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dc.contributor.authorGorman, Bryan R.
dc.contributor.authorLu, Junjie
dc.contributor.authorBaccei, Anna
dc.contributor.authorLowry, Nathan C.
dc.contributor.authorPurvis, Jeremy E.
dc.contributor.authorMangoubi, Rami S.
dc.contributor.authorLerou, Paul H.
dc.date.accessioned2015-02-17T15:29:30Z
dc.date.available2015-02-17T15:29:30Z
dc.date.issued2014-12
dc.date.submitted2014-08
dc.identifier.issn1932-6203
dc.identifier.urihttp://hdl.handle.net/1721.1/94550
dc.description.abstractHuman 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.en_US
dc.description.sponsorshipNational Institutes of Health (U.S.) (R01 EB006161-01A4)en_US
dc.description.sponsorshipNational Human Genome Research Institute (U.S.). (T 32 HG002295)en_US
dc.description.sponsorshipCharles Stark Draper Laboratory (Internal Research and Development Grant)en_US
dc.language.isoen_US
dc.publisherPublic Library of Scienceen_US
dc.relation.isversionofhttp://dx.doi.org/10.1371/journal.pone.0116037en_US
dc.rightsCreative Commons Attributionen_US
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en_US
dc.sourcePublic Library of Scienceen_US
dc.titleMulti-Scale Imaging and Informatics Pipeline for In Situ Pluripotent Stem Cell Analysisen_US
dc.typeArticleen_US
dc.identifier.citationGorman, 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.en_US
dc.contributor.departmentCharles Stark Draper Laboratoryen_US
dc.contributor.departmentHarvard University--MIT Division of Health Sciences and Technologyen_US
dc.contributor.mitauthorGorman, Bryan R.en_US
dc.contributor.mitauthorLowry, Nathan C.en_US
dc.contributor.mitauthorMangoubi, Rami S.en_US
dc.relation.journalPLoS ONEen_US
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dspace.orderedauthorsGorman, Bryan R.; Lu, Junjie; Baccei, Anna; Lowry, Nathan C.; Purvis, Jeremy E.; Mangoubi, Rami S.; Lerou, Paul H.en_US
mit.licensePUBLISHER_CCen_US
mit.metadata.statusComplete


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