Enhanced secretion of the amyotrophic lateral sclerosis ALS-associated misfolded TDP-43 mediated by the ER-ubiquitin specific peptidase USP19
Bibliographic record
Abstract
Proteinopathies, such as amyotrophic lateral sclerosis (ALS), are marked by the accumulation of misfolded proteins that disrupt cellular processes. Eukaryotic cells have developed protein quality control systems to eliminate these aberrant proteins, but these systems often fail to differentiate between normal and misfolded proteins. In ALS, pathological inclusions primarily composed of misfolded TDP-43 are a hallmark of the disease. Recently, a novel unconventional secretion process called misfolding-associated protein secretion (MAPS) has been discovered to selectively export misfolded proteins. USP19, an Endoplasmic Reticulum-associated ubiquitin peptidase, plays a crucial role in this process. In this study, we investigated the impact of ER-anchored USP19 on the secretion of misfolded TDP-43. Here we found that USP19 overexpression significantly promotes the secretion of soluble and aggregated misfolded TDP-43, requiring both ER anchoring and ubiquitin peptidase activity. Characterization of the cellular and molecular mechanisms involved in this process highlighted the importance of early autophagosomal and late endosomal/amphisomal compartments, while lysosomes did not play a key role. By using dominant-negative mutants and small interfering RNAs, we identified that USP19-mediated secretion of misfolded TDP-43 is modulated by key factors involved in cellular trafficking and secretion pathways, such as ATG7, the ESCRT-O HGS/HRS, the Rab GTPases RAB11A, RAB8A, and RAB27A, and the v-SNARE VAMP7. We also confirmed the crucial role of the DNAJC5/CSPα cochaperone. Overall, this study provides new insights into how cells manage the secretion of misfolded TDP-43 proteins and potentially opens new avenues for therapeutic interventions in ALS and related disorders.
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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 | 0.000 |
| 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".