MARCH1 E3 Ubiquitin Ligase Dampens the Innate Inflammatory Response by Modulating Monocyte Functions in Mice
Bibliographic record
Abstract
Abstract Ubiquitination was recently identified as a central process in the pathogenesis and development of numerous inflammatory diseases, such as obesity, atherosclerosis, and asthma. Treatment with proteasomal inhibitors led to severe side effects because ubiquitination is heavily involved in a plethora of cellular functions. Thus, new players regulating ubiquitination processes must be identified to improve therapies for inflammatory diseases. In addition to their role in adaptive immunity, endosomal MHC class II (MHCII) molecules were shown to modulate innate immune responses by fine tuning the TLR4 signaling pathway. However, the role of MHCII ubiquitination by membrane associated ring-CH-type finger 1 (MARCH1) E3 ubiquitin ligase in this process remains to be assessed. In this article, we demonstrate that MARCH1 is a key inhibitor of innate inflammation in response to bacterial endotoxins. The higher mortality of March1−/− mice challenged with a lethal dose of LPS was associated with significantly stronger systemic production of proinflammatory cytokines and splenic NK cell activation; however, we did not find evidence that MARCH1 modulates LPS or IL-10 signaling pathways. Instead, the mechanism by which MARCH1 protects against endotoxic shock rests on its capacity to promote the transition of monocytes from Ly6CHi to Ly6C+/−. Moreover, in competitive bone marrow chimeras, March1−/− monocytes and polymorphonuclear neutrophils outcompeted wild-type cells with regard to bone marrow egress and homing to peripheral organs. We conclude that MARCH1 exerts MHCII-independent effects that regulate the innate arm of immunity. Thus, MARCH1 might represent a potential new target for emerging therapies based on ubiquitination reactions in inflammatory diseases.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".