Escherichia coli: Physiological Clues Which Turn On the Synthesis of Antimicrobial Molecules
Bibliographic record
Abstract
Zoonotic pathogens, like Shiga toxin-producing Escherichia coli (STEC) are a food safety and health risk. To battle the increasing emergence of virulent microbes, novel mitigation strategies are needed. One strategy being considered to combat pathogens is antimicrobial compounds produced by microbes, coined microcins. However, effectors for microcin production are poorly understood, particularly in the context of complex physiological responses along the gastro-intestinal tract (GIT). Previously, we identified an E. coli competitor capable of producing a strong diffusible antimicrobial with microcin-associated characteristics. Our objective was to examine how molecule production of this competitor is affected by physiological properties associated with the GIT, namely the effects of carbon source, bile salt concentration and growth phase. Using previously described liquid- and agar-based assays determined that carbon sources do not affect antimicrobial production of E. coli O103F. However, bile salt concentrations affected production significantly, suggesting that E. coli O103F uses cues along the GIT to modulate the expression of antimicrobial production. Furthermore, E. coli O103F produces the molecule during the exponential phase, contrary to most microcins identified to date. The results underscored the importance of experimental design to identify producers of antimicrobials. To detect antimicrobials, conventional microbiological methods can be a starting point, but not the gold standard.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".