Biomolecular condensates: insights into early and late steps of the HIV-1 replication cycle
Bibliographic record
Abstract
A rapidly evolving understanding of phase separation in the biological and physical sciences has led to the redefining of virus-engineered replication compartments in many viruses with RNA genomes. Condensation of viral, host and genomic and subgenomic RNAs can take place to evade the innate immunity response and to help viral replication. Divergent viruses prompt liquid-liquid phase separation (LLPS) to invade the host cell. During HIV replication there are several steps involving LLPS. In this review, we characterize the ability of individual viral and host partners that assemble into biomolecular condensates (BMCs). Of note, bioinformatic analyses predict models of phase separation in line with several published observations. Importantly, viral BMCs contribute to function in key steps retroviral replication. For example, reverse transcription takes place within nuclear BMCs, called HIV-MLOs while during late replication steps, retroviral nucleocapsid acts as a driver or scaffold to recruit client viral components to aid the assembly of progeny virions. Overall, LLPS during viral infections represents a newly described biological event now appreciated in the virology field, that can also be considered as an alternative pharmacological target to current drug therapies especially when viruses become resistant to antiviral treatment.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".