Tesis sobre el tema "Imaging by mass spectrometry"

This work investigates the applicability of fast detectors to the technique of microscope-mode imaging mass spectrometry. By ionising analyte from a large area of the sample, and projecting the desorbed ions by the use of ion optics through a time-of-flight mass spectrometer onto a two- dimensional detector, time- (and hence mass-) dependent distributions of ions may be imaged. To date, this method of imaging mass spectrometry has been limited by the ability to image only one mass window of interest per experimental cycle, limiting throughput and processing speed. Thus, the alternative microprobe-mode imaging mass spectrometry is currently the dominant method of analysis, with its superior mass resolution. The application of fast detectors to microscope-mode imaging lifts the restriction of the detection of a single mass window per experimental cycle, potentially decreasing acquisition time by a factor of the number of mass peaks of interest. Additional advantages include the reduction of sample damage by laser ablation, and the potential identification of coincident eo-fragments of different masses originating from the same parent molecule. Theoretical calculations and simulations have been performed confirming the suitability of conventional time-of-flight velocity-mapped ion imaging apparatus for imaging mass spectrometry. Only small modifications to the repeller plate and laser beam path, together with the adjustment of the accelerating potential field, were required to convert the apparatus to a wide (7 mm diameter) field-of-view ion microscope. Factors affecting the mass and spatial resolution were investigated with these theoretical calculations, with theoretical calculations predicting a spatial resolution of about 26μm and m/m of 93. Typical experimental data collected from velocity-mapped ion imaging experiments were collected, and characterised in order to provide specifications for a novel time-stamping detector, the Pixel Imaging Mass Spectrometry detector. From these data, the suitability of thresholding and centroiding on the new detector was determined. Initial experiments using desorptionjionisation on silicon and conventional charge-coupled device cameras confirmed the correct spatial-mapping of the apparatus. Matrix-assisted laser desorptionjionisation techniques (MALDI) were used in experiments to determine the spatial and mass resolutions attainable with the apparatus. Experimental spatial resolutions of 14.4 μm and m/m of 60 were found. The better experimental spatial resolution indicates a higher di- rectionality of initial velocities from MALDI desorption than used in the theoretical predictions, while the poorer mass resolution could be attributed to limitations imposed by the use of the phosphor screen. Proof-of-concept experiments using fast-framing cameras and the new time-stamping detectors confirmed the feasibility of multiple mass acquisition in time-of-flight microscope mode ion imaging. Mass-dependent distributions were acquired of different pigment distributions in each experimental cycle. Finally, spatial-mapped images of coronal mouse brain sections were acquired using both conventional and fast detectors. The apparatus was demonstrated to provide accurate spatial distributions with a wide field-of-view, and multiple mass distributions were acquired with each experimental cycle using the new time-stamping detector.

Glucocorticoids are steroid hormones involved in the stress response, with a well-established role in promoting cardiovascular risk factors including obesity and diabetes. The focus of glucocorticoid research has shifted from understanding control of blood levels, to understanding the factors that control tissue steroid concentrations available for receptor activation; it is disruption of these tissue-specific factors that has emerged as underpinning pathophysiological mechanisms in cardiovascular risk, and revealed potential therapeutic targets. However, the field is hampered by the inability at present to measure concentrations of steroid within individual tissues and indeed within component cell types. This research project explores the potential for steroid measurements using mass spectrometry-based tissue imaging techniques combining matrix assisted laser desorption ionization with on-tissue derivatisation with Girard T and Fourier Transform Ion Cyclotron Resonance Mass Spectrometry (OTCD-MALDIFTICRMS). A mass spectrometry imaging (MSI) platform was developed and validated to quantify inert substrate and active product (11-dehydrocorticosterone (11DHC), corticosterone (CORT) respectively) of the glucocorticoid-amplifying enzyme 11β-hydroxysteroid dehydrogenase type 1 (11β-HSD1) in rodent tissues. A novel approach to derivatising keto-steroids in tissue sections using Girard T reagent was developed and validated. Signals were boosted (10⁴ fold) by formation of GirT hydrazones compared to non-derivatised neutral steroids. Active and inert glucocorticoids were detected in a variety of tissues, including adrenal gland and brain; in the latter, highest abundance was found in the cortex and hippocampus. The MSI platform was also applied to human biopsies and murine tissues for the analysis of other ketosterols such as androgens and oxysterols. Proof-of-principle validation that the MSI platform could be used to quantify differences in enzyme activity was carried out by following in vivo manipulation of 11β-HSD1. Regional steroid distribution of both substrate and product were imaged at 150-200μm resolution in mouse brain sections, and the identification confirmed by collision induced dissociation/liquid extraction surface analysis (CID-LESA). To validate the technique, the CORT/11DHC ratios (active/inert) were determined in 11β- HSD1 deficient mice and found to be reduced (KO vs WT; cortex (49 %*); hippocampus (46 %*); amygdala (57 %)). Following pharmacological inhibition by administration of UE2316, drug levels peaked at 1 h in tissue and at this time point, a reduction in CORT/11DHC ratios were also determined, although to a lesser degree than in KO mice, cortex (22%), hippocampus (25 %) and amygdala (33 %). The changes in ratios appeared driven by accumulation of DHC, the enzyme substrate. In brains of mice with 11β-HSD1 deficiency or inhibition, decreases in sub-regional CORT/11DHC ratio were quantified, as well as accumulation of an alternative 11β- HSD1 substrate, 7-ketocholesterol. MSI data correlated well with the standard liquid chromatography tandem mass spectrometry (LC-MS/MS) in whole brain homogenates. Subsequently, the MSI platform was also applied to measure the dynamic turnover of glucocorticoids by 11β-HSD1 in metabolic tissues using stable isotope tracers (Cortisol-D4 (9,11,12,12-D4) (D4F). D4F was detected in plasma, liver and brain after 6 h infusion and after 48 h in adipose. D3F generation was detected at 6 h in plasma and liver; at 24 h in brain specifically in cortex, hippocampus and amygdala; and at 48 h in adipose. The spatial distribution of d3F generation in brain by MSI closely matched enzyme localisation. In liver, an 11β-HSD1-riched tissue, substantial generation of d3F was detected, with a difference in d4F/d3F ratios compared with plasma (ᴧTTRᴧ 0.18± 0.03 (6 h), 0.27± 0.05 (24 h) and 0.38±0.04 (48 h)). A smaller difference in TTR was also detected between plasma and brain (ᴧTTR 0.09 ± 0.03 (24 h), 0.13±0.04 (48 h)), with no detectable regeneration in adipose. After genetic disruption of 11β-HSD1, d3F generation was not detected in plasma or any tissues, suggesting that 11β-HSD1 is the only enzyme carrying out this reaction. After pharmacological inhibition, a similar pattern was seen. The circulating concentration of drug peaked at 2 h and declined towards 4 h, with same pattern in liver and brain. The ᴧTTR ratios 2HPD between plasma and liver (0.27±0.08vs. 0.45± 0.04) and brain (0.11±0.2 vs. 0.19± 0.04) were smaller following drug administration than vehicle, indicating less d3F generation. Extent of enzyme inhibition in liver responded quickly to the declining drug, with ᴧTTR returning to normal by 4 h (0.38± 0.06). ᴧTTR had not normalised 4HPD in brain (0.12±0.02, suggesting buffering of this pool. In adipose, UE2316 was not detected and nor were rates of d3F altered by the drug. Two possible phase I CYP450 metabolites were identified in the brain differing in spatial distribution. In conclusion, MSI with on-tissue derivatisation is a powerful new tool to study the regional variation in abundance of steroids within tissues. We have demonstrated that keto-steroids can be studied by MALDI-MSI by using the chemical derivatisation method developed here and exemplified its utility for measuring pharmacodynamic effects of small molecule inhibitors of 11β-HSD1. This approach offers the prospect of many novel insights into tissue-specific steroid and sterol biology.

Mass Spectrometry Imaging (MSI) is a sensitive analytical tool for detecting and spatially localising thousands of ions generated across intact tissue samples. The datasets produced by MSI are large both in the number of measurements collected and the total data volume, which effectively prohibits manual analysis and interpretation. However, these datasets can provide insights into tissue composition and variation, and can help identify markers of health and disease, so the development of computational methods are required to aid their interpretation. To address the challenges of high dimensional data, randomised methods were explored for making data analysis tractable and were found to provide a powerful set of tools for applying automated analysis to MSI datasets. Random projections provided over 90% dimensionality reduction of MALDI MSI datasets, making them amenable to visualisation by image segmentation. Randomised basis construction was investigated for dimensionality reduction and data compression. Automated data analysis was developed that could be applied data compressed to 1% of its original size, including segmentation and factorisation, providing a direct route to the analysis and interpretation of MSI datasets. Evaluation of these methods alongside established dimensionality reduction pipelines on simulated and real-world datasets showed they could reproducibly extract the chemo-spatial patterns present.

Chemical imaging by mass spectrometry is a powerful approach by which to map spatial distributions of molecules to better understand their function in the system of interest. Over the last thirty years, MSI has evolved into a very powerful analytical tool for the investigation of chemically-complex samples including biological tissues, catalytic surfaces and thin layer chromatography plates, among many others. The work in this dissertation aimed to characterize existing MSI methods, while also developing novel instrumentation able to overcome the challenges found in a variety of applications. Different sample preparation and ionization techniques were evaluated to maximize detection of lipid species in brain tissues subjected to traumatic injury to better understand the biological processes involved. Next, differential mobility separation was coupled to an ambient MSI system that resulted in increased signal-to-noise ratios and image contrast. Third, bulky catalytic granite surfaces were imaged to determine specific mineral reactivity and demonstrate the ability of desorption electrospray ionization to image such samples. Fourth, a novel technique was developed names Robotic Plasma Probe Ionization (RoPPI), which uses a vision system-guided robotic arm to probe irregular surfaces for three dimensional surface imaging. Finally, a software program was developed to automatically screen MSI datasets acquired from thin layer chromatography separations for spot-like shapes corresponding to mixture components; this program was named DetectTLC. This research resulted in instrumentation advances for MSI that have enabled increased chemical diversity, enhanced sensitivity and image contrast, imaging of bulky or irregularly-shaped surfaces, and multivariate tools to facilitate data interpretation.

BACKGROUND Cardiovascular diseases are the world’s number one death cause, accounting for 17.1 million deaths a year. There is still much unknown about cardiovascular diseases and their physiological underlying mechanism. Understanding the nature of complex biological processes occurring in both healthy and diseased heart tissue requires identifying the compounds involved and determining where they are located. Summary METHODS We have investigated a complementary mass spectrometry imaging (MSI) approach using matrix-assisted laser desorption/ionization (MALDI) and secondary ion mass spectrometry (SIMS) on the major areas of rat heart: the pericardium, the myocardium, the endocardium, and the great vessels to study the native distribution and identity of atomics, lipids, peptides and proteins in rat heart sections. 40 layers of horizontal tissue slices were acquired and reconstructed into a 3 D dataset. RESULTS Surface rastering of heart tissue sections generated multiple secondary ions in a mass range up to 1500 m/z. In the negative spectra we identified cholesterol related ions that show high intensity in both atrias, the aorta, the pulmonary artery and the outline both ventricles. The m/z 105 (choline) signal localizes in both atrias, aorta, pulmonary artery, in the atrioventricular valves and semilunar valves but is not present in ventricles surface. DAG species with probable identifications as Oleic, Linoleic [OL]+ at m/z 602 and [OO]+ (Oleic, Oleic) at m/z 604, can be detected. The images of 3D reconstruction show a highly complementary localization between Na+, K+, ion at m/z 145 and ion at m/z 667. Na+ is localized to tissue regions corresponding to atrias, while K+ is strongly localized to tissue regions corresponding to ventricles surface.The ion at m/z 667 localized very precisely within the aortic wall and the ion at m/z 145 is primarily located to the atria regions. CONCLUSIONS To promote further research with cardiovascular disease, we report the identification of characteristic molecules that map the spatial organization in a rat heart’s structure. A series of images obtained from successive sections of animal heart could, in principle, be used to produce a molecular atlas. Such tissue atlases (based optical images) are widely used for anatomical and physiological reference. The specific aim of this project is to optimize the data obtained from Heart SIMS a analysis and the 3-D reconstructive techniques developed to aid in investigating and visualizing differential molecular localizations in heart rat structures. The results reported here represent the first 3D molecular reconstruction of rat heart by SIMS imaging.
Introduzione Le malattie cardiovascolari rappresentano nel mondo la prima causa di morte, contando 17.1 milioni di morti ogni anno. Attualmente i meccanismi fisiopatologici alla base delle patologie sono in larga parte ancora sconosciuti. Capire la natura dei complessi processi biologici in atto sia nel miocardio cardiaco sano che malato richiede l’identificazione e la localizzazione degli stessi elementi molecolari coinvolti. METODO Utilizzando tecniche complementari di spettrometria di massa d’immagine (SMI) quali la spettrometria di massa a ioni secondari (Secondary Ion Mass Spectrometry, SIMS) e la spettrometria di massa a desorbimento /ionizzazione laser assistita da matrice (Matrix-assisted laser desorption/ionization, MALDI) abbiamo analizzato le principali componenti del cuore del ratto: il pericardio, il miocardio, l’endocardio, le valvole e i grandi vasi al fine di studiare ed identificare l’originale distribuzione di atomi, lipidi, peptici e proteine nel tessuto cardiaco normale. Quaranta sezioni di tessuto cardiaco sono state acquisite e ricostruite ottenendo un database tridimensionale. RISULTATI L’analisi della superficie delle sezione di tessuto cardiaco ha generato molteplici ioni secondari con un intervallo di massa che raggiunge i 1500 m/z. Utilizzando la modalita’ negativa abbiamo identificato il colesterolo e gli ioni relativi ad esso che mostrato un alta intensita’ in entrambi gli atri, l’aorta, l’arteria polmonare e pericardio. La colina corrispondente a 105 m/z di massa molecolare risulta essere localizzata in entrambi gli atri, aorta, arteria polmonare, valvole atrioventricolari e valvole semilunari ma non risulta essere presente sulla superficie ventricolare. Sono state identificate molecole appartenenti al diacilglicerolo come acido Oleico, Linoleico [OL]+ corrispondenti alla massa molecolare di 602 m/z e [OO]+ (Oleico,Oleico) con massa molecolare di 604 m/z. Le immagini ottenute dalla ricostruzione tridimensionale mostrano una specifica localizzazione complementare tra il sodio, il potassio e gli ioni con massa molecolare di 145 m/z e 667 m/z. Il sodio e’maggiormente localizzato nelle regioni cardiache corrispondenti agli atri, mentre il potassio e’ maggiormente localizzato nelle regioni corrispondenti alla superficie ventricolari. Lo ione con massa molecolare di 667 m/z e’ localizzato con molta precisione all’interno della parete dell’aorta e lo ione con massa molecolare di 145 m/z e’ localizzato a livello delle regioni atriali. CONCLUSIONI Al fine di promuovere un’ulteriore ricerca in patologia cardiovascolare, riportiamo l’identificazione delle caratteristiche molecole che mappano l’organizzazione spaziale delle strutture cardiache del cuore del ratto. Una serie di immagini ottenute da sezioni successive del cuore potrebbero inizialmente essere utilizzate come un atlante molecolare e similmente, ad un atlante basato sulle immagini ottiche, essere ampiamente utilizzato come referente sia dal punto di vista fisiologico che anatomico. L’aiuto apportato da questo progetto e’ l’ottimizzazione dei dati ottenuti dall’analisi SIMS e lo sviluppo della tecnica per la ricostruzione tridimensionale al fine di investigare e visualizzare le differenti molecole localizzate nelle strutture del cuore di ratto. I risultati qui riportati rappresentano la prima ricostruzione tridimensionale ottenuta con immagini SIMS, del cuore di ratto.

