Unveiling epigenetic-driven synaptic remodeling by parallel analysis of nuclei and synapses using NucleuSynapse-Tag
Year: 2025
Type: article
Abstract: BACKGROUND: Neuronal functions rely on coordinated molecular mechanisms across cell compartments, with communication between the nucleus and synapses. However, a multiplex and quantitative analysis of nuclear and synaptic content in parallel remains a significant technical challenge. NEW METHOD: Neurons were tagged with EGFP by stereotaxic injection of AAV-EGFP viral particles into the dorsal dentate gyrus (DG) of mice. This was followed by dorsal hippocampal dissection, homogenization, and differential centrifugation to obtain the nuclear (P1) and synaptosomal crude fractions (P2); both P1 and P2 were obtained from the same hippocampal homogenate. After filtration, fractions were immunolabeled and analyzed by flow cytometry. RESULTS: synaptosomes isolated from DG neurons tagged with EGFP. Through parallel analyses of synaptosomes and nuclei tagged with EGFP using AAV-EGFP-shRNA-SUV39H1 particles, NucleuSynapse-Tag provided the first direct evidence supporting the idea that epigenetic mechanisms modulate BDNF protein levels at the synapse. COMPARISON WITH EXISTING METHODS: Unlike current methods that focus either on nuclei or on synapses, the NucleuSynapse-Tag protocol offers a quantitative approach for studying synaptic and nuclear molecular markers in parallel from a single brain sample, by tracking genetically fluorescent-tagged specific populations of neurons. CONCLUSIONS: Combined with tools like AAV, Cre mice, and tracers, our approach enables a comprehensive analysis of molecular remodeling in two interdependent subcellular compartments that control neuronal function and plasticity.
Source: Journal of Neuroscience Methods
Authors: Yunuen Moreno-López, Citlali A. Suárez-Rangel, José A. Bonilla, G. Aleph Prieto
Institution: Universidad Nacional Autónoma de México
Language: English
Subfield: Cellular and Molecular Neuroscience
Field: Neuroscience
Domain: Life Sciences
Open Access status: hybrid
Estimated APC paid: $3,900
OpenAlex ID: W4413276339
