Arginine methylation by PRMT1 regulates nuclear-cytoplasmic localization and toxicity of FUS/TLS harbouring ALS-linked mutations
Bibliographic record
Abstract
Mutations in FUS/TLS (fused in sarcoma/translated in liposarcoma) cause an inheritable form of amyotrophic lateral sclerosis (ALS6). In contrast to FUS(WT), which is concentrated in the nucleus, these mutants are abnormally distributed in the cytoplasm where they form inclusions and associate with stress granules. The data reported herein demonstrate the importance of protein arginine methylation in nuclear-cytoplasmic shuttling of FUS and abnormalities of ALS-causing mutants. Depletion of protein arginine methyltransferase 1 (PRMT1; the enzyme that methylates FUS) in mouse embryonic fibroblasts by gene knockout, or in human HEK293 cells by siRNA knockdown, diminished the ability of ALS-linked FUS mutants to localize to the cytoplasm and form inclusions. To examine properties of FUS mutants in the context of neurons vulnerable to the disease, FUS(WT) and ALS-linked FUS mutants were expressed in motor neurons of dissociated murine spinal cord cultures. In motor neurons, shRNA-mediated PRMT1 knockdown concomitant with the expression of FUS actually accentuated the shift in distribution of ALS-linked FUS mutants from the nucleus to the cytoplasm. However, when PRMT1 was inhibited prior to expression of ALS-linked FUS mutants, by pretreatment with a global methyltransferase inhibitor, ALS-linked FUS mutants were sequestered in the nucleus and cytoplasmic inclusions were reduced, as in the cell lines. Mitochondria were significantly shorter in neurons with cytoplasmic ALS-linked FUS mutants, a factor that could contribute to toxicity. We propose that arginine methylation by PRMT1 participates in the nuclear-cytoplasmic shuttling of FUS, particularly of ALS6-associated mutants, and thus contributes to the toxic gain of function conferred by these disease-causing mutations.
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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".