1H NMR-Based Metabolomics of Daphnia magna Sub-lethal Exposure to Organic Contaminants in the Absence and Presence of Dissolved Organic Matter
Bibliographic record
Abstract
Ecotoxicity tests which monitor observable endpoints such as mortality, growth and reproduction do not assess the molecular mode of action of contaminants in target organisms. Also, aquatic toxicity tests often do not include dissolved organic matter (DOM), which is ubiquitously found in natural waters. Hydrophobic organic contaminants sorb to DOM which may alter the bioavailability and toxicity of these contaminants. To assess this hypothesis, proton (1H) nuclear magnetic resonance (NMR)-based metabolomics was used to analyze the metabolome of Daphnia magna after acute sub-lethal exposure to organic contaminants in the absence or presence of DOM. Triclosan, carbamazepine and ibuprofen exposure resulted in different metabolic responses in D. magna. DOM at 5 mg dissolved organic carbon/L (DOC/L) did not change the D. magna metabolome from carbamazepine, imidacloprid or tris(2-chloroethyl) phosphate exposure, perhaps because these weakly hydrophobic contaminants do not sorb to DOM. The metabolic response of D. magna from 17α-ethynylestradiol (EE2) exposure was suppressed by 1, 2, 3, 4 and 5 mg DOC/L, likely from decreased EE2 bioavailability with DOM. The metabolic response in D. magna from perfluorooctane sulfonate (PFOS) exposure was not altered with 1 mg DOC/L. However, PFOS exposure with 2, 3, 4 and 5 mg DOC/L resulted in a unique metabolic response in D. magna, which may be due to enhanced PFOS bioavailability or combined action of PFOS and DOM on the metabolome. The metabolic response of D. magna from tris(2-butoxyethyl) phosphate (TBOEP) exposure was unaltered with 5 mg DOC/L, perhaps from the high potency of TBOEP. D. magna exposure to triphenyl phosphate (TPhP) with 5 mg DOC/L resulted in a unique metabolic response compared to TPhP exposure, possibly from combined stress of TPhP and DOM on the metabolome or altered TPhP bioavailability. The mode of action of mixtures of the hydrophobic contaminants triclosan, TPhP and diazinon in D. magna was not altered by 1 and 5 mg DOC/L. Overall, DOM may enhance or suppress the metabolic perturbations in aquatic organisms that originate from sub-lethal exposure to organic contaminants. Therefore, DOM should be included when evaluating molecular-level responses from sub-lethal ecotoxicity tests and during risk assessment of environmental mixtures.
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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".