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New Tools for Chemically Directed Glycoproteomics and Xe-based MRI Contrast Agents
Abstract
In recent years, technological advancements in the fields of mass spectrometry (MS) and molecular imaging have enabled scientists to ask and answer questions that once seemed impossibly challenging. For example, advancements in mass spectrometry have made it possible to provide a quantitative description of a human cell proteome, where both the identities and absolute abundances of thousands of proteins are simultaneously and reproducibly calculated. Equivalently, advancements in molecular imaging have made it possible to monitor the dynamics of posttranslational modifications, such as glycosylation, in living organisms.
Inspired by these advancements, this dissertation is divided into two sections that describe chemical approaches for both identifying and imaging biomolecules in living systems. In the first section, the biomolecules of interest are glycoproteins, and I describe chemical tools and computational strategies for identifying glycoproteins through MS. After a brief discussion of the importance of protein glycosylation in Chapter 1, I survey chemical methods that facilitate the study of glycoproteins through MS in Chapter 2. A major theme that emerges from this discussion is that although glycoproteins are highly abundant biomolecules, they exist as a complex mixture of enormously diverse structures, which has made identifying any one member of the population a great analytical challenge.
In Chapter 3, I introduce the concept of chemically directed proteomics. This method is used to direct MS analysis to specific species of interest (regardless of abundance) by chemically tagging them with an identifiable isotopic signature. Towards extending chemically directed proteomics beyond chemical labeling, in Chapter 4 I explore metabolic strategies to incorporate an isotopic signature directly into glycans using a specific mixture of monosaccharide isotopologs.
In the second section, the focus is molecular imaging, and I describe how viral nanoparticles can be used as molecular scaffolds to develop high sensitivity contrast agents for magnetic resonance imaging (MRI). After a brief discussion of the advantageous role that viral nanoparticles have played in the development of gadolinium-based contrast agents in Chapter 5, I then focus on a new class of contrast agents known as xenon biosensors. In Chapter 6, I describe the utility of xenon-based MRI for in vivo image and illustrate that through the combination of hyperpolarization and chemical exchange saturation transfer detection, xenon biosensors can achieve low detection thresholds.
Towards improving the detection sensitivity of xenon MRI further, biosensors can be assembled onto supramolecular scaffolds such as viral nanoparticles. In Chapter 7, I discuss the development of a bacteriophage MS2-based xenon biosensor-the first viral capsid functionalized as a 129Xe-based MRI contrast agent. Subsequently, in Chapter 8, I extend the application of viral capsids from spherical bacteriophage to filamentous bacteriophage by generating an M13 bacteriophage-based xenon biosensor. Bacteriophages where chosen because they are routinely used in phage display techniques for identifying new epitope-targeting groups such as peptides and antibody fragments. Accordingly, in Chapter 9, I describe the development of a phage-based xenon biosensor that possesses antibody fragments for targeted imaging of cancer cells in vitro.
In summary, this dissertation describes a number of chemical approaches for both identifying and imaging biomolecules within biologically relevant environments. In the future, it will be exciting to watch as these tools are further refined and improved upon to address outstanding questions in disease biology. In particular, there are a number of research projects underway to identify cancer-related cell surface glycoproteins that can serve as biomarkers for disease states. Additionally, efforts are underway to apply phage-based xenon biosensors to lung cancer detection and imaging in vivo.
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