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Breast cancer is the most prevalent form of cancer in women and accounts for 519,000 annual deaths (WHO Statistics). It has long been established that oestrogen (E2) stimulates tumour growth of oestrogen receptor (ER) positive breast cancer and is involved in the pathogenesis of the disease. Consequently, therapeutic approaches targeting the ER were developed. The use of endocrine therapy is an integral component in treating breast cancer however resistance to such drugs is a major limitation. Unfortunately, even initially responding tumours eventually develop resistance - acquired resistance. The aim of this study was to determine which intracellular pathways may be important in conferring acquired endocrine resistance. In order to do so, a three-stage MCF-7 cell model emulating the clinical development of acquired endocrine was used. MCF-7/LCC1 (LCC1) and MCF-7/LCC9 (LCC9) cells lines were derived from the oestrogen dependent and antioestrogen sensitive MCF-7 cell line. LCC1 cells remain responsive to endocrine therapies but their growth is not dependent on oestrogenic stimulus. LCC9 cells, on the other hand are fully resistant to endocrine therapies and completely oestrogen independent. A number of different cell membrane receptors and intracellular pathways have been implicated in endocrine resistance including HER receptor family, PI3K/Akt & MEK/ERK pathways. These pathways are of particular interest since they are able to activate ER in the absence of oestrogenic stimulus. It is likely that several pathways may be important in conferring resistance to endocrine therapies therefore the experiments in this study focussed on the transcriptional regulation of HER receptors, the activation of the Akt pathway and its implication to basic cellular processes. Following E2 treatment (48h), HER2/3/4 mRNA and protein levels were reduced in MCF- 7 and LCC1 but not in the endocrine-resistant LCC9 cell line as measured by QRT-PCR and Western blotting. The anti-estrogen fulvestrant (ICI 182,780) reversed the E2 modulation. A previous study has shown that ER and the HER2 promoter compete for limiting amounts of SRC-1 in oestrogen-responsive ZR-75-1 cells, causing HER2 repression after E2 stimulation (Newman et al.,Oncogene, 19, 490-7, 2000). ER RNAi abolished E2 repression of HER2 in MCF-7 and LCC1 cells. Furthermore, LCC9 cells have reduced SRC-1 recruitment to ER (assessed by ChIP) allowing SRC-1 to bind to the HER2 promoter. SRC-1 RNAi reduced HER2 transcription in MCF7 cells in a manner similar to E2 whilst it did not restore E2 repression in LCC9 suggesting that the latter cells have alternative mechanisms regulating HER2 transcription. RNAis against the other two p160 co-activators TIF2 and AIB1 did not restore E2 mediated HER2 repression in LCC9 cells. The importance of redundancy between p160 co-activators was also determined by performing double knockouts. SRC-1/TIF2 and TIF2/AIB1 double siRNAs had little effect on HER2 mRNA levels however SRC-1/AIB1 siRNA restored oestrogen mediated downregulation of HER2 transcription in LCC9 cells. This data indicates that SRC-1 and AIB1 co-activators play a role in the transcriptional regulation of HER receptor particularly in MCF-7 and LCC1 cells. The regulation of this transcriptional mechanism is altered in resistant LCC9 cells but, as evidenced by the double knockouts, p160 coactivators are still able to affect HER expression in these cells. This mechanism was further studied in primary breast cancer tumour material. The importance of the Akt pathway in this cell line model was also investigated as phospho-Akt levels are elevated in LCC1 and LCC9 cells. This in turn was shown to activate mTOR and ER (Ser167 residue phosphorylation) thereby contributing to increased growth and ligand independent activation of the oestrogen receptor respectively. Activation of PI3K and PTEN is unchanged in LCC1 and LCC9 cells suggesting that these proteins are not responsible for elevated Akt phosphorylation. In contrast, these cells do express higher levels of phospho-IGFR due to the high availability of receptor ligands (IGFI & IGFII). This is likely to be, at least partially, responsible for the elevated Akt activation. Moreover, the role of Akt isoforms was also determined as they are known to have different functions. The levels of Akt 2 phosphorylation are higher in endocrine resistant cell lines in comparison to parental MCF-7 cells. Interestingly, the Akt 3 phosphorylation is present in all cell lines whilst Akt 1 phosphorylation is minimal. Nevertheless, Akt RNAi studies reveal that Akt 1 and 2 siRNA dramatically reduce growth in MCF-7, LCC1 and LCC9 cells. These results suggest that Akt 2 phosphorylation may play a part in conferring endocrine resistance but the other isoforms are also important for normal cellular growth. The cell cycle profiles of LCC1 and LCC9 are very similar to MCF-7. Similarly, migration levels are unchanged in endocrine resistant cell lines. However, in the presence of antioestrogenic drugs, apoptosis in LCC1 and LCC9 cells in reduced in comparison to the parental MCF-7 cell line. Furthermore, LCC1 and LCC9 cells have higher invasion rates. The deregulation of HER receptor expression and elevated Akt activation may together confer survival advantage in LCC1 and LCC9 cells whilst also increasing their invading potential.

