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.

  • Original Article
  • Published:

Transplant Technology

Enrichment of cell subpopulations applying automated MACS technique: purity, recovery and applicability for PCR-based chimerism analysis

Bone Marrow Transplantation volume 45, pages 181–189 (2010)Cite this article

Abstract

Enrichment of cell subpopulations is a prerequisite for lineage-specific chimerism analysis (LCA), a frequent approach in follow-up after allo-SCT. An efficient enrichment technique is Magnetic Cell Sorting (MACS) using the AutoMACS separator. However, evaluation of purity, recovery and applicability for PCR-based chimerism analysis of MACS-enriched subpopulations from post-transplant peripheral blood, providing reduced cell numbers and/or unbalanced proportions of subpopulations, is currently unavailable. We performed enrichment of CD3-, CD14-, CD15-, CD19- and CD56-positive subpopulations using ‘Whole Blood MicroBeads’ and AutoMACS separator in 137 prospectively collected peripheral blood samples from 15 paediatric patients after allo-CD3-/CD19-depleted SCT. Purity was assessed by immune phenotyping. Recovery and applicability for chimerism analysis was evaluated. Excellent purity >90% was achieved in CD14-, CD15-positive cells in 81%, 95% of the isolates and in 86% of CD3 and CD19 isolates, if ACC was >400 cells per μl. Median purity of CD56-positive isolates was 78.9%. Recovery >90% was between 93 (CD56) and 37% (CD15). Conventional and real-time PCR-based chimerism analysis was feasible in virtually all samples. Isolation of cell subpopulations by automated cell enrichment in post-transplant peripheral blood is feasible and fast providing excellent purity and recovery for routine lineage-specific chimerism analysis.

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
Figure 2
Figure 3

Similar content being viewed by others

References

  1. Bader P, Kreyenberg H, Hoelle W, Dueckers G, Handgretinger R, Lang P et al. Increasing mixed chimerism is an important prognostic factor for unfavorable outcome in children with acute lymphoblastic leukemia after allogeneic stem-cell transplantation: possible role for pre-emptive immunotherapy? J Clin Oncol. 2004; 22: 1696–1706.

    Article  PubMed  Google Scholar 

  2. Willasch A, Hoelle W, Kreyenberg H, Niethammer D, Handgretinger R, Lang P et al. Outcome of allogeneic stem cell transplantation in children with non-malignant diseases. Haematologica 2006; 91: 788–794.

    PubMed  Google Scholar 

  3. Thiede C, Bornhauser M, Ehninger G . Strategies and clinical implications of chimerism diagnostics after allogeneic hematopoietic stem cell transplantation. Acta Haematol 2004; 112: 16–23.

    Article  PubMed  Google Scholar 

  4. Liesveld JL, Rothberg PG . Mixed chimerism in SCT: conflict or peaceful coexistence? Bone Marrow Transplant 2008; 42: 297–310.

    Article  CAS  PubMed  Google Scholar 

  5. Saito B, Fukuda T, Yokoyama H, Kurosawa S, Takahashi T, Fuji S et al. Impact of T cell chimerism on clinical outcome in 117 patients who underwent allogeneic stem cell transplantation with a busulfan-containing reduced-intensity conditioning regimen. Biol Blood Marrow Transplant 2008; 14: 1148–1155.

    Article  CAS  PubMed  Google Scholar 

  6. Ozyurek E, Cowan MJ, Koerper MA, Baxter-Lowe LA, Dvorak CC, Horn BN . Increasing mixed chimerism and the risk of graft loss in children undergoing allogeneic hematopoietic stem cell transplantation for non-malignant disorders. Bone Marrow Transplant 2008; 42: 83–91.

    Article  CAS  PubMed  Google Scholar 

  7. Lion T, Muller-Berat N . Chimerism testing after allogeneic stem cell transplantation: importance of timing and optimal technique for testing in different clinical-biological situations. Leukemia 2003; 17: 612.

    Article  CAS  PubMed  Google Scholar 

  8. Matthes-Martin S, Lion T, Haas OA, Frommlet F, Daxberger H, Konig M et al. Lineage-specific chimaerism after stem cell transplantation in children following reduced intensity conditioning: potential predictive value of NK cell chimaerism for late graft rejection. Leukemia 2003; 17: 1934–1942.

    Article  CAS  PubMed  Google Scholar 

  9. Lim ZY, Pearce L, Ingram W, Ho AY, Mufti GJ, Pagliuca A . Chimerism does not predict for outcome after alemtuzumab-based conditioning: lineage-specific analysis of chimerism of specific diseases may be more informative. Bone Marrow Transplant 2008; 41: 587–588.

    Article  CAS  PubMed  Google Scholar 

  10. Ringden O . Immunotherapy by allogeneic stem cell transplantation. Adv Cancer Res 2007; 97C: 25–60.

    Article  Google Scholar 

  11. Lion T . Detection of impending graft rejection and relapse by lineage-specific chimerism analysis. Methods Mol Med 2007; 134: 197–216.

    Article  CAS  PubMed  Google Scholar 

  12. Miura Y, Tanaka J, Toubai T, Tsutsumi Y, Kato N, Hirate D et al. Analysis of donor-type chimerism in lineage-specific cell populations after allogeneic myeloablative and non-myeloablative stem cell transplantation. Bone Marrow Transplant. 2006; 37: 837–843.

    Article  CAS  PubMed  Google Scholar 

  13. Zeiser R, Spyridonidis A, Wasch R, Ihorst G, Grullich C, Bertz H et al. Evaluation of immunomodulatory treatment based on conventional and lineage-specific chimerism analysis in patients with myeloid malignancies after myeloablative allogeneic hematopoietic cell transplantation. Leukemia 2005; 19: 814–821.

    Article  CAS  PubMed  Google Scholar 

  14. Bader P, Stoll K, Huber S, Geiselhart A, Handgretinger R, Niemeyer C et al. Characterization of lineage-specific chimaerism in patients with acute leukaemia and myelodysplastic syndrome after allogeneic stem cell transplantation before and after relapse. Br J Haematol 2000; 108: 761–768.

    Article  CAS  PubMed  Google Scholar 

  15. Breuer S, Matthes S, König M, Fritsch G, Pötschger U, Lawitschka A et al. Recipient chimerism in the T-cell lineage is indicative of impending graft rejection in pediatric patients undergoing allogeneic hematopoietic stem cell transplantation. In: 40th Congress of SIOP, abstract book. Wiley-Liss Inc.: Hoboken, NY, USA, 2008, pp 60–61.

    Google Scholar 

  16. Pongers-Willemse MJ, Verhagen OJ, Tibbe GJ, Wijkhuijs AJ, de Haas V, Roovers E et al. Real-time quantitative PCR for the detection of minimal residual disease in acute lymphoblastic leukemia using junctional region specific TaqMan probes. Leukemia 1998; 12: 2006–2014.

    Article  CAS  PubMed  Google Scholar 

  17. Kreyenberg H, Holle W, Mohrle S, Niethammer D, Bader P . Quantitative analysis of chimerism after allogeneic stem cell transplantation by PCR amplification of microsatellite markers and capillary electrophoresis with fluorescence detection: the Tuebingen experience. Leukemia 2003; 17: 237–240.

    Article  CAS  PubMed  Google Scholar 

  18. Watzinger F, Lion T, Steward C . The RSD code: proposal for a nomenclature of allelic configurations in STR-PCR-based chimerism testing after allogeneic stem cell transplantation. Leukemia 2006; 20: 1448–1452.

    Article  CAS  PubMed  Google Scholar 

  19. Scharf SJ, Smith AG, Hansen JA, McFarland C, Erlich HA . Quantitative determination of bone marrow transplant engraftment using fluorescent polymerase chain reaction primers for human identity markers. Blood 1995; 85: 1954–1963.

