Building a 'Repository of Science': the importance of integrating Biobanks within molecular pathology programmes

Repositories containing high quality human biospecimens linked with robust and relevant clinical and pathological information are required for the discovery and validation of biomarkers for disease diagnosis, progression and response to treatment. Current molecular based discovery projects using either low or high throughput technologies rely heavily on ready access to such sample collections. It is imperative that modern biobanks align with molecular diagnostic pathology practices not only to provide the type of samples needed for discovery projects but also to ensure requirements for ongoing sample collections and the future needs of researchers are adequately addressed. Biobanks within comprehensive molecular pathology programmes are perfectly positioned to offer more than just tumour derived biospecimens; for example, they have the ability to facilitate researchers gaining access to sample metadata such as digitised scans of tissue samples annotated prior to macrodissection for molecular diagnostics or pseudoanonymised clinical outcome data or research results retrieved from other users utilising the same or overlapping cohorts of samples. Furthermore, biobanks can work with molecular diagnostic laboratories to develop standardized methodologies for the acquisition and storage of samples required for new approaches to research such as ‘liquid biopsies’ which will ultimately feed into the test validations required in large prospective clinical studies in order to implement liquid biopsy approaches for routine clinical practice. We draw on our experience in Northern Ireland to discuss how this harmonised approach of biobanks working synergistically with molecular pathology programmes is key for the future success of precision medicine.

Circuit-aware design of energy-efficient massive MIMO systems

Densification is a key to greater throughput in cellular networks. The full potential of coordinated multipoint (CoMP) can be realized by massive multiple-input multiple-output (MIMO) systems, where each base station (BS) has very many antennas. However, the improved throughput comes at the price of more infrastructure; hardware cost and circuit power consumption scale linearly/affinely with the number of antennas. In this paper, we show that one can make the circuit power increase with only the square root of the number of antennas by circuit-aware system design. To this end, we derive achievable user rates for a system model with hardware imperfections and show how the level of imperfections can be gradually increased while maintaining high throughput. The connection between this scaling law and the circuit power consumption is established for different circuits at the BS.

Taxonomic and Functional Diversity of Soil and Hypolithic Microbial Communities in Miers Valley, McMurdo Dry Valleys, Antarctica

The McMurdo Dry Valleys of Antarctica are an extreme polar desert. Mineral soils support subsurface microbial communities and translucent rocks support development of hypolithic communities on ventral surfaces in soil contact. Despite significant research attention, relatively little is known about taxonomic and functional diversity or their inter-relationships. Here we report a combined diversity and functional interrogation for soil and hypoliths of the Miers Valley in the McMurdo Dry Valleys of Antarctica. The study employed 16S rRNA fingerprinting and high throughput sequencing combined with the GeoChip functional microarray. The soil community was revealed as a highly diverse reservoir of bacterial diversity dominated by actinobacteria. Hypolithic communities were less diverse and dominated by cyanobacteria. Major differences in putative functionality were that soil communities displayed greater diversity in stress tolerance and recalcitrant substrate utilization pathways, whilst hypolithic communities supported greater diversity of nutrient limitation adaptation pathways. A relatively high level of functional redundancy in both soil and hypoliths may indicate adaptation of these communities to fluctuating environmental conditions.

Fabrication and Characterization of Efficient Optical Filter Arrays Implemented by 3D Nanoimprint

