Hyperspectral Cytometry

  • Gérald Grégori
  • Bartek Rajwa
  • Valery Patsekin
  • James Jones
  • Motohiro Furuki
  • Masanobu Yamamoto
  • J. Paul RobinsonEmail author
Part of the Current Topics in Microbiology and Immunology book series (CT MICROBIOLOGY, volume 377)


Hyperspectral cytometry is an emerging technology for single-cell analysis that combines ultrafast optical spectroscopy and flow cytometry. Spectral cytometry systems utilize diffraction gratings or prism-based monochromators to disperse fluorescence signals from multiple labels (organic dyes, nanoparticles, or fluorescent proteins) present in each analyzed bioparticle onto linear detector arrays such as multianode photomultipliers or charge-coupled device sensors. The resultant data, consisting of a series of characterizing every analyzed cell, are not compensated by employing the traditional cytometry approach, but rather are spectrally unmixed utilizing algorithms such as constrained Poisson regression or non-negative matrix factorization. Although implementations of spectral cytometry were envisioned as early as the 1980s, only recently has the development of highly sensitive photomultiplier tube arrays led to design and construction of functional prototypes and subsequently to introduction of commercially available systems. This chapter summarizes the historical efforts and work in the field of spectral cytometry performed at Purdue University Cytometry Laboratories and describes the technology developed by Sony Corporation that resulted in release of the first commercial spectral cytometry system—the Sony SP6800. A brief introduction to spectral data analysis is also provided, with emphasis on the differences between traditional polychromatic and spectral cytometry approaches.


Spectral Unmixing Spectral Data Analysis Flow Cytometry System Fluorescence Emission Signal Unmixing Model 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. Asbury CL, Esposito R, Farmer C, van den Engh G (1996) Fluorescence spectra of DNA dyes measured in a flow cytometer. Cytometry 24:234–242. doi: 10.1002/(SICI)1097-0320(19960701)24:3<234:AID-CYTO6>3.0.CO;2-H PubMedCrossRefGoogle Scholar
  2. Bagwell CB, Adams EG (1993) Fluorescence spectral overlap compensation for any number of flow cytometry parameters. Ann N Y Acad Sci 677:167–184. doi: 10.1111/j.1749-6632.1993.tb38775.x PubMedCrossRefGoogle Scholar
  3. Bernstein HS, Hyun WC (2012) Strategies for enrichment and selection of stem cell-derived tissue precursors. Stem Cell Res Ther 3:17. doi: 10.1186/scrt108 PubMedCentralPubMedCrossRefGoogle Scholar
  4. Bilgin CC, Rittscher J, Filkins R, Can A (2012) Digitally adjusting chromogenic dye proportions in brightfield microscopy images. J Microsc 245:319–330. doi: 10.1111/j.1365-2818.2011.03579.x PubMedCrossRefGoogle Scholar
  5. Brown LO, Doorn SK (2008a) A controlled and reproducible pathway to dye-tagged, encapsulated silver nanoparticles as substrates for SERS multiplexing. Langmuir ACS J Surf Colloids 24:2277–2280. doi: 10.1021/la703853e CrossRefGoogle Scholar
  6. Brown LO, Doorn SK (2008b) Optimization of the preparation of glass-coated, dye-tagged metal nanoparticles as SERS substrates. Langmuir ACS J Surf Colloids 24:2178–2185. doi: 10.1021/la703218f CrossRefGoogle Scholar
  7. Buican TN (1990) Real-time fourier transform spectrometry for fluorescence imaging and flow cytometry. In: Proceedings of SPIE 1205. SPIE, Los Angeles, CA, pp 126–133Google Scholar
