Bioorthogonal chemistries have provided methods to investigate biomolecules in their native environments with minimal effects on cellular processes. Efforts to develop new bioorthogonal reactions have equipped researchers with powerful tools to probe complex biological systems. Despite the advancement of these tools, they remain limited in scope. Most bioorthogonal reactions comprise cycloadditions, and many of the key reagents cannot be used simultaneously due to cross reactivity issues. To address these limitations, I have developed new phosphine-based bioorthogonal chemistries with cyclopropenones (CpOs) and methods to deploy the two motifs in biological settings. This talk will focus on chemical activation of CpOs with bioorthogonal phosphines as a general proximity labeling platform.

Bioluminescence imaging with luciferase-luciferin pairs is routinely used to monitor cellular events in real time. This technology relies on enzymes (luciferases) that catalyze the adenylation and oxidation of small molecules (luciferins), resulting in light production. While powerful, this imaging modality has rarely been applied to multicomponent imaging due to a lack of distinguishable probes. Recent efforts have expanded the bioluminescence toolkit by engineering luciferases that selectively react with synthetic substrates (i.e., “orthogonal pairs”). These orthogonal probes comprise sterically and electronically modified luciferins that are selectively processed by mutant luciferases. However, the limited structural diversity among the luciferin analogs precluded the development of larger sets of compatible probes for studying complex processes. Additionally, the origin of selectivity between most orthogonal pairs is unknown, hindering rational design for additional pairs. I have worked on addressing limitations in bioluminescence imaging via three approaches. In one area, I developed a new class of luciferins with disubstituted cores. The disubstituted luciferins could be used in tandem with existing luciferins, including singly modified substrates. In addition, I identified sites that were key for substrate selectivity. In a second project, I explored the molecular basis for selectivity among a robust orthogonal pair. Mutations that contributed to substrate selectivity and thermal stability were identified. These mutations are currently being evaluated in mammalian cells to further verify the role of these sites for selectivity and stability. In the final area, I applied machine learning to identify new compound classes for orthogonal probe development. Luciferin analogs were clustered by similarities in reactivity, where substrates in different groups were orthogonal to each other. Ongoing work will investigate residue hotspots for each compound class to identify starting points for evolution. Collectively, my work addresses key voids in bioluminescence imaging and provides a mechanistic basis for new tool development. Continued advances will allow for multicomponent imaging in complex cellular environments.

Imaging tools have revolutionized our understanding of living systems by allowing researchers to visualize biological features in real time. Among the most popular imaging agents of this sort are the bioluminescent proteins (luciferases). These probes catalyze the oxidation of small molecule substrates (luciferins), releasing non-toxic, non-perturbing visible light in the process. Bioluminescence imaging (BLI) with luciferase-luciferin pairs is well suited for use in tissues and small animals. Since no excitation light is required, there is virtually no background signal. Indeed, BLI has been used to track numerous biological phenomena in vivo, including immune cell homing, tumor cell proliferation, and pathogen egress. Despite its remarkable versatility, bioluminescence lacks the spatial resolution necessary to monitor cell-cell interactions. Furthermore, BLI has been historically limited to monitoring one cell type or biological feature at a time. To address these issues, this dissertation involves engineering new luciferase tools and comprised two main goals: (1) engineering contact-dependent bioluminescent probes to report on cellular communication and (2) generating novel luciferase-luciferin pairs via directed enzyme evolution. Collectively, these tools will enable new studies of immune cell function, host-pathogen dynamics, and numerous other multi-cellular networks in vivo.

