Nuclear receptor ERRα and coactivator PGC-1β are effectors of IFN-γ-induced host defense
Bibliographic record
Abstract
Macrophage activation by the proinflammatory cytokine interferon-gamma (IFN-gamma) is a critical component of the host innate response to bacterial pathogenesis. However, the precise nature of the IFN-gamma-induced activation pathway is not known. Here we show using genome-wide expression and chromatin-binding profiling that IFN-gamma induces the expression of many nuclear genes encoding mitochondrial respiratory chain machinery via activation of the nuclear receptor ERR alpha (estrogen-related receptor alpha, NR3B1). Studies with macrophages lacking ERR alpha demonstrate that it is required for induction of mitochondrial reactive oxygen species (ROS) production and efficient clearance of Listeria monocytogenes (LM) in response to IFN-gamma. As a result, mice lacking ERR alpha are susceptible to LM infection, a phenotype that is localized to bone marrow-derived cells. Furthermore, we found that IFN-gamma-induced activation of ERR alpha depends on coactivator PGC-1 beta (peroxisome proliferator-activated receptor gamma coactivator-1 beta), which appears to be a direct target for the IFN-gamma/STAT-1 signaling cascade. Thus, ERR alpha and PGC-1 beta act together as a key effector of IFN-gamma-induced mitochondrial ROS production and host defense.
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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 | 0.001 |
| 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".