TY - JOUR
T1 - An integrated workflow to assess technical and biological variability of cell population frequencies in human peripheral blood by flow cytometry
AU - Burel, Julie G.
AU - Qian, Yu
AU - Arlehamn, Cecilia Lindestam
AU - Weiskopf, Daniela
AU - Zapardiel-Gonzalo, Jose
AU - Taplitz, Randy
AU - Gilman, Robert H.
AU - Saito, Mayuko
AU - De Silva, Aruna D.
AU - Vijayanand, Pandurangan
AU - Scheuermann, Richard H.
AU - Sette, Alessandro
AU - Peters, Bjoern
N1 - Funding Information:
This work was supported by the National Institute of Allergy and Infectious Diseases of the National Institutes of Health under award numbers U19AI118626 and R24AI108564. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health
Publisher Copyright:
Copyright © 2017 by The American Association of Immunologists, Inc.
PY - 2017/2/15
Y1 - 2017/2/15
N2 - 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 workflowby 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.
AB - 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 workflowby 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.
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U2 - 10.4049/jimmunol.1601750
DO - 10.4049/jimmunol.1601750
M3 - Article
C2 - 28069807
AN - SCOPUS:85014720873
SN - 0022-1767
VL - 198
SP - 1748
EP - 1758
JO - Journal of Immunology
JF - Journal of Immunology
IS - 4
ER -