Ion mobility (IM) spectrometry is a gas-phase electrophoretic technique in which ions are separated on the basis of their relative mobility in the presence of a weak electric field gradient and a buffer gas. Ion mobility-mass spectrometry (IM-MS) has the capability of separating ions based on m/z, size and shape, providing additional structural information compared to using mass spectrometry on its own. In this thesis, IM-MS has been used to investigate organic and organometallic complexes and identify reactants, intermediates and products in reaction mixtures. Collision cross sections (CCS) have been measured for three salen ligands, and their complexes with copper and zinc using travelling-wave ion mobility-mass spectrometry (TWIMS) and drift tube ion mobility-mass spectrometry (DTIMS), allowing a comparative size evaluation of the ligands and complexes. CCS measurements using TWIMS were determined using peptide and TAAH calibration standards with good intra-day and inter-day reproducibility. TWIMS measurements gave significantly larger CCS than DTIMS derived data in helium, indicating that the choice of calibration standards is important in ensuring the accuracy of TWIMS derived CCS measurements. The CCS data obtained from IM-MS measurements have been compared to CCS values obtained from X-ray coordinates and modelled structures. The analysis of small organic and organometallic molecules has been extended to investigations of the potential of IM-MS for reaction monitoring and structural studies of the components of catalytic cycles. Reaction mixtures of an organocatalysed Diels-Alder cycloaddition reaction have been monitored using IM-MS and high-field asymmetric waveform ion mobility-mass spectrometry (FAIMS-MS). Reactant, product, catalyst and reaction intermediates, including an intermediate not previously detected, were identified and the catalyst and intermediates monitored over time. An organometallic catalytic cycle using a palladium catalyst has been analysed using IM-MS and the CCS of reactants, intermediates and products have been measured and compared to theoretical CCS calculations. Good agreement was observed between measured and calculated data. Species not amenable to electrospray ionisation were covalently bound to an ionisable tag containing a quaternary ammonium ion allowing the tagged molecules to be detected by IM-MS.

Les polyoxométallates (POM) sont des composés anioniques constitués par l’assemblage de polyèdres d’oxydes métalliques {MOy}, (avec M, MoVI ou WVI) reliés entre eux par des atomes d'oxygène. Les POM forment ainsi une classe remarquable de clusters d’oxydes métalliques inorganiques nanométriques, avec une grande variété de charges et de structures. Il est possible de former des systèmes hybrides incluant la partie inorganique du POM et une partie organique greffée, permettant d’apporter de nouvelles fonctionnalités aux POM, tel que l’auto-assemblage. Nous avons consacré ces travaux de thèse à la caractérisation de systèmes classiques, hybrides et auto-assemblés de POM par spectrométrie de masse couplée à la spectrométrie à la mobilité ionique (IMS-MS). Une première approche expérimentale par spectrométrie de mobilité ionique en tube de dérive (DTIMS) nous a permis de déterminer les sections efficaces de collisions (CCS) de POM étalons dans l’hélium et dans l’azote. Les CCS des étalons POM nous ont ensuite permis d’étalonner une cellule IMS de type Travelling Wave (TWIMS). L’analyse par IMS-MS de POM hybrides organiques-inorganiques seuls ou en présence de PdCl2 a mis en évidence la présence de systèmes auto-assemblés triangulaires [POM3·cation3], carrés [POM4·cation4] ou pentagonaux [POM5·cation5] avec différents états de charges. Des valeurs de CCS de ces auto-assemblages ont également pu être estimées à partir de l’étalonnage de la cellule TWIMS. Par une approche théorique, nous avons modélisé plusieurs structures de POM standards avec et sans contre-ion tetrabutylammonium (TBA+) par la théorie de la fonctionnelle de la densité (DFT). Les structures optimisées ont été utilisées afin de déterminer des CCS théoriques grâce au logiciel MOBCAL, auquel nous avons incorporé les atomes de molybdène et de tungstène pour lesquels nous avons optimisé de nouveaux paramètres de potentiel de Lennard Jones. La correspondance des CCS expérimentales et théoriques des structures de POM standards offre de nouvelles possibilités pour une attribution structurale pour les POM hybrides auto-assemblés par coordination en présence de cations métalliques. / Polyoxometalates (POM) are anionic compounds formed by the assembly of metal oxide polyhedra {MOy}, (with M, MoVI or WVI) linked together by oxygen atoms. POM thus form a remarkable class of nanometric inorganic metal oxide clusters, with a wide variety of charges and structures. It is possible to form hybrid systems including the inorganic part of the POM and a grafted organic part, allowing new functionalities to be added to the POM, such as selfassembly. We have dedicated this thesis work to the characterization of standards, hybrid and self-assembled POM systems by mass spectrometry coupled to ion mobility spectrometry (IMS-MS). A first experimental approach using drift tube ion mobility spectrometry (DTIMS) allowed us to determine the collision cross sections (CCS) of standard POM in helium and nitrogen. The CCS of the POM standards then allowed us to calibrate an IMS cell of a Travelling Wave ion mobility instrument (TWIMS). The analysis by IMS-MS of organic-inorganic hybrid POMs alone or in the presence of transition metal cations revealed the presence of self-assembled triangular [POM3·cation3], square [POM4·cation4] or pentagonal [POM5·cation5] systems with different charge states. CCS values of these self-assemblies was estimated from the calibration of the TWIMS cell. Using a theoretical approach, we modelled several standard POM structures with and without tetrabutylammonium counterion (TBA+) using density functional theory (DFT). The optimized structures were used to determine theoretical CCS using the trajectory method of the MOBCAL software, in which we incorporated molybdenum and tungsten atoms for which we optimized new Lennard Jones potential parameters. The correspondence of experimental and theoretical CCS of standard POM structures offers new possibilities for structural attribution of self-assembled hybrid POM by coordination in the presence of metal cations.

