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Measurement of proliferation and disappearance of rapid turnover cell populations in human studies using deuterium-labeled glucose

Nature Protocols volume 4, pages 1313–1327 (2009)Cite this article

Abstract

Cell proliferation may be measured in vivo by quantifying DNA synthesis with isotopically labeled deoxyribonucleotide precursors. Deuterium-labeled glucose is one such precursor which, because it achieves high levels of enrichment for a short period, is well suited to the study of rapidly dividing cells, in contrast to the longer term labeling achieved with heavy water (2H2O). As deuterium is non-radioactive and glucose can be readily administered, this approach is suitable for clinical studies. It has been widely applied to investigate human lymphocyte proliferation, but solid tissue samples may also be analyzed. Rate, duration and route (intravenous or oral) of [6,6-2H2]-glucose administration should be adapted to the target cell of interest. For lymphocytes, cell separation is best achieved by fluorescence activated cell sorting (FACS), although magnetic bead separation is an alternative. DNA is then extracted, hydrolyzed enzymatically and analyzed by gas chromatography mass spectrometry (GC/MS). Appropriate mathematical modeling is critical to interpretation. Typical time requirements are as follows: labeling, 10–24 h; sampling, ∼3 weeks; DNA extraction/derivatization, 2–3 d; and GC/MS analysis, ∼2 d.

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Figure 1: Theoretical basis of glucose labeling of DNA synthesis.
Figure 2: Model for interpretation of lymphocyte enrichment.
Figure 3: General schematic of intravenous protocol for the analysis of lymphocyte kinetics.
Figure 4: Example of flow cytometry sorting plots.
Figure 5: Glucose enrichment curves.
Figure 6: Lymphocyte labeling curves.
Figure 7: Use of labeled glucose to measure cell proliferation in solid tissues.
Figure 8: Length of labeling period and interpretation of lymphocyte kinetics.
Figure 9: Models of lymphocyte heterogeneity.

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References

  1. Macallan, D.C. et al. Measurement of cell proliferation by labeling of DNA with stable isotope-labeled glucose: studies in vitro, in animals and in humans. Proc. Natl. Acad. Sci. USA 95, 708–713 (1998).

    Article  CAS  Google Scholar 

  2. Hellerstein, M.K. Measurement of T-cell kinetics: recent methodologic advances. Immunol. Today 20, 438–441 (1999).

    Article  CAS  Google Scholar 

  3. Busch, R., Neese, R.A., Awada, M., Hayes, G.M. & Hellerstein, M.K. Measurement of cell proliferation by heavy water labeling. Nat. Protoc. 2, 3045–3057 (2007).

    Article  CAS  Google Scholar 

  4. Neese, R.A. et al. Measurement in vivo of proliferation rates of slow turnover cells by 2H2O labeling of the deoxyribose moiety of DNA. Proc. Natl. Acad. Sci. USA 99, 15345–15350 (2002).

    Article  CAS  Google Scholar 

  5. Macallan, D.C. et al. Measurement and modeling of human T cell kinetics. Eur. J. Immunol. 33, 2316–2326 (2003).

    Article  CAS  Google Scholar 

  6. Asquith, B., Debacq, C., Macallan, D.C., Willems, L. & Bangham, C. Lymphocyte kinetics: the interpretation of labelling data. Trends Immunol. 23, 596–601 (2002).

    Article  CAS  Google Scholar 

  7. Tough, D.F. & Sprent, J. Turnover of naive- and memory-phenotype T cells. J. Exp. Med. 179, 1127–1135 (1994).

    Article  CAS  Google Scholar 

  8. Kovacs, J.A. et al. Identification of dynamically distinct subpopulations of T lymphocytes that are differentially affected by HIV. J. Exp. Med. 194, 1731–1741 (2001).

    Article  CAS  Google Scholar 

  9. Schwarting, R., Gerdes, J., Niehus, J., Jaeschke, L. & Stein, H. Determination of the growth fraction in cell suspensions by flow cytometry using the monoclonal antibody Ki-67. J. Immunol. Methods 90, 65–70 (1986).

    Article  CAS  Google Scholar 

  10. Quah, B.J., Warren, H.S. & Parish, C.R. Monitoring lymphocyte proliferation in vitro and in vivo with the intracellular fluorescent dye carboxyfluorescein diacetate succinimidyl ester. Nat. Protoc. 2, 2049–2056 (2007).

