Microscale Technologies for High-Throughput Analysis of Immune Cells

  • Mark Pogson
  • William Kelton
  • Sai T. ReddyEmail author


High-throughput microscale technologies such as next-generation sequencing (NGS), proteomics, and microfluidics-single cell analysis are now being applied for the quantitative analysis of immunological systems. In this chapter we go over several of the new and exciting developments of this emerging field of systems immunology. First, we describe the major advances in transcriptome analysis; this includes microarray technology and RNA sequencing, which have both contributed great insight into the quantitative gene expression profile of immune cells. We also highlight recent progress in combining microfluidics with RNA sequencing for whole transcriptome analysis from single immune cells. High-throughput immune repertoire analysis has also recently become a valuable method for obtaining quantitative information on the diversity and distribution of adaptive immune responses. Therefore, we describe advances in the NGS of antibody repertoires from B cell populations including its combination with microfluidicis-single cell analysis and proteomics technologies. We then describe how these approaches to antibody repertoire analysis have been used for monoclonal antibody discovery and engineering and vaccine profiling. In summary, these high-throughput microscale technologies have already impacted the study of many areas of immunology, including basic mechanisms, clinical and translational immunology, and biotechnology – this will only continue to expand as these technologies become more advanced and accessible.


Next-generation sequencing Proteomics Antibody repertoires Transcriptome 


  1. 1.
    Kidd BA, Peters LA, Schadt EE, Dudley JT (2014) Unifying immunology with informatics and multiscale biology. Nat Immunol 15:118–127. doi: 10.1038/ni.2787 CrossRefGoogle Scholar
  2. 2.
    Brusic V, Gottardo R, Kleinstein SH et al (2014) Computational resources for high-dimensional immune analysis from the Human Immunology Project Consortium. Nat Biotechnol 32:146–148. doi: 10.1038/nbt.2777 CrossRefGoogle Scholar
  3. 3.
    Snijder B, Kandasamy RK, Superti-Furga G (2014) Toward effective sharing of high-dimensional immunology data. Nat Biotechnol 32:755–759. doi: 10.1038/nbt.2974 CrossRefGoogle Scholar
  4. 4.
    Schena M, Shalon D, Davis RW, Brown PO (1995) Quantitative monitoring of gene expression patterns with a complementary DNA microarray. Science 270:467–470CrossRefGoogle Scholar
  5. 5.
    Shaffer AL, Rosenwald A, Hurt EM et al (2001) Signatures of the immune response. Immunity 15:375–385. doi: 10.1016/S1074-7613(01)00194-7 CrossRefGoogle Scholar
  6. 6.
    Painter MW, Davis S, Hardy RR et al (2011) Transcriptomes of the B and T lineages compared by multiplatform microarray profiling. J Immunol 186:3047–3057. doi: 10.4049/jimmunol.1002695 CrossRefGoogle Scholar
  7. 7.
    Kaech SM, Hemby S, Kersh E, Ahmed R (2002) Molecular and functional profiling of memory CD8 T cell differentiation. Cell 111:837–851. doi: 10.1016/S0092-8674(02)01139-X CrossRefGoogle Scholar
  8. 8.
    Ollila J, Vihinen M (2002) Microarray analysis of B-cell stimulation. In: Analysis of B cell memory formation using DNA microarrays. Elsevier, pp 77–99Google Scholar
  9. 9.
    Magalhães DAR, Macedo C, Junta CM et al (2005) Hybridization signatures during thymus ontogeny reveals modulation of genes coding for T-cell signaling proteins. Mol Immunol 42:1043–1048. doi: 10.1016/j.molimm.2004.09.031 CrossRefGoogle Scholar
  10. 10.
    Cretney E, Xin A, Shi W et al (2011) The transcription factors Blimp-1 and IRF4 jointly control the differentiation and function of effector regulatory T cells. Nat Immunol 12:304–311. doi: 10.1038/ni.2006 CrossRefGoogle Scholar
  11. 11.
    Kin NW, Crawford DM, Liu J et al (2008) DNA microarray gene expression profile of marginal zone versus follicular B cells and idiotype positive marginal zone B cells before and after immunization with Streptococcus pneumoniae. J Immunol 180:6663–6674. doi: 10.4049/jimmunol.180.10.6663 CrossRefGoogle Scholar
  12. 12.
    Wirth TC, Xue H-H, Rai D et al (2010) Repetitive antigen stimulation induces stepwise transcriptome diversification but preserves a core signature of memory CD8+ T cell differentiation. Immunity 33:128–140. doi: 10.1016/j.immuni.2010.06.014 CrossRefGoogle Scholar
  13. 13.
