Originally established as an analytical technique in the fields of physics and chemistry, mass spectrometry has now also become an essential tool in biology. Advances in ionisation methods and novel types of instrumentation have led to the development of mass spectrometry for the analysis of a wide variety of biological samples. The work presented here describes the use mass spectrometry for the study of a number of biological systems. A new family of techniques has been developed allowing ions to be created under ambient conditions. Three of these ambient ionisation techniques, coupled to different mass analysers, were employed for the rapid screening of pharmaceutical formulations. Active ingredients were identified and subjected to collisionally induced dissociation, enabling the elucidation of potential fragmentation pathways. Drug metabolites were also successfully identified from biological samples. Inorganic mass spectrometry was employed to probe the metal centres of the enzyme, particulate methane monooxygenase, a methane-oxidising complex found in certain bacteria. This protein has been extensively studied, but questions remain regarding its catalytic mechanism, particularly the involvement of indigenous metal ions. Inductively-coupled plasma mass spectrometry experiments have indicated the presence of copper and iron within the enzyme. Protein cross-sections, obtained using ion mobility mass spectrometry, can be used to probe the conformation of molecules in the gas phase. A commercial instrument was used to investigate human hemoglobin from clinical samples. A complex assembly mechanism was deduced, resolving previous disputes in the literature, and conformational differences were observed between healthy and sickle molecules. The field of proteomics is rapidly evolving; as described, techniques are constantly being developed and improved to deal with the enormous complexity that proteomes present. Three proteomics approaches were used to study a recently identified bacterium under two growth conditions. Differences in protein expression were observed and correlated to relevant biological pathways.

17β-estradiol is the most potent circulating estrogenic hormone. The classical mode of action of 17β-estradiol involves its translocation to the nucleus and regulation of transcription. However, numerous rapid, non-genomic actions of 17β-estradiol have been demonstrated in several cell types. This thesis demonstrates that 17β-estradiol rapidly elevates hepatocyte cGMP and stimulates plasma membrane Ca2+ efflux. In contrast, 17α-estradiol, an optical isomer, is without effect on cGMP or Ca2+ efflux. The Ca2+ efflux stimulation is protein kinase G (PKG)-dependent. This thesis also demonstrates the expression of PKG isoforms Iα and Iβ in hepatocytes, and that 17β-estradiol rapidly recruits PKGIα to the hepatocyte plasma membrane. The observed effects of 17β-estradiol are mimicked by 17β-estradiol rendered membrane-impermeant by linkage to BSA. Moreover, 17β-estradiol binding at the hepatocyte plasma membrane was directly visualised using fluoroscein-labelled 17β-estradiol-BSA. The nature of the plasma membrane receptor involved was found to have a similar pharmacological profile to the ‘γ-adrenergic receptor’. 17β-estradiol protects both liver and isolated hepatocytes under pathophysiological conditions that have been associated with a rise in intracellular Ca2+ concentration ([Ca2+]i). Hepatoprotection by 17β-estradiol has previously been attributed to its antioxidant properties. A rise in [Ca2+]i is a common early event in cell injury, activating many Ca2+-dependent enzymes including calpain. Single cell Ca2+ measurements showed that 17β-estradiol attenuates both the amplitude and duration of ATP-induced [Ca2+]i rises. 17β-estradiol protects hepatocytes against the [Ca2+]i-dependent elevation of calpain activity and the decline in cell viability induced by both ATP and the bile acid taurolithocholate. The effects of 17β-estradiol on [Ca2+]i, calpain activity and cell viability are dependent on PKG. I propose that 17β-estradiol stimulates plasma membrane Ca2+ efflux through elevation of cGMP and subsequent activation and recruitment of PKGIα to the plasma membrane; this is a potential mechanism through which 17β-estradiol protects hepatocytes by alleviating harmful [Ca2+]i rises.