Cellular interactions underlie diverse physiological processes. Efforts to image andmanipulate these interactions have provided key insights into how cellular networks maintain homeostasis, as well as influence disease pathophysiologies. However, many strategies provide only “snapshots” of interactions at static time points, limiting investigations into how contacts influence and modulate cellular behavior. Furthermore, many methods have historically relied on fluorescent proteins and small molecule fluorophores, which can be difficult to employ in thick tissues due to the need for an external source of excitation light. Thus, we need new strategies for long-term tracking of cell populations of interest post-contact. These strategies would ideally employ novel optical reporters emitting signals capable of penetrating thick tissues. My work has leveraged bioluminescence, an alternative imaging approach, comprised of enzymes (luciferases) capable of oxidizing small molecules (luciferins) to produce photons of light chemically. Bioluminescence imaging (BLI) with luciferase-luciferin pairs has been used for decades to track biological processes over time, but a lack of sufficiently red-shifted probes has limited applications in thick tissues. Bioluminescence has also garnered interest in recent years as a power source for driving optogenetic circuits. However, generalizable bioluminescent optogenetic toolsets remain elusive. Collectively, this dissertation aimed to address many voids in the imaging toolbox via: 1) engineering strategies for long-term tracking of cellular contact, 2) developing novel, red-shifted luciferase-luciferin pairs, 3) investigating the mechanism of bioluminescence-mediated optogenetics, and 4) employing these strategies to studies of cellular networks. Collectively, my work sets the stage for new discoveries relevant to immune function, cancer biology, and a multitude of other processes driven by cellular interactions in vivo.

Cancer metastases are driven by complex interactions among tumor cells, immune cells, and other cell types. Dissecting the roles of these cells is complicated by the inherent heterogeneity of the tumor environment. Currently we lack the models needed to profile cancer metastasis and monitor disease progression. Improved cancer models can be used in conjunction with noninvasive imaging probes to further visualize specific cell types and cellular interactions that are important to cancer progression in vivo. Bioluminescence is well suited for sensitive, noninvasive imaging in disease models. Bioluminescence relies on enzymes (luciferases) that generate light via the chemical oxidation of small molecule substrates (luciferins). No external excitation source is required, and enough tissue-penetrant light is released, enabling sensitive detection of cells and other biological features. Despite its broad applicability, bioluminescence has historically been limited to monitoring one cell population at a time and lacks the spatial resolution necessary to “see” cellular interactions relevant to cancer progression. This dissertation bridges the need for better methods to study metastatic progression by developing platforms that (1) enable multicomponent bioluminescence imaging in vivo, (2) recapitulate disease progression with new metastatic cancer models, (3) profile comprehensive transcriptome analyses of metastatic disease, and (4) facilitate tumor-immune cell monitoring through engineered imaging probes. Collectively, the imaging methods and models developed in this dissertation enable a more detailed examination of tumor heterogeneity and metastatic disease progression in vivo.

Optical imaging strategies have revolutionized our understanding of living systems. Among the most popular techniques for imaging in whole tissues and organisms is bioluminescence. The most widely used bioluminescent system comprises the luciferase enzyme from the firefly (Fluc) and its small molecule substrate, D-luciferin (D-luc). When introduced into cells, these components produce photons that can be captured by sensitive cameras. Since mammalian cells and tissues produce little to no endogenous light, bioluminescence imaging (BLI) is well suited for use in whole organisms. Despite its sensitivity and broad dynamic range, BLI has largely been limited to imaging one cell type at a time. Multicellular networks have been refractory to BLI owing to lack of distinct luciferase-luciferin probes. BLI also lacks adequate spatial resolution to directly visualize cell-to-cell contacts. To address these voids, my thesis work focused on: (1) developing “caged” luciferins to report on cell-cell interactions and (2) creating novel bioluminescent pairs via luciferin analog synthesis and luciferase enzyme engineering. Collectively, the tools developed from my thesis work will provide a better understanding of complex interactions in vivo.

Bioluminescence imaging using luciferase is a widely used technology. However, its scope is hampered by several limitations, most notably the lack of distinct luciferin-luciferase pairs suitable for multicomponent imaging. I addressed this problem by synthesizing novel luciferins which may be used by luciferase. Furthermore, I developed new techniques to evaluate whether a novel luciferin is intrinsically capable of emitting light.

