Researchers from University of California Report Findings in Immune System (The Effect of Cell Subset Isolation Method on Gene Expression in Leukocytes)
By a News Reporter-Staff News Editor at Health & Medicine Week -- Researchers detail new data in Immunology. According to news reporting out of La Jolla, California, by NewsRx editors, research stated, "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."
Our news journalists obtained a quote from the research from the University of California, "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."
According to the news editors, the research concluded: "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."
For more information on this research see: The Effect of Cell Subset Isolation Method on Gene Expression in Leukocytes. Cytometry Part A, 2014;85A(1):94-104. Cytometry Part A can be contacted at: Wiley-Blackwell, 111 River St, Hoboken 07030-5774, NJ, USA. (Wiley-Blackwell - www.wiley.com/; Cytometry Part A - onlinelibrary.wiley.com/journal/10.1002/(ISSN)1552-4930)
Our news journalists report that additional information may be obtained by contacting N. Beliakova-Bethell, University of California, Dept. of Pathol, La Jolla, CA 92093, United States. Additional authors for this research include M. Massanella, C. White, S.M. Lada, P.Y. Du, F. Vaida, J. Blanco, C.A. Spina and C.H. Woelk (see also Immunology).
Keywords for this news article include: La Jolla, California, Immunology, Leukocytes, United States, Immune System, Machine Learning, Emerging Technologies, Gene Expression Analysis, North and Central America
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