    CAS  PubMed  Google Scholar 

  20. Willasch A, Schneider G, Reincke BS, Shayegi N, Kreyenberg H, Kuci S et al. Sequence polymorphism systems for quantitative real-time polymerase chain reaction to characterize hematopoietic chimerism-high informativity and sensitivity as well as excellent reproducibility and precision of measurement. Lab Hematol 2007; 13: 73–84.

    Article  CAS  PubMed  Google Scholar 

  21. Steinbach D, Debatin KM . What do we mean by sensitivity when we talk about detecting minimal residual disease? Leukemia 2008; 22: 1638–1639.

    Article  CAS  PubMed  Google Scholar 

  22. The R Foundation for Statistical Computing c/o Institut für Statistik und Wahrscheinlichkeitstheorie der Technischen Universität Wien. R, a language and environment for statistical computing and graphics. University of Vienna, Austria 2003.

  23. Vitale M, Della CM, Carlomagno S, Romagnani C, Thiel A, Moretta L . et al. The small subset of CD56brightCD16- natural killer cells is selectively responsible for both cell proliferation and interferon-gamma production upon interaction with dendritic cells. Eur J Immunol 2004; 34: 1715–1722.

    Article  CAS  PubMed  Google Scholar 

  24. Romagnani C, Juelke K, Falco M, Morandi B, D'Agostino A, Costa R et al. CD56brightCD16- killer Ig-like receptor- NK cells display longer telomeres and acquire features of CD56dim NK cells upon activation. J Immunol 2007; 178: 4947–4955.

    Article  CAS  PubMed  Google Scholar 

  25. Beck O, Seidl C, Lehrnbecher T, Kreyenberg H, Schwabe D, Klingebiel T et al. Quantification of chimerism within peripheral blood, bone marrow and purified leukocyte subsets: comparison of singleplex and multiplex PCR amplification of short tandem repeat (STR) loci. Eur J Haematol. 2006; 76: 237–244.

    Article  CAS  PubMed  Google Scholar 

  26. Tomblyn M, Lazarus HM . Donor lymphocyte infusions: the long and winding road: how should it be traveled? Bone Marrow Transplant 2008.

  27. Klingebiel T, Bader P . Delayed lymphocyte infusion in children given SCT. Bone Marrow Transplant 2008; 41 (Suppl 2): S23–S26.

    Article  PubMed  Google Scholar 

  28. Formankova R, Sedlacek P, Krskova L, Rihova H, Sramkova L, Star J . Chimerism-directed adoptive immunotherapy in prevention and treatment of post-transplant relapse of leukemia in childhood. Haematologica 2003; 88: 117–118.

    PubMed  Google Scholar 

Download references

Acknowledgements

This work was supported by the ‘Adolf Messer Stiftung’, Koenigstein, Germany (PB) and by the ‘Paul und Ursula Klein-Stiftung’, Frankfurt, Germany (AW).

Author information

Authors and Affiliations

  1. Department of Pediatric Hematology, Oncology and Hemostaseology, Goethe University Frankfurt, Hospital for Children and Adolescents III, Frankfurt, Germany,

    A Willasch, S Eing, G Weber, S Kuçi, J Soerensen, A Jarisch, E Rettinger, U Koehl, T Klingebiel, H Kreyenberg & P Bader

  2. Department of Computer Science and Mathematics, Goethe University Frankfurt, Frankfurt, Germany

    G Schneider

Authors
  1. A Willasch
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. S Eing
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. G Weber
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. S Kuçi
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. G Schneider
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. J Soerensen
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. A Jarisch
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. E Rettinger
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. U Koehl
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. T Klingebiel
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. H Kreyenberg
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. P Bader
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to A Willasch.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Willasch, A., Eing, S., Weber, G. et al. Enrichment of cell subpopulations applying automated MACS technique: purity, recovery and applicability for PCR-based chimerism analysis. Bone Marrow Transplant 45, 181–189 (2010). https://doi.org/10.1038/bmt.2009.89

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/bmt.2009.89

Keywords

This article is cited by

Search

Advanced search

Quick links