Exon Level Transcriptomic Profiling of HIV-1-Infected CD4+ T Cells Reveals Virus-Induced Genes and Host Environment Favorable for Viral Replication
Bibliographic record
Abstract
HIV-1 is extremely specialized since, even amongst CD4(+) T lymphocytes (its major natural reservoir in peripheral blood), the virus productively infects only a small proportion of cells under an activated state. As the percentage of HIV-1-infected cells is very low, most studies have so far failed to capture the precise transcriptomic profile at the whole-genome scale of cells highly susceptible to virus infection. Using Affymetrix Exon array technology and a reporter virus allowing the magnetic isolation of HIV-1-infected cells, we describe the host cell factors most favorable for virus establishment and replication along with an overview of virus-induced changes in host gene expression occurring exclusively in target cells productively infected with HIV-1. We also establish that within a population of activated CD4(+) T cells, HIV-1 has no detectable effect on the transcriptome of uninfected bystander cells at early time points following infection. The data gathered in this study provides unique insights into the biology of HIV-1-infected CD4(+) T cells and identifies genes thought to play a determinant role in the interplay between the virus and its host. Furthermore, it provides the first catalogue of alternative splicing events found in primary human CD4(+) T cells productively infected with HIV-1.
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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".