Stimulatory and Toxic Effects of Neurotransmitters on the lux Operon-Dependent Bioluminescence of Escherichia coli K12 TGI
Bibliographic record
Abstract
Background: The normal functioning of the brain requires neuromediators, i.e., substances that transmit messages between nervous cells. Neurochemicals also function as signals that are involved in communication among the microorganisms that inhabit the human organism. While the impact of “classical” neurotransmitters including catecholamines, serotonin, and histamine on microorganisms has been investigated in a number of recent publications, this work provides evidence for the stimulatory and inhibitory (toxic) effects of some other important neurochemicals that have not received sufficient attention in the literature.Methods: The biosensor was based on a GM Escherichia coli K12 strain (TGI) that contained the lux operon of the luminescent soil bacterium Photorhabdus luminescencens ZMI. The biosensor was exposed to the action of the tested neurotransmitters for 15 mins to 144 hrs. The intensity of bacterial luminescence (counts / second) was monitored in the control and the experimental samples with an 1251 BioOrbit luminometer (Finland).Results: Neurochemicals such as putrescine, acetylcholine, taurin, and indole were found to stimulate, at low concentrations (0.1-10 µM), the luminescence of the strain E. coli K12 TGI containing the lux operon from Photorhabdus luminescencens ZMI. At higher concentrations, putrescine, taurin, and indole exerted a weak toxic influence, i.e. they marginally attenuated the luminescence of E. coli K12 TGI.Conclusions: Based on the data obtained, a regulatory, presumably receptor-dependent, effect is exerted by the tested neurochemicals on the bacterium E. coli K12 TGI, in an analogy to their impact on nervous, immune, and other specialized types of eukaryotic cells. However, high neurochemical concentrations are likely to produce nonspecific effects on the bacterial luciferase system and/or on membrane phosphorylation.
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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 | 0.001 | 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 | 0.001 |
| 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".