Neuropathy‐associated histidyl‐tRNA synthetase variants attenuate protein synthesis <i>in vitro</i> and disrupt axon outgrowth in developing zebrafish
Bibliographic record
Abstract
Charcot-Marie-Tooth disease (CMT) encompasses a set of genetically and clinically heterogeneous neuropathies characterized by length-dependent dysfunction of the peripheral nervous system. Mutations in over 80 diverse genes are associated with CMT, and aminoacyl-tRNA synthetases (ARS) constitute a large gene family implicated in the disease. Despite considerable efforts to elucidate the mechanistic link between ARS mutations and the CMT phenotype, the molecular basis of the pathology is unknown. In this work, we investigated the impact of three CMT-associated substitutions (V155G, Y330C, and R137Q) in the cytoplasmic histidyl-tRNA synthetase (HARS1) on neurite outgrowth and peripheral nervous system development. The model systems for this work included a nerve growth factor-stimulated neurite outgrowth model in rat pheochromocytoma cells (PC12), and a zebrafish line with GFP/red fluorescent protein reporters of sensory and motor neuron development. The expression of CMT-HARS1 mutations led to attenuation of protein synthesis and increased phosphorylation of eIF2α in PC12 cells and was accompanied by impaired neurite and axon outgrowth in both models. Notably, these effects were phenocopied by histidinol, a HARS1 inhibitor, and cycloheximide, a protein synthesis inhibitor. The mutant proteins also formed heterodimers with wild-type HARS1, raising the possibility that CMT-HARS1 mutations cause disease through a dominant-negative mechanism. Overall, these findings support the hypothesis that CMT-HARS1 alleles exert their toxic effect in a neuronal context, and lead to dysregulated protein synthesis. These studies demonstrate the value of zebrafish as a model for studying mutant alleles associated with CMT, and for characterizing the processes that lead to peripheral nervous system dysfunction.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| 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".