harnessing the vaginal and uterine microbiome for improved cattle fertility.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".