    Alizadeh AA, Eisen MB, Davis RE et al (2000) Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling. Nature 403:503–511. doi: 10.1038/35000501 CrossRefGoogle Scholar
  14. 14.
    Rosenwald A, Wright G, Leroy K et al (2003) Molecular diagnosis of primary mediastinal B cell lymphoma identifies a clinically favorable subgroup of diffuse large B cell lymphoma related to Hodgkin lymphoma. J Exp Med 198:851–862. doi: 10.1084/jem.20031074 CrossRefGoogle Scholar
  15. 15.
    Becker AM, Dao KH, Han BK et al (2013) SLE peripheral blood B cell, T cell and myeloid cell transcriptomes display unique profiles and each subset contributes to the interferon signature. PLoS One 8:e67003. doi: 10.1371/journal.pone.0067003 CrossRefGoogle Scholar
  16. 16.
    Raine T, Liu JZ, Anderson CA et al (2015) Generation of primary human intestinal T cell transcriptomes reveals differential expression at genetic risk loci for immune-mediated disease. Gut 64:250. doi: 10.1136/gutjnl-2013-306657 CrossRefGoogle Scholar
  17. 17.
    Leshchenko VV, Kuo P-Y, Shaknovich R et al (2010) Genomewide DNA methylation analysis reveals novel targets for drug development in mantle cell lymphoma. Blood 116:1025–1034. doi: 10.1182/blood-2009-12-257485 CrossRefGoogle Scholar
  18. 18.
    Metzker ML (2010) Sequencing technologies |[mdash]| the next generation. Nat Rev Genet 11:31–46. doi: 10.1038/nrg2626 CrossRefGoogle Scholar
  19. 19.
    Marioni JC, Mason CE, Mane SM et al (2008) RNA-seq: an assessment of technical reproducibility and comparison with gene expression arrays. Genome Res 18:1509–1517. doi: 10.1101/gr.079558.108 CrossRefGoogle Scholar
  20. 20.
    Zhao S, Fung-Leung W-P, Bittner A et al (2014) Comparison of RNA-Seq and microarray in transcriptome profiling of activated T cells. PLoS One 9:e78644. doi: 10.1371/journal.pone.0078644 CrossRefGoogle Scholar
  21. 21.
    Fritz EL, Rosenberg BR, Lay K et al (2013) A comprehensive analysis of the effects of the deaminase AID on the transcriptome and methylome of activated B cells. Nat Immunol 14:749–755. doi: 10.1038/ni.2616 CrossRefGoogle Scholar
  22. 22.
    Li X, Cui Z, Liu Y et al (2013) Transcriptome analysis and discovery of genes involved in immune pathways from hepatopancreas of microbial challenged mitten crab Eriocheir sinensis. PLoS One 8:e68233. doi: 10.1371/journal.pone.0068233 CrossRefGoogle Scholar
  23. 23.
    Zhao F, Yan C, Wang X et al (2013) Comprehensive transcriptome profiling and functional analysis of the frog (Bombina maxima) immune system. DNA Res 21:dst035–13. doi: 10.1093/dnares/dst035 Google Scholar
  24. 24.
    Meitern R, Andreson R, Hõrak P (2014) Profile of whole blood gene expression following immune stimulation in a wild passerine. BMC Genomics 15:533. doi: 10.1186/1471-2164-15-533 CrossRefGoogle Scholar
  25. 25.
    Wu AR, Neff NF, Kalisky T et al (2014) Quantitative assessment of single-cell RNA-sequencing methods. Nat Methods 11:41–46. doi: 10.1038/nmeth.2694 CrossRefGoogle Scholar
  26. 26.
    Tang F, Barbacioru C, Wang Y et al (2009) mRNA-Seq whole-transcriptome analysis of a single cell. Nat Methods 6:377–382. doi: 10.1038/nmeth.1315 CrossRefGoogle Scholar
  27. 27.
    Weinstein JA, Zeng X, Chien Y-H, Quake SR (2013) Correlation of gene expression and genome mutation in single B-cells. PLoS One 8:e67624. doi: 10.1371/journal.pone.0067624 CrossRefGoogle Scholar
  28. 28.
    Han A, Glanville J, Hansmann L, Davis MM (2014) Linking T-cell receptor sequence to functional phenotype at the single-cell level. Nat Biotechnol 32:684–692. doi: 10.1038/nbt.2938 CrossRefGoogle Scholar
  29. 29.