  8. Garini Y, Young IT, McNamara G (2006) Spectral imaging: principles and applications. Cytometry A 69A:735–747. doi: 10.1002/cyto.a.20311 CrossRefGoogle Scholar
  9. Gauci MR, Vesey G, Narai J et al (1996) Observation of single-cell fluorescence spectra in laser flow cytometry. Cytometry 25:388–393. doi: 10.1002/(SICI)1097-0320(19961201)25:4<388:AID-CYTO11>3.0.CO;2-R PubMedCrossRefGoogle Scholar
  10. Goddard G, Martin JC, Naivar M et al (2006) Single particle high resolution spectral analysis flow cytometry. Cytometry A 69A:842–851. doi: 10.1002/cyto.a.20320 CrossRefGoogle Scholar
  11. Grégori G, Patsekin V, Rajwa B et al (2012) Hyperspectral cytometry at the single-cell level using a 32-channel photodetector. Cytometry A 81A:35–44. doi: 10.1002/cyto.a.21120 CrossRefGoogle Scholar
  12. Haraguchi T, Shimi T, Koujin T et al (2002) Spectral imaging fluorescence microscopy. Genes Cells Devoted Mol Cell Mech 7:881–887CrossRefGoogle Scholar
  13. Johnson PE, Lund ML, Shorthill RW et al (2001) Real time biodetection of individual pathogenic microorganisms in food and water. Biomed Sci Instrum 37:191–196PubMedGoogle Scholar
  14. Keshava N, Mustard JF (2002) Spectral unmixing. Sigl Process Mag IEEE 19:44–57. doi: 10.1109/79.974727 CrossRefGoogle Scholar
  15. Lee DD, Seung HS (1999) Learning the parts of objects by non-negative matrix factorization. Nature 401:788–791. doi: 10.1038/44565 PubMedCrossRefGoogle Scholar
  16. Loken MR, Parks DR, Herzenberg LA (1977) Two-color immunofluorescence using a fluorescence-activated cell sorter. J Histochem Cytochem 25:899–907. doi: 10.1177/25.7.330738 PubMedCrossRefGoogle Scholar
  17. Nielsen AA (2001) Spectral mixture analysis: linear and semi-parametric full and iterated partial unmixing in multi- and hyperspectral image data. J Math Imaging Vis 15:17–37. doi: 10.1023/A:1011269530293 CrossRefGoogle Scholar
  18. Nolan JP, Condello D, Duggan E et al (2013) Visible and near infrared fluorescence spectral flow cytometry. Cytometry A 83A:253–264. doi: 10.1002/cyto.a.22241 CrossRefGoogle Scholar
  19. Novo D, Grégori G, Rajwa B (2013) Generalized unmixing model for multispectral flow cytometry utilizing nonsquare compensation matrices. Cytom Part J Int Soc Anal Cytol 83:508–520. doi: 10.1002/cyto.a.22272 CrossRefGoogle Scholar
  20. Pauca VP, Piper J, Plemmons RJ (2006) Nonnegative matrix factorization for spectral data analysis. Linear Algebra Its Appl 416:29–47. doi: 10.1016/j.laa.2005.06.025 CrossRefGoogle Scholar
  21. Perfetto SP, Chattopadhyay PK, Roederer M (2004) Seventeen-colour flow cytometry: unravelling the immune system. Nat Rev Immunol 4:648–655. doi: 10.1038/nri1416 PubMedCrossRefGoogle Scholar
  22. Rabinovich A, Agarwal S, Laris CA, et al (2003) Unsupervised color decomposition of histologically stained tissue samples. Adv Neural Inf Process Syst 16:667–674Google Scholar
  23. Robinson JP (2004) Multispectral cytometry: the next generation. Biophotonics Int 11:36–40Google Scholar
  24. Robinson JP, Rajwa B, Gregori G et al (2005) Multispectral cytometry of single bio-particles using a 32-channel detector. Proc SPIE 5692:359–365CrossRefGoogle Scholar
  25. Robinson JP, Rajwa B, Grégori G, et al (2007) Multi-spectral detector and analysis system. US Patent 7280204 B2Google Scholar
