Comparative proteomics in the wild: Accounting for intrapopulation variability improves describing proteome response in a Gammarus pulex field population exposed to cadmium
Bibliographic record
Abstract
High-throughput proteomics can be performed on animal sentinels for discovering key molecular biomarkers signing the physiological response and adaptation of organisms. Ecotoxicoproteomics is today amenable by means of proteogenomics to small arthropods such as Gammarids which are well known sentinels of aquatic environments. Here, we analysed two regional Gammarus pulex populations to characterize the potential proteome divergence induced in one site by natural bioavailable mono-metallic contamination (cadmium) compared to a non-contaminated site. Two RNAseq-derived protein sequence databases were established previously on male and female individuals sampled from the reference site. Here, individual proteomes were acquired on 10 male and 10 female paired organisms sampled from each site. Proteins involved in protein lipidation, carbohydrate metabolism, proteolysis, innate immunity, oxidative stress response and lipid transport were found more abundant in animals exposed to cadmium, while hemocyanins were found in lower abundance. The intrapopulation proteome variability of long-term exposed G. pulex was inflated relatively to the non-contaminated population. These results show that, while remaining a challenge for such organisms with not yet sequenced genomes, taking into account intrapopulation variability is important to better define the molecular players induced by toxic stress in a comparative field proteomics approach.
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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 | 0.001 | 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 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".