Comparative genomic analysis of Escherichia coli isolated from cases of bovine clinical mastitis and the dairy farm environment
Bibliographic record
Abstract
Escherichia coli is a major causative agent of environmental bovine mastitis, and this disease causes significant economic losses for the dairy industry. There is still debate in the literature as to whether mammary pathogenic E. coli (MPEC) is indeed a unique E. coli pathotype or if this infection is merely an opportunistic infection caused by any E. coli isolate being displaced from the bovine gastrointestinal tract to the environment and then into the udder. In this study, we conducted a thorough genomic analysis of 113 MPEC isolates from clinical mastitis cases and 100 environmental E. coli isolates from the environment of dairy farms around the world. A phylogenomic analysis indicated that MPEC and the environmental E. coli isolates formed clades based on common sequence types and O antigens but did not cluster based on mammary pathogenicity. The comparison of core and soft-core genes of each set of isolates identified the three genes of the ferric dicitrate uptake system (Fec), fecI, fecR and fecA, as soft-core genes of MPEC (n=110). These genes were also present in 27 E. coli isolates from environmental sources. Rather than being a virulence gene cluster, it is likely that the Fec system provides a competitive advantage to E. coli in the mammary gland – an iron-poor environment. Using this cluster as a marker for MPEC may offer an opportunity to develop novel treatments for E. coli mastitis, based on its presence.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.001 |
| 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) | 0.001 | 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".