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A Carrier Strategy for Mass Cytometry Analysis of Small Numbers of Cells

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Abstract

The recent launch of mass cytometry or cytometry by time of flight (CyTOF) has revolutionized flow cytometry. Similar to fluorescence flow cytometry, a key challenge for CyTOF is to analyze samples of limited amount or very rare cell populations under various experimental settings. Here we describe a carrier strategy that significantly reduces the required sample amount without losing analytical resolution. We were able to detect as few as 5 × 104 human peripheral blood mononuclear cells (PBMCs) using this method. This simple method thus enables the maximal usage of valuable clinical samples.

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References

  1. Swartz MA, Iida N, Roberts EW et al (2012) Tumor microenvironment complexity: emerging roles in cancer therapy. Cancer Res 72(10):2473–2480

    Article  CAS  Google Scholar 

  2. Satija R, Shalek AK (2014) Heterogeneity in immune responses: from populations to single cells. Trends Immunol 35(5):219–229

    Article  CAS  Google Scholar 

  3. Bandura DR, Baranov VI, Ornatsky OI et al (2009) Mass cytometry: technique for real time single cell multitarget immunoassay based on inductively coupled plasma time-of-flight mass spectrometry. Anal Chem 81(16):6813–6822

    Article  CAS  Google Scholar 

  4. Bendall SC, Simonds EF, Qiu P et al (2011) Single-cell mass cytometry of differential immune and drug responses across a human hematopoietic continuum. Science 332(6030):687–696

    Article  CAS  Google Scholar 

  5. Leipold MD, Newell EW, Maecker HT (2015) Multiparameter phenotyping of human PBMCs using mass cytometry. Methods Mol Biol 1343:81–95

    Article  CAS  Google Scholar 

  6. Pejoski D, Tchitchek N, Rodriguez Pozo A et al (2016) Identification of vaccine-altered circulating B cell phenotypes using mass cytometry and a two-step clustering analysis. J Immunol 196(11):4814–4831

    Article  CAS  Google Scholar 

  7. Chevrier S, Levine JH, Zanotelli VRT et al (2017) An immune Atlas of clear cell renal cell carcinoma. Cell 169(4):736–749.e718

    Article  CAS  Google Scholar 

  8. Lavin Y, Kobayashi S, Leader A et al (2017) Innate immune landscape in early lung adenocarcinoma by paired single-cell analyses. Cell 169(4):750–765.e717

    Article  CAS  Google Scholar 

  9. Good Z, Borges L, Vivanco Gonzalez N et al (2019) Proliferation tracing with single-cell mass cytometry optimizes generation of stem cell memory-like T cells. Nat Biotechnol 37(3):259–266

    Article  CAS  Google Scholar 

  10. Atkuri KR, Stevens JC, Neubert H (2015) Mass cytometry: a highly multiplexed single-cell technology for advancing drug development. Drug Metab Dispos 43(2):227–233

    Article  Google Scholar 

  11. Leary JF (1994) Chapter 20 strategies for rare cell detection and isolation. Methods Cell Biol 42:331–358

    Article  Google Scholar 

  12. Saeys Y, Van Gassen S, Lambrecht BN (2016) Computational flow cytometry: helping to make sense of high-dimensional immunology data. Nat Rev Immunol 16(7):449–462

    Article  CAS  Google Scholar 

  13. Van Der Maaten L, Hinton G (2008) Visualizing data using t-SNE. J Mach Learn Res 9(Nov):2579–2605

    Google Scholar 

  14. Van Gassen S, Callebaut B, Van Helden MJ et al (2015) FlowSOM: using self-organizing maps for visualization and interpretation of cytometry data. Cytometry A 87(7):636–645

    Article  Google Scholar 

  15. Zeglis BM, Pierre VC, Barton JK (2007) Metallo-intercalators and metallo-insertors. Chem Commun (Camb) 28(44):4565–4579

    Article  Google Scholar 

  16. Kutscher S, Dembek CJ, Deckert S et al (2013) Overnight resting of PBMC changes functional signatures of antigen specific T- cell responses: impact for immune monitoring within clinical trials. PLoS One 8(10):e76215

    Article  CAS  Google Scholar 

  17. Yao Y, Liu R, Shin MS et al (2014) CyTOF supports efficient detection of immune cell subsets from small samples. J Immunol Methods 415:1–5

    Article  CAS  Google Scholar 

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Acknowledgments

This work was supported by the Natural Science Foundation of Fujian Province of China No.2018 J05065, to LZ, and National Natural Science Foundation of China grants 31770952, 31570911, and 2017ZX10202203-003- 001 to G.F.

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Correspondence to Lei Zhang , Xiao Lei Chen or Guo Fu .

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Jia, X. et al. (2020). A Carrier Strategy for Mass Cytometry Analysis of Small Numbers of Cells. In: Liu, C. (eds) T-Cell Receptor Signaling. Methods in Molecular Biology, vol 2111. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-0266-9_2

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  • DOI: https://doi.org/10.1007/978-1-0716-0266-9_2

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  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-0716-0265-2

  • Online ISBN: 978-1-0716-0266-9

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