    Mahata B, Zhang X, Kolodziejczyk AA et al (2014) Single-cell RNA sequencing reveals T helper cells synthesizing steroids de novo to contribute to immune homeostasis. Cell Rep 7:1130–1142. doi: 10.1016/j.celrep.2014.04.011 CrossRefGoogle Scholar
  30. 30.
    Wetterstrand KA (2014) DNA sequencing costs: data from the NHGRI Genome Sequencing Program (GSP). Available at: Accessed 1 Dec 2014Google Scholar
  31. 31.
    Georgiou G, Ippolito GC, Beausang J et al (2014) The promise and challenge of high-throughput sequencing of the antibody repertoire. Nat Biotechnol 32:158–168. doi: 10.1038/nbt.2782 CrossRefGoogle Scholar
  32. 32.
    Robins H (2013) Immunosequencing: applications of immune repertoire deep sequencing. Curr Opin Immunol 25:646–652. doi: 10.1016/j.coi.2013.09.017 CrossRefGoogle Scholar
  33. 33.
    Galson JD, Pollard AJ, Trück J, Kelly DF (2014) Studying the antibody repertoire after vaccination: practical applications. Trends Immunol 35:319–331. doi: 10.1016/ CrossRefGoogle Scholar
  34. 34.
    Joshi SA, Boyd SD (2015) High-Throughput DNA sequencing analysis of antibody repertoires. In: Antibodies for infectious diseases. American Society of Microbiology, pp 345–362Google Scholar
  35. 35.
    Jiang N, Jiang N, Weinstein JA et al (2011) Determinism and stochasticity during maturation of the zebrafish antibody repertoire. Proc Natl Acad Sci U S A 108:5348–5353. doi: 10.1073/pnas.1014277108 CrossRefGoogle Scholar
  36. 36.
    Kaplinsky J, Li A, Sun A et al (2014) Antibody repertoire deep sequencing reveals antigen-independent selection in maturing B cells. Proc Natl Acad Sci U S A 111:E2622–E2629. doi: 10.1073/pnas.1403278111 CrossRefGoogle Scholar
  37. 37.
    Weinstein JA, Jiang N, White RA et al (2009) High-throughput sequencing of the Zebrafish antibody repertoire. Science 324:807–810. doi: 10.1126/science.1170020 CrossRefGoogle Scholar
  38. 38.
    Jackson KJL, Liu Y, Roskin KM et al (2014) Human responses to influenza vaccination show seroconversion signatures and convergent antibody rearrangements. Cell Host Microbe 16:105–114. doi: 10.1016/j.chom.2014.05.013 CrossRefGoogle Scholar
  39. 39.
    Jiang N, He J, Weinstein JA et al (2013) Lineage structure of the human antibody repertoire in response to influenza vaccination. Sci Transl Med 5:171ra19. doi: 10.1126/scitranslmed.3004794 CrossRefGoogle Scholar
  40. 40.
    Lavinder JJ, Wine Y, Giesecke C et al (2014) Identification and characterization of the constituent human serum antibodies elicited by vaccination. Proc Natl Acad Sci U S A 111:2259–2264. doi: 10.1073/pnas.1317793111 CrossRefGoogle Scholar
  41. 41.
    Laserson U, Vigneault F, Gadala-Maria D et al (2014) High-resolution antibody dynamics of vaccine-induced immune responses. Proc Natl Acad Sci U S A 111:4928–4933. doi: 10.1073/pnas.1323862111 CrossRefGoogle Scholar
  42. 42.
    Parameswaran P, Liu Y, Roskin KM et al (2013) Convergent antibody signatures in human dengue. Cell Host Microbe 13:691–700. doi: 10.1016/j.chom.2013.05.008 CrossRefGoogle Scholar
  43. 43.
    Boyd SD, Marshall EL, Merker JD et al (2009) Measurement and clinical monitoring of human lymphocyte clonality by massively parallel V-D-J pyrosequencing. Sci Transl Med 1:12ra23. doi: 10.1126/scitranslmed.3000540 CrossRefGoogle Scholar
  44. 44.
    Reddy ST, Ge X, Miklos AE et al (2010) Monoclonal antibodies isolated without screening by analyzing the variable-gene repertoire of plasma cells. Nat Biotechnol 28:965–969. doi: 10.1038/nbt.1673 CrossRefGoogle Scholar
  45. 45.
    DeKosky BJ, Ippolito GC, Deschner RP et al (2013) High-throughput sequencing of the paired human immunoglobulin heavy and light chain repertoire. Nat Biotechnol 31:166–169. doi: 10.1038/nbt.2492 CrossRefGoogle Scholar
  46. 46.
