京都大学 / 新制・課程博士 / 博士(工学) / 甲第23199号 / 工博第4843号 / 新制||工||1756(附属図書館) / 京都大学大学院工学研究科材料工学専攻 / (主査)教授 邑瀬 邦明, 教授 宇田 哲也, 教授 作花 哲夫 / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DFAM

Indiana University-Purdue University Indianapolis (IUPUI) / Non-coding RNAs across the genome have been associated with various biological processes, ranging from regulation of splicing to remodeling of chromatin. Amongst the repertoire of non-coding sequences lies a critical species of RNAs called long non-coding RNAs (lncRNAs). LncRNAs significantly contribute to a large spectrum of human phenotypes, including cancers, Heart failure, Diabetes, and Alzheimer’s disease. This dissertation emphasizes the need to characterize the functional role of lncRNAs to improve our understanding of human diseases. This work consolidates a resource from multiple computational genomics and natural language processing-based approaches to advance our ability to functionally annotate hundreds of lncRNAs and their interactions, providing a one-stop lncRNA functional annotation and dynamic interaction network and multi-facet omics data visualization platform. RNA interactions are vital in various cellular processes, from transcription to RNA processing. These interactions dictate the functional scope of the RNA. However, the multifaceted functional nature of RNA stems from its ability to form secondary structures. Therefore, this work establishes a computational method to characterize RNA secondary structure by integrating SHAPE-seq and long-read sequencing to enhance further our understanding of RNA structure in modulating the post-transcriptional regulatory processes and deciphering the influence at several layers of biological features, ranging from structure composition to consequent protein occupancy. This study will potentially impact the research community by providing methods, web interfaces, and computational pipelines, improving our functional understanding of long non-coding RNAs. This work also provides novel integration methods of technologies like Oxford Nanopore-based long-read sequencing, RNA structure-probing methods, and machine learning. The approaches developed in this dissertation are scalable and adaptable to investigate further the functional and regulatory role of RNA and its structure. Overall, this study accelerates the development of RNA-based diagnostics and the identification of therapeutic targets in human disease.

京都大学 / 新制・課程博士 / 博士(理学) / 甲第24125号 / 理博第4853号 / 新制||理||1694(附属図書館) / 京都大学大学院理学研究科化学専攻 / (主査)准教授 板東 俊和, 教授 深井 周也, 教授 秋山 芳展 / 学位規則第4条第1項該当 / Doctor of Science / Kyoto University / DGAM

Solid-state nanopores are a versatile class single-molecule sensors to electrically characterize a range of biological molecules. Nanopores operate on the simple premise that when a voltage is applied across a pore immersed in a salt solution, the passage of a biomolecule results in a transient blockage in the ionic current that provide information about the translocating molecule. This thesis presents studies employing various DNA nanostructures with solid-state nanopore electrical readout for the development of high sensitivity digital single-molecule assays to detect low-abundance biomarkers. Toward this ultimate goal, work presented in this thesis use nanopores to probe DNA nanostructures, their assembly, mechanical properties, and monitor their dynamics with time and temperature. DNA nanostructures are self-assembled via specific base pairing of DNA, their programmability make them particularly useful for applications including drug delivery, molecular computation and biosensing. Here, I first show results of translocation profiles and discuss folding characteristics, mobility, and molecular configuration during passage for different DNA nanostructures such as the short star-shaped DNA nanostructures and large helix-bundle DNA origami structures under various experimental conditions in an effort to understand the passage characteristics through nanopores of these structures before using them in biological assays. I conclude by presenting a magnetic bead-based immunoassay scheme using a digital solid-state nanopore readout. Nanopore has the ability to count molecules one at a time, this allows accurate and precise determination of the concentration of a biomarker in solution. Coupled with the use of specific choice of DNA nanostructures, as proxy labels for proteins of interest, I establish that nanopores sensors can reliably quantify the concentration of a protein biomarker from complex biofluids and overcome the traditional challenges associated with nanopore-based protein sensing, such as specificity, sensitivity, and consistency. I demonstrate the quantification of thyroid stimulating hormone (TSH) with a high degree of precision down to the femtomolar range by using a nanoparticle-based signal amplification strategy. The proposed assay scheme is generalizable to a framework for the detection and quantification of a wide range of target proteins, and given that its performance can further be improved with the use of parallelization, preconcentration, or miniaturization, it opens up exciting opportunities for the development of ultra-sensitive digital assay in a format that is compatible for point-of-care.

京都大学 / 新制・課程博士 / 博士(医学) / 甲第24783号 / 医博第4975号 / 新制||医||1066(附属図書館) / 京都大学大学院医学研究科医学専攻 / (主査)教授 村川 泰裕, 教授 波多野 悦朗, 教授 小川 誠司 / 学位規則第4条第1項該当 / Doctor of Medical Science / Kyoto University / DFAM

No description available.