Originally established as an analytical technique in the fields of physics and chemistry, mass spectrometry has recently become an essential tool in biological research. Advances in ionisation methods and novel types of instrumentation have led to the development of mass spectrometry for the analysis of a wide variety of biological samples. The work presented here describes the use of mass spectrometry to characterise a variety of synthetic and natural macromolecules. Transmissible spongiform encephalopathies (TSEs), also known as prion diseases, are a class of fatal, infectious neurodegenerative diseases that affect both humans and animals. Prion proteins are unprecedented infectious pathogens that cause a group of invariably fatal neurodegenerative diseases by means of an entirely novel mechanism. Ion mobility mass spectrometry (IM-MS) was used to probe the conformation of a variety of different prion proteins in the gas-phase. It was shown that IM-MS could distinguish between two recombinant structures representative of normal cellular prion protein, PrPC and the pathogenic scrapie form (PrPSc). The structure of the full-length prion protein was probed by means of IM-MS. A comparison of the estimated cross-sections of truncated prion protein constructs and full-length constructs suggested that the N-terminal flexible tail was associated with the core structure. Metal binding to two different prion protein constructs was investigated. It was observed that copper coordination to the N-terminal fragment could induce conformational changes in the octarepeat fragment. These changes were relatively small and could not be measured in the full-length prion protein. The data suggested that minor structural changes in the N-terminal could stimulate endocytosis via a minor, undetected, conformational change in the C-terminal domain. IM-MS was used as a high resolution separation technique to distinguish between mixtures of isobaric synthetic polymers. It was observed that the resolving power of IM-MS/MS was insufficient to resolve the higher molecular weight oligomers. In comparison, gel permeation chromatography (GPC)-nuclear magnetic resonance (NMR) spectroscopy (GPC-NMR) analysis of the same isobaric mixture could not separate the two components. It was observed that IM-MS was better than GPCNMR at separating isobaric poly(ethylene glycol) mixtures, especially when taking speed and sensitivity into account.

With the 1992 United Nations Convention on Biological Diversity humanity's ongoing search for biological resources became subject to global regulation. The collection of biological materials for use in agriculture and medicine by one nation from another became conditional on criteria of informed consent, benefit-sharing, and the preservation of environments. This practice has become known as bioprospecting. Collections of biological materials and/or of 'traditional' knowledge of how to utilize them which did not meet the Convention's requirements henceforth became known as biopiracy. The thesis takes its structure from the Convention, which is treated as marking a shift from historical biopiracy to contemporary bioprospecting. The thesis is that critics of the Convention who oppose it and the forms of bioprospecting which it mandates in terms of neo-colonialism and neo-imperialism have misunderstood the character of contemporary economic and political power. The thesis argues that although contemporary bioprospecting is not practiced, as the Convention requires it to be, in ways that are 'fair and equitable', it cannot be understood as a neo-imperialist practice. Instead, the thesis concludes that the Convention should be understood in the context of new forms of governance and sovereignty. The Convention facilitates planet management and supports the exercise of biopower. Several cases studies of imperialist biopiracy are presented and their social impacts are discussed in contrast to contemporary bioprospecting. A broad range of historical and sociological literature is brought together for the first time. The history of the transition from biopiracy to bioprospecting is described and discussed in terms of several social, epistemological/technological, scientific, political and economic changes, respectively: the transition from imperialism to globalization, a shift away from exploitation of 'nature' toward management of 'biodiversity', the transition from natural history to ecological science, the appearance of environmentalist concerns in national and global politics, the completion of the globalization of capitalist property relations and the demise of the notion of biological resources as the 'common heritage of humankind'.

One of the challenges of quantitative approaches to biological sciences is the lack of understanding of the interplay between form and function. Each cell is full of complex-shaped objects, which moreover change their form over time. To address this issue, we exploit recent advances in confocal microscopy, by using data collected from a series of optical sections taken at short regular intervals along the optical axis to reconstruct the Endoplasmic Reticulum (ER) in 3D, obtain its skeleton, then associate to each of its edges key geometric and dynamic characteristics obtained from the original filled in ER specimen. These properties include the total length, surface area, and volume of the ER specimen, as well as the length surface area, and volume of each of its branches. In a view to benefit from the well established graph theory algorithms, we abstract the obtained skeleton by a mathematical entity that is a graph. We achieve this by replacing the inner points in each edge in the skeleton by the line segment connecting its end points. We then attach to this graph the ER geometric properties as weights, allowing therefore a more precise quantitative characterisation, by thinning the filled in ER to its essential features. The graph plays a major role in this study and is the final and most abstract quantification of the ER. One of its advantages is that it serves as a geometric invariant, both in static and dynamic samples. Moreover, graph theoretic features, such as the number of vertices and their degrees, and the number of edges and their lengths are robust against different kinds of small perturbations. We propose a methodology to associate parameters such as surface areas and volumes to its individual edges and monitor their variations with time. One of the main contributions of this thesis is the use of the skeleton of the ER to analyse the trajectories of moving junctions using confocal digital videos. We report that the ER could be modeled by a network of connected cylinders (0.87μm±0.36 in diameter) with a majority of 3-way junctions. The average length, surface area and volume of an ER branch are found to be 2.78±2.04μm, 7.53±5.59μm2 and 1.81±1.86μm3 respectively. Using the analysis of variance technique we found that there are no significant differences in four different locations across the cell at 0.05 significance level. The apparent movement of the junctions in the plant ER consists of different types, namely: (a) the extension and shrinkage of tubules, and (b) the closing and opening of loops. The average velocity of a junction is found to be 0.25μm/sec±0.23 and lies in the range 0 to 1.7μm/sec which matches the reported actin filament range.