    Article  CAS  Google Scholar 

  11. Hawkins, E.D. et al. Measuring lymphocyte proliferation, survival and differentiation using CFSE time-series data. Nat. Protoc. 2, 2057–2067 (2007).

    Article  CAS  Google Scholar 

  12. Lyons, A.B. Analysing cell division in vivo and in vitro using flow cytometric measurement of CFSE dye dilution. J. Immunol. Methods 243, 147–154 (2000).

    Article  CAS  Google Scholar 

  13. Michie, C.A., McLean, A., Alcock, C. & Beverley, P.C. Lifespan of human lymphocyte subsets defined by CD45 isoforms. Nature 360, 264–265 (1992).

    Article  CAS  Google Scholar 

  14. Ho, D.D. et al. Rapid turnover of plasma virions and CD4 lymphocytes in HIV-1 infection. Nature 373, 123–126 (1995).

    Article  CAS  Google Scholar 

  15. Wolfe, R.R. & Chinkes, D.L. Calculation of substrate kinetics: single pool model. in Isotope Tracers in Metabolic Research (eds. Wolfe, R.R. & Chinkes, D.L.) 21–50 (John Wiley & Sons, Hoboken, New Jersey, 2005).

  16. Ladell, K. et al. Central memory CD8(+) T cells appear to have a shorter lifespan and reduced abundance as a function of HIV disease progression. J. Immunol. 180, 7907–7918 (2008).

    Article  CAS  Google Scholar 

  17. Vrisekoop, N. et al. Sparse production but preferential incorporation of recently produced naive T cells in the human peripheral pool. Proc. Natl. Acad. Sci. USA 105, 6115–6120 (2008).

    Article  CAS  Google Scholar 

  18. Vukmanovic-Stejic, M. et al. Human CD4+ CD25hi Foxp3+ regulatory T cells are derived by rapid turnover of memory populations in vivo . J. Clin. Invest. 116, 2423–2433 (2006).

    Article  CAS  Google Scholar 

  19. Macallan, D.C. et al. Rapid turnover of T cells in acute infectious mononucleosis. Eur. J. Immunol. 33, 2655–2665 (2003).

    Article  CAS  Google Scholar 

  20. Macallan, D.C. et al. Rapid turnover of effector-memory CD4(+) T cells in healthy humans. J. Exp. Med. 200, 255–260 (2004).

    Article  CAS  Google Scholar 

  21. Wallace, D.L. et al. Direct measurement of T cell subset kinetics in vivo in elderly men and women. J. Immunol. 173, 1787–1794 (2004).

    Article  CAS  Google Scholar 

  22. Macallan, D.C. et al. B cell kinetics in humans: rapid turnover of peripheral blood memory cells. Blood 105, 3633–3640 (2005).

    Article  CAS  Google Scholar 

  23. Defoiche, J. et al. Reduction of B cell turnover in chronic lymphocytic leukaemia. Br. J. Haematol. 143, 240–247 (2008).

    Article  Google Scholar 

  24. Hellerstein, M. et al. Directly measured kinetics of circulating T lymphocytes in normal and HIV-1-infected humans. Nat. Med. 5, 83–89 (1999).

    Article  CAS  Google Scholar 

  25. Hellerstein, M.K. et al. Subpopulations of long-lived and short-lived T cells in advanced HIV-1 infection. J. Clin. Invest. 112, 956–966 (2003).

    Article  CAS  Google Scholar 

  26. McCune, J.M. et al. Factors influencing T-cell turnover in HIV-1-seropositive patients. J. Clin. Invest. 105, R1–R8 (2000).

    Article  CAS  Google Scholar 

  27. Kovacs, J.A. et al. Induction of prolonged survival of CD4+ T lymphocytes by intermittent IL-2 therapy in HIV-infected patients. J. Clin. Invest. 115, 2139–2148 (2005).

    Article  CAS  Google Scholar 

  28. Read, S.W. et al. CD4 T cell survival after intermittent Interleukin-2 therapy is predictive of an Increase in the CD4 T cell count of HIV-infected patients. J. Infect. Dis. 198, 843–850 (2008).

    Article  CAS  Google Scholar 

  29. Ghattas, H. et al. Measuring lymphocyte kinetics in tropical field settings. Trans. R. Soc. Trop. Med. Hyg. 99, 675–685 (2005).

    Article  Google Scholar 

  30. Ghattas, H. et al. Long-term effects of perinatal nutrition on T lymphocyte kinetics in young Gambian men. Am. J. Clin. Nutr. 85, 480–487 (2007).

