A new, reliable, and high-throughput strategy to screen bacteria for antagonistic activity against Staphylococcus aureus
Bibliographic record
Abstract
BACKGROUND: Antibiotic-resistant Staphylococcus aureus clones have emerged globally over the last few decades. Probiotics have been actively studied as an alternative to antibiotics to prevent and treat S. aureus infections, but identifying new probiotic bacteria, that have antagonistic activity against S. aureus, is difficult since traditional screening strategies are time-consuming and expensive. Here, we describe a new plasmid-based method which uses highly stable plasmids to screen bacteria with antagonistic activity against S. aureus. RESULTS: or mCherry under the control of a S. aureus quorum-sensing (QS) promoter (agrP3). Using this recombinant plasmid pair, we tested 81 bacteria isolated from Holstein dairy milk to identify bacteria that had growth-inhibiting activity against S. aureus and suggest potential explanations for the growth inhibition. The stability test illustrated that pQS1 and pQS3 remained highly stable for at least 24 h in batch culture conditions without selection pressure from antibiotics. This allowed co-culturing of S. aureus with other bacteria. Using the newly developed pQS plasmids, we found commensal bacteria, isolated from raw bovine milk, which had growth-inhibiting activity (n = 13) and quorum-quenching (QQ) activity (n = 13) towards both S. aureus Sa25 (CC97) and Sa27 (CC151). The pQS-based method is efficient and effective for simultaneously screening growth-inhibiting and QQ bacteria against S. aureus on agar media. CONCLUSIONS: It was shown that growth-inhibiting and QQ activity toward pQS plasmid transformants of S. aureus can be simultaneously monitored by observing the zone of growth inhibition and reporter protein inhibition on agar plates. Newly identified antagonistic bacteria and their functional biomolecules are promising candidates for future development of probiotic drugs and prophylactics/therapeutics for bacterial infections including S. aureus. Furthermore, this new approach can be a useful method to find bacteria that can be used to prevent and treat S. aureus infections in both humans and animals.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".