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Mass Cytometry pp 217-226 | Cite as

Picturing Polarized Myeloid Phagocytes and Regulatory Cells by Mass Cytometry

  • Mikael RousselEmail author
  • Todd Bartkowiak
  • Jonathan M. IrishEmail author
Protocol
Part of the Methods in Molecular Biology book series (MIMB, volume 1989)

Abstract

The immune monocyte/phagocyte system (MPS) includes numerous cell subsets of the myeloid lineage including monocyte, macrophage, and dendritic cell (DC) populations that are heterogeneous both phenotypically and functionally. Previously, we characterized these diverse MPS phenotypes with multi-parametric mass cytometry (CyTOF). In order to expansively characterize monocytes, macrophages, and dendritic cells, a CyTOF panel was designed to measure 35 identity-, activation-, and polarization-markers. Here we provide a protocol to define a reference map for the myeloid compartment, including sample preparation, to produce reference cell subsets from the monocyte/phagocyte system. In particular, we focused on monocyte-derived macrophages that were further polarized in vitro with cytokine stimulation (i.e., M-CSF, GM-CSF, IL-4, IL-10, IFNγ, and LPS), as well as monocyte-derived DCs, and myeloid-derived suppressor cells (MDSCs), generated in vitro from human bone marrow and/or peripheral blood.

Key words

Mass cytometry Macrophage polarization Dendritic cells Myeloid-derived suppressor cells Myeloid regulatory cells 

