Abstract
Single cell mass cytometry is revolutionizing our ability to quantitatively characterize cellular biomarkers and signaling networks. Mass cytometry experiments routinely measure 25–35 features of each cell in primary human tissue samples. The relative ease with which a novice user can generate a large amount of high quality data and the novelty of the approach have created a need for example protocols, analysis strategies, and datasets. In this chapter, we present detailed protocols for two mass cytometry experiments designed as training tools. The first protocol describes detection of 26 features on the surface of human peripheral blood mononuclear cells. In the second protocol, a mass cytometry signaling network profile measures 25 node states comprised of five key signaling effectors (AKT, ERK1/2, STAT1, STAT5, and p38) quantified under five conditions (Basal, FLT3L, SCF, IL-3, and IFNγ). This chapter compares manual and unsupervised data analysis approaches, including bivariate plots, heatmaps, histogram overlays, SPADE, and viSNE. Data files in this chapter have been shared online using Cytobank (http://www.cytobank.org/irishlab/).
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Acknowledgements
The authors thank P.B. Ferrell for use of Kasumi-1 mass cytometry data. This work was supported by the NIH/NCI R00 CA143231, NIH/NCI R25 CA136440 (K.E.D.), the Vanderbilt International Scholars Program (N.L.), and Vanderbilt-Ingram Cancer Center (VICC NIH/NCI P50 CA68485) pilot grants including a Young Ambassador award.
Conflict of interest disclosure: J.M.I. declares a competing financial interest (cofounder and board member of Cytobank Inc.).
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Leelatian, N., Diggins, K.E., Irish, J.M. (2015). Characterizing Phenotypes and Signaling Networks of Single Human Cells by Mass Cytometry. In: Singh, A., Chandrasekaran, A. (eds) Single Cell Protein Analysis. Methods in Molecular Biology, vol 1346. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-2987-0_8
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DOI: https://doi.org/10.1007/978-1-4939-2987-0_8
Publisher Name: Humana Press, New York, NY
Print ISBN: 978-1-4939-2986-3
Online ISBN: 978-1-4939-2987-0
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