  26. Roederer M (2001) Spectral compensation for flow cytometry: Visualization artifacts, limitations, and caveats. Cytometry 45:194–205PubMedCrossRefGoogle Scholar
  27. Roederer M, De Rosa S, Gerstein R et al (1997) 8 color, 10-parameter flow cytometry to elucidate complex leukocyte heterogeneity. Cytometry 29:328–339PubMedCrossRefGoogle Scholar
  28. De Rosa SC, Herzenberg LA, Herzenberg LA, Roederer M (2001) 11-color, 13-parameter flow cytometry: identification of human naive T cells by phenotype, function, and T-cell receptor diversity. Nat Med 7:245–248. doi: 10.1038/84701 PubMedCrossRefGoogle Scholar
  29. Settle JJ, Drake NA (1993) Linear mixing and the estimation of ground cover proportions. Int J Remote Sens 14:1159. doi: 10.1080/01431169308904402 CrossRefGoogle Scholar
  30. Shapiro HM (2003) Practical Flow Cytometry, 4th edn. Wiley-Liss, Hoboken, NJ, USACrossRefGoogle Scholar
  31. Steen HB (1986) Simultaneous separate detection of low angle and large angle light scattering in an arc lamp-based flow cytometer. Cytometry 7:445–449. doi: 10.1002/cyto.990070509 PubMedCrossRefGoogle Scholar
  32. Stokke T, Steen HB (1986) Fluorescence spectra of Hoechst 33258 bound to chromatin. Biochim Biophys Acta BBA - Gene Struct Expr 868:17–23. doi: 10.1016/0167-4781(86)90081-3 CrossRefGoogle Scholar
  33. Wade CG, Rhyne RH Jr, Woodruff WH et al (1979) Spectra of cells in flow cytometry using a vidicon detector. J Histochem Cytochem Off J Histochem Soc 27:1049–1052CrossRefGoogle Scholar
  34. Wang J-CE, Kobie JJ, Zhang L et al (2009) An 11-color flow cytometric assay for identifying, phenotyping, and assessing endocytic ability of peripheral blood dendritic cell subsets in a single platform. J Immunol Methods 341:106–116. doi: 10.1016/j.jim.2008.11.002 PubMedCentralPubMedCrossRefGoogle Scholar
  35. Watson DA, Brown LO, Gaskill DF et al (2008) A flow cytometer for the measurement of Raman spectra. Cytometry A 73:119–128. doi: 10.1002/cyto.a.20520 PubMedCrossRefGoogle Scholar
  36. Zimmermann T (2005) Spectral imaging and linear unmixing in light microscopy. Microsc. Tech. Springer Verlag, Berlin/Heidelberg, pp 245–265Google Scholar
  37. Zimmermann T, Rietdorf J, Girod A et al (2002) Spectral imaging and linear un-mixing enables improved FRET efficiency with a novel GFP2-YFP FRET pair. FEBS Lett 531:245–249PubMedCrossRefGoogle Scholar
  38. Zimmermann T, Rietdorf J, Pepperkok R (2003) Spectral imaging and its applications in live cell microscopy. FEBS Lett 546:87–92. doi: 10.1016/S0014-5793(03)00521-0 PubMedCrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Gérald Grégori
    • 1
    • 4
  • Bartek Rajwa
    • 3
  • Valery Patsekin
    • 1
  • James Jones
    • 2
  • Motohiro Furuki
    • 5
  • Masanobu Yamamoto
    • 6
  • J. Paul Robinson
    • 1
    • 2
    • 7
    Email author
  1. 1.Department of Basic Medical SciencesCollege of Veterinary Medicine, Purdue UniversityWest LafayetteUSA
  2. 2.Weldon School of Biomedical EngineeringPurdue UniversityWest LafayetteUSA
  3. 3.Bindley Bioscience CenterPurdue UniversityWest LafayetteUSA
  4. 4.Mediterranean Institute of OceanographyAix-Marseille Université, Université du Sud-Toulon Var, CNRS, IRDMarseilleFrance
  5. 5.Life Science Business DivMBU, Sony CorporationTokyoJapan
  6. 6.Phototek Laboratory IncYokohamaJapan
  7. 7.Purdue University Cytometry LaboratoriesWest LafayetteUSA

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