It is a common goal in biophysics to understand protein structural properties and their relationship to protein function. I investigated protein structural properties using three coarse graining methods: a rigidity analysis method First, a geometric simulation method Froda and normal mode analysis as implemented in Elnemo to identify the protein directions of motion. Furthermore, I also compared the results between the coarse graining methods with the results from molecular dynamics and from experiments that I carried out. The results from the rigidity analysis across a set of protein families presented in chapter 3 highlighted two different patterns of protein rigidity loss, i.e. "sudden" and "gradual". It was found that theses characteristic patterns were in line with the rigidity distribution of glassy networks. The simulations of protein motion by merging flexibility, rigidity and normal mode analyses presented in chapter 4 were able to identify large conformational changes of proteins using minimal computational resources. I investigated the use of RMSD as a measure to characterise protein motion and showed that, despite it is a good measure to identify structural differences when comparing the same protein, the use of extensive RMSD better captures the extend of motion of a protein structure. The in-depth investigation of yeast PDI mobility presented in chapter 5 confirmed former experimental results that predicted a large conformational change for this enzyme. Furthermore, the results predicted: a characteristic rigidity distribution for yeast PDI, a minimum and a maximum active site distance and a relationship between the energy cutoff, i.e. the number of hydrogen bonds part of the network of bonds, and protein mobility. The results obtained were tested against molecular dynamics simulations in chapter 6. The MD simulation also showed a large conformational change for yeast PDI but with a slightly different minimum and maximum inter-cysteine distance. Furthermore, MD was able to reveal new data, i.e. the most likely inter-cysteine distance. In order to test the accuracy of the coarse graining and MD simulations I carried out cross-linking experiments to test the minimum inter-cysteine distance predictions. The results presented in chapter 7 show that human PDI minimum distance is below 12Å whereas the yeast PDI minimum distance must be above 12Å as no cross-linking structures where found with the available (12Å long) cross-linkers.

The complex environment of a living cell contains many molecules interacting in a variety of ways. Examples include the physical interaction between two proteins, or the biochemical interaction between an enzyme and its substrate. A challenge of systems biology is to understand the network of interactions between biological molecules, derived experimentally or computationally. Sophisticated dynamic modelling approaches provide detailed knowledge about single processes or individual pathways. However such methods are far less tractable for holistic cellular models, which are instead represented at the level of network topology. Current network analysis packages tend to be standalone desktop tools which rely on local resources and whose operations are not easily integrated with other software and databases. A key contribution of this thesis is an extensible toolkit of biological network construction and analysis operations, developed as web services. Web services are a distributed technology that enable machine-to-machine interaction over a network, and promote interoperability by allowing tools deployed on heterogeneous systems to interface. A conceptual framework has been created, which is realised practically through the proposal of a common graph format to standardise network data, and the investigation of open-source deployment technologies. Workflows are a graph of web services, allowing analyses to be carried out as part of a bigger software pipeline. They may be constructed using web services within the toolkit together with those from other providers, and can be saved, shared and reused, allowing biologists to construct their own complex queries over various tools and datasets, or execute pre-constructed workflows designed by expert bioinformaticians. Biologically relevant results have been produced as a result of this approach. One very interesting hypothesis has been generated regarding the regulation of yeast glycolysis by a protein found to interact with seven glycolytic enzymes. This has implied a potentially novel regulatory mechanism whereby the protein in question binds these enzymes to form an 'energy production unit'. Also of interest are workflows which identify termini (system inputs and outputs), and cycles, which are crucial for acquiring a physiological perspective on network behaviour.

