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dc.contributor.authorKim, Joseph J.
dc.contributor.authorBennett, Neal K.
dc.contributor.authorDevita, Mitchel S.
dc.contributor.authorChahar, Sanjay
dc.contributor.authorViswanath, Satish
dc.contributor.authorLee, Eunjee A.
dc.contributor.authorShao, Paul P.
dc.contributor.authorChilders, Erin P.
dc.contributor.authorLiu, Shichong
dc.contributor.authorGarcia, Benjamin A.
dc.contributor.authorBecker, Matthew L.
dc.contributor.authorHwang, Nathaniel S.
dc.contributor.authorMadabhushi, Anant
dc.contributor.authorVerzi, Michael P.
dc.contributor.authorMoghe, Prabhas V.
dc.contributor.authorJung, Giyoung
dc.contributor.authorKulesa, Anthony Benjamin
dc.date.accessioned2017-12-18T15:13:43Z
dc.date.available2017-12-18T15:13:43Z
dc.date.issued2017-01
dc.date.submitted2016-07
dc.identifier.issn2045-2322
dc.identifier.urihttp://hdl.handle.net/1721.1/112780
dc.description.abstractWhile distinct stem cell phenotypes follow global changes in chromatin marks, single-cell chromatin technologies are unable to resolve or predict stem cell fates. We propose the first such use of optical high content nanoscopy of histone epigenetic marks (epi-marks) in stem cells to classify emergent cell states. By combining nanoscopy with epi-mark textural image informatics, we developed a novel approach, termed EDICTS (Epi-mark Descriptor Imaging of Cell Transitional States), to discern chromatin organizational changes, demarcate lineage gradations across a range of stem cell types and robustly track lineage restriction kinetics. We demonstrate the utility of EDICTS by predicting the lineage progression of stem cells cultured on biomaterial substrates with graded nanotopographies and mechanical stiffness, thus parsing the role of specific biophysical cues as sensitive epigenetic drivers. We also demonstrate the unique power of EDICTS to resolve cellular states based on epi-marks that cannot be detected via mass spectrometry based methods for quantifying the abundance of histone posttranslational modifications. Overall, EDICTS represents a powerful new methodology to predict single cell lineage decisions by integrating high content super-resolution nanoscopy and imaging informatics of the nuclear organization of epi-marks.en_US
dc.description.sponsorshipNational Institutes of Health (U.S.) (Grant GM110174)en_US
dc.publisherNature Publishing Groupen_US
dc.relation.isversionofhttp://dx.doi.org/10.1038/srep39406en_US
dc.rightsCreative Commons Attribution 4.0 Internationalen_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_US
dc.sourceNatureen_US
dc.titleOptical High Content Nanoscopy of Epigenetic Marks Decodes Phenotypic Divergence in Stem Cellsen_US
dc.typeArticleen_US
dc.identifier.citationKim, Joseph J. et al. “Optical High Content Nanoscopy of Epigenetic Marks Decodes Phenotypic Divergence in Stem Cells.” Scientific Reports 7 (January 2017): 39406 © 2017 The Author(s)en_US
dc.contributor.departmentHarvard University--MIT Division of Health Sciences and Technologyen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Biological Engineeringen_US
dc.contributor.mitauthorJung, Giyoung
dc.contributor.mitauthorKulesa, Anthony Benjamin
dc.relation.journalScientific Reportsen_US
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dc.date.updated2017-12-06T21:09:10Z
dspace.orderedauthorsKim, Joseph J.; Bennett, Neal K.; Devita, Mitchel S.; Chahar, Sanjay; Viswanath, Satish; Lee, Eunjee A.; Jung, Giyoung; Shao, Paul P.; Childers, Erin P.; Liu, Shichong; Kulesa, Anthony; Garcia, Benjamin A.; Becker, Matthew L.; Hwang, Nathaniel S.; Madabhushi, Anant; Verzi, Michael P.; Moghe, Prabhas V.en_US
dspace.embargo.termsNen_US
dc.identifier.orcidhttps://orcid.org/0000-0003-2834-430X
dc.identifier.orcidhttps://orcid.org/0000-0001-9927-9715
mit.licensePUBLISHER_CCen_US


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