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DC Field | Value | Language |
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dc.contributor.advisor | Toettcher, Jared E | |
dc.contributor.author | Jena, Siddhartha Gautama | |
dc.contributor.other | Molecular Biology Department | |
dc.date.accessioned | 2021-10-04T13:26:10Z | - |
dc.date.available | 2021-10-04T13:26:10Z | - |
dc.date.created | 2021-01-01 | |
dc.date.issued | 2021 | |
dc.identifier.uri | http://arks.princeton.edu/ark:/99999/fk44t82g47 | - |
dc.description.abstract | The comparison of cells to computing machines is cliched, perhaps, but at least somewhat accurate. Cells are under profound pressure to interpret information from their surroundings and current internal state, and to turn this information into actions that they must perform to stay alive. Continuing with our analogy, signaling pathways are the wires of the massive computer contained in each and every cell. Although there are a large number of signaling pathways, the realm of behaviors that any one pathway can control is enormous.Time-varying inputs, or signaling dynamics, provide a possible explanation for how one pathway may convey different types of information to a range of targets. Rather than simply be on or off in a time-invariant fashion, a pathway can exhibit pulses of rapid activation and inactivation, the frequency, duration, and amplitude of which may be all interpreted in different ways by various cellular machinery. However, if and how signaling dynamics can transmit information to cellular behavior remains largely unexplored. Here, I explore gene regulation downstream of signaling dynamics, with a primary focus on using the Ras/Erk signaling pathway as a testbed. This pathway has been studied for decades, yet only recently has been found to exhibit rapid, pulsatile dynamics in a range of systems. Elucidating the function of dynamics and how they feed forward into gene regulatory mechanisms requires the use of interdisciplinary approaches that study effects from the molecular to the population level. I first study the emergence of transcriptional heterogeneity as a function of signaling duration, amplitude, and combinatorics. Next, I use chromatin profiling to better understand how regulatory DNA responds to optogenetic pulses of signaling input. Moving to the level of population-level signaling dynamics, I leverage machine learning methods to elucidate the autonomous and coupled contributions to cell signaling, using cellular perturbations from a receptor tyrosine kinase (RTK) drug screen. Lastly, I discuss the effects that can arise when transcription factor dynamics intersect with regulatory logic in chromatin in a developing animal. | |
dc.format.mimetype | application/pdf | |
dc.language.iso | en | |
dc.publisher | Princeton, NJ : Princeton University | |
dc.relation.isformatof | The Mudd Manuscript Library retains one bound copy of each dissertation. Search for these copies in the library's main catalog: <a href=http://catalog.princeton.edu>catalog.princeton.edu</a> | |
dc.subject | Erk signaling | |
dc.subject | Heterogeneity | |
dc.subject | Keratinocytes | |
dc.subject | Point processes | |
dc.subject | Signaling dynamics | |
dc.subject | Transcription | |
dc.subject.classification | Molecular biology | |
dc.subject.classification | Developmental biology | |
dc.subject.classification | Statistics | |
dc.title | Signaling dynamics shape gene regulation across scales | |
dc.type | Academic dissertations (Ph.D.) | |
pu.date.classyear | 2021 | |
pu.department | Molecular Biology | |
Appears in Collections: | Molecular Biology |
Files in This Item:
File | Size | Format | |
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Jena_princeton_0181D_13793.pdf | 4.84 MB | Adobe PDF | View/Download |
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