Both GEF domains of the autism and epilepsy-associated Trio protein are required for proper tangential migration of GABAergic interneurons
Bibliographic record
Abstract
Abstract Recessive mutations in the TRIO gene are associated with intellectual deficiency (ID), autism spectrum disorder (ASD) and developmental epileptic encephalopathies (DEE). TRIO is a dual guanine nucleotide exchange factor (GEF) that activates Rac1, Cdc42 and RhoA. Trio has been extensively studied in excitatory neurons, and has recently been found to regulate the switch from tangential to radial migration in GABAergic interneurons (INs), through GEFD1-Rac1-dependent SDF1α/CXCR4 signalling. Given the central role of Rho-GTPases during neuronal migration and the implication of IN pathologies in ASD and DEE, we investigated the relative roles of both Trio’s GEF domains in regulating the dynamics of INs tangential migration. In Trio -/- mice, we observed reduced numbers of tangentially migrating INs, with intact progenitor proliferation. Further, we noted increased growth cone collapse in developing INs, suggesting altered cytoskeleton dynamics. To bypass the embryonic mortality of Trio -/- mice, we generated Dlx5/6 Cre ;Trio c/c conditional mutant mice, which develop spontaneous seizures and behavioral deficits reminiscent of ASD and ID. These phenotypes are associated with reduced cortical IN density and functional cortical inhibition. Mechanistically, this reduction of cortical IN numbers reflects a premature switch to radial migration, with an aberrant early entry in the cortical plate, as well as major deficits in cytoskeletal dynamics, including enhanced leading neurite branching and slower nucleokinesis reflecting reduced actin filament condensation and turnover. Further, we show that both Trio GEFD1 and GEFD2 domains are required for proper IN migration, with a dominant role of the RhoA-activating GEFD2 domain. Altogether, our data show a critical role of the DEE/ASD-associated Trio gene in the establishment of cortical inhibition and the requirement of both GEF domains in regulating IN migration dynamics.
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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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".