Siglec-9 defines and restrains a natural killer subpopulation highly cytotoxic to HIV-infected cells
Bibliographic record
Abstract
Siglec-9 is an MHC-independent inhibitory receptor expressed on a subset of natural killer (NK) cells. Siglec-9 restrains NK cytotoxicity by binding to sialoglycans (sialic acid-containing glycans) on target cells. Despite the importance of Siglec-9 interactions in tumor immune evasion, their role as an immune evasion mechanism during HIV infection has not been investigated. Using in vivo phenotypic analyses, we found that Siglec-9+ CD56dim NK cells, during HIV infection, exhibit an activated phenotype with higher expression of activating receptors and markers (NKp30, CD38, CD16, DNAM-1, perforin) and lower expression of the inhibitory receptor NKG2A, compared to Siglec-9- CD56dim NK cells. We also found that levels of Siglec-9+ CD56dim NK cells inversely correlate with viral load during viremic infection and CD4+ T cell-associated HIV DNA during suppressed infection. Using in vitro cytotoxicity assays, we confirmed that Siglec-9+ NK cells exhibit higher cytotoxicity towards HIV-infected cells compared to Siglec-9- NK cells. These data are consistent with the notion that Siglec-9+ NK cells are highly cytotoxic against HIV-infected cells. However, blocking Siglec-9 enhanced NK cells' ability to lyse HIV-infected cells, consistent with the known inhibitory function of the Siglec-9 molecule. Together, these data support a model in which the Siglec-9+ CD56dim NK subpopulation is highly cytotoxic against HIV-infected cells even whilst being restrained by the inhibitory effects of Siglec-9. To harness the cytotoxic capacity of the Siglec-9+ NK subpopulation, which is dampened by Siglec-9, we developed a proof-of-concept approach to selectively disrupt Siglec/sialoglycan interactions between NK and HIV-infected cells. We achieved this goal by conjugating Sialidase to several HIV broadly neutralizing antibodies. These conjugates selectively desialylated HIV-infected cells and enhanced NK cells' capacity to kill them. In summary, we identified a novel, glycan-based interaction that may contribute to HIV-infected cells' ability to evade NK immunosurveillance and developed an approach to break this interaction.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".