Familial amyloid polyneuropathy: TTR sequencing and "in silico" analysis

Familial amyloid polyneuropathy (FAP) or paramiloidosis is an autosomal dominant neurodegenerative disease with onset on adult age that is characterized by mutated protein deposition in the form of amyloid substance. FAP is due to a point alteration in the transthyretin (TTR) gene and until now more than 100 amyloidogenic mutations have been described in TTR gene. FAP shows a wide variation in age-at-onset (AO) (19-82 years, in Portuguese cases) and the V30M mutation often runs through several generation of asymptomatic carriers, before expressing in a proband, but the protective effect disappear in a single generation, with offspring of late-onset cases having early onset. V30M mutation does not explain alone the symptoms and AO variability of the disease observed in the same family. Our aim in this study was to identify genetic factors associated with AO variability and reduced penetrance which can have important clinical implications. To accomplish this we genotyped 230 individuals, using a directautomated sequencing approach in order to identify possible genetic modifiers within the TTR locus. After genotyping, we assessed a putative association of the SNPs found with AO and an intensive in silico analysis was performed in order to understand a possible regulation of gene expression. Although we did not find any significant association between SNPs and AO, we found very interesting and unreported results in the in silico analysis since we observed some alterations in the mechanism of splicing, transcription factors binding and miRNAs binding. All of these mechanisms when altered can lead to dysregulation of gene expression, which can have an impact in AO and phenotypic variability. These putative mechanisms of regulation of gene expression within the TTR gene could be used in the future as potential therapeutical targets, and could improve genetic counselling and follow-up of mutation carriers.

Saccharomycotin transcriptomics by next-generation sequencing

The non-standard decoding of the CUG codon in Candida cylindracea raises a number of questions about the evolutionary process of this organism and other species Candida clade for which the codon is ambiguous. In order to find some answers we studied the transcriptome of C. cylindracea, comparing its behavior with that of Saccharomyces cerevisiae (standard decoder) and Candida albicans (ambiguous decoder). The transcriptome characterization was performed using RNA-seq. This approach has several advantages over microarrays and its application is booming. TopHat and Cufflinks were the software used to build the protocol that allowed for gene quantification. About 95% of the reads were mapped on the genome. 3693 genes were analyzed, of which 1338 had a non-standard start codon (TTG/CTG) and the percentage of expressed genes was 99.4%. Most genes have intermediate levels of expression, some have little or no expression and a minority is highly expressed. The distribution profile of the CUG between the three species is different, but it can be significantly associated to gene expression levels: genes with fewer CUGs are the most highly expressed. However, CUG content is not related to the conservation level: more and less conserved genes have, on average, an equal number of CUGs. The most conserved genes are the most expressed. The lipase genes corroborate the results obtained for most genes of C. cylindracea since they are very rich in CUGs and nothing conserved. The reduced amount of CUG codons that was observed in highly expressed genes may be due, possibly, to an insufficient number of tRNA genes to cope with more CUGs without compromising translational efficiency. From the enrichment analysis, it was confirmed that the most conserved genes are associated with basic functions such as translation, pathogenesis and metabolism. From this set, genes with more or less CUGs seem to have different functions. The key issues on the evolutionary phenomenon remain unclear. However, the results are consistent with previous observations and shows a variety of conclusions that in future analyzes should be taken into consideration, since it was the first time that such a study was conducted.

Mixing performance evaluation of additive manufactured milli-scale reactors

The mixing performance of three passive milli-scale reactors with different geometries was investigated at different Reynolds numbers. The effects of design and operating characteristics such as mixing channel shape and volume flow rate were investigated. The main objective of this work was to demonstrate a process design method that uses on Computational Fluid Dynamics (CFD) for modeling and Additive Manufacturing (AM) technology for manufacture. The reactors were designed and simulated using SolidWorks and Fluent 15.0 software, respectively. Manufacturing of the devices was performed with an EOS M-series AM system. Step response experiments with distilled Millipore water and sodium hydroxide solution provided time-dependent concentration profiles. Villermaux-Dushman reaction experiments were also conducted for additional verification of CFD results and for mixing efficiency evaluation of the different geometries. Time-dependent concentration data and reaction evaluation showed that the performance of the AM-manufactured reactors matched the CFD results reasonably well. The proposed design method allows the implementation of new and innovative solutions, especially in the process design phase, for industrial scale reactor technologies. In addition, rapid implementation is another advantage due to the virtual flow design and due to the fast manufacturing which uses the same geometric file formats.

Techniques for batch reinforcement learning in robotics

This thesis addresses the Batch Reinforcement Learning methods in Robotics. This sub-class of Reinforcement Learning has shown promising results and has been the focus of recent research. Three contributions are proposed that aim to extend the state-of-art methods allowing for a faster and more stable learning process, such as required for learning in Robotics. The Q-learning update-rule is widely applied, since it allows to learn without the presence of a model of the environment. However, this update-rule is transition-based and does not take advantage of the underlying episodic structure of collected batch of interactions. The Q-Batch update-rule is proposed in this thesis, to process experiencies along the trajectories collected in the interaction phase. This allows a faster propagation of obtained rewards and penalties, resulting in faster and more robust learning. Non-parametric function approximations are explored, such as Gaussian Processes. This type of approximators allows to encode prior knowledge about the latent function, in the form of kernels, providing a higher level of exibility and accuracy. The application of Gaussian Processes in Batch Reinforcement Learning presented a higher performance in learning tasks than other function approximations used in the literature. Lastly, in order to extract more information from the experiences collected by the agent, model-learning techniques are incorporated to learn the system dynamics. In this way, it is possible to augment the set of collected experiences with experiences generated through planning using the learned models. Experiments were carried out mainly in simulation, with some tests carried out in a physical robotic platform. The obtained results show that the proposed approaches are able to outperform the classical Fitted Q Iteration.

Thermodynamic efficiency of carbon capture and utilisation in anaerobic batch digestion process

Carbon capture and storage (CCS) in the oil and water industries is becoming common and a significant consumer of energy typically requiring 150–450 °C and or several hundred bar pressure [1] particularly in geological deposition. A biological carbon capture and conversion has been considered in conventional anaerobic digestion processes. The process has been utilised in biological mixed culture, where acetoclastic bacteria and hydrogenophilic methanogens play a major key role in the utilisation of carbon dioxide. However, the bio catalytic microorganisms, hydrogenophilic methanogens are reported to be unstable with acetoclastic bacteria. In this work the biochemical thermodynamic efficiency was investigated for the stabilisation of the microbial process in carbon capture and utilisation. The authors observed that a thermodynamic efficiency of biological carbon capture and utilisation (BCCU) had 32% of overall reduction in yield of carbon dioxide with complimentary increase of 30% in yield of methane, while the process was overall endothermic. Total consumption of energy (≈0.33 MJ l−1) was estimated for the carbonate solubility (0.1 mol l−1) in batched BCCU. This has a major influence on microbial composition in the bioreactor. This thermodynamic study is an essential tool to aid the understanding of the interactions between operating parameters and the mixed microbial culture.

Marine protist diversity in European coastal waters and sediments as revealed by high-throughput sequencing

Although protists are critical components of marine ecosystems, they are still poorly characterized. Here we analysed the taxonomic diversity of planktonic and benthic protist communities collected in six distant European coastal sites. Environmental deoxyribonucleic acid (DNA) and ribonucleic acid (RNA) from three size fractions (pico-, nano- and micro/mesoplankton), as well as from dissolved DNA and surface sediments were used as templates for tag pyrosequencing of the V4 region of the 18S ribosomal DNA. Beta-diversity analyses split the protist community structure into three main clusters: picoplankton-nanoplankton-dissolved DNA, micro/mesoplankton and sediments. Within each cluster, protist communities from the same site and time clustered together, while communities from the same site but different seasons were unrelated. Both DNA and RNA-based surveys provided similar relative abundances for most class-level taxonomic groups. Yet, particular groups were overrepresented in one of the two templates, such as marine alveolates (MALV)-I and MALV-II that were much more abundant in DNA surveys. Overall, the groups displaying the highest relative contribution were Dinophyceae, Diatomea, Ciliophora and Acantharia. Also, well represented were Mamiellophyceae, Cryptomonadales, marine alveolates and marine stramenopiles in the picoplankton, and Monadofilosa and basal Fungi in sediments. Our extensive and systematic sequencing of geographically separated sites provides the most comprehensive molecular description of coastal marine protist diversity to date.

