Characterizing Phenotypes and Signaling Networks of Single Human Cells by Mass Cytometry.

Leelatian N, Diggins KE, Irish JM
Methods Mol Biol. 2015 1346: 99-113

PMID: 26542718 · PMCID: PMC4656023 · DOI:10.1007/978-1-4939-2987-0_8

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 IFN╬│). 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/ ).

MeSH Terms (9)

Cell Line Flow Cytometry Humans Immunophenotyping Leukocytes, Mononuclear Phenotype Phosphorylation Signal Transduction Single-Cell Analysis

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