188 research outputs found
Evolutionary diversification of methanotrophic ANME-1 archaea and their expansive virome
No full textANME-1 archaea are important because of their ability to metabolize methane through anaerobic oxidation. Here the authors use metagenomics on hydrothermal samples from the Gulf of California to characterize a family of ANME-1 and its virome. 'Candidatus Methanophagales' (ANME-1) is an order-level clade of archaea responsible for anaerobic methane oxidation in deep-sea sediments. The diversity, ecology and evolution of ANME-1 remain poorly understood. In this study, we use metagenomics on deep-sea hydrothermal samples to expand ANME-1 diversity and uncover the effect of virus-host dynamics. Phylogenetic analyses reveal a deep-branching, thermophilic family, 'Candidatus Methanospirareceae', closely related to short-chain alkane oxidizers. Global phylogeny and near-complete genomes show that hydrogen metabolism within ANME-1 is an ancient trait that was vertically inherited but differentially lost during lineage diversification. Metagenomics also uncovered 16 undescribed virus families so far exclusively targeting ANME-1 archaea, showing unique structural and replicative signatures. The expansive ANME-1 virome contains a metabolic gene repertoire that can influence host ecology and evolution through virus-mediated gene displacement. Our results suggest an evolutionary continuum between anaerobic methane and short-chain alkane oxidizers and underscore the effects of viruses on the dynamics and evolution of methane-driven ecosystems
Metabolic marker gene mining provides insight in global mcrA diversity and, coupled with targeted genome reconstruction, sheds further light on metabolic potential of the Methanomassiliicoccales
No full textOver the past years, metagenomics has revolutionized our view of microbial diversity. Moreover, extracting near-complete genomes from metagenomes has led to the discovery of known metabolic traits in unsuspected lineages. Genome-resolved metagenomics relies on assembly of the sequencing reads and subsequent binning of assembled contigs, which might be hampered by strain heterogeneity or low abundance of a target organism. Here we present a complementary approach, metagenome marker gene mining, and use it to assess the global diversity of archaeal methane metabolism through the mcrA gene. To this end, we have screened 18,465 metagenomes for the presence of reads matching a database representative of all known mcrA proteins and reconstructed gene sequences from the matching reads. We use our mcrA dataset to assess the environmental distribution of the Methanomassiliicoccales and reconstruct and analyze a draft genome belonging to the ‘Lake Pavin cluster’, an uncultivated environmental clade of the Methanomassiliicoccales. Analysis of the ‘Lake Pavin cluster’ draft genome suggests that this organism has a more restricted capacity for hydrogenotrophic methylotrophic methanogenesis than previously studied Methanomassiliicoccales, with only genes for growth on methanol present. However, the presence of the soluble subunits of methyltetrahydromethanopterin:CoM methyltransferase (mtrAH) provide hypothetical pathways for methanol fermentation, and aceticlastic methanogenesis that await experimental verification. Thus, we show that marker gene mining can enhance the discovery power of metagenomics, by identifying novel lineages and aiding selection of targets for in-depth analyses. Marker gene mining is less sensitive to strain heterogeneity and has a lower abundance threshold than genome-resolved metagenomics, as it only requires short contigs and there is no binning step. Additionally, it is computationally cheaper than genome resolved metagenomics, since only a small subset of reads needs to be assembled. It is therefore a suitable approach to extract knowledge from the many publicly available sequencing projects
Metabolic marker gene mining provides insight in global mcrA diversity and, coupled with targeted genome reconstruction, sheds light on metabolic versatility of the<i>Methanomassiliicoccales</i>
No full textAbstractOver the past years, metagenomics has revolutionized our view of microbial diversity. Moreover, extracting near-complete genomes from metagenomes has led to the discovery of known metabolic traits in unsuspected lineages. Genome-resolved metagenomics relies on assembly of the sequencing reads and subsequent binning of assembled contigs, which might be hampered by strain heterogeneity or low abundance of a target organism. Here we present a complementary approach, metagenome marker gene mining, and use it to assess the global diversity of archaeal methane metabolism through the mcrA gene. To this end, we have screened 18,465 metagenomes for the presence of reads matching a database representative of all known mcrA proteins and reconstructed gene sequences from the matching reads. We use our mcrA dataset to assess the environmental distribution of theMethanomassiliicoccalesand reconstruct and analyze a draft genome belonging to the ‘Lake Pavin cluster’, an understudied environmental clade of theMethanomassiliicoccales. Thus, we show that marker gene mining can enhance the discovery power of metagenomics, by identifying novel lineages and aiding selection of targets for in-depth analyses. Marker gene mining is less sensitive to strain heterogeneity and has a lower abundance threshold than genome-resolved metagenomics, as it only requires short contigs and there is no binning step. Additionally, it is computationally cheaper than genome resolved metagenomics, since only a small subset of reads needs to be assembled. It is therefore a suitable approach to extract knowledge from the many publicly available sequencing projects.</jats:p