Domestication and the storage starch biosynthesis pathway: Signatures of selection from a whole sorghum genome sequencing strategy

Next-generation sequencing of complete genomes has given researchers unprecedented levels of information to study the multifaceted evolutionary changes that have shaped elite plant germplasm. In conjunction with population genetic analytical techniques and detailed online databases, we can more accurately capture the effects of domestication on entire biological pathways of agronomic importance. In this study, we explore the genetic diversity and signatures of selection in all predicted gene models of the storage starch synthesis pathway of Sorghum bicolor, utilizing a diversity panel containing lines categorized as either ‘Landraces’ or ‘Wild and Weedy’ genotypes. Amongst a total of 114 genes involved in starch synthesis, 71 had at least a single signal of purifying selection and 62 a signal of balancing selection and others a mix of both. This included key genes such as STARCH PHOSPHORYLASE 2 (SbPHO2, under balancing selection), PULLULANASE (SbPUL, under balancing selection) and ADP-glucose pyrophosphorylases (SHRUNKEN2, SbSH2 under purifying selection). Effectively, many genes within the primary starch synthesis pathway had a clear reduction in nucleotide diversity between the Landraces and wild and weedy lines indicating that the ancestral effects of domestication are still clearly identifiable. There was evidence of the positional rate variation within the well-characterized primary starch synthesis pathway of sorghum, particularly in the Landraces, whereby low evolutionary rates upstream and high rates downstream in the metabolic pathway were expected. This observation did not extend to the wild and weedy lines or the minor starch synthesis pathways.

Optimisation de l'extraction, en réacteur "batch", de biomasse énergétique à l'aide d'émulsions ultrasoniques de solvants verts

L’industrie des biocarburants de deuxième génération utilise, entre autre, la biomasse lignocellulosique issue de résidus forestiers et agricoles et celle issue de cultures énergétiques. Le sorgho sucré [Sorghum bicolor (L.) Moench] fait partie de ces cultures énergétiques. L’intérêt croissant de l’industrie agroalimentaire et des biocarburants pour cette plante est dû à sa haute teneur en sucres (jusqu’à 60% en masse sèche). En plus de se développer rapidement (en 5-6 mois), le sorgho sucré a l’avantage de pouvoir croître sur des sols pauvres en nutriments et dans des conditions de faibles apports en eau, ce qui en fait une matière première intéressante pour l’industrie, notamment pour la production de bioéthanol. Le concept de bioraffinerie alliant la production de biocarburants à celle de bioénergies ou de bioproduits est de plus en plus étudié afin de valoriser la production des biocarburants. Dans le contexte d’une bioraffinerie exploitant la biomasse lignocellulosique, il est nécessaire de s’intéresser aux différents métabolites extractibles en plus des macromolécules permettant la fabrication de biocarburants et de biocommodités. Ceux-ci pouvant avoir une haute valeur ajoutée et intéresser l’industrie pharmaceutique ou cosmétique par exemple. Les techniques classiques pour extraire ces métabolites sont notamment l’extraction au Soxhlet et par macération ou percolation, qui sont longues et coûteuses en énergie. Ce projet s’intéresse donc à une méthode d’extraction des métabolites primaires et secondaires du sorgho sucré, moins coûteuse et plus courte, permettant de valoriser économiquement l’exploitation industrielle du de cette culture énergétique. Ce travail au sein de la CRIEC-B a porté spécifiquement sur l’utilisation d’une émulsion ultrasonique eau/carbonate de diméthyle permettant de diminuer les temps d’opération (passant à moins d’une heure au lieu de plusieurs heures) et les quantités de solvants mis en jeu dans le procédé d’extraction. Cette émulsion extractive permet ainsi de solubiliser à la fois les métabolites hydrophiles et ceux hydrophobes. De plus, l’impact environnemental est limité par l’utilisation de solvants respectueux de l’environnement (80 % d’eau et 20 % de carbonate de diméthyle). L’utilisation de deux systèmes d’extraction a été étudiée. L’un consiste en la recirculation de l’émulsion, en continu, au travers du lit de biomasse; le deuxième permet la mise en contact de la biomasse et des solvants avec la sonde à ultrasons, créant l’émulsion et favorisant la sonolyse de la biomasse. Ainsi, en réacteur « batch » avec recirculation de l’émulsion eau/DMC, à 370 mL.min[indice supérieur -1], au sein du lit de biomasse, l’extraction est de 37,91 % en 5 minutes, ce qui est supérieur à la méthode ASTM D1105-96 (34,01 % en 11h). De plus, en réacteur « batch – piston », où la biomasse est en contact direct avec les ultrasons et l’émulsion eau/DMC, les meilleurs rendements sont de 35,39 % en 17,5 minutes, avec 15 psig de pression et 70 % d’amplitude des ultrasons. Des tests effectués sur des particules de sorgho grossières ont donné des résultats similaires avec 30,23 % d’extraits en réacteur « batch » avec recirculation de l’émulsion (5 min, 370 mL.min[indice supérieur -1]) et 34,66 % avec le réacteur « batch-piston » (30 psig, 30 minutes, 95 % d’amplitude).

