Imaging Immunity in Lymph Nodes: Past, Present and Future

  • James Butler
  • Amy Sawtell
  • Simon Jarrett
  • Jason Cosgrove
  • Roger Leigh
  • Jon Timmis
  • Mark Coles
Chapter
First Online:
Part of the Advances in Experimental Medicine and Biology book series (AEMB, volume 915)

Abstract

Immune responses occur as a result of stochastic interactions between a plethora of different cell types and molecules that regulate the migration and function of innate and adaptive immune cells to drive protection from pathogen infection. The trafficking of immune cells into peripheral tissues during inflammation and then subsequent migration to draining lymphoid tissues has been quantitated using radiolabelled immune cells over 40 years ago. However, how these processes lead to efficient immune responses was unclear. Advances in physics (multi-photon), chemistry (probes) and biology (animal models) have provided immunologists with specialized tools to quantify the molecular and cellular mechanisms driving immune function in lymphoid tissues through directly visualising cellular behaviours in 3-dimensions over time. Through the temporal and spatial resolution of multi-photon confocal microscopy immunologists have developed new insights into normal immune homeostasis, host responses to pathogens, anti-tumour immune responses and processes driving development of autoimmune pathologies, by the quantification of the interactions and cellular migration involved in adaptive immune responses. Advances in deep tissue imaging, including new fluorescent proteins, increased resolution, speed of image acquisition, sensitivity, number of signals and improved data analysis techniques have provided unprecedented capacity to quantify immune responses at the single cell level. This quantitative information has facilitated development of high-fidelity mathematical and computational models of immune function. Together this approach is providing new mechanistic understanding of immune responses and new insights into how immune modulators work. Advances in biophysics have therefore revolutionised our understanding of immune function, directly impacting on the development of next generation immunotherapies and vaccines, and is providing the quantitative basis for emerging technology of simulation-guided experimentation and immunotherapeutic design.

Keywords

Multi-photon Immunity Cellular interactions Imaging Migration Modelling Lymph nodes 
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References

  1. Ackerknecht M, Hauser MA, Legler DF, Stein JV (2015) In vivo TCR signaling in CD4(+) T cells imprints a cell-intrinsic, transient low-motility pattern independent of chemokine receptor expression levels, or microtubular network, integrin, and protein kinase C activity. Front Immunol 8(6):297. doi: 10.3389/fimmu.2015.00297.eCollection 2015
  2. Acton SE, Farrugia AJ, Astarita JL, Mourão-Sá D, Jenkins RP, Nye E, Hooper S, van Blijswijk J, Rogers NC, Snelgrove KJ, Rosewell I, Moita LF, Stamp G, Turley SJ, Sahai E, Reis e Sousa C (2014) Dendritic cells control fibroblastic reticular network tension and lymph node expansion. Nature 514(7523):498–502CrossRefPubMedPubMedCentralGoogle Scholar
  3. Alden K, Timmis J, Andrews PS, Veiga-Fernandes H, Coles MC (2012) Pairing experimentation and computational modeling to understand the role of tissue inducer cells in the development of lymphoid organs. Front Immunol 3:172. doi: 10.3389/fimmu.2012.00172 CrossRefPubMedPubMedCentralGoogle Scholar
