Sample Collection Method Bias Effects in Quantitative Phosphoproteomics
Bibliographic record
Abstract
Current advances in selective enrichment, fractionation, and MS detection of phosphorylated peptides allowed identification and quantitation of tens of thousands phosphosites from minute amounts of biological material. One of the major challenges in the field is preserving the in vivo phosphorylation state of the proteins throughout the sample preparation workflow. This is typically achieved by using phosphatase inhibitors and denaturing conditions during cell lysis. Here we determine if the upstream cell collection techniques could introduce changes in protein phosphorylation. To evaluate the effect of sample collection protocols on the global phosphorylation status of the cell, we compared different sample workflows by metabolic labeling and quantitative mass spectrometry on Saccharomyces cerevisiae cell cultures. We identified highly similar phosphopeptides for cells harvested in ice cold isotonic phosphate buffer, cold ethanol, trichloroacetic acid, and liquid nitrogen. However, quantitative analyses revealed that the commonly used phosphate buffer unexpectedly activated signaling events. Such effects may introduce systematic bias in phosphoproteomics measurements and biochemical analysis.
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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 | 0.005 | 0.005 |
| 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 | 0.001 |
| 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".