title: 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 cells. Using this technique, we demonstrate that multiple subpopulations exist within a well-studied and putatively homogeneous stem cell population, murine long-term hematopoietic stem cells (LT-HSCs). These subgroups are defined by nonrandom patterns that are distinguishable from noise and are consistent with known functional properties of these cells. We anticipate that this analytic framework can also be applied to other cell types to elucidate the relationship between transcriptional and phenotypic variation.
authors: Department of Surgery, Stanford University School of Medicine, Stanford, California, United States of America.
authors: Jason P
authors: JP
authors: Glotzbach
authors: Michael
authors: M
authors: Januszyk
authors: Ivan N
authors: IN
authors: Vial
authors: Victor W
authors: VW
authors: Wong
authors: Alexander
authors: A
authors: Gelbard
authors: Tomer
authors: T
authors: Kalisky
authors: Hariharan
authors: H
authors: Thangarajah
authors: Michael T
authors: MT
authors: Longaker
authors: Stephen R
authors: SR
authors: Quake
authors: Gilbert
authors: G
authors: Chu
authors: Geoffrey C
authors: GC
authors: Gurtner
mesh_terms: D000465:Algorithms; D000818:Animals; D016000:Cluster Analysis; D005434:Flow Cytometry; D005786:Gene Expression Regulation; D006412:Hematopoietic Stem Cells / Q000166:cytology* / Q000378:metabolism; D007257:Information Theory; D008297:Male; D051379:Mice; D008810:Mice, Inbred C57BL; D044085:Microfluidics / Q000379:methods*; D008954:Models, Biological; D015999:Multivariate Analysis; D059010:Single-Cell Analysis / Q000379:methods*; D013997:Time Factors; D014158:Transcription, Genetic