  4. Alden K, Read M, Timmis J, Andrews P, Veiga-Fernades H, Coles M (2013) Spartan: a comprehensive tool for understanding uncertainty in simulations of biological systems. PLOS Comput Biol 9(2):e1002916. doi: 10.1371/journal.pcbi.1002916
  5. Alden K, Andrews PS, Veiga-Fernandes H, Timmis J, Coles MC (2014) Utilising a simulation platform to understand the effect of domain model assumptions. Nat Comput. doi: 10.1007/s11047-014-9428-7 PubMedCentralGoogle Scholar
  6. Ahrens MB, Orger MB, Robson DN, Li JM, Keller PJ (2013) Whole-brain functional imaging at cellular resolution using light-sheet microscopy. Nat Methods 10:413–420CrossRefPubMedGoogle Scholar
  7. Angermann BR, Klauschen F, Garcia AD, Prustel T, Zhang F, Germain RN, Meier-Schellersheim M (2012) Computational modeling of cellular signaling processes embedded into dynamic spatial contexts. Nat Methods 9(3):283–289CrossRefPubMedPubMedCentralGoogle Scholar
  8. Angus KL, Griffiths G (2013) Cell polarisation and the immunological synapse. Curr Opin Cell Biol 24:85–89CrossRefGoogle Scholar
  9. Arnon TI, Horton RM, Grigorova IL, Cyster JG (2013) Visualization of splenic marginal zone B-cell shuttling and follicular B-cell egress. Nature 493(7434):684–688CrossRefPubMedGoogle Scholar
  10. Bajénoff M, Egen JG, LKoo LY, Laugier JP, Brau F, Glaichenhaus N, Germain RN (2006) Stromal cell networks regulate lymphocyte entry, migration, and territoriality in lymph nodes. Immunity 25(6):989–1001CrossRefPubMedPubMedCentralGoogle Scholar
  11. Batista FD, Harwood NE (2009) The who, how and where of antigen presentation to B cells. Nat Rev Immunol 9(1):15–27CrossRefPubMedGoogle Scholar
  12. Beck A, Wurch T, Bailly C, Corvaia N (2010) Strategies and challenges for the next generation of therapeutic antibodies. Nat Rev Immunol 10:345–352CrossRefPubMedGoogle Scholar
  13. Beltman JB, Maree AFM, Lynch JN, Miller MJ, de Boer RJ (2007) Lymph node topology dictates T cell migration behaviour. J Exp Med 204(4):771–780CrossRefPubMedPubMedCentralGoogle Scholar
  14. Beltman JN, Maree AFM, de Boer RJ (2009) Analysing immune cell migration 9:789–798Google Scholar
  15. Blum KS, Pabst R (2006) Keystones in lymph node development. J Anat 209(5):585–595CrossRefPubMedPubMedCentralGoogle Scholar
  16. Bousso P, Robey EA (2004) Dynamic behaviour of T cells and thymocytes in lymphoid organs as revealed by two-photon microscopy. Immunity 21:349–355CrossRefPubMedGoogle Scholar
  17. Cahalan MD, Parker I (2008) Choreography of cell motility and interaction dynamics imaged by two-photon microscopy in lymphoid organs. Annu Rev Immunol 26:585–626CrossRefPubMedPubMedCentralGoogle Scholar
  18. Cannons JL1, Qi H, Lu KT, Dutta M, Gomez-Rodriguez J, Cheng J, Wakeland EK, Germain RN, Schwartzberg PL (2010) Optimal germinal center responses require a multistage T cell: B cell adhesion process involving integrins, SLAM-associated protein, and CD84. Immunity 26;32(2):253–65Google Scholar
  19. Catron DM, Itano AA, Pape KA, Mueller DL, Jenkins MK (2004) Visualising the first 50 hr of the primary immune response to a soluble antigen. Immunity 21:341–347CrossRefPubMedGoogle Scholar
  20. Cilfone N, Kirschner D, Linderman JJ (2014) Strategies for Efficient numerical implementation of hybrid multi-scale agent-based models to describe biological systems. Cell Mol Bioeng. doi: 10.1007/s12195-014-0363-6 Google Scholar
