Comparative Analysis of Antisense RNA, Double-Stranded RNA, and Delta Ribozyme-Mediated Gene Regulation in <i>Toxoplasma gondii</i>
Bibliographic record
Abstract
RNA tools, namely, antisense RNA, double-stranded RNA (dsRNA), and delta ribozyme, were comparatively analyzed for the development of effective RNA-based gene modulators. The gene encoding uracil phosphoribosyltransferase (UPRT) of Toxoplasma gondii was used as a target and a negative selectable marker. Using plasmid transformation and drug selection assays, we obtained T. gondii transformants resistant to 5-fluoro-2'-deoxyuridine (FDUR), the cytotoxic prodrug and substrate of UPRT, when the plasmids expressing dsRNA and active delta ribozyme were used. No resistant transformants were detected when the plasmids carrying the antisense RNA, the inactive delta ribozyme, or the chloramphenicol acetyltransferase (CAT) genes were used. Parasites generated using the plasmids expressing dsRNA and the delta ribozyme become resistant to FDUR with an LD50 of 50 +/- 5 microM and 25 +/- 8 microM, respectively. These values are approximately 25-fold and 12-fold higher than that of the RH parental parasite strain, indicating that UPRT activity of the transformed parasites was drastically inhibited. Using Northern and Southern blot analysis, we demonstrated that dsRNA and the delta ribozyme interrupt the expression of UPRT. These two RNA tools should, thus, be very useful for the study of gene expression.
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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 | 0.000 |
| 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".