SAYSD1 senses UFMylated ribosome to safeguard co-translational protein translocation at the endoplasmic reticulum
Bibliographic record
Abstract
Translocon clogging at the endoplasmic reticulum (ER) as a result of translation stalling triggers ribosome UFMylation, activating translocation-associated quality control (TAQC) to degrade clogged substrates. How cells sense ribosome UFMylation to initiate TAQC is unclear. We conduct a genome-wide CRISPR-Cas9 screen to identify an uncharacterized membrane protein named SAYSD1 that facilitates TAQC. SAYSD1 associates with the Sec61 translocon and also recognizes both ribosome and UFM1 directly, engaging a stalled nascent chain to ensure its transport via the TRAPP complex to lysosomes for degradation. Like UFM1 deficiency, SAYSD1 depletion causes the accumulation of translocation-stalled proteins at the ER and triggers ER stress. Importantly, disrupting UFM1- and SAYSD1-dependent TAQC in Drosophila leads to intracellular accumulation of translocation-stalled collagens, defective collagen deposition, abnormal basement membranes, and reduced stress tolerance. Thus, SAYSD1 acts as a UFM1 sensor that collaborates with ribosome UFMylation at the site of clogged translocon, safeguarding ER homeostasis during animal development.
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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 | 0.001 |
| Research integrity | 0.001 | 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".