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A Novel Class of Liposomal Contrast Agents for Molecular MRI

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A Novel Class of Liposomal Contrast Agents for Molecular MRI LisNRs: A Novel Class of Liposomal Contrast Agents for Molecular MRI by Jacob Cyert Simon B.A., Physics B.A. (Hons.), Molecular and Cell Biology University of California, Berkeley, 2012 Submitted to the Department of Biological Engineering in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Biological Engineering at the Massachusetts Institute of Technology February 2021 © 2021 Massachusetts Institute of Technology. All rights reserved. Signature of Author: Department of Biological Engineering January 12th, 2021 Certified by: Alan Jasanoff Professor of Biological Engineering, Brain and Cognitive Sciences, Nuclear Science and Engineering Thesis Supervisor Accepted by: Katharina Ribbeck Hyman Career Development Professor of Biological Engineering Graduate Program Committee Chair 1 Thesis Committee Accepted by: K. Dane Wittrup C.P. Dubbs Professor of Chemical Engineering and Biological Engineering Thesis Committee Chairman Accepted by: Alan Jasanoff Professor of Biological Engineering Thesis Supervisor Accepted by: Barbara Imperiali Class of 1922 Professor of Biology and Chemistry Thesis Committee Member Accepted by: Peter Caravan Professor of Radiology, Harvard Medical School Co-director, Institute for Innovation in Imaging, Massachusetts General Hospital Thesis Committee Member 2 LisNRs: A Novel Class of Liposomal Contrast Agents for Molecular MRI by Jacob Cyert Simon Submitted to the Department of Biological Engineering On 1/12/2020 in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy in Biological Engineering ABSTRACT Biological systems depend on numerous molecular messengers that transduce information across large distances. Understanding the spatial and temporal dynamics of molecular signaling networks is crucial for the construction of systems- and organism-level models of biological function. Molecular imaging, a technique that employs chemical probes to relay molecular events into spatially-resolved signal changes, is a promising strategy for studying complex molecular signaling networks in situ. Magnetic resonance imaging (MRI) is a leading noninvasive imaging modality that allows for imaging of large volumes of deep tissue with high spatiotemporal resolution. Paramagnetic molecular sensors enable detection of molecular phenomena with MRI (molecular MRI). The scope of molecular MRI experiments thus far, however, has been limited by the modest sensitivity and signal changes provided by existing probes. In this dissertation, I introduce Liposomal Nanoparticle Reporters (LisNRs), a novel class of MRI-detectible sensor that utilizes an innovative contrast mechanism in which reversible modulation of the water permeability of liposomal bilayers simultaneously modulates water access to a large, concentrated pool of conventional T1-weighted MRI contrast agents. This architecture gives rise to significant signal amplification with respect to first-generation MRI probes that rely on stoichiometric sensing mechanisms in which binding of one analyte molecule modulates water access to a single paramagnetic metal ion. I employ two strategies for the signal-dependent modulation of liposomal water permeability. The first approach uses reversible modulation of lipid bilayer fluidity to induce changes in passive bilayer water permeability. To demonstrate this concept, I build Light- LisNR, a photosensitive MRI contrast agent, which I use to map light distribution in the rat brain. The second approach utilizes ligand-gated water-permeable channels to modulate bilayer water permeability. I demonstrate the potential of this strategy for molecular sensing using biotin/streptavidin as a model system. Together, this work introduces and demonstrates a novel platform for sensing with MRI that addresses longstanding challenges of low sensitivity and signal change with existing MRI-detectible probes. Thesis Supervisor: Alan Jasanoff Title: Professor of Biological Engineering 3 Acknowledgements To my advisor, Alan Jasanoff For your kindness, mentorship, and the confidence you showed in me by giving me the freedom to create my own thesis project. To my collaborators, For everything you have contributed to the work presented here. Thanks to Miriam Schwalm for taking Light-LisNR in vivo. Thanks to Nina Hartrampf and Mackenzie Poskus of the Pentelute group for synthesizing Alamethicin. Thanks to Johannes Morstein of the Trauner group for synthesizing azoPC. To the Jasanoff lab, For making the lab such a supportive environment and a great place to work. I feel fortunate to have made so many lasting relationships during my time at MIT. I especially want to recognize Peter Harvey, Ali Barandov, and Greg Thiabaud for teaching me everything I know about chemistry. To my friends, For making my time in Cambridge special. To my family, For everything you have done to help me along the way. I am looking forward to the day we can celebrate this accomplishment together. Most of all, Thanks to my partner, Josephine Dybe, for everything you have done to support me throughout. 4 Table of Contents Background and Introduction .......................................................................................... 6 Modalities for Molecular Imaging ................................................................................. 7 Optical Imaging ......................................................................................................... 7 Radiotracer Imaging ................................................................................................. 9 Magnetic Resonance Imaging (MRI) ...................................................................... 10 Light-LisNR: Sensing Light in Deep Tissue with MRI .................................................... 20 Abstract ...................................................................................................................... 20 Introduction ................................................................................................................ 21 Results ....................................................................................................................... 24 Discussion .................................................................................................................. 30 Materials and Methods ............................................................................................... 32 Ligand-Responsive LisNRs for Molecular MRI .............................................................. 51 Abstract ...................................................................................................................... 51 Introduction ................................................................................................................ 51 Results ....................................................................................................................... 54 Discussion .................................................................................................................. 57 Materials and Methods ............................................................................................... 60 Engineering Binding Proteins for Competitive Sensing ................................................. 67 Abstract ...................................................................................................................... 67 Introduction ................................................................................................................ 67 Results ....................................................................................................................... 70 Discussion .................................................................................................................. 72 Materials and Methods ............................................................................................... 74 Conclusions and Future Directions ............................................................................... 82 Synopsis, Significance, and Impact ........................................................................... 82 Limitations .................................................................................................................. 82 Future Work ............................................................................................................... 84 References .................................................................................................................... 87 5 Background and Introduction Molecular biology seeks to understand the mechanistic basis of biological function at the molecular level with the eventual goal of integrating this detailed information into complete models of biological function from the bottom up. This approach has led to a wealth of accumulated knowledge about the specific function of isolated molecules in simplified experimental conditions, but the integration of such knowledge into models of higher-order biological function, and dysfunction, at organ and organism scales remains a major challenge. Nowhere in modern biology is the difficulty of integrating molecular mechanisms into large-scale models more obvious than in neuroscience. The human brain consists of approximately 100 billion neurons1, each making on average 7000 synaptic connections2, not to mention the important roles of a multitude of supporting cell types like astrocytes, microglia, and oligodendrocytes3. Beyond the sheer complexity of such massive cellular and molecular networks, the
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