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Dielectrophoretic cell separation and gene expression profiling on microelectronic chip arrays.

Abstract

Cell membrane dielectric properties of five different cultivated cell lines and human peripheral blood mononuclear cells (PBMC) were determined from dielectrophoretic crossover frequency measurements on a 5 x 5 microelectronic chip array. Based on distinct dielectric property differences between individual cell types, efficient cell separations were achieved by dielectrophoresis on this 5 x 5 array, which included separation of monocytic cells (U937) or human T cell leukemia virus type 1 (HTLV-1) tax-transformed cells (Ind-2) from PBMC, as well as separation of neuroblastoma cells (SH-SY5Y) from glioma cells (HTB). The purity of dielectrophoretically separated cells can be greater than 95%. Expression profiles of IL-1, TNF-alpha, and TGF-beta genes for U937 cells mixed with PBMC before and after the separation were determined by a means of electric field-facilitated hybridization on a 10 x 10 microelectronic chip array. By using the expression levels of pure U937 cells as a control, it was shown that the gene expression profiles of the postseparation cells were significantly different from those of the preseparation cell mixtures. The increase in gene expression levels for U937 cells upon lipopolysaccharide induction could be accurately determined only in the postseparation cells, while the preseparation samples masked these changes. Furthermore, by cultivating the separated HTB and SH-SY5Y cells and measuring expression of the stress-related gene c-fos, dielectrophoretic forces were shown to have little effect on cell survival and stress. The presented approach of using microelectronic chip arrays for both cell separation and gene expression profiling provides a great potential for accurate genetic analysis of specific cell subpopulations in heterogeneous samples.

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BibTeXRIS

Ying Huang, Sunghae Joo, Melanie Duhon, Michael Heller, Bruce Wallace, Xiao Xu. 2002-07-15. Dielectrophoretic cell separation and gene expression profiling on microelectronic chip arrays.. https://doi.org/10.1021/ac011273v

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