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

• Published in: PloS one Vol. 9; no. 12; p. e116037
• Main Authors: Gorman, Bryan R, Lu, Junjie, Baccei, Anna, Lowry, Nathan C, Purvis, Jeremy E, Mangoubi, Rami S, Lerou, Paul H
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 31.12.2014; Public Library of Science (PLoS)
• Subjects: Apoptosis; Automation; Bioinformatics; Biology and Life Sciences; Cell cycle; Cell Differentiation; Cell Lineage; Cells, Cultured; Colonies; Deoxyribonucleic acid; DNA; DNA damage; DNA Damage - genetics; DNA Repair - genetics; Embryonic Stem Cells - cytology; Embryos; Engineering and Technology; Fluorescence; G1 Phase - genetics; G2 Phase - genetics; Gene expression; Heterogeneity; Humans; Image analysis; Image processing; Image Processing, Computer-Assisted - methods; Informatics; Laboratories; Medical Informatics - methods; Medical research; Medical schools; Medicine; Methods; Microscopy; Microscopy, Fluorescence - methods; mRNA; Multiscale analysis; Pediatrics; Pipelines; Pluripotency; Pluripotent Stem Cells - cytology; Population; Research and Analysis Methods; RNA; Spatial distribution; Staining and Labeling; Stem cells; Womens health
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0116037

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.