Regulatory networks define phenotypic classes of human stem cell lines.
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Regulatory networks define phenotypic classes of human stem cell lines. / Müller, Franz-Josef; Laurent, Louise C; Kostka, Dennis; Ulitsky, Igor; Williams, Roy; Lu, Christina; Park, In-Hyun; Rao, Mahendra S; Shamir, Ron; Schwartz, Philip H; Schmidt, Nils-Ole; Loring, Jeanne F.
In: NATURE, Vol. 455, No. 7211, 7211, 2008, p. 401-405.Research output: SCORING: Contribution to journal › SCORING: Journal article › Research › peer-review
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T1 - Regulatory networks define phenotypic classes of human stem cell lines.
AU - Müller, Franz-Josef
AU - Laurent, Louise C
AU - Kostka, Dennis
AU - Ulitsky, Igor
AU - Williams, Roy
AU - Lu, Christina
AU - Park, In-Hyun
AU - Rao, Mahendra S
AU - Shamir, Ron
AU - Schwartz, Philip H
AU - Schmidt, Nils-Ole
AU - Loring, Jeanne F
PY - 2008
Y1 - 2008
N2 - Stem cells are defined as self-renewing cell populations that can differentiate into multiple distinct cell types. However, hundreds of different human cell lines from embryonic, fetal and adult sources have been called stem cells, even though they range from pluripotent cells-typified by embryonic stem cells, which are capable of virtually unlimited proliferation and differentiation-to adult stem cell lines, which can generate a far more limited repertoire of differentiated cell types. The rapid increase in reports of new sources of stem cells and their anticipated value to regenerative medicine has highlighted the need for a general, reproducible method for classification of these cells. We report here the creation and analysis of a database of global gene expression profiles (which we call the 'stem cell matrix') that enables the classification of cultured human stem cells in the context of a wide variety of pluripotent, multipotent and differentiated cell types. Using an unsupervised clustering method to categorize a collection of approximately 150 cell samples, we discovered that pluripotent stem cell lines group together, whereas other cell types, including brain-derived neural stem cell lines, are very diverse. Using further bioinformatic analysis we uncovered a protein-protein network (PluriNet) that is shared by the pluripotent cells (embryonic stem cells, embryonal carcinomas and induced pluripotent cells). Analysis of published data showed that the PluriNet seems to be a common characteristic of pluripotent cells, including mouse embryonic stem and induced pluripotent cells and human oocytes. Our results offer a new strategy for classifying stem cells and support the idea that pluripotency and self-renewal are under tight control by specific molecular networks.
AB - Stem cells are defined as self-renewing cell populations that can differentiate into multiple distinct cell types. However, hundreds of different human cell lines from embryonic, fetal and adult sources have been called stem cells, even though they range from pluripotent cells-typified by embryonic stem cells, which are capable of virtually unlimited proliferation and differentiation-to adult stem cell lines, which can generate a far more limited repertoire of differentiated cell types. The rapid increase in reports of new sources of stem cells and their anticipated value to regenerative medicine has highlighted the need for a general, reproducible method for classification of these cells. We report here the creation and analysis of a database of global gene expression profiles (which we call the 'stem cell matrix') that enables the classification of cultured human stem cells in the context of a wide variety of pluripotent, multipotent and differentiated cell types. Using an unsupervised clustering method to categorize a collection of approximately 150 cell samples, we discovered that pluripotent stem cell lines group together, whereas other cell types, including brain-derived neural stem cell lines, are very diverse. Using further bioinformatic analysis we uncovered a protein-protein network (PluriNet) that is shared by the pluripotent cells (embryonic stem cells, embryonal carcinomas and induced pluripotent cells). Analysis of published data showed that the PluriNet seems to be a common characteristic of pluripotent cells, including mouse embryonic stem and induced pluripotent cells and human oocytes. Our results offer a new strategy for classifying stem cells and support the idea that pluripotency and self-renewal are under tight control by specific molecular networks.
M3 - SCORING: Zeitschriftenaufsatz
VL - 455
SP - 401
EP - 405
JO - NATURE
JF - NATURE
SN - 0028-0836
IS - 7211
M1 - 7211
ER -
