Gamma-Protocadherins regulate filopodia self-recognition and dynamics to drive dendrite self-avoidance
Bibliographic record
Abstract
SUMMARY Neurons form cell type-specific morphologies that are shaped by molecular cues and their cellular events governing dendrite growth. One growth rule is distributing dendrites uniformly within a neuron’s territory by avoiding sibling or ‘self’ branches. In mammalian neurons, dendrite self-avoidance is regulated by the clustered Protocadherins (cPcdhs), a large family of recognition molecules. Genetic and molecular studies suggest that the cPcdhs mediate homophilic recognition and repulsion between self-dendrites but this model has not been tested through direct investigation of self-avoidance during development. Here we performed live imaging and 4D quantifications of dendrite morphogenesis to define the cPcdh-dependent mechanisms of self-avoidance. We focused on the mouse retinal starburst amacrine cell (SAC), which requires the gamma-Pcdhs ( Pcdhgs ) and self/non-self recognition to establish a stereotypic radial morphology while permitting dendritic interactions with neighboring SACs. Through morphogenesis, SACs extend a transient population of dynamic filopodia that fill the growing arbor and contact nearby self-dendrites. Compared to non-self-contacting filopodia, self-contacting events have longer lifetimes and a subset persists as filopodia bridges. In the absence of the Pcdhgs , non-self-contacting filopodia dynamics are unaffected but self-contact-induced retractions are significantly diminished. Filopodia bridges accumulate, leading to the bundling of dendritic processes and disruption to the arbor shape. By tracking dendrite self-avoidance in real-time, our findings demonstrate that the γ-Pcdhs selectively mediate contact-induced retractions upon filopodia self-recognition. Our results also illustrate how self-avoidance shapes the stochastic and space-filling behaviors of filopodia for robust dendritic pattern formation in mammalian neurons. HIGHLIGHTS Dendrite self-avoidance proceeds through interstitial filopodia and contact-induced retractions between sibling processes. Self-contacting filopodia exhibit longer lifetimes and a subset of contacts persist. Pcdhgs selectively regulate self-contact-induced retractions. Loss of Pcdhgs and filopodia self-avoidance disrupts dendritic arbor shape.
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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".