Toxicity and disruption of quorum sensing in Aliivibrio fisheri by environmental chemicals: Impacts of selected contaminants and microplastics
Bibliographic record
Abstract
The purpose of this study was to examine the effects of dissolved and particulate compounds on quorum sensing in the marine luminescent bacterium Aliivibrio fisheri. Bacteria were exposed to increasing concentrations of CuSO4 (Cu2+), gadolinium chloride (Gd3+), 20-nm silver nanoparticles (nanoAg) and 1-3 μm microplastic polyethylene beads for 250 min. During this period, luminescence measurements were taken at 5-min intervals. Toxicity was first examined by measuring luminescence output at 5-min and 30-min incubation time. Based on the effective concentration that decreases luminescence by 20% (EC20), the compounds were toxic at the following concentrations in decreasing toxicity: Cu2+ (3.2 mg/L) < nanoAg (3.4 mg/L, reported) < Gd3+ (34 mg/L) < microplastics (2.6 g/L). The data revealed that luminescence changed non-linearly over time. In control bacteria, luminescence changed at eight specific major frequencies between 0.04 and 0.27 cycle/min after Fourier transformation of time-dependent luminescence data. The addition of dissolved Cu2+ and Gd3+ eliminated the amplitude changes at these frequencies in a concentration-dependent manner, indicating loss of quorum sensing between bacteria at concentrations below EC20. In the presence of nanoAg and microplastic beads, the decreases in amplitudes were modest but compressed the luminescence profiles, with shorter frequencies appearing at concentrations well below EC20. Thus, loss of communication between bacteria occurs at non-toxic concentrations. In addition, with exposure to a mixture of the above compounds at concentrations that do not produce effects for Gd3+, nanoAg and microplastics, Cu2+ toxicity was significantly enhanced, suggesting synergy. This study revealed for the first time that small microplastic particles and nanoparticles can disrupt quorum sensing in marine bacteria.
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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 | 0.001 | 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 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".