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Glioblastoma (GBM) is the most common and most aggressive primary brain tumour, with an extremely poor prognosis. Despite extensive research into this aggressive tumour, overall survival has been unaffected in the past 15 years with average survival at 12-15 months with optimal standard of care treatment. Glioblastoma tumour cells exhibit strong proliferative and infiltrative characteristics, which contributes to the infiltration of tumour cells into healthy brain. This feature means safe total resection of all tumour cells is impossible, which contributes to the poor survival and prognosis of GBM. Defining a safe tumour volume for resection and further understanding the underlying biochemistry of glioblastoma tumour cells at the molecular level, are therefore important aspects of research that can help to improve overall patient survival. Investigation of the lipidomic changes associated with tumours is a rapidly growing field, with mass spectrometry imaging techniques widely used for molecular pathology applications. Lipidomic profiling provides downstream analysis of the proteomic and genomic changes that are also used to characterise tumours. Mass spectrometry imaging analysis by desorption electrospray ionisation mass spectrometry (DESI-MS) imaging provides an ideal toll to study investigate lipid profiles and small molecules pre-clinical model of GBM and human GBM biopsies. Laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) imaging is highly specified for metal analysis and has also been used to study the metal ion distribution in the pre-clinical model of GBM, particularly that of gadolinium which was used as an MRI contrast agent alongside other endogenous metal species. The work outlined here has utilised DESI-MSI in the analysis of brain tumour samples to examine GBM at a molecular level. Overall survival in GBM has not improved for the last 15 years, so a full understanding of GBM at the molecular level is required in the hope to find new therapeutic strategies. Untargeted DESI-MS acquisition has allowed the generation of hundreds of lipid images, with subsequent multivariate statistical analysis revealing key molecular pathways implicated in GBM. Phosphatidylinositol lipid signalling molecules and overexpression of the PI3-K pathway as well as altered metabolism via beta-oxidation of fatty acids and carnitines have been observed in the pre-clinical models. This altered metabolic activity of GBM utilising fatty acid oxidation for energy production translated to human glioblastoma biopsies, where large number of acyl-carnitines were also detected. The use of histology stains other than H&E have been investigated for compatibility with DESI-MS lipidomic analysis. Cresyl violet, toluidine blue, and methylene blue staining showing compatibility with DESI-MS imaging analysis which could provide an alternative data directed stream for targeted tissue analysis.

Non-covalent interactions play an important role in the stabilisation and structure of various organic and biological molecules and are therefore of importance in astrochemistry, biochemistry, and material science. The work in this thesis focuses on pi-pi and/or CH-pi interactions, i.e. the interaction of aromatic rings. Resonant two-photon ionisation of the benzene dimer was performed experimentally. The binding energy of neutral benzene, naphthalene, anthracene, pyrene, and coronene dimers and their heterodimers and trimers were successfully calculated theoretically. The binding energy of heterodimer and trimer radical cations of benzene, naphthalene, and anthracene clusters were also calculated. The experimental set-up was upgraded and extended with two new nanosecond laser systems for excitation and ionisation, coupled to a very substantially modified ultrahigh- vacuum apparatus with a reflectron and linear Time-of-Flight Mass Spectrometer (TOF-MS) and a ZEKE electron analyser, in order to study molecular clusters based on their mass detection, using the supersonic free-jet expansion technique. The TOF of the benzene monomer appeared at 57.976 μs and that of the benzene dimer at 79.893 μs. The DFT-D3 results for the binding energy were identical to the high level ab initio SCS-MP2. The difference in binding energies of aromatic dimers between the stacked and T-shaped geometries increased with the increasing number of aromatic rings. The binding energy for the benzene dimer was very flat, so different ab initio method calculations were performed for its T-shaped and parallel-displaced geometries. The geometry of Polycyclic Aromatic Hydrocarbon (PAH) dimers shows two different structural preferences depending on their size. Large PAHs such as naphthalene, anthracene, pyrene and coronene favour a stacked geometry, whereas the theoretical work on the benzene dimer indicates a TT-shaped geometry as the global minimum based on the most accurate computational methods: QCISD(T) and CCSD(T), but the PD isomer was confirmed to be the global minimum based on the DFT functionals and SCS-MP2 method. The sandwich isomer was found to be the global minimum structure of cation dimer and trimer complexes.

Fourier Transform infrared spectroscopy, in particular, infrared microspectroscopy, has great potential for clinical applications in the flow of cancer diagnosis. Using large focal plane array detectors and with advancements in computer power, infrared hyperspectral imaging has significant advantages in both accuracy and speed of diagnosis. In light of previous research on cancer diagnosis and digital histopathology using infrared imaging, further studies combined with machine learning algorithms have been conducted and are presented in this thesis. Human tissue samples including breast and prostate have been studied. Initial studies have been conducted on breast tissue on CaF2. Infrared images were obtained and analysed using two machine learning algorithms namely Random Forest and AdaBoost. This demonstrated that good classification results, classification accuracies of 89% and 92%, could be obtained to distinguish cancerous from normal associated tissue (NAT). The caveolin-1 stain was applied as a possible breast cancer diagnosis correlated stain. Classification accuracies on cancerous and NAT spectra were 100% and 71.4% respectively in the independent test, which indicates the great potential of caveolin-1 as a biomarker correlated with breast cancer diagnosis. For further implementation of infrared spectroscopy into clinical field, glass substrates, which are cheap and robust, are selected as potential new substrate for infrared disease diagnosis. Studies related to the performance of cancer diagnosis and digital H&E staining using infrared spectra collected from glass slides were conducted on breast tissue. Excellent separation between cancerous and NAT spectra was obtained with classification accuracies of 81.3% and 83.2% on cancer and NAT classes in the independent test. In addition, unbalanced classes are commonly observed in breast tissue analysis, as the epithelium cells are often much fewer in number compared with the stroma cells. A study using different sampling methods and classification methods to solve the problem and boost the classification results was conducted on the spectra collected from breast tissue on CaF2. Lastly, to test whether similar performance of classification can be observed from other types of tissue, studies on prostate tissue with glass substrates were also conducted. Reasonable classification results, classification accuracies, 72% and 68% were obtained with threshold (85% top scored testing spectra) added in the independent test (10 cores).

Mass spectrometry imaging (MSI) can be used in the investigation of biological tissue in detecting elements, metabolites, lipids, peptides and proteins. Secondary ion mass spectrometry (SIMS) is the most mature technique used in MSI. SIMS is characterized by its ability to provide high spatial resolution and high-sensitivity imaging of elements (in dynamic mode) and small-medium mass molecules (in static mode), potentially making it a very powerful tool in drug distribution studies that are vital to developing and validating new therapies. Primary malignant brain tumours are universally fatal and glioblastoma multiforme (GBM) is the most frequent and severe type. Boron neutron capture therapy (BNCT) is a form of targeted radiotherapy based on the preferential accumulation of 10B in the tumour core and infiltrating cells relative to contiguous normal cells. Validation of BNCT relies, therefore, on imaging boron at the cellular level within biological tissue. This study focused on assessment of the imaging capabilities of dynamic and static SIMS instruments (CAMECA NanoSIMS 50L and BioToF-SIMS) in detecting the relative concentration and localisation of 10B from the BNCT agent boronophenylalanine (BPA) in primary cell cultures and in imprint samples of tissue biopsies from GBM human brain tumours and the border around the tumours (BAT). The samples received BPA in vitro and, in vivo respectively, and were used for the first time in this project. In addition, the effect of tyrosine preloading and efflux treatment on 10BPA uptake was investigated in primary cell cultures. The performance of both instruments was compared in terms of spatial resolution, sensitivity and quantitative measurement. The results show that the use of the NanoSIMS 50L with a Cs+ beam provided greater spatial resolution in the imaging of 10B distributions at the cellular and sub-cellular levels in the samples and higher sensitivity in the detection of ions of low abundance when compared with BioToF-SIMS with an Au+ beam, whereas the performance of the two instruments was similar in terms of the quantitative measurement. NanoSIMS 50L images also showed that the 10B from BPA accumulated in GBM tumour samples at a higher concentration than for BAT samples. In cell cultures, pre-loading of tyrosine did not improve the BPA uptake while exposure to the efflux process led to a decrease the BPA level in the cells. The images also showed the preferential accumulation of 10B in cell nuclei compared with the cytoplasmic areas in the cell culture samples, which is an important factor in the success of BNCT.