In dieser Arbeit werden optische Filterarrays für hochqualitative spektroskopische Anwendungen im sichtbaren (VIS) Wellenlängenbereich untersucht. Die optischen Filter, bestehend aus Fabry-Pérot (FP)-Filtern für hochauflösende miniaturisierte optische Nanospektrometer, basieren auf zwei hochreflektierenden dielektrischen Spiegeln und einer zwischenliegenden Resonanzkavität aus Polymer. Jeder Filter erlaubt einem schmalbandigem spektralen Band (in dieser Arbeit Filterlinie genannt) ,abhängig von der Höhe der Resonanzkavität, zu passieren. Die Effizienz eines solchen optischen Filters hängt von der präzisen Herstellung der hochselektiven multispektralen Filterfelder von FP-Filtern mittels kostengünstigen und hochdurchsatz Methoden ab. Die Herstellung der multiplen Spektralfilter über den gesamten sichtbaren Bereich wird durch einen einzelnen Prägeschritt durch die 3D Nanoimprint-Technologie mit sehr hoher vertikaler Auflösung auf einem Substrat erreicht. Der Schlüssel für diese Prozessintegration ist die Herstellung von 3D Nanoimprint-Stempeln mit den gewünschten Feldern von Filterkavitäten. Die spektrale Sensitivität von diesen effizienten optischen Filtern hängt von der Genauigkeit der vertikalen variierenden Kavitäten ab, die durch eine großflächige ‚weiche„ Nanoimprint-Technologie, UV oberflächenkonforme Imprint Lithographie (UV-SCIL), ab. Die Hauptprobleme von UV-basierten SCIL-Prozessen, wie eine nichtuniforme Restschichtdicke und Schrumpfung des Polymers ergeben Grenzen in der potenziellen Anwendung dieser Technologie. Es ist sehr wichtig, dass die Restschichtdicke gering und uniform ist, damit die kritischen Dimensionen des funktionellen 3D Musters während des Plasmaätzens zur Entfernung der Restschichtdicke kontrolliert werden kann. Im Fall des Nanospektrometers variieren die Kavitäten zwischen den benachbarten FP-Filtern vertikal sodass sich das Volumen von jedem einzelnen Filter verändert , was zu einer Höhenänderung der Restschichtdicke unter jedem Filter führt. Das volumetrische Schrumpfen, das durch den Polymerisationsprozess hervorgerufen wird, beeinträchtigt die Größe und Dimension der gestempelten Polymerkavitäten. Das Verhalten des großflächigen UV-SCIL Prozesses wird durch die Verwendung von einem Design mit ausgeglichenen Volumen verbessert und die Prozessbedingungen werden optimiert. Das Stempeldesign mit ausgeglichen Volumen verteilt 64 vertikal variierenden Filterkavitäten in Einheiten von 4 Kavitäten, die ein gemeinsames Durchschnittsvolumen haben. Durch die Benutzung der ausgeglichenen Volumen werden einheitliche Restschichtdicken (110 nm) über alle Filterhöhen erhalten. Die quantitative Analyse der Polymerschrumpfung wird in iii lateraler und vertikaler Richtung der FP-Filter untersucht. Das Schrumpfen in vertikaler Richtung hat den größten Einfluss auf die spektrale Antwort der Filter und wird durch die Änderung der Belichtungszeit von 12% auf 4% reduziert. FP Filter die mittels des Volumengemittelten Stempels und des optimierten Imprintprozesses hergestellt wurden, zeigen eine hohe Qualität der spektralen Antwort mit linearer Abhängigkeit zwischen den Kavitätshöhen und der spektralen Position der zugehörigen Filterlinien.

La face cachée de la dune : communautés fongiques du sol: dynamique, succession et interactions avec la végétation d’un écosystème dunaire côtier aux Îles de la Madeleine, Qc

