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dc.contributor.advisorBrodbelt, Jennifer S.
dc.creatorCotham, Victoria Christine
dc.date.accessioned2019-01-30T15:53:12Z
dc.date.available2019-01-30T15:53:12Z
dc.date.created2016-12
dc.date.issued2016-10-06
dc.date.submittedDecember 2016
dc.identifierdoi:10.15781/T2DZ03N7K
dc.identifier.urihttp://hdl.handle.net/2152/72663
dc.description.abstractImmunoglobulin G (IgG) antibodies represent important analytical targets both for their therapeutic properties and for their critical role in the adaptive immune response. While much of the primary structure is conserved across the IgG class, subtle changes in amino acid sequence and the presence or absence of post-translational modifications can have a profound effect on the function and therapeutic potential of a given antibody. As such, there remains a high demand for versatile analytical tools capable of both identification and complete structural characterization of IgGs. The work presented in this dissertation largely focuses on the development of mass spectrometry-based methods for the improved analysis of antibodies. This was accomplished using strategic enzymatic Brodbeltselectivity for regions of particular diagnostic value or to facilitate comprehensive structural characterization. A method based on chromophore-mediated 351 nm UVPD was developed as a means to streamline the identification of antibodies in mixtures by enhancing selectively for the third complementarity determining region of the IgG heavy chain (CDR-H3). The hypervariable sequences within this region serve as the primary determinant of antigen binding specificity and thus provide a molecular signature by which to differentiate unique antibodies. To accomplish this, a highly conserved cysteine residue located in the framework preceding the CDR-H3 region was exploited for selective tagging with an Alexa Fluor 350 (AF350) thiol-selective maleimide. This site-specific tagging combined with strategic enzymatic digestion and 351 nm UVPD allowed selective dissociation of only AF350-labeled peptides for facile discrimination of CDR-H3 sequences within a high-throughput liquid chromatography-tandem mass spectrometry (LC-MS/MS) based workflow. Two variations of middle-down mass spectrometry based on either restricted Lys-C proteolysis or hinge-selective IdeS digestion combined with 193 nm UVPD were used for the characterization of monoclonal antibodies. Both strategies yielded considerably greater diagnostic sequence information when benchmarked against conventional collision- and electron-based activation methods. The Lys-C proteolysis method was found to have considerable implications for the analysis of serological antibody repertoires owing to its facile implementation into high-throughput proteomic workflows and ability to unambiguously differentiate unique CDR-H3 sequences. The development and implementation of a front-end dual spray reactor for high-throughput ion/ion-mediated bioconjugation is demonstrated for the enhanced structural characterization of unmodified and post-translationally modified peptide cations by 193 nm UVPD and CID. The ability to generate ion/ion complexes in real-time followed by efficient covalent conversion allowed integration of the dual spray reactor into a high-throughput LC-MS [superscript n] workflow for rapid derivatization of peptide mixtures.
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.subjectMass spectrometry
dc.subjectAntibodies
dc.subjectIgG
dc.subjectUltraviolet photodissociation
dc.titleMass spectrometry combined with strategic enzymatic digestion, selective derivatization and ultraviolet photodissociation for the identification and characterization of Immunoglobulin G antibodies
dc.typeThesis
dc.date.updated2019-01-30T15:53:13Z
dc.contributor.committeeMemberCrooks, Richard M
dc.contributor.committeeMemberGeorgiou, George
dc.contributor.committeeMemberWebb, Lauren J
dc.contributor.committeeMemberZhang, Yan
dc.description.departmentChemistry
thesis.degree.departmentChemistry
thesis.degree.disciplineChemistry
thesis.degree.grantorThe University of Texas at Austin
thesis.degree.levelDoctoral
thesis.degree.nameDoctor of Philosophy
dc.creator.orcid0000-0002-8757-3869
dc.type.materialtext


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