Cell-Selective Chemoproteomics for Biological Discovery

Citation

Stone, Shannon Elizabeth (2018) Cell-Selective Chemoproteomics for Biological Discovery. Dissertation (Ph.D.), California Institute of Technology. doi:10.7907/Z9V122ZF. https://resolver.caltech.edu/CaltechTHESIS:07222017-155020423

Abstract

Cellular protein synthesis changes rapidly in response to internal and external cues in ways that vary from cell to cell. Global proteomic analyses of microbial communities, tissues, and organisms have provided important insights into the behavior of such systems, but can obscure the diversity of responses characteristic of different cellular subpopulations. Recent advances in cell-specific proteomics—fueled in part by the development of bioorthogonal chemistries, more sensitive mass spectrometers and more advanced mining algorithms—have yielded unprecedented glimpses into how proteins are expressed in space and time. Whereas previous cell-specific proteomic analyses were confined to abundant cells in relatively simple systems, recent advances in chemoproteomics allow researchers to map the protein expression patterns of even rare cells in complex tissues and whole organisms.

Chapter 1 highlights recently developed strategies for cell-selective proteomics, including metabolic labeling strategies such as bioorthogonal noncanonical amino acid tagging (BONCAT). Bioorthogonal noncanonical amino acid tagging (BONCAT) is a chemoproteomic technique that enables temporal labeling of proteins. In cell-selective BONCAT, expressing a mutant aminoacyl-tRNA synthetase under the control of cell-specific genetic elements affords cellular resolution; only cells of interest can selectively incorporate a noncanonical amino acid into proteins for subsequent detection and identification. Chapter 2 details protocols to set up a cell-selective BONCAT system.

While BONCAT had previously been applied to studies of microbial pathogenesis in tissue culture-based models of infection, we sought to further develop the method to identify the proteome of methicillin-resistant Staphylococcus aureus (MRSA) within a mouse model of infection, as detailed in Chapter 3. We used this technique to enrich for staphylococcal proteins made within the host and in addition to finding many factors known to be important for infection, we also found many that had not previously been associated with infection. Screening several of these previously unknown factors in vivo led to the discovery of a novel protein important for MRSA infection. This unbiased approach to cell-selectively label pathogenic proteins during infection could be used as a global discovery tool for novel anti-infective strategies.

In Chapter 4, we combine this cell-selective BONCAT strategy with microbial identification after passive clarity technique (MiPACT) to visualize both staphylococcal protein synthesis and ribosomal RNA within whole skin abscesses during infection. In Chapter 5, we continue developing cell-selective BONCAT to study microbial protein synthesis in the context of a living mouse by extending the system to Bacteroides fragilis, a common human gut commensal.

Finally, cell-selective BONCAT is wholly dependent on the bioorthogonal nature of the azide and its detection reagents. Fishing out an azide-tagged molecule from the rest of the cellular milieu requires optimization of enrichment-based strategies. In Chapter 6, we describe the development of a peptide to quantitate the gain of our enrichments.

While innovations in mass spectrometry and computational algorithms have facilitated the identification and quantification of thousands of proteins simultaneously from complex samples, this abundance of data does not necessarily lead to biological insight. Cell-specific proteomic techniques will play a key role in the identification of the mechanisms that govern cell specialization and that allow organisms to respond to changing environments. Overall, this work demonstrates the power of cell-selective chemoproteomics to ascertain biological insights in complex systems.

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