Metabolomics is the methodical scientific study of biochemical processes associated with the metabolome—which comprises the entire collection of metabolites in any biological entity. Metabolome changes occur as a result of modifications in the genome and proteome, and are, therefore, directly related to cellular phenotype. Thus, metabolomic analysis is capable of providing a snapshot of cellular physiology. Untargeted metabolomics is an impartial, all-inclusive approach for detecting as many metabolites as possible without a priori knowledge of their identity. Hence, it is a valuable exploratory tool capable of providing extensive chemical information for discovery and hypothesis-generation regarding biochemical processes. A history of metabolomics and advances in the field corresponding to improved analytical technologies are described in Chapter 1 of this dissertation. Additionally, Chapter 1 introduces the analytical workflows involved in untargeted metabolomics research to provide a foundation for Chapters 2 – 5. Part I of this dissertation which encompasses Chapters 2 – 3 describes the utilization of mass spectrometry (MS)-based untargeted metabolomic analysis to acquire new insight into cancer detection. There is a knowledge deficit regarding the biochemical processes of the origin and proliferative molecular mechanisms of many types of cancer which has also led to a shortage of sensitive and specific biomarkers. Chapter 2 describes the development of an in vitro diagnostic multivariate index assay (IVDMIA) for prostate cancer (PCa) prediction based on ultra performance liquid chromatography-mass spectrometry (UPLC-MS) metabolic profiling of blood serum samples from 64 PCa patients and 50 healthy individuals. A panel of 40 metabolic spectral features was found to be differential with 92.1% sensitivity, 94.3% specificity, and 93.0% accuracy. The performance of the IVDMIA was higher than the prevalent prostate-specific antigen blood test, thus, highlighting that a combination of multiple discriminant features yields higher predictive power for PCa detection than the univariate analysis of a single marker. Chapter 3 describes two approaches that were taken to investigate metabolic patterns for early detection of ovarian cancer (OC). First, Dicer-Pten double knockout (DKO) mice that phenocopy many of the features of metastatic high-grade serous carcinoma (HGSC) observed in women were studied. Using UPLC-MS, serum samples from 14 early-stage tumor DKO mice and 11 controls were analyzed. Iterative multivariate classification selected 18 metabolites that, when considered as a panel, yielded 100% accuracy, sensitivity, and specificity for early-stage HGSC detection. In the second approach, serum metabolic phenotypes of an early-stage OC pilot patient cohort were characterized. Serum samples were collected from 24 early-stage OC patients and 40 healthy women, and subsequently analyzed using UPLC-MS. Multivariate statistical analysis employing support vector machine learning methods and recursive feature elimination selected a panel of metabolites that differentiated between age-matched samples with 100% cross-validated accuracy, sensitivity, and specificity. This small pilot study demonstrated that metabolic phenotypes may be useful for detecting early-stage OC and, thus, supports conducting larger, more comprehensive studies. Many challenges exist in the field of untargeted metabolomics. Part II of this dissertation which encompasses Chapters 4 – 5 focuses on two specific challenges. While metabolomic data may be used to generate hypothesis concerning biological processes, determining causal relationships within metabolic networks with only metabolomic data is impractical. Proteins play major roles in these networks; therefore, pairing metabolomic information with that acquired from proteomics gives a more comprehensive snapshot of perturbations to metabolic pathways. Chapter 4 describes the integration of MS- and NMR-based metabolomics with proteomics analyses to investigate the role of chemically mediated ecological interactions between Karenia brevis and two diatom competitors, Asterionellopsis glacialis and Thalassiosira pseudonana. This integrated systems biology approach showed that K. brevis allelopathy distinctively perturbed the metabolisms of these two competitors. A. glacialis had a more robust metabolic response to K. brevis allelopathy which may be a result of its repeated exposure to K. brevis blooms in the Gulf of Mexico. However, K. brevis allelopathy disrupted energy metabolism and obstructed cellular protection mechanisms including altering cell membrane components, inhibiting osmoregulation, and increasing oxidative stress in T. pseudonana. This work represents the first instance of metabolites and proteins measured simultaneously to understand the effects of allelopathy or in fact any form of competition. Chromatography is traditionally coupled to MS for untargeted metabolomics studies. While coupling chromatography to MS greatly enhances metabolome analysis due to the orthogonality of the techniques, the lengthy analysis times pose challenges for large metabolomics studies. Consequently, there is still a need for developing higher throughput MS approaches. A rapid metabolic fingerprinting method that utilizes a new transmission mode direct analysis in real time (TM-DART) ambient sampling technique is presented in Chapter 5. The optimization of TM-DART parameters directly affecting metabolite desorption and ionization, such as sample position and ionizing gas desorption temperature, was critical in achieving high sensitivity and detecting a broad mass range of metabolites. In terms of reproducibility, TM-DART compared favorably with traditional probe mode DART analysis, with coefficients of variation as low as 16%. TM-DART MS proved to be a powerful analytical technique for rapid metabolome analysis of human blood sera and was adapted for exhaled breath condensate (EBC) analysis. To determine the feasibility of utilizing TM-DART for metabolomics investigations, TM-DART was interfaced with traveling wave ion mobility spectrometry (TWIMS) time-of-flight (TOF) MS for the analysis of EBC samples from cystic fibrosis patients and healthy controls. TM-DART-TWIMS-TOF MS was able to successfully detect cystic fibrosis in this small sample cohort, thereby, demonstrating it can be employed for probing metabolome changes. Finally, in Chapter 6, a perspective on the presented work is provided along with goals on which future studies may focus.