No detectable differences in Nef-mediated downregulation of HLA-I and CD4 molecules among HIV-1 group M lineages circulating in Cameroon, where the pandemic originated
Bibliographic record
Abstract
HIV-1 group M (HIV-1M) lineages downregulate HLA-I and CD4 expression via their Nef proteins. We hypothesized that these Nef functions may be partially responsible for the differences in prevalence of viruses from different lineages that co-circulate within an epidemic. Here, we characterized these two Nef activities in HIV-1M isolates from Cameroon, where multiple variants have been circulating since the pandemic's origin. Single HIV-1 Nef clones from 234 HIV-1-ART naïve individuals living in remote villages and two cosmopolitan cities of Cameroon, sampled between 2000 and 2013, were isolated from plasma HIV RNA and analyzed for their capacity to downregulate HLA-I and CD4 molecules. We found that, despite a large degree of within- and inter- lineage variation, the ability of Nef to downregulate HLA-I was similar across these different viruses. Moreover, Nef-mediated CD4 downregulation activity was also well conserved across the different lineages found in Cameroon. In addition, we observed a trend towards higher HLA-I downregulation activity of viruses circulating in the cosmopolitan cities versus the remote villages, whereas the CD4 downregulation activities were similar across the two settings. Furthermore, we noted a significant decline of HLA-I downregulation activity from 2000 to 2013, providing additional evidence supporting the attenuation of the global HIV-1M population over time. Finally, we identified 18 amino acids associated with differential HLA-I downregulation and 13 amino acids associated with differential CD4 downregulation within the dominant CRF02_AG lineage. Our lack of observation of HIV lineage-related differences in Nef-mediated HLA-I and CD4 downregulation function suggests that these activities do not substantively influence the prevalence of different HIV-1M lineages in Cameroon.
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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) | 0.001 | 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".