Quantitative screening of embryonic stem cell differentiation: endoderm formation as a model.
Embryonic stem (ES) cells have attracted much attention as a possible source of functional cells for regenerative medicine. Therapeutic use of ES cells requires control over the types and frequencies of cells generated during their in vitro differentiation. Due to the complexity of factors that impact upon ES cell differentiation, novel approaches for the optimization of tissue-specific development are required. This motivates our use of factorial and composite design methods to make empirical investigations more efficient, and to reveal unexpected interactions missed by conventional dose-response analysis. Factorial experiments would benefit from the high content evaluation of a large number of test conditions, necessitating the development of a quantitative screening technology (QST) capable of reporting the absolute number and frequency of target cells. We have developed and validated such a technology for ES cell differentiation analysis using automated fluorescence microscopy, employing endoderm differentiation as a model system. To test this platform, a two-level factorial experiment was carried out to identify major and interactive effects of glucose, insulin, retinoic acid (RA), basic fibroblast growth factor (bFGF), and epidermal growth factor (EGF) on endoderm formation. RA was found to have inhibitory effects on endoderm formation, while low glucose proved beneficial. QST was demonstrated to be a powerful tool to study factors impacting endoderm-specific ES cell differentiation, and should be applicable to the analysis of a range of ES cell-derived tissues.
Chang
Karen H
KH
Institute of Biomaterials and Biomedical Engineering and Department of Chemical Engineering and Applied Chemistry, University of Toronto, 4 Taddle Creek Road, Room 407, Rosebrugh Building, Toronto, Ontario M5S 3G9, Canada.
Zandstra
Peter W
PW
D000465:Algorithms; D000818:Animals; D018929:Cell Culture Techniques / Q000379:methods*; D002454:Cell Differentiation / Q000502:physiology*; D002460:Cell Line; D003198:Computer Simulation; D005163:Factor Analysis, Statistical; D018507:Gene Expression Regulation, Developmental / Q000502:physiology; D005947:Glucose / Q000378:metabolism; D006133:Growth Substances / Q000494:pharmacology; D006801:Humans; D051379:Mice; D008954:Models, Biological; D041681:NIH 3T3 Cells; D013234:Stem Cells / Q000166:cytology* / Q000187:drug effects / Q000502:physiology*; D023822:Tissue Engineering / Q000379:methods*
D006133:Growth Substances; D005947:Glucose