ASM-Clust: classifying functionally diverse protein families using alignment score matrices
No full textRapid advances in sequencing technology have resulted in the availability of genomes from organisms across the tree of life. Accurately interpreting the function of proteins in these genomes is a major challenge, as annotation transfer based on homology frequently results in misannotation and error propagation. This challenge is especially pressing for organisms whose genomes are directly obtained from environmental samples, as interpretation of their physiology and ecology is often based solely on the genome sequence. For complex protein (super)families containing a large number of sequences, classification can be used to determine whether annotation transfer is appropriate, or whether experimental evidence for function is lacking. Here we present a novel computational approach for de novo classification of large protein (super)families, based on clustering an alignment score matrix obtained by aligning all sequences in the family to a small subset of the data. We evaluate our approach on the enolase family in the Structure Function Linkage Database
Using YOLOv5 for the Detection of Icebergs in SAR Imagery
No full textThis research aims to analyse the sensitivity of the YOLOv5 object detection algorithm to current issues related to the tracking of icebergs in SAR imagery. To this end a sensitivity study was done on (1) the sensitivity of the algorithm to variations in input image resolution, (2) the sensitivity of the algorithm to variations in contrast between an iceberg and its surroundings and (3) the sensitivity of the algorithm to variations in icebergs size. The results show that the algorithm is very robust against variations in contrast between iceberg and surroundings, but is significantly sensitive to iceberg size. Furthermore, it seems that only by using high resolution images, the spatial features of icebergs can be well distinguished from features of other objects in the ocean. The YOLOv5 algorithm thus shows great potential for iceberg detection applications, but it should be explored if thecurrent sensitivity to size can be overcome if a more evenly distributed training dataset is used. On top of this, it should be noted that this research only serves as an exploratory analysis on the application of the algorithm and it should thus still be explored if our results based on augmented data, also apply on real data.Civil Engineerin
Miniaturization of a Water-Jet Drill for Microfracture Surgery
No full textAs part of a larger project called “Healing Water” this thesis project investigated aspects of minimally invasive water-jet drilling as a technology to be used in micro-fracture surgery. Drilling prototypes were developed and tested to gain a better understanding of the potential and the behaviour of high-pressure water jets in conjunction with minimally invasive devices. Specifically, this thesis focussed on the possible negative effects of inner diameter and curvature on drilling success. This thesis found that minimally invasive water jet drilling (in perspex, simulating bone) is possible. However, unwanted movement due to thrust reaction is a point of concern. Dealing with the thrust reaction as well as investigating real-world practicalities and limitations of the surgical procedure should be the focus of further R&D.Healing WaterBiomedical Engineerin
Combined Path Tracking and Stability Control using Model Predictive Control
No full textThis thesis presents a new MPC controller which integrates path tracking and stability control into one controller. Previously these tasks were done by separate controllers, where one controller handled the path tracking while another controller ensured the vehicle was kept in the stable operating region. A drawback of this method is that the controllers have opposing objectives. The path tracker could require a higher steering wheel angle to follow the path, while the Vehicle Stability Controller (VSC) might require a lower angle to keep the vehicle stable. By integrating these two controllers into one controller, the new controller is able to take both tasks into account and optimise the control output such that both objectives are satisfied. This is achieved by implementing two extra yaw rates into the MPC model. These are the expected yaw rates based on the steering wheel angle and lateral acceleration of the vehicle. By comparing these two yaw rates to the actual yaw rate, the stability of the vehicle can be determined. The MPC controller is then able to prioritise path tracking or vehicle stability. This is achieved by actively varying the weights in the cost function depending on the vehicle state. To compare the new MPC controller, 8 benchmark controllers have been created. These controllers can be divided into two groups of four controllers. The