Silencing of SPC2 Expression Using an Engineered δ Ribozyme in the Mouse βTC-3 Endocrine Cell Line
Bibliographic record
Abstract
Endoproteolytic processing is carried out by subtilase-like pro-protein convertases in mammalian cells. In order to understand the distinct roles of a member of this family (SPC2), gene silencing in cultured cells is an ideal approach. Previous studies showed limited success in either the degree of inhibition obtained or the stability of the cell lines. Here we demonstrate the high potential of delta ribozyme as a post-transcriptional gene silencing tool in cultured cells. We used an expression vector based on the RNA polymerase III promoter to establish betaTC-3 stable cell lines expressing the chimeric tRNA(Val)-delta ribozyme transcript targeting SPC2 mRNA. Northern and Western blot hybridizations showed a specific reduction of SPC2 mRNA and protein. Validation of processing effects was tested by measuring the levels of dynorphin A-(1-8), which are present in betaTC-3 cells as a result of the unique cleavage of dynorphin A-(1-17) by SPC2. Moreover, a differential proteomic analysis confirmed these results and allowed identification of secretogranin II as a potential substrate of SPC2. The development of efficient, specific, and durable silencing tools, such as described in the present work, will be of great importance in elucidating the functions of the subtilase-like pro-protein convertases in regard to peptide processing and derived cellular events.
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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 | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".