基于单细胞转录组测序的细粒棘球蚴感染小鼠肝T细胞异质性分析

doi:10.12140/j.issn.1000-7423.2024.03.002

中国寄生虫学与寄生虫病杂志 ›› 2024, Vol. 42 ›› Issue (3): 286-294.doi: 10.12140/j.issn.1000-7423.2024.03.002

基于单细胞转录组测序的细粒棘球蚴感染小鼠肝T细胞异质性分析

江楠¹(), 苏雅馨¹, 蒋小凤¹, 沈玉娟¹^,², 曹建平¹^,²^,^*()

1 中国疾病预防控制中心寄生虫病预防控制所（国家热带病研究中心），传染病溯源预警与智能决策全国重点实验室，国家卫生健康委员会寄生虫病原与媒介生物学重点实验室，世界卫生组织热带病合作中心，科技部国家级热带病国际研究中心，上海 200025
2 上海交通大学医学院-国家热带病研究中心全球健康学院，上海 200025

收稿日期:2024-05-18 修回日期:2024-05-22 出版日期:2024-06-30 发布日期:2024-07-16
通讯作者: *曹建平（1964—），男，博士，研究员，从事寄生虫感染与免疫研究。E-mail：caojp@chinacdc.cn
作者简介:江楠（1986—），女，博士研究生，从事寄生虫感染与免疫研究。E-mail：Drjiangn0712@163.com
基金资助:
国家自然科学基金(82072307);国家自然科学基金(82272369)

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 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)

摘要/Abstract

摘要：

目的从单细胞水平探究细粒棘球蚴感染小鼠不同时期肝组织微环境细胞中T细胞亚型组成及其转录谱特征。方法从课题组前期细粒棘球蚴感染后1个月（1只）、3个月（1只）和6个月（2只）的BALB/c小鼠和健康小鼠（1只，对照组）肝组织的单细胞转录组测序数据集（中国国家生物信息中心组学原始数据归档库：CRA008416）（https://ngdc.cncb.ac.cn/gsa）中提取测序数据进行质控。采用统一流形逼近与投影（UMAP）算法对单细胞群聚类进行可视化作图，采用共享最近邻相似度（SNN）聚类算法分析最优细胞分群。采用SingleR软件包基于immgen参考数据集对细胞亚群进行细胞类型注释。使用Seurat软件包的FindMarkers函数分析不同时期感染小鼠和对照组小鼠的调节性T细胞（Treg）和CD8⁺T细胞的差异表达基因（DEG）。利用基因本体论（GO）和京都基因与基因组百科全书（KEGG）分别对DEG进行功能富集分析和通路富集分析。结果质控后获得37 760个细胞，人工优化后分为8种类型细胞。对T细胞重聚类后获得12个细胞群。注释后鉴定获得7种T细胞，包括CD4⁺初始T细胞、CD4⁺效应T细胞、Treg、CD8⁺初始T细胞、CD8⁺T细胞、增殖性T细胞、γδ T细胞。在细粒棘球蚴感染1个月后T细胞各亚群占比无明显变化，感染后3个月增殖性T细胞（11.91%，56/470）和Treg（13.40%，63/470）占比均高于对照组（3.51%，38/1 082；4.34%，47/1 082），感染后6个月CD8⁺ T细胞占比（30.20%，1 145/3 791）高于对照组（15.43%，167/1 082）。Treg在感染后3个月高表达肿瘤坏死因子-α诱导蛋白8（Tnfaip8）、Maf、伊卡洛斯家族锌指3（Ikzf3）等维持Treg的基因；CD8⁺T细胞在感染后6个月高表达白细胞表面分化抗原40配体（Cd40lg）、类几丁质酶3（Chil3）、分泌型磷蛋白1（Spp1）等耗竭性基因。GO分析结果显示，感染后3个月Treg的DEG主要富集于转化生长因子β受体复合物组装、正调节T细胞活化、环磷酸腺苷介导的信号传导等通路；感染后6个月CD8⁺T细胞的DEG主要富集调节血管内皮生长因子受体、色氨酸分解代谢过程、细胞外基质细胞信号等通路。KEGG分析结果显示，感染后3个月Treg的DEG主要参与原发性免疫缺陷和Ras信号传导途径等通路；感染后6个月CD8⁺T细胞DEG主要参与脂肪酸代谢、谷胱甘肽代谢、叶酸代谢等通路。结论细粒棘球蚴感染后3个月、6个月小鼠的肝组织T细胞亚型存在差异，感染后3个月Treg占比增加，感染后6个月CD8⁺ T细胞占比增加，Treg、CD8⁺ T细胞的DEG及其主要富集的通路存在差异。

关键词: 细粒棘球绦虫, 单细胞转录组测序, T细胞, 免疫微环境

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

中图分类号:

R383.33

江楠, 苏雅馨, 蒋小凤, 沈玉娟, 曹建平. 基于单细胞转录组测序的细粒棘球蚴感染小鼠肝T细胞异质性分析[J]. 中国寄生虫学与寄生虫病杂志, 2024, 42(3): 286-294.

