<p>Mass spectrometry imaging (MSI) is a label-free technique that enables mapping hundreds of molecules in biological samples with high sensitivity and molecular specificity. MSI experiments usually sample a virtual grid of pixels on a sample surface. A full mass spectrum is acquired at each pixel. Typically, a single MSI experiment generates hundreds of thousands of spectra, each containing thousands of molecular features. The size of MSI data keeps increasing with MSI technology improvements in spatial resolution and molecular coverage. Subsequent interpretation of the vast and complex MSI data is a major bottleneck for deriving biological conclusions from the experimental results. In chapter 1, I review recently emerging computational methods in MSI for data analysis and “smart” experiments. I also provide a outlook for a future paradigm shift in MSI with transformative computational methods.<br> </p> <p>In my research, I have developed several approaches for the analysis and mining of the MSI data in a data-driven manner. In chapter 2, I introduce a vendor-neutral data processing pipeline for visualizing ion images from MSI data, which supports both standard and unconventional MSI acquisition strategies. In chapter 3, a spatial segmentation method is described. This method combines matrix factorization and manifold learning to enable the identification of distinct cells or tissue subregions in an unsupervised manner. In chapter 4, I describe a self-supervised approach for identifying and clustering colocalized molecules using contrastive learning, which helps analyze molecular pathways in biological samples. In chapter 5, I introduce a precise image registration method for studying individual fibers in mouse muscle tissue using multimodal MSI and immunofluorescence imaging. The locations of different types of muscle fibers obtained from immunofluorescence images are registered to MSI space, which enables biomarker discovery based on spatially resolved metabolomics and lipidomics data.</p> <p><br> Computational methods also provide powerful strategies for enhancing MSI capabilities, such as throughput, molecular coverage, and specificity. In chapter 6, I describe a “smart” sampling method for enhancing the experimental throughput of MSI. In collaboration with Prof. Dong Hye Ye’s group at Marquette University, we have developed a deep learning algorithm for sparse sampling (DLADS), which dynamically estimates molecularly informative tissue locations and guides sampling in MSI experiments. We coupled DLADS with nanospray desorption electrospray ionization (nano DESI) MSI platform through software and hardware integration. This approach preferentially samples informative tissue locations and reconstructs high-fidelity\ ion images with sparse MSI data, which improves the throughput of nano-DESI MSI experiments by 2.3-fold.<br>  </p>

Mass spectrometry imaging (MSI) is a high-throughput technique that in addition to performing protein identification, can capture the spatial localization of proteins within biological tissue. Nevertheless, sample pre-processing and MSI instrumentation limit protein identification capability in MSI compared to more standard tandem mass spectrometry-based proteomics methods. Despite these limitations, the current protein identification approaches used in MSI were originally designed for standard mass spectrometry-based proteomics and do not take advantage of the spatial information acquired in MSI. Herein, I explore the benefit of using the spatial spectral information for protein identification using two objectives. For the first objective, I developed a novel supervised learning spatially-aware protein identification algorithm (SAPID) for mass spectrometry imaging and benchmarked it against ProteinProphet and Percolator, which are state-of-the-art tools for protein identification confidence assessment. I showed that SAPID identifies on average 20% more proteins at <1% false discovery rate compared to the other two algorithms.Furthermore, more proteins are identified when spatial features are used to identify proteins compared to when they are not suggesting their additional benefit. For the second objective, I used SAPID to rescue false positive and false negative protein identifications made by ProteinProphet. By examining a combination of data sampling and learning algorithms, I was able to achieve a good classification performance compared to the baseline given the extremeimbalance in the dataset. Finally, by improving proteome characterization in MSI, our approach will help providing a better understanding of the processes taking place in biological tissues.

