Abstract:
This study presents a comprehensive protocol for assembling and applying tetrahedral DNA nanostructures (TDNs) as carriers for neurotransmitter delivery, explicitly targeting the treatment of α-synucleinopathies such as Parkinson’s disease. TDNs, self-assembled from four single-stranded DNA oligonucleotides, offer a stable, programmable, and biocompatible platform with enhanced nuclease resistance and the ability to traverse the blood-brain barrier (BBB) via catherin-1-mediated transcytosis. The protocol details the synthesis, characterization, and functionalization of TDNs with neurotransmitters-serotonin, epinephrine, and norepinephrine-through electrostatic and hydrogen bonding interactions, exploiting the negative charge of the DNA backbone and the positive charge of protonated neurotransmitter amines. Structural validation is achieved via electrophoretic mobility shift assays, atomic force microscopy, dynamic light scattering, and fluorescence quenching studies. Functional assays in MPTP-induced PC12 cell models demonstrate that TDN-neurotransmitter complexes (TD:NTs) are efficiently internalized, reduce α-synuclein accumulation, and mitigate key pathological features, including oxidative stress, iron buildup, lipid peroxidation, and autophagy. In vivo zebrafish studies confirm high brain tissue accumulation and negligible neurotoxicity. Compared to conventional nanocarriers, TDNs exhibit superior biocompatibility, BBB permeability, and drug loading efficiency, while minimizing immunogenicity and off-target effects. Nonetheless, limitations such as restricted drug payload, rapid systemic clearance, and susceptibility to enzymatic degradation are acknowledged, alongside the need for further research into long-term safety and targeted delivery. This protocol establishes a robust workflow for TDN synthesis, neurotransmitter conjugation, and biological validation, underscoring the potential of TDNs as next-generation nanocarriers for targeted neurotransmitter delivery in neurodegenerative disease therapy.