The University of Southampton
University of Southampton Institutional Repository

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

The effect of cell subset isolation method on gene expression in leukocytes
The effect of cell subset isolation method on gene expression in leukocytes
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.
negative immunomagnetic selection, positive immunomagnetic selection, fluorescent activated cell sorting, CD4+ T cell, CD8+ T cell, B cell, monocyte, gene expression, microarray
1552-4922
94-104
Beliakova-Bethell, N.
5919f4d5-b2a8-4d9a-a3be-d0a78d8485b1
Massanella, M.
eeb62381-5782-4bd5-9b99-fdeac4337bcc
White, C.H.
6ba24ae5-dcad-4c90-abfc-243e1dd32b19
Lada, S.
761120a8-eb82-4317-af63-ba82b91e6476
Du, P.
69536198-13c6-4220-a12d-f1cb5daa383b
Vaida, F.
31640c24-468e-4bce-a45d-dabb45fa140b
Blanco, J.
e0bb79a1-35dd-46b0-888d-572157c73c28
Spina, C.A.
644b537b-d0f2-4c09-a43e-8b54f74c68a9
Woelk, C.H.
4d3af0fd-658f-4626-b3b5-49a6192bcf7d
Beliakova-Bethell, N.
5919f4d5-b2a8-4d9a-a3be-d0a78d8485b1
Massanella, M.
eeb62381-5782-4bd5-9b99-fdeac4337bcc
White, C.H.
6ba24ae5-dcad-4c90-abfc-243e1dd32b19
Lada, S.
761120a8-eb82-4317-af63-ba82b91e6476
Du, P.
69536198-13c6-4220-a12d-f1cb5daa383b
Vaida, F.
31640c24-468e-4bce-a45d-dabb45fa140b
Blanco, J.
e0bb79a1-35dd-46b0-888d-572157c73c28
Spina, C.A.
644b537b-d0f2-4c09-a43e-8b54f74c68a9
Woelk, C.H.
4d3af0fd-658f-4626-b3b5-49a6192bcf7d

Beliakova-Bethell, N., Massanella, M., White, C.H., Lada, S., Du, P., Vaida, F., Blanco, J., Spina, C.A. and Woelk, C.H. (2014) The effect of cell subset isolation method on gene expression in leukocytes. Cytometry Part A, 85 (1), 94-104. (doi:10.1002/cyto.a.22352).

Record type: Article

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.

This record has no associated files available for download.

More information

e-pub ahead of print date: 20 September 2013
Published date: January 2014
Keywords: negative immunomagnetic selection, positive immunomagnetic selection, fluorescent activated cell sorting, CD4+ T cell, CD8+ T cell, B cell, monocyte, gene expression, microarray
Organisations: Clinical & Experimental Sciences

Identifiers

Local EPrints ID: 379201
URI: http://eprints.soton.ac.uk/id/eprint/379201
ISSN: 1552-4922
PURE UUID: c11603bb-caf0-41eb-82a9-41aaa50e327d

Catalogue record

Date deposited: 18 Jul 2015 13:53
Last modified: 14 Mar 2024 20:35

Export record

Altmetrics

Contributors

Author: N. Beliakova-Bethell
Author: M. Massanella
Author: C.H. White
Author: S. Lada
Author: P. Du
Author: F. Vaida
Author: J. Blanco
Author: C.A. Spina
Author: C.H. Woelk

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×