    Article  CAS  Google Scholar 

  31. Reichard, P. Interactions between deoxyribonucleotide and DNA synthesis. Annu. Rev. Biochem. 57, 349–374 (1988).

    Article  CAS  Google Scholar 

  32. Cohen, A., Barankiewicz, J., Lederman, H.M. & Gelfand, E.W. Purine and pyrimidine metabolism in human T lymphocytes. Regulation of deoxyribonucleotide metabolism. J. Biol. Chem. 258, 12334–12340 (1983).

    CAS  PubMed  Google Scholar 

  33. Stevens, R.A. et al. General immunologic evaluation of patients with human immunodeficiency virus infection. in Manual of Molecular and Clinical Laboratory Immunology (eds. Detrick, B., Hamilton, R.G. & Folds, J.D.) 848–861 (ASM Press, Washington DC, 2006).

  34. Lawrence, C.W. & Braciale, T.J. Activation, differentiation, and migration of naive virus-specific CD8+ T cells during pulmonary influenza virus infection. J. Immunol. 173, 1209–1218 (2004).

    Article  CAS  Google Scholar 

  35. Okoye, A. et al. Progressive CD4+ central memory T cell decline results in CD4+ effector memory insufficiency and overt disease in chronic SIV infection. J. Exp. Med. 204, 2171–2185 (2007).

    Article  CAS  Google Scholar 

  36. Marshall, D.R. et al. Measuring the diaspora for virus-specific CD8+ T cells. Proc. Natl. Acad. Sci. USA 98, 6313–6318 (2001).

    Article  CAS  Google Scholar 

  37. Agrewala, J.N. et al. Unique ability of activated CD4+ T cells but not rested effectors to migrate to non-lymphoid sites in the absence of inflammation. J. Biol. Chem. 282, 6106–6115 (2007).

    Article  CAS  Google Scholar 

  38. Marzo, A.L., Yagita, H. & Lefrancois, L. Cutting edge: migration to nonlymphoid tissues results in functional conversion of central to effector memory CD8 T cells. J. Immunol. 179, 36–40 (2007).

    Article  CAS  Google Scholar 

  39. Berhanu, D., Mortari, F., De Rosa, S.C. & Roederer, M. Optimized lymphocyte isolation methods for analysis of chemokine receptor expression. J. Immunol. Methods 279, 199–207 (2003).

    Article  CAS  Google Scholar 

  40. Hodge, T.W., Sasso, D.R. & McDougal, J.S. Humans with OKT4-epitope deficiency have a single nucleotide base change in the CD4 gene, resulting in substitution of TRP240 for ARG240. Hum. Immunol. 30, 99–104 (1991).

    Article  CAS  Google Scholar 

  41. Tchilian, E.Z. & Beverley, P.C. Altered CD45 expression and disease. Trends Immunol. 27, 146–153 (2006).

    Article  CAS  Google Scholar 

  42. Neese, R.A. et al. Advances in the stable isotope-mass spectrometric measurement of DNA synthesis and cell proliferation. Anal. Biochem. 298, 189–195 (2001).

    Article  CAS  Google Scholar 

  43. Fox, S.D. et al. A comparison of microLC/electrospray ionization-MS and GC/MS for the measurement of stable isotope enrichment from a [2H2]-glucose metabolic probe in T-cell genomic DNA. Anal. Chem. 75, 6517–6522 (2003).

    Article  CAS  Google Scholar 

  44. Asquith, B. et al. In vivo T lymphocyte dynamics in humans and the impact of human T-lymphotropic virus 1 infection. Proc. Natl. Acad. Sci. USA 104, 8035–8040 (2007).

    Article  CAS  Google Scholar 

  45. Borghans, J.A. & De Boer, R.J. Quantification of T-cell dynamics: from telomeres to DNA labeling. Immunol. Rev. 216, 35–47 (2007).

    Article  Google Scholar 

  46. Hellerstein, M. HIV tropism and CD4+ T-cell depletion. Nat. Med. 8, 537–538 (2002).

    Article  CAS  Google Scholar 

  47. Ribeiro, R.M., Mohri, H., Ho, D.D. & Perelson, A.S. In vivo dynamics of T cell activation, proliferation, and death in HIV-1 infection: why are CD4+ but not CD8+ T cells depleted? Proc. Natl. Acad. Sci. USA 99, 15572–15577 (2002).

