A common epitope is shared by activated signal transducer and activator of transcription-5 (STAT5) and the phosphorylated erythropoietin receptor: implications for the docking model of STAT activation
Bibliographic record
Abstract
Erythropoietin (EPO) specifically activates the Janus kinase JAK2 and the transcription factor signal transducer and activator of transcription-5 (STAT5). All members of the STAT family are tyrosine phosphorylated in response to cytokine stimulation at a conserved carboxy-terminal tyrosine, Y694, in the case of STAT5. To determine structural features important for STAT signaling, we generated an activation-specific STAT5 antibody using a phosphopeptide containing amino acids 687 to 698 of STAT5 as antigen. This antibody specifically recognizes tyrosine- phosphorylated STAT5 but not nonphosphorylated STAT5. In immunoprecipitation reactions from cell lines and primary erythroblasts, 2 distinct polyclonal activation-specific STAT5 antibodies selectively immunoprecipitate the tyrosine phosphorylated EPO receptor (EPO-R) in addition to STAT5 under native and denaturing conditions. We propose that the activation-specific STAT5 antibody recognizes the 2 substrates to which the STAT5 SH2 domain interacts, namely, the tyrosine- phosphorylated EPO-R and STAT5 itself. Several studies have implicated EPO-R Y343, Y401, Y431, and Y479 in the recruitment of STAT5. Using a series of EPO-R tyrosine mutants expressed in Ba/F3 cells, we have shown that the activation-specific STAT5 antibody immunoprecipitates an EPO-R containing only 2 tyrosines at positions 343 and 401, confirming the importance of these tyrosines in STAT5 recruitment. These data uncover a novel aspect of STAT SH2 domain recognition and demonstrate the utility of activation-specific antibodies for examining the specificity of STAT-cytokine receptor interactions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".