JIANG Nan, SU Yaxin, JIANG Xiaofeng, SHEN Yujuan, CAO Jianping. Heterogeneity analysis of T cells in liver of mice infected with Echinococcus granulosus based on single-cell RNA sequencing[J]. Chinese Journal of Parasitology and Parasitic Diseases, 2024, 42(3): 286-294.

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参考文献 41

[1]	McManus DP, Gray DJ, Zhang WB, et al. Diagnosis, treatment, and management of echinococcosis[J]. BMJ, 2012, 344: e3866.
[2]	Kui Y, Xue CZ, Wang X, et al. Progress of echinococcosis control in China, 2022[J]. Chin J Parasitol Parasit Dis, 2024, 42(1): 8-16. (in Chinese)
	(蒉嫣, 薛垂召, 王旭, 等. 2022年全国棘球蚴病防治工作进展[J]. 中国寄生虫学与寄生虫病杂志, 2024, 42(1): 8-16.) doi: 10.12140/j.issn.1000-7423.2024.01.002
[3]	Gottstein B, Soboslay P, Ortona E, et al. Chapter one immunology of alveolar and cystic echinococcosis (AE and CE)[J]. Adv Parasitol, 2017, 96: 1-54.
[4]	Ammann RW, Eckert J. Cestodes. Echinococcus[J]. Gastroenterol Clin North Am, 1996, 25(3): 655-689.
[5]	Govindasamy A, Bhattarai PR, John J. Liver cystic echinococcosis: a parasitic review[J]. Ther Adv Infect Dis, 2023, 10: 20499361231171478.
[6]	Zhao JJ, Zhang SY, Liu Y, et al. Single-cell RNA sequencing reveals the heterogeneity of liver-resident immune cells in human[J]. Cell Discov, 2020, 6: 22. doi: 10.1038/s41421-020-0157-z pmid: 32351704
[7]	Massalha H, Bahar Halpern K, Abu-Gazala S, et al. A single cell atlas of the human liver tumor microenvironment[J]. Mol Syst Biol, 2020, 16(12): e9682.
[8]	Hedlund E, Deng QL. Single-cell RNA sequencing: technical advancements and biological applications[J]. Mol Aspects Med, 2018, 59: 36-46. doi: S0098-2997(17)30053-5 pmid: 28754496
[9]	Chu MJ, Song YF, Lu HH, et al. Advances in the application of single cell sequencing technology in the study of zoonotic parasitic diseases[J]. Chin Vet Sci, 2023, 53(2): 231-238. (in Chinese)
	(褚梦洁, 宋雅菲, 卢惠红, 等. 单细胞测序技术在人兽共患寄生虫病研究中的应用进展[J]. 中国兽医科学, 2023, 53(2): 231-238.)
[10]	Wendt G, Zhao L, Chen R, et al. A single-cell RNA-seq atlas of Schistosoma mansoni identifies a key regulator of blood feeding[J]. Science, 2020, 369(6511): 1644-1649.
[11]	Waldman BS, Schwarz D, Wadsworth MH 2nd, et al. Identification of a master regulator of differentiation in Toxoplasma[J]. Cell, 2020, 180(2): 359-372.e16.
[12]	Rawat M, Srivastava A, Johri S, et al. Single-cell RNA sequencing reveals cellular heterogeneity and stage transition under temperature stress in synchronized Plasmodium falciparum cells[J]. Microbiol Spectr, 2021, 9(1): e0000821.
[13]	Yang QQ, Jia WZ, Wang XQ, et al. Single-cell RNA sequencing deciphers transcriptional profiles of hepatocytes in mouse with hepatic alveolar echinococcosis[J]. Chin J Schisto Control, 2023, 35(3): 236-243. (in Chinese)
	(杨清清, 贾万忠, 王向前, 等. 基于单细胞转录组测序解析小鼠肝泡型棘球蚴病肝脏细胞转录谱特征[J]. 中国血吸虫病防治杂志, 2023, 35(3): 236-243.)
[14]	Jiang XF, Zhang XF, Jiang N, et al. The single-cell landscape of cystic echinococcosis in different stages provided insights into endothelial and immune cell heterogeneity[J]. Front Immunol, 2022, 13: 1067338.
[15]	Ayers J, Milner RJ, Cortés-Hinojosa G, et al. Novel application of single-cell next-generation sequencing for determination of intratumoral heterogeneity of canine osteosarcoma cell lines[J]. J Vet Diagn Invest, 2021, 33(2): 261-278. doi: 10.1177/1040638720985242 pmid: 33446089
[16]	Dobin A, Davis CA, Schlesinger F, et al. STAR: ultrafast universal RNA-seq aligner[J]. Bioinformatics, 2013, 29(1): 15-21. doi: 10.1093/bioinformatics/bts635 pmid: 23104886
[17]	McGinnis CS, Murrow LM, Gartner ZJ. DoubletFinder: doublet detection in single-cell RNA sequencing data using artificial nearest neighbors[J]. Cell Syst, 2019, 8(4): 329-337.e4. doi: S2405-4712(19)30073-0 pmid: 30954475
[18]	Aran D, Looney AP, Liu LQ, et al. Reference-based analysis of lung single-cell sequencing reveals a transitional profibrotic macrophage[J]. Nat Immunol, 2019, 20(2): 163-172. doi: 10.1038/s41590-018-0276-y pmid: 30643263
[19]	Heng TS, Painter MW, Immunological Genome Project Consortium. The Immunological Genome Project: networks of gene expression in immune cells[J]. Nat Immunol, 2008, 9(10): 1091-1094. doi: 10.1038/ni1008-1091 pmid: 18800157
[20]	Pan W, Zhou HJ, Shen YJ, et al. Surveillance on the status of immune cells after Echinnococcus granulosus protoscoleces infection in Balb/c mice[J]. PLoS One, 2013, 8(3): e59746.
[21]	Zhang XF, Gong WC, Cao SK, et al. Dynamic changes of myeloid-derived suppressor cells and regulatory T cells in livers of mice infected with Echinococcus granulosus[J]. Chin J Schisto Control, 2019, 31(6): 622-627. (in Chinese)
	(张小凡, 巩文词, 曹胜魁, 等. 细粒棘球绦虫感染小鼠肝脏髓源抑制性细胞与调节性T细胞比例动态变化[J]. 中国血吸虫病防治杂志, 2019, 31(6): 622-627.)
[22]	Zhang Q, Zhu YR, Lv CJ, et al. AhR activation promotes Treg cell generation by enhancing Lkb1-mediated fatty acid oxidation via the Skp2/K63-ubiquitination pathway[J]. Immunology, 2023, 169(4): 412-430. doi: 10.1111/imm.13638 pmid: 36930164
[23]	Klann JE, Remedios KA, Kim SH, et al. Talin plays a critical role in the maintenance of the regulatory T cell pool[J]. J Immunol, 2017, 198(12): 4639-4651. doi: 10.4049/jimmunol.1601165 pmid: 28515282
[24]	Han YH, Kim HJ, Na H, et al. RORα induces KLF4-mediated M2 polarization in the liver macrophages that protect against nonalcoholic steatohepatitis[J]. Cell Rep, 2017, 20(1): 124-135.
[25]	Haim-Vilmovsky L, Henriksson J, Walker JA, et al. Mapping Rora expression in resting and activated CD4⁺ T cells[J]. PLoS One, 2021, 16(5): e0251233.
[26]	Overacre-Delgoffe AE, Chikina M, Dadey RE, et al. Interferon-γ drives treg fragility to promote anti-tumor immunity[J]. Cell, 2017, 169(6): 1130-1141.e11. doi: S0092-8674(17)30532-9 pmid: 28552348
[27]	Andrabi SBA, Batkulwar K, Bhosale SD, et al. HIC1 interacts with FOXP3 multi protein complex: novel pleiotropic mechanisms to regulate human regulatory T cell differentiation and function[J]. Immunol Lett, 2023, 263: 123-132. doi: 10.1016/j.imlet.2023.09.001 pmid: 37838026
[28]	Bonazzi S, d’Hennezel E, Beckwith REJ, et al. Discovery and characterization of a selective IKZF2 glue degrader for cancer immunotherapy[J]. Cell Chem Biol, 2023, 30(3): 235-247.e12. doi: 10.1016/j.chembiol.2023.02.005 pmid: 36863346