first group is able to use differential braking in the control output, while the second group can only output an equal brake torque for all wheels. The benchmark controllers use different methods for path tracking and stability control, to get an understanding of the performance benefits of each method.These different methods include: adding an extra target yaw rate based on path curvature and speed for tracking, adding constraints to ensure vehicle stability and using a separate stability controller to stabilise the vehicle. All controllers are evaluated using the industry standard Moose test as well as a double lane change in simulations. These manoeuvres are used in industry to evaluate stability and can also be used to evaluate path tracking. Furthermore the robustness of the controllers was evaluated by changing various parameters. These variations include: changing vehicle speed, adding extra weight to the vehicle, lowering the road 𝜇 level and performing a lane change where each lane has a different 𝜇 level. The results were evaluated using objective Key Performance Indicators regarding tracking performance and vehicle stability. The results show that the new MPC controller with the combined path tracking and stability control improves performance in both objectives. The new controller improves path tracking by 8% compared to the pure path tracking controller. While the stability is improved by 11% compared to the controller with a separate VSC. Furthermore the new controller was able to keep the vehicle stable at higher speeds and was more robust to varying conditions.Mechanical Engineering | Vehicle Engineerin
Metagenomic analysis of nitrogen and methane cycling in the Arabian Sea oxygen minimum zone
No full textOxygen minimum zones (OMZ) are areas in the global ocean where oxygen concentrations drop to below one percent. Low oxygen concentrations allow alternative respiration with nitrate and nitrite as electron acceptor to become prevalent in these areas, making them main contributors to oceanic nitrogen loss. The contribution of anammox and denitrification to nitrogen loss seems to vary in different OMZs. In the Arabian Sea, both processes were reported. Here, we performed a metagenomics study of the upper and core zone of the Arabian Sea OMZ, to provide a comprehensive overview of the genetic potential for nitrogen and methane cycling. We propose that aerobic ammonium oxidation is carried out by a diverse community of Thaumarchaeota in the upper zone of the OMZ, whereas a low diversity of Scalindua-like anammox bacteria contribute significantly to nitrogen loss in the core zone. Aerobic nitrite oxidation in the OMZ seems to be performed by Nitrospina spp. and a novel lineage of nitrite oxidizing organisms that is present in roughly equal abundance as Nitrospina. Dissimilatory nitrate reduction to ammonia (DNRA) can be carried out by yet unknown microorganisms harbouring a divergent nrfA gene. The metagenomes do not provide conclusive evidence for active methane cycling; however, a low abundance of novel alkane monooxygenase diversity was detected. Taken together, our approach confirmed the genomic potential for an active nitrogen cycle in the Arabian Sea and allowed detection of hitherto overlooked lineages of carbon and nitrogen cycle bacteria
Decreasing message complexity in Byzantine Fault Tolerant communications using Consistent-Broadcast
No full textDuring this research we have replaced Bracha’s layer in the state-of-the-art Bracha-Dolev protocol to improve the performance by decreasing the message complexity of the protocol running on top of a given network topology so long as the requirements stated by Bracha and Dolev are met. Bracha-Dolev is an algorithm that is used to establish a Byzantine fault tolerant communication in a network but it requires a lot of messages to reach consensus. This improvement has been achieved by utilizing a Byzantine Consistent Broadcast algorithm in place of Bracha’s layer: Authenticated Echo Broadcast in order to reduce the message complexity and reduce the network consumption compared to the original optimized Bracha-Dolev algorithm.Some of the optimizations applied to optimized Bracha-Dolev have also been applied to this new protocol under the hard assumption that the sender is always reliable. As a result, this new protocol is an optimal choice in such instances where these constraints hold and where multiple faulty nodes are present in the system.CSE3000 Research ProjectComputer Science and Engineerin
Durability of stiffened CFRP panels with initial delaminations
No full textA numerical fatigue delamination model is validated by means of experimental tests. Delamination is initiated on the skin-stiffener interface which, under cyclic compressive loading and in the post-buckling regime, grows at a decreasing rate. A cohesive zone formulation is used to model the static and fatigue delamination growth, good agreement is found in terms of delamination shape. Further investigation is required, using improved material inputs, for the model to be validated in terms of delamination magnitude. The numerical model shows promising characteristics, which may be employed for future damage tolerant composite structural designs.INOVAAerospace Engineerin
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