Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Innovation
  • Published:

Laser scanning cytometry: understanding the immune system in situ

Nature Reviews Immunology volume 7, pages 897–904 (2007)Cite this article

Abstract

Flow cytometry allows quantitative analysis of the identity and effector function of individual cells. However, it cannot provide information on cellular responses that occur within physiological tissue microenvironments. Laser scanning cytometry is an emerging technology that allows imaging and quantitative analysis of individual cells in tissues in situ. This article describes the technology and its potential for delineating the molecular and cellular events underpinning the immune response in health and disease.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Figure 1: Laser scanning cytometry (LSC).
Figure 2: Analysis of ERK signalling in OVA-specific T cells.
Figure 3: Tissue map analysis of OVA-specific transgenic T cells in vivo.

Similar content being viewed by others

References

  1. Grierson, A. M. et al. Direct quantitation of T cell signaling by laser scanning cytometry. J. Immunol. Methods 301, 140–153 (2005).

    Article  CAS  Google Scholar 

  2. Pozarowski, P., Holden, E. & Darzynkiewicz, Z. Laser scanning cytometry: principles and applications. Methods Mol. Biol. 319, 165–192 (2006).

    Article  CAS  Google Scholar 

  3. Gerstner, A. O. et al. Quantitative histology by multicolor slide-based cytometry. Cytometry A 59, 210–219 (2004).

    Article  Google Scholar 

  4. Tarnok, A. & Gerstner, A. O. Clinical applications of laser scanning cytometry. Cytometry 50, 133–143 (2002).

    Article  Google Scholar 

  5. Mittag, A. et al. Polychromatic (eight-color) slide-based cytometry for the phenotyping of leukocyte, NK, and NKT subsets. Cytometry A 65, 103–115 (2005).

    Article  Google Scholar 

  6. Mittag, A., Lenz, D., Gerstner, A. O. & Tarnok, A. Hyperchromatic cytometry principles for cytomics using slide based cytometry. Cytometry A 69, 691–703 (2006).

    Article  Google Scholar 

  7. Luther, E., Kamentsky, L., Henriksen, M. & Holden, E. Next-generation laser scanning cytometry. Methods Cell Biol. 75, 185–218 (2004).

    Article  CAS  Google Scholar 

  8. Kamentsky, L. A. & Kamentsky, L. D. Microscope-based multiparameter laser scanning cytometer yielding data comparable to flow cytometry data. Cytometry 12, 381–387 (1991).

    Article  CAS  Google Scholar 

  9. Rew, D. A., Woltmann, G. & Kaur, D. Near-clinical applications of laser scanning cytometry. Methods Mol. Biol. 319, 193–212 (2006).

    Article  CAS  Google Scholar 

  10. Mittag, A. et al. Sequential photobleaching of fluorochromes for polychromatic slide-based cytometry. Cytometry A 69, 139–141 (2006).

    Article  Google Scholar 

  11. Gerstner, A. O. et al. Comparison of immunophenotyping by slide-based cytometry and by flow cytometry. J. Immunol. Methods 311, 130–138 (2006).

    Article  CAS  Google Scholar 

  12. Dey, P. Role of ancillary techniques in diagnosing and subclassifying non-Hodgkin's lymphomas on fine needle aspiration cytology. Cytopathology 17, 275–287 (2006).

    Article  CAS  Google Scholar 

  13. Holme, A. L., Yadav, S. K. & Pervaiz, S. Automated laser scanning cytometry: a powerful tool for multi-parameter analysis of drug-induced apoptosis. Cytometry A 71, 80–86 (2007).

    Article  Google Scholar 

  14. Laffers, W., Mittag, A., Lenz, D., Tarnok, A. & Gerstner, A. O. Iterative restaining as a pivotal tool for n-color immunophenotyping by slide-based cytometry. Cytometry A 69, 127–130 (2006).

    Article  Google Scholar 

  15. Bocsi, J. et al. Novel aspects of systems biology and clinical cytomics. Cytometry A 69, 105–108 (2006).

    Article  Google Scholar 

  16. Gerstner, A. O. et al. Preoperative detection of laryngeal cancer in mucosal swabs by slide-based cytometry. Eur. J. Cancer 41, 445–452 (2005).

    Article  Google Scholar 

  17. Gerstner, A. O. et al. Prediction of upper aerodigestive tract cancer by slide-based cytometry. Cytometry A 69, 582–587 (2006).

