Lck-dependent Fyn Activation Requires C Terminus-dependent Targeting of Kinase-active Lck to Lipid Rafts
Bibliographic record
Abstract
Mechanisms regulating the activation and delivery of function of Lck and Fyn are central to the generation of the most proximal signaling events emanating from the T cell antigen receptor (TcR) complex. Recent results demonstrate that lipid rafts (LR) segregate Lck and Fyn and play a fundamental role in the temporal and spatial coordination of their activation. Specifically, TcR-CD4 co-aggregation-induced Lck activation outside LR results in Lck translocation to LR where the activation of LR-resident Fyn ensues. Here we report a structure-function analysis toward characterizing the mechanism supporting Lck partitioning to LR and its capacity to activate co-localized Fyn. Using NIH 3T3 cells ectopically expressing FynT, we demonstrate that only LR-associated, kinase-active (Y505F)Lck reciprocally co-immunoprecipitates with and activates Fyn. Mutational analyses revealed a profound reduction in the formation of Lck-Fyn complexes and Fyn activation, using kinase domain mutants K273R and Y394F of (Y505F)Lck, both of which have profoundly compromised kinase activity. The only kinase-active Lck mutants tested that revealed impaired physical and enzymatic engagement with Fyn were those involving truncation of the C-terminal sequence YQPQP. Remarkably, sequential truncation of YQPQP resulted in an increasing reduction of kinase-active Lck partitioning to LR, in both fibroblasts and T cells. This in turn correlated with an ablation of the capacity of these truncates to enhance TcR-mediated interleukin-2 production. Thus, Lck-dependent Fyn activation is predicated by proximity-mediated transphosphorylation of the Fyn kinase domain, and targeting kinase-active Lck to LR is dependent on the C-terminal sequence QPQP.
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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".