Quality assurance for polychromatic flow cytometry

Abstract

This protocol outlines a three-part quality assurance program to optimize, calibrate and monitor flow cytometers used to measure cells labeled with five or more fluorochromes (a practice known as polychromatic flow cytometry). The initial steps of this program (system optimization) ensure that the instrument's lasers, mirrors and filters are optimally configured for the generation and transmission of multiple fluorescent signals. To determine the sensitivity and dynamic range of each fluorescence detector, the system is then calibrated by measuring fluorescence over a range of photomultiplier tube (PMT) voltages by determining the PMT voltage range and linearity (Steps 2–10) and validating the PMT voltage (Steps 11–17). Finally, to ensure consistent performance, we provide procedures to monitor the precision, accuracy and sensitivity of fluorescence measurements over time. All three aspects of this program should be performed upon installation, or whenever changes occur along the flow cytometer's optical path. However, only a few of these procedures need to be carried out on a routine basis.

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Figure 1: Quality assurance particles.
Figure 2: Voltage series applied to eight-peak Rainbow beads and unlabeled CompBeads.
Figure 3: Determining the linear PMT voltage range using a plot of CV, PMT linearity and ratio.
Figure 4: Sample graphic illustrating CV, PMT linearity and signal-to-background ratio.
Figure 5: Compensation profiles of a selected group of detectors.
Figure 6: Time plots of accuracy, precision and sensitivity.

References

  1. 1

    De Rosa, S.C., Brenchley, J.M. & Roederer, M. Beyond six colors: a new era in flow cytometry. Nat. Med. 9, 112–117 (2003).

    CAS  Article  Google Scholar 

  2. 2

    De Rosa, S.C., Herzenberg, L.A. & Roederer, M. 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 (2001).

    CAS  Article  Google Scholar 

  3. 3

    Delobel, P. et al. Persistence of distinct HIV-1 populations in blood monocytes and naive and memory CD4 T cells during prolonged suppressive HAART. AIDS 19, 1739–1750 (2005).

    Article  Google Scholar 

  4. 4

    Brenchley, J.M. et al. T-cell subsets that harbor human immunodeficiency virus (HIV) in vivo: implications for HIV pathogenesis. J. Virol. 78, 1160–1168 (2004).

    CAS  Article  Google Scholar 

  5. 5

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

    CAS  Article  Google Scholar 

  6. 6

    Chattopadhyay, P.K. & Roederer, M. Immunophenotyping of T cell subpopulations in HIV disease. in Current Protocols in Immunology (eds. Coligan, J.E., Bierer, B., Margulies, D.H., Shevach, E.M. & Strober, W.) 12.12.1–12.12.15 (John Wiley & Sons, Hoboken, New Jersey, USA, 2005).

    Google Scholar 

  7. 7

    Roederer, M. Multiparameter FACS analysis. in Current Protocols in Immunology (eds. Coligan, J.E., Bierer, B., Margulies, D.H., Shevach, E.M. & Strober, W.) 5.8.1–5.8.10 (John Wiley & Sons, New York, 2002).

    Google Scholar 

  8. 8

    Pattanapanyasat, K. & Thakar, M.R. CD4+ T cell count as a tool to monitor HIV progression & anti-retroviral therapy. Indian J. Med. Res. 121, 539–549 (2005).

    PubMed  Google Scholar 

  9. 9

    De Rosa, S.C. et al. Vaccination in humans generates broad T cell cytokine responses. J. Immunol. 173, 5372–5380 (2004).

    CAS  Article  Google Scholar 

  10. 10

    Brown, A.E. et al. Clinical prognosis of patients with early-stage human immunodeficiency virus (HIV) disease: contribution of HIV-1 RNA and T lymphocyte subset quantitation. Mil. Med. 166, 571–576 (2001).

    CAS  Article  Google Scholar 

  11. 11

    Rosner, E. et al. Assessment of the impact of a CD4+ T-cell testing laboratory improvement program. Arch. Pathol. Lab. Med. 122, 512–519 (1998).

    CAS  PubMed  Google Scholar 

  12. 12

    Bergeron, M. et al. Impact of unified procedures as implemented in the Canadian Quality Assurance Program for T lymphocyte subset enumeration. Participating Flow Cytometry Laboratories of the Canadian Clinical Trials Network for HIV/AIDS Therapies. Cytometry 33, 146–155 (1998).

    CAS  Article  Google Scholar 

  13. 13

    Schenker, E.L. et al. Evaluation of a dual-color flow cytometry immunophenotyping panel in a multicenter quality assurance program. Cytometry 14, 307–317 (1993).

    CAS  Article  Google Scholar 

  14. 14

    Liu, C.M., Muirhead, K.A., George, S.P. & Landay, A.L. Flow cytometric monitoring of human immunodeficiency virus-infected patients. Simultaneous enumeration of five lymphocyte subsets. Am. J. Clin. Pathol. 92, 721–728 (1989).

    CAS  Article  Google Scholar 

  15. 15

    Horan, P.K., Muirhead, K.A. & Slezak, S.E. Standards and controls in flow cytometry. In Flow Cytometry and Sorting 2nd edn. (eds. Melamed, M. et al.) 397–414 (Wiley-Liss, New York, 1990).

    Google Scholar 

  16. 16

    Shapiro, H.M. Practical Flow Cytometry (Wiley-Liss, Hoboken, New Jersey, USA, 2003).

    Google Scholar 

  17. 17

    Schwartz, A., Marti, G.E., Poon, R., Gratama, J.W. & Fernandez-Repollet, E. Standardizing flow cytometry: a classification system of fluorescence standards used for flow cytometry. Cytometry 33, 106–114 (1998).

    CAS  Article  Google Scholar 

  18. 18

    Schwartz, A., Fernandez Repollet, E., Vogt, R. & Gratama, J.W. Standardizing flow cytometry: construction of a standardized fluorescence calibration plot using matching spectral calibrators. Cytometry 26, 22–31 (1996).

    CAS  Article  Google Scholar 

  19. 19

    Schwartz, A. et al. Formalization of the MESF unit of fluorescence intensity. Cytometry B Clin. Cytom. 57, 1–6 (2004).

    Article  Google Scholar 

  20. 20

    Zenger, V.E., Vogt, R., Mandy, F., Schwartz, A. & Marti, G.E. Quantitative flow cytometry: inter-laboratory variation. Cytometry 33, 138–145 (1998).

    CAS  Article  Google Scholar 

  21. 21

    Marti, G.E. et al. (eds.) Fluorescence calibration and quantitation measurement of fluorescence intensity: approved guideline. (Clinical Laboratory Standards Institute, National Committee for Clinical Laboratory Standards, Wayne, Pennsylvania, USA, 2004).

  22. 22

    Chase, E.S. & Hoffman, R.A. Resolution of dimly fluorescent particles: a practical measure of fluorescence sensitivity. Cytometry 33, 267–279 (1998).

    CAS  Article  Google Scholar 

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Acknowledgements

We would like to thank D. Parks (Stanford University School of Medicine) for his expert advice and knowledge and J. Trotter (BD Biosciences) for his conceptual work in quality controls and technical support.

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Correspondence to Stephen P Perfetto.

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Perfetto, S., Ambrozak, D., Nguyen, R. et al. Quality assurance for polychromatic flow cytometry. Nat Protoc 1, 1522–1530 (2006). https://doi.org/10.1038/nprot.2006.250

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