Irgm1 protects hematopoietic stem cells by negative regulation of IFN signaling
Bibliographic record
Abstract
The IFN-inducible immunity-related p47 GTPase Irgm1 has been linked to Crohn disease as well as susceptibility to tuberculosis. Previously we demonstrated that HSC quiescence and function are aberrant in mice lacking Irgm1. To investigate the molecular basis for these defects, we conducted microarray expression profiling of Irgm1-deficient HSCs. Cell-cycle and IFN-response genes are up-regulated in Irgm1(-/-) HSCs, consistent with dysregulated IFN signaling. To test the hypothesis that Irgm1 normally down-regulates IFN signaling in HSCs, we generated Irgm1(-/-)Ifngr1(-/-) and Irgm1(-/-)Stat1(-/-) double-knockout animals. Strikingly, hyperproliferation, self-renewal, and autophagy defects in Irgm1(-/-) HSCs were normalized in double-knockout animals. These defects were also abolished in Irgm1(-/-)Irgm3(-/-) double-knockout animals, indicating that Irgm1 may regulate Irgm3 activity. Furthermore, the number of HSCs was reduced in aged Irgm1(-/-) animals, suggesting that negative feedback inhibition of IFN signaling by Irgm1 is necessary to prevent hyperproliferation and depletion of the stem cell compartment. Collectively, our results indicate that Irgm1 is a powerful negative regulator of IFN-dependent stimulation in HSCs, with an essential role in preserving HSC number and function. The deleterious effects of excessive IFN signaling may explain how hematologic abnormalities arise in patients with inflammatory conditions.
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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) | 0.001 | 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 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".