Ubc9 Interacts with and SUMOylates the TCR Adaptor SLP-76 for NFAT Transcription in T Cells
Bibliographic record
Abstract
Although the immune adaptor SH2 domain containing leukocyte phosphoprotein of 76 kDa (SLP-76) integrates and propagates the TCR signaling, the regulation of SLP-76 during the TCR signaling is incompletely studied. In this article, we report that SLP-76 interacts with the small ubiquitin-like modifier (SUMO) E2 conjugase Ubc9 and is a substrate for Ubc9-mediated SUMOylation in human and mouse T cells. TCR stimulation promotes SLP-76-Ubc9 binding, accompanied by an increase in SLP-76 SUMOylation. Ubc9 binds to the extreme C terminus of SLP-76 spanning residues 516-533 and SUMOylates SLP-76 at two conserved residues K266 and K284. In addition, SLP-76 and Ubc9 synergizes to augment the TCR-mediated IL-2 transcription by NFAT in a manner dependent of SUMOylation of SLP-76. Moreover, although not affecting the TCR proximal signaling events, the Ubc9-mediated SUMOylation of SLP-76 is required for TCR-induced assembly of Ubc9-NFAT complex for IL-2 transcription. Together, these results suggest that Ubc9 modulates the function of SLP-76 in T cell activation both by direct interaction and by SUMOylation of SLP-76 and that the Ubc9-SLP-76 module acts as a novel regulatory complex in the control of T cell activation.
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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) | 0.002 | 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".