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PLoS One. 2014 Dec 31;9(12):e116037. doi: 10.1371/journal.pone.0116037. eCollection 2014.

Multi-scale imaging and informatics pipeline for in situ pluripotent stem cell analysis.

Author information

1
Department Of Pediatric Newborn Medicine and Department of Medicine, Division of Genetics, Brigham and Women's Hospital; Harvard Medical School; Harvard Stem Cell Institute, Boston, Massachusetts, United States of America; Harvard-MIT Division Of Health Sciences and Technology, Massachusetts Institute Of Technology, Cambridge, Massachusetts, United States of America; Charles Stark Draper Laboratory, Cambridge, Massachusetts, United States of America.
2
Department Of Pediatric Newborn Medicine and Department of Medicine, Division of Genetics, Brigham and Women's Hospital; Harvard Medical School; Harvard Stem Cell Institute, Boston, Massachusetts, United States of America.
3
Charles Stark Draper Laboratory, Cambridge, Massachusetts, United States of America.
4
Department Of Genetics, University of North Carolina School of Medicine, Chapel Hill, North Carolina, United States of America.

Abstract

Human pluripotent stem (hPS) cells are a potential source of cells for medical therapy and an ideal system to study fate decisions in early development. However, hPS cells cultured in vitro exhibit a high degree of heterogeneity, presenting an obstacle to clinical translation. hPS cells grow in spatially patterned colony structures, necessitating quantitative single-cell image analysis. We offer a tool for analyzing the spatial population context of hPS cells that integrates automated fluorescent microscopy with an analysis pipeline. It enables high-throughput detection of colonies at low resolution, with single-cellular and sub-cellular analysis at high resolutions, generating seamless in situ maps of single-cellular data organized by colony. We demonstrate the tool's utility by analyzing inter- and intra-colony heterogeneity of hPS cell cycle regulation and pluripotency marker expression. We measured the heterogeneity within individual colonies by analyzing cell cycle as a function of distance. Cells loosely associated with the outside of the colony are more likely to be in G1, reflecting a less pluripotent state, while cells within the first pluripotent layer are more likely to be in G2, possibly reflecting a G2/M block. Our multi-scale analysis tool groups colony regions into density classes, and cells belonging to those classes have distinct distributions of pluripotency markers and respond differently to DNA damage induction. Lastly, we demonstrate that our pipeline can robustly handle high-content, high-resolution single molecular mRNA FISH data by using novel image processing techniques. Overall, the imaging informatics pipeline presented offers a novel approach to the analysis of hPS cells that includes not only single cell features but also colony wide, and more generally, multi-scale spatial configuration.

PMID:
25551762
PMCID:
PMC4281228
DOI:
10.1371/journal.pone.0116037
[Indexed for MEDLINE]
Free PMC Article

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