单细胞测序技术在肝脏疾病的应用与展望

doi:10.13560/j.cnki.biotech.bull.1985.2020-0463

摘要/Abstract

摘要：

新兴的单细胞测序技术能够从单细胞水平揭示基因组、转录组和表观遗传学等分子水平发生的基因变异与表观修饰状态,也可用于鉴定新的细胞类型和表面标记物。这将帮助人们探明疾病发生时细胞基因、转录或表观修饰方面的变化,了解细胞之间的联系,以及深入理解肿瘤异质性。目前,单细胞测序技术已用于多种疾病的研究,其在肝脏疾病,包括肝硬化、肝癌中已有相关成果。于此,综述了单细胞测序技术在肝脏发育及肝病中的应用,讨论了肝脏疾病发生的内在机制以及该技术仍存在的问题,提出可能的解决方案,如发展三维单细胞测序技术将更能帮助人们深刻理解肝脏疾病发生机制。

关键词: 单细胞测序技术, 组学测序, 肝脏, 肝病

Abstract:

Emerging single-cell sequencing is a potent technique,which can not only reveal mutations on genomics,transcriptomics and epigenetic modification at the molecular level but also be used to identify new cell types and surface markers. It can also help to detect changes in cell genes,transcriptomics or epigenetic modifications when a disease occurs,to understand the interactions among cells as well as to comprehensively understand tumor heterogeneity. Currently,single-cell sequencing has been applied to the studies on many diseases,and achievements on liver diseases including cirrhosis and liver cancer to some accomplishments are reported. Herein,the applications of single-cell sequencing in liver development and liver diseases are reviewed,underlying mechanisms of liver diseases and the issues of this technology are discussed,and the feasible resolutions are proposed,for instance,developing 3D single-cell sequencing technology may help us to deeply understand the mechanisms of liver deseases.

Key words: single-cell sequencing, omics sequencing, liver, liver diseases

过冬冬, 孙芬, 贺轩昂, 羊东晔, 黄来强. 单细胞测序技术在肝脏疾病的应用与展望[J]. 生物技术通报, 2021, 37(1): 137-144.

GUO Dong-dong, SUN Fen, HE Xuan-ang, YANG Dong-ye, HUANG Lai-qiang. Application and Prospects of Single-Cell Sequencing in Liver Disease[J]. Biotechnology Bulletin, 2021, 37(1): 137-144.

