The impact of heptose phosphates on HIV latency and human immune responses
Bibliographic record
Abstract
Use of HIV-specific antiretroviral therapeutic agents (ARTs) achieves total control of viremia and prevents progression of HIV to AIDS, but they are not a cure. Shock-and-kill therapy aims to use HIV latency reversal agents to promote clearance of HIV infected CD4 T-cells that make up the HIV reservoir to achieve drug-free remission from HIV. Latency reversal agents proposed for shock-and-kill showed suboptimal clinical performance and novel compounds that can promote HIV latency reversal and promote an antiviral immune response is sorely needed. Work in our lab dedicated to unravelling the molecular mechanisms behind the infectious synergy between Neisseria gonorrhoeae and HIV discovered that heptose phosphates are a novel class of microbe-associated molecular patterns (MAMPs) that is shed by N.gonorrhoeae to drive the modulation of an inflammatory response through the TIFA-dependent NF-κB signaling cascade. Here, I report that immunogenic heptose phosphates show promise as HIV latency reversal agents. Heptose phosphates effectively induced HIV latency reversal in neoplastic T-cell lines latently infected with HIV without overt toxicity and activated NF-κB and NFAT in a TIFA dependent manner. Further, heptose phosphates synergized with conventional latency reversal agents. Despite causing limited and donor specific HIV latency reversal in CD8 T-cell depleted PBMCs and failing to promote HIV latency reversal in primary CD4 T-cells latently infected with HIV ex vivo, heptose phosphates induced specific activation of memory CD4 T-cell subsets in peripheral blood mononuclear cell (PBMC) cultures. Heptose phosphates induced a diverse cytokine response indicative of simultaneous pro- and anti-inflammatory immune responses. Taking an unbiased approach to determine the cells responsible for this apparent contradiction, single-cell RNA sequencing of PBMCs from a healthy donor treated with heptose phosphates was performed. This approach revealed a type-II interferon response shared across cells present in the dataset. This response primed CD4 T-cells to respond to heptose phosphates further by increasing TIFA protein within them. This priming effect showed potential for HIV latency reversal induction in PBMCs from chronically HIV infected donors. Overall, heptose phosphates display characteristics of HIV latency reversal agents and ongoing research is warranted to make use of these compounds in the clinic a reality
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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".