单细胞测序和空间转录组技术在口腔医学的应用进展

doi:10.13591/j.cnki.kqyx.2024.03.010

摘要/Abstract

摘要：

单细胞测序和空间转录组技术在生命科学领域的应用是近年的研究热点,通过联合单细胞测序及空间转录组技术,能够在单细胞水平揭示细胞特定空间位置上的信息,以进一步探究疾病发生发展的机制及疾病的防治。在口腔医学领域,这一技术已被应用于口腔组织干细胞、口腔组织发生发育、口腔微生物及各类口腔疾病的研究中。该文阐述了单细胞测序和空间转录组技术在口腔领域的应用进展并展望两者联合应用的前景,以期为口腔疾病的诊疗提供新思路。

关键词: 单细胞测序, 空间转录组, 口腔医学, 生物信息分析

Abstract:

The application of single-cell sequencing and spatial transcriptome technology in life science field has been a hot research topic in recent years. By combining single-cell sequencing and spatial transcriptome technology, it can reveal information on specific spatial location of cells at single-cell level to further investigate the mechanism of disease development and disease prevention and treatment. In the field of dentistry, it has been applied to the study on oral tissue stem cells, oral histogenesis and development, oral microbiology and various oral diseases. This paper describes the progress of single-cell sequencing and spatial transcriptome technology in stomatology and looks into the prospect of their combined application, in order to provide new ideas for the diagnosis and treatment of oral diseases.

Key words: single-cell RNA sequencing, spatial transcriptomics, stomatology, bioinformatic analysis

中图分类号:

R349.8

张夏桐, 吴文治, 陈卓. 单细胞测序和空间转录组技术在口腔医学的应用进展[J]. 口腔医学, 2024, 44(3): 214-221.

ZHANG Xiatong, WU Wenzhi, CHEN Zhuo. Progress of single-cell RNA sequencing and spatial transcriptomics in stomatology[J]. Stomatology, 2024, 44(3): 214-221.

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参考文献 57

[1]	Tang FC, Barbacioru C, Wang YZ, et al. mRNA-Seq whole-transcriptome analysis of a single cell[J]. Nat Methods, 2009, 6(5):377-382. doi: 10.1038/nmeth.1315 pmid: 19349980
[2]	Song YL, Xu X, Wang W, et al. Single cell transcriptomics: Moving towards multi-omics[J]. Analyst, 2019, 144(10):3172-3189. doi: 10.1039/c8an01852a pmid: 30849139
[3]	Angermueller C, Clark SJ, Lee HJ, et al. Parallel single-cell sequencing links transcriptional and epigenetic heterogeneity[J]. Nat Methods, 2016, 13(3):229-232. doi: 10.1038/nmeth.3728 pmid: 26752769
[4]	Chen S, Lake BB, Zhang K. High-throughput sequencing of the transcriptome and chromatin accessibility in the same cell[J]. Nat Biotechnol, 2019, 37(12):1452-1457. doi: 10.1038/s41587-019-0290-0 pmid: 31611697
[5]	Liu LQ, Liu CY, Quintero A, et al. Deconvolution of single-cell multi-omics layers reveals regulatory heterogeneity[J]. Nat Commun, 2019, 10(1):470. doi: 10.1038/s41467-018-08205-7 pmid: 30692544
[6]	Peterson VM, Zhang KX, Kumar N, et al. Multiplexed quantification of proteins and transcripts in single cells[J]. Nat Biotechnol, 2017, 35(10):936-939. doi: 10.1038/nbt.3973 pmid: 28854175
[7]	Lian QY, Xin HY, Ma JZ, et al. Artificial-cell-type aware cell-type classification in CITE-seq[J]. Bioinformatics, 2020, 36(Suppl_1):i542-i550. doi: 10.1093/bioinformatics/btaa467
[8]	Ståhl PL, Salmén F, Vickovic S, et al. Visualization and analysis of gene expression in tissue sections by spatial transcriptomics[J]. Science, 2016, 353(6294):78-82. doi: 10.1126/science.aaf2403 pmid: 27365449
[9]	Moor AE, Itzkovitz S. Spatial transcriptomics: Paving the way for tissue-level systems biology[J]. Curr Opin Biotechnol, 2017, 46: 126-133. doi: 10.1016/j.copbio.2017.02.004
[10]	Marx V. Method of the year: Spatially resolved transcriptomics[J]. Nat Methods, 2021, 18(1):9-14. doi: 10.1038/s41592-020-01033-y pmid: 33408395
[11]	Chen J, Suo SB, Tam PP, et al. Spatial transcriptomic analysis of cryosectioned tissue samples with Geo-seq[J]. Nat Protoc, 2017, 12(3):566-580. doi: 10.1038/nprot.2017.003 pmid: 28207000
[12]	Chen KH, Boettiger AN, Moffitt JR, et al. RNA imaging. Spatially resolved, highly multiplexed RNA profiling in single cells[J]. Science, 2015, 348(6233):aaa6090.
[13]	Shah S, Takei Y, Zhou W, et al. Dynamics and spatial genomics of the nascent transcriptome by intron seqFISH[J]. Cell, 2018, 174(2):363-376. e16. doi: S0092-8674(18)30647-0 pmid: 29887381
[14]	Eng CHL, Lawson M, Zhu Q, et al. Transcriptome-scale super-resolved imaging in tissues by RNA seqFISH[J]. Nature, 2019, 568(7751):235-239. doi: 10.1038/s41586-019-1049-y
[15]	Elosua-Bayes M, Nieto P, Mereu E, et al. SPOTlight: Seeded NMF regression to deconvolute spatial transcriptomics spots with single-cell transcriptomes[J]. Nucleic Acids Res, 2021, 49(9):e50. doi: 10.1093/nar/gkab043 pmid: 33544846
[16]	Stuart T, Butler A, Hoffman P, et al. Comprehensive integration of single-cell data[J]. Cell, 2019, 177(7):1888-1902. e21. doi: S0092-8674(19)30559-8 pmid: 31178118
[17]	Ding DC, Shyu WC, Lin SZ. Mesenchymal stem cells[J]. Cell Transplant, 2011, 20(1):5-14. doi: 10.3727/096368910X
[18]	Sanz AR, Carrión FS, Chaparro AP. Mesenchymal stem cells from the oral cavity and their potential value in tissue engineering[J]. Periodontol 2000, 2015, 67(1):251-267. doi: 10.1111/prd.2015.67.issue-1
[19]	Pagella P, de Vargas Roditi L, Stadlinger B, et al. A single-cell atlas of human teeth[J]. iScience, 2021, 24(5):102405. doi: 10.1016/j.isci.2021.102405
[20]	Lee S, Chen DZ, Park M, et al. Single-cell RNA sequencing analysis of human dental pulp stem cell and human periodontal ligament stem cell[J]. J Endod, 2022, 48(2):240-248. doi: 10.1016/j.joen.2021.11.005
[21]	Lin WM, Li QW, Zhang DT, et al. Mapping the immune microenvironment for mandibular alveolar bone homeostasis at single-cell resolution[J]. Bone Res, 2021, 9(1):17. doi: 10.1038/s41413-021-00141-5 pmid: 33723232
[22]	Deo PN, Deshmukh R. Oral microbiome: Unveiling the fundamentals[J]. J Oral MaxillofacPathol, 2019, 23(1):122-128.
[23]	Cross KL, Campbell JH, Balachandran M, et al. Targeted isolation and cultivation of uncultivated bacteria by reverse genomics[J]. Nat Biotechnol, 2019, 37(11):1314-1321. doi: 10.1038/s41587-019-0260-6 pmid: 31570900
[24]	Campbell AG, Schwientek P, Vishnivetskaya T, et al. Diversity and genomic insights into the uncultured Chloroflexi from the human microbiota[J]. Environ Microbiol, 2014, 16(9):2635-2643. doi: 10.1111/1462-2920.12461 pmid: 24738594
[25]	Beall CJ, Campbell AG, Griffen AL, et al. Genomics of the uncultivated, periodontitis-associated bacterium Tannerella sp. BU045(oral taxon 808)[J]. mSystems, 2018, 3(3):e00018-e00018.
[26]	Cross KL, Chirania P, Xiong WL, et al. Insights into the evolution of host association through the isolation and characterization of a novel human periodontal pathobiont, Desulfobulbusoralis[J]. mBio, 2018, 9(2):e02061-e02017.
[27]	Kuchina A, Brettner LM, Paleologu L, et al. Microbial single-cell RNA sequencing by split-pool barcoding[J]. Science, 2021, 371(6531):eaba5257. doi: 10.1126/science.aba5257
[28]	Ma PJ, Amemiya HM, He LL, et al. Bacterial droplet-based single-cell RNA-seq reveals antibiotic-associated heterogeneous cellular states[J]. Cell, 2023, 186(4):877-891. e14. doi: 10.1016/j.cell.2023.01.002 pmid: 36708705
[29]	Dar D, Dar N, Cai L, et al. Spatial transcriptomics of planktonic and sessile bacterial populations at single-cell resolution[J]. Science, 2021, 373(6556):eabi4882. doi: 10.1126/science.abi4882
[30]	Yu TS, Klein OD. Molecular and cellular mechanisms of tooth development, homeostasis and repair[J]. Development, 2020, 147(2):dev184754.
[31]	Shi YQ, Yu YJ, Zhou YQ, et al. A single-cell interactome of human tooth germ from growing third molar elucidates signaling networks regulating dental development[J]. Cell Biosci, 2021, 11(1):178. doi: 10.1186/s13578-021-00691-5 pmid: 34600587
[32]	Matsubara T, Iga T, Sugiura Y, et al. Coupling of angiogenesis and odontogenesis orchestrates tooth mineralization in mice[J]. J Exp Med, 2022, 219(4):e20211789. doi: 10.1084/jem.20211789
[33]	Chiba Y, Yoshizaki K, Tian T, et al. Integration of single-cell RNA- and CAGE-seq reveals tooth-enriched genes[J]. J Dent Res, 2021, 101(5):542-550. doi: 10.1177/00220345211049785
[34]	Jing JJ, Feng JF, Yuan Y, et al. Spatiotemporal single-cell regulatory atlas reveals neural crest lineage diversification and cellular function during tooth morphogenesis[J]. Nat Commun, 2022, 13(1):4803. doi: 10.1038/s41467-022-32490-y pmid: 35974052
[35]	Takada K, Chiba T, Miyazaki T, et al. Single cell RNA sequenc-ing reveals critical functions of Mkx in periodontal ligament homeostasis[J]. Front Cell Dev Biol, 2022, 10: 795441. doi: 10.3389/fcell.2022.795441
[36]	Merritt CR, Ong GT, Church SE, et al. Multiplex digital spatial profiling of proteins and RNA in fixed tissue[J]. Nat Biotechnol, 2020, 38(5):586-599. doi: 10.1038/s41587-020-0472-9 pmid: 32393914
[37]	Lee HS, Joo JY, Sohn DH, et al. Single-cell RNA sequencing reveals rebalancing of immunological response in patients with periodontitis after non-surgical periodontal therapy[J]. J Transl Med, 2022, 20(1):504. doi: 10.1186/s12967-022-03702-2 pmid: 36329504
[38]	Qian SJ, Huang QR, Chen RY, et al. Single-cell RNA sequencing identifies new inflammation-promoting cell subsets in Asian patients with chronic periodontitis[J]. Front Immunol, 2021, 12: 711337. doi: 10.3389/fimmu.2021.711337
[39]	Chen Y, Wang H, Yang QD, et al. Single-cell RNA landscape of the osteoimmunology microenvironment in periodontitis[J]. Theranostics, 2022, 12(3):1074-1096. doi: 10.7150/thno.65694 pmid: 35154475
[40]	Caetano AJ, D’Agostino EM, Sharpe P, et al. Expression of periodontitis susceptibility genes in human gingiva using single-cell RNA sequencing[J]. J Periodontal Res, 2022, 57(6):1210-1218. doi: 10.1111/jre.v57.6
[41]	Agrafioti P, Morin-Baxter J, Tanagala KKK, et al. Decoding the role of macrophages in periodontitis and type 2 diabetes using single-cell RNA-sequencing[J]. FASEB J, 2022, 36(2):e22136.
[42]	Lundmark A, Gerasimcik N, Båge T, et al. Gene expression profiling of periodontitis-affected gingival tissue by spatial transcrip-tomics[J]. Sci Rep, 2018, 8(1):9370. doi: 10.1038/s41598-018-27627-3 pmid: 29921943
[43]	Lei Y, Yan W, Lin ZY, et al. Comprehensive analysis of partial epithelial mesenchymal transition-related genes in hepatocellular carcinoma[J]. J Cell Mol Med, 2021, 25(1):448-462. doi: 10.1111/jcmm.16099 pmid: 33215860
[44]	Huynh NCN, Huang TT, Nguyen CTK, et al. Comprehensive integrated single-cell whole transcriptome analysis revealed the p-EMT tumor cells-CAFs communication in oral squamous cell carcinoma[J]. Int J Mol Sci, 2022, 23(12):6470. doi: 10.3390/ijms23126470
[45]	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. e24. doi: S0092-8674(17)31270-9 pmid: 29198524
[46]	Chen JT, Yang JF, Li H, et al. Single-cell transcriptomics reveal the intratumoral landscape of infiltrated T-cell subpopulations in oral squamous cell carcinoma[J]. MolOncol, 2021, 15(4):866-886.
[47]	Hsieh YP, Wu YH, Cheng SM, et al. Single-cell RNA sequencing analysis for oncogenic mechanisms underlying oral squamous cell carcinoma carcinogenesis with Candida albicans infection[J]. Int J MolSci, 2022, 23(9):4833.
[48]	Schmitd Ligia B, Cindy P, Bellile Emily L, et al. Spatial and transcriptomic analysis of perineural invasion in oral cancer[J]. Clin Cancer Res, 2022: clincanres. 4543. 2021.
[49]	Zhao RW, Han WH, Tang KL, et al. Function of normal oral mucosa revealed by single-cell RNA sequencing[J]. J Cell Biochem, 2022, 123(9):1481-1494. doi: 10.1002/jcb.v123.9
[50]	Williams DW, Greenwell-Wild T, Brenchley L, et al. Human oral mucosa cell atlas reveals a stromal-neutrophil axis regulating tissue immunity[J]. Cell, 2021, 184(15):4090-4104. e15. doi: 10.1016/j.cell.2021.05.013 pmid: 34129837
[51]	Wang Q, Lin W, Zhou X, et al. Single-cell transcriptomic atlas of gingival mucosa in type 2 diabetes[J]. J Dent Res, 2022, 101(13):1654-1664. doi: 10.1177/00220345221092752
[52]	Li QH, Wang F, Shi YJ, et al. Single-cell immune profiling reveals immune responses in oral lichen planus[J]. Front Immunol, 2023, 14: 1182732. doi: 10.3389/fimmu.2023.1182732
[53]	Caetano AJ, Redhead Y, Karim F, et al. Spatially resolved transcriptomics reveals pro-inflammatory fibroblast involved in lymphocyte recruitment through CXCL8 and CXCL10[J]. eLife, 2023, 12: e81525.
[54]	Saviano A, Henderson NC, Baumert TF. Single-cell genomics and spatial transcriptomics: Discovery of novel cell states and cellular interactions in liver physiology and disease biology[J]. J Hepatol, 2020, 73(5):1219-1230.
[55]	Qi JJ, Sun HX, Zhang Y, et al. Single-cell and spatial analysis reveal interaction of FAP⁺ fibroblasts and SPP1⁺ macrophages in colorectal cancer[J]. Nat Commun, 2022, 13(1):1742. doi: 10.1038/s41467-022-29366-6
[56]	Fawkner-Corbett D, Antanaviciute A, Parikh K, et al. Spatiotemporal analysis of human intestinal development at single-cell resolution[J]. Cell, 2021, 184(3):810-826. e23. doi: 10.1016/j.cell.2020.12.016 pmid: 33406409
[57]	Goodyer WR, Beyersdorf BM, Paik DT, et al. Transcriptomic profiling of the developing cardiac conduction system at single-cell resolution[J]. Circ Res, 2019, 125(4):379-397. doi: 10.1161/CIRCRESAHA.118.314578 pmid: 31284824

原理与特点	单细胞测序	空间转录组
原理	通过微流控,微液滴,微孔技术等将单个细胞遗传物质均匀扩增、标记建库后进行测序,主要流程为单细胞分离与标记、基因组扩增、高通量测序和数据分析等	基于一种特殊化设计的样本捕获芯片,每个捕获点含有数百万探针,当组织切片透化贴在芯片上时,这些探针捕获被释放的mRNA,进行后续的文库构建与测序
特点	①精确度高,达到单细胞水平,但失去细胞原始空间位置 ②组学信息丰富,可获得单细胞内多组学信息	①同时保留细胞的空间位置信息与转录信息,但难以达到单细胞精度 ②具有可视化,将基因表达谱映射到相应的组织形态中