O-GlcNAcylation: A Nutrient-Sensitive Metabolic Rheostat in Anti-Viral Immunity and Viral Pathogenesis
Bibliographic record
Abstract
Viruses account for the most abundant biological entities in the biosphere and can be either symbiotic or pathogenic. While pathogenic viruses have developed strategies to evade immunity, the host immune system evolved overlapping and redundant defenses to sense and fight viral infections. Nutrition and metabolic needs sculpt viral-host interactions and determine the course and outcomes of the infection. In this review, we focus on the hexosamine biosynthesis pathway (HBP), a nutrient sensing pathway that controls immune responses and host-viral interactions. The HBP converges on O-GlcNAcylation, a dynamic post-translational modification of cellular proteins, that emerged as a critical effector of immune cell development, differentiation and effector functions. We highlight recent discoveries identifying the impact of this metabolic modification on anti-viral immunity and viral restriction, and conversely on exacerbating viral-induced pathologic inflammation or viral oncogenesis. We discuss the clinical implications of these findings and perspectives of harnessing this pathway for therapeutic purposes.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".