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<p> Mass spectrometry imaging (MSI) is an advanced analytical technique that renders spatially defined images of complex label-free samples. Nanospray desorption electrospray ionization (nano-DESI) MSI is an ambient ionization direct liquid extraction technique in which analytes are extracted by means of a continuous liquid flow between two fused-silica capillaries. The droplet generated between the two capillaries is controlled by a delicate balance of solvent flow, solvent aspiration, capillary angles, and distance from the surface. This technique produces reproducible ion images with up to 10 µm resolution and can be used to identify and quantify multiple analytes on a given surface.  This thesis discusses some of the applications of this technique to biological systems, as well as the work done to develop methodology to further improve this technique’s specificity and sensitivity. Herein, applications that push the limits of the current capabilities of nano-DESI are presented, such as the high-resolution imaging of lipid species in skeletal muscle at the single-fiber level, and the quantification of low-abundance drug metabolites.  The second theme of this thesis, developing new capabilities, introduces ion mobility mass spectrometry imaging. This integrated technique increases the selectivity previously possible with MSI. To support these efforts, the work in this thesis has generated data analysis workflows that not only make these experiments possible but also further endeavor to increase sensitivity and combat instrument limitations on mobility resolution. Finally, this thesis present streamlined workflows for tandem MS experiments and modifications to a recently introduced microfluidic variant of the nano-DESI technique. In all, this thesis showcases the current capabilities of the nano-DESI technique and lays the groundwork for future improvements and capabilities.      </p>

Mass spectrometry imaging (MSI) has been extensively used to produce qualitative maps of distributions of proteins, peptides, lipids, neurotransmitters, small molecule pharmaceuticals and their metabolites directly in biological tissue sections. Moreover, during the last 10 years, there has been growing demand to quantify target compounds in tissue sections of various organs. This thesis focuses on development and application of a novel instrument- and manufacturer-independent MSI software suite, msIQuant, in the open access format imzML, which has been developed specifically for quantitative analysis of MSI data. The functionality of msIQuant facilitates automatic generation of calibration curves from series of standards that can be used to determine concentrations of specific analytes. In addition, it provides many tools for image visualization, including modules enabling multiple interpolation, low intensity transparency display, and image fusion and sharpening. Moreover, algorithms and advanced data management modules in msIQuant facilitate management of the large datasets generated following rapid recent increases in the mass and spatial resolutions of MSI instruments, by using spectra transposition and data entropy reduction (at four selectable levels: coarse, medium, fine or superfine) before lossless compression of the data. As described in the thesis, implementation of msIQuant has been exemplified in both quantitative (relative or absolute) and qualitative analyses of distributions of neurotransmitters, endogenous substances and pharmaceutical drugs in brain tissue sections. Our laboratory have developed a molecular-specific approach for the simultaneous imaging and quantitation of multiple neurotransmitters, precursors, and metabolites, such as tyrosine, tryptamine, tyramine, phenethylamine, dopamine, 3-methoxytyramine, serotonin, gamma-aminobutyric acid (GABA), and acetylcholine, in histological tissue sections at high spatial resolution by matrix-assisted laser desorption ionization (MALDI) and desorption electrospray ionization (DESI) MSI. Chemical derivatization by charge-tagging primary amines of analytes significantly increased the sensitivity, enabling mapping of neurotransmitters that were not previously detectable by MSI. The two MSI approaches have been used to directly measure changes in neurotransmitter levels in specific brain structures in animal disease models, which facilitates understanding of biochemical mechanisms of drug treatments. In summary, msIQuant software has proven potency (particularly in combination with the reported derivatization technique) for both qualitative and quantitative analyses. Further developments will enable its implementation in multiple operating system platforms and use for statistical analysis.