Axons are directed along stereotypic pathways to their targets by cues arrayed in the extracellular environment. Identifying the cellular and molecular nature of these signals is of high interest and the developing optic pathway is a useful model system for achieving this. Although previous studies have identified several molecules essential for optic pathway formation, in vivo only subsets of retinal axons rely on them. I focused on the Dscam (Down’s syndrome cell adhesion molecule) and Sidekick (Sdk) cell adhesion molecules for potentially playing crucial roles in this system. In situ hybridisation in the embryonic mouse visual system showed Dscam and Sdk-1 expression in the RGC layer of the retina, along the optic pathway and in the visual targets. Sdk-2 was detected in the glia of the optic nerve and optic chiasm, marking the pathway that RGC axons follow, but not in RGCs. No DscamL1 was detected in RGCs or the optic pathway at the stages investigated and it was discounted from future analysis. In vitro, DSCAM promoted RGC axon outgrowth, whereas SDK 1 was inhibitory. SDK 2 had no effect on RGC axon outgrowth, suggesting it does not play a direct role in their pathfinding. Repeating this assay using retinal explants from the Dscamdel17 mouse mutant, showed that DSCAM enhanced retinal axon outgrowth, at least in part, through homophilic interactions. Analysis of visual system development in Dscam mutants showed DSCAM involvement in RGC axon fasciculation and in enhancing their growth, particularly within the ipsilateral optic tract. Retinal cell counts revealed that DSCAM played diverse roles in controlling cell number. Pre- and postnatal retinas lacking DSCAM contained more RGCs and mitotic cells. Postnatally, Dscam-/- retinas also show decreased cell death. In many cases, defect severity was dose-dependent, with an intermediate phenotype in the heterozygous mice, implicating DSCAM in the neurological defects of Downs’ Syndrome patients.

Increasing evidence highlights that term labour is an inflammatory event associated with increased production of pro-­‐inflammatory mediators and leukocyte influx into the intrauterine tissues. Preterm labour (PTL), defined as labour before 37 weeks gestation, is a major clinical problem, and preterm birth is the leading cause of neonatal mortality and morbidity worldwide. The causes of PTL are poorly understood, but intrauterine infection and inflammation have been shown to be important factors. Therefore, there is growing interest in the hypothesis that preterm labour may occur as a result of the premature activation of the inflammatory pathways normally initiated with labour at term, either idiopathically, or in response to a pathological intrauterine infection. The aim of this thesis was to use a mouse model of infection-­induced PTL to: characterise the local inflammatory and immune response to an intrauterine infection; investigate the potential of anti‐inflammatory agents to delay delivery of pups and to improve their survival; and to investigate the role of specific immune cell populations in infection-­induced preterm labour. To characterise the inflammatory and immune response to intrauterine infection, CD1 mice received an intrauterine injection of PBS vehicle or increasing doses of bacterial-­derived lipopolysaccharide (LPS) on day 17 of gestation. Time to delivery, and the number of live born pups were determined. Intrauterine administration of increasing doses of LPS dose-­dependently induced preterm labour and reduced the proportion of live born pups. Analysis of tissues harvested six hours post-­surgery demonstrated that in response to intrauterine LPS administration, there was increased expression of inflammatory cytokines and chemokines within the utero-­placental tissues, amniotic fluid and maternal serum; and an influx of neutrophils into the decidua, compared to mice receiving PBS. Given these results, the potential of anti‐inflammatory agents to delay LPS-­induced preterm delivery and improve pup survival was then investigated using the same mouse model. Prior to intrauterine LPS administration, mice were pre-­‐treated with epi-­lipoxin, BML-­111 (a stable lipoxin analogue), or IL-­10. Time to delivery was unaffected by pre-­treatment with the anti-­inflammatory agents, however epi-­lipoxin significantly increased the proportion of live born pups in mice delivering preterm, compared to mice receiving