Proteome Profile of Cytosolic Component of Zebrafish Liver Generated by LC−ESI MS/MS Combined with Trypsin Digestion and Microwave-Assisted Acid Hydrolysis
Bibliographic record
Abstract
The zebrafish genome has recently been sequenced and annotated allowing for high-throughput proteomic analysis. Here, we report for the first time a proteomic subset of zebrafish liver, an important organ for metabolizing toxins. Using a newly developed analytical procedure, we have identified 1204 proteins from the cytosolic component of a zebrafish liver tissue sample. Our methods involve cell-compartment fractionation of liver tissue samples, four levels of protein digestion, and off-line two-dimensional liquid chromatography (2-D LC) separations of resultant peptides. Proteins are identified using an electrospray ionization quadrupole time-of-flight tandem mass spectrometer (ESI-QTOF MS/MS), which provides high-resolution and high-accuracy mass measurement of peptide ions and their fragment ions. We demonstrate that greater proteome coverage can be achieved by combining the results obtained from four methods of protein digestion: three tryptic digests (one in buffer, one in methanol, and another in SDS), and a microwave-assisted acid hydrolysate of the protein extracts. Identified proteins--which included several groups of established protein biomarkers--were functionally classified. We discuss the functions and implications of these biomarkers within the context of zebrafish toxicology.
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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) | 0.001 | 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) | 0.000 | 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".