Examination of Bacterial Inhibition Using a Catalytic DNA
Bibliographic record
Abstract
Determination of accurate dosage of existing antibiotics and discovery of new antimicrobials or probiotics entail simple but effective methods that can conveniently track bacteria growth and inhibition. Here we explore the application of a previously reported fluorogenic E. coli-specific DNAzyme (catalytic DNA), RFD-EC1, as a molecular probe for monitoring bacterial inhibition exerted by antibiotics and for studying bacterial competition as a result of cohabitation. Because the DNAzyme method provides a convenient way to monitor the growth of E. coli, it is capable of determining the minimal inhibitory concentration (MIC) of antibiotics much faster than the conventional optical density (OD) method. In addition, since the target for RFD-EC1 is an extracellular protein molecule from E. coli, RFD-EC1 is able to identify pore-forming antibiotics or compounds that can cause membrane leakage. Finally, RFD-EC1 can be used to analyse the competition of cohabitating bacteria, specifically the inhibition of growth of E. coli by Bacillus subtilis. The current work represents the first exploration of a catalytic DNA for microbiological applications and showcases the utility of bacteria-sensing fluorogenic DNAzymes as simple molecular probes to facilitate antibiotic and probiotic research.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".