Cross-packaging of genetically distinct mouse and primate retroviral RNAs
Bibliographic record
Abstract
BACKGROUND: The mouse mammary tumor virus (MMTV) is unique from other retroviruses in having multiple viral promoters, which can be regulated by hormones in a tissue specific manner. This unique property has lead to increased interest in studying MMTV replication with the hope of developing MMTV based vectors for human gene therapy. However, it has recently been reported that related as well as unrelated retroviruses can cross-package each other's genome raising safety concerns towards the use of candidate retroviral vectors for human gene therapy. Therefore, using a trans complementation assay, we looked at the ability of MMTV RNA to be cross-packaged and propagated by an unrelated primate Mason-Pfizer monkey virus (MPMV) that has intracellular assembly process similar to that of MMTV. RESULTS: Our results revealed that MMTV and MPMV RNAs could be cross-packaged by the heterologous virus particles reciprocally suggesting that pseudotyping between two genetically distinct retroviruses can take place at the RNA level. However, the cross-packaged RNAs could not be propagated further indicating a block at post-packaging events in the retroviral life cycle. To further confirm that the specificity of cross-packaging was conferred by the packaging sequences (psi), we cloned the packaging sequences of these viruses on expression plasmids that generated non-viral RNAs. Test of these non-viral RNAs confirmed that the reciprocal cross-packaging was primarily due to the recognition of psi by the heterologous virus proteins. CONCLUSION: The results presented in this study strongly argue that MPMV and MMTV are promiscuous in their ability to cross-package each other's genome suggesting potential RNA-protein interactions among divergent retroviral RNAs proposing that these interactions are more complicated than originally thought. Furthermore, these observations raise the possibility that MMTV and MPMV genomes could also co-package providing substrates for exchanging genetic information.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".