Lignocellulosic biomass (e.g., non food-based agricultural resides and forestry wastes) has recently been promoted for use as a source of bioethanol instead of food-based materials (e.g., corn and sugar cane), however to fully realize these benefits an improved understanding of lignocellulosic recalcitrance must be developed. The primary goal of this thesis is to gain fundamental knowledge about the surface of the plant cell wall, which is to be integrated into understanding biomass recalcitrance. Imaging mass spectrometry by TOF-SIMS and MALDI-IMS is applied to understand detailed spatial and lateral changes of major components in the surface of biomass under submicron scale. Using TOF-SIMS analysis, we have demonstrated a dilute acid pretreated poplar stem represented chemical differences between surface and bulk compositions. Especially, abundance of xylan was observed on the surface while sugar profile data showed most xylan (ca. 90%) removed from the bulk composition. Water only flowthrough pretreated poplar also represented difference chemistry between surface and bulk, which more cellulose revealed on the surface compared to bulk composition. In order to gain the spatial chemical distribution of biomass, 3-dimensional (3D) analysis of biomass using TOF-SIMS has been firstly introduced in the specific application of understanding recalcitrance. MALDI-IMS was also applied to visualize different molecular weight (e.g., DP) of cellulose oligomers on the surface of biomass.

It is well established that lipids play an important role in diseases such as non-alcoholic fatty liver disease and cardiovascular diseases. However, in the past decade, it has come to light that lipids may be important in other diseases; particularly in cancer and neurological disorders. Here, lipid metabolism has been investigated using pre-clinical cancer models for melanoma, glioma, non-small-cell lung cancer and colorectal cancer. The role of lipids in the recovery post-stroke has also been studied. Mass spectrometry imaging offers an ideal tool to study lipids in tissue ex-vivo. Lipids ionise well in a number of mass spectrometry modalities, and hundreds of lipids can be imaged in one mass spectrometry imaging experiment. Furthermore, mass spectrometry imaging offers excellent spatial resolution. In this work, both MALDI-MS and DESI-MS have been used for mass spectrometry imaging. Tumour lipid heterogeneity has been a particular focus of this this project. Heterogeneity exists within tumours, as well as between tumours in the same patient; and this causes major problems for therapy. Owing to the untargeted nature, and high spatial resolution of mass spectrometry imaging, it is an excellent technique to study lipid heterogeneity. Adjacent sections (or in some cases the same section used for mass spectrometry imaging), were used for immunofluorescence and H&E staining. By comparing mass spectrometry images with staining techniques, biological reasons for lipid heterogeneity can be established. Here, a particular focus has been on hypoxia (low oxygen tensions), which is a key contributor to tumour heterogeneity, and is associated with aggressive cancers. Additionally, hypoxia is a feature of ischaemic stroke, and lipids in ischaemic stroke have also been investigated. PET is a non-invasive imaging technique which is able to image a radiolabelled molecule (tracer) in the body. Here, PET has been used as a complementary in-vivo technique to mass spectrometry imaging. The tracers [11C] acetate and [18F]-FTHA have been used to image fatty acid synthase and fatty acid uptake in tumours; both of which are hypothesised to be key in cancer progression. REIMS is a newly established mass spectrometry technique. It is ideal for analysing lipids in cells, as sample preparation is minimal. Here, approaches for cell pellet analysis have been tested, and used to detect lipids in cancer cell lines.

Mass spectrometry imaging (MSI) is a powerful tool that provides mass-specific surface images with micron or sub-micron spatial resolutions. In a microscope MSI experiment, large sample surfaces are illuminated with a defocused laser or primary ion beam, enabling all surface molecules to be desorbed and ionised simultaneously before being electrostatically projected onto a position-sensitive imaging detector at the end of a time-of-flight mass analyser. Traditionally only the image of one mass-to-charge ratio can be obtained in a single acquisition, which limits its applicability. However, the development of event-triggered sensors, such as CMOS-based cameras, revives the microscope MSI method by allowing multi-mass imaging. Therefore, the challenges facing microscope have MSI shifted to improving its mass resolution, effective mass range, and mass accuracy. This thesis proposes effective solutions to each of them, and thus significantly improves the performance and applicability of microscope MSI. To increase the mass range, two modified post-extraction differential acceleration (PEDA) techniques, double-field PEDA and time-variable PEDA, were used to demonstrate mass-resolved stigmatic imaging over a broad m/z range. In double-field PEDA, a potential energy cusp was introduced into the ion acceleration region of an imaging mass spectrometer, creating two m/z foci that were tuned to overlap at the detector plane. This resulted in two focused m/z distributions that stretched the mass-resolved window with m/Δm >= 1000 to 165 Da without any loss in image quality; a range that doubled the 65 Da achieved under similar conditions using the original PEDA technique. In time-variable PEDA, a dynamic pulsed electric field was used to maximize the effective mass range of PEDA. By simultaneously focusing ions between 300 to 700 m/z using an exponentially rising voltage pulse, time-variable PEDA provides an effective mass range more than six times wider than the original PEDA method. Although reflectrons are widely used to improve the mass resolving power of ToF-MS, incorporating them in a microscope MSI instrument is novel. A reflectron MSI instrument was designed and implemented. Simulations demonstrated that one-stage gridless reflectrons were more compatible with the spatial imaging goal of the microscope MSI instrument than the gridded reflectrons. Preliminary experimental results showed that coupling the gridless reflectron with single-field PEDA achieved a mass resolution above 8,000 m/Δm while keeping a spatial resolution of 20 um. In conclusion, the gridless reflectron was able to triple the mass resolving power without losing any spatial imaging power. The poor mass accuracy hurdle was overcome by machine learning algorithms, which can construct clinical diagnostic models that recognise the peak pattern of biological mass spectra and classify them accurately without knowing the actual mass of each peak. After a proof of concept "experiment", where the mass spectra of dye molecules were classified by various learning algorithms, three pairs of datasets (ovarian cancer, prostate cancer, chronic fatigue and their respective controls) were used to build classifiers that accurately distinguish blood samples from controls. Possible biomarkers were also discovered by evaluating the importance of each m/z feature, which may assist further studies.

Mass spectrometry imaging (MSI) is a powerful tool for mapping the spatial distribution and relative abundance of molecules across a sample surface. The distribution of proteins, metabolites, lipids and drugs can be determined and unlike other molecular imaging techniques, such as immunohistochemistry (IHC), MSI is completely label-free. Therefore, this technique does not require prior knowledge of the molecule to be imaged and thousands of molecules can be imaged at once. This is particularly useful for untargeted imaging, to discover molecules which are important for a certain condition. For example, a healthy tissue sample can be compared to a diseased sample in the same imaging run to help understand the molecules involved in the disease process. MSI has become a popular technique in fields such as neuroscience, drug distribution studies and as a biomarker discovery tool in cancer. However, the use of MSI in microbiology has to date been limited. In the present study MSI was used to investigate molecular host-microbe interactions of both beneficial and pathogenic bacteria of the gastrointestinal tract. In the initial part of this thesis, MSI was employed to discover molecular changes in the host, caused by Salmonella enterica serovar Typhimurium infection. S. Typhimurium is a Gram-negative facultative intracellular bacterium and is a leading cause of food-borne infection worldwide in humans. The symptoms include abdominal cramps and diarrhoea, and although this infection is usually self-limiting with individuals recovering without the requirement for treatment, it can be more serious in young, old, malnourished, or immunocompromised people. S. Typhimurium is transmitted by ingestion of contaminated food or water. The bacteria infect cells of the gastrointestinal tract, causing inflammation, and cross the epithelial layer of the gut to enter underlying specialised immune tissue, the Peyer’s patches. S. Typhimurium can be taken up by immune cells, but can survive within these cells and are transported to another specialised immune location, the mesenteric lymph nodes (MLNs). In the present study, an S. Typhimurium infected, gastroenteritis mouse model was used to investigate host-pathogen interaction. Various tissue types were collected from 72 h infected, 48 h infected and uninfected mice including colon, Peyer’s patches and MLN. IHC staining was used to locate tissue types and regions where S. Typhimurium were present and MSI was employed to find molecular changes caused by the infection. This preliminary analysis highlighted 73 molecules that differed in abundance or distribution between infected and uninfected samples, across all three tissue types. These molecules could be investigated further in future, however, subsequent analysis focused on one molecule, which was identified as palmitoylcarnitine, a molecule involved in fatty acid metabolism. This molecule was present at high abundance in areas of the MLNs 72 h post infection, where both bacteria and infection induced tissue damage were present. This molecule was also present in uninfected samples and areas of infected tissue where no bacteria were present at lower levels, therefore this molecule was deemed to be host derived. It was hypothesised that this molecule could either be; produced by the immune system to directly damage S. Typhimurium, be produced by the immune system to enhance the immune response, or be a by-product of tissue damage and could further damage host cells. Therefore, subsequent analysis focused on testing the effects of palmitoylcarnitine to investigate these hypotheses. No effects were found when testing this molecule on bacterial growth or virulence. Palmitoylcarnitine localised to areas of immune cell, T cell, B cell and macrophage, disruption in the MLNs. Cells from MLNs were isolated and cultured in the presence of palmitoylcarnitine to investigate any effects of this molecule on immune cell death or activation. Palmitoylcarnitine was found to cause cell death by apoptosis of a particular subset of immune cells, CD4+CD25+ T cells. These immune cells are mostly likely regulatory T cells, which protect the host against excess damage during an immune response. Therefore, the overall hypothesis was S. Typhimurium infection could be disrupting fatty acid metabolism, leading to accumulation of palmitoylcarnitine. This in turn causes death of CD4+CD25+ T cells, which could be responsible for causing the excess tissue damage found in the MLNs during infection. The second part of this thesis employed MSI to investigate the interaction between the beneficial bacteria of the gastrointestinal tract, the microbiota, and the host brain. An altered microbiota has recently been linked to diseases throughout the body and differences in the microbiota have been found in patients with neurological disorders, such as autism, Parkinson’s disease and depression. There is still little known about the links between the brain and microbiota and how the microbiota may be influencing the brain. In the present study the colons and brains of mice with absent or depleted microbiota were compared to conventionally colonized mice to investigate possible links between the gut and the brain. MSI was demonstrated to be an effective technique to image known molecules, as well as previously unknown molecules which changed between microbiota depleted and conventionally colonized mice. A previously unknown microbiota derived molecule was chosen for further identification and analysis. This study demonstrates the capabilities of MSI as a discovery tool to find molecules important for host-microbe interactions. This study also aids in advancing the use of this technique in the field of microbiology, which would be highly beneficial in future to help understand immune evasion strategies of pathogenic bacteria and how the microbiota is interacting and crucial to the host.

