A non-targeted proteomics investigation of cylindrospermopsin-induced hepatotoxicity
Bibliographic record
Abstract
Cyanobacteria is perhaps the phylum that profit the most from the escalating hypereutrophication of continental waters. The resulting cyanobacterial blooms may accumulate a variety of potent toxins. Cylindrospermopsin (CYN) is a cyanotoxin known for inhibiting protein synthesis, and producing oxidative stress as well as DNA damage in eukaryotic cells. Since the toxin\\'s molecular mechanisms and targets are still unclear, we purified the cyanotoxin from our lab strains and employed a shotgun proteomics approach to reveal the major changes in HepG2 cells at sublethal doses of CYN (1 µM for 6, 12 and 24h). Metabolically labeled cells were stimulated and lysed after each treatment, their tryptic digests were separated by nano HPLC and analyzed by high-resolution tandem mass spectrometry (HRMS) on data dependent acquisition mode. We scanned an average of 4000 proteins in every sample throughout the three timepoints. Cholesterol biosynthesis and transport was mostly downregulated throughout the timepooints of the experiment. Downregulation of proteins related to ubiquitination (e.g. UBE2L3) and proteolysis pathways (e.g. PSMA2) was observed in the proteomics dataset, and these results were validated by western blot. Transcription, translation and cell cycle processes showed convoluted regulation dynamics involving known cell cycle regulators like PCNA. Downregulation of mitochondrial enzymes, oxidative stress and damage to the mithochondrial inner membrane was early evidenced after a 6 hrs treatment and validated using a JC-1, a mitochondrial membrane potential probe. The resulting dataset gives us a first glimpse of the protein groups affected at the early stage of CYN cell intoxication.
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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 | 0.001 |
| 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".