Identification of Novel Subcellular Localization and Trafficking of HIV-1 Nef Variants from Reference Strains G (F1.93.HH8793) and H (BE.93.VI997)
Bibliographic record
Abstract
The human immunodeficiency virus type 1 (HIV-1) accessory protein Nef, plays an essential role in disease progression and pathogenesis via hijacking the host cellular membrane-trafficking machinery. Interestingly, HIV-1 group-M subtypes display differences in the rate of disease progression. However, few reports investigated how the cellular behaviors and activities of Nef isolates from reference strains may differ between HIV-1 group-M subtypes. Here, we characterize how differing cellular distributions of Nef proteins across group-M subtypes may impact protein function using immunofluorescence microscopy and flow cytometric analysis. We demonstrate that Nef variants isolated from HIV-1 group-M subtypes display differences in expression, with low expressing Nef proteins from reference strains of subtypes G (F1.93.HH8793) and H (BE.93.VI997) also displaying decreased functionality. Additionally, we demonstrate variations in the subcellular distribution and localization of these Nef proteins. Nef from subtype G (F1.93.HH8793) and H (BE.93.VI997) reference strains also failed to colocalize with the trans-Golgi network, and were not differentially localized to cellular markers of multivesicular bodies or lysosomes. Strikingly, our results demonstrate that HIV-1 Nef proteins from reference strains G (F1.93.HH8793) and H (BE.93.VI997) highly colocalize with labeled mitochondrial compartments.
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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".