Bioorthogonal chemical reporters are small functional groups that can be metabolically incorporated into biomolecules by the cell’s native metabolic machinery. These moieties can be covalently modified with probes for detection or isolation. I applied this strategy to profile glycoproteins in Toxoplasma gondii, a prevalent intracellular parasite that infects nearly one-third of the world's population and may cause life-threatening conditions in immunocompromised patients. Using the bioorthogonal chemical reporter strategy, I identified a large, diverse set of glycosylated proteins in T. gondii including some previously unannotated proteins likely involved in modulating host-parasite interactions.

In addition to glycosylated structures, parasites and host cells exchange numerous other metabolites. Simultaneous monitoring of these communication pathways requires multiple cell-compatible reactions that can be used concurrently, or “mutually orthogonal” bioorthogonal chemistries. Unfortunately, the existing toolbox of bioorthogonal chemistries is rather sparse, limiting our ability to look at multiple biomolecules in tandem. As part of Prescher lab, I have contributed to the development of novel chemical reporters for simultaneous profiling of host-pathogen crosstalk. My labmates and I established a new bioorthogonal chemical reaction—a cycloaddition between 1,3-disubstituted cyclopropenes and tetrazines—that can be used in living systems. Excitingly, this reaction can be used in tandem with common azide-alkyne chemistries for multi-component imaging. We also demonstrated that 1,3-disubstituted cyclopropenes can be used concurrently with isomeric cyclopropenes—3,3- cyclopropenes—in biological labeling applications. Both of these molecules harbor unique reaction preferences, enabling them to be used simultaneously. This was noteworthy result, since the structures of these cyclopropenes only differ by the placement of a single methyl group. I also developed another orthogonal chemical reporter for use in multi-component applications: methylene cyclopropane. This molecule exhibits unique cycoaddition reactivities and is poised to join the ranks of useful chemical reporters.

Genetically-encoded fluorescent probes have revolutionized our understanding of biological systems. However, the transition of fluorescent probes in vivo has been hampered by the opacity of tissue and its propensity for autofluorescence. A complementary imaging technology, bioluminescence, does not suffer from these complications because it does not require excitation light. Thus, the technique is exquisitely sensitive–with the ability to see as few as ten cells in a mouse. Bioluminescence relies on luciferase enzymes that catalyze the oxidation of small-molecule substrates (luciferins), releasing photons of light in the process. Unfortunately, the optimal luciferases for in vivo use rely on the same luciferins, precluding studies of more than one feature at a time.

To address this issue, I developed and analyzed a number of new luciferin probes, and created a selection platform to find mutually orthogonal luciferases and luciferins for multicomponent imaging. In contrast to the spectroscopic resolution of fluorescent tools, these probes were designed to exhibit substrate resolution. Combining luciferin analogs and mutant enzymes, we tested 20 luciferins with 207 luciferases, generating 4,140 enzyme-substrate combinations, and thus a potential for more than 4 million possible sets. Since it would be impractical to evaluate these manually, I derived a mathematical quantification of orthogonality to score each potential pairing. Next, I wrote a supercomputer algorithm to search this dataset for the highest-scoring pairs. The software provided a ranked list of mutually orthogonal enzyme-substrate pairs that were biochemically verified. Resolution was maintained when these probes were moved into mouse models, highlighting the speed and accuracy of my approach.

My most recent work focused on increasing the practicality of these tools for preclinical imaging. The major drawbacks of our approach included temporal resolution and background emission. I addressed these issues by utilizing traditional spectral unmixing algorithms to deconvolute substrate signals mathematically. This enabled sequential imaging of substrates, and the ability to resolve smaller numbers of cells. With a top orthogonal pair I "unmixed" gradients of mutant luciferases in bacterial lysate and resolved mixtures of these mutants in mouse tumor models. These tools and algorithm will be useful for visualizing multiple cell types in mouse models.