There is no doubt that microbes are important drivers of bioprocesses that have huge impact on ecosystems that support life on Earth. The prime goal of microbial ecology is to unravel microbial functional diversity and metabolic networks in natural habitats, aimed to improve the quality of life for plants and animals. The steady increase in technological advancements and their application in microbial ecology have greatly enhanced our understanding of functions and metabolic interactions of microbes. Stable isotope probing of bacteria has also emerged as a novel approach to unravel metabolic functions and interactions of microbes directly within environmental samples. The main goal of this thesis is to apply advanced techniques and isotope labelling to gain deeper insights into community functions of microbes, and how cells interact within mixed populations. Firstly, Raman spectroscopy and surface-enhanced Raman scattering (SERS) were optimised and applied in parallel with chemometrics to differentiate near isogenic mutants of Campylobacter jejuni. The optimised conditions for SERS were subsequently applied in combination with isotope labelling for quantitative metabolic fingerprinting of Escherichia coli at bulk and single-cell levels. The results of this study demonstrated the potential application of SERS imaging to characterise E. coli enriched with 13C, 15N and dual 13C and 15N isotopes in a bacterial mixture. Single-cell analysis revealed valuable biochemical information which, if coupled with DNA/RNA-based tools, may permit taxonomic resolution of novel functionally active microbes in future investigations. Furthermore, Raman, Fourier-transform infrared spectroscopies and isotope probing were employed to investigate the rate of incorporation of 13C-labelled substrate by E. coli. This kinetics study generated quantitative data which revealed additive isotope uptake by cells and different rates at which isotopes flow into cellular biomolecules at various time points. This study highlights the potential applicability of vibrational spectroscopy for accurate detection of primary substrate consumers, and to resolve cross-feeding of metabolic products in a microbial community. Finally, Raman spectroscopy, culture volatile metabolites profiling and reverse stable isotope labelling employing kinetics principles of substrate uptake, were used to identify Pseudomonas putida capable of degrading phenol in a two-species community with E. coli. Heavy water was used to investigate cellular metabolic activities and interactions. The results clearly indicate that P. putida was metabolically active in axenic and co-cultures. Whilst E. coli did not show any detectable growth or activity in axenic cultures, it became metabolically active in co-cultures with P. putida. This study also demonstrated the uncoupling of metabolic activity from substrate metabolism by E. coli in co-cultures. Together, these findings indicate the potential application of vibrational spectroscopy and isotope labelling to link bacterial identity to microbially-mediated bioprocesses and to elucidate metabolic interactions in microbial communities in situ.

Although prostate cancer is the most diagnosed cancer in men worldwide, there is geographical variance in both incidence and morbidity, with higher trends in Westernised developed countries. In particular, the high levels of the omega-6 polyunsaturated fatty acid arachidonic acid (AA) in Western diets has been shown to promote aggressive prostate cancer in vitro. However, the exact mechanism through which AA induces the aggressive phenotype has not been fully characterised. Here Fourier transform infrared microspectroscopy (FT-IRM) coupled with fluorescence microscopy (FM) was used to follow AA metabolism in prostate cancer cell lines. Using partially deuterated AA, (d8-AA), with a distinctive C-D stretch seen at 2251 cm-1 providing molecular specificity, coupled with Nile Red Fluorescence imaging, it has been shown that, unlike the non-invasive prostate cancer cell lines PNT2 and LNCaP, invasive prostate cancer lines PC-3M, PC-3. LNCaP C4-2B and DU145 readily uptake and metabolise AA, producing prostaglandin E2 (PGE2) via the cyclooxygenase-2 (COX-2) pathway. Inhibition of the COX-2 pathway with NS938 reduces the invasive stimulus of AA and blocks the uptake of AA. Similarly, the addition of the omega-3 poly unsaturated fatty acid Docosahexaenoic acid (DHA), previously shown to inhibit AA induced invasion, inhibited cellular AA uptake in invasive cell line PC-3. In conclusion, it has been demonstrated that FT-IRM can be utilised to follow metabolomics processes within a prostate model and provide an insight to the molecular pathways underlying the metabolome. This could play a pivotal role in understanding the chemistry and behaviour of the initiation of metastatic prostate cancer.

Energetic polyatomic cluster beams are increasingly used in materials processing and surface analysis applications. In secondary ion mass spectrometry (SIMS) such beams have previously been utilised to investigate the chemical distribution of organic molecules (polymers, biological molecules and pharmaceuticals etc). One important application is in organic electronics, where the depth-distribution of organic components is important in the device performance. Massive gas cluster ion beams (GCIBs) have produced more successful depth-profiles for organic electronic devices that smaller projectiles including SF5+ and C60+. However, further work is needed to investigate and optimise experimental parameters to deliver the necessary SIMS performance. This study focused on molecular depth profiling of organic insulator (PMMA) and semiconductor (PTAA and TIPS-pentacene) materials, in single and bi-layered combinations, utilising cluster SIMS, using C60+ and Arn+, at different temperatures and energies. In general, at room temperature, the best depth resolution was obtained, using large Ar-GCIBs of low energy per atom (E/n ~10 eV), in comparison with the smaller Ar-GCIBs or with C60+ beams at the same total impact energy. On materials which sputtering under C60+ bombardment, ion and neutral yields were greatest due to the higher E/n, compared with GCIBs. Data from PMMA show that the sputter yield under C60 and Arn projectiles conform to the published 'universal' dependence of Y/n to E/n. Depth profiling of the semiconductor compounds were unsuccessful, using C60+ projectiles. For depth profiles using large GCIB projectiles, an increase in the secondary ion yield was observed at the interface with the silicon substrate - a phenomenon which was not observed for the smaller projectiles. In general, the most successful depth profiles (i.e. more constant molecular and fragment secondary ion yields, observed at pseudo-steady-state regions) and best depth resolutions were obtained at cryogenic temperatures - conditions under which corresponding sputtering yields and secondary ion yields were suppressed.

Proteins are crucial for virtually all cellular processes and life; studying the way they fold into three-dimensional structures, or the lack of defined structure, and their dynamics is therefore imperative. Ion mobility mass spectrometry is ideally suited for obtaining global structural information, but requires coupling with other methods to afford local structural details. We have modified a Synapt G2-S to enable ultraviolet photodissociation, a fast and structurally-sensitive fragmentation method, of mass-selected ions either prior to or post ion mobility separation. Using 266 nm photons, we first demonstrate the capabilities of the instrument by sequencing peptides LHRH, GHRP-6 and the mini protein TrpCage. Mobility-selection allows separate UVPD spectra to be obtained for the m/z coincident Gramicidin A monomer and dimer, revealing differences in fragmentation patterns. Synchronising a single laser pulse to the start of the mobility-cycle allows discrimination between primary and secondary fragments. We also observe distinct spectra for two conformational families of 5+ melittin, indicating that UVPD at 266 nm may be conformer-dependent. We then applied our methodology to the proteins ubiquitin, cytochrome c and myoglobin using 213 nm photons. UVPD was carried out pre-ion mobility at different source conditions which altered the conformations prior to UVPD. Initial unfolding resulted in increased fragmentation yield as well as an increase in cleavage sites, which when mapped onto crystal structures revealed the sites in which initial unfolding occurred. We hypothesised that the differences in compact to extended UVPD spectra may be due to non-covalently linked fragments originating from folded precursors, and tested this by collisionally activating photoproducts post ion mobility. This revealed an increase in both yield and cleavage sites when applied to compact conformations indicating that non-covalently held fragments are indeed prevalent in UVPD of structured precursor conformations. In harsh source conditions, only cytochrome c exhibited an increase in a-type fragments, indicating that in-source activation resulted in loss of non-covalent bonding for ubiquitin and myoglobin. However, UVPD-IM-CID of compact conformations could not fully replicate the spectra obtained by UVPD of extended conformations even when secondary UVPD was accounted for; therefore it is apparent that inherent differences in the UVPD process exist between conformations. We further modified the source region of the instrument to allow LED irradiation within the sample capillary. For the photoreceptor UVR8, UV-IM-MS comparison of full-length and a truncated version revealed the presence of two distinct conformational families in the wild-type, a compact and a more extended one, due to the presence of disordered C- and N-terminal tails. Our setup allowed us to follow the receptor dynamics upon UV irradiation and postulate a role of the disordered tails in the photo-activation process.

