Immunoproteasomes control activation of innate immune signaling and microglial function
Bibliographic record
Abstract
Microglia are the resident immune cells of the central nervous system (CNS) and play a major role in the regulation of brain homeostasis. To maintain their cellular protein homeostasis, microglia express standard proteasomes and immunoproteasomes (IP), a proteasome isoform that preserves protein homeostasis also in non-immune cells under challenging conditions. The impact of IP on microglia function in innate immunity of the CNS is however not well described. Here, we establish that IP impairment leads to proteotoxic stress and triggers the unfolded and integrated stress responses in mouse and human microglia models. Using proteomic analysis, we demonstrate that IP deficiency in microglia results in profound alterations of the ubiquitin-modified proteome among which proteins involved in the regulation of stress and immune responses. In line with this, molecular analysis revealed chronic activation of NF-κB signaling in IP-deficient microglia without further stimulus. In addition, we show that IP impairment alters microglial function based on markers for phagocytosis and motility. At the molecular level IP impairment activates interferon signaling promoted by the activation of the cytosolic stress response protein kinase R. The presented data highlight the importance of IP function for the proteostatic potential as well as for precision proteolysis to control stress and immune signaling in microglia function.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".