Host-Soluble Galectin-1 Promotes HIV-1 Replication through a Direct Interaction with Glycans of Viral gp120 and Host CD4
Bibliographic record
Abstract
Sexual transmission of HIV-1 requires virus adsorption to a target cell, typically a CD4(+) T lymphocyte residing in the lamina propria, beneath the epithelium. To escape the mucosal clearance system and reach its target cells, HIV-1 has evolved strategies to circumvent deleterious host factors. Galectin-1, a soluble lectin found in the underlayers of the epithelium, increases HIV-1 infectivity by accelerating its binding to susceptible cells. By comparison, galectin-3, a family member expressed by epithelial cells and part of the mucosal clearance system, does not perform similarly. We show here that galectin-1 directly binds to HIV-1 in a β-galactoside-dependent fashion through recognition of clusters of N-linked glycans on the viral envelope gp120. Unexpectedly, this preferential binding of galectin-1 does not rely on the primary sequence of any particular glycans. Instead, glycan clustering arising from the tertiary structure of gp120 hinders its binding by galectin-3. Increased polyvalency of a specific ligand epitope is a common strategy for glycans to increase their avidity for lectins. In this peculiar occurrence, glycan clustering is instead exploited to prevent binding of gp120 by galectin-3, which would lead to a biological dead-end for the virus. Our data also suggest that galectin-1 binds preferentially to CD4, the host receptor for gp120. Together, these results suggest that HIV-1 exploits galectin-1 to enhance gp120-CD4 interactions, thereby promoting virus attachment and infection events. Since viral adhesion is a rate-limiting step for HIV-1 entry, modulation of the gp120 interaction with galectin-1 could thus represent a novel approach for the prevention of HIV-1 transmission.
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 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 | 0.000 | 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) | 0.000 | 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".