    Article  CAS  Google Scholar 

  48. Mohri, H. et al. Increased turnover of T lymphocytes in HIV-1 infection and its reduction by antiretroviral therapy. J. Exp. Med. 194, 1277–1287 (2001).

    Article  CAS  Google Scholar 

  49. Di, M.M. et al. Naive T-cell dynamics in human immunodeficiency virus type 1 infection: effects of highly active antiretroviral therapy provide insights into the mechanisms of naive T-cell depletion. J. Virol. 80, 2665–2674 (2006).

    Article  Google Scholar 

  50. Zhang, Y. et al. In vivo kinetics of human natural killer cells: the effects of ageing and acute and chronic viral infection. Immunology 121, 258–265 (2007).

    Article  CAS  Google Scholar 

  51. Chen, J.J. et al. CD4 lymphocytes in the blood of HIV(+) individuals migrate rapidly to lymph nodes and bone marrow: support for homing theory of CD4 cell depletion. J. Leukoc. Biol. 72, 271–278 (2002).

    CAS  PubMed  Google Scholar 

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Acknowledgements

We acknowledge financial support from the Medical Research Council (UK), the Wellcome Trust, Merck Serono and the Charitable Trustees of St. George's Hospital, London, during the execution of studies included in this report.

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Authors and Affiliations

  1. Centre for Infection, Cellular and Molecular Medicine, St. George's, University of London, London, UK

    Derek C Macallan, Yan Zhang, Hala Ghattas & Julien Defoiche

  2. Department of Immunology, Imperial College, London, UK

    Becca Asquith

  3. Edward Jenner Institute for Vaccine Research, Compton, Berks, UK

    Catherine de Lara & Peter C L Beverley

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  1. Derek C Macallan
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Contributions

All authors contributed to the development of the methodology and to the description of the protocol.

Corresponding author

Correspondence to Derek C Macallan.

Supplementary information

Supplementary Fig. 1: GC/MS chromatogram of the PFTA derivative of deoxyadenosine.

Deuterium enrichment is determined from the ratio of the M+2 ion (m/z 437, magenta curve) to the M+0 ion (m/z 437, black curve). The two peaks represent cis- and trans-isomers; the larger peak is used for analysis. (PDF 1183 kb)

Supplementary Fig. 2: Example of cell sorting protocol for CD4 and CD8 CD45-sorted “naïve” and “memory” populations using magnetic beads.

(1) Add CD8 multisort beads to peripheral blood lymphocytes (20 µl per 106 cells); incubate, 10°C, 20 min. (2) CD8+ cells bind to magnetic beads. (3) Wash cells with PBS/BSA/EDTA and pass through a mini-MACS magnet: Retain the CD8− cells which pass through the column for CD4 processing; CD8+ cells remain within the column/magnet. (4) Remove the column from the magnet and flush out retained (CD8+) cells. Repeat Steps 3–4 with a new column to increase purity. (5) Add Multisort release reagent to CD8+ cells from Step 4; incubate, 10°C, 15 min. (6) The release reagent cleaves the magnetic beads from the cells. (7) Pass CD8+ cells through a column to ensure removal of magnetic beads from the cell suspension. (8) Incubate CD8+ cells with CD45R0 beads, 10°C, 15 min. (9) Pass cells through a column: CD8+CD45R0+ cells are retained in the column; CD8+CD45R0− cells pass through. Remove column from magnet and flush out CD8+CD45R0+ cells. Repeat Step 9 for CD45R0+ cells to increase purity. (10) Re-incubate CD8+CD45R0− cells with CD45R0 beads (10°C, 20 min) to ensure removal of any remaining CD8+CD45R0+ cells and RA/R0 double-positive cells. (11) Pass cells through a column. CD8+CD45R0− cells pass through; any CD8+CD45R0+ cells remain in the column. Repeat Step 11 for CD8+CD45R0− cells to increase purity. In parallel for CD4+ populations, take the CD8− cells from step 3, add CD4 multisort reagent, then follow Steps 1–11 as for CD8+ cells to isolate CD4+CD45R0+ from and CD4+CD45R0− subpopulations. (Adapted from Ghattas et al29) (PDF 1547 kb)

Supplementary Material 1: Estimation of dilution factor for precursor enrichment (PDF 78 kb)

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Macallan, D., Asquith, B., Zhang, Y. et al. Measurement of proliferation and disappearance of rapid turnover cell populations in human studies using deuterium-labeled glucose. Nat Protoc 4, 1313–1327 (2009). https://doi.org/10.1038/nprot.2009.117

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