CHINESE JOURNAL OF PARASITOLOGY AND PARASITIC DISEASES ›› 2024, Vol. 42 ›› Issue (3): 286-294.doi: 10.12140/j.issn.1000-7423.2024.03.002

• ORIGINAL ARTICLES • Previous Articles     Next Articles

Heterogeneity analysis of T cells in liver of mice infected with Echinococcus granulosus based on single-cell RNA sequencing

JIANG Nan1(), SU Yaxin1, JIANG Xiaofeng1, SHEN Yujuan1,2, CAO Jianping1,2,*()   

  1. 1 National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention; Chinese Center for Tropical Diseases Research; National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases; Key Laboratory on Parasite and Vector Biology, Ministry of Health; WHO Collaborating Centre for Tropical Diseases; National Center for International Research on Tropical Diseases, Ministry of Science and Technology, Shanghai 200025, China
    2 School of Global Health, Chinese Center for Tropical Diseases Research, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
  • Received:2024-05-18 Revised:2024-05-22 Online:2024-06-30 Published:2024-07-16
  • Supported by:
    National Natural Science Foundation of China(82072307);National Natural Science Foundation of China(82272369)

Abstract:

Objective To explore the composition and transcriptional profile characteristics of T cell subtypes in liver tissue microenvironment cells of mice infected with Echinococcus granulosus at different time points at the single-cell level. Methods Data were extracted from the single-cell RNA sequencing dataset (genome sequence archive: CRA008416) of BALB/c mouse liver tissue at 1 month (1 mouse), 3 months (1 mouse) and 6 months (2 mice) after E. granulosus infection and healthy mouse (1 mouse, control group) in the previous study of the research group and quality control was conducted. The uniform manifold approximation and projection (UMAP) method was used to visualize the single cell clusters, and the clustering algorithm adopted shared nearest neighbour (SNN) to obtain the optimal cell clusters. SingleR software package was used for cell type annotation of cell subsets based on the immgen reference dataset. FindMarkers function from Seurat software package was used to analyze differentially expressed genes (DEGs) of regulatory T cells (Tregs) and CD8+ T cells in mice infected at different time points and control group mice. Functional enrichment and pathway enrichment of DEGs were analyzed using gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG), respectively. Results After quality control, 37 760 cells were obtained, which were divided into 8 types after manual optimization. After re-clustering the T cells, 12 cell groups were obtained. Seven T cell subtypes were annotated and identified, including CD4+ naive T cells, CD4+ effector T cells, Tregs, CD8+ naive T cells, CD8+ T cells, proliferative T cells, γδ T cells. The proportion of each T cell subtype did not change significantly at 1 month after E. granulosus infection. The proportion of proliferative T cells (11.91%, 56/470) and Tregs (13.40%, 63/470) were significantly higher than those in control group (3.51%, 38/1 082; 4.34%, 47/1 082) at 3 months after infection. The proportion of CD8+ T cells (30.20%, 1 145/3 791) was significantly higher than that of the control group (15.43%, 167/1 082) at 6 months after infection. Tregs showed high expression of tumor necrosis factor-α-induced protein 8 (Tnfaip8), Maf, IKAROS family zinc finger 3 (Ikzf3) and other Treg-maintaining genes at 3 months after infection, while CD8+ T cells showed high expression of depletion genes such as CD40 ligand (Cd40lg), chitinase-like 3 (Chil3), secreted phosphoprotein 1 (Spp1) at 6 months after infection. GO analysis showed that DEGs of Tregs were mainly concentrated in transforming growth factor beta receptor complex assembly, positive regulation of T cell activation, cyclic adenosine monophosphate (cAMP) mediated signalling pathway at 3 months after infection; while the DEGs of CD8+ T cells were mainly concentrated in the regulation of vascular endothelial growth factor receptor, tryptophan catabolic process, extracellular matrix-cell signalling pathways at 6 months after infection. KEGG analysis showed that DEGs of Tregs were mainly involved in primary immune deficiency and Ras signalling pathway at 3 months after infection; while the DEGs of CD8+ T cells were mainly involved in fatty acid metabolism, glutathione metabolism, folate metabolism and other pathways at 6 months after infection. Conclusion There are differences in T cell subtypes in liver of mice at 3 months and 6 months after E. granulosus infection; the proportion of Tregs increased at 3 months, and CD8+ T cells increased at 6 months after infection. There were differences in DEGs and their main enrichment pathways of Tregs and CD8+ T cells.

Key words: Echinococcus granulosus, Single-cell RNA sequencing, T cells, Immune microenvironment

CLC Number: