Serving the Society Since 1986
Advanced Search
Volume 39 Issue 1
February 2024
    Citation: Jia-Tong Chang, Li-Bo Liu, Pei-Gang Wang, Jing An. Single-cell RNA sequencing to understand host-virus interactions .VIROLOGICA SINICA, 2024, 39(1) : 1-8.  http://dx.doi.org/10.1016/j.virs.2023.11.009
    shu

    Single-cell RNA sequencing to understand host-virus interactions

    • Department of Microbiology, School of Basic Medical Sciences, Capital Medical University, Beijing 100069, China

    • Corresponding author: Pei-Gang Wang, pgwang@ccmu.edu.cn
      Jing An, anjing@ccmu.edu.cn
    • Received Date: 08 March 2023
      Accepted Date: 23 November 2023
      Available online: 25 November 2023
    • Single-cell RNA sequencing (scRNA-seq) has allowed for the profiling of host and virus transcripts and host-virus interactions at single-cell resolution. This review summarizes the existing scRNA-seq technologies together with their strengths and weaknesses. The applications of scRNA-seq in various virological studies are discussed in depth, which broaden the understanding of the immune atlas, host-virus interactions, and immune repertoire. scRNA-seq can be widely used for virology in the near future to better understand the pathogenic mechanisms and discover more effective therapeutic strategies.
    • 加载中

      1. Acosta, E.G., Bartenschlager, R., 2016. Paradoxical role of antibodies in dengue virus infections: considerations for prophylactic vaccine development. Expert Review of Vaccines 15, 467-482.

      2. Afik, S., Yates, K.B., Bi, K., Darko, S., Godec, J., Gerdemann, U., Swadling, L., Douek, D.C., Klenerman, P., Barnes, E.J., Sharpe, A.H., Haining, W.N., Yosef, N., 2017. Targeted reconstruction of T cell receptor sequence from single cell RNA-seq links CDR3 length to T cell differentiation state. Nucleic Acids Res 45, e148.

      3. Aibar, S., Gonzalez-Blas, C.B., Moerman, T., Huynh-Thu, V.A., Imrichova, H., Hulselmans, G., Rambow, F., Marine, J.C., Geurts, P., Aerts, J., van den Oord, J., Atak, Z.K., Wouters, J., Aerts, S., 2017. SCENIC: single-cell regulatory network inference and clustering. Nat Methods 14, 1083-1086.

      4. Aran, D., Looney, A.P., Liu, L., Wu, E., Fong, V., Hsu, A., Chak, S., Naikawadi, R.P., Wolters, P.J., Abate, A.R., Butte, A.J., Bhattacharya, M., 2019. Reference-based analysis of lung single-cell sequencing reveals a transitional profibrotic macrophage. Nat Immunol 20, 163-172.

      5. Balzer, M.S., Ma, Z., Zhou, J., Abedini, A., Susztak, K., 2021. How to Get Started with Single Cell RNA Sequencing Data Analysis. J Am Soc Nephrol 32, 1279-1292.

      6. Brandt, L., Cristinelli, S., Ciuffi, A., 2020. Single-Cell Analysis Reveals Heterogeneity of Virus Infection, Pathogenicity, and Host Responses: HIV as a Pioneering Example. Annu Rev Virol 7, 333-350.

      7. Bray, N.L., Pimentel, H., Melsted, P., Pachter, L., 2016. Near-optimal probabilistic RNA-seq quantification. Nat Biotechnol 34, 525-527.

      8. Brinton, M.A., Basu, M., 2015. Functions of the 3’ and 5’ genome RNA regions of members of the genus Flavivirus. Virus Res 206, 108-119.

      9. Cao, Y., Su, B., Guo, X., Sun, W., Deng, Y., Bao, L., Zhu, Q., Zhang, X., Zheng, Y., Geng, C., Chai, X., He, R., Li, X., Lv, Q., Zhu, H., Deng, W., Xu, Y., Wang, Y., Qiao, L., Tan, Y., Song, L., Wang, G., Du, X., Gao, N., Liu, J., Xiao, J., Su, X., Du, Z., Feng, Y., Qin, Chuan, Qin, Chengfeng, Jin, R., Xie, X.S., 2020. Potent Neutralizing Antibodies against SARS-CoV-2 Identified by High-Throughput Single-Cell Sequencing of Convalescent Patients’ B Cells. Cell 182, 73-84.e16.

      10. Caruccio, N., 2011. Preparation of next-generation sequencing libraries using NexteraTM technology: simultaneous DNA fragmentation and adaptor tagging by in vitro transposition. Methods Mol Biol 733, 241-255.

      11. Choi, J.R., Yong, K.W., Choi, J.Y., Cowie, A.C., 2020. Single-Cell RNA Sequencing and Its Combination with Protein and DNA Analyses. Cells 9, 1130.

      12. Dai, X., Cai, L., He, F., 2022. Single-cell sequencing: expansion, integration and translation. Briefings in Functional Genomics elac011.

      13. Das, R., Bar, N., Ferreira, M., Newman, A.M., Zhang, L., Bailur, J.K., Bacchiocchi, A., Kluger, H., Wei, W., Halaban, R., Sznol, M., Dhodapkar, M.V., Dhodapkar, K.M., 2018. Early B cell changes predict autoimmunity following combination immune checkpoint blockade. J Clin Invest 128, 715-720.

      14. de Kanter, J.K., Lijnzaad, P., Candelli, T., Margaritis, T., Holstege, F.C.P., 2019. CHETAH: a selective, hierarchical cell type identification method for single-cell RNA sequencing. Nucleic Acids Res 47, e95.

      15. Delorey, T.M., Ziegler, C.G.K., Heimberg, G., Normand, R., Yang, Y., Segerstolpe, A, Abbondanza, D., Fleming, S.J., Subramanian, A., Montoro, D.T., Jagadeesh, K.A., Dey, K.K., Sen, P., Slyper, M., Pita-Juarez, Y.H., Phillips, D., Biermann, J., Bloom-Ackermann, Z., Barkas, N., Ganna, A., Gomez, J., Melms, J.C., Katsyv, I., Normandin, E., Naderi, P., Popov, Y.V., Raju, S.S., Niezen, S., Tsai, L.T.-Y., Siddle, K.J., Sud, M., Tran, V.M., Vellarikkal, S.K., Wang, Y., Amir-Zilberstein, L., Atri, D.S., Beechem, J., Brook, O.R., Chen, J., Divakar, P., Dorceus, P., Engreitz, J.M., Essene, A., Fitzgerald, D.M., Fropf, R., Gazal, S., Gould, J., Grzyb, J., Harvey, T., Hecht, J., Hether, T., Jane-Valbuena, J., Leney-Greene, M., Ma, H., McCabe, C., McLoughlin, D.E., Miller, E.M., Muus, C., Niemi, M., Padera, R., Pan, L., Pant, D., Pe’er, C., Pfiffner-Borges, J., Pinto, C.J., Plaisted, J., Reeves, J., Ross, M., Rudy, M., Rueckert, E.H., Siciliano, M., Sturm, A., Todres, E., Waghray, A., Warren, S., Zhang, S., Zollinger, D.R., Cosimi, L., Gupta, R.M., Hacohen, N., Hibshoosh, H., Hide, W., Price, A.L., Rajagopal, J., Tata, P.R., Riedel, S., Szabo, G., Tickle, T.L., Ellinor, P.T., Hung, D., Sabeti, P.C., Novak, R., Rogers, R., Ingber, D.E., Jiang, Z.G., Juric, D., Babadi, M., Farhi, S.L., Izar, B., Stone, J.R., Vlachos, I.S., Solomon, I.H., Ashenberg, O., Porter, C.B.M., Li, B., Shalek, A.K., Villani, A.-C., Rozenblatt-Rosen, O., Regev, A., 2021. COVID-19 tissue atlases reveal SARS-CoV-2 pathology and cellular targets. Nature 595, 107-113.

      16. DePasquale, E.A.K., Schnell, D.J., Van Camp, P.-J., Valiente-Alandi, I., Blaxall, B.C., Grimes, H.L., Singh, H., Salomonis, N., 2019. DoubletDecon: Deconvoluting Doublets from Single-Cell RNA-Sequencing Data. Cell Rep 29, 1718-1727.e8.

      17. Dijk, E.L. van, Jaszczyszyn, Y., Naquin, D., Thermes, C., 2018. The Third Revolution in Sequencing Technology. Trends in Genetics 34, 666-681.

      18. Dobin, A., Davis, C.A., Schlesinger, F., Drenkow, J., Zaleski, C., Jha, S., Batut, P., Chaisson, M., Gingeras, T.R., 2013. STAR: ultrafast universal RNA-seq aligner. Bioinformatics 29, 15-21.

      19. Golumbeanu, M., Cristinelli, S., Rato, S., Munoz, M., Cavassini, M., Beerenwinkel, N., Ciuffi, A., 2018. Single-Cell RNA-Seq Reveals Transcriptional Heterogeneity in Latent and Reactivated HIV-Infected Cells. Cell Reports 23, 942-950.

      20. Grun, D., van Oudenaarden, A., 2015. Design and Analysis of Single-Cell Sequencing Experiments. Cell 163, 799-810.

      21. Hashimshony, T., Wagner, F., Sher, N., Yanai, I., 2012. CEL-Seq: Single-Cell RNA-Seq by Multiplexed Linear Amplification. Cell Reports 2, 666-673.

      22. Hie, B., Bryson, B., Berger, B., 2019. Efficient integration of heterogeneous single-cell transcriptomes using Scanorama. Nat Biotechnol 37, 685-691.

      23. Hoffmann, M., Kleine-Weber, H., Schroeder, S., Kruger, N., Herrler, T., Erichsen, S., Schiergens, T.S., Herrler, G., Wu, N.-H., Nitsche, A., Muller, M.A., Drosten, C., Pohlmann, S., 2020. SARS-CoV-2 Cell Entry Depends on ACE2 and TMPRSS2 and Is Blocked by a Clinically Proven Protease Inhibitor. Cell 181, 271-280.e8.

      24. Huang, H., Sikora, M.J., Islam, S., Chowdhury, R.R., Chien, Y., Scriba, T.J., Davis, M.M., Steinmetz, L.M., 2019. Select sequencing of clonally expanded CD8+ T cells reveals limits to clonal expansion. Proc Natl Acad Sci U S A 116, 8995-9001.

      25. Hwang, B., Lee, J.H., Bang, D., 2018. Single-cell RNA sequencing technologies and bioinformatics pipelines. Exp Mol Med 50, 96.

      26. Kanehisa, M., Furumichi, M., Tanabe, M., Sato, Y., Morishima, K., 2017. KEGG: new perspectives on genomes, pathways, diseases and drugs. Nucleic Acids Res 45, D353-D361.

      27. Kramer, K.J., Wilfong, E.M., Voss, K., Barone, S.M., Shiakolas, A.R., Raju, N., Roe, C.E., Suryadevara, N., Walker, L., Wall, S.C., Paulo, A., Schaefer, S., Dahunsi, D., Westlake, C.S., Crowe, J.E., Carnahan, R.H., Rathmell, J.C., Bonami, R.H., Georgiev, I.S., Irish, J.M., 2021. Single-Cell Profiling of the Antigen-Specific Response to BNT162b2 SARS-CoV-2 RNA Vaccine. bioRxiv 2021.07.28.453981.

      28. Levitin, H.M., Yuan, J., Sims, P.A., 2018. Single-Cell Transcriptomic Analysis of Tumor Heterogeneity. Trends Cancer 4, 264-268.

      29. Levy, S.E., Boone, B.E., 2019. Next-Generation Sequencing Strategies. Cold Spring Harb Perspect Med 9, a025791.

      30. Liberzon, A., Subramanian, A., Pinchback, R., Thorvaldsdottir, H., Tamayo, P., Mesirov, J.P., 2011. Molecular signatures database (MSigDB) 3.0. Bioinformatics 27, 1739-1740.

      31. Liu, X., Wu, J., 2018. History, applications, and challenges of immune repertoire research. Cell Biol Toxicol 34, 441-457.

      32. Liu, W., Jia, J., Dai, Y., Chen, W., Pei, G., Yan, Q., Zhao, Z., 2022. Delineating COVID-19 immunological features using single-cell RNA sequencing. Innovation (Camb) 3, 100289.

      33. Lun, A.T.L., Bach, K., Marioni, J.C., 2016. Pooling across cells to normalize single-cell RNA sequencing data with many zero counts. Genome Biol 17, 75.

      34. Luo, G., Gao, Q., Zhang, S., Yan, B., 2020. Probing infectious disease by single-cell RNA sequencing: Progresses and perspectives. Comput Struct Biotechnol J 18, 2962-2971.

      35. Michielsen, L., Reinders, M.J.T., Mahfouz, A., 2021. Hierarchical progressive learning of cell identities in single-cell data. Nat Commun 12, 2799.

      36. Ofengeim, D., Giagtzoglou, N., Huh, D., Zou, C., Yuan, J., 2017. Single-Cell RNA Sequencing: Unraveling the Brain One Cell at a Time. Trends Mol Med 23, 563-576.

      37. O’Neal, J.T., Upadhyay, A.A., Wolabaugh, A., Patel, N.B., Bosinger, S.E., Suthar, M.S., 2019. West Nile Virus-Inclusive Single-Cell RNA Sequencing Reveals Heterogeneity in the Type I Interferon Response within Single Cells. J Virol 93, e01778-18.

      38. Paik, D.T., Cho, S., Tian, L., Chang, H.Y., Wu, J.C., 2020. Single-cell RNA sequencing in cardiovascular development, disease and medicine. Nat Rev Cardiol 17, 457-473.

      39. Picelli, S., 2017. Single-cell RNA-sequencing: The future of genome biology is now. RNA Biology 14, 637.

      40. Picelli, S., Faridani, O.R., Bjorklund, A.K., Winberg, G., Sagasser, S., Sandberg, R., 2014. Full-length RNA-seq from single cells using Smart-seq2. Nat Protoc 9, 171-181.

      41. Qi, F., Qian, S., Zhang, S., Zhang, Z., 2020. Single cell RNA sequencing of 13 human tissues identify cell types and receptors of human coronaviruses. Biochem Biophys Res Commun 526, 135-140.

      42. Qu, L., Li, S., Qiu, H.J., 2020. Applications of single-cell RNA sequencing in virology. Yi Chuan 42, 269-277.

      43. Ramskold, D., Luo, S., Wang, Y.-C., Li, R., Deng, Q., Faridani, O.R., Daniels, G.A., Khrebtukova, I., Loring, J.F., Laurent, L.C., Schroth, G.P., Sandberg, R., 2012. Full-length mRNA-Seq from single-cell levels of RNA and individual circulating tumor cells. Nat Biotechnol 30, 777-782.

      44. Raredon, M.S.B., Yang, J., Garritano, J., Wang, M., Kushnir, D., Schupp, J.C., Adams, T.S., Greaney, A.M., Leiby, K.L., Kaminski, N., Kluger, Y., Levchenko, A., Niklason, L.E., 2022. Computation and visualization of cell-cell signaling topologies in single-cell systems data using Connectome. Sci Rep 12, 4187.

      45. Ren, X., Wen, W., Fan, X., Hou, W., Su, Bin, Cai, P., Li, J., Liu, Y., Tang, F., Zhang, F., Yang, Y., He, Jiangping, Ma, W., He, Jingjing, Wang, P., Cao, Q., Chen, F., Chen, Y., Cheng, X., Deng, G., Deng, X., Ding, W., Feng, Y., Gan, R., Guo, C., Guo, W., He, S., Jiang, C., Liang, J., Li, Y., Lin, J., Ling, Y., Liu, H., Liu, J., Liu, N., Liu, S.-Q., Luo, M., Ma, Q., Song, Q., Sun, W., Wang, G., Wang, F., Wang, Y., Wen, X., Wu, Q., Xu, G., Xie, X., Xiong, X., Xing, X., Xu, H., Yin, C., Yu, D., Yu, K., Yuan, J., Zhang, B., Zhang, P., Zhang, T., Zhao, J., Zhao, Peidong, Zhou, J., Zhou, W., Zhong, S., Zhong, X., Zhang, S., Zhu, L., Zhu, P., Zou, B., Zou, J., Zuo, Z., Bai, F., Huang, X., Zhou, P., Jiang, Q., Huang, Z., Bei, J.-X., Wei, L., Bian, X.-W., Liu, X., Cheng, T., Li, X., Zhao, Pingsen, Wang, F.-S., Wang, H., Su, Bing, Zhang, Zheng, Qu, K., Wang, X., Chen, J., Jin, R., Zhang, Zemin, 2021. COVID-19 immune features revealed by a large-scale single-cell transcriptome atlas. Cell 184, 1895-1913.e19.

      46. Russell, A.B., Elshina, E., Kowalsky, J.R., te Velthuis, A.J.W., Bloom, J.D., 2019. Single-Cell Virus Sequencing of Influenza Infections That Trigger Innate Immunity. J Virol 93, e00500-e00519.

      47. Salmen, F., De Jonghe, J., Kaminski, T.S., Alemany, A., Parada, G.E., Verity-Legg, J., Yanagida, A., Kohler, T.N., Battich, N., van den Brekel, F., Ellermann, A.L., Arias, A.M., Nichols, J., Hemberg, M., Hollfelder, F., van Oudenaarden, A., 2022. High-throughput total RNA sequencing in single cells using VASA-seq. Nat Biotechnol 40, 1780-1793.

      48. Singh, M., Al-Eryani, G., Carswell, S., Ferguson, J.M., Blackburn, J., Barton, K., Roden, D., Luciani, F., Giang Phan, T., Junankar, S., Jackson, K., Goodnow, C.C., Smith, M.A., Swarbrick, A., 2019. High-throughput targeted long-read single cell sequencing reveals the clonal and transcriptional landscape of lymphocytes. Nat Commun 10, 3120.

      49. Smith, T., Heger, A., Sudbery, I., 2017. UMI-tools: modeling sequencing errors in Unique Molecular Identifiers to improve quantification accuracy. Genome Res 27, 491-499.

      50. Stephenson, E., Reynolds, G., Botting, R.A., Calero-Nieto, F.J., Morgan, M.D., Tuong, Z.K., Bach, K., Sungnak, W., Worlock, K.B., Yoshida, M., Kumasaka, N., Kania, K., Engelbert, J., Olabi, B., Spegarova, J.S., Wilson, N.K., Mende, N., Jardine, L., Gardner, L.C.S., Goh, I., Horsfall, D., McGrath, J., Webb, S., Mather, M.W., Lindeboom, R.G.H., Dann, E., Huang, N., Polanski, K., Prigmore, E., Gothe, F., Scott, J., Payne, R.P., Baker, K.F., Hanrath, A.T., Schim van der Loeff, I.C.D., Barr, A.S., Sanchez-Gonzalez, A., Bergamaschi, L., Mescia, F., Barnes, J.L., Kilich, E., de Wilton, A., Saigal, A., Saleh, A., Janes, S.M., Smith, C.M., Gopee, N., Wilson, C., Coupland, P., Coxhead, J.M., Kiselev, V.Y., van Dongen, S., Bacardit, J., King, H.W., Rostron, A.J., Simpson, A.J., Hambleton, S., Laurenti, E., Lyons, P.A., Meyer, K.B., Nikolic, M.Z., Duncan, C.J.A., Smith, K.G.C., Teichmann, S.A., Clatworthy, M.R., Marioni, J.C., Gottgens, B., Haniffa, M., 2021. Single-cell multi-omics analysis of the immune response in COVID-19. Nat Med 27, 904-916.

      51. Steuerman, Y., Cohen, M., Peshes-Yaloz, N., Valadarsky, L., Cohn, O., David, E., Frishberg, A., Mayo, L., Bacharach, E., Amit, I., Gat-Viks, I., 2018. Dissection of Influenza Infection In Vivo by Single-Cell RNA Sequencing. Cell Syst 6, 679-691.e4.

      52. Stuart, T., Satija, R., 2019. Integrative single-cell analysis. Nat Rev Genet 20, 257-272.

      53. Sureshchandra, S., Lewis, S.A., Doratt, B.M., Jankeel, A., Coimbra Ibraim, I., Messaoudi, I., 2021. Single-cell profiling of T and B cell repertoires following SARS-CoV-2 mRNA vaccine. JCI Insight 6, e153201.

      54. Tang, F., Barbacioru, C., Wang, Y., Nordman, E., Lee, C., Xu, N., Wang, X., Bodeau, J., Tuch, B.B., Siddiqui, A., Lao, K., Surani, M.A., 2009. mRNA-Seq whole-transcriptome analysis of a single cell. Nat Methods 6, 377-382.

      55. The Gene Ontology Consortium, 2017. Expansion of the Gene Ontology knowledgebase and resources. Nucleic Acids Res 45, D331-D338.

      56. Trapnell, C., Cacchiarelli, D., Grimsby, J., Pokharel, P., Li, S., Morse, M., Lennon, N.J., Livak, K.J., Mikkelsen, T.S., Rinn, J.L., 2014. Pseudo-temporal ordering of individual cells reveals dynamics and regulators of cell fate decisions. Nat Biotechnol 32, 381-386.

      57. Uyar, O., Dominguez, J.M., Bordeleau, M., Lapeyre, L., Ibanez, F.G., Vallieres, L., Tremblay, M.-E., Corbeil, J., Boivin, G., 2022. Single-cell transcriptomics of the ventral posterolateral nucleus-enriched thalamic regions from HSV-1-infected mice reveal a novel microglia/microglia-like transcriptional response. J Neuroinflammation 19, 81.

      58. Van den Berge, K., Roux de Bezieux, H., Street, K., Saelens, W., Cannoodt, R., Saeys, Y., Dudoit, S., Clement, L., 2020. Trajectory-based differential expression analysis for single-cell sequencing data. Nat Commun 11, 1201.

      59. Vento-Tormo, R., Efremova, M., Botting, R.A., Turco, M.Y., Vento-Tormo, M., Meyer, K.B., Park, J.-E., Stephenson, E., Polanski, K., Goncalves, A., Gardner, L., Holmqvist, S., Henriksson, J., Zou, A., Sharkey, A.M., Millar, B., Innes, B., Wood, L., Wilbrey-Clark, A., Payne, R.P., Ivarsson, M.A., Lisgo, S., Filby, A., Rowitch, D.H., Bulmer, J.N., Wright, G.J., Stubbington, M.J.T., Haniffa, M., Moffett, A., Teichmann, S.A., 2018. Single-cell reconstruction of the early maternal-fetal interface in humans. Nature 563, 347-353.

      60. Waickman, A.T., Friberg, H., Gromowski, G.D., Rutvisuttinunt, W., Li, T., Siegfried, H., Victor, K., McCracken, M.K., Fernandez, S., Srikiatkhachorn, A., Ellison, D., Jarman, R.G., Thomas, S.J., Rothman, A.L., Endy, T., Currier, J.R., 2021. Temporally integrated single cell RNA sequencing analysis of PBMC from experimental and natural primary human DENV-1 infections. PLoS Pathog 17, e1009240. h.

      61. Wang, C., de Mochel, N.S.R., Christenson, S.A., Cassandras, M., Moon, R., Brumwell, A.N., Byrnes, L.E., Li, A., Yokosaki, Y., Shan, P., Sneddon, J.B., Jablons, D., Lee, P.J., Matthay, M.A., Chapman, H.A., Peng, T., 2018. Expansion of hedgehog disrupts mesenchymal identity and induces emphysema phenotype. J Clin Invest 128, 4343-4358.

      62. Wang, X., He, Y., Zhang, Q., Ren, X., Zhang, Z., 2021. Direct Comparative Analyses of 10X Genomics Chromium and Smart-seq2. Genomics Proteomics Bioinformatics 19, 253-266.

      63. WHO, 2023. WHO Coronavirus (COVID-19) Dashboard. https://covid19.who.int (accessed 14 November 2023).

      64. Wilk, A.J., Rustagi, A., Zhao, N.Q., Roque, J., Martinez-Colon, G.J., McKechnie, J.L., Ivison, G.T., Ranganath, T., Vergara, R., Hollis, T., Simpson, L.J., Grant, P., Subramanian, A., Rogers, A.J., Blish, C.A., 2020. A single-cell atlas of the peripheral immune response in patients with severe COVID-19. Nat Med 26, 1070-1076.

      65. Wolock, S.L., Lopez, R., Klein, A.M., 2019. Scrublet: Computational Identification of Cell Doublets in Single-Cell Transcriptomic Data. Cell Syst 8, 281-291.e9.

      66. Wong, R., Belk, J.A., Govero, J., Uhrlaub, J.L., Reinartz, D., Zhao, H., Errico, J.M., D’Souza, L., Ripperger, T.J., Nikolich-Zugich, J., Shlomchik, M.J., Satpathy, A.T., Fremont, D.H., Diamond, M.S., Bhattacharya, D., 2020. Affinity-restricted memory B cells dominate recall responses to heterologous flaviviruses. Immunity 53, 1078-1094.e7.

      67. Wu, H., Huang, X.Y., Sun, M.X., Wang, Y., Zhou, H.Y., Tian, Y., He, B., Li, K., Li, D.-Y., Wu, A.P., Wang, H., Qin, C.-F., 2023. Zika virus targets human trophoblast stem cells and prevents syncytialization in placental trophoblast organoids. Nat Commun 14, 5541.

      68. Yang, B., Fan, J., Huang, J., Guo, E., Fu, Y., Liu, S., Xiao, R., Liu, C., Lu, F., Qin, T., He, C., Wang, Z., Qin, X., Hu, D., You, L., Li, X., Wang, T., Wu, P., Chen, G., Zhou, J., Li, K., Sun, C., 2021. Clinical and molecular characteristics of COVID-19 patients with persistent SARS-CoV-2 infection. Nat Commun 12, 3501.

      69. Yang, W., Liu, L.B., Liu, F.L., Wu, Y.H., Zhen, Z.D., Fan, D.Y., Sheng, Z.Y., Song, Z.R., Chang, J.T., Zheng, Y.T., An, J., Wang, P.G., 2023. Single-cell RNA sequencing reveals the fragility of male spermatogenic cells to Zika virus-induced complement activation. Nat Commun 14, 2476.

      70. Young, M.D., Behjati, S., 2020. SoupX removes ambient RNA contamination from droplet-based single-cell RNA sequencing data. Gigascience 9, giaa151.

      71. Zanini, F., Pu, S.Y., Bekerman, E., Einav, S., Quake, S.R., 2018a. Single-cell transcriptional dynamics of flavivirus infection. eLife 7, e32942.

      72. Zanini, F., Robinson, M.L., Croote, D., Sahoo, M.K., Sanz, A.M., Ortiz-Lasso, E., Albornoz, L.L., Rosso, F., Montoya, J.G., Goo, L., Pinsky, B.A., Quake, S.R., Einav, S., 2018b. Virus-inclusive single-cell RNA sequencing reveals the molecular signature of progression to severe dengue. Proc Natl Acad Sci U S A 115, E12363-E12369.

      73. Zhang, X., Liu, L., 2019. Applications of single cell RNA sequencing to research of stem cells. World J Stem Cells 11, 722-728.

      74. Zhang, Z., Luo, D., Zhong, X., Choi, J.H., Ma, Y., Wang, S., Mahrt, E., Guo, W., Stawiski, E.W., Modrusan, Z., Seshagiri, S., Kapur, P., Hon, G.C., Brugarolas, J., Wang, T., 2019. SCINA: A Semi-Supervised Subtyping Algorithm of Single Cells and Bulk Samples. Genes (Basel) 10, E531.

      75. Zhang, Y., Wang, D., Peng, M., Tang, L., Ouyang, J., Xiong, F., Guo, C., Tang, Y., Zhou, Y., Liao, Q., Wu, X., Wang, H., Yu, J., Li, Y., Li, X., Li, G., Zeng, Z., Tan, Y., Xiong, W., 2021. Single-cell RNA sequencing in cancer research. J Exp Clin Cancer Res 40, 81.

      76. Zhao, R., Wang, M., Cao, Jing, Shen, J., Zhou, X., Wang, D., Cao, Jimin, 2021. Flavivirus: From Structure to Therapeutics Development. Life (Basel) 11, 615.

      77. Zhao, X.N., You, Y., Cui, X.M., Gao, H.X., Wang, G.L., Zhang, S.B., Yao, L., Duan, L.J., Zhu, K.L., Wang, Y.L., Li, L., Lu, J.H., Wang, H.B., Fan, J.F., Zheng, H.W., Dai, E.H., Tian, L.Y., Ma, M.J., 2021. Single-cell immune profiling reveals distinct immune response in asymptomatic COVID-19 patients. Signal Transduct Target Ther 6, 342.

      78. Ziegenhain, C., Vieth, B., Parekh, S., Reinius, B., Guillaumet-Adkins, A., Smets, M., Leonhardt, H., Heyn, H., Hellmann, I., Enard, W., 2017. Comparative Analysis of Single-Cell RNA Sequencing Methods. Mol Cell 65, 631-643.e4.

      79. Zou, X., Chen, K., Zou, J., Han, P., Hao, J., Han, Z., 2020. Single-cell RNA-seq data analysis on the receptor ACE2 expression reveals the potential risk of different human organs vulnerable to 2019-nCoV infection. Front Med 14, 185-192.

    • 加载中
    PDF

    Article Metrics

    Article views(1283) PDF downloads(18) Cited by()

    Related
    Proportional views

      Single-cell RNA sequencing to understand host-virus interactions

        Corresponding author: Pei-Gang Wang, pgwang@ccmu.edu.cn
        Corresponding author: Jing An, anjing@ccmu.edu.cn
      • Department of Microbiology, School of Basic Medical Sciences, Capital Medical University, Beijing 100069, China
      • Received Date: 08 March 2023
      • Accepted Date: 23 November 2023

      Abstract: Single-cell RNA sequencing (scRNA-seq) has allowed for the profiling of host and virus transcripts and host-virus interactions at single-cell resolution. This review summarizes the existing scRNA-seq technologies together with their strengths and weaknesses. The applications of scRNA-seq in various virological studies are discussed in depth, which broaden the understanding of the immune atlas, host-virus interactions, and immune repertoire. scRNA-seq can be widely used for virology in the near future to better understand the pathogenic mechanisms and discover more effective therapeutic strategies.

        HTML

      Reference (79) Relative (20)

      目录

      This journal is a member of, and subscribes to the principles of, the Committee on Publication Ethics (COPE)

      鄂ICP备05001977号

         

      鄂公网安备 42010602003674号

      Copyright © 2019 Virologica Sinica. All rights reserved

      /

      DownLoad:  Full-Size Img  PowerPoint
      Return
      Return