Comparative phosphoproteomics analysis of the effects of L-methionine on dairy cow mammary epithelial cells
Bibliographic record
Abstract
Lu, L., Gao, X., Li, Q., Huang, J., Liu, R. and Li, H. 2012. Comparative phosphoproteomics analysis of the effects of L-methionine on dairy cow mammary epithelial cells. Can. J. Anim. Sci. 92: 433–442. L-methionine is an essential amino acid that plays fundamental roles in protein synthesis. Many nuclear phosphorylated proteins such as Stat5 (signal transducer and activator of transcription 5) and mTOR (mammalian target of rapamycin) regulate milk protein synthesis. But a comprehensive understanding of transcriptional and posttranscriptional regulation of milk protein synthesis is lacking. In the current study, two-dimensional gel electrophoresis (2-DE)/MS-based proteomics analysis was used to identify phosphoproteins responsible for milk protein synthesis in dairy cow mammary epithelial cells (DCMECs). The effects of L-methionine on DCMECs were analyzed by CASY (Counter Analyser System) technique, reversed phase high performance liquid chromatography. The results showed that rate of cell proliferation and expression of β-casein were increased in DCMECs treated with 0.6 mM L-methionine for 24 h. Five proteins for which expression was significantly increased in DCMECs were selected, and their expression changes were verified by quantitative real-time PCR and Western blot analysis. The five up-regulated expressed phosphoproteins included Staphylococcal nuclease domain-containing protein 1(SND1), Septin-6, Glycyl-tRNA synthetase (GARS), Twinfilin-1 and eukaryotic elongation factor1-beta (eEF1B). This study revealed that availability of L-methionine influences the levels of nuclear phosphorylated proteins of DCMECs which opens a new avenue for the study of the molecular mechanism linking to milk protein synthesis.
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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 | 0.000 | 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) | 0.000 | 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".