Domestication and the storage starch biosynthesis pathway: signatures of selection from a whole sorghum genome sequencing strategy

Next-generation sequencing of complete genomes has given researchers unprecedented levels of information to study the multifaceted evolutionary changes that have shaped elite plant germplasm. In conjunction with population genetic analytical techniques and detailed online databases, we can more accurately capture the effects of domestication on entire biological pathways of agronomic importance. In this study, we explore the genetic diversity and signatures of selection in all predicted gene models of the storage starch synthesis pathway of Sorghum bicolor, utilizing a diversity panel containing lines categorized as either ‘Landraces’ or ‘Wild and Weedy’ genotypes. Amongst a total of 114 genes involved in starch synthesis, 71 had at least a single signal of purifying selection and 62 a signal of balancing selection and others a mix of both. This included key genes such as STARCH PHOSPHORYLASE 2 (SbPHO2, under balancing selection), PULLULANASE (SbPUL, under balancing selection) and ADP-glucose pyrophosphorylases (SHRUNKEN2, SbSH2 under purifying selection). Effectively, many genes within the primary starch synthesis pathway had a clear reduction in nucleotide diversity between the Landraces and wild and weedy lines indicating that the ancestral effects of domestication are still clearly identifiable. There was evidence of the positional rate variation within the well-characterized primary starch synthesis pathway of sorghum, particularly in the Landraces, whereby low evolutionary rates upstream and high rates downstream in the metabolic pathway were expected. This observation did not extend to the wild and weedy lines or the minor starch synthesis pathways.

Ecology, physiology and performance in high-rate anaerobic digestion

The design demands on water and sanitation engineers are rapidly changing. The global population is set to rise from 7 billion to 10 billion by 2083. Urbanisation in developing regions is increasing at such a rate that a predicted 56% of the global population will live in an urban setting by 2025. Compounding these problems, the global water and energy crises are impacting the Global North and South alike. High-rate anaerobic digestion offers a low-cost, low-energy treatment alternative to the energy intensive aerobic technologies used today. Widespread implementation however is hindered by the lack of capacity to engineer high-rate anaerobic digestion for the treatment of complex wastes such as sewage. This thesis utilises the Expanded Granular Sludge Bed bioreactor (EGSB) as a model system in which to study the ecology, physiology and performance of high-rate anaerobic digestion of complex wastes. The impacts of a range of engineered parameters including reactor geometry, wastewater type, operating temperature and organic loading rate are systematically investigated using lab-scale EGSB bioreactors. Next generation sequencing of 16S amplicons is utilised as a means of monitoring microbial ecology. Microbial community physiology is monitored by means of specific methanogenic activity testing and a range of physical and chemical methods are applied to assess reactor performance. Finally, the limit state approach is trialled as a method for testing the EGSB and is proposed as a standard method for biotechnology testing enabling improved process control at full-scale. The arising data is assessed both qualitatively and quantitatively. Lab-scale reactor design is demonstrated to significantly influence the spatial distribution of the underlying ecology and community physiology in lab-scale reactors, a vital finding for both researchers and full-scale plant operators responsible for monitoring EGSB reactors. Recurrent trends in the data indicate that hydrogenotrophic methanogenesis dominates in high-rate anaerobic digestion at both full- and lab-scale when subject to engineered or operational stresses including low-temperature and variable feeding regimes. This is of relevance for those seeking to define new directions in fundamental understanding of syntrophic and competitive relations in methanogenic communities and also to design engineers in determining operating parameters for full-scale digesters. The adoption of the limit state approach enabled identification of biological indicators providing early warning of failure under high-solids loading, a vital insight for those currently working empirically towards the development of new biotechnologies at lab-scale.