Background Post-translational modifications, particularly SUMOylation, plays a crucial role in α-synuclein (α-syn) aggregation, a key pathological feature of Parkinson’s disease (PD). Curcumin, a natural polyphenol, has shown neuroprotective potential, but its effects on SUMOylation-related signaling in PD remain unclear. Objective This study aimed to investigate whether curcumin modulates α-syn SUMOylation and to elucidate the underlying molecular mechanisms in PD model mice. Methods A PD model was established in male C57BL/6 mice via unilateral intrastriatal injection of α-syn preformed fibrils (PFFs). Six months after α-syn PFFs injection, mice were treated intravenously with curcumin (25 mg/kg/day) or vehicle for 1 month. Behavioral tests (open field, rotarod) assessed motor function. Neuropathology was evaluated by immunohistochemistry and western blotting for tyrosine hydroxylase (TH), phosphorylated α-syn (p-syn), SUMOylation pathway components (SUMO1, SAE2, UBC9, PIAS1/2), and ubiquitin. Striatal dopamine levels were measured by HPLC. Results Curcumin treatment ameliorated motor deficits and anxiety-like behaviors in PD mice. It partially preserved dopaminergic neurons and reduced p-syn aggregation in the substantia nigra, accompanied by increased striatal dopamine levels. Mechanistically, curcumin was associated with reduced SUMO1 and increased ubiquitin levels, suggesting modulation of SUMOylation-related signaling. Among SUMOylation enzymes, UBC9 expression was decreased, whereas E1 (SAE2) and E3 (PIAS1/2) components were not substantially affected. Conclusion Our findings demonstrated that curcumin exerted neuroprotective effects in a PD model by attenuating α-syn pathology. The protective mechanism involves the inhibition of α-syn SUMOylation, primarily through the downregulation of the UBC9 enzyme. This study identifies UBC9-mediated SUMOylation as a potential target for curcumin and highlight a promising strategy for modifying α-syn-associated pathology in PD.
Yao Li, Zhuang Zhu, Kezhong Zhang· Frontiers in Neuroscience· 0 citations
Spatial transcriptomics (ST) profiles genome-wide gene expression while preserving the two-dimensional spatial context of mRNA molecules within tissue sections, enabling studies of tissue architecture and microenvironment-associated biology. However, ST analysis remains challenging because data import, quality control, integration, deconvolution, spatial statistics, and visualization often require multiple software environments and reproducible parameter choices. This protocol presents a practical computational workflow for public ST datasets in R, beginning with data acquisition and software setup and proceeding through Seurat-based data loading, quality control, normalization, multi-sample integration, clustering, and spatially variable gene analysis. The workflow then applies complementary deconvolution strategies, including reference-guided SPOTlight analysis and unsupervised STdeconvolve topic modeling, followed by Giotto-based spatial cell-cell communication analysis and interactive region-of-interest (ROI) selection using a custom Python Dash application. By emphasizing script-based execution, explicit parameter rationales, expected outputs, and troubleshooting checkpoints, the protocol provides an adaptable framework for standard array-based ST datasets and related platforms after dataset- and platform-specific parameter evaluation.
Hua-Lin Wang, Weijia Chen, Yan Wu et al.· Journal of Visualized Experi...· 0 citations