only LPS. To further investigate the role of immune cells in infection-­induced PTL, antibody-­based depletion strategies were used to selectively deplete specific immune cell populations to determine whether they played a causative role in LPS­‐induced preterm delivery. Despite successful depletion of macrophages or neutrophils, it was not found to significantly affect LPS-­induced preterm delivery, suggesting these immune cells are not required for the induction of preterm labour in response to intrauterine infection. However, it is likely that they contribute to the intrauterine inflammatory response as depletion resulted in altered inflammatory signalling within the intrauterine tissues. Collectively, this work has demonstrated that the presence of intrauterine bacterial LPS, as a surrogate model of infection, induces a robust inflammatory and immune response within the utero‐placental tissues that involves the increased production of inflammatory mediators and the influx of immune cells into the decidua, which ultimately leads to PTL. Whilst the anti-­inflammatory treatments tested here did not delay LPS-­induced PTL, epi-­lipoxin attenuated LPS-­induced mortality in pups born preterm, suggesting this anti‐inflammatory agent may be useful in protecting the fetus from the adverse effects of infection-­induced preterm birth. Using models such as the one described here, are vital to improving our understanding of the events regulating the induction of PTL and will ultimately aid the search for novel therapeutic options for the treatment of PTL.

D.Ing. / The rapid use of digital images and the necessity to compress them, has created the need for the development of image quality metrics. Subjective evaluation is the most accurate of the image quality evaluation methods, but it is time consuming, tedious and expensive. In the mean time widely used objective evaluations such as the mean squared error measure has proven that they do not assess the image quality the way a human observer does. Since the human observer is the final receiver of most visual information, taking the way humans perceive visual information will be greatly beneficial for the development of an objective image quality metric that will reflect the subjective evaluation of distorted images. Many attempts have been carried out in the past, which tried to develop distortion metrics that model the processes of the human visual system, and many promising results have been achieved. However most of these metrics were developed with the use of simple visual stimuli, and most of these models were based on the visibility threshold measures, which are not representative of the distortion introduced in complex natural compressed images. In this thesis, a new image quality metric based on the human visual system properties as related to image perception is proposed. This metric provides an objective image quality measure for the subjective quality of coded natural images with suprathreshold degradation. This proposed model specifically takes into account the structure of the natural images, by analyzing the images into their different components, namely: the edges, texture and background (smooth) components, as these components influence the formation of perception in the HVS differently. Hence the HVS sensitivity to errors in images depends on weather these errors lie in more active areas of the image, such as strong edges or texture, or in the less active areas such as the smooth areas. These components are then summed to obtain the combined image which represents the way the HVS is postulated to perceive the image. Extensive subjective evaluation was carried out for the different image components and the combined image, obtained for the coded images at different qualities. The objective (RMSE) for these images was also calculated. A transformation between the subjective and the objective quality measures was performed, from which the objective metric that can predict the human perception of image quality was developed. The metric was shown to provide an accurate prediction of image quality, which agrees well with the prediction provided by the expensive and lengthy process of subjective evaluation. Furthermore it has the desired properties of the RMSE of being easier and cheaper to implement. Therefore, this metric will be useful for evaluating error mechanisms present in proposed coding schemes.

Recent developments in automation and novel experimental techniques have led to the accumulation of vast amounts of biological data and the emergence of numerous databases to store the wealth of information. Consequentially, bioinformatics have drawn considerable attention, accompanied by the development of a plethora of tools for the analysis of biological data. DNA microarrays constitute a prominent example of a high-throughput experimental technique that has required substantial contribution of bioinformatics tools. Following its popularity there is an on-going effort to integrate gene expression with other types of data in a common analytical approach. Pathway based microarray analysis seeks to facilitate microarray data in conjunction with biochemical pathway data and look for a coordinated change in the expression of genes constituting a pathway. However, it has been observed that genes in a pathway may show variable expression, with some appearing activated while others repressed. This thesis aims to add some contribution to pathway based microarray analysis and assist the interpretation of such observations, based on the fact that in all organisms a substantial number of genes take part in more than one biochemical pathway. It explores the hypothesis that the expression of such genes represents a net effect of their contribution to all their constituent pathways, applying statistical and data mining approaches. A heuristic search methodology is proposed to manipulate the pathway contribution of genes to follow underlying trends and interpret microarray results centred on pathway behaviour. The methodology is further refined to account for distinct genes encoding enzymes that catalyse the same reaction, and applied to modules, shorter chains of reactions forming sub-networks within pathways. Results based on various datasets are discussed, showing that the methodology is promising and may assist a biologist to decipher the biochemical state of an organism, in experiments where pathways exhibit variable expression.

Recent advances in genome editing and metabolic engineering enabled a precise construction of de novo biosynthesis pathways for high-value natural products. One important design decision to make for the engineering of heterologous biosynthesis systems is concerned with which foreign metabolic genes to introduce into a given host organism. Although this decision must be made based on multifaceted factors, a major one is the suitability of pathways for the endogenous metabolism of a host organism, in part because the efficacy of heterologous biosynthesis is affected by competing endogenous pathways. To address this point, we developed an open-access web server called MRE (metabolic route explorer) that systematically searches for promising heterologous pathways by considering competing endogenous reactions in a given host organism. MRE utilizes reaction Gibbs free energy information. However, 25% of the reactions do not have accurate estimations or cannot be estimated. To address this issue, we developed a method called FC (fingerprint contribution) to provide a more accurate and complete estimation of the reaction free energy. To rationally design a productive heterologous biosynthesis system, it is essential to consider the suitability of foreign reactions for the specific endogenous metabolic infrastructure of a host. For a given pair of starting and desired compounds in a given chassis organism, MRE ranks biosynthesis routes from the perspective of the integration of new reactions into the endogenous metabolic system. For each promising heterologous biosynthesis pathway, MRE suggests actual enzymes for foreign metabolic reactions and generates information on competing endogenous reactions for the consumption of metabolites. The URL of MRE is http://www.cbrc.kaust.edu.sa/mre/. Accurate and wide-ranging prediction of thermodynamic parameters for biochemical reactions can facilitate deeper insights into the workings and the design of metabolic systems. Here, we introduce a machine learning method, referred to as fingerprint contribution (FC), with chemical fingerprint-based features for the prediction of the Gibbs free energy of biochemical reactions. From a large pool of 2D fingerprint-based features, this method systematically selects a small number of relevant ones and uses them to construct a regularized linear model. FC is freely available for download at http://sfb.kaust.edu.sa/Pages/Software.aspx.

Geobacillus thermoglucosidasius is a Gram-positive thermophilic eubacterium (45-70‰) that has the ability to convert pre-treated lignocellulosic material LCM into ethanol. This organism has been genetically engineered such that its yield of ethanol production is in excess of 90% of the theoretical maximum [38]. There remains considerable scope to develop G.thermoglucosidasius to produce alternative fuels and chemicals of industrial importance. For such a useful bacterium the understanding of the global metabolism remains poorly characterised. To gain a better insight into the metabolic pathways and capabilities of G. thermoglucosidasius a bottom-up approach to construct a comprehensive metabolic model of the organism was applied. The model was build from manually annotated genome and incorporates data from wet lab experiments for accurate in silico analyses. The model simulations has highlighted a potential experimental design for the in silico production of succinate and butane-2,3-diol. PathwayBooster is also introduced in this study as a tool for curating metabolic pathways. The methodology is based on the assumption that the core metabolic capabilities are shared among evolutionarily closely related species [80]. This approach led to the further analysis of members of the genus Geobacillus with respect to their core metabolic capabilities, genome re-arrangements and shared unique features. Theoretical route for the biosynthesis of Vitamin B12 is presented here, which is novel to the canonical aerobic and anaerobic pathways known to date and ubiquitous amongst Geobacillus spp. The analysis of the gene assignment for this bacterium has highlighted the presence of NADP-dependent GAPDH. The theoretical function of this novel and previously uncategorised enzyme in the genus Geobacillus has been confirmed through enzymatic assays.