    Article  Google Scholar 

  18. Kornblau, S. M. et al. Studying the right cell in acute myelogenous leukemia: dynamic changes of apoptosis and signal transduction pathway protein expression in chemotherapy resistant ex-vivo selected “survivor cells”. Cell Cycle 5, 2769–2777 (2006).

    Article  CAS  Google Scholar 

  19. Taatjes, D. J., Zuber, C. & Roth, J. The histochemistry and cell biology vade mecum: a review of 2005–2006. Histochem. Cell Biol. 126, 743–788 (2006).

    Article  CAS  Google Scholar 

  20. Adams, C. L., Grierson, A. M., Mowat, A. M., Harnett, M. M. & Garside, P. Differences in the kinetics, amplitude, and localization of ERK activation in anergy and priming revealed at the level of individual primary T cells by laser scanning cytometry. J. Immunol. Methods 173, 1579–1586 (2004).

    Article  CAS  Google Scholar 

  21. Marshall, F. A., Grierson, A. M., Garside, P., Harnett, W. & Harnett, M. M. ES-62, an immunomodulator secreted by filarial nematodes, suppresses clonal expansion and modifies effector function of heterologous antigen-specific T cells in vivo. J. Immunol. 175, 5817–5826 (2005).

    Article  CAS  Google Scholar 

  22. Smith, K. M., Brewer, J. M., Rush, C. M., Riley, J. & Garside, P. In vivo generated Th1 cells can migrate to B cell follicles to support B cell responses. J. Immunol. 173, 1640–1646 (2004).

    Article  CAS  Google Scholar 

  23. Taatjes, D. J. et al. Laser-based microscopic approaches: application to cell signaling in environmental lung disease. Biotechniques 31, 880–882, 884, 886–888, 890, 892–894 (2001).

    Article  CAS  Google Scholar 

  24. Garside, P. E. et al. Visualization of specific B and T lymphocyte interactions in the lymph node. Science 281, 96–99 (1998).

    Article  CAS  Google Scholar 

  25. Pape, K. A. et al. Use of adoptive transfer of T-cell antigen-receptor-transgenic T cell for the study of T-cell activation in vivo. Immunol. Rev. 156, 67–78 (1997).

    Article  CAS  Google Scholar 

  26. Croxford, J. L., Miyake, S., Huang, Y. Y., Shimamura, M. & Yamamura, T. Invariant Vα19i T cells regulate autoimmune inflammation. Nature Immunol. 7, 987–994 (2006).

    Article  CAS  Google Scholar 

  27. Jarman, E. R., Tan, K. A. & Lamb, J. R. Transgenic mice expressing the T cell antigen receptor specific for an immunodominant epitope of a major allergen of house dust mite develop an asthmatic phenotype on exposure of the airways to allergen. Clin. Exp. Allergy 35, 960–969 (2005).

    Article  CAS  Google Scholar 

  28. Maffia, P. et al. Inducing experimental arthritis and breaking self-tolerance to joint-specific antigens with trackable, ovalbumin-specific T cells. J. Immunol. 173, 151–156 (2004).

    Article  CAS  Google Scholar 

  29. Osman, G. E. et al. Expression of a type II collagen-specific TCR transgene accelerates the onset of arthritis in mice. Int. Immunol. 10, 1613–1622 (1998).

    Article  CAS  Google Scholar 

  30. Bettelli, E., Baeten, D., Jager, A., Sobel, R. A. & Kuchroo, V. K. Myelin oligodendrocyte glycoprotein-specific T and B cells cooperate to induce a Devic-like disease in mice. J. Clin. Invest. 116, 2393–2402 (2006).

    Article  CAS  Google Scholar 

  31. Amend, B. et al. Induction of autoimmunity by expansion of autoreactive CD4+CD62Llow cells in vivo. J. Immunol. 177, 4384–4390 (2006).

    Article  CAS  Google Scholar 

  32. Huang, J. C., Vestberg, M., Minguela, A., Holmdahl, R. & Ward, E. S. Analysis of autoreactive T cells associated with murine collagen-induced arthritis using peptide-MHC multimers. Int. Immunol. 16, 283–293 (2004).

    Article  CAS  Google Scholar 

  33. Korn, T. et al. Myelin-specific regulatory T cells accumulate in the CNS but fail to control autoimmune inflammation. Nature Med. 13, 423–431 (2007).

