Protein profiles of enzymatically isolated rumen epithelium in sheep fed a fibrous diet
Bibliographic record
Abstract
BACKGROUND: The rumen wall plays a major role in efficient transfer of digested nutrients in the rumen to peripheral tissues through the portal venous system. Some of these substrates are metabolised in the epithelium during this process. To identify the specific proteins involved in these processes, we used proteomic technologies. Protein extracts were prepared from ventral rumen tissue of six sheep fed a fibrous diet at 1.5× maintenance energy requirements. Using a newly developed method, we were able to enzymatically isolate the epithelial cells from underlying tissue layers, thus allowing cytosol and membrane fractions to be independently analysed using liquid chromatography tandem mass spectrometry (LC MS/MS). RESULTS: = 85). However, a quarter of the proteins identified were assigned to the plasma membrane or organelle membranes, some of which transport nutrients and metabolites. Of these 91 were transmembrane proteins (TMHMM), 27 had an N-terminal signal peptide (signalP) and TMHMM motif, 13 had a glycosylphosphatidylinositol (GPI) anchor and signalP sequence, 67 had beta (β) strands or 17 β strands and a transit peptide sequence, indicating the identified proteins were integral or peripheral membrane proteins. Subunits of the 5 protein complexes involved in mitochondrial cellular energy production were well represented. Structural proteins (15%), proteins involved in the metabolism of lipids and proteins (26%) and those with steroid or cytokine action were a feature of the proteome. CONCLUSION: Our research has developed a procedure to isolate rumen epithelium proteins from the underlying tissue layers so that they may be profiled using proteomic technologies. The approach improves the number of proteins that can be profiled that are specific to the epithelium of the rumen wall. It provides new insights into the proteins of structural and nutritional importance in the rumen epithelium, that carry out nutrient transport and metabolism, cell growth and signalling.
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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 | 0.001 | 0.000 |
| 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 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".