参考文献 49

[1]	Sanger F, Nicklen S, Coulson AR. DNA sequencing with chain-terminating inhibitors[J]. Proceedings of the National Academy of Sciences, 1977,74(12):5463-5467.
[2]	Collins FS, Morgan M, Patrinos A. The human genome project:lessons from large-scale biology[J]. Science, 2003,300(5617):286-290. URL pmid: 12690187
[3]	Tang F, Barbacioru C, Wang Y, et al. mRNA-Seq whole-transcriptome analysis of a single cell[J]. Nature Methods, 2009,6(5):377-382. doi: 10.1038/nmeth.1315 URL pmid: 19349980
[4]	Lee JW, Stone ML, Porrett PM, et al. Hepatocytes direct the formation of a pro-metastatic niche in the liver[J]. Nature, 2019,567(7747):249-252.
[5]	Duncan AW, Dorrell C, Grompe M. Stem cells and liver regeneration[J]. Gastroenterology, 2009,137(2):466-481. URL pmid: 19470389
[6]	Adam M, Potter AS, Potter SS. Psychrophilic proteases dramatically reduce single-cell RNA-seq artifacts:a molecular atlas of kidney development[J]. Development, 2017,144(19):3625-3632.
[7]	Lafzi A, Moutinho C, Picelli S, et al. Tutorial:guidelines for the experimental design of single-cell RNA sequencing studies[J]. Nature Protocols, 2018,13(12):2742-2757. URL pmid: 30446749
[8]	Rinke C, Lee J, Nath N, et al. Obtaining genomes from uncultivated environmental microorganisms using FACS-based single-cell genomics[J]. Nature Protocols, 2014,9(5):1038-1048. URL pmid: 24722403
[9]	Brouzes E, Medkova M, Savenelli N, et al. Droplet microfluidic technology for single-cell high-throughput screening[J]. Proceedings of the National Academy of Sciences, 2009,106(34):14195-14200.
[10]	Picelli S, Björklund ÅK, Faridani OR, et al. Smart-seq2 for sensitive full-length transcriptome profiling in single cells[J]. Nature Methods, 2013,10(11):1096-1098.
[11]	Gawad C, Koh W, Quake SR. Single-cell genome sequencing:current state of the science[J]. Nature Reviews Genetics, 2016,17(3):175-188. URL pmid: 26806412
[12]	Huang L, Ma F, Chapman A, et al. Single-cell whole-genome amplification and sequencing:methodology and applications[J]. Annual Review of Genomics and Human Genetics, 2015,16:79-102. doi: 10.1146/annurev-genom-090413-025352 URL pmid: 26077818
[13]	Navin NE. Cancer genomics:one cell at a time[J]. Genome Biology, 2014,15(8):452-465.
[14]	Lasken RS. Single-cell sequencing in its prime[J]. Nature Biotechnology, 2013,31(3):211-212. doi: 10.1038/nbt.2523 URL pmid: 23471069
[15]	Lasken RS. Single-cell genomic sequencing using multiple displacement amplification[J]. Current Opinion in Microbiology, 2007,10(5):510-516. doi: 10.1016/j.mib.2007.08.005 URL pmid: 17923430
[16]	Macaulay IC, Haerty W, Kumar P, et al. G&T-seq:parallel sequencing of single-cell genomes and transcriptomes[J]. Nature Methods, 2015,12(6):519-522. URL pmid: 25915121
[17]	Cui P, Lin Q, Ding F, et al. A comparison between ribo-minus RNA-sequencing and polyA-selected RNA-sequencing[J]. Genomics, 2010,96(5):259-265. doi: 10.1016/j.ygeno.2010.07.010 URL pmid: 20688152
[18]	Ziegenhain C, Vieth B, Parekh S, et al. Comparative analysis of single-cell RNA sequencing methods[J]. Molecular Cell, 2017,65(4):631-643.
[19]	Lorthongpanich C, Cheow LF, Balu S, et al. Single-cell DNA-methylation analysis reveals epigenetic chimerism in preimplantation embryos[J]. Science, 2013,341(6150):1110-1112.
[20]	Stuart T, Butler A, Hoffman P, et al. Comprehensive integration of single-cell data[J]. Cell, 2019,177(7):1888-1902.
[21]	Dey SS, Kester L, Spanjaard B, et al. Integrated genome and transcriptome sequencing of the same cell[J]. Nature Biotechnology, 2015,33(3):285-289. URL pmid: 25599178
[22]	Hou Y, Guo H, Cao C, et al. Single-cell triple omics sequencing reveals genetic, epigenetic, and transcriptomic heterogeneity in hepatocellular carcinomas[J]. Cell Research, 2016,26(3):304-319. URL pmid: 26902283
[23]	Bian S, Hou Y, Zhou X, et al. Single-cell multiomics sequencing and analyses of human colorectal cancer[J]. Science, 2018,362(6418):1060-1063.
[24]	Van Der Auwera GA, Carneiro MO, Hartl C, et al. From FastQ data to high-confidence variant calls：the Genome Analysis Toolkit best practices pipeline[J]. Current Protocols in Bioinformatics, 2013, 43(1110):11.10.1-11.10.33.
[25]	Ding B, Zheng L, Zhu Y, et al. Normalization and noise reduction for single cell RNA-seq experiments[J]. Bioinformatics, 2015,31(13):2225-2227. doi: 10.1093/bioinformatics/btv122 URL pmid: 25717193
[26]	Kobak D, Berens P. The art of using t-SNE for single-cell transcriptomics[J]. Nature Communications, 2019,10(1):5416. doi: 10.1038/s41467-019-13056-x URL pmid: 31780648
