Substrates of the ASB2α E3 ubiquitin ligase in dendritic cells
Bibliographic record
Abstract
Conventional dendritic cells (cDCs) comprise distinct populations with specialized immune functions that are mediators of innate and adaptive immune responses. Transcriptomic and proteomic approaches have been used so far to identify transcripts and proteins that are differentially expressed in these subsets to understand the respective functions of cDCs subsets. Here, we showed that the Cullin 5-RING E3 ubiquitin ligase (E3) ASB2α, by driving degradation of filamin A (FLNa) and filamin B (FLNb), is responsible for the difference in FLNa and FLNb abundance in the different spleen cDC subsets. Importantly, the ability of these cDC subsets to migrate correlates with the level of FLNa. Furthermore, our results strongly point to CD4 positive and double negative cDCs as distinct populations. Finally, we develop quantitative global proteomic approaches to identify ASB2α substrates in DCs using ASB2 conditional knockout mice. As component of the ubiquitin-proteasome system (UPS) are amenable to pharmacological manipulation, these approaches aimed to the identification of E3 substrates in physiological relevant settings could potentially lead to novel targets for therapeutic strategies.
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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 | 0.001 | 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 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".