The use of secondary ion mass spectrometry (SIMS) for high spatial resolution qualitative mass spectrometry imaging (MSI) offers superior lateral resolution over competing technologies. There are however various caveats imposed for bioanalytical applications, extensive fragmentation and poor ion yields for high mass analytes both require redress. The development of cluster ion sources has increased sputter yields and reduced chemical damage, however the local chemical environment will often enhance or supress ionisation probabilities leading to inaccurate quantitative imaging. Laser post-ionisation sputtered neutral mass spectrometry (L-SNMS) offers the potential to overcome the sample matrix effect by essentially moving the ionisation process into the gas phase. Research is presented here that utilises various laser post-ionisation techniques with the main aim being to increase the available useful ion yields and decrease fragmentation. It was concluded that the 265 nm wavelength gave the best ion yields compared to the other wavelengths investigated for L-SNMS, enhanced ion yields were observed for key diagnostic fragments compared with Au+ SIMS for the pharmaceutics under investigation. The internal energies imparted onto neutrals sputtered by Au+, Au3+ and C60+ primary ion beams are investigated and it was confirmed that the extent of photofragmentation increased proportionally to the energy per nucleon of the primary ion beam projectile. Laser power dependence on the extent of fragmentation decreased as a function of energy per nucleon with sublimed gas-phase analytes having the lowest laser power dependence. Resonance ionisation mass spectrometry is investigated and applied to the analysis of key biological agents of interest. During the analysis of cisplatin it was discovered that an alternative two photon RIS scheme was possible for platinum (presumably a 2+1 scheme with Lambda 1 slightly detuned from the Pt resonance) and that this scheme was more efficient than the 3 photon scheme published in the literature. And finally the use of atmospheric pressure laser ionisation (APLI) for liquid chromatography/mass spectrometry (LC/MS) is investigated. In this research the application of femtosecond laser pulses to APLI is reported for the first time and compared with more mature LC/MS ionisation techniques.

