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.

Validation of Electronic Health Record Phenotyping of Bipolar Disorder Cases and Controls

Objective: The study was designed to validate use of elec-tronic health records (EHRs) for diagnosing bipolar disorder and classifying control subjects. Method: EHR data were obtained from a health care system of more than 4.6 million patients spanning more than 20 years. Experienced clinicians reviewed charts to identify text features and coded data consistent or inconsistent with a diagnosis of bipolar disorder. Natural language processing was used to train a diagnostic algorithm with 95% specificity for classifying bipolar disorder. Filtered coded data were used to derive three additional classification rules for case subjects and one for control subjects. The positive predictive value (PPV) of EHR-based bipolar disorder and subphenotype di- agnoses was calculated against diagnoses from direct semi- structured interviews of 190 patients by trained clinicians blind to EHR diagnosis. Results: The PPV of bipolar disorder defined by natural language processing was 0.85. Coded classification based on strict filtering achieved a value of 0.79, but classifications based on less stringent criteria performed less well. No EHR- classified control subject received a diagnosis of bipolar dis- order on the basis of direct interview (PPV=1.0). For most subphenotypes, values exceeded 0.80. The EHR-based clas- sifications were used to accrue 4,500 bipolar disorder cases and 5,000 controls for genetic analyses. Conclusions: Semiautomated mining of EHRs can be used to ascertain bipolar disorder patients and control subjects with high specificity and predictive value compared with diagnostic interviews. EHRs provide a powerful resource for high-throughput phenotyping for genetic and clinical research.

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.

Studies of Protein-Protein and Protein-Water Interactions by Small Angle X-Ray Scattering, Terahertz Spectroscopy, ASMOS, And Computer Simulation

The protein folding problem has been one of the most challenging subjects in biological physics due to its complexity. Energy landscape theory based on statistical mechanics provides a thermodynamic interpretation of the protein folding process. We have been working to answer fundamental questions about protein-protein and protein-water interactions, which are very important for describing the energy landscape surface of proteins correctly. At first, we present a new method for computing protein-protein interaction potentials of solvated proteins directly from SAXS data. An ensemble of proteins was modeled by Metropolis Monte Carlo and Molecular Dynamics simulations, and the global X-ray scattering of the whole model ensemble was computed at each snapshot of the simulation. The interaction potential model was optimized and iterated by a Levenberg-Marquardt algorithm. Secondly, we report that terahertz spectroscopy directly probes hydration dynamics around proteins and determines the size of the dynamical hydration shell. We also present the sequence and pH-dependence of the hydration shell and the effect of the hydrophobicity. On the other hand, kinetic terahertz absorption (KITA) spectroscopy is introduced to study the refolding kinetics of ubiquitin and its mutants. KITA results are compared to small angle X-ray scattering, tryptophan fluorescence, and circular dichroism results. We propose that KITA monitors the rearrangement of hydrogen bonding during secondary structure formation. Finally, we present development of the automated single molecule operating system (ASMOS) for a high throughput single molecule detector, which levitates a single protein molecule in a 10 µm diameter droplet by the laser guidance. I also have performed supporting calculations and simulations with my own program codes.

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.

Real-Time PCR Assays for the Detection of Puccinia psidii

Puccinia psidii (Myrtle rust) is an emerging pathogen that has a wide host range in the Myrtaceae family; it continues to show an increase in geographic range and is considered to be a significant threat to Myrtaceae plants worldwide. In this study, we describe the development and validation of three novel real-time polymerase reaction (qPCR) assays using ribosomal DNA and β-tubulin gene sequences to detect P. psidii. All qPCR assays were able to detect P. psidii DNA extracted from urediniospores and from infected plants, including asymptomatic leaf tissues. Depending on the gene target, qPCR was able to detect down to 0.011 pg of P. psidii DNA. The most optimum qPCR assay was shown to be highly specific, repeatable, and reproducible following testing using different qPCR reagents and real-time PCR platforms in different laboratories. In addition, a duplex qPCR assay was developed to allow coamplification of the cytochrome oxidase gene from host plants for use as an internal PCR control. The most optimum qPCR assay proved to be faster and more sensitive than the previously published nested PCR assay and will be particularly useful for high-throughput testing and to detect P. psidii at the early stages of infection, before the development of sporulating rust pustules.

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.

Characterization of nanoparticle mediated laser transfection by femtosecond laser pulses for applications in molecular medicine

Background: In molecular medicine, the manipulation of cells is prerequisite to evaluate genes as therapeutic targets or to transfect cells to develop cell therapeutic strategies. To achieve these purposes it is essential that given transfection techniques are capable of handling high cell numbers in reasonable time spans. To fulfill this demand, an alternative nanoparticle mediated laser transfection method is presented herein. The fs-laser excitation of cell-adhered gold nanoparticles evokes localized membrane permeabilization and enables an inflow of extracellular molecules into cells. Results: The parameters for an efficient and gentle cell manipulation are evaluated in detail. Efficiencies of 90% with a cell viability of 93% were achieved for siRNA transfection. The proof for a molecular medical approach is demonstrated by highly efficient knock down of the oncogene HMGA2 in a rapidly proliferating prostate carcinoma in vitro model using siRNA. Additionally, investigations concerning the initial perforation mechanism are conducted. Next to theoretical simulations, the laser induced effects are experimentally investigated by spectrometric and microscopic analysis. The results indicate that near field effects are the initial mechanism of membrane permeabilization. Conclusion: This methodical approach combined with an automated setup, allows a high throughput targeting of several 100,000 cells within seconds, providing an excellent tool for in vitro applications in molecular medicine. NIR fs lasers are characterized by specific advantages when compared to lasers employing longer (ps/ns) pulses in the visible regime. The NIR fs pulses generate low thermal impact while allowing high penetration depths into tissue. Therefore fs lasers could be used for prospective in vivo applications.

Seasonal and Species Variation of the Hepatotoxin Indospicine in Australian Indigofera Legumes as Measured by UPLC−MS/MS

Livestock industries have maintained a keen interest in pasture legumes because of the high protein content and nutritive value. Leguminous Indigofera plant species have been considered as having high feeding values to be utilized as pasture, but the occurrence of the toxic constituent indospicine in some species has restricted this utility. Indospicine has caused both primary and secondary hepatotoxicosis and also reproductive losses, but has only previously been determined in a small number of Indigofera species. This paper validates a high throughput ultra-performance liquid chromatography−tandem mass spectrometry (UPLC−MS/MS) method to determine indospicine content of various Indigofera species found in Australian pasture. Twelve species of Indigofera together with Indigastrum parviflorum plants were collected and analysed. Out of the 84 samples analyzed, *I. spicata contained the highest indospicine level (1003 ± 328 mg/kg DM, n = 4) followed by I. linnaei (755 ± 490 mg/kg DM, n = 51). Indospicine was not detected in 9 of the remaining 11 species, and at only low levels (<10 mg/kg DM) in 2 out of 8 I. colutea specimens and in 1 out of 5 I. linifolia specimens. Indospicine concentrations were below quantitation levels for other Indigofera spp. (I. adesmiifolia, I. georgei, I. hirsuta, I. leucotricha,* I. oblongifolia, I. australis and I. trita) and Indigastrum parviflorum. One of the more significant findings to emerge from this study is that the indospicine content of I. linnaei is highly variable (159 to 2128 mg/kg DM, n = 51), and differs across both regions and seasons. Its first re-growth after spring rain has a higher (p < 0.01) indospicine content than growth following more substantial summer rain. The species collected include the predominant Indigofera in Australia pasture, and of these, only *I. spicata and I. linnaei contain high enough levels of indospicine to pose a potential toxic threat to grazing herbivores.

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.

Laser ablation-based one-step generation and bio-functionalization of gold nanoparticles conjugated with aptamers

Background: Bio-conjugated nanoparticles are important analytical tools with emerging biological and medical applications. In this context, in situ conjugation of nanoparticles with biomolecules via laser ablation in an aqueous media is a highly promising one-step method for the production of functional nanoparticles resulting in highly efficient conjugation. Increased yields are required, particularly considering the conjugation of cost-intensive biomolecules like RNA aptamers. Results: Using a DNA aptamer directed against streptavidin, in situ conjugation results in nanoparticles with diameters of approximately 9 nm exhibiting a high aptamer surface density (98 aptamers per nanoparticle) and a maximal conjugation efficiency of 40.3%. We have demonstrated the functionality of the aptamer-conjugated nanoparticles using three independent analytical methods, including an agglomeration-based colorimetric assay, and solid-phase assays proving high aptamer activity. To demonstrate the general applicability of the in situ conjugation of gold nanoparticles with aptamers, we have transferred the method to an RNA aptamer directed against prostate-specific membrane antigen (PSMA). Successful detection of PSMA in human prostate cancer tissue was achieved utilizing tissue microarrays. Conclusions: In comparison to the conventional generation of bio-conjugated gold nanoparticles using chemical synthesis and subsequent bio-functionalization, the laser-ablation-based in situ conjugation is a rapid, one-step production method. Due to high conjugation efficiency and productivity, in situ conjugation can be easily used for high throughput generation of gold nanoparticles conjugated with valuable biomolecules like aptamers.

Synthetic biology in droplet-based microfluidics

Droplet microfluidics is an active multidisciplinary area of research that evolved out of the larger field of microfluidics. It enables the user to handle, process and manipulate micrometer-sized emulsion droplets on a micro- fabricated platform. The capability to carry out a large number of individual experiments per unit time makes the droplet microfluidic technology an ideal high-throughput platform for analysis of biological and biochemical samples. The objective of this thesis was to use such a technology for designing systems with novel implications in the newly emerging field of synthetic biology. Chapter 4, the first results chapter, introduces a novel method of droplet coalescence using a flow-focusing capillary device. In Chapter 5, the development of a microfluidic platform for the fabrication of a cell-free micro-environment for site-specific gene manipulation and protein expression is described. Furthermore, a novel fluorescent reporter system which functions both in vivo and in vitro is introduced in this chapter. Chapter 6 covers the microfluidic fabrication of polymeric vesicles from poly(2-methyloxazoline-b-dimethylsiloxane-b-2-methyloxazoline) tri-block copolymer. The polymersome made from this polymer was used in the next Chapter for the study of a chimeric membrane protein called mRFP1-EstA∗. In Chapter 7, the application of microfluidics for the fabrication of synthetic biological membranes to recreate artificial cell- like chassis structures for reconstitution of a membrane-anchored protein is described.

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.