[27]	Aizarani N, Saviano A, Sagar, et al. A human liver cell atlas reveals heterogeneity and epithelial progenitors[J]. Nature, 2019,572(7768):199-204.
[28]	MacParland SA, Liu JC, Ma XZ, et al. Single cell RNA sequencing of human liver reveals distinct intrahepatic macrophage populations[J]. Nature Communications, 2018,9(1):4383. doi: 10.1038/s41467-018-06318-7 URL pmid: 30348985
[29]	Popescu DM, Botting RA, Stephenson E, et al. Decoding human fetal liver haematopoiesis[J]. Nature, 2019,574(7778):365-371. URL pmid: 31597962
[30]	Ramachandran P, Dobie R, Wilson-Kanamori J, et al. Resolving the fibrotic niche of human liver cirrhosis at single-cell level[J]. Nature, 2019,575(7783):512-518. doi: 10.1038/s41586-019-1631-3 URL pmid: 31597160
[31]	Krenkel O, Hundertmark J, Ritz TP, et al. Single cell RNA sequencing identifies subsets of hepatic stellate cells and myofibroblasts in liver fibrosis[J]. Cells, 2019,8(5):503-513.
[32]	Dobie R, Wilson-Kanamori JR, Henderson BEP, et al. Single-cell transcriptomics uncovers zonation of function in the mesenchyme during liver fibrosis[J]. Cell Reports, 2019,29(7):1832-1847. doi: 10.1016/j.celrep.2019.10.024 URL pmid: 31722201
[33]	Fu J, Wang H. Precision diagnosis and treatment of liver cancer in China[J]. Cancer Letters, 2018,412:283-288. doi: 10.1016/j.canlet.2017.10.008 URL pmid: 29050983
[34]	Zhang Q, He Y, Luo N, et al. Landscape and dynamics of single immune cells in hepatocellular carcinoma[J]. Cell, 2019,179(4):829-845. doi: 10.1016/j.cell.2019.10.003 URL pmid: 31675496
[35]	Xue R, Chen L, Zhang C, et al. Genomic and transcriptomic profiling of combined hepatocellular and intrahepatic cholangiocarcinoma reveals distinct molecular subtypes[J]. Cancer Cell, 2019,35(6):932-947. doi: 10.1016/j.ccell.2019.04.007 URL pmid: 31130341
[36]	Zheng H, Pomyen Y, Hernandez MO, et al. Single-cell analysis reveals cancer stem cell heterogeneity in hepatocellular carcinoma[J]. Hepatology, 2018,68(1):127-140. doi: 10.1002/hep.29778 URL pmid: 29315726
[37]	Guo X, Zhang Y, Zheng L, et al. Global characterization of T cells in non-small-cell lung cancer by single-cell sequencing[J]. Nature Medicine, 2018,24(7):978-985. doi: 10.1038/s41591-018-0045-3 URL pmid: 29942094
[38]	Zhang L, Yu X, Zheng L, et al. Lineage tracking reveals dynamic relationships of T cells in colorectal cancer[J]. Nature, 2018,564(7735):268-272. doi: 10.1038/s41586-018-0694-x URL pmid: 30479382
[39]	Azizi E, Carr AJ, Plitas G, et al. Single-cell map of diverse immune phenotypes in the breast tumor microenvironment[J]. Cell, 2018,174(5):1293-1308. doi: 10.1016/j.cell.2018.05.060 URL pmid: 29961579
[40]	Puram SV, Tirosh I, Parikh AS, et al. Single-cell transcriptomic analysis of primary and metastatic tumor ecosystems in head and neck cancer[J]. Cell, 2017,171(7):1611-1624.
[41]	Young MD, Mitchell TJ, Braga FAV, et al. Single-cell transcriptomes from human kidneys reveal the cellular identity of renal tumors[J]. Science, 2018,361(6402):594-599.
[42]	Hu Z, Artibani M, Alsaadi A, et al. The repertoire of serous ovarian cancer non-genetic heterogeneity revealed by single-cell sequencing of normal fallopian tube epithelial cells[J]. Cancer Cell, 2020,37(2):226-242.
[43]	Zhong S, Zhang S, Fan X, et al. A single-cell RNA-seq survey of the developmental landscape of the human prefrontal cortex[J]. Nature, 2018,555(7697):524-528.
[44]	Mathys H, Davila-Velderrain J, Peng Z, et al. Author correction:Single-cell transcriptomic analysis of Alzheimer’s disease[J]. Nature, 2019,571(7763):E1-E1.
[45]	Haber AL, Biton M, Rogel N, et al. A single-cell survey of the small intestinal epithelium[J]. Nature, 2017,551(7680):333-339.
[46]	Veres A, Faust AL, Bushnell HL, et al. Charting cellular identity during human in vitro β-cell differentiation[J]. Nature, 2019,569(7756):368-373.
[47]	Yu K, Hu YQ, Wu F, et al. Surveying brain tumor heterogeneity by single-cell RNA sequencing of multi-sector biopsies[J]. National Science Review, 2020,7(8):1306-1318.
[48]	Halpern KB, Shenhav R, Massalha H, et al. Paired-cell sequencing enables spatial gene expression mapping of liver endothelial cells[J]. Nature Biotechnology, 2018,36(10):962-970.
[49]	Halpern KB, Shenhav R, Matcovitch-Natan O, et al. Single-cell spatial reconstruction reveals global division of labour in the mammalian liver[J]. Nature, 2017,542(7641):352-356.