L’oxygénation d’un tissu ou d’une cellule résulte d’un équilibre entre la disponibilité en oxygène et sa consommation. Un arrêt de la circulation ou des variations de la pression partielle en oxygène sont responsables d’une réduction de l’apport en oxygène induisant une réponse adaptative.L’objectif de ce travail a été de caractériser l’hypoxie de l’échelle cellulaire à tissulaire par la complémentarité de deux techniques d’imagerie par spectrométrie de masse (ISM) : La spectrométrie de masse à ionisation secondaire (SIMS) et l’ionisation/désorption par laser assistée par matrice (MALDI). L’ISM fournit la détection, l’identification et la distribution d’une variété d’espèces moléculaires endogènes et exogènes directement sur tissu sans marquage. Afin de caractériser l’hypoxie, un modèle in vitro de culture cellulaire en trois dimensions (sphéroïde) et un modèle in vivo d’accident vasculaire cérébral ont été utilisés.L’imagerie TOF-SIMS nous a permis de voir que la disponibilité réduite de l’oxygène au centre des sphéroides induit de profonds changements métaboliques. L’imagerie MALDI-TOF, quant à elle, a permis de visualiser la pharmacocinétique de différents traitements dans des sphéroides traités.Concernant l’étude sur l’accident vasculaire cérébral, l’imagerie SIMS et MALDI nous ont fourni une signature moléculaire de l’hypoxie tissulaire, apportant de nouvelles connaissances sur les changements physiopathologiques induits par la lésion tissulaire.La complémentarité de ces deux techniques d’imagerie permet donc une réelle synergie pour l’étude de l’hypoxie dans différents modèles. / Tissue or cells oxygenation results from a balance between oxygen availability and consumption. This availability is determined by the amount of oxygen carried by the blood irrigating the tissue and its diffusion capacity through the cell membranes. The interruption of blood flow or variations in the oxygen partial pressure are responsible for a reduction of oxygen intake that induces an adaptive response.The aim of my work is to characterize the hypoxia from cellular to tissue-level via the complementarity of two mass spectrometry imaging (MSI) methods: the Secondary Ion Mass Spectrometry (SIMS) and Matrix-Assisted Laser Desorption and Ionization (MALDI). MSI has the potential to provide detection, identification and distribution of a variety of different endogenous and exogenous molecular species directly from the tissue without labelling. Here we combine them to characterize hypoxia in vitro on a 3D cell culture system (spheroid) and in vivo using ischemic rat model.We have shown via TOF-SIMS imaging that reduced availability of oxygen to the center of spheroids induces profound metabolic changes. MALDI-TOF imaging helped to visualize the pharmacokinetics of different treatments in treated spheroids.Concerning the ischemic stroke, MSI provides a molecular signature of hypoxia in tissue, which could bring new insights into the pathological changes induced by the tissue injury.The complementarity of these two imaging techniques allows real synergy for the study of hypoxia in different models.

Secondary Ion Mass Spectrometry (SIMS) is a powerful technique for high spatial resolution chemical mapping and characterization of native surfaces. The use of massive cluster projectiles has been shown to extend the applicable mass range of SIMS and improve secondary ion yields 100 fold or beyond. These large projectiles however, present a challenge in terms of focusing due to the initial spatial and kinetic energy spreads inherent to their generation. In the present work, we describe the development and construction of a novel primary ion (PI) column employing a gold nanoparticle – liquid metal ion source (AuNP-LMIS) and the coupling to ultrahigh resolution mass spectrometers (e.g., Fourier Transform Ion Cyclotron Resonance Mass Spectrometer, FT-ICR MS) for accurate chemical characterization of complex biological surfaces. This work describes the ion dynamics, development and the experimental characterization of the AuNP-LMIS.

ToF-SIMS imaging has been drawing attention due to the wide range of applications in the biological and biomedical fields. These applications include the acquisition of quantitative and qualitative data that ranges in scale from single cells to organs, image visualisation and interpretation of biomarkers for diagnosis and development of pharmaceutics. This study focused on molecular imaging of mouse brain tissue sections using cluster primary ion beams. First, cluster ion beams were applied to comparative background studies of biomolecules and brain total lipid extract. Enhancement of the secondary ion signal was observed using water-containing cluster primary ion beams, especially for [M+H]+ type secondary ions. Water-containing clusters were then used to acquire ToF-SIMS images from the cerebellar area of serial mouse brain tissue sections. Again, water-containing cluster beams produced the highest secondary ion yields in both grey and white matter, gaining a new level of insight into the lipid compositions of both types of tissue in the brain. A clinical case was also evaluated with ToF-SIMS imaging, using cluster beams for the analysis of 3xTg-AD mouse brain tissue. SIMS images were registered with fluorescence microscopy images for the in situ identification and co-localisation of the Amyloid-β plaques on the SIMS images. Spectra from regions of interest were analysed to identify possible ion fragments derived from the Aβ protein. The co-localisation of cholesterol was also studied from images obtained with different primary ion beams. The results presented show that cluster ToF-SIMS can be successfully applied to brain tissue imaging. New primary ion beam technologies allow us to acquire data with more useful secondary ion yield for clinical applications and biological research. Nevertheless, future technological improvements are required for specialised applications e.g. cellular imaging. Moreover, processing the data obtained is still challenging and more data processing tools are also needed for interpretation.

