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

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

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.

MeSH terms

  • Adult
  • Age Factors
  • CD4-Positive T-Lymphocytes
  • CD56 Antigen / genetics
  • CD56 Antigen / immunology
  • Cell Count / methods
  • Female
  • Flow Cytometry / methods*
  • Flow Cytometry / standards*
  • Flow Cytometry / statistics & numerical data
  • Humans
  • Immunophenotyping* / methods
  • Latent Tuberculosis / diagnosis
  • Latent Tuberculosis / immunology
  • Leukocytes, Mononuclear
  • Male
  • Sex Factors
  • T-Lymphocyte Subsets / immunology*
  • Workflow*

Substances

  • CD56 Antigen
  • NCAM1 protein, human