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Scripps-Led Team Create Stem Cell Matrix from Gene Expression Patterns

NEW YORK (GenomeWeb News) – Using gene expression profiles garnered from roughly 150 cell samples, an international team of researchers has developed a “stem cell matrix” to begin cataloguing the genes and pathways involved in stem cell processes such as pluripotency, the ability to differentiate into any cell type.
The work, appearing in Nature’s advanced online publication yesterday, uncovered a gene expression signature present in all of the pluripotent stem cells tested. Based on these profiles, the researchers came up with a network of protein-protein interactions involved in pluripotency, which they placed in a database called PluriNet. Those expression patterns and protein networks are providing new insights into the molecular bases for pluripotency, while drawing distinctions between these and other stem cells. 
“Our results offer a new strategy for classifying stem cells by their molecular machinery,” senior author Jeanne Loring, director of the Scripps Research Institute’s Center for Regenerative Medicine and researcher at the Burnham Institute for Medical Research, said in a statement. “We show that pluripotence and self-renewal are under tight control by specific molecular networks.”
Stem cells are typically defined as self-renewing cells that are capable of differentiating into multiple cells types. Even so, this designation has become murky as scientists have discovered self-regenerating progenitor cells with a more limited differentiation potential. For example, progenitor cells found in the adult brain and other organs are capable of self-renewal even though they can only differentiate into certain types of cells.
Being able to distinguish between pluripotent, multipotent, and differentiated cells has become even more relevant with the advent of induced pluripotent stem cells.
“Many human cell preparations have been purported to be multi- or pluripotent but there has been no practical way to define pluripotency in human cells,” lead author Franz-Josef Müller, a researcher affiliated with the Scripps Center for Regenerative Medicine and Germany’s University Hospital Schleswig Holstein, said in a statement.
To begin drawing molecular distinctions between these cell types, Müller, Loring, and their co-workers determined the gene expression profile for about 150 pluripotent, multipotent, and differentiated cell types using Illumina WG8 and WG6 Sentrix BeadChip microarrays. They then applied unbiased, computer-based method and systems biology methods developed by collaborators at Israel’s Tel Aviv University to group and classify the cells based on these expression patterns.
Overall, the cell types tested fell into more than a dozen different clusters. One of these contained all of the best characterized human pluripotent stem cells. Other pluripotent cells — including mouse embryonic stem cells and mouse induced pluripotent stem cells — also clustered with this group. The same was not true of multipotent and differentiated cells. For example, cell lines originally designated neural stem cells actually contained several different gene expression profiles and clustered into diverse clusters.
Based on the set of genes that were differentially expressed in the pluripotent cell lines, the researchers identified a protein-protein interaction network that signifies pluripotency in the cell lines tested. This pluripotency-associated network, called PluriNet, contained known stem cell pathways, such as the NANOG network, as well as pathways involved in processes such as DNA repair and replication and cell cycle control.
“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,” the authors wrote.
The authors emphasized that the PluriNet collection is an ongoing effort, which will be expanded as more and more information on gene expression patterns in stem cells and related cell types becomes available.
“As more direct evidence for protein-protein interactions in human cells becomes available,” they wrote, “it will be possible to refine the networks we have defined and make them more useful for testing hypotheses about the nature of stem cell pluripotency and multipotency.”

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