    Cheung WC, Beausoleil SA, Zhang X et al (2012) A proteomics approach for the identification and cloning of monoclonal antibodies from serum. Nat Biotechnol 30:447–452. doi: 10.1038/nbt.2167 CrossRefGoogle Scholar
  47. 47.
    Glanville J, Zhai W, Berka J et al (2009) Precise determination of the diversity of a combinatorial antibody library gives insight into the human immunoglobulin repertoire. Proc Natl Acad Sci U S A 106:20216–20221. doi: 10.1073/pnas.0909775106 CrossRefGoogle Scholar
  48. 48.
    Zhu J, Wu X, Zhang B et al (2013) De novo identification of VRC01 class HIV-1-neutralizing antibodies by next-generation sequencing of B-cell transcripts. Proc Natl Acad Sci U S A 110:E4088–E4097. doi: 10.1073/pnas.1306262110 CrossRefGoogle Scholar
  49. 49.
    Li J, Li J, Sai T et al (2006) Human antibodies for immunotherapy development generated via a human B cell hybridoma technology. Proc Natl Acad Sci U S A 103:3557–3562. doi: 10.1073/pnas.0511285103 CrossRefGoogle Scholar
  50. 50.
    Brickell PM, Brickell PM (1991) Immortalization of human B-lymphocytes by Epstein-Barr Vlls, Practical molecular virology. Humana Press, Totowa, NJ, pp 213–218Google Scholar
  51. 51.
    Sendra VG, Lie A, Romain G et al (2013) Detection and isolation of auto-reactive human antibodies from primary B cells. Methods 64:153–159. doi: 10.1016/j.ymeth.2013.06.018 CrossRefGoogle Scholar
  52. 52.
    Ogunniyi AO, Thomas BA, Politano TJ et al (2014) Profiling human antibody responses by integrated single-cell analysis. Vaccine 32:2866–2873. doi: 10.1016/j.vaccine.2014.02.020 CrossRefGoogle Scholar
  53. 53.
    Love JC, Ronan JL, Grotenbreg GM et al (2006) A microengraving method for rapid selection of single cells producing antigen-specific antibodies. Nat Biotechnol 24:703–707. doi: 10.1038/nbt1210 CrossRefGoogle Scholar
  54. 54.
    Wine Y, Boutz DR, Lavinder JJ et al (2013) Molecular deconvolution of the monoclonal antibodies that comprise the polyclonal serum response. Proc Natl Acad Sci U S A 110:2993–2998. doi: 10.1073/pnas.1213737110 CrossRefGoogle Scholar
  55. 55.
    Wrammert J, Smith K, Miller J et al (2008) Rapid cloning of high-affinity human monoclonal antibodies against influenza virus. Nature 453:667–671. doi: 10.1038/nature06890 CrossRefGoogle Scholar
  56. 56.
    Scheid JF, Mouquet H, Feldhahn N et al (2009) A method for identification of HIV gp140 binding memory B cells in human blood. J Immunol Methods 343:65–67. doi: 10.1016/j.jim.2008.11.012 CrossRefGoogle Scholar
  57. 57.
    Busse CE, Czogiel I, Braun P et al (2013) Single-cell based high-throughput sequencing of full-length immunoglobulin heavy and light chain genes. Eur J Immunol 44:597–603. doi: 10.1002/eji.201343917 CrossRefGoogle Scholar
  58. 58.
    Bradshaw EM, Kent SC, Tripuraneni V et al (2008) Concurrent detection of secreted products from human lymphocytes by microengraving: Cytokines and antigen-reactive antibodies. Clin Immunol 129:10–18. doi: 10.1016/j.clim.2008.06.009 CrossRefGoogle Scholar
  59. 59.
    Meijer P-J, Andersen PS, Haahr Hansen M et al (2006) Isolation of human antibody repertoires with preservation of the natural heavy and light chain pairing. J Mol Biol 358:764–772. doi: 10.1016/j.jmb.2006.02.040 CrossRefGoogle Scholar
  60. 60.
    Smith K, Garman L, Wrammert J et al (2009) Rapid generation of fully human monoclonal antibodies specific to a vaccinating antigen. Nat Protoc 4:372–384. doi: 10.1038/nprot.2009.3 CrossRefGoogle Scholar
  61. 61.
    Sato S, Beausoleil SA, Popova L et al (2012) Proteomics-directed cloning of circulating antiviral human monoclonal antibodies. Nat Biotechnol 30:1039–1043. doi: 10.1038/nbt.2406 CrossRefGoogle Scholar
  62. 62.
