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J Immunol. 2017 Feb 15;198(4):1748-1758. doi: 10.4049/jimmunol.1601750. Epub 2017 Jan 9.

An Integrated Workflow To Assess Technical and Biological Variability of Cell Population Frequencies in Human Peripheral Blood by Flow Cytometry.

Author information

1
La Jolla Institute for Allergy and Immunology, La Jolla, CA 92037; jburel@lji.org.
2
J. Craig Venter Institute, La Jolla, CA 92037.
3
La Jolla Institute for Allergy and Immunology, La Jolla, CA 92037.
4
Division of Infectious Diseases, University of California, San Diego, La Jolla, CA 92093.
5
Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD 21205.
6
Universidad Peruana Caytano Hereida, Lima 15102, Peru.
7
Department of Virology, Tohoku University, Sendai 9808575, Japan.
8
Genetech Research Center, Colombo 00800, Sri Lanka; and.
9
Department of Pathology, University of California, San Diego, La Jolla, CA 92093.

Abstract

In the context of large-scale human system immunology studies, controlling for technical and biological variability is crucial to ensure that experimental data support research conclusions. In this study, we report on a universal workflow to evaluate both technical and biological variation in multiparameter flow cytometry, applied to the development of a 10-color panel to identify all major cell populations and T cell subsets in cryopreserved PBMC. Replicate runs from a control donation and comparison of different gating strategies assessed the technical variability associated with each cell population and permitted the calculation of a quality control score. Applying our panel to a large collection of PBMC samples, we found that most cell populations showed low intraindividual variability over time. In contrast, certain subpopulations such as CD56 T cells and Temra CD4 T cells were associated with high interindividual variability. Age but not gender had a significant effect on the frequency of several populations, with a drastic decrease in naive T cells observed in older donors. Ethnicity also influenced a significant proportion of immune cell population frequencies, emphasizing the need to account for these covariates in immune profiling studies. We also exemplify the usefulness of our workflow by identifying a novel cell-subset signature of latent tuberculosis infection. Thus, our study provides a universal workflow to establish and evaluate any flow cytometry panel in systems immunology studies.

PMID:
28069807
PMCID:
PMC5296239
DOI:
10.4049/jimmunol.1601750
[Indexed for MEDLINE]
Free PMC Article

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