Immunoproteasomes shape the transcriptome and regulate the function of dendritic cells (IRM7P.476)
Bibliographic record
Abstract
Abstract Background: By regulating protein degradation, constitutive proteasomes (CPs) regulate practically all fundamental cellular processes. Vertebrates also express immunoproteasomes (IPs), but the only well-established non-redundant role for IPs is their enhanced ability to generate peptides for MHC-I presentation. Results: Here we show that IPs regulate the expression of 8,104 genes in maturing bone marrow-derived dendritic cells (DCs). IPs regulated transcription of many mRNAs and maturation of a subset of them. These genes were separated into 15 different kinetic patterns, and Gene-Ontology analysis revealed enrichment linked to immune functions and housekeeping cellular processes, highlighting the complexity of the transcriptional cascade regulated by IPs. Notably, IPs’ impact on transcription was mediated through the non-redundant regulation of critical immune-related pathways, such as Nf-kB, STATs and IRFs. Furthermore, even when loaded with optimal amounts of SIINFEKL, IP-deficient DCs were inefficient for in vivo priming of OT-1 T cells. Conclusion: Our study shows that the role of IPs is not limited to antigen processing and highlights a new and critical role for IPs in regulation of gene expression. The dramatic impact of IPs on the transcriptional landscape could explain the various immune and non-immune phenotypes observed in vertebrates with IP-deficiency or -mutation.
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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".