    Fridy PC, Li Y, Keegan S et al (2014) A robust pipeline for rapid production of versatile nanobody repertoires. Nat Methods 11:1253–1260. doi: 10.1038/nmeth.3170 CrossRefGoogle Scholar
  63. 63.
    Tiller T, Meffre E, Yurasov S et al (2008) Efficient generation of monoclonal antibodies from single human B cells by single cell RT-PCR and expression vector cloning. J Immunol Methods 329:112–124. doi: 10.1016/j.jim.2007.09.017 CrossRefGoogle Scholar
  64. 64.
    Krause JC, Krause JC, Tsibane T et al (2012) Human monoclonal antibodies to pandemic 1957 H2N2 and pandemic 1968 H3N2 influenza viruses. J Virol 86:6334–6340. doi: 10.1128/JVI.07158-11 CrossRefGoogle Scholar
  65. 65.
    Yu X, Tsibane T, McGraw PA et al (2008) Neutralizing antibodies derived from the B cells of 1918 influenza pandemic survivors. Nature 455:532–536. doi: 10.1038/nature07231 CrossRefGoogle Scholar
  66. 66.
    Lanzavecchia A, Corti D, Sallusto F (2007) Human monoclonal antibodies by immortalization of memory B cells. Curr Opin Biotechnol 18:523–528. doi: 10.1016/j.copbio.2007.10.011 CrossRefGoogle Scholar
  67. 67.
    Wilson PC, Andrews SF (2012) Tools to therapeutically harness the human antibody response. Nat Rev Immunol 12:709–719. doi: 10.1038/nri3285 CrossRefGoogle Scholar
  68. 68.
    Wardemann H (2003) Predominant autoantibody production by early human B cell precursors. Science 301:1374–1377. doi: 10.1126/science.1086907 CrossRefGoogle Scholar
  69. 69.
    Scheid JF, Mouquet H, Feldhahn N et al (2009) Broad diversity of neutralizing antibodies isolated from memory B cells in HIV-infected individuals. Nature 458:636–640. doi: 10.1038/nature07930 CrossRefGoogle Scholar
  70. 70.
    Di Niro R, Mesin L, Zheng N-Y et al (2012) High abundance of plasma cells secreting transglutaminase 2–specific IgA autoantibodies with limited somatic hypermutation in celiac disease intestinal lesions. Nat Med 18:441–445. doi: 10.1038/nm.2656 CrossRefGoogle Scholar
  71. 71.
    Scheid JF, Mouquet H, Ueberheide B et al (2011) Sequence and structural convergence of broad and potent HIV antibodies that mimic CD4 binding. Science 333:1633–1637. doi: 10.1126/science.1207227 CrossRefGoogle Scholar
  72. 72.
    Mouquet H, Klein F, Scheid JF et al (2011) Memory B cell antibodies to HIV-1 gp140 cloned from individuals infected with clade A and B viruses. PLoS One 6:e24078. doi: 10.1371/journal.pone.0024078 CrossRefGoogle Scholar
  73. 73.
    Wu X, Yang ZY, Li Y et al (2010) Rational design of envelope identifies broadly neutralizing human monoclonal antibodies to HIV-1. Science 329:856–861. doi: 10.1126/science.1187659 CrossRefGoogle Scholar
  74. 74.
    Trama AM, Moody MA, Alam SM et al (2014) HIV-1 envelope gp41 antibodies can originate from terminal ileum B cells that share cross-reactivity with commensal bacteria. Cell Host Microbe 16:215–226. doi: 10.1016/j.chom.2014.07.003 CrossRefGoogle Scholar
  75. 75.
    Lu DR, Tan Y-C, Kongpachith S et al (2014) Identifying functional anti-Staphylococcus aureus antibodies by sequencing antibody repertoires of patient plasmablasts. Clin Immunol 152:77–89. doi: 10.1016/j.clim.2014.02.010 CrossRefGoogle Scholar
  76. 76.
    DeKosky BJ, Kojima T, Rodin A et al (2015) In-depth determination and analysis of the human paired heavy- and light-chain antibody repertoire. Nat Med 21:86–91. doi: 10.1038/nm.3743 CrossRefGoogle Scholar
  77. 77.
    Ostuni E, Chen CS, Ingber DE, Whitesides GM (2001) Selective deposition of proteins and cells in arrays of microwells. Langmuir 17:2828–2834. doi: 10.1021/la001372o CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Department of Biosystems Science and EngineeringETH ZurichBaselSwitzerland

Personalised recommendations