Does swab type matter? Comparing methods for Mannheimia haemolytica recovery and upper respiratory microbiome characterization in feedlot cattle
Bibliographic record
Abstract
BACKGROUND: Bovine respiratory disease (BRD) is caused by interactions among host, environment, and pathogens. One standard method for antemortem pathogen identification in cattle with BRD is deep-guarded nasopharyngeal swabbing, which is challenging, costly, and waste generating. The objective was to compare the ability to recover Mannheimia haemolytica and compare microbial community structure using 29.5 inch (74.9 cm) deep-guarded nasopharyngeal swabs, 16 inch (40.6 cm) unguarded proctology swabs, or 6 inch (15.2 cm) unguarded nasal swabs when characterized using culture, real time-qPCR, and 16S rRNA gene sequencing. Samples for aerobic culture, qPCR, and 16S rRNA gene sequencing were collected from the upper respiratory tract of cattle 2 weeks after feedlot arrival. RESULTS: There was high concordance of culture and qPCR results for all swab types (results for 77% and 81% of sampled animals completely across all 3 swab types for culture and qPCR respectively). Microbial communities were highly similar among samples collected with different swab types, and differences identified relative to treatment for BRD were also similar. Positive qPCR results for M. haemolytica were highly concordant (81% agreed completely), but samples collected by deep-guarded swabbing had lower amounts of Mh DNA identified (Kruskal-Wallis analysis of variance on ranks, P < 0.05; Dunn-test for pairwise comparison with Benjamini-Hochberg correction, P < 0.05) and lower frequency of positive compared to nasal and proctology swabs (McNemar's Chi-square test, P < 0.05). CONCLUSIONS: Though differences existed among different types of swabs collected from individual cattle, nasal swabs and proctology swabs offer comparable results to deep-guarded nasopharyngeal swabs when identifying and characterizing M. haemolytica by culture, 16S rRNA gene sequencing, and qPCR.
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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 | 0.024 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".