The effect of cell subset isolation method on gene expression in leukocytes

Authors

  • Nadejda Beliakova-Bethell,

    Corresponding author
    1. Department of Medicine, University of California San Diego, La Jolla, California
    • Correspondence to: Nadejda Beliakova-Bethell, Assistant Project Scientist, University of California San Diego, Department of Medicine, Stein Clinical Research Building, Rm. 303, 9500 Gilman Drive, #0679, La Jolla, CA 92093-0679, USA. E-mail: nbeliako@ucsd.edu

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  • Marta Massanella,

    1. Institut de recerca de la Sida-IrsiCaixa, Institut d'Investigació en Ciències de la Salut Germans Trias i Pujol, IGTP, Badalona, Spain
    Current affiliation:
    1. Department of Pathology, University of California San Diego, La Jolla, California, USA
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  • Cory White,

    1. Department of Medicine, University of California San Diego, La Jolla, California
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  • Steven M. Lada,

    1. Veterans Affairs San Diego Healthcare System, San Diego, California
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  • Pinyi Du,

    1. Veterans Affairs San Diego Healthcare System, San Diego, California
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  • Florin Vaida,

    1. Department of Family and Preventive Medicine, University of California San Diego, La Jolla, California
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  • Julià Blanco,

    1. Institut de recerca de la Sida-IrsiCaixa, Institut d'Investigació en Ciències de la Salut Germans Trias i Pujol, IGTP, Badalona, Spain
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  • Celsa A. Spina,

    1. Veterans Affairs San Diego Healthcare System, San Diego, California
    2. Department of Pathology, University of California San Diego, La Jolla, California
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  • Christopher H. Woelk

    1. Department of Medicine, University of California San Diego, La Jolla, California
    2. Veterans Affairs San Diego Healthcare System, San Diego, California
    3. Faculty of Medicine, University of Southampton, Southampton, Hants, United Kingdom
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  • Nadejda Beliakova-Bethell and Marta Massanella contributed equally to this work.

Abstract

Multiple scientific disciplines require the isolation of specific subsets of blood cells from patient samples for gene expression analysis by microarray or RNA-sequencing, preserving disease- or treatment-related signatures. However, little is known with respect to the impact of different cell isolation methods on gene expression and the effects of positive selection, negative selection, and fluorescence activated cell sorting (FACS) have not previously been assessed in parallel. To address this knowledge gap, CD4+ T cells, CD8+ T cells, B cells, and monocytes were isolated from blood samples from five independent donors using positive immunomagnetic selection, negative immunomagnetic selection, and FACS. We hypothesized that positive selection and FACS would yield higher purity but may have an impact on gene expression since both methods utilize antibodies that bind surface receptors of the cell type of interest. Moreover, FACS might upregulate stress response genes due to passage of the cells through the sorter. Microarray gene expression data were generated and subjected to unsupervised clustering and differential gene expression analysis. Surprisingly, these analyses revealed that gene expression signatures were more similar between cells isolated by negative selection and FACS compared to cells isolated by positive selection. Moreover, genes that are involved in the response to stress generally had the highest expression in cells isolated by negative or positive selection and not FACS. Thus, FACS is the recommended method for isolation of leukocyte subsets for gene expression studies since this method results in the purest subset populations and does not appear to induce a stress response. © 2013 International Society for Advancement of Cytometry

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