Aminoglycoside-induced premature termination codon readthrough of <i>COL4A5</i> nonsense mutations that cause Alport syndrome
Bibliographic record
Abstract
ABSTRACT Alport syndrome (AS) is characterized by glomerular basement membrane (GBM) abnormalities leading to progressive glomerulosclerosis. Mutations in the COL4A3, COL4A4 or COL4A5 genes encoding type IV collagen α3α4α5 cause AS. Truncated α3, α4, and α5 chains lacking an intact COOH-terminal noncollagenous domain due to a premature termination codon (PTC) cannot assemble into heterotrimers or incorporate into the GBM. Therefore, achieving full-length protein expression is a potential therapy for AS caused by truncating nonsense mutations. Small molecule-based PTC readthrough (PTC-RT) therapy has been well studied in other genetic diseases, but whether PTC-RT is applicable to AS is unexplored. To investigate the feasibility of PTC-RT therapy in AS, we made a cDNA to express COL4A5 fused to a C-terminal NanoLuc luciferase (NLuc) to monitor full-length translation. Full-length COL4A5-NLuc produces luminescence, but mutants truncated due to a PTC do not. To screen for COL4A5 nonsense mutants susceptible to PTC-RT, we introduced 49 individual nonsense mutations found in AS patients into the COL4A5-NLuc cDNA. Luciferase assays revealed that 11 mutations ( C29X, S36X, E130X, C1521X, R1563X, C1567X, W1594X, S1632X, R1683X, C1684X and K1689X ) were susceptible to PTC-RT induced by G418, which is known to have high readthrough activity. Moreover, we found that some next-generation “designer” PTC-RT drugs induced RT, and RT enhancer compounds increased the efficacy of PTC-RT in a G418-susceptible PTC mutant. These results suggest that PTC-RT therapy is a feasible approach for some patients with AS. Our luciferase-based COL4A5 translation reporter system will contribute to further development of PTC-RT therapies in a personalized medicine approach to treating AS.
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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".