An introduction to mass cytometry: fundamentals and applications - PubMed (original) (raw)
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An introduction to mass cytometry: fundamentals and applications
Scott D Tanner et al. Cancer Immunol Immunother. 2013 May.
Abstract
Mass cytometry addresses the analytical challenges of polychromatic flow cytometry by using metal atoms as tags rather than fluorophores and atomic mass spectrometry as the detector rather than photon optics. The many available enriched stable isotopes of the transition elements can provide up to 100 distinguishable reporting tags, which can be measured simultaneously because of the essential independence of detection provided by the mass spectrometer. We discuss the adaptation of traditional inductively coupled plasma mass spectrometry to cytometry applications. We focus on the generation of cytometry-compatible data and on approaches to unsupervised multivariate clustering analysis. Finally, we provide a high-level review of some recent benchmark reports that highlight the potential for massively multi-parameter mass cytometry.
Conflict of interest statement
The authors are employees of, and receive remuneration from, DVS Sciences Inc. Scott Tanner, Vladimir Baranov, Olga Ornatsky, and Dmitry Bandura are co-founders of and equity shareholders in DVS Sciences Inc. Scott Tanner is a member of the Board of Directors of DVS Sciences, Inc.
Figures
Fig. 1
Mass spectrum of 30 enriched stable isotopes of the lanthanides, recorded for solution analysis at concentrations of approximately 20 ng/L (20 parts per trillion W/W) for each isotope
Fig. 2
Computer screen shot during mass cytometric analysis of adult PBMC. These cells were probed with antibodies against 27 surface antigens. Each antibody was labeled with a different stable isotope (given in the table at the top of the figure: the antigen is indicated, such as CD2, followed by the isotope used to tag the corresponding antibody, 175Lu). In addition, cellular DNA was labeled with an Ir-intercalator (used as a trigger for cell recognition)
Fig. 3
Radial polar plot display of 20-parameter data for two cell lines (KG1a and THP-1) and a patient bone marrow sample (BCLQ), representative of different acute myeloid leukemia subtypes. Intensity is displayed in logarithmic form as the distance from the axis of the plot. In this instance, the plots provide the marker signals averaged over a cell population: similar displays can be generated for gated populations or even for individual cells
Fig. 4
Unsupervised neural network analysis of Ramos B cells contaminated with 0.1 % PBMC from a leukemia patient. a Two-dimensional dot plot (CD45 vs. CD20) for the entire sample. These data were subjected to a UNN requesting identification of 15 distinguishable clusters of cell, 5 of which are shown in b. Radial polar plots are shown for these 5 clusters in d: 14 of the 15 clusters were similar and were distinguished as “different clusters” principally on the basis of intensity. A 15th cluster corresponding to the gated region in a was identified on the basis of its polar plot shown in c as the cells corresponding to the leukemia patient
Fig. 5
Bone marrow samples were analyzed for 31 proteins, of which 13 were cell surface markers used for subpopulation analysis, and 18 were intracellular signaling molecules used to measure functional response to stimulation and inhibition. The data presented here focus on the 13 cell differentiation markers. The data were subjected to unsupervised cluster analysis (SPADE), which identifies distinct phenotype populations and determines the relationships based on nearest neighbor populations (see [17, 18] for detailed information). a Highlights the major steps in defining the SPADE hierarchical tree. The outcome of the analysis is the “tree” shown in b which is interpreted to reflect immunological populations based on the marker distributions, a subset of which are shown in c and d. The “tree” that is formed is reminiscent of the hierarchical progression that is consistent with models for hematopoiesis. From Bendall et al. [17]. Reprinted with permission from AAAS
Fig. 6
Major T cell clusters were determined using metal-encoded tetramer probes and examined using 25 metal-labeled antibodies against cell differentiation and signaling molecules. The data are displayed in a as 3D PCA plots constructed from the 25 antibody response signals, principally distinguishing differentiation state, memory segregation, and memory status (see [19] for details). Phenotypic and functional capacity progression are displayed in b and c by expansion along the PC2 (memory progression) axis. Reprinted from Newell et al. [19] with permission from Elsevier
Fig. 7
Exemplary data from an assay of PBMC using 9 probes to distinguish 14 immunological populations, 14 probes against 14 intracellular signaling molecules, and 7 bar-coding elements to multiplex 96 samples that were probed with 8 concentrations each of 12 stimulants (96 samples) and inhibited with each of 27 inhibitors. In this instance, the data are presented for the population identified as CD14+ HLA-DRmid showing the signaling responses for the 14 signaling molecules (arrayed as in the upper left figure) to the 12 stimulants indicated at the left (one per row) and inhibitors indicated in each column. The size and color of each spot indicates the IC50 and percent inhibition observed in each instance (see [20] for details). For example, in this instance, in the presence of ruxolitinib, inhibition of phosphorylation of STAT1 (IC50 = 23 nM, 93 % inhibition) and STAT3 (IC50 = 4 nM, 147 % inhibition) was observed. Reprinted by permission from Macmillan Publishers Ltd.: Bodenmiller et al. [20]
References
- Houk RS, Fassel VA, Flesch GD, Svec HJ, Gray AL, Taylor CE. Inductively coupled argon plasma as an ion source for mass spectrometric determination of trace elements. Anal Chem. 1980;52:2283–2289. doi: 10.1021/ac50064a012. - DOI
- Ornatsky OI, Lou X, Nitz M, Schafer S, Sheldrick WS, Baranov VI, Bandura DR, Tanner SD. Study of cell antigens and intracellular DNA by identification of element-containing labels and metallointercalators using inductively coupled plasma mass spectrometry. Anal Chem. 2008;80:2539–2547. doi: 10.1021/ac702128m. - DOI - PubMed
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