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

Mass spectrometry imaging (MSI) is a MS-based technique. It provides a way of ascertaining both spatial distribution and relative abundance of a large variety of analytes from various biological sample surfaces. MSI is able to generate distribution maps of multiple analytes simultaneously without any labeling and does not require a prior knowledge of the target analytes, thus it has become an attractive molecular histology tool. MSI has been widely used in medicine and pharmaceutical fields, while its application in plants is recent although information regarding the spatial organization of metabolic processes in plants is of great value for understanding biological questions such as plant development, plant environment interactions, gene function and regulatory processes. The application of MSI to these studies, however, is not straightforward due to the inherent complexity of the technique. In this thesis, the issues of plant sample preparation, surface properties heterogeneity, fast MSI analysis for spatially resolved population studies and data analysis are addressed. More specifically, two MSI approaches, namely matrix assisted laser desorption ionization (MALDI) imaging and desorption electrospray ionization (DESI) imaging, have been evaluated and compared by mapping the localization of a range of secondary and primary metabolites in apple and grapes, respectively. The work based on MALDI has been focused on the optimization of sample preparation for apple tissues to preserve the true quantitative localization of metabolites and on the development of specific data analysis tool to enhance the chemical identification in untargeted MSI (chapter 3). MALDI imaging allows high-spatial localization analysis of metabolites, but it is not suitable for applications where rapid and high throughput analysis is required when the absolute quantitative information is not necessary as in the case of screening a large number of lines in genomic or plant breeding programs. DESI imaging, in contrast, is suitable for high throughput applications with the potential of obtaining statistically robust results. However, DESI is still in its infancy and there are several fundamental aspects which have to be investigated before using it as a reliable technique in extensive imaging applications. With this in mind, we investigated how DESI imaging can be used to map the distribution of the major organic acids in different grapevine tissue parts, aiming at statistically comparing their distribution differences among various grapevine tissues and gaining insights into their metabolic pathways in grapevine. Our study demonstrated that this class of molecules can be successfully detected in grapevine stem sections, but the surface property differences within the structurally heterogeneous grapevine tissues can strongly affect their semi-quantitative detection in DESI, thereby masking their true distribution. Then we decided to investigate this phenomenon in details, in a series of dedicated imaging studies, and the results have been presented in chapter 4. At the same time, during DESI experiments we have observed the production of the dianions of small dicarboxylates acids. We further studied the mechanism of formation of such species in the ion source proposing the use of doubly charged anions as a possible proxy to visualize the distributions of organic acid salts directly in plant tissues (chapter 5). The structural organization of the PhD thesis is as below: Chapter one and Chapter two describe the general MSI principle, compare the most widely used MSI ion sources, and discuss the current status in MSI data pre-processing and statistical methods. Due to the importance of sample preparation in MSI, sample handling for plant samples is independently reviewed in chapter two, with all the essential steps being fully discussed. The first two chapters describe the comprehensive picture regarding to MSI in plants. Chapter three presents high spatial and high mass resolution MALDI imaging of flavonols and dihydrochalcones in apple. Besides its importance in plant research, our results demonstrate that how data analysis as such Intensity Correlation Analysis could benefit untargeted MSI analysis. Chapter four discusses how sample surface property differences in a structurally/biologically heterogeneous sample affect the quantitative mapping of analytes in the DESI imaging of organic acids in grapevine tissue sections. Chapter five discusses the mechanism of formation of dicarboxylate dianions in DESI and ESI Chapter six summarizes the work in the thesis and discusses the future perspectives.

Mass spectrometry imaging (MSI) is a MS-based technique. It provides a way of ascertaining both spatial distribution and relative abundance of a large variety of analytes from various biological sample surfaces. MSI is able to generate distribution maps of multiple analytes simultaneously without any labeling and does not require a prior knowledge of the target analytes, thus it has become an attractive molecular histology tool. MSI has been widely used in medicine and pharmaceutical fields, while its application in plants is recent although information regarding the spatial organization of metabolic processes in plants is of great value for understanding biological questions such as plant development, plant environment interactions, gene function and regulatory processes. The application of MSI to these studies, however, is not straightforward due to the inherent complexity of the technique. In this thesis, the issues of plant sample preparation, surface properties heterogeneity, fast MSI analysis for spatially resolved population studies and data analysis are addressed. More specifically, two MSI approaches, namely matrix assisted laser desorption ionization (MALDI) imaging and desorption electrospray ionization (DESI) imaging, have been evaluated and compared by mapping the localization of a range of secondary and primary metabolites in apple and grapes, respectively. The work based on MALDI has been focused on the optimization of sample preparation for apple tissues to preserve the true quantitative localization of metabolites and on the development of specific data analysis tool to enhance the chemical identification in untargeted MSI (chapter 3). MALDI imaging allows high-spatial localization analysis of metabolites, but it is not suitable for applications where rapid and high throughput analysis is required when the absolute quantitative information is not necessary as in the case of screening a large number of lines in genomic or plant breeding programs. DESI imaging, in contrast, is suitable for high throughput applications with the potential of obtaining statistically robust results. However, DESI is still in its infancy and there are several fundamental aspects which have to be investigated before using it as a reliable technique in extensive imaging applications. With this in mind, we investigated how DESI imaging can be used to map the distribution of the major organic acids in different grapevine tissue parts, aiming at statistically comparing their distribution differences among various grapevine tissues and gaining insights into their metabolic pathways in grapevine. Our study demonstrated that this class of molecules can be successfully detected in grapevine stem sections, but the surface property differences within the structurally heterogeneous grapevine tissues can strongly affect their semi-quantitative detection in DESI, thereby masking their true distribution. Then we decided to investigate this phenomenon in details, in a series of dedicated imaging studies, and the results have been presented in chapter 4. At the same time, during DESI experiments we have observed the production of the dianions of small dicarboxylates acids. We further studied the mechanism of formation of such species in the ion source proposing the use of doubly charged anions as a possible proxy to visualize the distributions of organic acid salts directly in plant tissues (chapter 5). The structural organization of the PhD thesis is as below: Chapter one and Chapter two describe the general MSI principle, compare the most widely used MSI ion sources, and discuss the current status in MSI data pre-processing and statistical methods. Due to the importance of sample preparation in MSI, sample handling for plant samples is independently reviewed in chapter two, with all the essential steps being fully discussed. The first two chapters describe the comprehensive picture regarding to MSI in plants. Chapter three presents high spatial and high mass resolution MALDI imaging of flavonols and dihydrochalcones in apple. Besides its importance in plant research, our results demonstrate that how data analysis as such Intensity Correlation Analysis could benefit untargeted MSI analysis. Chapter four discusses how sample surface property differences in a structurally/biologically heterogeneous sample affect the quantitative mapping of analytes in the DESI imaging of organic acids in grapevine tissue sections. Chapter five discusses the mechanism of formation of dicarboxylate dianions in DESI and ESI Chapter six summarizes the work in the thesis and discusses the future perspectives.

Mass spectrometry imaging (MSI) is a MS-based technique. It provides a way of ascertaining both spatial distribution and relative abundance of a large variety of analytes from various biological sample surfaces. MSI is able to generate distribution maps of multiple analytes simultaneously without any labeling and does not require a prior knowledge of the target analytes, thus it has become an attractive molecular histology tool. MSI has been widely used in medicine and pharmaceutical fields, while its application in plants is recent although information regarding the spatial organization of metabolic processes in plants is of great value for understanding biological questions such as plant development, plant environment interactions, gene function and regulatory processes. The application of MSI to these studies, however, is not straightforward due to the inherent complexity of the technique. In this thesis, the issues of plant sample preparation, surface properties heterogeneity, fast MSI analysis for spatially resolved population studies and data analysis are addressed. More specifically, two MSI approaches, namely matrix assisted laser desorption ionization (MALDI) imaging and desorption electrospray ionization (DESI) imaging, have been evaluated and compared by mapping the localization of a range of secondary and primary metabolites in apple and grapes, respectively. The work based on MALDI has been focused on the optimization of sample preparation for apple tissues to preserve the true quantitative localization of metabolites and on the development of specific data analysis tool to enhance the chemical identification in untargeted MSI (chapter 3). MALDI imaging allows high-spatial localization analysis of metabolites, but it is not suitable for applications where rapid and high throughput analysis is required when the absolute quantitative information is not necessary as in the case of screening a large number of lines in genomic or plant breeding programs. DESI imaging, in contrast, is suitable for high throughput applications with the potential of obtaining statistically robust results. However, DESI is still in its infancy and there are several fundamental aspects which have to be investigated before using it as a reliable technique in extensive imaging applications. With this in mind, we investigated how DESI imaging can be used to map the distribution of the major organic acids in different grapevine tissue parts, aiming at statistically comparing their distribution differences among various grapevine tissues and gaining insights into their metabolic pathways in grapevine. Our study demonstrated that this class of molecules can be successfully detected in grapevine stem sections, but the surface property differences within the structurally heterogeneous grapevine tissues can strongly affect their semi-quantitative detection in DESI, thereby masking their true distribution. Then we decided to investigate this phenomenon in details, in a series of dedicated imaging studies, and the results have been presented in chapter 4. At the same time, during DESI experiments we have observed the production of the dianions of small dicarboxylates acids. We further studied the mechanism of formation of such species in the ion source proposing the use of doubly charged anions as a possible proxy to visualize the distributions of organic acid salts directly in plant tissues (chapter 5). The structural organization of the PhD thesis is as below: Chapter one and Chapter two describe the general MSI principle, compare the most widely used MSI ion sources, and discuss the current status in MSI data pre-processing and statistical methods. Due to the importance of sample preparation in MSI, sample handling for plant samples is independently reviewed in chapter two, with all the essential steps being fully discussed. The first two chapters describe the comprehensive picture regarding to MSI in plants. Chapter three presents high spatial and high mass resolution MALDI imaging of flavonols and dihydrochalcones in apple. Besides its importance in plant research, our results demonstrate that how data analysis as such Intensity Correlation Analysis could benefit untargeted MSI analysis. Chapter four discusses how sample surface property differences in a structurally/biologically heterogeneous sample affect the quantitative mapping of analytes in the DESI imaging of organic acids in grapevine tissue sections. Chapter five discusses the mechanism of formation of dicarboxylate dianions in DESI and ESI Chapter six summarizes the work in the thesis and discusses the future perspectives.

Mass spectrometry imaging (MSI) enables two- and three-dimensional overviews of hundreds of unlabelled molecular species including drugs, metabolites, lipids and proteins in complex samples such as intact tissue. In this research, a new extensible software platform is presented, suitable for spectral preprocessing, multivariate analysis and visualisation of large MSI datasets from all major MSI vendors. Principal component analysis (PCA) has been widely used in the unsupervised processing of MSI data. Standard implementations of PCA require the entire dataset to be stored in memory, necessitating a compromise between the number of pixels and the number of peaks to include. In this research a new method which has no limitation on the number of pixels is developed. Hierarchical composition of data has been shown as an efficient method of capturing the information present within images in other fields. An adaptation of these ideas to MSI data is described. The way in which imaging data are presented can have a significant impact on the perceived structure, especially when using false colour to display images. The research presented in this thesis has resulted in new recommendations for presentation of MS images. Finally, the software and algorithms presented were used to analyse MSI data from a traumatic brain injury model. Manual exploration and use of multivariate analysis methods such as PCA did not reveal any differences between the injured hemisphere of the brain and the control hemisphere, however the hierarchical composition algorithms identified multiple ion images which appear elevated in the injured hemisphere.

Until recently, the use of microscope-mode imaging mass spectrometry (MSI) was restricted by the available technology. Fast cameras were limited to acquiring a single image relating to a set m/z range which had to be predefined before the experiment was started. Now, new developments in camera technology have produced time-stamping cameras that can record the arrival time of ions at a detector, without the need to define an exposure time. This allows the images relating to different species with a range of m/z to be acquired simultaneously. One of these cameras is the Pixel Imaging Mass Spectrometry (PImMS) camera, which has the added advantage that each pixel within the sensor has four memory registers. This means that up to four events can be observed, by each pixel, within a single time-of-flight cycle. Here, the application of the PImMS camera to microscope-mode MSI is presented. Initial experiments are conducted using a converted conventional velocity-map imaging instrument. Simulations are presented in order to predict the performance of the ion optics when used for spatial imaging, and the result of these simulations is then compared to those obtained experimentally, using a commercially available charge-coupled device (CCD) camera and a photomultiplier tube (PMT). These spatial resolutions along with simultaneously obtained mass resolutions are then compared to those obtained using a PImMS1 camera. Further experiments are presented in which the PImMS1 camera is used in conjunction with a modified commercially available mass spectrometer, the LT2 Plus (produced by Scientific Analysis Instruments Ltd - SAI). This instrument is designed to obtain isotopic resolution for m/z < 1000, whilst also maintaining a spatial resolution better than 50μm. These specifications are obtained using the PImMS1 camera, and it is shown that images of multiple chemical species can be obtained simultaneously. A new data analysis method is developed, which attempts to model the shape of PImMS data event clusters. Although the application of this method cannot be fully realised with data obtained with a PImMS1 camera, a modified version is successfully applied to PImMS1 data and produces both an improvement in the time precision of the camera, as well as a more efficient use of the available data. Finally, various designs for a primary ion beam are presented that could be used in place of the standard laser desorption system. The ion beam is designed for use with an MSI instrument, ablating sample from a large area of sample, and with a short pulse length for time-of-flight analysis. A final design is presented that can produce beam pulse that can be focussed down to form a pulse length of 5ns, across a target of 2.5mm. As a collection, the works detailed in this thesis present the development of a stigmatic ion microscope that uses the PImMS camera, from a proof-of-concept to a viable analytical instrument.

