Glycine decarboxylase deficiency–induced motor dysfunction in zebrafish is rescued by counterbalancing glycine synaptic level
Bibliographic record
Abstract
Glycine encephalopathy (GE), or nonketotic hyperglycinemia (NKH), is a rare recessive genetic disease caused by defective glycine cleavage and characterized by increased accumulation of glycine in all tissues. Here, based on new case reports of GLDC loss-of-function mutations in GE patients, we aimed to generate a zebrafish model of severe GE in order to unravel the molecular mechanism of the disease. Using CRISPR/Cas9, we knocked out the gldc gene and showed that gldc-/- fish recapitulate GE on a molecular level and present a motor phenotype reminiscent of severe GE symptoms. The molecular characterization of gldc-/- mutants showed a broad metabolic disturbance affecting amino acids and neurotransmitters other than glycine, with lactic acidosis at stages preceding death. Although a transient imbalance was found in cell proliferation in the brain of gldc-/- zebrafish, the main brain networks were not affected, thus suggesting that GE pathogenicity is mainly due to metabolic defects. We confirmed that the gldc-/- hypotonic phenotype is due to NMDA and glycine receptor overactivation, and demonstrated that gldc-/- larvae depict exacerbated hyperglycinemia at these synapses. Remarkably, we were able to rescue the motor dysfunction of gldc-/- larvae by counterbalancing pharmacologically or genetically the level of glycine at the synapse.
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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".