An information theoretic, microfluidic-based single cell analysis permits identification of subpopulations among putatively homogeneous stem cells.

ABSTRACT: An incomplete understanding of the nature of heterogeneity within stem cell populations remains a major impediment to the development of clinically effective cell-based therapies. Transcriptional events within a single cell are inherently stochastic and can produce tremendous variability, even among genetically identical cells. It remains unclear how mammalian cellular systems overcome this intrinsic noisiness of gene expression to produce consequential variations in function, and what impact this has on the biologic and clinical relevance of highly 'purified' cell subgroups. To address these questions, we have developed a novel method combining microfluidic-based single cell analysis and information theory to characterize and predict transcriptional programs across hundreds of individual

SUBMITTER: Glotzbach JP 

PROVIDER: S-EPMC3120839 | biostudies-literature | 2011

REPOSITORIES: biostudies-literature