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Profiling presynaptic scaffolds using split-GFP reconstitution reveals cell-type-specific spatial configurations in

Hongyang Wu1, Yoh Maekawa2, Sayaka Eno1

  • 1Graduate School of Life Sciences, Tohoku University, Sendai, Japan.

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|March 18, 2026
PubMed
Summary

Researchers visualized presynaptic active zone (AZ) scaffold protein Bruchpilot (Brp) in neurons. This revealed cell-type-specific synapse patterns and structural plasticity in the mushroom body circuit.

Keywords:
CRISPR/Cas9D. melanogasterneurosciencesplit-GFPsynapse profiling

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Area of Science:

  • Neuroscience
  • Cell Biology
  • Connectomics

Background:

  • Understanding neuronal circuit computational logic requires characterizing intracellular synapse heterogeneity.
  • Spatial synapse patterns and their inter-individual variability are largely unknown despite connectomics advances.

Purpose of the Study:

  • To visualize endogenous Bruchpilot (Brp) in a cell-type-specific manner.
  • To quantitatively profile active zone (AZ) structures in identified neurons of the mushroom body circuit.
  • To investigate synaptic heterogeneity and plasticity.

Main Methods:

  • Directed split-GFP reconstitution for visualizing endogenous Bruchpilot (Brp).
  • Development of a high-throughput quantification pipeline for AZ structure profiling.
  • Analysis of AZ cluster patterns in identified mushroom body neurons across individuals.

Main Results:

  • Revealed cell-type-dependent synaptic heterogeneity and stereotypy in Brp cluster patterns.
  • Discovered previously unidentified sub-compartmental synapse configurations.
  • Identified transient structural plasticity of synapses triggered by associative learning.
  • Characterized multilayered spatial configurations of AZs, from overall distribution to local arrangements.

Conclusions:

  • Synaptic structure exhibits both cell-type-specific heterogeneity and stereotypy.
  • Associative learning induces transient structural plasticity in synaptic configurations.
  • Multilayered spatial organization of active zones provides insights into neuronal computation.