Endoplasmic Reticulum-Targeted Subunit Toxins Provide a New Approach to Rescue Misfolded Mutant Proteins and Revert Cell Models of Genetic Diseases
Bibliographic record
Abstract
Many germ line diseases stem from a relatively minor disturbance in mutant protein endoplasmic reticulum (ER) 3D assembly. Chaperones are recruited which, on failure to correct folding, sort the mutant for retrotranslocation and cytosolic proteasomal degradation (ER-associated degradation-ERAD), to initiate/exacerbate deficiency-disease symptoms. Several bacterial (and plant) subunit toxins, retrograde transport to the ER after initial cell surface receptor binding/internalization. The A subunit has evolved to mimic a misfolded protein and hijack the ERAD membrane translocon (dislocon), to effect cytosolic access and cytopathology. We show such toxins compete for ERAD to rescue endogenous misfolded proteins. Cholera toxin or verotoxin (Shiga toxin) containing genetically inactivated (± an N-terminal polyleucine tail) A subunit can, within 2-4 hrs, temporarily increase F508delCFTR protein, the major cystic fibrosis (CF) mutant (5-10x), F508delCFTR Golgi maturation (<10x), cell surface expression (20x) and chloride transport (2x) in F508del CFTR transfected cells and patient-derived F508delCFTR bronchiolar epithelia, without apparent cytopathology. These toxoids also increase glucocerobrosidase (GCC) in N370SGCC Gaucher Disease fibroblasts (3x), another ERAD-exacerbated misfiling disease. We identify a new, potentially benign approach to the treatment of certain genetic protein misfolding diseases.
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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) | 0.001 | 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 | 0.001 | 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".