Multi-Scale Imaging and Informatics Pipeline for In Situ Pluripotent Stem Cell Analysis
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gorman-2014-multi-scale imaging.pdf
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Author(s)
Gorman, Bryan R.
Lu, Junjie
Baccei, Anna
Lowry, Nathan C.
Purvis, Jeremy E.
Mangoubi, Rami S.
Lerou, Paul H.
Date Issued
December 2014
Journal
PLoS ONE
Publisher
Public Library of Science
Citation
Gorman, Bryan R., Junjie Lu, Anna Baccei, Nathan C. Lowry, Jeremy E. Purvis, Rami S. Mangoubi, and Paul H. Lerou. “Multi-Scale Imaging and Informatics Pipeline for In Situ Pluripotent Stem Cell Analysis.” Edited by Rodrigo Alexandre Panepucci. PLoS ONE 9, no. 12 (December 31, 2014): e116037.
Version
Final published version
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.
MIT Department
Charles Stark Draper Laboratory
Harvard University--MIT Division of Health Sciences and Technology
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DOI of Published Version
https://doi.org/10.1371/journal.pone.0116037
