The nasopharyngeal microbiota of beef cattle before and after transport to a feedlot
Bibliographic record
Abstract
BACKGROUND: The nasopharyngeal (NP) microbiota plays an important role in bovine health, comprising a rich and diverse microbial community. The nasopharynx is also the niche for potentially pathogenic agents which are associated with bovine respiratory disease (BRD), a serious and costly illness in feedlot cattle. We used 14 beef heifers from a closed and disease-free herd to assess the dynamics of the NP microbiota of cattle that are transported to a feedlot. Cattle were sampled prior to transport to the feedlot (day 0) and at days 2, 7, and 14. RESULTS: The structure of the NP microbiota changed significantly over the course of the study, with the largest shift occurring between day 0 (prior to transport) and day 2 (P < 0.001). Phylogenetic diversity and richness increased following feedlot placement (day 2; P < 0.05). The genera Pasteurella, Bacillus, and Proteus were enriched at day 0, Streptococcus and Acinetobacter at day 2, Bifidobacterium at day 7, and Mycoplasma at day 14. The functional potential of the NP microbiota was assessed using PICRUSt, revealing that replication and repair, as well as translation pathways, were more relatively abundant in day 14 samples. These differences were driven mostly by Mycoplasma. Although eight cattle were culture-positive for the BRD-associated bacterium Pasteurella multocida at one or more sampling times, none were culture-positive for Mannheimia haemolytica or Histophilus somni. CONCLUSIONS: This study investigated the effect that feedlot placement has on the NP microbiota of beef cattle over a 14-d period. Within two days of transport to the feedlot, the NP microbiota changed significantly, increasing in both phylogenetic diversity and richness. These results demonstrate that there is an abrupt shift in the NP microbiota of cattle after transportation to a feedlot. This may have importance for understanding why cattle are most susceptible to BRD after feedlot placement.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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 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".