C. elegans is as an extremely powerful model for the study of innate immunity. MAP kinase signaling pathways in C. elegans are involved in the response of C. elegans to infection by pathogenic bacteria. The yeast S. cerevisiae can infect C. elegans, producing pathogenic effects. In this project, we tested whether several MAP kinase pathways are important for C. elegans¡¯ resistance to yeast infection. We tested members of several MAP kinase pathways including tir-1, nsy-1, sek-1 and pmk-1 in the p38 pathway, mek-1, jnk-1 and kgb-1 in JNK pathway and mek-2 and mpk-1 in the ERK pathway. We used survival assays to compare the responses of mutants of components of these pathways to the control responses of wild-type C. elegans. In the survival assay, we found that mutants in all three MAP kinase pathways showed a decreased survival relative to wild type; therefore all three pathways are important for innate immunity against the yeast pathogen. With respect to the p38 pathway, mutations affected survival but not the deformed anal region (Dar) phenotype, a putative defensive response induced by yeast in wild-type C. elegans. This indicates that for the p38 pathway, survival depends on some other immune response besides Dar. Finally, we hypothesize that cross talk occurs between p38 and JNK MAPK pathways in the C. elegans immune responses.

Os compostos BTEX (benzeno, tolueno, etilbenzeno e xilenos) são os contaminantes mais frequentemente encontrados dentre os hidrocarbonetos de petróleo. A remoção destes compostos é dependente da atividade de uma população de micro-organismos adaptados capazes de promover a biodegradação dos mesmos. Neste estudo, foram utilizadas cinco cepas isoladas de área contaminada capazes de degradar estes compostos. As concentrações de BTEX foram determinadas por análises quantitativas realizadas por cromatografia gasosa com extração por headspace. Uma série de experimentos foi realizada para investigar a capacidade destas cepas de remover os compostos BTEX de forma individual e simultânea. Os ensaios de indução de vias metabólicas mostraram que cada um dos BTEX foi capaz de induzir as vias de degradação de todos os quatro substratos, resultado que foi visualizado a partir do crescimento das cepas em cada um dos BTEX após as mesmas terem sido ambientadas em apenas um deles. Para os ensaios de degradação, Os resultados revelaram que as cinco cepas foram capazes de degradar todos os BTEX, tanto na forma de um único substrato bem como em forma de mistura. As taxas de remoção de um único substrato ficaram entre 63,9% e 97,9%. Houve um aumento da degradação dos compostos quando os mesmo foram fornecidos em forma de mistura. Com exceção do benzeno, todos os compostos foram degradados até atingirem concentrações que ficaram abaixo do limite de potabilidade estipulados, dentro de 9 horas. / BTEX (benzene, toluene, ethylbenzene and xylenes) compounds are the most frequently encountered subsurface contaminants among the various petroleum hydrocarbons. Removal of these compounds is dependent on the activity of a population of microorganisms adapted to promote biodegradation of them. In this study, five strains isolated from contaminated groundwater .able to degrade BTEX compounds were used. BTEX concentrations were determined by quantitative analysis performed by gaseous chromatography with headspace extraction. A series of batch experiments were carried out to investigate the ability of the strains for removing BTEX compounds using single and mixed substrates. The pathway induction assays showed that each one of the BTEX compounds was able to induce the degradation pathways of all four substrates, result that was visualized from the growth of the strains in each of the BTEX after they had been set in only one of them. For the degradation assays, the results revealed that the five strains were able to degrade all BTEX, both in the form of a single substrate as well as in the form of a mixture. The rates of removal of a single substrate were between 63.9% and 97.9%. There was an increased degradation of the compounds when they were provided as a mixture. With the exception of benzene, all compounds were degraded to concentrations below the stipulated drinking limit within 9 hours.