References

  1. 1.
    Guilliams M, Ginhoux F, Jakubzick C et al (2014) Dendritic cells, monocytes and macrophages: a unified nomenclature based on ontogeny. Nat Rev Immunol 14:571–578.  https://doi.org/10.1038/nri3712CrossRefPubMedPubMedCentralGoogle Scholar
  2. 2.
    Ancuta P (2015) A slan-based nomenclature for monocytes? Blood 126:2536–2538.  https://doi.org/10.1182/blood-2015-10-675470CrossRefPubMedGoogle Scholar
  3. 3.
    Ziegler-Heitbrock L, Ancuta P, Crowe S et al (2010) Nomenclature of monocytes and dendritic cells in blood. Blood 116:e74–e80.  https://doi.org/10.1182/blood-2010-02-258558CrossRefPubMedGoogle Scholar
  4. 4.
    Bronte V, Brandau S, Chen SH et al (2016) Recommendations for myeloid-derived suppressor cell nomenclature and characterization standards. Nat Commun 7:12150.  https://doi.org/10.1038/ncomms12150CrossRefPubMedPubMedCentralGoogle Scholar
  5. 5.
    Murray PJ, Allen JE, Biswas SK et al (2014) Macrophage activation and polarization: nomenclature and experimental guidelines. Immunity 41:14–20.  https://doi.org/10.1016/j.immuni.2014.06.008CrossRefPubMedPubMedCentralGoogle Scholar
  6. 6.
    Engblom C, Pfirschke C, Pittet MJ (2016) The role of myeloid cells in cancer therapies. Nat Rev Cancer 16:447–462.  https://doi.org/10.1038/nrc.2016.54CrossRefPubMedGoogle Scholar
  7. 7.
    Ginhoux F, Schultze JL, Murray PJ et al (2016) New insights into the multidimensional concept of macrophage ontogeny, activation and function. Nat Immunol 17:34–40.  https://doi.org/10.1038/ni.3324CrossRefPubMedGoogle Scholar
  8. 8.
    Greenplate AR, Johnson DB, Roussel M et al (2016) Myelodysplastic syndrome revealed by systems immunology in a melanoma patient undergoing anti-PD-1 therapy. Cancer Immunol Res 4:474–480.  https://doi.org/10.1158/2326-6066.CIR-15-0213CrossRefPubMedPubMedCentralGoogle Scholar
  9. 9.
    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 332:687–696.  https://doi.org/10.1126/science.1198704CrossRefPubMedPubMedCentralGoogle Scholar
  10. 10.
    Spitzer MH, Nolan GP (2016) Mass Cytometry: single cells, many features. Cell 165:780–791.  https://doi.org/10.1016/j.cell.2016.04.019CrossRefPubMedPubMedCentralGoogle Scholar
  11. 11.
    Saeys Y, Van Gassen S, Lambrecht BN (2016) Computational flow cytometry: helping to make sense of high-dimensional immunology data. Nat Rev Immunol 16:449–462.  https://doi.org/10.1038/nri.2016.56CrossRefPubMedGoogle Scholar
  12. 12.
    Diggins KE, Greenplate AR, Leelatian N et al (2017) Characterizing cell subsets using marker enrichment modeling. Nat Methods 14:275–278.  https://doi.org/10.1038/nmeth.4149CrossRefPubMedPubMedCentralGoogle Scholar
  13. 13.
    Amir EAD, Davis KL, Tadmor MD et al (2013) viSNE enables visualization of high dimensional single-cell data and reveals phenotypic heterogeneity of leukemia. Nat Biotechnol 31:545–552.  https://doi.org/10.1038/nbt.2594CrossRefGoogle Scholar
  14. 14.
    Qiu P, Simonds EF, Bendall SC et al (2011) Extracting a cellular hierarchy from high-dimensional cytometry data with SPADE. Nat Biotechnol 29:886–891.  https://doi.org/10.1038/nbt.1991CrossRefPubMedPubMedCentralGoogle Scholar
  15. 15.
    Diggins KE, Gandelman JS, Roe CE et al (2018) Generating quantitative cell identity labels with marker enrichment modeling (MEM). Curr Protoc Cytom 83(2018):10.21.1–10.21.28.  https://doi.org/10.1002/cpcy.34CrossRefGoogle Scholar
  16. 16.
    Alcántara-Hernández M, Leylek R, Wagar LE et al (2017) High-dimensional phenotypic mapping of human dendritic cells reveals interindividual variation and tissue specialization. Immunity 47(6):1037–1050.e6.  https://doi.org/10.1016/j.immuni.2017.11.001CrossRefPubMedPubMedCentralGoogle Scholar
  17. 17.
    See P, Dutertre CA, Chen J et al (2017) Mapping the human DC lineage through the integration of high-dimensional techniques. Science 356:eaag3009.  https://doi.org/10.1126/science.aag3009CrossRefPubMedGoogle Scholar
  18. 18.
    Schulz D, Severin Y, Zanotelli VRT et al. (2019) In-Depth Characterization of Monocyte-Derived Macrophages using a Mass Cytometry-Based Phagocytosis Assay. Scientific reports 9:1925 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6374473/ PMID: 30760760
  19. 19.
    Sander J, Schmidt SV, Cirovic B et al (2017) Cellular differentiation of human monocytes is regulated by time-dependent interleukin-4 signaling and the transcriptional regulator NCOR2. Immunity 47:1051–1066.e12.  https://doi.org/10.1016/j.immuni.2017.11.024CrossRefPubMedPubMedCentralGoogle Scholar
  20. 20.
    Chevrier S, Levine JH, Zanotelli VRT et al (2017) An immune atlas of clear cell renal cell carcinoma. Cell 169:736–738.e18.  https://doi.org/10.1016/j.cell.2017.04.016CrossRefPubMedPubMedCentralGoogle Scholar
  21. 21.
    Lavin Y, Kobayashi S, Leader A et al (2017) Innate immune landscape in early lung adenocarcinoma by paired single-cell analyses. Cell 169:750–757.e15.  https://doi.org/10.1016/j.cell.2017.04.014CrossRefPubMedPubMedCentralGoogle Scholar
  22. 22.
    Krieg C, Nowicka M, Guglietta S et al (2018) High-dimensional single-cell analysis predicts response to anti-PD-1 immunotherapy. Nat Med 9:2579–2514.  https://doi.org/10.1038/nm.4466CrossRefGoogle Scholar
  23. 23.
    Roussel M, Ferrell PB, Greenplate AR et al (2017) Mass cytometry deep phenotyping of human mononuclear phagocytes and myeloid-derived suppressor cells from human blood and bone marrow. J Leukoc Biol 102:437–447.  https://doi.org/10.1189/jlb.5MA1116-457RCrossRefPubMedGoogle Scholar
  24. 24.
    Xue J, Schmidt SV, Sander J et al (2014) Transcriptome-based network analysis reveals a spectrum model of human macrophage activation. Immunity 40:274–288.  https://doi.org/10.1016/j.immuni.2014.01.006CrossRefPubMedPubMedCentralGoogle Scholar
  25. 25.
    Marigo I, Bosio E, Solito S et al (2010) Tumor-induced tolerance and immune suppression depend on the C/EBPbeta transcription factor. Immunity 32:790–802.  https://doi.org/10.1016/j.immuni.2010.05.010CrossRefPubMedPubMedCentralGoogle Scholar
  26. 26.
    Lechner MG, Liebertz DJ, Epstein AL (2010) Characterization of cytokine-induced myeloid-derived suppressor cells from normal human peripheral blood mononuclear cells. J Immunol 185:2273–2284.  https://doi.org/10.4049/jimmunol.1000901CrossRefPubMedPubMedCentralGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Univ Rennes, CHU Rennes, Inserm, MICMAC [(MIcroenvironment, Cell differentiation, iMmunology And Cancer)]—UMR_S 1236, EFSRennesFrance
  2. 2.Department of Pathology, Microbiology and Immunology and Vanderbilt-Ingram Cancer CenterVanderbilt University Medical CenterNashvilleUSA
  3. 3.Department of Cell and Developmental BiologyVanderbilt University School of MedicineNashvilleUSA

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