[29]	Lou YW, Liu SX. The TIPE (TNFAIP8) family in inflammation, immunity, and cancer[J]. Mol Immunol, 2011, 49(1/2): 4-7.
[30]	Xu M, Pokrovskii M, Ding Y, et al. C-MAF-dependent regulatory T cells mediate immunological tolerance to a gut pathobiont[J]. Nature, 2018, 554(7692): 373-377.
[31]	Wu H, Zhao XF, Hochrein SM, et al. Mitochondrial dysfunction promotes the transition of precursor to terminally exhausted T cells through HIF-1α-mediated glycolytic reprogramming[J]. Nat Commun, 2023, 14(1): 6858.
[32]	Klement JD, Paschall AV, Redd PS, et al. An osteopontin/CD44 immune checkpoint controls CD8⁺ T cell activation and tumor immune evasion[J]. J Clin Invest, 2018, 128(12): 5549-5560. doi: 10.1172/JCI123360 pmid: 30395540
[33]	Soysouvanh F, Rousseau D, Bonnafous S, et al. Osteopontin-driven T-cell accumulation and function in adipose tissue and liver promoted insulin resistance and MAFLD[J]. Obesity, 2023, 31(10): 2568-2582. doi: 10.1002/oby.23868 pmid: 37724058
[34]	Wang KY, Hou HY, Zhang YN, et al. Ovarian cancer-associated immune exhaustion involves SPP1⁺ T cell and NKT cell, symbolizing more malignant progression[J]. Front Endocrinol, 2023, 14: 1168245.
[35]	Sharma P, Sharma A, Vishwakarma AL, et al. Host lung immunity is severely compromised during tropical pulmonary eosinophilia: role of lung eosinophils and macrophages[J]. J Leukoc Biol, 2016, 99(4): 619-628.
[36]	Jung IY, Narayan V, McDonald S, et al. BLIMP1 and NR4A3 transcription factors reciprocally regulate antitumor CAR T cell stemness and exhaustion[J]. Sci Transl Med, 2022, 14(670): eabn7336.
[37]	Symonds ALJ, Miao TZ, Busharat Z, et al. Egr2 and 3 maintain anti-tumour responses of exhausted tumour infiltrating CD8⁺ T cells[J]. Cancer Immunol Immunother, 2023, 72(5): 1139-1151.
[38]	Bai YM, Hu ML, Chen ZX, et al. Single-cell transcriptome analysis reveals RGS1 as a new marker and promoting factor for T-cell exhaustion in multiple cancers[J]. Front Immunol, 2021, 12: 767070.
[39]	Zhuang J, Qu ZB, Chu J, et al. Single-cell transcriptome analysis reveals T population heterogeneity and functions in tumor microenvironment of colorectal cancer metastases[J]. Heliyon, 2023, 9(7): e17119.
[40]	Srivastava R, Dervillez X, Khan AA, et al. The herpes simplex virus latency-associated transcript gene is associated with a broader repertoire of virus-specific exhausted CD8⁺ T cells retained within the trigeminal ganglia of latently infected HLA transgenic rabbits[J]. J Virol, 2016, 90(8): 3913-3928. doi: 10.1128/JVI.02450-15 pmid: 26842468
[41]	Srirat T, Hayakawa T, Mise-Omata S, et al. NR4a1/2 deletion promotes accumulation of TCF1⁺ stem-like precursors of exhausted CD8⁺ T cells in the tumor microenvironment[J]. Cell Rep, 2024, 43(3): 113898.

基于单细胞转录组测序的细粒棘球蚴感染小鼠肝T细胞异质性分析

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

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[13]	李玲慧, 王伟, 侯昕伶, 施阳, 李德伟, 李亮, 王慧, 李静, 张传山. 多房棘球蚴感染对小鼠脾自然杀伤T细胞及其亚群的影响[J]. 中国寄生虫学与寄生虫病杂志, 2021, 39(3): 311-317.
[14]	田梦潇, 臧小燕, 郭刚, 齐文静, 郭宝平, 任远, 李军, 张文宝. 丝氨酸蛋白酶在细粒棘球绦虫中的表达及活性鉴定[J]. 中国寄生虫学与寄生虫病杂志, 2021, 39(2): 233-239.
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