Autoinducer-2 Triggers the Oxidative Stress Response in <i>Mycobacterium avium</i> , Leading to Biofilm Formation
Bibliographic record
Abstract
Mycobacterium avium is an environmental organism and opportunistic pathogen with inherent resistance to drugs, environmental stresses, and the host immune response. To adapt to these disparate conditions, M. avium must control its transcriptional response to environmental cues. M. avium forms biofilms in various environmental settings, including drinking water pipes and potable water reservoirs. In this study, we investigated the role of the universal signaling molecule autoinducer-2 (AI-2) in biofilm formation by M. avium. The addition of the compound to planktonic M. avium cultures resulted in increased biofilm formation. Microarray and reverse transcriptase PCR studies revealed an upregulation of the oxidative stress response upon addition of AI-2. This suggests that the response to AI-2 might be related to oxidative stress, rather than quorum sensing. Consistent with this model, addition of hydrogen peroxide, a known stimulus of the oxidative stress response, to M. avium cultures resulted in elevated biofilm formation. These results suggest that AI-2 does not act as a quorum-sensing signal in M. avium. Instead, biofilm formation is triggered by environmental stresses of biotic and abiotic origins and AI-2 may exert effects on that level.
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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 | 0.000 |
| 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) | 0.001 | 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".