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Title: Measuring Biomolecular Dynamics Using Single-Molecule Fluorescence in an Anti-Brownian Trap
Authors: Wilson, Hugh Sutcliffe
Advisors: WangYang, QuanHaw
Contributors: Quantitative Computational Biology Department
Keywords: ABEL trap
Biomolecular structural dynamics
Subjects: Biophysics
Physical chemistry
Issue Date: 2022
Publisher: Princeton, NJ : Princeton University
Abstract: Dynamic biomolecular assemblies underpin diverse functions central to life. A long-standing paradigm in molecular biology is that structure determines function, and many powerful experimental and computational tools can provide snapshots of biomolecular structure. However, beyond the snapshot of a given structure, dynamic changes also hold critical information to fully understand function. Despite this, there is currently no measurement platform that can follow the structural dynamics and interactions of a biomolecule or assembly over its entire functional cycle in solution. To address this gap, this dissertation develops a new measurement platform which combines measurements of nanoscale structural dynamics using single-molecule Förster resonance energy transfer (FRET) with a device known as the Anti-Brownian Electrokinetic (ABEL) trap. This trap enables extended observation of individual molecules in solution and detection of their interactions through measurement of single-molecule transport coefficients. New algorithms for data analysis are also developed and applications to a range of protein-nucleic acid interactions are demonstrated. First, I describe the development of the new measurement platform. The platform achieves high precision in measuring FRET from single molecules, which enables clear resolution of small differences in biomolecular structure. Furthermore, combining this high-precision with measurement of single-molecule transport coefficients provides simultaneous access to the assembly state and conformation of biomolecules interacting in solution. Next, I outline a new data analysis algorithm to detect state changes in multichannel data. The algorithm builds on an existing log-likelihood-ratio-test framework for detecting change points and extends it to work with multiple measurement channels with different noise statistics and time resolution. This extension successfully enables detection of correlated and uncorrelated changes across multiple channels of simulated data. I also demonstrate the capability to detect changes in biomolecular conformation and assembly state on example measurements. Last, I apply the new measurement platform and data analysis tools to study the conformational heterogeneity of RNA during assembly of the CRISPR/Cas9 ribonucleoprotein. I demonstrate the ability to resolve multiple states along the assembly pathway and show that a different dynamic ensemble of RNA conformations exists at each assembly stage.
Alternate format: The Mudd Manuscript Library retains one bound copy of each dissertation. Search for these copies in the library's main catalog:
Type of Material: Academic dissertations (Ph.D.)
Language: en
Appears in Collections:Quantitative Computational Biology

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