Doug Auld, Ph.D. Novartis Institutes for BioMedical Research

Single-cell “mass cytometry” approach shows ability to measure a greater number of parameters simultaneously.

ASSAY & Drug Development Technologies offers a unique combination of original research and reports on the techniques and tools being used in cutting-edge drug development. The journal includes a “Literature Search and Review” column that identifies published papers of note and discusses their importance. GEN presents one article that was analyzed in the “Literature Search and Review” column, a paper published in ACS Chemical Biology titled “Single-cell mass cytometry of differential immune and drug responses across a human hematopoietic continuum.” Authors of the paper are Bendall SC, Simonds EF, Qiu P, Amir el-AD, Krutzik PO, Finck R, Bruggner RV,Melamed R, Trejo A, Ornatsky OI, Balderas RS, Plevritis SK, Sachs K, Pe’er D, Tanner SD, and Nolan GP.

Abstract from ACS Chemical Biology

Flow cytometry is an essential tool for dissecting the functional complexity of hematopoiesis. We used single-cell “mass cytometry” to examine healthy human bone marrow, measuring 34 parameters simultaneously in single cells (binding of 31 antibodies, viability, DNA content, and relative cell size). The signaling behavior of cell subsets spanning a defined hematopoietic hierarchy was monitored with 18 simultaneous markers of functional signaling states perturbed by a set of ex vivo stimuli and inhibitors. The data set allowed for an algorithmically driven assembly of related cell types defined by surface antigen expression, providing a superimposable map of cell signaling responses in combination with drug inhibition. Visualized in this manner, the analysis revealed previously unappreciated instances of both precise signaling responses that were bounded within conventionally defined cell subsets and more continuous phosphorylation responses that crossed cell population boundaries in unexpected manners yet tracked closely with cellular phenotype. Collectively, such single-cell analyses provide systemwide views of immune signaling in healthy human hematopoiesis, against which drug action and disease can be compared for mechanistic studies and pharmacologic intervention.

Commentary

Multiplexing using fluorescent probes is limited by the spectral overlap of the emission spectrum. This restricts the number of measured parameters and for most laboratories, multiplexing more than four fluorophores can be challenging. Atomic mass spectrometry (DVS Sciences), which measures the mass of individual atoms as opposed to the mass of the intact molecule, provides high resolution and sensitivity and offers the ability to detect multiple parameters by employing elements of the periodic table as tags.

In the method shown here, antibodies are labeled with a common tag containing a polymer that can chelate ~30 metal ions. To boost the signal, three such polymers can be linked to an antibody so that each antibody carries nearly 100 metal ions. Choosing metals not found in cells contained within a single series of the periodic table such as lanthanide metals allows for use of a single chelator for the labeling step and sensitive detection of antigen.

Following labeling, the cells are treated with the test conditions and then analyzed in a flow cytometer in which the detection is based on atomic mass spectrometry. Cells are passed through an inductively coupled argon plasma beam operating at a temperature approximately equal to that found on the surface of the sun (~5500 K). This temperature effectively vaporizes the cells and disintegrates their components into a cloud of fully ionized atoms. The ionized cloud of elemental ions is then passed through a time-of-flight atomic mass spectrometer, and the signals for each of the metals previously contained within single cells are quantified (see Figures A, B, C, D, and E).


Mass cytometry profiling of immune cell response patterns. Figure A: Workflow summary of mass cytometry analysis. Cells are stained with epitopespecific antibodies conjugated to transition element isotope reporters, each with a different mass. Cells are nebulized into single-cell droplets, and an elemental mass spectrum is acquired for each. The integrated elemental reporter signals for each cell can then be analyzed by using traditional flow cytometry methods as well as more advanced approaches such as heat maps of induced phosphorylation and tree plots.


