Standardization and quality control for high-dimensional mass cytometry studies of human samples.

TitleStandardization and quality control for high-dimensional mass cytometry studies of human samples.
Publication TypeJournal Article
Year of Publication2016
AuthorsKleinsteuber K, Corleis B, Rashidi N, Nchinda N, Lisanti A, Cho JL, Medoff BD, Kwon D, Walker BD
JournalCytometry A
Volume89
Issue10
Pagination903-913
Date Published10/01/2016
ISSN1552-4930
Abstract

Mass cytometry (CyTOF), a mass spectrometry-based single cell phenotyping technology, allows utilization of over 35 antibodies in a single sample and is a promising tool for translational human immunology studies. Although several analysis tools are available to interpret the complex data sets generated, a robust method for standardization and quality control within and across studies is needed. Here we report an efficient and easily adaptable method to monitor quality of individual samples in human immunology studies and to facilitate reproducible data analysis. Samples to be assessed are spiked with a defined amount of reference peripheral blood mononuclear cells from a healthy donor, derived from a single large blood draw. The presence of known standardized numbers and phenotypic profiles of these reference cells greatly facilitates sample analysis by allowing for: 1) quality control for consistent staining of each antibody in the panel, 2) identification of potential batch effects, and 3) implementation of a robust gating strategy. We demonstrate the utility of this method using peripheral blood and bronchoalveolar lavage samples from HIV(+) patients by characterizing their CD8(+) T-cell phenotypes and cytokine expression, respectively. Our results indicate that this method allows quality control of experimental conditions and results in highly reproducible population frequencies through a robust gating strategy. © 2016 International Society for Advancement of Cytometry.

DOI10.1002/cyto.a.22935
Alternate JournalCytometry A
PubMed ID27575385
Grant ListUM1 AI100663 / AI / NIAID NIH HHS / United States
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