  21. Coombes JL, Robey EA (2010) Dynamic imaging of host-pathogen interactions in vivo. Nat Rev Immunol 10:353–364CrossRefPubMedGoogle Scholar
  22. Corcoran LM, Tarlinton DM (2016) Regulation of germinal center responses, memory B cells and plasma cell formation-an update. Curr Opin Immunol 39:59–67CrossRefPubMedGoogle Scholar
  23. Cosgrove J, Butler J, Alden K, Read M, Kumar V, Cucurull-Sanchez L, Timmis J, Coles M (2015) Agent-based modeling in systems pharmacology. CPT: Pharmacom Syst Pharmacol 4(11):615–629Google Scholar
  24. De Silva NS, Klein U (2015) Dynamics of B cells in germinal centres. Nat Rev Immunol. 15(3):137–148Google Scholar
  25. Dong CY, Kim KH, Buehler C, Hsu L, Kim H (2000) So PTC, probing deep-tissue structures by two-photon fluorescence microscopy, emerging tools for single cell analysis: advances in optical measurement technologies. Wiley-Liss, pp 221–237Google Scholar
  26. Fletcher AL, Acton SE, Knoblich K (2015) Lymph node fibroblastic reticular cells in health and disease. Nat Rev Immunol 15(6):350–361CrossRefPubMedPubMedCentralGoogle Scholar
  27. Germain RN, Miller MJ, Dustin M, Nussenzweig MC (2006) Dynamics imaging of the immune system: progress, pitfalls and promise. Nat Rev Immunol 6:497–507CrossRefPubMedGoogle Scholar
  28. Gerner MY, Torabi-Parizi P, Germain RN (2015) Strategically localized dendritic cells promote rapid T cell responses to lymph-borne particulate antigens. Immunity 42:172–185CrossRefPubMedGoogle Scholar
  29. Green JA, Cyster JG (2012) S1PR2 links germinal center confinement and growth regulation. Immunol Rev 247(1):36–51CrossRefPubMedPubMedCentralGoogle Scholar
  30. Gong C1, Mattila JT, Miller M, Flynn JL, Linderman JJ, Kirschner D (2013) Predicting lymph node output efficiency using systems biology. J Theor Biol. 335:169–184Google Scholar
  31. Ghigo C, Mondor I, Jorquera A, Nowak J, Wienert S, Zahner SP, Clausen BE, Luche H, Malissen B, Klauschen F, Bajénoff M (2013) Multicolor fate mapping of Langerhans cell homeostasis. J Exp Med 210(9):1657–1664CrossRefPubMedPubMedCentralGoogle Scholar
  32. Harris TH, Banigan EJ, Christian DA, Konradt C, Woino EDT, Norose K, Wilson EH, John B, Weninger W, Luster AD, Liu AJ, Hunter CA (2012) Generalized Lévy walks and the role of chemokines in migration of effector CD8+T cells. Nature 486:545–548PubMedPubMedCentralGoogle Scholar
  33. Headley MB, Bins A, Nip A, Roberts EW, Looney MR, Gerard A, Krummel MF (2016) Visualization of immediate immune responses to pioneer metastatic cells in the lung. Nature 24;531(7595):513–7Google Scholar
  34. Huang AY, Qi H, Germain RN (2004) Illuminating the landscape of in vivo immunity: insights from dynamic in situ imaging of secondary lymphoid tissues. Immunity 21(3):331–339PubMedGoogle Scholar
  35. Kirschner DE, Linderman JL (2009) Mathematical and computational approaches can complement experimental studies of host pathogen interactions. Cell Microb 11(4). doi: 10.1111/j.1462-5822.2009.01281
  36. Kislitsyn A, Savinkov R, Novkovic M, Onder L, Bocharov G (2015) Computational approach to 3D modeling of the lymph node geometry. Computation 3(2):222–234. doi: 10.3390/computation3020222 CrossRefGoogle Scholar
  37. Lämmermann T, Afonso PV, Angermann BR, Wang JM, Kastenmüller W, Parent CA, Germain RN (2013) Neutrophil swarms require LTB4 and integrins at sites of cell death in vivo. Nature 498(7454):371–375CrossRefPubMedGoogle Scholar
