Currently, quantifiable investigations of the epigenome require cell lysis and are population based, prohibiting direct investigations of intact intranuclear structural organization and introducing noise into data obtained from inherently heterogeneous stem cell populations. To address this, we have developed and employed a single-cell high-content image informatics framework to capture organizational signatures of epigenetic signaling components from images of cellular nuclei obtained via superresolution nanoscopy. High dimensional quantitative texture descriptors of the organizational dynamics of key posttranslational modifications to core histone proteins were imaged in different human stem cell systems using time-gated stimulated emission depletion confocal nanoscopy. Influential texture descriptors were identified, validated at the nanoscale using immuno-gold electron microscopy, and organizational sub-classifiers were generated from this bioimage informatics data representing a range of “open” versus “closed” chromatin states. When applied to growth factor-induced lineage differentiation of human mesenchymal stem cells, the organizational classifiers showed a clear evolution with temporal cell state, which was more sensitive than the conventional mass spectrometry-based quantitation of the relative abundance of these PTMs. When a range of stem cell phenotypes sharing common DNA sequences were imaged, clear sub-classifiers emerged correlating with the divergent phenotypes for undifferentiated, adipogenic, and osteogenic hMSCs, as well as for human foreskin fibroblasts, induced pluripotent stem cells, neural stem cells, and reprogrammed neurons. Thus, high content bioimage informatics reflective of chromatin organization yields a higher order organizational signature corresponding to an epigenetic “activity” state. To elucidate the influence of biophysical factors on stem cell epigenetic states, these imaging-based organizational classifiers were tested on human mesenchymal stem cells exposed to physically constraining cues, and successfully predicted the early differentiation toward adipogenic hMSCs on hydrogel substrates with spatially graded mechanical stiffness, as well as osteogenic hMSCs on soft-lithographed, graded nanotopographies. In summary, in contrast to the traditional reductionist, population-level readouts in epigenomics, the approach outlined in this thesis offers a more integrated, single-cell, organizational index of emergent stem cell activity in response to defined environmental cues, and can be applied for the screening of discrete microenvironmental properties for the enhancement of stem cell behavioral control and facilitated integration in regenerative medicine applications.
Subject (authority = RUETD)
Topic
Biomedical Engineering
Subject (authority = ETD-LCSH)
Topic
Epigenetics
Subject (authority = ETD-LCSH)
Topic
Image processing--Data processing
Subject (authority = ETD-LCSH)
Topic
Electron microscopy
RelatedItem (type = host)
TitleInfo
Title
Rutgers University Electronic Theses and Dissertations
Identifier (type = RULIB)
ETD
Identifier
ETD_6154
PhysicalDescription
Form (authority = gmd)
electronic resource
InternetMediaType
application/pdf
InternetMediaType
text/xml
Extent
1 online resource (xviii, 194 p. : ill.)
Note (type = degree)
Ph.D.
Note (type = bibliography)
Includes bibliographical references
Note (type = statement of responsibility)
by Joseph Jung-Woong Kim
RelatedItem (type = host)
TitleInfo
Title
Graduate School - New Brunswick Electronic Theses and Dissertations
Identifier (type = local)
rucore19991600001
Location
PhysicalLocation (authority = marcorg); (displayLabel = Rutgers, The State University of New Jersey)
Rutgers University. Graduate School - New Brunswick
AssociatedObject
Type
License
Name
Author Agreement License
Detail
I hereby grant to the Rutgers University Libraries and to my school the non-exclusive right to archive, reproduce and distribute my thesis or dissertation, in whole or in part, and/or my abstract, in whole or in part, in and from an electronic format, subject to the release date subsequently stipulated in this submittal form and approved by my school. I represent and stipulate that the thesis or dissertation and its abstract are my original work, that they do not infringe or violate any rights of others, and that I make these grants as the sole owner of the rights to my thesis or dissertation and its abstract. I represent that I have obtained written permissions, when necessary, from the owner(s) of each third party copyrighted matter to be included in my thesis or dissertation and will supply copies of such upon request by my school. I acknowledge that RU ETD and my school will not distribute my thesis or dissertation or its abstract if, in their reasonable judgment, they believe all such rights have not been secured. I acknowledge that I retain ownership rights to the copyright of my work. I also retain the right to use all or part of this thesis or dissertation in future works, such as articles or books.