Elemental detection is an emerging area in bioanalysis. Thanks to the rapid advancement in instrumentation such as inductively coupled plasma-mass spectrometry (ICP-MS), low detection limit and quick analysis can be achieved. Besides, ICP-MS also suffers less matrix effect as compared to molecular mass spectrometry, so a precise and accurate detection of toxic or essential elements can be provided. Different types of sample introduction or separation systems such as laser ablation (LA) and liquid chromatograph (LC) are excellent hyphenation options for the elemental detection apart from the total analysis of standalone ICP-MS analysis. Spatial analysis and speciation of the two mentioned techniques provide additional merits to the elemental detection in bioanalysis.;LA-ICP-MS makes use of a laser to ablate the solid sample, and the generated sample aerosol is then transferred to ICP-MS for detection. It can be used for bioimaging. There are examples of LA mapping of biological tissues to reveal the spatial distribution of metal, to study the neurodegenerated disease in brain or the accumulation in metallodrug in tumor mass. In order to incorporate the imaging tool in drug development, in the first part of this thesis, LA-ICP-MS bioimaging of liver and kidney was performed to compare the differential spatial distribution of two structurally different platinum-based anti-cancer drug candidates. It was expected that this approach can assist the chemical modification in drug development.;To put this idea a step further, the spatial analysis tool was tested for its potential in therapeutic drug monitoring. Hair profiling in whiskers of mice treated with vanadium anti-diabetic complex or gadolinium-based contrasting agents at different dosage levels were conducted. Results shown that different deposition behaviors and accumulation/elimination profile can be observed, demonstrating a great potential in routine clinical application.;On the other hand, LC-ICP-MS offers the possibility for speciation study. Several accessories for organic solvent introduction in ICP-MS make the coupling of reverse phase chromatography using high percentage of organic solvent in the mobile phase more convenient. To demonstrate the advantage of this configuration, a speciation of bromine-containing drug in mice urine and plasma was included in the last part of this project for metabolite profiling study.;In Short, this work presents several useful hyphenated techniques of ICP-MS in bioanalysis, proving the tremendous potential of elemental detection in drug development (assisting molecular modification in drug design and metabolite profiling) and therapeutic drug monitoring (hair profiling)

Today we are collecting a large amount of tissue samples to store for future studies of different health conditions, in hopes that the focus in health care will shift from treatments to early detection and prevention, by the use of biomarkers. To make sure that the storing of tissue is done in a reliable way, where the molecular profile of the samples are preserved, we first need to characterise how these changes occur. In this thesis, data from mice brains were collected using MALDI imaging mass spectrometry (IMS) and an analysis pipeline for robust MALDI IMS data handling and evaluation was implemented. The finished pipeline contains two reduction algorithms, catching images with interesting intensity features, while taking the spatial information into account, along with a robust similarity measurement, for measuring the degree of co-localisation. It also includes a clustering algorithm built upon the similarity measurement and an amino acid mass comparer, iteratively generating combinations of amino acids for further mass comparisons with mass differences between cluster members. Availability: The source code is available at https://github.com/stephanieherman/thesis

Cells have been found to have an inherent heterogeneity that has led to an increase in the development of single-cell analysis methods to characterize the extent of heterogeneity that can be found in seemingly identical cells. With an understanding of normal cellular variability, the identification of disease induced cellular changes, known as biomarkers, may become more apparent and readily detectable. Biomarker discovery in single-cells is challenging and needs to focus on molecules that are abundant in cells. Lipids are widely abundant in cells and play active roles in cellular signaling, energy metabolism, and are the main component of cellular membranes. The regulation of lipid metabolism is often disrupted or lost during disease progression, especially in cancer, making them ideal candidates as biomarkers. Challenges exist in the analysis of lipids beyond those of single-cell analysis. Lipid extraction solvents must be compatible with the lipid or lipids of interest. Many lipids are isobaric making mass spectrometry analysis difficult without separations. Single-cell extractions using nanomanipulation coupled to mass spectrometry has shown to be an excellent method for lipid analysis of tissues and cell cultures. Extraction solvents are tunable for specific lipid classes, nanomanipulation prevents damage to neighboring cells, and lipid separations are possible through phase dispersion. The most important aspect of single-cell analysis is that it uncovers the extent of cellular heterogeneity that exists among cellular populations that remains undetected during averaged sampling.

Desorption Electrospray Ionization Mass spectrometry Imaging (DESI-MSI) is an area of great interest and a promising tool in the field of chemical imaging. It is a powerful, label-free technique, which can determine, map and visualize different molecular compounds on a sample surface. The amount of information acquired in a single DESI-MSI experiment is enormous compared to other techniques, as it can simultaneously detect different compounds with their spatial distribution on the surface. The experiment can be used to produce two-dimensional and three-dimensional images. Chapter 2 focuses on the design and optimization of the setup for performing DESI-MS imaging on various substrates. The proposed setup was tested for its lateral spatial resolution. To provide proof-of-concept of the design, preliminary tests were performed to generate images from commercial thin layer chromatographic plates and photographic paper. Chapter 3 focuses on demonstrating the compatibility of novel microfabricated Thin Layer Chromatography plates (M-TLC plates) for detection with DESI-MSI.

Matrix assisted laser desorption/ionisation mass spectrometry imaging is a recent addition to the existing family of molecular imaging technologies. It has the capacity to map the distribution of molecules within a biological tissue section, without the need for radionuclide or fluorescent labelling procedures. The primary aim of the work presented in this thesis was to assess the use of a high repetition rate laser for MALDI-MS image analysis by developing methodologies for the detection of a number of different compounds from a variety of biological tissues. Additional investigations include and examination of strategies for normalisation and statistical interpretation of MALDI-MS image data. The application of a solvent assisted indirect imaging approach for the analysis of drugs in skin is described. Studies have been carried out in order to gauge how the use of a solvent in the blotting process aids the indirect imaging technique. Further experiments have been performed to assess the level of analyte migration induced by incorporation of a sample wetting step. In a direct tissue imaging experiment the distribution of a prodrug and its active metabolite has been determined in treated tumour tissue. Endogenous markers have been employed to assist in determining correlation between drug activation and hypoxic regions within tumours. Different methods of data normalisation are investigated for their effects on image data, and statistical evaluation of MALDI-MS acquired image data have been examined in relation to extracting hidden variables from multidimensional image data sets.

Surface-Assisted Laser Desorption/Ionization Mass Spectrometry (SALDI-MS) is an analytical technique enabling direct chemical analysis of solid samples. Analytes could be desorbed/ionized upon nitrogen laser irradiation from a SALDI substrate-coated sample, then analyzed by MS. The substrate is involved in the transfer of laser energy to the analytes, and eventually assists the desorption/ionization of analytes. The analytical performance of SALDI-MS, such as detection sensitivity, is dependent on different parameters of the substrate, such as size, morphology and form. In this thesis, the effects of several substrate parameters on the SALDI process were investigated. SALDI-MS based Imaging Mass Spectrometry (IMS) method was also developed using efficient SALDI substrate identified in the fundamental studies. IMS is a chemical-specific mapping technique which allows parallel mapping of multiple analytes in solid samples. The desorption mechanism of SALDI is investigated using two groups of substrate, the carbon allotropes and the noble metal nanoparticles. Ion desorption efficiency and internal energy transfer were probed and correlated in carbon-based SALDI. It was found that the ion desorption efficiency and internal energy transfer was in opposite order. Substrate that transferred more internal energy to ions did not show higher ion desorption efficiency. This result could not be explained by the Thermal Desorption model which was a generally believed mechanism of the SALDI desorption process. A non-thermal model, the Phase Transition model is proposed to account for the SALDI desorption process. The Phase Transition model suggests that the substrate is melted/ restructured upon laser irradiation, and this will assist ion desorption. The Phase Transition model is supported by the morphological change of carbon substrates after SALDI and high initial velocity of ions desorbed by carbon-based SALDI (> 1,000 ms-1). SALDI-MS is useful for small molecule analysis due to the relatively clean background in the low mass region. SALDI-IMS is developed and applied to the imaging of spatial distribution of small molecules in forensic and biological samples. Gold nanoparticles (AuNPs) was selected as the substrate from several other noble metal NPs. A solvent-free method, argon ion sputtering, was employed for coating AuNPs on sample surface prior to SALDI-IMS analysis. Fine details of the samples, such as the fine pattern of latent fingerprints and handwriting on questioned documents can be preserved and imaged reliably by avoiding the use of solvent. Fatty acids, drugs and ink components can be imaged in forensic samples including latent fingerprints, banknotes and checks. The solvent-free SALDI-IMS method was also applied to image the distribution of metabolites in intact animal tissues. Spatial distributions of neurotransmitters, nucleobases and fatty acids can be imaged from mouse brain and tumor tissue sections.
published_or_final_version
Chemistry
Doctoral
Doctor of Philosophy

Imaging mass spectrometry (IMS) in microscope mode allows the spatially resolved molecular constitution of a large sample section to be analysed in a single experiment. If performed in a linear mass spectrometer, the applicability of microscope IMS is limited by a number of factors: the low mass resolving power of the employed ion optics; the time resolution afforded by the scintillator screen based particle detector and the multi-hit capability, per pixel, of the employed imaging sensor. To overcome these limitations, this thesis concerns the construction of an advanced ion optic employing a pulsed extraction method to gain a higher ToF resolution, the development of a bright scintillator screen with short emission lifetime, and the application of the Pixel Imaging Mass Spectrometry (PImMS) sensor with multi-mass imaging and time stamping capabilities. Initial experimental results employing a three electrode ion optic to spatially map ions emitted from a sample surface are presented. By applying a static electric potential a time-of-flight resolution of t/2Δt=54 and a spatial resolution of 20 μm are determined across a field-of-view of 4 mm diameter. While the moderate time-of-flight resolution only allows particles separated by a few Dalton to be distinguished, the instrument is used to demonstrate the multi-mass imaging capabilities of the PImMS sensor when being applied to image grid structures or tissue samples. An improved time-of-flight resolution is achieved by post extraction differential acceleration of a selected range of ions (up to 100 Da) using a newly developed five electrode ion optic. This modification is shown to correct the initial velocity spread of the ions coming off the sample surface, which yields an enhanced time-of-flight resolution of t/2Δt=2000 . The spatial resolution of the instrument is found to be 20 μm across a field-of-view of 4 mm. Adjusting the extraction field strength applied to the ion optic of the constructed mass spectrometer allows the optimised mass range to be tuned to any mass of interest. Ion images are recorded for various samples with comparable spatial and ToF resolution. Hence, studies on tissue sections and multi sample arrays become accessible with the improved design and operational principle of the microscope mode IMS instrument. A fast and efficient conversion of impinging ions into detectable flashes of light, which can consequently be recorded by a fast imaging sensor, is essential to maintain the achievable time-of-flight and spatial resolution of the IMS instrument constructed. In order to find a suitable fast and bright scintillator to be applied in a microchannel based particle detector, various inorganic and organic substances are characterised in terms of their emission properties following electron excitation. Poly-para-phenylene laser dye screens are found to show an outstanding performance among all substances analysed. An emission life time of below 4 ns and a brightness exceeding that of a P47 screen (industry standard) by a factor 2× is determined. No signal degradation is observed over an extended period, and the spatial resolution is found to be comparable to commercial imaging detectors. Hence, these scintillator screens are fully compatible with any ion imaging application requiring a high time resolution. In a further series of mass spectrometric experiments, ions are accelerated onto a scintillator mounted in front of a multi pixel photon counter. The charged particle impact stimulated the emission of a few photons, which are collected by the fast photon counter. Poly-para-phenylene laser dyes again show an outstanding efficiency for the conversion of ions into photons, resulting in a signal enhancement of up to 5× in comparison to previous experiments, which employed an inorganic LYSO scintillator.

The purpose of the work described in this thesis was to develop and apply efficient methodologies based on MALDI-MSI for the direct analysis and targeting of protein tumour biomarkers within both frozen and formalin fixed paraffin embedded (FFPE) cancerous tissue sections. Method development for protein analysis directly in tumour tissue sections were performed using tumour xenograft models. This involved improvements in sample preparation, such as tissue washing protocols, and the development of data pre-processing methods prior to statistical analysis using a freely available software package, which referred to as Spec Align. The use of MALDI-MSI for studying proteome patterns directly from tumour tissue sections with no requirement for known targets is demonstrated. In addition, in situ identification of proteins within tumour tissue sections was achieved and correlated with their localisation. The method demonstrated here involved the use of octyl glucoside, a non-ionic detergent, which aims to improve the solubilisation and detection of low abundance and membrane-associated proteins within tumour tissue section after on-tissue digestion. The coupling of MALDI-MSI with ion mobility separation (IMS) has been found to improve the specificity and selectivity of the method. Combining these two methodological approaches allowed the targeting and identification of known tumour biomarkers and potential protein markers in various tumour tissue samples including frozen AQ4N dosed colon tumour xenografts and FFPE human adenocarcinoma tissue sections. The localisation and identification of proteins correlated to tumour growth and aggressiveness were studied using IMS-Tag MALDI-MSI, a novel concept developed in this work. In order to demonstrate its use as a potential biomarker discovery tool, MALDI-MSI was used for high throughput analysis of proteins within tissue micro arrays. Combining MALDI-MSI with statistical analysis allowed the design of a novel tumour classification model based on proteomic imaging information after on-tissue digestion. Another challenge for the MALDI-MSI technology is to achieve more targeted quantitative approaches for in situ analysis of proteins. A proof-of-concept based on multiple reaction monitoring (MRM) analysis with MALDI-MSI is described using a high repetition rate solid state laser. This aimed to improve the sensitivity and specificity of the methodology for the investigation of peptides/proteins directly within tumour tissue sections.

