Literature DB >> 17588935

Markers and methods for cell sorting of human embryonic stem cell-derived neural cell populations.

Jan Pruszak1, Kai-Christian Sonntag, Moe Hein Aung, Rosario Sanchez-Pernaute, Ole Isacson.   

Abstract

Neural cells differentiated in vitro from human embryonic stem cells (hESC) exhibit broad cellular heterogeneity with respect to developmental stage and lineage specification. Here, we describe standard conditions for the use and discovery of markers for analysis and cell selection of hESC undergoing neuronal differentiation. To generate better-defined cell populations, we established a working protocol for sorting heterogeneous hESC-derived neural cell populations by fluorescence-activated cell sorting (FACS). Using genetically labeled synapsin-green fluorescent protein-positive hESC-derived neurons as a proof of principle, we enriched viable differentiated neurons by FACS. Cell sorting methodology using surface markers was developed, and a comprehensive profiling of surface antigens was obtained for immature embryonic stem cell types (such as stage-specific embryonic antigen [SSEA]-3, -4, TRA-1-81, TRA-1-60), neural stem and precursor cells (such as CD133, SSEA-1 [CD15], A2B5, forebrain surface embryonic antigen-1, CD29, CD146, p75 [CD271]), and differentiated neurons (such as CD24 or neural cell adhesion molecule [NCAM; CD56]). At later stages of neural differentiation, NCAM (CD56) was used to isolate hESC-derived neurons by FACS. Such FACS-sorted hESC-derived neurons survived in vivo after transplantation into rodent brain. These results and concepts provide (a) a feasible approach for experimental cell sorting of differentiated neurons, (b) an initial survey of surface antigens present during neural differentiation of hESC, and (c) a framework for developing cell selection strategies for neural cell-based therapies.

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Year:  2007        PMID: 17588935      PMCID: PMC2238728          DOI: 10.1634/stemcells.2006-0744

Source DB:  PubMed          Journal:  Stem Cells        ISSN: 1066-5099            Impact factor:   6.277


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