Histidine supplementation can escalate or rescue HARS deficiency in a Charcot–Marie–Tooth disease model
Bibliographic record
Abstract
Aminoacyl-tRNA synthetases are essential enzymes responsible for charging amino acids onto cognate tRNAs during protein synthesis. In histidyl-tRNA synthetase (HARS), autosomal dominant mutations V133F, V155G, Y330C and S356N in the HARS catalytic domain cause Charcot-Marie-Tooth disease type 2 W (CMT2W), while tRNA-binding domain mutation Y454S causes recessive Usher syndrome type IIIB. In a yeast model, all human HARS variants complemented a genomic deletion of the yeast ortholog HTS1 at high expression levels. CMT2W associated mutations, but not Y454S, resulted in reduced growth. We show mistranslation of histidine to glutamine and threonine in V155G and S356N but not Y330C mutants in yeast. Mistranslating V155G and S356N mutants lead to accumulation of insoluble proteins, which was rescued by histidine. Mutants V133F and Y330C showed the most significant growth defect and decreased HARS abundance in cells. Here, histidine supplementation led to insoluble protein aggregation and further reduced viability, indicating histidine toxicity associated with these mutants. V133F proteins displayed reduced thermal stability in vitro, which was rescued by tRNA. Our data will inform future treatment options for HARS patients, where histidine supplementation may either have a toxic or compensating effect depending on the nature of the causative HARS variant.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".