Cette thèse a été consacrée à l’amélioration de méthodes en imagerie par spectrométrie de masse, et à leur utilisation pour l’analyse in situ de substances naturelles. Une première partie a été consacrée à développer une nouvelle méthode permettant d’acquérir en imagerie TOF-SIMS des images avec une résolution de 400 nm tout en préservant la résolution en masse. Pour cela, une extraction retardée des ions secondaires a été caractérisée et optimisée. Une seconde partie a eu pour objectif d’étudier le phénomène de duraminisation d’un arbre tropical de l’espèce Dicorynia guianensis, qui est l’un des plus exploités en Guyane française et dont le duramen est réputé être imputrescible. Les images par spectrométrie de masse TOF-SIMS enregistrées avec la méthode développée ont montré à l’échelle sub-micrométrique les changements métaboliques s’opérant autour de la zone de transition, où s’opère la duraminisation. Les techniques TOF-SIMS et MALDI-TOF ont ensuite été utilisées pour l’analyse d’une surface sur laquelle ont crû deux souches microbiennes en compétition. Les deux souches ont été extraites d’un if japonais (Cephalotaxus harringtonia), l’une étant un champignon endophyte (Paraconiothyrium variabile) et l’autre une bactérie pathogène à ce conifère (Bacillus subtilis). Les résultats ont montré que le champignon était capable d’hydrolyser les surfactines produites par la bactérie. Enfin, les imageries par spectrométrie de masse MALDI-TOF et TOF-SIMS sont deux méthodes de choix pour l’étude de modèle in vitro de ce qui pourrait se produire in vivo. / This thesis was devoted to the improvement of mass spectrometry imaging methods, and to their use for in situ analysis of natural substances. The first part of this thesis has been dedicated to the development of a new acquisition mode in TOF-SIMS imaging able to acquire images with a high spatial resolution of 400 nm while keeping a good mass resolution. For that, a delayed extraction of the secondary ions has been characterized and optimized. Then, a second part has been dedicated to the study of heartwood production in a tropical species named Dicorynia guianensis. This species is one of the most exploited in French Guiana for its heartwood which exhibits a good durability. Metabolic changes are shown by sub-micrometric resolution ion images recorded in and around the transition zone, where the heartwood formation occurs. Then, TOF-SIMS and MALDI-TOF have both been used to analyse the surface of a bacterial competition. Species have been isolated from a Japanese conifer (Cephalotaxus harringtonia), from which the stains are an endophitic fungi (Paraconiothyrium variabile) and a pathogenic bacteria of the conifer (Bacillus subtilis). The results have shown that the fungus is able to hydrolyze surfactines produced by the bacteria during the competition. Furthermore, both the MALDI-TOF and the TOF-SIMS mass spectrometry imaging are methods of choice to study in vitro models of what could happen in vivo.