  38. Looney MR, Thorton EE, Sen D, Lamm WJ, Glenny RW, Krummel MF (2011) Stabilized imaging of immune surveillance in the mouse lung. Nat Methods 8(1):91–96CrossRefPubMedGoogle Scholar
  39. Ludewig B, Stein JV, Sharpe J, Cervantes-Barragan L, Thiel V, Bocharov G (2012) Eur J Immunol 42:3116–3125CrossRefPubMedGoogle Scholar
  40. Mempel TR, Scimone ML, Mora JR, von Andrian UH (2004a) In vivo imaging of leukocyte trafficking in blood vessels and tissues. Curr Opin Immunol 16(4):406–417CrossRefPubMedGoogle Scholar
  41. Mempel TR, Henrickson SE, Von Andrian UH (2004b) T-cell priming by dendritic cells in lymph nodes occurs in three distinct phases. Nature 427(6970):154–159CrossRefPubMedGoogle Scholar
  42. Meyer-Hermann M, Figge MT, Toellner KM (2009) Germinal centres seen through the mathematical eye: B-cell models on the catwalk. Trends Immunol 30(4):157–164CrossRefPubMedGoogle Scholar
  43. Meyer-Hermann M, Mohr E, Pelletier N, Zhang Y, Victora GD, Toellner KM (2012) A theory of germinal center B cell selection, division, and exit. Cell Reports 2(1):162–74Google Scholar
  44. Michalet X, Pinaud FF, Bentolila LA, Tsya JM, Doose S, Li JJ, Sundaresan G, Wu AM, Gambhir SS, Weiss S (2005) Quantum dots for live cells, in vivo imaging and diagnostics. Science 307:538–544CrossRefPubMedPubMedCentralGoogle Scholar
  45. Muppidi JR, Schmitz R, Green JA, Xiao W, Larsen AB, Braun SE, An J, Xu Y, Rosenwald A, Ott G, Gascoyne RD, Rimsza LM, Campo E, Jaffe ES, Delabie J, Smeland EB, Braziel RM, Tubbs RR, Cook JR, Weisenburger DD, Chan WC, Vaidehi N, Staudt LM, Cyster JG (2014) Loss of signalling via Gα13 in germinal centre B-cell-derived lymphoma. Nature 516(7530):254–258Google Scholar
  46. Phan TG, Grigorova I, Okada T, Cyster JG (2007) Subcapsular encounter and complement-dependent transport of immune complexes by lymph node B cells. Nat Immunol 8(9):992–1000Google Scholar
  47. Rantakari P, Auvinen K, Jäppinen N, Kapraali M, Valtonen J, Karikoski M, Gerke H, Iftakhar-E-Khuda I, Keuschnigg J, Umemoto E, Tohya K, Miyasaka M, Elima K, Jalkanen S, Salmi M (2015) The endothelial protein PLVAP in lymphatics controls the entry of lymphocytes and antigens into lymph nodes. Nat Immunol. 16(4):386–396Google Scholar
  48. Robey EA, Bousso P (2003) Visualizing thymocyte motility using 2-photon microscopy. Immunol Rev 195:51–57CrossRefPubMedGoogle Scholar
  49. Rossy J, Pageon SV, Davis DM, Gaus K (2013) Super-resolution microscopy of the immunological synapse. Curr Opin Immunol 25(3):307–312CrossRefPubMedGoogle Scholar
  50. Russo E, Teijeira A, Vaahtomeri K, Willrodt AH, Bloch JS, Nitschké M, Santambrogio L, Kerjaschki D, Sixt M, Halin C (2016) Intralymphatic CCL21 promotes tissue egress of dendritic cells through afferent lymphatic vessels. Cell Reports. pii:S2211-1247(16)30026-2. doi: 10.1016/j.celrep.2016.01.048
  51. Shulman Z, Gitlin AD, Weinstein JS, Lainez B, Esplugues E, Flavell RA, Craft JE, Nussenzweig MC (2014) Dynamic signaling by T follicular helper cells during germinal center B cell selection. Science 345(6200):1058–1062Google Scholar
  52. Sixt M, Kanazawa N, Selg M, Samson T, Roos G, Reinhardt DP, Pabst R, Lutz MB, Sorokin L (2005) The conduit system transports soluble antigens from the afferent lymph to resident dendritic cells in the T cell area of the lymph node. Immunity 22(1):19–29CrossRefPubMedGoogle Scholar