    Article  CAS  Google Scholar 

  34. Fang, W. et al. Self-reactive B lymphocytes overexpressing Bcl-xL escape negative selection and are tolerized by clonal anergy and receptor editing. Immunity 9, 35–45 (1998).

    Article  CAS  Google Scholar 

  35. Krutzik, P. O. & Nolan, G. P. Fluorescent cell barcoding in flow cytometry allows high-throughput drug screening and signaling profiling. Nature Methods 3, 361–368 (2006).

    Article  CAS  Google Scholar 

  36. Wilson, E. H. et al. Hyporesponsiveness of murine B lymphocytes exposed to the filarial nematode secreted product ES-62 in vivo. Immunology 109, 238–245 (2003).

    Article  CAS  Google Scholar 

  37. Parsons, C. H. et al. KSHV targets multiple leukocyte lineages during long-term productive infection in NOD/SCID mice. J. Clin. Invest. 116, 1963–1973 (2006).

    Article  CAS  Google Scholar 

  38. Fanning, S. L. et al. Receptor cross-linking on human plasmacytoid dendritic cells leads to the regulation of IFN-α production. J. Immunol. 177, 5829–5839 (2006).

    Article  CAS  Google Scholar 

  39. Arechiga, A. F. et al. Cutting edge: FADD is not required for antigen receptor-mediated NF-κB activation. J. Immunol. 175, 7800–7804 (2005).

    Article  CAS  Google Scholar 

  40. Perfetto, S. P., Chattopadhyay, P. K. & Roederer, M. Seventeen-colour flow cytometry: unravelling the immune system. Nature Rev. Immunol. 4, 648–655 (2004).

    Article  CAS  Google Scholar 

  41. Schubert, W. A three-symbol code for organized proteomes based on cyclical imaging of protein locations. Cytometry A 71, 352–360 (2007).

    Article  Google Scholar 

  42. Butt, O. I., Krishnan, P., Kulkarni, S. S., Moldovan, L. & Moldovan, N. I. Quantification and functional analysis of chemotaxis by laser scanning cytometry. Cytometry A 64, 10–15 (2005).

    Article  Google Scholar 

  43. Doyle, S. E. et al. Toll-like receptors induce a phagocytic gene program through p38. J. Exp. Med. 199, 81–90 (2004).

    Article  CAS  Google Scholar 

  44. Koo, M. K., Oh, C. H., Holme, A. L. & Pervaiz, S. Simultaneous analysis of steady-state intracellular pH and cell morphology by automated laser scanning cytometry. Cytometry A 71, 87–93 (2007).

    Article  Google Scholar 

  45. Mital, J., Schwarz, J., Taatjes, D. J. & Ward, G. E. Laser scanning cytometer-based assays for measuring host cell attachment and invasion by the human pathogen Toxoplasma gondii. Cytometry A 69, 13–19 (2006).

    Article  Google Scholar 

  46. Hanania, E. G. et al. Automated in situ measurement of cell-specific antibody secretion and laser-mediated purification for rapid cloning of highly-secreting producers. Biotechnol. Bioeng. 91, 872–876 (2005).

    Article  CAS  Google Scholar 

  47. Szaniszlo, P. et al. Scanning cytometry with a LEAP: laser-enabled analysis and processing of live cells in situ. Cytometry A 69, 641–651 (2006).

    Article  Google Scholar 

  48. Ecker, R. C. & Tarnok, A. Cytomics goes 3D: toward tissomics. Cytometry A 65, 1–3 (2005).

    Article  Google Scholar 

  49. Mosch, B., Mittag, A., Lenz, D., Arendt, T. & Tarnok, A. Laser scanning cytometry in human brain slices. Cytometry A 69, 135–138 (2006).

    Article  Google Scholar 

  50. Mosch, B. et al. Aneuploidy and DNA replication in the normal human brain and Alzheimer's disease. J. Neurosci. 27, 6859–6867 (2007).

    Article  CAS  Google Scholar 

  51. Jaiswal, J. K., Mattoussi, H., Mauro, J. M. & Simon, S. M. Long-term multiple color imaging of live cells using quantum dot bioconjugates. Nature Biotechnol. 21, 47–51 (2003).

    Article  CAS  Google Scholar 

Download references

Acknowledgements

I would like to thank A. Morton for generating the cellular and tissue images used in this article and the Medical Research Council for funding this research. I would also like to thank W. Harnett for constructive discussion relating to the manuscript.

