Rac2, a Hematopoiesis-Specific Rho GTPase, Specifically Regulates Mast Cell Protease Gene Expression in Bone Marrow-Derived Mast Cells
Bibliographic record
Abstract
Rho family GTPases activate intracellular kinase cascades to modulate transcription of multiple genes. Previous studies have examined the roles of the ubiquitously expressed Rho GTPase, Rac1, in regulation of gene expression in cell lines and implicated NF-kappaB, serum response factor, and kinase signaling pathways in this regulation. To understand the role of the closely related but hematopoiesis-specific Rho GTPase, Rac2, in regulation of gene transcription, we compared the gene expression profiles between wild-type and Rac2(-/-) bone marrow-derived mast cells. Our data demonstrate remarkable specificity in the regulation of gene expression by Rac2 versus Rac1. Microarray analysis demonstrated that expression of 38 known genes was significantly altered in Rac2(-/-) mast cells after cytokine stimulation compared with those in wild-type cells. Of these, the expression of the mouse mast cell protease 7 (MMCP-7) gene in wild-type cells was highly induced at the transcriptional level after stimulation with stem cell factor (SCF). In spite of compensatorily increased expression of Rac1 in Rac2-deficient cells, SCF-induced MMCP-7 transcription did not occur. Surprisingly, the loss of MMCP-7 induction was not due to decreased activation of NF-kappaB, a transcription factor postulated to lie downstream of Rac1 and known to play a critical role in hematopoietic cell differentiation and proliferation. However, the activities of c-Jun N-terminal kinases (JNKs) were markedly decreased in Rac2(-/-) mast cells. Our results suggest that cytokine-stimulated activation of MMCP-7 gene transcription is selectively regulated by a Rac2-dependent JNK signaling pathway in primary mast cells and imply a remarkable specificity in the regulation of transcriptional activity by these two highly related Rho GTPases.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".