Given the ever increasing quantity of sequence data, functional annotation of new gene sequences persists as being a significant challenge for bioinformatics. This is a particular problem for transcriptomics studies in crop plants where large genomes and evolutionarily distant model organisms, means that identifying the function of a given gene used on a microarray, is often a non-trivial task. Information pertinent to gene annotations is spread across technically and semantically heterogeneous biological databases. Combining and exploiting these data in a consistent way has the potential to improve our ability to assign functions to new or uncharacterised genes. Methods: The Ondex data integration framework was further developed to integrate databases pertinent to plant gene annotation, and provide data inference tools. The CoPSA annotation pipeline was created to provide automated annotation of novel plant genes using this knowledgebase. CoPSA was used to derive annotations for Affymetrix GeneChips available for plant species. A conjoint approach was used to align GeneChip sequences to orthologous proteins, and identify protein domain regions. These proteins and domains were used together with multiple evidences to predict functional annotations for sequences on the GeneChip. Quality was assessed with reference to other annotation pipelines. These improved gene annotations were used in the analysis of a time-series transcriptomics study of the differential responses of durum wheat varieties to water stress. Results and Conclusions: The integration of plant databases using the Ondex showed that it was possible to increase the overall quantity and quality of information available, and thereby improve the resulting annotation. Direct data aggregation benefits were observed, as well as new information derived from inference across databases. The CoPSA pipeline was shown to improve coverage of the wheat microarray compared to the NetAffx and BLAST2GO pipelines. Leverage of these annotations during the analysis of data from a transcriptomics study of the durum wheat water stress responses, yielded new biological insights into water stress and highlighted potential candidate genes that could be used by breeders to improve drought response.

Understanding how function relates to multiple layers of inactions between biological entities is one of the key goals of bioinformatics research, in particular in such areas as systems biology. However, the realisation of this objective is hampered by the sheer volume and multi-level heterogeneity of potentially relevant information. This work addressed this issue by developing a set of integration pipelines and analysis methods as part of an Ondex data integration framework. The integration process incorporated both relevant data from a set of publically available databases and information derived from predicted approaches, which were also implemented as part of this work. These methods were used to assemble integrated datasets that were of relevance to the study of the model plant species Arabidopsis thaliana and applicable for the network-driven analysis. A particular attention was paid to the evaluation and comparison of the different sources of these data. Approaches were implemented for the identification and characterisation of functional modules in integrated networks and used to study and compare networks constructed from different types of data. The benefits of data integration were also demonstrated in three different bioinformatics research scenarios. The analysis of the constructed datasets has also resulted in a better understanding of the functional role of genes identified in a study of a nitrogen uptake mutant and allowed to select candidate genes for further exploration.

In this thesis, a series of mathematical models suitable for describing biological tissue growth are developed. The motivation for this work is a bioreactor system which provides perfusion and compressive mechanical stimulation to a cell-seeded scaffold; however, the formulation is sufficiently general to be applied to a vast range of tissue engineering applications. Our models are used to investigate the influence of (i) cell-cell and cell-scaffold interactions, and (ii) the mechanical environment, on tissue growth. In the first part of the thesis, we extend a model due to Franks (2002) (in which the cell and culture medium phases are represented by viscous fluids) by including perfusion and coupling the cells' response to their environment. Specifically, we consider the effect of the cell density and pressure on tissue growth. We analyse the model using analytic and numerical techniques; numerical simulations suggest that comparison of construct morphology in the presence and absence of perfusion provides a means to identify the dominant regulatory growth stimulus. The solid characteristics of the construct and interactions between the cells and scaffold are necessarily neglected in the two phase model. Guided by this, we develop more complex three phase models. Using numerical simulations, the influence of cell-cell and cell-scaffold interactions is investigated and less porous scaffolds are shown to improve control over cell behaviour. We use the model to compare the cells' response to different regulatory stimuli, including flow-induced shear stress. Our results suggest that uniform initial cell seeding and stimulating cell movement are crucial in maintaining the mechanical integrity of tissue constructs. We also study the effect of scaffold compression on the mechanical environment of the cells contained within, developing both a classical Biot formulation and a multiphase model. We demonstrate that the bioreactor geometry introduces significant spatial variation in the mechanical stimuli relevant to tissue growth and that such considerations will play a key role in comprehensive models of mechanotransduction-affected growth.