Figures B and C: Representative antibody surface-staining results and cell population definitions (‘‘gating’’) for (B) fluorescence and (C) mass cytometry analysis of fixed PBMCs (peripheral blood mononuclear cells) from the same donor. Replicate analysis of a second donor is provided in Fig. S1A and S1B in the article’s Supporting Online Material. *Pearson correlation between frequencies measured by fluorescence or mass cytometry, including both donors (r = 0.99, p < 0.000001, two-tailed t test) (Table S1 and Fig. S1C in the article’s Supporting Online Material).

This article demonstrates a tour-de-force of this technology for the analysis of human hematologic cell types. The differentiation states of hematopoietic cells can be determined by “cluster of differentiation” (CD) markers. To create an “immunophenotype” panel, antibodies that monitored 13 core CD surface markers and 18 subset-specific cell-CD surface markers were used. In addition, a second panel was constructed using antibodies containing the same 13 core markers as well as 18 intracellular markers reflective of intracellular signaling events (e.g., through phosphoprotein detection). In addition three labels for total DNA, cell length, and cell viability were also used, so each panel measured 34 parameters.

Comparing the data for various phosphoproteins from atomic mass cytometry with conventional fluorescence cyotometry showed that both qualitatively and quantitatively similar patterns were obtained with each method. The data can be exported as typical .fcs files but the wealth of data generated is overwhelming. To address this issue, data analysis was performed using SPADE (spanning-tree progression analysis of densitynormalized events; see: Qiu et al., Nat Biotechnol 2011;29:886–891). SPADE analysis provides unsupervised clustering of the data and the results can be visualized with two-dimensional tree plots.

For example, in the immunophenotype panel, each node in the tree plot represents a cell cluster having a similar phenotype in the 13 dimensional space defined by the core surface markers. Well-defined cell types such as T cells or monocytes can provide internal standards for the nodes that enabled capturing unexpected transitional cell types and defining lineage by determining the relationships between each cell cluster. The functional state of each cell type can be similarly treated and visualized. Significant signaling events within each subtype were examined.

In addition to providing a system-level view of hematopoiesis this study examines pharmacological modulation with well-known kinase inhibitors such as dasatinib, which points to polypharmacology, which may explain the efficacy of this compound in certain B-cell malignancies. This approach demonstrates a method for the analysis of pathways using the resolving power of atomic mass spectrometry. Assay development of multiplexed formats using fluorophores is difficult due to the large differences in fluorescent brightness between probes and the spectral overlap. In mass cytometry the isotope signals vary within a twofold range and the isotopic masses are readily separated upon detection, which allows for a much greater number of parameters to be simultaneously measured and more facile assay optimization. The technology demonstrates a unique approach to high content methods that enables pathway analysis from primary cell types.


Figure D: Induction of STAT3 and 5 phosphorylation by various ex vivo stimuli in naive CD4+ CD45RA+ T cells [(B) and (C), red boxes] as measured by (top) fluorescence and (bottom) mass cytometry. Red arrows indicate the expected shift along the STAT phosphorylation axes. Figure E: Heatmap summary of induced STAT phosphorylation in immune populations from the PBMC donor defined in (B) and (C) [column headers refer to blue polygons in (B) and (C)]. Responses to the indicated stimuli in each row were measured by (top) fluorescence and (bottom) mass cytometry. Color scale indicates the difference in log2 mean intensity of the stimulated condition compared with the unstimulated control. Signaling responses of a second donor are provided in Fig. S1D in the article’s Supporting Online Material. **Pearson correlation between signaling induction measured by fluorescence or mass cytometry, including both donors (pSTAT3: r = 0.92; p < 0.000001, two-tailed t test [Fig. S1E in the article’s Supporting Online Material]; pSTAT5: r = 0.89, p < 0.000001, two-tailed t test [Figs. S1E and S1F in the article’s Supporting Online Material]).

The initial resistance that the high-content/high-throughput community had to face has been overcome, and now most in the field acknowledge that flow cytometry is enormously high throughput and very high content. To learn more, click here.

Doug Auld, Ph.D., is affiliated with the Novartis Institutes for BioMedical Research.

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