Mass-selected cluster anions are employed as model micro-solutions to study solvent effects on the structural motifs and electronic structure of anionic solutes, including the roles of the solvent in controlling the outcomes of photochemical processes. Interaction of light with cluster anions can potentially lead to cluster photodissociation in addition to photodetachment. We investigate these competing processes by means of photoelectron imaging spectroscopy combined with tandem time-of-flight (TOF) mass spectrometry. Photoelectron images are reported for members of the [(CO2)n(H2O)m]- cluster series. For homogeneous solvation, the photodetachment bands show evidence of cluster core switching between a CO2- monomer anion and a covalent (CO2)2- dimer anionic core, confirming previous observations. The Photoelectron Angular Distributions (PADs) of the monomer- and dimer-based clusters reveal an interference effect that result in similar PADs. Stabilization of the metastable CO2- anion by water solvent molecules is highlighted because its ability to "trap" the excess electron on CO2. Most surprising is the effect of the water solvent in quenching the autodetachment channel in excited states normally embedded in the electron detachment continuum, allowing excited CO2-(H2O)m clusters to follow reaction paths that lead to cluster fragmentation. Observed O- based photoproducts are attributed to photodissociation of the CO2- cluster core and are dominant for small parent clusters, whereas a water evaporation channel dominates for larger clusters. Addition of a second CO2 to these clusters is shown to preferentially form monomer based clusters, whose photodissociation exhibit an additional CO3- based channel, characteristic of a photoinitiated intracluster ion-molecule reaction between nascent O- and the additional CO2 solvent molecule. Changes in the PADs of NO- are monitored as a function of electron kinetic energy for the NO-(N2O)n and NO-(H2O)n cluster anions. In contrast with hydration, angular distributions become progressively more isotropic for the N2O case, particularly when the photoelectron kinetic energies are in the vicinity of the 2Pi shape resonance of the N2O solvent molecules. First time observation of the CH3SOCH- anion of dimethylsulfoxide is reported along with the photoelectron images of this organic anion and of the monohydrated cluster. Observed photodissociation products are HCSO- and SO-.

Con il termine di –omica spaziale si intende l’insieme di diverse tecniche che consentono di rilevare alterazioni significative delle biomolecole all’interno dei loro tessuti d’origine o delle strutture cellulari, permettendo quindi di integrare ed ampliare la comprensione dei cambiamenti biologici che si verificano in tessuti patologici complessi ed eterogenei, come il cancro. Tuttavia, per comprendere appieno la complessità e le dinamiche al di là delle condizioni patologiche, è necessario studiare e integrare diverse analisi molecolari, come quelle di lipidi e glicani, in modo da ottenere un’istantanea molecolare il più completa ed estesa possibile della malattia. Tra le tecniche di -omica spaziale, quella di desorbimento e ionizzazione laser assistiti da matrice (MALDI) abbinata alla spettrometria di massa imaging (MSI), permette lo studio della componente molecolare del tessuto patologico tramite un approccio multiplex, che permette di esaminare diverse centinaia di biomolecole in una singola analisi. Pertanto, l’analisi MALDI-MSI viene utilizzata per studi -omici spaziali di proteine, peptidi e N-glicani su campioni di tessuti clinici fissati in formalina e inclusi in paraffina (FFPE). Per quanto riguarda i lipidi, invece, questo tipo di analisi è sempre stato considerato poco efficace su campioni FFPE a causa della perdita di una grande quantità di contenuto lipidico durante le fasi di lavaggio con solventi organici, mentre i restanti lipidi resistenti ai solventi sono inaccessibili poiché trattenuti nei legami incrociati della formalina. In questi tre anni di dottorato, abbiamo sviluppato nuovi approcci MALDI-MSI per l'analisi spaziale multi-omica su campioni di tessuto clinico FFPE. Le prime tre pubblicazioni riportate in questa tesi si sono concentrate sullo sviluppo di protocolli MALDI-MSI per lipidi in campioni FFPE. In particolare, due di essi descrivono il metodo di preparazione del campione per la rilevazione di ioni di fosfolipidi carichi positivamente, principalmente fosfatidilcoline (PC), in campioni clinici di carcinoma renale a cellule chiare (ccRCC) e in un modello di xenotrapianto di cancro al seno. La terza pubblicazione riporta la possibilità di utilizzare ioni di fosfolipidi carichi negativamente, principalmente fosfatidilinositoli (PI), per definire firme lipidiche in grado di distinguere i gradi di tumore del colon-retto che presentano diverse quantità di linfociti infiltranti il tumore (TIL). Il lavoro finale propone un originale metodo MALDI-MSI multi-omico per l'analisi sequenziale di lipidi, N-glicani e peptidi triptici su una singola sezione FFPE. In particolare, il metodo è stato inizialmente implementato su replicati tecnici di cervello murino e successivamente utilizzato su campioni di ccRCC, come ulteriore prova, ottenendo una caratterizzazione più completa del tessuto tumorale grazie alla combinazione delle informazioni molecolari. Complessivamente, questi risultati aprono la strada a un nuovo approccio multi-omico spaziale basato sulla spettrometria di massa imaging (MSI) che è in grado di restituire un ritratto molecolare più ampio e più preciso della malattia.
The field of spatial omics defines the gathering of different techniques that allow the detection of significant alterations of biomolecules in the context of their native tissue or cellular structures. As such, they extend the landscape of biological changes occurring in complex and heterogeneous pathological tissues, such as cancer. However, additional molecular levels, such as lipids and glycans, must be studied to define a more comprehensive molecular snapshot of disease and fully understand the complexity and dynamics beyond pathological condition. Among the spatial-omics techniques, matrix-assisted laser desorption/ionisation (MALDI)-mass spectrometry imaging (MSI) offers a powerful insight into the chemical biology of pathological tissues in a multiplexed approach where several hundreds of biomolecules can be examined within a single experiment. Thus, MALDI-MSI has been readily employed for spatial omics studies of proteins, peptides and N-Glycans on clinical formalin-fixed paraffin-embedded (FFPE) tissue samples. Conversely, MALDI-MSI analysis of lipids has always been considered not feasible on FFPE samples due to the loss of a great amount of lipid content during washing steps with organic solvents, with the remaining solvent-resistant lipids being involved in the formalin cross-links. In this three-year thesis work, novel MALDI-MSI approaches for spatial multi-omics analysis on clinical FFPE tissue samples were developed. The first three publications reported in this thesis focused on the development of protocols for MALDI-MSI of lipids in FFPE samples. In particular, two of them describe a sample preparation method for the detection of positively charged phospholipids ions, mainly phosphatidylcholines (PCs), in clinical clear cell Renal Cell Carcinoma (ccRCC) samples and in a xenograft model of breast cancer. The third publication reports the possibility to use negatively charged phospholipids ions, mainly phosphatidylinositols (PIs), to define lipid signatures able to distinguish colorectal cancers with different amount of tumour infiltrating lymphocytes (TILs). The final work proposes a unique multi-omic MALDI-MSI method for the sequential analysis of lipids, N-Glycans and tryptic peptides on a single FFPE section. Specifically, the method feasibility was first established on murine brain technical replicates. The method was consequently used on ccRCC samples, as a proof of concept, assessing a more comprehensive characterisation of the tumour tissue when combining the multi-level molecular information. Altogether, these findings pave the way for new MSI-based spatial multi-omics approach aiming at an extensive and more precise molecular portrait of disease.

A common analytical problem in applying LA sampling concerns dealing with large planar samples, e.g. gel plates, Si wafers, tissue sections or geological samples. As the current state of the art stands, there are two solutions to this problem: either sub-sample the substrate or build a custom cell. Both have their inherent drawbacks. With sub-sampling, the main issue is to ensure that a representative is sample taken to correctly determine the analytes of interest. Constructing custom cells can be time consuming, even for research groups that are experienced or skilled, as they have to be validated before data can be published. There are various published designs and ideas that attempt to deal with the issue of large samples, all of which ultimately enclose the sample in a box. The work presented in this thesis shows a viable alternative to enclosed sampling chambers. The non-contact cell is an open cell that uses novel gas dynamics to remove the necessity for an enclosed box and, therefore, enables samples of any arbitrary size to be sampled. The upper size limit of a sample is set by the travel of the XY stages on the laser ablation system, not the dimensions of the ablation cell.

Biomarker research is of great interest in the field of traumatic brain injury (TBI), since there are numerous potential markers that may indicate central nervous system damage, yet the brain is normally well isolated and discovery is at its infancy. Traditional methods for biomarker discovery include time consuming multi step chromatographic mass spectrometery (MS) techniques or pre-defined serial probing using traditional assays, making the identification of biomarker panels limiting and expensive. These shortfalls have motivated the development of a MS based probe that can be embedded into 3D neural cultures and obtain temporal and spatial information about the release of biomarkers. Using the high sensitivity MS ionization method of nano-electrospray ionization (nano-ESI) with an in-line microdialysis (MD) unit allows us to use MS to analyze low concentrations of TBI biomarkers from within cell cultures with no need for off-line sample manipulation. This thesis goes through the development of the probe by studying the theoretical principles, simulations and experimental results of the probe's capability to sample small local concentrations of a marker within cell culture matrix, the MD unit's sample manipulation capabilities, and the ability to detect markers using in-line MD-nano-ESI MS.

Two projects are presented here. In the first, metal-cyclopentadienyl bond dissociation energies (BDEs) were measured for seven metallocene ions (Cp2M+, Cp = η5-cyclopentadienyl = c-C5H5, M = Ti, V, Cr, Mn, Fe, Co, Ni) using threshold collision-induced dissociation (TCID) performed in a guided ion beam tandem mass spectrometer. For all seven room temperature metallocene ions, the dominant dissociation pathway was simple Cp loss from the metal. Traces of other fragment ions were also detected, such as C10H10+, C10H8+, C8H8+, C3H3+, H2M+, C3H3M+, C6H6M+, and C7H6M+, depending on the metal center. Statistical modeling of the Cp-loss TCID experimental data, including consideration of energy distributions, multiple collisions, and kinetic shifts, allow the extraction of 0 K [CpM+ - Cp] BDEs. These are found to be 4.95 ± 0.15, 4.02 ± 0.14, 4.22 ± 0.13, 3.51 ± 0.12, 4.26 ± 0.15, 4.57 ± 0.15, and 3.37 ± 0.12 eV for Cp2To+, Cp2V+, Cp2Cr+, Cp2Mn+, Cp2Fe+, Cp2Co+, and Cp2Ni+, respectively. The measured BDE trend is largely in line with arguments based on a simple molecular orbital picture, with the exceptions of a reversal in Cp2Mn+ and Cp2Ni+ BDEs (although within uncertainty), and the exceptional case of titanocene, most likely attributable to its bent structure. The new results presented here are compared to previous literature values and are found to provide a more complete and accurate set of thermochemical parameters. In the second project, imaging photoelectron photoion coincidence (iPEPICO) spectroscopy has been used to determine 0 K appearance energies for the unimolecular dissociation reactions of several energy selected 1-alkyl iodide cations n-CnH2n+1I+ → CnH2n+1+ + I, (n = 2-5). The 0 K appearance energies of the iodine-loss fragment ions were determined to be 9.836 ± 0.010, 9.752 ± 0.010, 9.721 ± 0.010, and 9.684 ± 0.010 eV for n-C3H7I, n-C4H9I, n-C5H11I, and n-C6H13I molecules, respectively. Isomerization of then-alkyl iodide structures into 2-iodo species adds complexity to this study. Using literature adiabatic ionization energies, ionic bond dissociation energies were calculated for the four modeled iodoalkyl cations and it was shown that as the alkyl chain length increases, the carbon-halogen bond strength decreases, supporting the suggestions set forth by inductive effects. In the modeling with statistical energy distributions and rate theory, the role of hindered rotors was also evaluated and no strong experimental evidence was found either way. The heaviest species in the series, heptyl iodide (C7H15I) was also measured via iPEPICO and showed to have a greater complexity of fragmentation than the lighter analogs. Sequential dissociation of the first fragment ion, C7H15+ leads to C4H9+, C5H11+, and C3H7+ ions in competitive dissociation processes, dominated at low energies by the C4H9+ cation.

Massenspektrometrisches Imaging (MSI) ist unverzichtbar für die Untersuchung der räumlichen Verteilung von Molekülen in einer Vielzahl von biologischen Proben. Seit seiner Einführung hat sich MALDI zu einer dominierenden Bildgebungsmethode entwickelt, die sich als nützlich erwiesen hat, um die Komplexität von Lipidstrukturen in biologischen Geweben zu bestimmen. Einerseits ist die Rolle von Cisplatin bei der Behandlung von menschlichen malignen Erkrankungen gut etabliert, jedoch ist Nephrotoxizität eine limitierende Nebenwirkung, die Veränderungen des renalen Lipidprofils beinhaltet. Dies führte zu der Motivation, die Lipidzusammensetzung des Nierengewebes in mit Cisplatin behandelten Ratten zu untersuchen, um die involvierten Lipid-Signalwege aufzuklären. Es wurde eine Methode zur Kartierung der Lipidzusammensetzung in Nierenschnitten unter Verwendung von MALDI MSI entwickelt. Die Verteilung von Nierenlipiden in Cisplatin-behandelten Proben zeigte deutliche Unterschiede in Bezug auf die Kontrollgruppen. Darüber hinaus wurde die Beurteilung der Ionenbilder von Lipiden in Cisplatin-behandelten Nieren meist als qualitative Aspekte betrachtet. Relative quantitative Vergleiche wurden durch den variablen Einfluss von experimentellen und instrumentellen Bedingungen begrenzt. Daher bestand die Notwendigkeit, ein Normalisierungsverfahren zu entwickeln, das einen Vergleich der Lipidintensität verschiedener Proben ermöglicht. Das Verfahren verwendete einen Tintenstrahldrucker, um eine Mischung der MALDI-Matrix und der internen internen Lipid-Metall-Standards aufzubringen. Unter Verwendung von ICP-MS erlaubte der interne Metallstandard, die Konsistenz der Matrix und der internen Standards zu bestätigen. Die Anwendung der Methode zur Normalisierung von Ionenintensitäten von Nierenlipiden zeigte eine ausgezeichnete Bildkorrektur und ermöglichte einen relativen quantitativen Vergleich von Lipidbildern in Cisplatin-behandelten Proben.
Mass spectrometry imaging is indispensable for studying the spatial distribution of molecules within a diverse range of biological samples. Since its introduction, MALDI has become a dominant imaging method, which proved useful to sort out the complexity of lipid structures in biological tissues. The role of cisplatin in the treatment of human malignancies is well-established. However, nephrotoxicity is a limiting side effect that involves an acute injury of the proximal tubule and alterations in the renal lipid profile. This evolved the motivation to study the spatial distribution of lipids in the kidney tissue of cisplatin-treated rats to shed light on the lipid signaling pathways involved. A method for mapping of lipid distributions in kidney sections using MALDI-LTQ-Orbitrap was developed, utilizing the high performance of orbitrap detection. The distribution of kidney lipids in cisplatin-treated samples revealed clear differences with respect to control group, which could be correlated to the proximal tubule injury. The findings highlight the usefulness of MALDI MSI as complementary tool for clinical diagnostics. Furthermore, assessment of the ion images of lipids in cisplatin-treated kidney mostly considered qualitative aspects. Relative quantitative comparisons were limited by the variable influence of experimental and instrumental conditions. Hence, the necessity developed to establish a normalization method allowing comparison of lipid intensity in MALDI imaging measurements of different samples. The method employed an inkjet printer to apply a mixture of the MALDI matrix and dual lipid-metal internal standards. Using ICP-MS, the metal internal standard allowed to confirm the consistency of the matrix and internal standards application. Applying the method to normalize ion intensities of kidney lipids demonstrated excellent image correction and successfully enabled relative quantitative comparison of lipid images in control and cisplatin-treated samples.