Prostate cancer is the most frequently diagnosed cancer in males within the western world. Current practices to identify prostate cancer are limited to screening for prostate specific antigen in blood samples and a digital rectal examination, both of which lack sensitivity. If a post-operative examination identifies malignancies, the prognosis is generally uncertain. Although the majority of prostate tumours are indolent in nature, for some patients the cancer will rapidly metastasise and life expectancy can be as short as 1-2 months. At present, identifying high-risk patients is estimated based upon the outcome of collated pathological results, such as PSA score and Gleason score. The aim of this project was to investigate if spectral biomarkers relating to prostate cancer can be identified using infrared based platforms. The project is divided into two clinical research areas; blood analysis and tissue analysis. The first strand of the project investigates the use attenuated total reflection-Fourier transform infrared spectroscopy as a 'liquid biopsy' application for the diagnosis of prostate cancer in blood serum. To begin with, a number of preliminary investigations were carried out in the pre-analytical stage. This included a drying study, a small pilot study, and investigations into the spectral variance within sample replicates. Once all pre-analytical investigations were resolved, a clinical diagnostic study was initiated to determine if patients with prostate cancer can be discriminated from those with BPH using 1 μL of blood serum. The study examined the spectral profiles of 58 patients (26 with BPH and 32 with prostate cancer) in triplicate measurements, and found that patients can be discriminated on benign and malignant prostate conditions. A radial basis function support vector machine (RBF-SVM) model achieved mean sensitivity and specificity values of 94%, and 77%, respectively. The second strand of the project investigates if spectral markers of metastatic prostate cancer can be identified in post-operative prostate needle biopsies using Fourier transform infrared spectroscopic chemical imaging and a Random Forest classification model. The study progresses in three stages and investigates differences in classification accuracy when using different intra-core spectral profiles for training a classification model, and the effects on classification accuracy using different patients in the training and testing groups. In the first two stages 36 patients (17 metastatic and 19 non-metastatic patients) are investigated and in the third stage at total of 60 are investigated (30 metastatic and 30 non-metastatic patients). Annotations were performed on infrared images to extract only tumour epithelium for analysis. By dividing the patients in to training and testing groups, a robust Random Forest model was constructed using tumorous epithelium from metastatic and non-metastatic cores. The Random Forest model achieved sensitivities and specificities ranging from 57-93% and 41-99%, respectively. In addition to the metastatic study, a further study was carried out to investigate if surrogate spectral marker for EphA2 expression in TURP cores can be identified using chemical imaging. High EphA2 in prostate epithelium has been linked to poorer prognosis and can be detected in the early stages of the disease. Again, the study uses the application of annotating infrared images to extract key spectral profile for interrogation. In the first instant, tumour and normal associated tissue cores were assessed to examine if same tissue types can be discriminated according to EphA2 expression. The study then goes on to use EphA2 stained images as references in annotating specific homogenous regions of EphA2 on infrared images with the notion of building a classifier to identify low and high EphA2 expression in independent tissue cores. Image registration is applied as a way to improve annotations on a pixel level, however, after many attempt the concept of image registration could not be applied. The images of a core which were to registered (infrared image, H&E stained image and EphA2 stained image) were taken on different modalities and were of serial sections therefore it proved extremely challenging to find 'landmarks' within the images which could be registered.

Time-of-Flight Secondary Ion Mass Spectrometry (ToF-SIMS) is a significantly advanced chemical imaging technique with robust application across many fields of the pharmacology, chemistry and materials science. Several novel approaches are being developed to reach the technique's full potential, such as the development of cluster ion beams. Analysis with large cluster ion beams demonstrates ion yield enhancement of intact molecular ion, decreased fragmentation and reduced surface damage accumulation. Nevertheless, the main drawback of the development of SIMS is a matrix effect which accounts for the main obstacle to achieving a quantitative analysis regarding concentration measurement of analytes in complex chemical environments. Several methods are applied to mitigate matrix effects such as laser post-ionisation SIMS, metal-assisted SIMS or incorporation of an internal standard. This study focused on assessment of gas cluster ion beams of a different chemical composition including C60+, Arn+, (H2O)n+ and (Ar/H2O)n+ (n=100-10000) on the analysis of mixtures of standard biomolecules. Ionisation of analytes in single, binary and multiple component samples was compared and assessed with gas phase basicity (GPB). In addition, altering sample preparation such as trehalose embedding or freezing samples was applied to the multiple component mixtures to evaluate the effect of sample state along with differing ion beams on the ion yield and on quantitative data analysis. The result showed that to quantify SIMS data, matrix ionisation effects must be addressed. Analyte ionisation in mixtures generally correlated with the GPB order in positive mode and reverse in the negative ion mode. Using water ion beams and frozen sample ameliorated matrix effect by providing additional protons in the sputtering process.

Fc-fusion proteins (e.g. EPO-Fc) are the most often created fusion proteins due to their beneficial biological and pharmacological properties. The economic success of Fc-fusion proteins and other biopharmaceuticals production however, greatly depends on a robust, low-cost and highly effective protein mammalian cell extraction system . Understanding of how cells respond to a protein production environment based on metabolic profiles provides new goals for bioengineering of cell lines for best performance in biomanufacturing. Furthermore, insights on how individual cell metabolism and therefore phenotype, respond to cell microenvironment allows the underlying biological mechanisms to be explored in greater detail. This study focused on the application of mass spectrometry (MS) technologies, combining the analysis of metabolic profiles of cells extracts by GC-MS and MALDI-MS and spatial visualisation and distribution of metabolites within cells producing the fusion protein by MALDI-MSI and SIMS imaging. The analysis of external and internal metabolome profiles of cells producing the protein showed an extended effect of EPO-Fc fusion protein production on cell metabolism. The findings indicate that changes observed in EPO-Fc producing cells are related to enhanced protein and lipid synthesis highlighting that these cells are in a state of increased metabolic activity with the protein exocytosis into growth medium. Moreover, the composition of lipid bilayer of induced cells seemed to be different to non-induced cells. These findings were confirmed with the analysis of EPO-Fc induced cells using MS metabolic imaging. Multivariate analysis highlighted a number of metabolites that were significantly influenced by the protein expression when compared to control cells. The major metabolic changes in induced cells were those related to lipid metabolism. The information about metabolic changes in tetracycline-induced cells obtained from the analysis of cell populations was further supported with the analysis based on single-cell studies. Single-cell based studies also proved that investigations of individual cells provide additional insights about changes in metabolism of induced cells that can be referred to a unique, single cell and its phenotype. The analysis of CHO cells revealed a high level of heterogeneity within a cell population. Different cell phenotype and hence, metabolite content allowed for correlation between cell locations and their metabolite characteristics, specific for each type of cells. This project has successfully shown combination of bio-analytical techniques to investigate external and internal metabolome changes related to a fusion protein production in mammalian cells. Additionally, the significance of single cell approaches in metabolomics has also been highlighted, providing insights into the sub-cellular distribution of metabolites in cells producing EPO-Fc and information on the level of heterogeneity within a cell population. A multidimensional approach for metabolic profiling and future technological improvements of single-cell platforms are required to provide improved data acquisition and data analysis in order to better understand unknown processes involved in cell metabolism.

The 21st Century has seen a rise in incidence of complex diseases such as cancer and in the quest to develop essential new therapeutic options, the study of drug-cell interactions can yield powerful information. Acute myeloid leukaemia (AML) is an aggressive cancer that causes life-threatening deficits of functional blood cells in humans for which current treatment options are highly toxic and often poorly tolerated. A combination of two existing drugs, bezafibrate and medroxyprogesterone acetate in a drug redeployment situation has shown promise in vitro and in vivo and further investigations are crucial to elucidate the mode of action of this treatment. This project investigated the mechanistic action of BaP at a cellular level. Orthogonal spectroscopic and mass spectrometric platforms were employed to probe the biochemical composition of two AML cell lines, HL60 and K562 in the presence and absence of this combined drug treatment. Analysis was performed on single living cells, dehydrated cells, fixed cells and cell extracts to give a large and detailed data set. A consideration of the main spectral differences obtained by Synchrotron-FTIR and ATR-FTIR in conjunction with multivariate statistical analysis revealed a significant change to the cellular lipid composition with drug treatment; furthermore, this response was not caused by cell apoptosis. In particular, the ratio of CH2:CH3 was observed to increase with BaP treatment and this was determined to be a significant change in both cell lines (p <0.05). An overall increase in lipid unsaturation suggests that BaP targets cellular lipid biosynthesis. Raman microspectroscopy added a further dimension to the spectroscopic study by providing spatial information of lipid distribution which suggested that BaP-induced saturation change is uniform across a single cell. UHPLC-MS was employed for global metabolomics analysis of AML cell extracts and revealed a number of biochemical pathways that were indicated as targets of BaP therapy in both cell lines. Univariate and multivariate analysis determined statistically significant metabolites for which putative identifications were made. Pyrimidine metabolism was the most significant pathway identified for changes consistent in both HL60 and K562 cell lines. The complementarity of ToF-SIMS and UHPLC-MS provided large coverage of the lipidome of AML cells through untargeted and targeted approaches. For data derived by both techniques, a general increase in polyunsaturated species for BaP treated cell extracts was observed which correlated well with findings from spectroscopic investigations. Adopting a multi-disciplinary approach to cell analysis can afford a powerful insight into understanding drug mode of action at a cellular level and novel information regarding BaP mechanistic action in AML cell lines was revealed. This analytical approach could be extended to the future study of drug-cell interactions for other oncological systems.

Traditional solution and solid state approaches (Nuclear Magnetic Resonance, X-Ray Crystallography) are methods of choice when analysing both biological and inorganic analytes. However, the characterisation of transient species, often encountered in self-assembling systems, is difficult. Such systems rarely produce crystals of high quality and due to their dynamic nature; their structures are difficult to study with NMR. Hyphenated gas phase methods which rely on mass spectrometry detection offer simultaneous structural analysis and direct stoichiometry measurement. As a consequence, it is possible to investigate specific, non-interacting molecules and molecular complexes in an isolated environment. This thesis focuses on the development and applications of two such methods - ion mobility mass spectrometry (IM-MS) and cold ion spectroscopy. IM-MS measurements yield a so called collisional cross sectional area (CCS). This parameter can be pictured as a rotationally averaged, shadow projection of a molecule structure. When correlated with the ion abundance, a CCS distribution yields intuitively interpretable information about the conformational preferences of an isolated molecule. Although indispensable in describing a "global" geometrical structure, the CCS parameter itself provides a limited insight into the local structural features of the assembly. Ion spectroscopy, both in the UV and IR regions, can provide an extra layer of highly descriptive information. Here, we present several cases where the above techniques have been applied. With the aid of IM-MS, we have analysed the geometry of inorganic supramolecular assemblies, highlighting the stability of particular metal-ligand interactions. Using cold ion spectroscopy, we have assessed the fine structural information of self-assembled oligomers of an amyloidogenic peptide. We correlated spectral features of isolated oligomers to features observed in the mature fibrils; therefore attempting to delineate the events in early stages of amyloidogenic aggregation. A major part of this report focusses on technological aspects of the design and development of a high resolution, variable temperature ion mobility mass spectrometer (VT-IM-MS). The thermal stability of molecules is a vital aspect in industrial process development and formulation science. Solution phase Differential Scanning Calorimetry (DSC) is a widely applied technique, allowing to monitor reversibility of thermally induced conformational transitions, a key aspect in protein folding analysis. The instrument reported here aims to provide parallel information about gaseous ions, with a particular focus on protein ions. Capabilities of the newly built instrument have been tested using small, rigid molecules, a small protein and a large multiprotein complex.

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.

High surface sensitivity and lateral resolution imaging make Time-of-Flight SecondaryIon Mass Spectrometry (ToF-SIMS) a unique and powerful tool for biologicalanalysis. Many of these biological systems, including drug-cell interactions, requireboth the identification and location of specific chemicals. ToF-SIMS, used in imagingmode, is making great strides towards the goal of single cell and tissue analysis. The experiments, however, result in huge volumes of data. Here advanced computationalapproaches employing sophisticated techniques to convert these data intoknowledge are introduced. This thesis aims to produce a framework for data analysis, integrating novel algorithms,image analysis and 3D visualisation. New schema outlined in this thesisaddress the issues of the immense size of 3D image stacks and the complexity containedwithin the enormous wealth of information in ToF-SIMS data. To deal with the issues of size and complexity of ToF-SIMS data, new techniquesto processing image data are investigated. Automated compression routines for ToF-SIMSimages using a peak picking routine tailored for ToF-SIMS are evaluated. Newuser friendly GUIs capable of processing and visualising very large image stacks areintroduced as part of a tool-kit designed to streamline the process of multivariateanalysis and image processing. Along with this two well known classification routines,namely AdaBoost and SVMs, are also applied to ToF-SIMS data of severalbacterial strains to test their ability to classify SIMS data accurately. This thesispresent several new approaches to data processing and interpretation of ToF-SIMSdata.