A SILAC-Based Method for Quantitative Proteomic Analysis of Intestinal Organoids
Bibliographic record
Abstract
Organoids have the potential to bridge 3D cell culture to tissue physiology by providing a model resembling in vivo organs. Long-term growing organoids were first isolated from intestinal crypt cells and recreated the renewing intestinal epithelial niche. Since then, this technical breakthrough was applied to many other organs, including prostate, liver, kidney and pancreas. We describe here how to apply a SILAC-based quantitative proteomic approach to measure protein expression changes in intestinal organoids under different experimental conditions. We generated SILAC organoid media that allow organoids to grow and differentiate normally, and confirmed the incorporation of isotopically labelled amino acids. Furthermore, we used a treatment reported to affect organoid differentiation to demonstrate the reproducibility of the quantification using this approach and to validate the identification of proteins that correlate with the inhibition of cellular growth and development. With the combined use of quantitative mass spectrometry, SILAC and organoid culture, we validated this approach and showed that large-scale proteome variations can be measured in an "organ-like" system.
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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 | 0.001 |
| 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) | 0.003 | 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".