Author information

Authors and Affiliations

  1. Margaret M. Harnett is at the Division of Immunology, Infection and Inflammation, Glasgow Biomedical Research Centre, University of Glasgow, G12 8TA, UK. M.Harnett@bio.gla.ac.uk,

    Margaret M. Harnett

Authors
  1. Margaret M. Harnett
    View author publications

    You can also search for this author in PubMed Google Scholar

Ethics declarations

Competing interests

The author declares no competing financial interests.

Supplementary information

Supplementary information S1 (table)

Comparison of applications and properties of LSC versus FCM and FIA (PDF 230 kb)

Related links

Related links

FURTHER INFORMATION

Margaret M. Harnett's homepage

Compucyte corporation

Imagestream cytometer

Olympus

Glossary

Background contour

The contour that is set on an unstained region to calculate the background fluorescence so that it can be subtracted from the real signal.

Collimated laser beam

Light that is collimated has parallel rays. A laser beam on its formation is almost collimated but its beam radius always tends to increase with the distance from the laser's source. A collimated laser beam is one which is optimized to have an even lower light divergence such that the beam radius does not change significantly over the propagation distance. The use of such laser beams in laser scanning cytometry allows the analysis of depths of field of typically 20–30 μm.

Differential photobleaching

Differential photostability of dyes of similar emission spectra can be exploited to generate virtual colours. Therefore, in the first scan, photostable (for example, Alexa 532) and conventional (for example, phycoerythrin) stains on different antigens cannot be distinguished, but, following photobleaching, two populations appear that can be identified by reference to pre- and post-bleaching analysis.

Holmes effect

The cell overlap that occurs because of the inability to generate tissue sections of infinite thinness. This overlap results in inaccuracies in detecting frequencies and spatial characteristics of individual cell populations.

Integration contour

The contour defined by the edge of the cell, which can be set either by an optimal number of pixels representing the cell size and/or by cell-surface staining.

Iterative staining

Sequential staining using different antibodies but with the same fluorochrome allows identical colours to appear as distinct parameters (that is 'virtual colours') when newly labelled cells appear during sequential stains. During iterative staining, each cell serves as its own unstained control and a bleaching step before each re-staining can be included to improve sensitivity. Moreover, the use of the same fluorochrome reduces the need for compensation.

Multiple thresholding

The scanning of tissue at a single threshold value of, for example, nuclear staining may not detect all relevant cells, whereas repeated analysis at different threshold levels compensates for inaccuracies in detecting cells of different diameters and cell density across the section. Merging of the multiple threshold scan files by laser scanning cytometry software allows all cells recognized at the same x–y-coordinates to be analysed as a single cell, thereby providing a more accurate analysis.

Peripheral contours

The contours that are set 1 pixel out from the threshold contour (for example, the nucleus) and 1 pixel in from the integration contour (for example, the edge of cell) to allow analysis of staining within this region.

Phantom contours

These comprise a lattice of contours over the tissue which recognizes pixels within the contours as cells, thereby generating information on the mean fluorescence intensity of such staining within the tissue rather than on an individual cell basis.

Photoactivation

Quantum dot fluorescence intensity can be increased by laser exposure allowing generation of new virtual colours by analogous analysis to that used for differential photobleaching.

Photodestruction of tandem dyes

Virtual colours can be generated by laser-induced photodestruction of the fluorescence resonance energy transfer (FRET) between the donor and acceptor fluorochromes of tandem dyes.

Quantum dots

Semiconductor nanocrystals that have stable, discrete quantized energy spectra and fluoresce following exposure to light. They can therefore be used as fluorochrome tags on molecules such as antibodies to visualize molecular and cellular interactions.

Threshold contour

The contour that is set to detect individual cells typically on the basis of their nuclear DNA staining.

Tissue map

A map generated from the plotting of the precise x–y-coordinates and the emitted fluorescence obtained by laser scanning cytometry of each detected cell in a tissue sample. Tissue maps allow the visualization and quantitative analysis of the molecular and cellular interactions that occur within tissues.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Harnett, M. Laser scanning cytometry: understanding the immune system in situ. Nat Rev Immunol 7, 897–904 (2007). https://doi.org/10.1038/nri2188

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1038/nri2188

This article is cited by

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing