The characterization of biomolecules and biomolecular complexes represents an area of significant research activity because of the link between structure and function. Drug development relies on structural information in order to target certain domains. Many traditional biochemical techniques, however, are limited by their ability to characterize only certain stable forms of a molecule. As a result, multidimensional approaches, such as ion mobility mass spectrometry coupled to mass spectrometry (IMS-MS), are becoming very attractive tools as they provide fast separation, detection and identification of molecules, in addition to providing three-dimensional shape for structural elucidation. The present work expands the use and application of trapped ion mobility spectrometry-coupled to mass spectrometry (TIMS-MS) by analyzing a range of biomolecules (including proteoforms, intrinsically disordered peptides, DNA and molecular complexes). The aim is to i) evaluate the TIMS platform measuring sensitivity, selectivity, and separation of targeted compounds, ii) pioneer new applications of TIMS for a more efficient and higher throughput methodologies for identification and characterization of biomolecular ions, and iii) characterize the dynamics of selected biomolecules for insight into the folding pathways and the intra-or intermolecular interactions that define their conformational space.

The complexity of biological matrices makes the detection and quantification of compounds of interest challenging. For successful targeted or untargeted identification of compounds within a biological environment, the use of complementary separation techniques is routinely required; in many situations, a single analytical technique is not sufficient. In the present dissertation, a multidimensional analytical technique was developed and evaluated, a combination of new sample preparation/extraction protocols, liquid chromatography, trapped ion mobility and mass spectrometry (e.g., LC-TIMS-MS and LC-TIMS-MS/MS). The performance of these techniques was evaluated for the detection of polybrominated diphenyl ethers metabolites, polychlorinated biphenyls metabolites in human plasma, opioid metabolites in human urine, and lipids in Dictyostelium discoideum cells. The new workflows and methods described in the body of this dissertation allows for rapid, selective, sensitive and high-resolution detection of biomarkers in biological matrices with increased confidence, sensitivity and shorter sample preparation and analysis time.

This dissertation focuses on the development of analytical methods based on Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) and their applications for separation and structural characterization of oligosaccharides. Porous graphitized carbon liquid chromatography (PGC-LC), gated-trapped ion mobility spectrometry (Gated-TIMS), and electronic excitation dissociation tandem mass spectrometry (EED MS/MS) are three essential techniques employed here. First, the EED method was optimized to generate more informative glycan tandem mass spectra for accurate structural analysis. Glycans were reduced and permethylated or labeled with a reducing-end fixed charge to increase sensitivity, avoid gas-phase structural rearrangement, and facilitate spectral interpretation. EED of glycans produced nearly complete series of Z-, Y- and 1,5X-ions, that appear in the spectra as triplets with characteristic spacing, thus facilitating accurate determination of the glycan topology. Additional radical-driven dissociation pathways were identified, from which different types of linkage-diagnostic ions (cross-ring, secondary, or internal fragments) were generated. The results demonstrated that linkage analysis can be accomplished by utilizing one or a combination of several linkage-diagnostic fragments. EED MS/MS was then implemented, in conjunction with PGC-LC or Gated-TIMS, for on-line separation and characterization of complex mixtures of glycans. These two methods were successfully applied for high-throughput and detailed structural analysis of N-glycans released from human serum, O-glycans released from bovine submaxillary mucin and free oligosaccharides. The performance of these methods was tested and improved through analysis of different types of glycans from a variety of biological sources. Finally, in collaboration with bioinformaticians, a spectral interpretation algorithm, GlycoDeNovo, has been developed for automated and de novo glycan topology reconstruction from their tandem mass spectra. A large number of EED tandem spectra of glycan standards generated in house were used as the training dataset to establish appropriate IonClassifiers for candidate ranking. GlycoDeNovo is capable of identifying correct topologies from MS/MS spectra of glycans in different derivatized forms. Several aspects of this collaborative project were covered in this thesis, including glycan derivatization, data acquisition and manual spectral interpretation to guide the development and evaluate the performance of the automated approach. In this thesis research, integrated approaches utilizing PGC-LC–EED-MS/MS and Gated-TIMS–EED-MS/MS, and the appropriate bioinformatics software, have been established for structural analysis of glycan mixtures. They hold great potential for comprehensive, automated, and de novo glycome characterization.