RALDH Activity Induced by Bacterial/Fungal Pathogens in CD16+ Monocyte-Derived Dendritic Cells Boosts HIV Infection and Outgrowth in CD4+ T Cells
Bibliographic record
Abstract
Abstract HIV reservoirs persist in gut-homing CD4+ T cells of people living with HIV and receiving antiretroviral therapy, but the antigenic specificity of such reservoirs remains poorly documented. The imprinting for gut homing is mediated by retinoic acid (RA), a vitamin A–derived metabolite produced by dendritic cells (DCs) exhibiting RA-synthesizing (RALDH) activity. RALDH activity in DCs can be induced by TLR2 ligands, such as bacterial peptidoglycans and fungal zymosan. Thus, we hypothesized that bacterial/fungal pathogens triggering RALDH activity in DCs fuel HIV reservoir establishment/outgrowth in pathogen-reactive CD4+ T cells. Our results demonstrate that DCs derived from intermediate/nonclassical CD16+ compared with classical CD16− monocytes exhibited superior RALDH activity and higher capacity to transmit HIV infection to autologous Staphylococcus aureus–reactive T cells. Exposure of total monocyte-derived DCs (MDDCs) to S. aureus lysates as well as TLR2 (zymosan and heat-killed preparation of Listeria monocytogenes) and TLR4 (LPS) agonists but not CMV lysates resulted in a robust upregulation of RALDH activity. MDDCs loaded with S. aureus or zymosan induced the proliferation of T cells with a CCR5+integrin β7+CCR6+ phenotype and efficiently transmitted HIV infection to these T cells via RALDH/RA–dependent mechanisms. Finally, S. aureus– and zymosan-reactive CD4+ T cells of antiretroviral therapy-treated people living with HIV carried replication-competent integrated HIV-DNA, as demonstrated by an MDDC-based viral outgrowth assay. Together, these results support a model in which bacterial/fungal pathogens in the gut promote RALDH activity in MDDCs, especially in CD16+ MDDCs, and subsequently imprint CD4+ T cells with gut-homing potential and HIV permissiveness. Thus, nonviral pathogens play key roles in fueling HIV reservoir establishment/outgrowth via RALDH/RA–dependent mechanisms that may be therapeutically targeted.
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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".