<i>N</i> -Acetylglucosaminyltransferase V (Mgat5)-Mediated <i>N</i> -Glycosylation Negatively Regulates Th1 Cytokine Production by T Cells
Bibliographic record
Abstract
The differentiation of naive CD4(+) T cells into either proinflammatory Th1 or proallergic Th2 cells strongly influences autoimmunity, allergy, and tumor immune surveillance. We previously demonstrated that beta1,6GlcNAc-branched complex-type (N-acetylglucosaminyltransferase V (Mgat5)) N-glycans on TCR are bound to galectins, an interaction that reduces TCR signaling by opposing agonist-induced TCR clustering at the immune synapse. Mgat5(-/-) mice display late-onset spontaneous autoimmune disease and enhanced resistance to tumor progression and metastasis. In this study we examined the role of beta1,6GlcNAc N-glycan expression in Th1/Th2 cytokine production and differentiation. beta1,6GlcNAc N-glycan expression is enhanced by TCR stimulation independent of cell division and declines at the end of the stimulation cycle. Anti-CD3-activated splenocytes and naive T cells from Mgat5(-/-) mice produce more IFN-gamma and less IL-4 compared with wild-type cells, the latter resulting in the loss of IL-4-dependent down-regulation of IL-4Ralpha. Swainsonine, an inhibitor of Golgi alpha-mannosidase II, blocked beta1,6GlcNAc N-glycan expression and caused a similar increase in IFN-gamma production by T cells from humans and mice, but no additional enhancement in Mgat5(-/-) T cells. Mgat5 deficiency did not alter IFN-gamma/IL-4 production by polarized Th1 cells, but caused an approximately 10-fold increase in IFN-gamma production by polarized Th2 cells. These data indicate that negative regulation of TCR signaling by beta1,6GlcNAc N-glycans promotes development of Th2 over Th1 responses, enhances polarization of Th2 cells, and suggests a mechanism for the increased autoimmune disease susceptibility observed in Mgat5(-/-) mice.
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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".