A Diacylglycerol-Protein Kinase C-RasGRP1 Pathway Directs Ras Activation upon Antigen Receptor Stimulation of T Cells
Bibliographic record
Abstract
Ras GTPases are on/off switches regulating numerous cellular responses by signaling to various effector molecules. In T lymphocytes, Ras can be activated by two Ras exchange factors, SOS and RasGRP1, which are recruited through the adapters Grb2 and LAT and via the second-messenger diacylglycerol (DAG), respectively. Mitogen-activated protein (MAP) kinase phosphorylation patterns induced by active Ras can vary and contribute to distinct cellular responses. The different consequences of Ras activation by either guanine exchange factor are unknown. DAG also recruits and activates the kinase protein kinase Ctheta (PKCtheta) turning on the Erk MAP kinase pathway, but the biochemical mechanism responsible is unclear. We generated T-cell clones deficient in phorbol myristate acetate (a surrogate for DAG)-induced Ras activation. Analysis of a RasGRP1-deficient Jurkat T-cell clone and RasGRP1 RNA interference in wild-type cells revealed that RasGRP1 is required for optimal, antigen receptor-triggered Ras-Erk activation. RasGRP1 relies on its DAG-binding domain to selectively activate Erk kinases. Activation of Erk correlates with the phosphorylation of threonine residue 184 in RasGRP1. This phosphorylation event requires the activities of novel PKC kinases. Conversely, active PKCtheta depends on RasGRP1 sufficiency to effectively trigger downstream events. Last, DAG-PKC-RasGRP1-driven Ras-Erk activation in T cells is a unique signaling event, not simply compensated for by SOS activity.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".