Allele-Specific Inactivation of an Autosomal Dominant Epidermolysis Bullosa Simplex Mutation Using CRISPR-Cas9
Bibliographic record
Abstract
Epidermolysis bullosa simplex (EBS) is a rare mechanobullous disease caused by dominant-negative mutations in either keratin 5 ( KRT5 ) or keratin 14 ( KRT14 ) genes. Until now, there is no cure for EBS and the care is primarily palliative. The discovery of the clustered regularly interspaced short palindromic repeat (CRISPR)-Cas9 system raised hope for the treatment of EBS and many other autosomal dominant diseases by mutant allele-specific gene disruption. In this study, we aim to disrupt the mutant allele for the heterozygous EBS pathogenic variation c.449T>C (p.Leu150Pro) within KRT5 . This mutation generates, naturally, a novel protospacer-adjacent motif for the endonuclease Streptococcus pyogenes Cas9 . Thus, we designed a single-guide RNA that guides the Cas9 to introduce a DNA cleavage of the mutant allele in patient's keratinocytes. Then, transfected cells were single-cell cloned and analyzed by deep sequencing. The expression of KRT5 and KRT14 was quantified, and the keratin intermediate filament stability was assessed. Results showed successful stringent mutant allele-specific knockout. An absence of synthesis of mutant transcript was further confirmed indicating permanent mutant allele-specific inactivation. Edited EBS patient keratinocytes produced a lower amount of K5 and K14 proteins compared with nonedited EBS cells, and no disturbance of cellular properties was observed.
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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".