Sequences Downstream of the 5′ Splice Donor Site Are Required for both Packaging and Dimerization of Human Immunodeficiency Virus Type 1 RNA
Bibliographic record
Abstract
Two copies of human immunodeficiency virus type 1 RNA are incorporated into each virus particle and are further converted to a stable dimer as the virus particle matures. Several RNA segments that flank the 5' splice donor site at nucleotide (nt) 289 have been shown to act as packaging signals. Among these, RNA stem-loop 1 (SL1) (nt 243 to 277) can trigger RNA dimerization through a "kissing-loop" mechanism and thus is termed the dimerization initiation site. However, it is unknown whether other packaging signals are also needed for dimerization. To pursue this subject, we mutated stem-loop 3 (SL3) (nt 312 to 325), a GA-rich region (nt 325 to 336), and two G-rich repeats (nt 363 to 367 and nt 405 to 409) in proviral DNA and assessed the effects on RNA dimerization by performing native Northern blot analyses. Our results show that the structure but not the specific RNA sequence of SL3 is needed not only for efficient viral RNA packaging but also for dimerization. Mutations of the GA-rich sequence severely diminished viral RNA dimerization as well as packaging; the combination of mutations in both SL3 and the GA-rich region led to further decreases, implying independent roles for each of these two RNA motifs. Compensation studies further demonstrated that the RNA-packaging and dimerization activity of the GA-rich sequence may not depend on a putative interaction between this region and a CU repeat sequence at nt 227 to 233. In contrast, substitutions in the two G-rich sequences did not cause any diminution of viral RNA packaging or dimerization. We conclude that both the SL3 motif and GA-rich RNA sequences, located downstream of the 5' splice donor site, are required for efficient RNA packaging and dimerization.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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 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".