Genome-Wide Innate Immune Responses in HIV-1-Infected Macrophages Are Preserved Despite Attenuation of the NF-κB Activation Pathway
Bibliographic record
Abstract
Macrophages contribute to HIV-1 infection at many levels. They provide permissive cells at the site of inoculation, augment virus transfer to T cells, generate long-lived viral reservoirs, and cause bystander cell apoptosis. A body of evidence suggests that the role of macrophages in cellular host defense is also compromised by HIV-1 infection. In this respect, macrophages are potent cells of the innate immune system that initiate and regulate wide-ranging immunological responses. This study focuses on the effect of HIV-1 infection on innate immune responses by macrophages at the level of signal transduction, whole genome transcriptional profiling, and cytokine secretion. We show that in an ex vivo model, M-CSF-differentiated monocyte-derived macrophages uniformly infected with replicating CCR5-tropic HIV-1, without cytopathic effect, exhibit selective attenuation of the NF-kappaB activation pathway in response to TLR4 and TLR2 stimulation. However, functional annotation clustering analysis of genome-wide transcriptional responses to LPS stimulation suggests substantial preservation of gene expression changes at the systems level, with modest attenuation of a subset of up-regulated LPS-responsive genes, and no effect on a selection of inflammatory cytokine responses at the protein level. These results extend existing reports of inhibitory interactions between HIV-1 accessory proteins and NF-kappaB signaling pathways, and whole genome expression profiling provides comprehensive assessment of the consequent effects on immune response gene expression. Unexpectedly, our data suggest innate immune responses are broadly preserved with limited exceptions, and pave the way for further study of the complex relationship between HIV-1 and immunological pathways within macrophages.
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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 | 0.001 |
| 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".