The pancreas is a large glandular organ with mixed exocrine and endocrine functions, located in the abdominal cavity behind the stomach. The endocrine portion, 1-2 % of its total volume, is represented by islets of Langerhans and plays a significant role in the pathophysiology of diabetes. The islets mainly contain β cells, which produce and release the hormonal protein insulin into the bloodstream in order to reduce glucose concentrations in the blood [1]. Dysfunction of this regulatory mechanism can lead to the development of type 2 diabetes mellitus (T2DM), a chronic metabolic disorder characterized by increased glucose levels in the blood and caused by either the resistance to insulin or the inability of β cells to produce (enough) insulin, or a combination of both [2,3]. The number of people affected by T2DM is growing world-wide, driven by the spread of obesity. The absence of characteristic symptoms complicates early diagnosis of the disease and can lead to premature death if left untreated [4]. For all these reasons, in order to get a better understanding of the complex pathophysiology leading to the onset of T2DM and its progression, elucidation of the molecular mechanisms underlying the disorder is paramount. This PhD thesis aims to characterize, at the molecular level, the pancreas, focusing particularly on the islet of Langerhans and on their involvement in type two diabetes. cells failure, in type two diabetes, is caused by several factors: environmental factors, such as high-fat diets and sedentary lifestyle, and genetic predisposition [5]. Individuals with high fasting levels of plasma free fatty acids (FFAs) have an elevated risk of developing T2DM [6]. In fact, prolonged exposure to FFAs impairs insulin secretion in vivo and in vitro [7,8] inducing β cells death [9]. Palmitate is the most common saturated FFA in human plasma and it has been used in vitro studies on isolated islets or β cells lines to investigate the mechanisms of lipotoxicity. Prolonged exposure to palmitate may promote the inhibition of insulin transcription [10], the induction of ER stress in β cells [11,12], the production of reactive oxygen species (ROS) [13], and ceramides [14] and finally to cells death. Some evidence suggest that palmitate could induce these effects through defects in mitochondrial function [13,15]. Nowadays, the relationship of lipotoxicity mechanisms to mitochondrial function is not well understood and remain under investigation. As far as mitochondria concerns, they play a central role in coupling glucose metabolism to insulin secretion. Mitochondrial dysfunction impairs glucose stimulated insulin secretion and may promote β cells death. Moreover, mitochondria are the major source of ROS but also the target of their damaging effects. An overproduction of free radicals in β cells by the mitochondrial respiratory chain produces peroxidation of mitochondrial membrane [16], impairment of ATP production [16] and damage of mitochondrial DNA [17] which regulates oxidative phosphorylation process involved in the insulin secretion from pancreatic β cells. The molecular mechanisms by which palmitate affects β cells function and survival, have been studied using different approaches such as RNA-based studies [18] and proteomic analysis [19]. Very recently, Cnop et al. [18], mapped the transcriptome of human islets of Langherans, by using RNA-sequencinq (RNA-seq), following a 48h exposure to the saturated FFA palmitate and suggesting novel mechanisms of palmitate-induced β cells dysfunction and death. Little is known about mitochondrial responses to induced-palmitate stress and about the mechanisms through which glucagon-like peptide-1 (GLP-1) exerts its potential protective effect in β cells mitochondrial dysfunction. Brun et al. [20], using pharmacological and siRNA approaches, investigated the mitochondrial responses in isolated INS-1E cells mitochondria preparations exposed to different stressors: glucose, fatty acids and oxidative stress. They suggested a selective modification in expression levels of energy sensors and mitochondrial carriers after these different stress conditions. As far as the proteomic approach concerns, only one paper showed the changes of INS-1E mitochondrial proteome after stress induced by high glucose exposure [21]. The purpose of the first part of this thesis was to investigate, for the first time, the lipotoxic effect of palmitate on mitochondria from rat INS-1E cells in the presence and in the absence of GLP-1 by using proteomics and metabolomics approaches. A different expression of mitochondrial proteins was evaluated by using two-dimensional electrophoresis (2-DE) coupled to tandem mass spectrometry (MS/MS) and quantitative shotgun analysis. The use of 2-DE allowed to validate shot-gun results and to overcome the limit of this technique by evaluating potential transformations which could occur in mitochondrial proteins such as post-translational modifications and protein degradation. Moreover, the metabolomic differences targeting aminoacids and carnitines, since they are related to the mitochondrial metabolism and activity, were measured. The study of mitochondrial alteration in rat INS-1E cells after treatment with palmitate and/or GLP- constitutes an important starting point before moving to the study of human cells and towards a better understanding of mitochondrial dysfunction in the context of type two diabetes. The second part of this thesis focused on the development of ultra-high resolution mass spectrometry imaging methods for the analysis of proteins in mouse and human pancreas tissues. The ability of matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) to simultaneously record the distributions of hundreds of molecules in tissue makes it a powerful discovery method for molecular pathology. MALDI-MSI combines the chemical specificity of modern mass spectrometry with the imaging capabilities of microscopy; it allows a highly multiplexed and untargeted analysis of biomolecular ions and enables their localization within the tissue section [22]. In clinical applications and diagnostics MALDI-MSI has been used to analyse a large variety of analyte classes, such as xenobiotics [23], metabolites [24], lipids [25,26], N-linked glycans [27,28], peptides [29], and proteins [30,31]. Sample preparation is critical to the success of a MALDI-MSI experiment, and must be optimized prior to any clinical investigation. Several reports on method development for protein analysis from different tissues have been published, and indicate that the optimum sample preparation method may be tissue type and application specific [32–34]. To date only a few studies have been published for MALDI-MSI of pancreas tissues. The ability of the MALDI-MSI to measure the peptide hormones located in the endocrine and exocrine pancreas was shown [35–37]. Minerva et al. [38,39] reported two different methods for the analysis of endogenous peptides from the pancreases of obese and wild type mice. Another three studies focused on the analysis of proteolytic peptides from pancreas [40–42], one of which compared healthy and type 1 diabetes [42]. Four studies focused on the analysis of intact proteins from pancreas: a 3D MALDI-MSI datasets from mouse pancreas in the mass m/z range 1600-15000 had been registered [43], and three focused on biomarker discovery on pancreas cancer tissue (ductal cancer, pre-neoplastic pancreatic lesions, pancreatic adenocarcinoma and insulinoma) [44–46]. When analysing intact proteins in clinical tissue samples the possibility of post-translational modifications (PTMs) and proteolytic processing must be considered, especially for pancreas tissue which is characterized by rapid post mortem degradation [47]. The analysis of intact proteins allows the identification of any proteoforms by retaining any PTMs or proteolytic processing, and which can be clinically very relevant. Poté et al. [48] have demonstrated that a specific protein acetylation was indicative of microvascular invasion in hepatocellular carcinoma, and a specific truncation of thymosin beta 4 has been found to be associated with stromal activation in breast cancer and patient survival in malignant melanoma [49]. MALDI-MSI of intact proteins has been performed predominantly using time-of-flight (TOF) based mass spectrometers, operated in linear mode [50,51]. Linear MALDI-TOF systems provide limited resolving power and mass accuracy (50-200 ppm) [52], which complicates protein identity assignments by mass matching MSI datasets with liquid chromatography (LC) MS/MS-based protein identifications. Recently Fourier transform ion cyclotron resonance (FTICR) mass spectrometry has been adapted for MALDI profiling [53–55] and MALDI-MSI [56]. MALDI-FTICR-MSI provides the high mass accuracy and high resolving power required to analyse intact proteins (≤ 17.000 m/z) with isotopic resolution, and to assign protein identities with additional confidence [56]. In the current work the workflows for the MSI analysis of intact proteins directly from pancreas tissue by MALDI-TOF-MS and MALDI-FTICR-MS had been developed. Method development, with special emphasis on sample preparation (e.g., tissue washing, matrix choice, MALDI-matrix deposition) was performed on mouse pancreas tissues. Afterward, the method optimization was extended to the analysis of endogenous peptides. The embedding of the tissue in a supporting material allows easy handling and precise microtoming of sections. In clinical laboratories, for histological applications, tissues cut on cryostat microtomes are usually embedded in the optimal cutting temperature (OCT) polymer. However, care should be taken to avoid contamination of the tissue sections with OCT, because its components can lead to ion suppression during mass spectrometry analysis by MALDI-TOF-MS. Recently, there is evidence [57] that it is feasible to analyse lipids from tissues embedded in OCT compound by MALDI-MSI after extensive tissue washing using water-based solutions. Also Green-Mitchell et al. [42] in the study on on-tissue reduction of insulin, used OCT embedded pancreas tissues. Seeley et al. [58] in a review of 2008 also reported that, after washing steps to remove OCT, “[…] spectra obtained from OCT-embedded samples are virtually identical to those obtained from fresh frozen tissue”. However, most of the studies principally showed how the PEG contamination in the spectra is reduced after removing OCT compound with suitable washing steps [34,59], but any of them showed the comparison between data from OCT-embedded and non-embedded tissues after the application of the same sample preparation procedure. On this basis, here an in-depth comparison between mass spectrometry imaging data obtained from OCT-embedded and non-embedded tissues was performed. The optimized methods were applied to a small set of human pancreas samples (3x T2DM and 3x control), so that small endocrine compartments (islets of Langerhans) may be analysed in control and pathological tissues. In particular, human pancreas samples were collected from the same individual both OCT-embedded and non-embedded. References [1] Gittes, G., Developmental biology of the pancreas: a comprehensive review. Developmental biology 2009, 326, 4–35. 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Le cancer est la deuxième cause de décès dans le monde, avec 10 millions de morts et 19 millions de nouveaux cas en 2020. Le cancer du sein, le plus fréquent chez les femmes, comptait 2,26 millions de cas et près de 685 000 décès cette même année, soulignant l'urgence de recherches ciblées. Le diagnostic repose souvent sur des biopsies analysées histopathologiquement pour identifier les caractéristiques moléculaires des cellules cancéreuses. En fonction de l'expression de certains biomarqueurs (récepteurs hormonaux, oncoprotéines, récepteurs de facteurs de croissance), les sous-types de cancer du sein sont classés pour orienter le traitement. Pourtant, environ 30 % des patientes connaissent une récidive ou des métastases, principalement en raison de l'hétérogénéité tumorale. Les études génomiques ont révélé que les tumeurs du sein contiennent des sous-populations cellulaires distinctes, avec des réponses variées aux traitements. Comprendre et traiter cette complexité est essentiel pour améliorer les résultats thérapeutiques.L'objectif principal de cette étude est d'affiner la caractérisation des tumeurs en évaluant l'hétérogénéité protéomique du cancer du sein. Grâce à la spectrométrie de masse, notamment l'imagerie MALDI, cette étude vise à identifier et analyser les sous-populations moléculaires des tumeurs. En comprenant cette hétérogénéité, des cibles thérapeutiques potentielles peuvent être identifiées, permettant le développement de traitements plus personnalisés adaptés à chaque profil tumoral. Les résultats initiaux sur oragnoides de patientes ont montré que les traitements guidés par la protéomique surpassaient les thérapies conventionnelles, offrant une meilleure efficacité antitumorale. Cette approche a aussi permis d'identifier des biomarqueurs associés à la résistance aux médicaments, orientant ainsi les futures stratégies de traitement. Cependant, elle nécessite une grande quantité de matériel biologique et est chronophage, ce qui complique son application clinique à grande échelle.Le deuxième objectif de l'étude est de développer un modèle d'apprentissage automatique pour prédire les voies biologiques et informations protéiques à partir des analyses lipidiques via MALDI MSI. Ce modèle, appelé 'dry proteomic', relie les clusters lipidiques aux voies protéiques, améliorant la caractérisation tumorale sans nécessiter de longs processus protéomiques. Validée sur des tissus cérébraux de rats puis appliquée au glioblastome, cette approche a démontré son potentiel pour analyser des tumeurs complexes et hétérogènes. Elle permet de réduire le temps nécessaire pour analyser les tumeurs du sein, facilitant ainsi une utilisation clinique plus rapide.Le troisième objectif est d'appliquer le concept de dry proteomic pour mieux comprendre l'hétérogénéité spatiale et temporelle du cancer du sein. En prenant en compte l'expansion clonale, les sous-types tumoraux et l'historique des traitements, cette méthode vise à identifier des cibles exploitables à différents stades de la maladie.Le dernier objectif consiste à développer une nouvelle technique d'IHC multiplexée utilisant la technologie "tag mass". Cette méthode permet une identification rapide et précise des cibles protéiques pour une intervention thérapeutique et offre une cartographie spatiale de ces cibles. De plus, elle permet d'analyser les interactions entre cellules tumorales et immunitaires, renforçant ainsi la précision des traitements, notamment dans le cadre de l'immunothérapie.Ces objectifs de recherche visent à améliorer la caractérisation des tumeurs du sein, à optimiser les stratégies thérapeutiques et à surmonter l'hétérogénéité moléculaire qui contribue à la résistance aux traitements et aux récidives. En intégrant la protéomique, les prédictions basées sur l'intelligence artificielle et les techniques d'imagerie avancée, cette étude cherche à révolutionner le traitement personnalisé du cancer du sein et à améliorer les résultats pour les patientes
Cancer remains the second leading cause of death globally, with approximately 10 million cancer-related deaths and 19 million new cases reported in 2020. Breast cancer is the most prevalent type among women, accounting for 2.26 million cases and nearly 685,000 deaths in 2020, highlighting the urgent need for focused research on this disease. Diagnosis typically relies on biopsy samples examined through histopathological analysis, identifying the molecular and morphological characteristics of cancer cells. Based on the expression of hormone receptors, oncoproteins, growth factor receptors, and other biomarkers, breast cancer subtypes are classified to guide treatment. However, despite current therapies, approximately 30% of patients experience recurrence or metastasis, largely due to tumor heterogeneity. Genomic studies have revealed that breast cancer tumors are composed of genetically distinct subpopulations of cells, each with unique molecular profiles and varied responses to treatment. Understanding and addressing this complexity is critical to improving therapeutic outcomes.The study's primary objective is to refine tumor characterization by assessing the proteomic heterogeneity of breast cancer. Through the use of mass spectrometry, specifically MALDI MSI, the research aims to identify and analyze the distinct molecular subpopulations within tumors. By understanding this heterogeneity at a proteomic level, potential druggable targets can be identified, facilitating the development of more personalized treatments tailored to individual tumor profiles. Initial results from patient-derived tumor samples showed that proteomics-guided treatments outperformed conventional therapies, offering better anti-tumor efficacy. This approach also identified biomarkers related to drug resistance, helping to guide future treatment strategies. However, this method requires large amounts of biological material and can be time-consuming, posing challenges for widespread clinical application.The second objective focused on developing a machine learning model to predict biological pathways and protein information from lipid analysis via MALDI MSI, thus bypassing the need for separate spatial proteomics experiments. This "dry proteomics" method aims to link lipid clusters to protein pathways, enhancing tumor characterization without lengthy proteomic workflows. The approach was first validated using rat brain tissues and then applied to glioblastoma, confirming its potential in analyzing complex, heterogeneous tumors. By enabling faster predictions of protein data from lipid images, this method could significantly reduce the time required for breast cancer tumor analysis, making it more feasible for clinical use.The third objective involves applying the dry proteomics workflow to better understand the spatial and temporal heterogeneity of breast cancer. By accounting for clonal expansion, tumor subtypes, and treatment history, this approach seeks to identify actionable targets at various stages of the disease.The final objective is the development of a novel MALDI IHC multiplex technique, using tag mass technology. This approach will allow for rapid, sensitive identification of key protein targets for therapeutic intervention and provide spatial mapping of these targets. Additionally, this method enables detailed analysis of the interactions between tumor and immune cells, enhancing the precision of treatments, especially in immunotherapy contexts.Together, these research objectives aim to improve the characterization of breast cancer tumors, enhancing the precision of therapeutic strategies by addressing the molecular heterogeneity that contributes to treatment resistance and disease recurrence. By integrating proteomic data, machine learning predictions, and advanced imaging techniques, this study seeks to revolutionize personalized breast cancer treatment and improve patient outcomes through a more tailored approach to therapy

