HIF1a/SLC7A11 signaling attenuates 6-hydroxydopamine-induced ferroptosis in animal and cell models of Parkinson's disease

Background: The pathogenesis of Parkinson's disease (PD) is associated with ferroptosis. The role of HIF1a is involved in several diseases, but its specific function in PD remains uncertain. Methods: In this study, we generated animal and cellular models of PD using the neurotoxin 6-OHDA. The occurrence of ferroptosis was determined by measuring levels of ferroptosis-related proteins, Fe2 & thorn; amount and transmission electron microscopy analysis in the PD models, and was further confirmed by using a ferroptosis inhibitor. HIF1a overexpressing and HIF1a knockdown SH-SY5Y cells were constructed by lentivirus transfection. Then, the levels of lipid peroxide, ROS, SLC7A11, and GPX4 were detected to elucidate the relationship between HIF1a and ferroptosis. Luciferase assay was used to analyze the regulation between HIF1a and SLC7A11. Results: We observed a significant downregulation of HIF1a in both animal and cellular PD models. Overexpression of HIF1a mitigated 6-OHDA-induced ferroptosis in SH-SY5Y cells, while, conversely, downregulation of HIF1a promoted ferroptosis in SH-SY5Y cells. BioEdit Sequence Alignment Editor software identified a hypoxia response element (HRE) within the promoter sequence of SLC7A11. The dual-luciferase reporter assays demonstrated that the co-expression of HIF1a and the SLC7A11 promoter significantly augmented reporter activity in SH-SY5Y cells. Moreover, introduction of a mutation into the HRE of the SLC7A11 promoter abolished the induction of SLC7A11 by HIF1a overexpression, resulted in a reduction in promoter activity compared with wild-type cells. Conclusions: The collective findings of this study indicate that HIF1a can inhibit ferroptosis by positively regulating SLC7A11. This investigation has shed light on the crucial involvement of the HIF1a/SLC7A11 signaling axis in ferroptosis in PD models, thereby presenting patients with PD a promising therapeutic target. (c) 2024 The Authors. Published by Elsevier Ltd on behalf of Tsinghua University Press. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).