L'imagerie par spectrométrie de masse est d’un grand intérêt pour aborder les questions biologiques en fournissant simultanément des informations chimiques et spatiales. En particulier, la spectrométrie de masse baptisée TOF-SIMS est bien reconnue par sa haute résolution spatiale (< 1 μm), qui est essentielle pour révéler l'information chimique dans une zone submicronique. L'emploi croissant de cette technique dans la caractérisation des échantillons biologiques a bénéficié du développement de nouvelles sources d'ions d’agrégats. Cependant, les processus d'ionisation/désorption des analytes sous les impacts d’agrégats lourds sont encore mal compris. D'un autre côté, techniquement, les instruments TOF-SIMS commerciaux actuels ne peuvent pas fournir une résolution en masse suffisante ni une précision sur la détermination de la masse pour l'identification moléculaire, ce qui rend les analyses de systèmes biologiques complexes très difficiles, et nécessite le recours à la fragmentation MS/MS. Cette thèse vise à mieux comprendre la production d'ions sous l’impact d’agrégats lourds et à explorer la capacité MS/MS du spectromètre de masse par temps de vol combiné à l’imagerie ionique en utilisant le spectromètre de masse PHI nanoTOF II. Ce dernier point a été réalisé en cartographiant en haute résolution spatiale des métabolites importants de bois. Pour comprendre la production d'ions sous les impacts d’agrégats d'argon massifs, l'énergie interne des ions secondaires a été mesurée en utilisant la mesure du taux de survie d'une série d'ions benzylpyridinium. L'étude de diverses conditions d'impact (énergie, vitesse, taille des agrégats) a montré que la vitesse joue le rôle majeur dans la distribution d'énergie interne et la fragmentation moléculaire dans le régime à faible énergie par atome (E/n < 10 eV).Les capacités de la fragmentation MS/MS et d'imagerie en parallèle du spectromètre PHI nanoTOF II nouvellement conçu ont été évalués par cartographie MS/MS in situ des métabolites bioactifs rubrynolide et rubrenolide dans les espèces amazoniennes de bois Sextonia rubra, ainsi qu’une identification in situ des métabolites précurseurs. L'imagerie TOF-SIMS 2D et 3D a permis de localiser les cellules où cette biosynthèse s’effectue. Les résultats ont conduit à la proposition d'une voie possible de biosynthèse des deux métabolites. Pour étendre l'application de l'imagerie TOF-SIMS dans l'analyse chimique du bois, la distribution radiale des extraits de bois dans le duramen du bois du mélèze européen a également été étudiée. / Mass spectrometry imaging has been shown of great interest in addressing biological questions by providing simultaneously chemical and spatial information. Particularly, TOF-SIMS is well recognized for its high spatial resolution (< 1 µm) which is essential in disclosing chemical information within a submicron area. The increasing use of TOF-SIMS in characterizing biological samples has greatly benefited from the introduction of new cluster ion sources. However, the ionization/desorption of the analytes under impacts of large clusters is still poorly understood. On the other hand, technically, current commercial TOF-SIMS instruments generally cannot provide sufficient mass resolution or mass accuracy for molecular identification, making analyses of complex biological systems especially challenging when no MS/MS fragmentation is available. Thus this thesis is aimed to get a better understanding of ion production under cluster impacts, to explore the MS/MS capability of the parallel imaging MS/MS Spectrometer (PHI nanoTOF II), as well as to apply TOF-SIMS to map important wood metabolites with high spatial resolution.In order to understand ion production under impacts of massive argon clusters, internal energy distributions of secondary ions were measured using survival yield method which involves the analyses of a series of benzylpyridinium ions. Investigation of various impacting conditions (energy, velocity, cluster size) suggested that velocity of the clusters play a major role in internal energy distribution and molecular fragmentation in the low energy per atom regime (E/n < 10 eV). The MS/MS fragmentation and parallel imaging capabilities of the newly designed PHI nanoTOF II spectrometer were evaluated by in situ MS/MS mapping of bioactive metabolites rubrynolide and rubrenolide in Amazonia wood species Sextonia rubra. Then this parallel imaging MS/MS technique was applied to perform in situ identification of related precursor metabolites in the same tree species. 2D and 3D TOF-SIMS imaging were carried out to target the plant cells that biosynthesize rubrynolide and rubrenolide. The results led to the proposal of a possible biosynthesis pathway of these two metabolites. In addition, to expand the application of TOF-SIMS imaging in wood chemistry analysis, radial distribution of wood extractives in the heartwood of European larch was also investigated.