Literature DB >> 20024182

Sequential CD34 cell fractionation by magnetophoresis in a magnetic dipole flow sorter.

Thomas Schneider1, Stephan Karl, Lee R Moore, Jeffrey J Chalmers, P Stephen Williams, Maciej Zborowski.   

Abstract

Cell separation and fractionation based on fluorescent and magnetic labeling procedures are common tools in contemporary research. These techniques rely on binding of fluorophores or magnetic particles conjugated to antibodies to target cells. Cell surface marker expression levels within cell populations vary with progression through the cell cycle. In an earlier work we showed the reproducible magnetic fractionation (single pass) of the Jurkat cell line based on the population distribution of CD45 surface marker expression. Here we present a study on magnetic fractionation of a stem and progenitor cell (SPC) population using the established acute myelogenous leukemia cell line KG-1a as a cell model. The cells express a CD34 cell surface marker associated with the hematopoietic progenitor cell activity and the progenitor cell lineage commitment. The CD34 expression level is approximately an order of magnitude lower than that of the CD45 marker, which required further improvements of the magnetic fractionation apparatus. The cells were immunomagnetically labeled using a sandwich of anti-CD34 antibody-phycoerythrin (PE) conjugate and anti-PE magnetic nanobead and fractionated into eight components using a continuous flow dipole magnetophoresis apparatus. The CD34 marker expression distribution between sorted fractions was measured by quantitative PE flow cytometry (using QuantiBRITE PE calibration beads), and it was shown to be correlated with the cell magnetophoretic mobility distribution. A flow outlet addressing scheme based on the concept of the transport lamina thickness was used to control cell distribution between the eight outlet ports. The fractional cell distributions showed good agreement with numerical simulations of the fractionation based on the cell magnetophoretic mobility distribution in the unsorted sample.

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Year:  2009        PMID: 20024182      PMCID: PMC3509203          DOI: 10.1039/b908210g

Source DB:  PubMed          Journal:  Analyst        ISSN: 0003-2654            Impact factor:   4.616


  37 in total

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