A chemical-genetic approach to inhibit Csk activates T cells independently of the T cell receptor (35.4)
Bibliographic record
Abstract
Abstract Src family kinases are normally inhibited by phosphorylation of their C-terminal tail by the tyrosine kinase Csk, and are positively regulated by the phosphatase CD45 and by receptor stimulation. Attempts to study the role of Csk in T cell receptor (TCR) signaling have been hampered by early embryonic lethality of Csk-/- mice and by perturbed thymocyte development in LckCre x Cskfl/fl mice. We have established a small-molecule inhibitor system to determine the effects of Csk localization and catalytic function on the regulation of TCR signaling. A novel analog-sensitive allele of Csk, CskAS, maintains normal function, but can be rapidly and specifically inhibited by 3IB-PP1, an analog of the PP1 kinase inhibitor. The function of wild-type Csk is unaffected by 3IB-PP1. We show that membrane-targeted CskAS, but not cytoplasmic CskAS, blocks TCR signal transduction. Using 3IB-PP1 to inhibit CskAS leads to rapid activation of proximal T cell signaling events including phosphorylation of CD3ζ and ERK1/2, increased cytoplasmic calcium, and downstream upregulation of CD69 expression and downregulation of the TCR. Together, these data suggest that introduction of CskAS alleles are sufficient to alter the basal steady state of Src family kinase activity in T cells. Inhibition of CskAS thus releases cells from tonic inhibition, resulting in rapid T cell activation, even in the absence of stimulation through the antigen receptor. This chemical-genetic approach of specific Csk inhibition is a useful means of studying the dynamic inhibition of TCR signaling and may be useful for manipulating the function of T cells. Research support: JRS, NIH T32 Training Grant; CZ, NF1 Foundation; KMS, HHMI; AW, HHMI and the Rosalind Russell Medical Research Center for Arthritis
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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) | 0.001 | 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) | 0.002 | 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".