Attenuated <i>Listeria monocytogenes</i> Vectors Overcome Suppressive Plasma Factors During HIV Infection to Stimulate Myeloid Dendritic Cells to Promote Adaptive Immunity and Reactivation of Latent Virus
Bibliographic record
Abstract
HIV-1 infection is characterized by myeloid dendritic cell (DC) dysfunction, which blunts the responsiveness to vaccine adjuvants. We previously showed that nonviral factors in HIV-seropositive plasma are partially responsible for mediating this immune suppression. In this study we investigated recombinant Listeria monocytogenes (Lm) vectors, which naturally infect and potently activate DCs from seronegative donors, as a means to overcome DC dysfunction associated with HIV infection. Monocyte-derived DCs were cocultured with plasma from HIV-infected donors (HIV-moDCs) to induce a dysregulated state and infected with an attenuated, nonreplicative vaccine strain of Lm expressing full length clade B consensus gag (KBMA Lm-gag). Lm infection stimulated cytokine secretion [interleukin (IL)-12p70, tumor necrosis factor (TNF)-α, and IL-6] and Th-1 skewing of allogeneic naive CD4 T cells by HIV-moDCs, in contrast to the suppressive effects observed by HIV plasma on moDCs on toll-like receptor ligand stimulation. Upon coculture of "killed" but metabolically active (KBMA) Lm-gag-infected moDCs from HIV-infected donors with autologous cells, expansion of polyfunctional, gag-specific CD8(+) T cells was observed. Reactivation of latent proviruses by moDCs following Lm infection was also observed in models of HIV latency in a TNF-α-dependent manner. These findings reveal the unique ability of Lm vectors to contend with dysregulation of HIV-moDCs, while simultaneously possessing the capacity to activate latent virus. Concurrent stimulation of innate and adaptive immunity and disruption of latency may be an approach to reduce the pool of latently infected cells during HIV infection. Further study of Lm vectors as part of therapeutic vaccination and eradication strategies may advance this evolving field.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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".