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.

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.

Cette thèse vise à relever le défi sanitaire urgent de la tuberculose (TB) par le développement d'une stratégie d'imagerie par spectrométrie de masse quantitative ou QMSI, en se concentrant spécifiquement sur les médicaments antiTB tels que la clofazimine (CFZ), la rifampicine (RIF), et l'éthambutol (ETM). TB, causée par Mycobacterium tuberculosis (Mtb), constitue une menace pour la santé mondiale, également renforcée par la résistance bactérienne, induisant la mise en place de lignes de thérapie basées sur l'utilisation d'un traitement adapté et plus efficace avec un panel d'antibiotiques éprouvés. Tout ceci requière une meilleure compréhension globale de la quantification des médicaments dans l'espace et de la caractérisation de la matrice biologique environnante.Le design expérimental est basé sur le modèle d'un mime tissulaire pour le développement d'une approche de QMSI de plusieurs antibiotiques à partir d'une unique coupe de tissu, établissant un équilibre entre la quantification précise des médicaments, la préservation du microenvironnement tissulaire, ainsi que la compatibilité avec l'imagerie multimodale. Les défis associés à la diversité des médicaments antiTB, chacun ayant des exigences analytiques uniques, sont relevés. Le choix des médicaments se porte sur la CFZ, la RIF, et l'ETM en raison de leur détectabilité et de leur pertinence clinique.Le premier objectif détaille l'optimisation de la QMSI à travers un modèle de tissu mime, l'établissement de la courbe d'étalonnage, et la justification du choix des médicaments. Les résultats et la discussion couvrent l'évaluation de la détection des médicaments dans des tissus pulmonaires de souris infectées par Mtb puis traitées avec un panel d'antibiotiques, la détermination de la sensibilité et des limites de détection, et les subtilités de l'approche QMSI. Les défis spécifiques à la CFZ, tels que la solubilité, sont abordés. A notre connaissance, l'étude aboutit pour la première fois à la quantification de la CFZ par MALDI-MSI.Sur la base de ces travaux, une nouvelle approche basée sur la MALDI QMSI a été développée pour la quantification et la localisation simultanées de la CFZ, de la RIF, et l'ETM. De par l'apport de la MALDI-MSI en termes de résolution spatiale et au regard des résultats encourus, cette étude surpasse la microdissection laser combinée à la chromatographie en phase liquide, et se présente comme une alternative crédible.L'analyse en mode ionisation positif révèle que la CFZ s'accumule au niveau du bord cellulaire, et dans les macrophages spumeux, tandis que l'ETM se localise principalement dans le système vasculaire. La RIF, dont l'analyse a été effectuée en mode d'ionisation négatif, présente une distribution plus uniforme dans les régions tissulaires. L'acquisition à double polarité, fournit un ensemble de données complet, détectant également les espèces lipidiques bactériennes associées à Mtb à partir d'une unique coupe de tissu.Nous tirons pleinement partie de la nature hyperspectrale du MALDI-MSI comme base d'analyse afin de quantifier les médicaments dans les tissus, notre objectif principal. Cependant, nos décisions QMSI ont été prises en toute conscience pour faciliter les futures analyses multi-omiques et multimodales. De telles analyses multi-omiques ont été explorées par MALDI-MSI, ainsi que la faisabilité d'implémenter d'autres modalités telles que la spectroscopie Raman, et l'imagerie MALDI associée à l'immunohistochimie (MALDI-IHC).Les approches de cette thèse font progresser notre compréhension des niveaux de médicaments dédiés au traitement de la TB, et mettent en évidence la polyvalence de la MALDI QMSI pour des applications plus larges. Les résultats de l'étude offrent un outil puissant pour évaluer l'efficacité des médicaments dans des micro-environnements complexes, fournissant des informations précieuses sur la distribution des médicaments et leurs caractérisations moléculaires, ainsi que leurs quantifications multi-cibles
This thesis aims to address the urgent health challenge of tuberculosis (TB) through the development of a robust and efficient quantitative mass spectrometry imaging (QMSI) strategy, specifically focusing on the anti-TB drugs - clofazimine (CFZ), rifampicin (RIF), and ethambutol (ETM). TB, caused by Mycobacterium tuberculosis (Mtb), poses a global health threat, also reinforced by bacterial resistance, leading to the implementation of lines of therapy based on the use of an adapted treatment with a panel of proven antibiotics for more effective treatment. For these reasons, a more comprehensive understanding of spatially-aware drug quantification and characterization of the surrounding molecular microenvironment is required.The investigation adopts the tissue mimetic model for the development of a QMSI approach for the quantification of multiple antibiotics from a single tissue section, striking a balance between accurate drug quantification, preservation of the tissue microenvironment, as well as compatibility with multimodal imaging. Challenges associated with the diverse panel of TB drugs, each with unique analytical requirements, are navigated. The choice of drugs prioritizes CFZ, RIF, and ETM for their detectability and clinical relevance.The first aim details the adoption of QMSI through the mimetic tissue model, calibration curve establishment, and the rationale behind drug choices. Results and discussion cover the evaluation of drug detectability in lung tissue from mice infected with tuberculosis and then treated with a panel of antibiotics, and discusses the determination of sensitivity and detection limits, and the intricacies of the QMSI approach. Challenges specific to CFZ, such as solubility, are addressed. The study culminates in the quantification of CFZ by MALDI-MSI for the first time to our knowledge.Building on this groundwork, a novel MALDI QMSI workflow is developed for the simultaneous quantification and localization of CFZ, RIF, and ETM in TB-infected mouse lung tissue. The study surpasses the gold standard of laser capture microdissection combined with liquid chromatography MS regarding spatial resolution.Positive ionization mode analysis reveals CFZ accumulating in the cellular rim and within foamy macrophages, while ETM primarily localizes in the vasculature. RIF, which was analyzed in negative ionization mode, exhibits a more uniform distribution across tissue regions. By analyzing in both positive and negative ionization modes, a comprehensive dataset detecting bacterial lipid species associated with Mtb from a single tissue section is obtained.We leverage the hyperspectral nature of MALDI-MSI as the basis for analyses in order to quantify drugs in tissue, our main objective; however, our QMSI decisions were informed to facilitate future multi-omic and multimodal analyses. Such multi-omic analyses were explored by MALDI-MSI, as well as the feasibility of implementing other modalities such as Raman spectroscopy and MALDI-Immunohistochemistry (MALDI-IHC).The approaches of this thesis advance our understanding of drug levels in TB-infected tissue and showcase the versatility of MALDI QMSI for broader applications. The study's outcomes offer a powerful tool for evaluating drug efficacy in complex microenvironments, providing valuable insights into the molecular characterization and multi-targeted quantification of anti-TB drugs

In this thesis, the detection of global proteomics alteration and changes in neuropeptide distribution caused by neuropathic pain in rat spinal cord tissue was the main focus. Neuropathic pain (NP) is a major clinical syndrome caused by disease or dysfunction of the nervous system and often mediated by neuronal networks in the spinal cord. The estimated prevalence of NP is 6-8% in general population. Only in the United States, the indirect cost associated with chronic pain has been estimated to 100 billion dollars each year and NP substantially contributes to this cost. So far, the underlying mechanisms of NP are not well understood. Proteomics techniques are commonly used in biology system studies, due to its high throughput, capability of unbiased analysis and sensitivity. It builds up a bridge to link genes, peptides, proteins, and the disease. Two proteomic/peptidomic approaches were developed, evaluated and discussed in this thesis. Both of them were further applied in the studies of neuropathic pain. First approach is a quantitative proteomic approach using liquid chromatography combined with Fourier transform mass spectrometry (LC-FTMS), which is developed for quantitative analysis of proteins originated from small central nervous system (CNS) samples. This approach was successfully applied in the study of the rat spinal cord tissue proteome in a neuropathic pain model. Another approach is using matrix assisted laser desorption ionization mass spectrometry (MALDI-MS) for the visualization of the distribution of neuropeptides in rat spinal cord, which in the future will be applied in investigating the ongoing signal transmission under neuropathic pain conditions. Results provided by these two methods are of high importance for the general understanding of the underlying pathophysiological mechanisms and potential identification of new targets for novel treatment of neuropathic pain.

By providing both the chemical identity and the spatial organization of each component in biological samples, Imaging Mass Spectrometry (IMS) becomes an emerging tool in clinic and pharmacological study. Most work in IMS has been focused on protein and peptide mapping in biological samples to take advantage of effective analyte ionization in MALDI-MS, and also partially due to the limitation of MALDI-MS in small molecule detection. The focus of my research is to develop novel tools to image spatial distribution of small molecules in biological samples. A surface-based mass spectrometric imaging method, i.e. Desorption/Ionization on Silicon (DIOS), was used for biological surface analysis in the concept-proof investigation. More over, possible proton transferring pathways and impact of local chemical environment have been systematically investigated in the fundamental understanding of ionization mechanism of SALDI-MS. Based on the finding on the SALDI mechanism, a hybrid ionization approach, ME-SALDI has been developed by combing the strength of the conventional MALDI matrix and SALDI, where the improved detection sensitivity with reduced matrix-analyte interference and the improved imaging capability through analysis of mouse brain and heart sections has been demonstrated. In addition, the impact of vacuum stability of matrix in ME-SALDI-IMS applications has been examined. A solvent free, homogenous and reproducible sublimation method has been developed for ionic matrix in ME-SALDI, by which improved vacuum stability and MS detection have been achieved. Furthermore, a new generation of meso-porous oxide substrate was developed as a novel ME-SALDI substrate with a superior storage stability, extended detectable mass range and robust substrate preparation.

