A Serine Protease Inhibitor Prevents Endoplasmic Reticulum Stress-induced Cleavage but Not Transport of the Membrane-bound Transcription Factor ATF6
Bibliographic record
Abstract
Mammalian cells express several transcription factors embedded in the endoplasmic reticulum (ER) as transmembrane proteins that are activated by proteolysis, and two types of these proteins have been extensively investigated. One type comprises the sterol regulatory element-binding proteins (SREBP-1 and SREBP-2). The other type comprises the activating transcription factors 6 (ATF6alpha and ATF6beta), which are activated in response to ER stress. It was shown previously that both SREBP and ATF6 are cleaved sequentially first by the Site-1 protease (serine protease) and then by the Site-2 protease (metalloprotease) (Ye, J., Rawson, R. B., Komuro, R., Chen, X., Dave, U. P., Prywes, R., Brown, M. S., and Goldstein, J. L. (2000) Mol. Cell 6, 1355-1364). In this study, we examined various protease inhibitors and found that 4-(2-aminoethyl)benzenesulfonyl fluoride (AEBSF), a serine protease inhibitor, prevented ER stress-induced cleavage of ATF6alpha and ATF6beta, resulting in inhibition of transcriptional induction of ATF6-target genes. AEBSF also inhibited production of the mature form of SREBP-2 that was induced in response to sterol depletion, and appeared to directly prevent cleavage of ATF6alpha and ATF6beta by inhibiting Site-1 protease. As the Site-1 protease is localized in the Golgi apparatus, both SREBP and ATF6 must relocate to the Golgi apparatus to be cleaved. We showed here that AEBSF treatment had little effect on ER stress-induced translocation of ATF6 from the ER to the Golgi apparatus, but blocked nuclear localization of ATF6. These results indicate that the transport of ATF6 from the ER to the Golgi apparatus and that from the Golgi apparatus to the nucleus are distinct steps that can be distinguished by treatment with AEBSF.
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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) | 0.001 | 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) | 0.001 | 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".