Developing a Non-aureus Staphylococci Transposon Mutant Library and Testing it in a Bovine Mammary Gland Infection Model
Bibliographic record
Abstract
Bovine mastitis is a prevalent and costly disease impacting the mammary gland health of dairy cows, resulting in 300-400 million CAD in annual losses to the Canadian dairy industry. Although mastitis can be caused by numerous bacterial species, non-aureus staphylococci (NAS) collectively account for a significant number of chronic subclinical infections. Among these, Staphylococcus simulans and Staphylococcus chromogenes are among the most frequently isolated and host-adapted NAS species associated with bovine mastitis yet are greatly understudied. To better understand the mechanisms underlying S. simulans adaptation to the bovine mammary gland, we constructed a transposon mutant library containing approximately 100,000 unique mutants derived from a bovine S. simulans isolate. The library was produced by transforming a transposon-plasmid system then inducing transposon mutagenesis via high temperature and using negative selection to kill non-mutant cells. The mutant library was tested in all mammary glands of three lactating cows for 48 hours. Inoculation resulted in the development of clinical mastitis, characterized by inflammation and altered milk appearance. Mutant libraries were recovered from all six sets of supramammary lymph nodes and three mammary glands. Output libraries size averaged to 127,696 CFU per tissue. We attempted to develop and optimize a protocol to prepare isolated DNA from the mutant libraries for downstream next generation sequencing and analysis by targeting transposon insertions via probe hybridization and circularization. The protocol was tested successfully on a control plasmid template but requires further optimization for transposon libraries. We discuss what parts of the protocol require optimization and explore ways to further optimize the protocol, then describe which mutant knockouts we expect to see based on our previous analysis of putative virulence factors of S. simulans strains from our collection. We then conclude with alternative approaches and recommended changes to the project and future directions. This work represents the first use of a live bovine mammary gland model to screen a large transposon mutant library and offers a new tool for any researchers interested in identifying genes of interest for pathogens involved in mastitis such as other NAS species, Staphylococcus aureus, Streptococcus uberis, and E. coli.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".