Les écosystèmes dunaires remplissent plusieurs fonctions écologiques essentielles comme celle de protéger le littoral grâce à leur capacité d’amortissement face aux vents et vagues des tempêtes. Les dunes jouent aussi un rôle dans la filtration de l’eau, la recharge de la nappe phréatique, le maintien de la biodiversité, en plus de présenter un attrait culturel, récréatif et touristique. Les milieux dunaires sont très dynamiques et incluent plusieurs stades de succession végétale, passant de la plage de sable nu à la dune bordière stabilisée par l’ammophile à ligule courte, laquelle permet aussi l’établissement d’autres herbacées, d’arbustes et, éventuellement, d’arbres. Or, la survie de ces végétaux est intimement liée aux microorganismes du sol. Les champignons du sol interagissent intimement avec les racines des plantes, modifient la structure des sols, et contribuent à la décomposition de la matière organique et à la disponibilité des nutriments. Ils sont donc des acteurs clés de l’écologie des sols et contribuent à la stabilisation des dunes. Malgré cela, la diversité et la structure des communautés fongiques, ainsi que les mécanismes influençant leur dynamique écologique, demeurent relativement méconnus. Le travail présenté dans cette thèse explore la diversité des communautés fongiques à travers le gradient de succession et de conditions édaphiques d’un écosystème dunaire côtier afin d’améliorer la compréhension de la dynamique des sols en milieux dunaires. Une vaste collecte de données sur le terrain a été réalisée sur une plaine de dunes reliques se trouvant aux Îles de la Madeleine, Qc. J’ai échantillonné plus de 80 sites répartis sur l’ensemble de ce système dunaire et caractérisé les champignons du sol grâce au séquençage à haut débit. Dans un premier temps, j’ai dressé un portait d’ensemble des communautés fongiques du sol à travers les différentes zones des dunes. En plus d’une description taxonomique, les modes de vie fongiques ont été prédits afin de mieux comprendre comment les variations au niveau des communautés de champignons du sol peuvent se traduire en changements fonctionnels. J’ai observé un niveau de diversité fongique élevé (plus de 3400 unités taxonomiques opérationnelles au total) et des communautés taxonomiquement et fonctionnellement distinctes à travers un gradient de succession et de conditions édaphiques. Ces résultats ont aussi indiqué que toutes les zones des dunes, incluant la zone pionière, supportent des communautés fongiques diversifiées. Ensuite, le lien entre les communautés végétales et fongiques a été étudié à travers l’ensemble de la séquence dunaire. Ces résultats ont montré une augmentation claire de la richesse spécifique végétale, ainsi qu’une augmentation de la diversité des stratégies d’acquisition de nutriments (traits souterrains lié à la nutrition des plantes, soit mycorhizien à arbuscule, ectomycorhizien, mycorhizien éricoide, fixateur d’azote ou non spécialisé). J’ai aussi pu établir une forte corrélation entre les champignons du sol et la végétation, qui semblent tous deux réagir de façon similaire aux conditions physicochimiques du sol. Le pH du sol influençait fortement les communautés végétales et fongiques. Le lien observé entre les communautés végétales et fongiques met l’emphase sur l’importance des interactions biotiques positives au fil de la succession dans les environnements pauvres en nutriments. Finalement, j’ai comparé les communautés de champignons ectomycorhiziens associées aux principales espèces arborescentes dans les forêts dunaires. J’ai observé une richesse importante, avec un total de 200 unités taxonomiques opérationnelles ectomycorhiziennes, appartenant principalement aux Agaricomycètes. Une analyse de réseaux n’a pas permis de détecter de modules (c'est-à-dire des sous-groupes d’espèces en interaction), ce qui indique un faible niveau de spécificité des associations ectomycorhiziennes. De plus, je n’ai pas observé de différences en termes de richesse ou de structure des communautés entre les quatre espèces hôtes. En conclusion, j’ai pu observer à travers la succession dunaire des communautés diversifiées et des structures distinctes selon la zone de la dune, tant chez les champignons que chez les plantes. La succession semble toutefois moins marquée au niveau des communautés fongiques, par rapport aux patrons observés chez les plantes. Ces résultats ont alimenté une réflexion sur le potentiel et les perspectives, mais aussi sur les limitations des approches reposant sur le séquençage à haut-débit en écologie microbienne.

Structure et biogéographie des communautés de pico- et de nanoeurcaryotes pélagiques autour de l'archipel du Svalbard

L’Arctique s’est réchauffé rapidement et il y a urgence d’anticiper les effets que cela pourrait avoir sur les protistes à la base de la chaîne alimentaire. Le phytoplancton de l’Océan Arctique inclut les pico- et nano-eucaryotes (0.45-10 μm diamètre de la cellule) et plusieurs de ceux-ci sont des écotypes retrouvés seulement dans l’Arctique alors que d’autres sont introduits des océans plus méridionaux. Alors que les océans tempérés pénètrent dans l’Arctique, il devient pertinent de savoir si ces communautés microbiennes pourraient être modifiées. L’archipel du Svalbard est une région idéale pour observer la biogéographie des communautés microbiennes sous l’influence de processus polaires et tempérés. Bien qu’ils soient géographiquement proches, les régions côtières entourant le Svalbard sont sujettes à des intrusions alternantes de masses d’eau de l’Arctique et de l’Atlantique en plus des conditions locales. Huit sites ont été échantillonnés en juillet 2013 pour identifier les protistes selon un gradient de profondeur et de masses d’eau autour de l’archipel. En plus des variables océanographiques standards, l’eau a été échantillonnée pour synthétiser des banques d’amplicons ciblant le 18S SSU ARNr et son gène pour ensuite être séquencées à haut débit. Cinq des sites d’étude avaient de faibles concentrations de chlorophylle avec des compositions de communauté post-efflorescence dominée par les dinoflagellés, ciliés, des alvéolés parasites putatifs, chlorophycées et prymnesiophytées. L’intrusion des masses d’eau et les conditions environnementales locales étaient corrélées avec la structure des communautés ; l’origine de la masse d’eau contribuant le plus à la distance phylogénétique des communautés microbiennes. Au sein de trois fjords, de fortes concentrations de chlorophylle sous-entendaient des activités d’efflorescence. Un fjord était dominé par Phaeocystis, un deuxième par un clade arctique identifié comme un Pelagophyceae et un troisième par un assemblage mixte. En général, un signal fort d’écotypes liés à l’Arctique prédominait autour du Svalbard.

Diversité microbienne associée au cycle du méthane dans les mares de fonte du pergélisol subarctique

La fonte et l’effondrement du pergélisol riche en glace dans la région subarctique du Québec ont donné lieu à la formation de petits lacs (mares de thermokarst) qui émettent des gaz à effet de serre dans l’atmosphère tels que du dioxyde de carbone et du méthane. Pourtant, la composition de la communauté microbienne qui est à la base des processus biogéochimiques dans les mares de fonte a été très peu étudiée, particulièrement en ce qui concerne la diversité et l’activité des micro-organismes impliqués dans le cycle du méthane. L’objectif de cette thèse est donc d’étudier la diversité phylogénétique et fonctionnelle des micro-organismes dans les mares de fonte subarctiques en lien avec les caractéristiques de l’environnement et les émissions de méthane. Pour ce faire, une dizaine de mares ont été échantillonnées dans quatre vallées situées à travers un gradient de fonte du pergélisol, et disposant de différentes propriétés physico-chimiques. Selon les vallées, les mares peuvent être issues de la fonte de palses (buttes de tourbe, à dominance organique) ou de lithalses (buttes de sol à dominance minérale) ce qui influence la nature du carbone organique disponible pour la reminéralisation microbienne. Durant l’été, les mares étaient fortement stratifiées; il y avait un fort gradient physico-chimique au sein de la colonne d’eau, avec une couche d’eau supérieure oxique et une couche d’eau profonde pauvre en oxygène ou anoxique. Pour identifier les facteurs qui influencent les communautés microbiennes, des techniques de séquençage à haut débit ont été utilisées ciblant les transcrits des gènes de l’ARNr 16S et des gènes impliqués dans le cycle du méthane : mcrA pour la méthanogenèse et pmoA pour la méthanotrophie. Pour évaluer l’activité des micro-organismes, la concentration des transcrits des gènes fonctionnels a aussi été mesurée avec des PCR quantitatives (qPCR). Les résultats montrent une forte dominance de micro-organismes impliqués dans le cycle du méthane, c’est-à-dire des archées méthanogènes et des bactéries méthanotrophes. L’analyse du gène pmoA indique que les bactéries méthanotrophes n’étaient pas seulement actives à la surface, mais aussi dans le fond de la mare où les concentrations en oxygène étaient minimales; ce qui est inattendu compte tenu de leur besoin en oxygène pour consommer le méthane. En général, la composition des communautés microbiennes était principalement influencée par l’origine de la mare (palse ou lithalse), et moins par le gradient de dégradation du pergélisol. Des variables environnementales clefs comme le pH, le phosphore et le carbone organique dissous, contribuent à la distinction des communautés microbiennes entre les mares issues de palses ou de lithalses. Avec l’intensification des effets du réchauffement climatique, ces communautés microbiennes vont faire face à des changements de conditions qui risquent de modifier leur composition taxonomique, et leurs réponses aux changements seront probablement différentes selon le type de mares. De plus, dans le futur les conditions d’oxygénation au sein des mares seront soumises à des modifications majeures associées avec un changement dans la durée des périodes de fonte de glace et de stratification. Ce type de changement aura un impact sur l’équilibre entre la méthanogenèse et la méthanotrophie, et affectera ainsi les taux d’émissions de méthane. Cependant, les résultats obtenus dans cette thèse indiquent que les archées méthanogènes et les bactéries méthanotrophes peuvent développer des stratégies pour survivre et rester actives au-delà des limites de leurs conditions d’oxygène habituelles.

Post-translational lysine-acetylation of Ran and its regulation by Sirtuin deacetylases

Through recent advances in high-throughput mass spectrometry it has become evident that post-translational N-(epsilon)-lysine-acetylation is a modification found on thousands of proteins of all cellular compartments and all essential physiological processes. Many aspects in the biology of lysine-acetylation are poorly understood, including its regulation by lysine-acetyltransferases and lysine-deacetylases (KDACs). Here, the role of this modification was investigated for the small GTP-binding protein Ran, which, inter alia, is essential for the regulation of nucleocytoplasmic transport. To this end, site-specifically acetylated Ran was produced in E. coli by genetic code expansion. For five previously identified sites, Ran acetylation was tested regarding its impact on the intrinsic GTP hydrolysis rate, the assembly of export complexes (modeled in vitro with the export receptor CRM1 and the export substrate Spn1) and the interaction of Ran with its GTPase activation protein RanGAP and RanBP1. Overall, mild effects of Ran acetylation were observed for intrinsic and RanGAP-stimulated GTP hydrolysis rates. The interaction of active Ran with RanBP1 was negatively influenced by Ran acetylation at K159. Moreover, CRM1 bound to Ran acetylated at K37, K99 or K159 interacted more strongly with Spn1. Thus, lysine-acetylation interferes with essential aspects of Ran function. An in vitro screen was performed to identify potential Ran KDACs. The NAD+-dependent KDACs of the Sirtuin class showed activity towards two acetylation sites of Ran, K37 and K71. The specificity of Sirtuins was further analyzed based on an additional Ran acetylation site, K38. Since deacetylation of RanAcK38 was much slower compared to RanAcK37, di-acetylated RanAcK37/38 was tested next. The deacetylation rate of di-acetylated Ran was comparable to that of RanAcK37. Deacetylation experiments under single turnover conditions revealed that deacetylation occurs first at the K38 site in the di-acetylated RanAcK37/38 background. The ability of Sirtuins to deacetylate two adjacent AcKs was further investigated based on two proteins, which had previously been found to be di-acetylated and targeted by Sirtuins, namely the tumor suppressor protein p53 and phosphoenolpyruvate carboxykinase 1 (PEPCK1). p53 was readily deacetylated at two di-acetylation sites (K372/372 and K381/382), whereas PEPCK1 was not deacetylated in vitro. Taken together, these results have important implications for the substrate specificity of Sirtuins.

Optimization of a multielectrode array (MEA)-based approach to study the impact of Aβ on the SH-SY5Y cell line

The human brain stores, integrates, and transmits information recurring to millions of neurons, interconnected by countless synapses. Though neurons communicate through chemical signaling, information is coded and conducted in the form of electrical signals. Neuroelectrophysiology focus on the study of this type of signaling. Both intra and extracellular approaches are used in research, but none holds as much potential in high-throughput screening and drug discovery, as extracellular recordings using multielectrode arrays (MEAs). MEAs measure neuronal activity, both in vitro and in vivo. Their key advantage is the capability to record electrical activity at multiple sites simultaneously. Alzheimer’s disease (AD) is the most common neurodegenerative disease and one of the leading causes of death worldwide. It is characterized by neurofibrillar tangles and aggregates of amyloid-β (Aβ) peptides, which lead to the loss of synapses and ultimately neuronal death. Currently, there is no cure and the drugs available can only delay its progression. In vitro MEA assays enable rapid screening of neuroprotective and neuroharming compounds. Therefore, MEA recordings are of great use in both AD basic and clinical research. The main aim of this thesis was to optimize the formation of SH-SY5Y neuronal networks on MEAs. These can be extremely useful for facilities that do not have access to primary neuronal cultures, but can also save resources and facilitate obtaining faster high-throughput results to those that do. Adhesion-mediating compounds proved to impact cell morphology, viability and exhibition of spontaneous electrical activity. Moreover, SH-SY5Y cells were successfully differentiated and demonstrated acute effects on neuronal function after Aβ addition. This effect on electrical signaling was dependent on Aβ oligomers concentration. The results here presented allow us to conclude that the SH-SY5Y cell line can be successfully differentiated in properly coated MEAs and be used for assessing acute Aβ effects on neuronal signaling.

Real-time analytics on large dynamic graphs

In today's fast-paced and interconnected digital world, the data generated by an increasing number of applications is being modeled as dynamic graphs. The graph structure encodes relationships among data items, while the structural changes to the graphs as well as the continuous stream of information produced by the entities in these graphs make them dynamic in nature. Examples include social networks where users post status updates, images, videos, etc.; phone call networks where nodes may send text messages or place phone calls; road traffic networks where the traffic behavior of the road segments changes constantly, and so on. There is a tremendous value in storing, managing, and analyzing such dynamic graphs and deriving meaningful insights in real-time. However, a majority of the work in graph analytics assumes a static setting, and there is a lack of systematic study of the various dynamic scenarios, the complexity they impose on the analysis tasks, and the challenges in building efficient systems that can support such tasks at a large scale. In this dissertation, I design a unified streaming graph data management framework, and develop prototype systems to support increasingly complex tasks on dynamic graphs. In the first part, I focus on the management and querying of distributed graph data. I develop a hybrid replication policy that monitors the read-write frequencies of the nodes to decide dynamically what data to replicate, and whether to do eager or lazy replication in order to minimize network communication and support low-latency querying. In the second part, I study parallel execution of continuous neighborhood-driven aggregates, where each node aggregates the information generated in its neighborhoods. I build my system around the notion of an aggregation overlay graph, a pre-compiled data structure that enables sharing of partial aggregates across different queries, and also allows partial pre-computation of the aggregates to minimize the query latencies and increase throughput. Finally, I extend the framework to support continuous detection and analysis of activity-based subgraphs, where subgraphs could be specified using both graph structure as well as activity conditions on the nodes. The query specification tasks in my system are expressed using a set of active structural primitives, which allows the query evaluator to use a set of novel optimization techniques, thereby achieving high throughput. Overall, in this dissertation, I define and investigate a set of novel tasks on dynamic graphs, design scalable optimization techniques, build prototype systems, and show the effectiveness of the proposed techniques through extensive evaluation using large-scale real and synthetic datasets.