Orientador: Rodrigo Ramos Catharino
Texto em português e inglês
Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Ciências Médicas
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Resumo: Atualmente, as doenças cardiovasculares constituem uma das primeiras causas de mortes no Brasil e no mundo. Neste cenário, as estatinas constituem uma notável classe de medicamentos redutores de colesterol e têm sido associadas com uma expressiva diminuição da morbidade e mortalidade cardiovascular para pacientes em prevenção primária ou secundária da doença coronariana. Elas agem inibindo competitivamente a enzima HMG-CoA redutase, através da afinidade destes fármacos pelo sítio ativo da enzima. Esta enzima é responsável por catalisar a conversão do substrato HMG-CoA em mevalonato, um dos precursores do colesterol. A crescente necessidade e busca por medicamentos cada vez mais efetivos traz a preocupação na segurança destes produtos para seus usuários. Neste sentido, o conhecimento das impurezas e produtos de degradação torna-se necessário para garantir sua qualidade. Uma técnica muito utilizada para análises de impurezas e degradantes é a espectrometria de massas, pois é uma técnica sensível e seletiva e permite elucidar as estruturas químicas presentes na formulação do medicamento. Sendo assim, amostras de Atorvastatina cálcica foram analisadas pela técnica de espectrometria de massas por imagem (MALDI-MSI), permitindo a quantificação de impurezas do medicamento através da imagem da distribuição dessa impureza no comprimido. Dessa forma, é possível minimizar o preparo de amostra e obter um melhor conhecimento da formulação
Abstract: Currently, cardiovascular diseases constitute one of the first causes of deaths in Brazil and in the world. In this scenario, the statins are a notable class of medicines and cholesterol reducers have been associated with a significant reduction in cardiovascular morbidity and mortality for patients in primary or secondary prevention of coronary heart disease. They act by inhibiting competitively the enzyme HMG-CoA reductase, through the affinity of these drugs by the active site of the enzyme. This enzyme is responsible for catalyzing the conversion of HMG-CoA to mevalonate substrate, one of the precursors of cholesterol. The growing need and search for increasingly effective drugs brings the concern on the safety of these drugs for their users. In this sense, the knowledge of the impurities and degradation products becomes necessary to ensure their quality. A widely used technique for analysis of impurities and degrading is mass spectrometry, because it is a sensitive and selective technique and allows elucidating the chemical structures of the present formulation of the medicinal product. Thus, samples of Atorvastatin calcium were analyzed by the technique of mass spectrometry imaging (MALDI-MSI), which allows the quantification of impurities from the medicine through the image of the distribution of impurity in the tablet. That way, it is possible minimize sample preparation and get a better understanding of the formulation
Mestrado
Ciencias Biomedicas
Mestra em Ciências Médicas

Laser Ablation Inductively coupled plasma mass spectrometry (LA-ICP-MS) and Raman spectroscopy are both powerful imaging techniques. Their applications are numerous and extremely potential in the field of biology. In order to improve upon LA-ICP-MS an in-house built cold cell was developed and its effectiveness studied by imaging Brassica napus seeds. To further apply LA-ICP-MS and Raman imaging to the field of entomology a prong gilled mayfly (Ephemeroptera: Leptophlebiidae) from the Róbalo River, located on Navarino Island in Chile, was studied. Analysis of both samples showcased LA-ICP-MS and Raman spectroscopy as effective instruments for imaging trace elements and larger molecules in biological samples respectively.

We have built an imaging mass spectrometer adapted for ultrashort laser pulses as its ionization technique, as an alternative to other imaging techniques. Before my arrival, the mass spectrometer has only been subject to preliminary tests on noble gases. Since then, we’ve made some modifications to the system in order to properly analyze solids. This thesis shows how we obtain our ultrashort laser pulses, the inner workings of our homemade imaging mass spectrometer, and the results that we’ve obtained with it so far. We tested two modes of operation concerning the extraction of the ions from the system into the mass analyzer: continuous and pulsed. We discuss the advantages and disadvantages of each configuration. We also display preliminary imaging results with our imaging technique of a simple WO3 and ITO structure. We conclude by comparing the resolution of this image to the different techniques in imaging mass spectrometry, how we can further improve our mass spectrometer, and the future use of this machine. Nous avons construit un spectromètre de masse adapté pour les pulses de laser très courts comme technique d’ionisation, pour acquisition des images d’un échantillon. Avant je suis arrivé, le spectromètre de masse avait seulement été utilisé pour des tests préliminaires de gaz nobles. Depuis ce moment, nous avons modifié le système pour analyser les solides. Cette thèse démontre comment on obtient nos pulses de laser très courts, comment notre spectromètre fait maison fonctionne et les résultats nous avons obtenus jusqu’à présent. Nous avons testé deux configurations différentes au sujet de l’extraction des ions du système : constant et pulsé. Nous discutons aussi les avantages et désavantages de chaque mode d’opération. Nous démontrons aussi des images préliminaires d’un substrat mixte de WO3 et ITO. Nous concluons par comparer la résolution des images aux autres techniques de collection d’images, comment nous pouvons améliorer notre spectromètre de masse et les plans pour la machine dans le futur.

Chronical kidney disease (CKD) is a worldwide health problem with increasing incidence, where the major part accounts for chronic glomerulonephrites (GN). It is a group of diseases of various aetiology and multiform clinical course, having various prognosis which is often hardly predictable as well as existing prognostic markers are not always certain. There is an urging need of new reliable and specific prognostic and therapeutic markers research. A modern proteomic technology - Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) has been employed in many GN studies showing promising results. We aimed to study several forms of primary and secondary glomerulonephrites (membranous nephropathy, IgA nephropathy, diabetic nephropathy) to enlighten possible molecular alterations significant of diseases’ progression. The studies were performed on renal tissue biopsies, analysing them with high spatial resolution MALDI-MSI to get better visualisation of signals’ co-localisation on tissue. We performed a comparison of molecular profiles of various forms of GN. As a result, we were able to generate and distinguish specific tryptic peptides profiles of different cell regions (tubules, glomeruli, interstitium, connective tissue) and detect proteins with an altered intensity, implicated in inflammatory and healing pathways. MALDI-MSI, being able to define renal structures, could provide additional diagnostic and prognostic information. Generation of collective diagnostic panels may fulfil our pathogenesis understanding and assist clinical prognostic assessment.
Chronical kidney disease (CKD) is a worldwide health problem with increasing incidence, where the major part accounts for chronic glomerulonephrites (GN). It is a group of diseases of various aetiology and multiform clinical course, having various prognosis which is often hardly predictable as well as existing prognostic markers are not always certain. There is an urging need of new reliable and specific prognostic and therapeutic markers research. A modern proteomic technology - Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) has been employed in many GN studies showing promising results. We aimed to study several forms of primary and secondary glomerulonephrites (membranous nephropathy, IgA nephropathy, diabetic nephropathy) to enlighten possible molecular alterations significant of diseases’ progression. The studies were performed on renal tissue biopsies, analysing them with high spatial resolution MALDI-MSI to get better visualisation of signals’ co-localisation on tissue. We performed a comparison of molecular profiles of various forms of GN. As a result, we were able to generate and distinguish specific tryptic peptides profiles of different cell regions (tubules, glomeruli, interstitium, connective tissue) and detect proteins with an altered intensity, implicated in inflammatory and healing pathways. MALDI-MSI, being able to define renal structures, could provide additional diagnostic and prognostic information. Generation of collective diagnostic panels may fulfil our pathogenesis understanding and assist clinical prognostic assessment.

Biological functions within cells and organisms are mainly carried out by the translational products; proteins and peptides. The analysis and characterization of these biomolecules are of great importance for the progress in disease research and biomarker and drug discovery. The term peptidomics was introduced to describe the comprehensive analysis of peptides (e.g. neuropeptides) in biological tissues. In this thesis, a peptidomics approach using nanoflow liquid chromatography coupled to electrospray mass spectrometry (MS) has been developed for detection, identification, and quantification of neuropeptides in different disease models. A thoroughly controlled sample preparation technique and targeted neuropeptide sequence collections have been used to improve sample quality and to increase the number of identified neuropeptides. In particular, neuropeptide changes in experimental models of Parkinson’s disease (PD), with or without L-DOPA treatment, and the effect of antidepressant treatment on neuropeptide expression have been investigated. Several novel, potentially bioactive, neuropeptides have been identified and a number of peptides derived from precursors such as secretogranin-1, preproenkephalin-B, and somatostatin have been found differentially expressed. Some of them represent novel findings, not previously associated with PD or treatment with antidepressants. In addition, MALDI imaging MS (IMS), a technology that permits detection and spatial distribution determination of endogenous compounds and/or administered drugs directly on tissue sections, has been used in both small protein and drug applications. MALDI IMS on tissue samples from experimental models of PD revealed differential expression patterns of two small proteins involved in calcium regulation, PEP-19 and FKBP-12. Biomolecular interaction analysis was performed on FKBP-12 using surface plasmon resonance together with MS and several potential binding partners were identified. In a second approach, MALDI IMS was used to study the distribution of the anticholinergic bronchodilator tiotropium in rat lung following inhalation of the drug. The distribution of the drug was monitored in both MS and MS/MS mode and the levels where linearly quantifiable in the range of 80 fmol – 5 pmol. Conclusively, in this thesis mass spectrometry based technologies have successfully been developed to detect, identify, and characterize small proteins, peptides, and drugs in various tissue samples.

This thesis presents applications of high resolution secondary ion mass spectrometry (NanoSIMS) analysis for stable isotope imaging in biological samples. These projects were designed to explore the potential applications of NanoSIMS analysis, and to develop protocols and novel methodologies to visualize and quantify biological processes. Working with collaborators in the UK and USA, I have applied NanoSIMS analysis to study 3 research areas, including molecule interactions, single cell metabolisms and lipid imaging in tissues. Antimicrobial peptides (AMPs) play important role in the immune system, and understanding how AMPs interact with cell membranes can provide useful information to design new therapies to control infection. The pore structures and dynamics of the interaction of AMPs with membranes has been visualized for the first time and confirmed with combined AFM and NanoSIMS analysis. A correlative backscattered electron (BSE) imaging and NanoSIMS analysis methodology has been developed to study glutamine metabolism in single cancer cells. This method enables us to measure the chemical information in specific organelles in these cells and can be widely applied to study metabolisms and to trace the uptake of labelled molecules in biological matrices. Quantitative analysis on the effects of hypoxic conditions and the PYGL gene were studied. Applying correlative BSE and NanoSIMS analysis, I also studied lipid uptake mechanisms in various mouse tissues, including brown adipose tissue, heart, intestines, liver and skeletal muscle, mainly focused on a recently discovered protein, GPIHBP1, and its function in the lipid uptake process. TRL margination was proved to depend on the GPIBP1-LPL complex, and 3 stages of lipid transport from capillary lumen to lipid droplets was also visualized by combined BSE and NanoSIMS analysis.

Time-of-flight secondary ion mass spectrometry (ToF-SIMS) has proven its ability to characterise (in)organic surfaces, and is increasingly used for the characterisation of biological samples such as single cells. By combining ion imaging and molecular depth profiling it is possible to render 3D chemical images, which provides a novel, label-free way to investigate biological systems. Major challenges lie, however, in the development of data analysis tools and protocols that preserve the cell morphology. Here, we develop and employ such tools and protocols for the investigation of neuronal networks. One of the reasons 3D ToF-SIMS imaging of cells is underused is the lack of powerful data analysis tools as 3D ToF-SIMS measurements generate very large data sets. To address this issue, we developed a method that allows the application of principal component analysis (PCA) to be expanded to large 3D images making 3D ToF-SIMS image processing of whole, intact cells and cellular networks with multivariate analysis now accessible on a routine basis. Using this method, we are able to separate cellular material from the substrate and can then correct z-offsets due to the cells' topography resulting in a more accurate surface heightmap. The method also facilitates differentiation between cellular components such as lipids and amino acids allowing the cell membrane, the cytoplasm and the extracellular matrix (ECM) to be easily distinguished from one another. These developments permit us to investigate the intracellular localisation of specific native and non-native compounds label-free, not just in single cells but also in larger cellular networks. The visualisation of the cellular uptake of non-native compounds, namely fluorescent dyes, in primary rat cortical neurons and the chemical differentiation between cell types, namely primary rat cortical neurons and retinal pigment epithelium (RPE) cells, are presented as applications. Even though the dyes have distinct fragment ions in the high mass range, it was not possible to detect the fluorophores by 3D ToF-SIMS imaging of freeze-dried cells. However, it was possible to detect distinct differences in the kind of ions detected for freeze-dried primary rat cortical neurons and RPE cells albeit in the low mass range. To obtain meaningful results, however, it is paramount that sample preparation does not induce significant physical or chemical changes. We present the first comprehensive comparison between large 3D ToF-SIMS images of freeze-dried and frozen-hydrated cells using PCA to facilitate the data analysis of these large data sets. A higher degree of colocalisation of the K+ signal with cell regions is observed for frozen-hydrated cells, which indicates a lower degree of membrane damage and migration of diffusible chemical species. Frozen-hydrated cell samples are therefore considered to best reflect the native cell state, but freeze-dried cell samples allow far easier sample handling. The mass spectrum of frozen-hydrated cellular material also has increased ion intensities for higher-mass fragments, which is an additional advantage, because the poor signal-to-noise ratio of molecular species with m/z > 200 is a major bottleneck in the advancement of ToF-SIMS imaging as a diagnostic tool.