The occurrence of <i>Aerococcus urinaeequi</i> and non-aureus Staphylococci in raw milk negatively correlates with <i>Escherichia coli</i> clinical mastitis
Bibliographic record
Abstract
Abstract Escherichia coli is a common environmental pathogen associated with clinical mastitis (CM) in dairy cattle. There is an interest in optimizing the udder microbiome to increase the resistance of dairy cattle to E. coli CM; however, the details of which members of the healthy udder microbiota may play a role in antagonizing E. coli are unknown. In this study, we characterized the bacterial community composition in raw milk collected from quarters of lactating Holstein dairy cows that developed E. coli CM during lactation, including milk from both healthy and diseased quarters (n=1,172). The milk microbiome from infected quarters was compared before, during, and after CM. A combination of 16S rRNA gene amplicon and shotgun metagenomic sequencing were used generate datasets with a high level of both depth and breadth. The microbial diversity present in raw milk significantly decreased in quarters experiencing E. coli CM, indicating that E. coli displaces other members of the microbiome. However, the diversity recovered very rapidly after infection. Two genera: Staphylococcus, Aerococcus, and the family Oscillospiraceae were significantly more abundant in healthy quarters with low inflammation. Species of these genera: Staphylococcus auricularis, Staphylococcus haemolyticus, and Aerocussus urinaeequi were identified by shotgun metagenomics. Thus, these species are of interest for optimizing the microbiome to discourage E. coli colonization without triggering inflammation. Importance In this study we show that E. coli outcompetes and displaces several members of the udder microbiome during CM, but that microbial diversity recovers post-infection. In milk from quarters which remained healthy, the community composition was often highly dominated by S. auricularis, S. haemolyticus, A. urinaeequi, and S. marcescens without corresponding increases in somatic cell count (SCC). Community dominance by these organisms, without inflammation, could indicate that these species could be potential prophylactics that could contribute to colonization resistance for the pathogen and prevent future instances of E. coli CM.
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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) | 0.000 | 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) | 0.001 | 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".