  53. Sumen C, Mempel T, Mazo IB, von Andrian UH (2004) Intravital microscopy: visualizing immunity in context. Immunity 21:315–329Google Scholar
  54. Tainaka K, Kubota SI, Suyama TQ, Susaki EA, Perrin D, Ukai-Tadenuma M, Ukai H, Ueda HR (2014) Whole-body imaging with single-cell resolution by tissue decolorization. Cell 159(4):911–24Google Scholar
  55. Tarakhovsky A (2005) On imaging, speed, and the future of lymphocyte signaling. J Exp Med 201:505–508CrossRefPubMedPubMedCentralGoogle Scholar
  56. Tas JM, Mesin L, Pasqual G, Targ S, Jacobsen JT, Mano YM, Chen CS, Weill JC, Reynaud CA, Browne EP, Meyer-Hermann M, Victora GD (2016) Visualizing antibody affinity maturation in germinal centers. Science 351(6277):1048–1054Google Scholar
  57. Thorton EE, Looney MR, Bose O, Sen D, Sheppard D, Locksley R, Huang X, Krummel MF (2012) Spatiotemporal separated antigen uptake by aveolar dendritic cells and airway presentation to T cells in the lung. J Exp Med 209(6):1183–1199CrossRefGoogle Scholar
  58. Ulvmar MH, Werth K, Braun A, Kelay P, Hub E, Eller K, Chan L, Lucas B, Novitzky-Basso I, Nakamura K, Rülicke T, Nibbs RJ, Worbs T, Förster R, Rot A (2014) The atypical chemokine receptor CCRL1 shapes functional CCL21 gradients in lymph nodes. Nat Immunol 15(7):623–630CrossRefPubMedGoogle Scholar
  59. Victoria GD, Schwixker TA, Fooksman DR, Kamphorst AO, Meyer-Hermann M, Dustin ML, Nussenzweig MC (2010) Germinal centre dynamics revealed by multiphoton microscopy with a photoactivatable fluorescent reporter. Cell 143:592–605CrossRefGoogle Scholar
  60. von Andrian UH, Mempel TR (2003) Homing and cellular traffic in lymph nodes. Nat Rev Immunol 3(11):867–878Google Scholar
  61. Weber M, Hauschild R, Schwarz J, Moussion C, de Vries I, Legler DF, Luther SA, Bollenbach T, Sixt M (2013) Interstitial dendritic cell guidance by haptotactic chemokine gradients. Science 339(6117):328–332. doi: 10.1126/science.1228456
  62. Wei SH, Parker I, Miller MJ, Cahalan MD (2003) A stochastic view of lymphocyte motility and trafficking within the lymph node. Immunol Rev 195:136–159CrossRefPubMedGoogle Scholar
  63. Weiner LM, Rishi Surana R, Wang S (2010) Monoclonal antibodies: versatile platforms for cancer immunotherapy. Nat Rev Immunol 10:317–327CrossRefPubMedPubMedCentralGoogle Scholar
  64. Weninger W, Biro M, Jain R (2014) Leukocyte migration in the interstitial space of non-lymphoid organs. Nat Rev Immunol 14(4):232–246CrossRefPubMedGoogle Scholar
  65. Witt C, Raychaudhuri S, Chakraborty AK (2005) Movies, measurement, and modeling: the three Ms of mechanistic immunology. J Exp Med 201(4):501–504CrossRefPubMedPubMedCentralGoogle Scholar
  66. Zipfel WR, Williams RM, Webb WW (2003) Nonlinear magic: multiphoton microscopy in the biosciences. Nat Biotechnol 21(11):1369–1377CrossRefPubMedGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • James Butler
    • 1
    • 2
    • 3
  • Amy Sawtell
    • 1
  • Simon Jarrett
    • 1
    • 2
    • 3
  • Jason Cosgrove
    • 1
    • 2
    • 3
  • Roger Leigh
    • 1
  • Jon Timmis
    • 2
    • 3
  • Mark Coles
    • 1
    • 2
  1. 1.Centre for Immunology and Infection, Department of BiologyYorkUK
  2. 2.York Computational Immunology LaboratoryYorkUK
  3. 3.Department of ElectronicsUniversity of YorkYorkUK

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