Background Paraquat (PQ) is one of the most widely used herbicides in the world and a risk factor for Parkinson's disease (PD), but the mechanisms underlying PD are poorly understood. Single-cell RNA sequencing (scRNA-seq) technology can study cellular heterogeneity at genetic level, providing insights into the pathogenesis of PQ-induced PD.

Objective To analyze the brain cell grouping of PQ-infected mice and the biological processes involved in the subpopulation of PD-like changes cells by scRNA-seq, and to provide clues for revealing potential mechanisms of PQ-induced PD-like changes in mouse brains.

Methods Six male 6-week-old C57BL/6 mice were randomly divided into a control group and an experimental group, three mice in each group, and were intraperitoneally injected with 0 (saline) and 10.0 mg·kg⁻¹ PD respectively, once every two days, for 10 consecutive injections for modeling. After infection, mouse brains were taken and scRNA-seq was performed. Cell segmentation was performed according to gene expression characteristics of different cell types, PD-related cell subsets were screened by bioinformatics tools, and gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), gene set enrichment analysis (GSEA), protein interaction network analysis, and transcription factor prediction were performed on their characteristic genes. Finally, GO and KEGG analyses were performed on the differential genes of PD-associated cell subsets between the PQ-treated group and the control group, and the biological processes in which these genes may participate were analyzed.

Results The sequencing data met quality control standards, a total of 55779 cells were obtained, and all cell dimensionality reduction analysis results showed that they could be further divided into 37 clusters, including 5 major cell types. Based on the KEGG analysis of the top 20 characteristic genes of each subpopulation, the specifically expressed Cluster 33 subpopulation (dopaminergic neurons) was screened and found to be significantly associated with PD. The results of GO analysis showed that the biological function of this subpopulation mainly enriched neurotransmitter transport and regulation. The results of GSEA analysis showed that the tyrosine metabolic pathway and the ligand-receptor interaction pathway of neural activity in brain tissues were significantly enriched. The analysis of transcriptional regulatory networks showed that 39 transcription factors were expressed differently. The metabolic pathway of the dopamine neuronal subset, endocytosis, Ras-associated protein 1 (Rap1) signaling pathway, and mitogen-activated protein kinase (MAPK) signaling pathway were all affected by PQ exposure, according to further analysis of its effects on this subpopulation. The GO analysis showed that differential genes were involved in biological processes such as ion transport and synaptic assembly regulation, and were involved in the cellular component formation of cytoplasm and synapses.

Conclusion This study has initially mapped the transcriptome of single cells in the mouse brain after PQ exposure, and screened out the specific expression of Cluster 33 subgroup (dopaminergic neurons), which is significantly correlated with PD, and its biological function changes may be one of the mechanisms of PD-like changes in the mouse brain induced by PQ.