Genomic and biochemical investigation of soybean antioxidant metabolism in response to growth at elevated carbon dioxide and elevated ozone

Metabolism in an environment containing of 21% oxygen has a high risk of oxidative damage due to the formation of reactive oxygen species. Therefore, plants have evolved an antioxidant system consisting of metabolites and enzymes that either directly scavenge ROS or recycle the antioxidant metabolites. Ozone is a temporally dynamic molecule that is both naturally occurring as well as an environmental pollutant that is predicted to increase in concentration in the future as anthropogenic precursor emissions rise. It has been hypothesized that any elevation in ozone concentration will cause increased oxidative stress in plants and therefore enhanced subsequent antioxidant metabolism, but evidence for this response is variable. Along with increasing atmospheric ozone concentrations, atmospheric carbon dioxide concentration is also rising and is predicted to continue rising in the future. The effect of elevated carbon dioxide concentrations on antioxidant metabolism varies among different studies in the literature. Therefore, the question of how antioxidant metabolism will be affected in the most realistic future atmosphere, with increased carbon dioxide concentration and increased ozone concentration, has yet to be answered, and is the subject of my thesis research. First, in order to capture as much of the variability in the antioxidant system as possible, I developed a suite of high-throughput quantitative assays for a variety of antioxidant metabolites and enzymes. I optimized these assays for Glycine max (soybean), one of the most important food crops in the world. These assays provide accurate, rapid and high-throughput measures of both the general and specific antioxidant action of plant tissue extracts. Second, I investigated how growth at either elevated carbon dioxide concentration or chronic elevated ozone concentration altered antioxidant metabolism, and the ability of soybean to respond to an acute oxidative stress in a controlled environment study. I found that growth at chronic elevated ozone concentration increased the antioxidant capacity of leaves, but was unchanged or only slightly increased following an acute oxidative stress, suggesting that growth at chronic elevated ozone concentration primed the antioxidant system. Growth at high carbon dioxide concentration decreased the antioxidant capacity of leaves, increased the response of the existing antioxidant enzymes to an acute oxidative stress, but dampened and delayed the transcriptional response, suggesting an entirely different regulation of the antioxidant system. Third, I tested the findings from the controlled environment study in a field setting by investigating the response of the soybean antioxidant system to growth at elevated carbon dioxide concentration, chronic elevated ozone concentration and the combination of elevated carbon dioxide concentration and elevated ozone concentration. In this study, I confirmed that growth at elevated carbon dioxide concentration decreased specific components of antioxidant metabolism in the field. I also verified that increasing ozone concentration is highly correlated with increases in the metabolic and genomic components of antioxidant metabolism, regardless of carbon dioxide concentration environment, but that the response to increasing ozone concentration was dampened at elevated carbon dioxide concentration. In addition, I found evidence suggesting an up regulation of respiratory metabolism at higher ozone concentration, which would supply energy and carbon for detoxification and repair of cellular damage. These results consistently support the conclusion that growth at elevated carbon dioxide concentration decreases antioxidant metabolism while growth at elevated ozone concentration increases antioxidant metabolism.

DATA DRIVEN APPROACHES TO IDENTIFY DETERMINANTS OF HEART DISEASES AND CANCER RESISTANCE

Cancer and cardio-vascular diseases are the leading causes of death world-wide. Caused by systemic genetic and molecular disruptions in cells, these disorders are the manifestation of profound disturbance of normal cellular homeostasis. People suffering or at high risk for these disorders need early diagnosis and personalized therapeutic intervention. Successful implementation of such clinical measures can significantly improve global health. However, development of effective therapies is hindered by the challenges in identifying genetic and molecular determinants of the onset of diseases; and in cases where therapies already exist, the main challenge is to identify molecular determinants that drive resistance to the therapies. Due to the progress in sequencing technologies, the access to a large genome-wide biological data is now extended far beyond few experimental labs to the global research community. The unprecedented availability of the data has revolutionized the capabilities of computational researchers, enabling them to collaboratively address the long standing problems from many different perspectives. Likewise, this thesis tackles the two main public health related challenges using data driven approaches. Numerous association studies have been proposed to identify genomic variants that determine disease. However, their clinical utility remains limited due to their inability to distinguish causal variants from associated variants. In the presented thesis, we first propose a simple scheme that improves association studies in supervised fashion and has shown its applicability in identifying genomic regulatory variants associated with hypertension. Next, we propose a coupled Bayesian regression approach -- eQTeL, which leverages epigenetic data to estimate regulatory and gene interaction potential, and identifies combinations of regulatory genomic variants that explain the gene expression variance. On human heart data, eQTeL not only explains a significantly greater proportion of expression variance in samples, but also predicts gene expression more accurately than other methods. We demonstrate that eQTeL accurately detects causal regulatory SNPs by simulation, particularly those with small effect sizes. Using various functional data, we show that SNPs detected by eQTeL are enriched for allele-specific protein binding and histone modifications, which potentially disrupt binding of core cardiac transcription factors and are spatially proximal to their target. eQTeL SNPs capture a substantial proportion of genetic determinants of expression variance and we estimate that 58% of these SNPs are putatively causal. The challenge of identifying molecular determinants of cancer resistance so far could only be dealt with labor intensive and costly experimental studies, and in case of experimental drugs such studies are infeasible. Here we take a fundamentally different data driven approach to understand the evolving landscape of emerging resistance. We introduce a novel class of genetic interactions termed synthetic rescues (SR) in cancer, which denotes a functional interaction between two genes where a change in the activity of one vulnerable gene (which may be a target of a cancer drug) is lethal, but subsequently altered activity of its partner rescuer gene restores cell viability. Next we describe a comprehensive computational framework --termed INCISOR-- for identifying SR underlying cancer resistance. Applying INCISOR to mine The Cancer Genome Atlas (TCGA), a large collection of cancer patient data, we identified the first pan-cancer SR networks, composed of interactions common to many cancer types. We experimentally test and validate a subset of these interactions involving the master regulator gene mTOR. We find that rescuer genes become increasingly activated as breast cancer progresses, testifying to pervasive ongoing rescue processes. We show that SRs can be utilized to successfully predict patients' survival and response to the majority of current cancer drugs, and importantly, for predicting the emergence of drug resistance from the initial tumor biopsy. Our analysis suggests a potential new strategy for enhancing the effectiveness of existing cancer therapies by targeting their rescuer genes to counteract resistance. The thesis provides statistical frameworks that can harness ever increasing high throughput genomic data to address challenges in determining the molecular underpinnings of hypertension, cardiovascular disease and cancer resistance. We discover novel molecular mechanistic insights that will advance the progress in early disease prevention and personalized therapeutics. Our analyses sheds light on the fundamental biological understanding of gene regulation and interaction, and opens up exciting avenues of translational applications in risk prediction and therapeutics.

Host cellular regulatory networks in dengue virus-human interactions

Dengue fever is one of the most important mosquito-borne diseases worldwide and is caused by infection with dengue virus (DENV). The disease is endemic in tropical and sub-tropical regions and has increased remarkably in the last few decades. At present, there is no antiviral or approved vaccine against the virus. Treatment of dengue patients is usually supportive, through oral or intravenous rehydration, or by blood transfusion for more severe dengue cases. Infection of DENV in humans and mosquitoes involves a complex interplay between the virus and host factors. This results in regulation of numerous intracellular processes, such as signal transduction and gene transcription which leads to progression of disease. To understand the mechanisms underlying the disease, the study of virus and host factors is therefore essential and could lead to the identification of human proteins modulating an essential step in the virus life cycle. Knowledge of these human proteins could lead to the discovery of potential new drug targets and disease control strategies in the future. Recent advances of high throughput screening technologies have provided researchers with molecular tools to carry out investigations on a large scale. Several studies have focused on determination of the host factors during DENV infection in human and mosquito cells. For instance, a genome-wide RNA interference (RNAi) screen has identified host factors that potentially play an important role in both DENV and West Nile virus replication (Krishnan et al. 2008). In the present study, a high-throughput yeast two-hybrid screen has been utilised in order to identify human factors interacting with DENV non-structural proteins. From the screen, 94 potential human interactors were identified. These include proteins involved in immune signalling regulation, potassium voltage-gated channels, transcriptional regulators, protein transporters and endoplasmic reticulum-associated proteins. Validation of fifteen of these human interactions revealed twelve of them strongly interacted with DENV proteins. Two proteins of particular interest were selected for further investigations of functional biological systems at the molecular level. These proteins, including a nuclear-associated protein BANP and a voltage-gated potassium channel Kv1.3, both have been identified through interaction with the DENV NS2A. BANP is known to be involved in NF-kB immune signalling pathway, whereas, Kv1.3 is known to play an important role in regulating passive flow of potassium ions upon changes in the cell transmembrane potential. This study also initiated a construction of an Aedes aegypti cDNA library for use with DENV proteins in Y2H screen. However, several issues were encountered during the study which made the library unsuitable for protein interaction analysis. In parallel, innate immune signalling was also optimised for downstream analysis. Overall, the work presented in this thesis, in particular the Y2H screen provides a number of human factors potentially targeted by DENV during infection. Nonetheless, more work is required to be done in order to validate these proteins and determine their functional properties, as well as testing them with infectious DENV to establish a biological significance. In the long term, data from this study will be useful for investigating potential human factors for development of antiviral strategies against dengue.

A model of macadamia with application to pruning in orchards

A self-organising model of macadamia, expressed using L-Systems, was used to explore aspects of canopy management. A small set of parameters control the basic architecture of the model, with a high degree of self-organisation occurring to determine the fate and growth of buds. Light was sensed at the leaf level and used to represent vigour and accumulated basipetally. Buds also sensed light so as to provide demand in the subsequent redistribution of the vigour. Empirical relationships were derived from a set of 24 completely digitised trees after conversion to multiscale tree graphs (MTG) and analysis with the OpenAlea software library. The ability to write MTG files was embedded within the model so that various tree statistics could be exported for each run of the model. To explore the parameter space a series of runs was completed using a high-throughput computing platform. When combined with MTG generation and analysis with OpenAlea it provided a convenient way in which thousands of simulations could be explored. We allowed the model trees to develop using self-organisation and simulated cultural practices such as hedging, topping, removal of the leader and limb removal within a small representation of an orchard. The model provides insight into the impact of these practices on potential for growth and the light distribution within the canopy and to the orchard floor by coupling the model with a path-tracing program to simulate the light environment. The lessons learnt from this will be applied to other evergreen, tropical fruit and nut trees.

Engineering the transition from non-living to living matter

Re-creating and understanding the origin of life represents one of the major challenges facing the scientific community. We will never know exactly how life started on planet Earth, however, we can reconstruct the most likely chemical pathways that could have contributed to the formation of the first living systems. Traditionally, prebiotic chemistry has investigated the formation of modern life’s precursors and their self-organisation under very specific conditions thought to be ‘plausible’. So far, this approach has failed to produce a living system from the bottom-up. In the work presented herein, two different approaches are employed to explore the transition from inanimate to living matter. The development of microfluidic technology during the last decades has changed the way traditional chemical and biological experiments are performed. Microfluidics allows the handling of low volumes of reagents with very precise control. The use of micro-droplets generated within microfluidic devices is of particular interest to the field of Origins of Life and Artificial Life. Whilst many efforts have been made aiming to construct cell-like compartments from modern biological constituents, these are usually very difficult to handle. However, microdroplets can be easily generated and manipulated at kHz rates, making it suitable for high-throughput experimentation and analysis of compartmentalised chemical reactions. Therefore, we decided to develop a microfluidic device capable of manipulating microdroplets in such a way that they could be efficiently mixed, split and sorted within iterative cycles. Since no microfluidic technology had been developed before in the Cronin Group, the first chapter of this thesis describes the soft lithographic methods and techniques developed to fabricate microfluidic devices. Also, special attention is placed on the generation of water-in-oil microdroplets, and the subsequent modules required for the manipulation of the droplets such as: droplet fusers, splitters, sorters and single/multi-layer micromechanical valves. Whilst the first part of this thesis describes the development of a microfluidic platform to assist chemical evolution, finding a compatible set of chemical building blocks capable of reacting to form complex molecules with endowed replicating or catalytic activity was challenging. Abstract 10 Hence, the second part of this thesis focuses on potential chemistry that will ultimately possess the properties mentioned above. A special focus is placed on the formation of peptide bonds from unactivated amino acids, despite being one of the greatest challenges in prebiotic chemistry. As opposed to classic prebiotic experiments, in which a specific set of conditions is studied to fit a particular hypothesis, we took a different approach: we explored the effects of several parameters at once on a model polymerisation reaction, without constraints on hypotheses on the nature of optimum conditions or plausibility. This was facilitated by development of a new high-throughput automated platform, allowing the exploration of a much larger number of parameters. This led us to discover that peptide bond formation is less challenging than previously imagined. Having established the right set of conditions under which peptide bond formation was enhanced, we then explored the co-oligomerisation between different amino acids, aiming for the formation of heteropeptides with different structure or function. Finally, we studied the effect of various environmental conditions (rate of evaporation, presence of salts or minerals) in the final product distribution of our oligomeric products.