T Cell Activation In Vivo Targets Diacylglycerol Kinase α to the Membrane: A Novel Mechanism for Ras Attenuation
Bibliographic record
Abstract
Diacylglycerol kinase (DGK) phosphorylates diacylglycerol to produce phosphatidic acid, leading to decreased and increased levels, respectively, of these two lipid messengers that play a central role in T cell activation. Nine DGK isoforms, grouped into five subtypes, are found in higher organisms; all contain a conserved C-terminal domain and at least two cysteine-rich motifs of unknown function. In this study, we have researched in vivo the regulation of DGK alpha, using a transgenic mouse model in which injection of an antigenic peptide activates the majority of peripheral T cells. We demonstrate that DGK alpha, highly expressed in resting T lymphocytes, is subject to complex control at the mRNA and protein levels during in vivo T cell activation. Subcellular fractionation of T lymphocytes shortly after in vivo engagement of the TCR shows rapid translocation of cytosolic DGK alpha to the membrane fraction. At early time points, DGK alpha translocation to the membrane correlates with rapid translocation of Ras guanyl nucleotide-releasing protein (RasGRP), a nucleotide exchange activator for Ras that associates to the membrane through a diacylglycerol-binding domain. To demonstrate a causal relationship between DGK alpha activity and RasGRP relocation to the membrane, we determined RasGRP translocation kinetics in a T cell line transiently transfected with constitutive active and dominant-negative DGK alpha mutants. We show that membrane localization of DGK alpha is associated with a negative regulatory signal for Ras activation by reversing RasGRP translocation. This study is the first demonstration of in vivo regulation of DGK alpha, and provides new insight into the functional role of a member of this family of lipid kinases in the regulation of the immune response.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".