We investigated four different problems using coarse grained computational models : self-assembly of single stranded (ss) DNA virus, ejection dynamics of double stranded(ds) DNA from phages, translocation of ssDNA through MspA protein pore, and segmental dynamics of a polymer translocating through a synthetic nanopore. In the first part of the project, we investigated the self-assembly of a virus with and without its genome. A coarse-grained model was proposed for the viral subunit proteins and its genome (ssDNA). Langevin dynamics simulation, and replica exchange method were used to determine the kinetics and energetics of the self-assembly process, respectively. The self-assembly follows a nucleation-growth kind of mechanism. The ssDNA plays a crucial role in the self-assembly by acting as a template and enhancing the local concentration of the subunits. The presence of the genome does not changes the mechanism of the self-assembly but it reduces the nucleation time and enhances the growth rate by almost an order of magnitude. The second part of the project involves the investigation of the dynamics of the ejection of dsDNA from phages. A coarse-grained model was used for the phage and dsDNA. Langevin dynamics simulation was used to investigate the kinetics of the ejection. The ejection is a stochastic process and a slow intermediate rate kinetics was observed for most ejection trajectories. We discovered that the jamming of the DNA at the pore mouth at high packing fraction and for a disordered system is the reason for the intermediate slow kinetics. The third part of the project involves translocation of ssDNA through MspA protein pore. MspA protein pore has the potential for genome sequencing because of its ability to clearly distinguish the four different nucleotides based on their blockade current, but it is a challenge to use this pore for any practical application because of the very fast traslocation time. We resolved the state of DNA translocation reported in the recent experimental work . We also investigated two methods for slowing down the translocation process: pore mutation and use of alternating voltage. Langevin dynamics simulation and Poisson Nernst Planck solver were used for the investigation. We demonstrated that mutation of the protein pore or applying alternating voltage is not a perfect solution for increasing translocation time deterministically. Both strategies resulted in enhanced average translocation time as well as the width of the translocation time distribution. The increase in the width of the translocation time distribution is undesired. In the last part of the project, we investigated the applicability of the polyelectrolyte theory in the computer simulation of polyelectrolyte translocation through nanopores. We determined that the Debye Huckel approximation is acceptable for most translocation simulations as long as the coarse grained polymer bead size is comparable or larger than the Debye length. We also determined that the equilibrium translocation theory is applicable to the polyelectrolyte translocation through a nanopore under biasing condition. The unbiased translocation behavior of a polyelectrolyte chain is qualitatively different from the Rouse model predictions, except for the case where the polyelectrolyte is very small compared to the nanopore. .

Atriplex hortensis (2n = 2x = 18, 1C genome size ~1.1 gigabases), also known as garden orach, is a highly nutritious, broadleaf annual of the Amaranthaceae-Chenopodiaceae family that has spread from its native Eurasia to other temperate and subtropical environments worldwide. Atriplex is a highly complex and polyphyletic genus of generally halophytic and/or xerophytic plants, some of which have been used as food sources for humans and animals alike. Although there is some literature describing the taxonomy and ecology of orach, there is a lack of genetic and genomic data that would otherwise help elucidate the genetic variation, phylogenetic position, and future potential of this species. Here, we report the assembly of the first highquality, chromosome-scale reference genome for orach cv. ‘Golden’. Sequence data was produced using Oxford Nanopore’s MinION sequencing technology in conjunction with Illumina short-reads and chromatin-contact mapping. Genome assembly was accomplished using the high-noise, single-molecule sequencing assembler, Canu. The genome is enriched for highly repetitive DNA (68%). The Canu assembly combined with the Hi-C chromatin-proximity data yielded a final assembly containing 1,325 scaffolds with a contig N50 of 98.9 Mb and with 94.7% of the assembly represented in the nine largest, chromosome-scale scaffolds. Sixty-eight percent of the genome was classified as highly repetitive DNA, with the most common repetitive elements being Gypsy and Copia-like LTRs. The annotation was completed using MAKER which identified 31,010 gene models and 2,555 tRNA genes. Completeness of the genome was assessed using the Benchmarking Universal Single Copy Orthologs (BUSCO) platform, which quantifies functional gene content using a large core set of highly conserved orthologous genes (COGs). Of the 1,375 plant-specific COGs in the Embryophyta database, 1,330 (96.7%) were identified in the Atriplex assembly. We also report the results of a resequencing panel consisting of 21 accessions which illustrates a high degree of genetic similarity among cultivars and wild material from various locations in North America and Europe. These genome resources provide vital information to better understand orach and facilitate future study and comparison.

[pt] Esta tese trata do movimento de nanopartículas através de nanoporos – translocação – e como esse fenômeno pode ser utilizado como ferramenta de caracterização. Nanopartículas, não apenas ocorrem amplamente na natureza, mas também têm sido extensivamente aprimoradas em pesquisas acadêmicas e em desenvolvimento industrial. Devido às suas propriedades únicas, nanopartículas são utilizadas em diversas aplicações industriais. Ferramentas de caracterização que são acessíveis, fáceis de usar e robustas são fundamentais para pesquisa e controle de qualidade na ciência e tecnologia de nanopartículas. Raramente todas essas características desejáveis são encontradas em uma única ferramenta de caracterização. Por exemplo, o Espalhamento Dinâmico de Luz é uma técnica conhecida por ser de fácil execução, mas mede o tamanho de muitas partículas ao mesmo tempo, sendo propensa a erros em distribuições dispersas e mistas. Por outro lado, a visualização direta das partículas por Microscopia Eletrônica de Transmissão fornece informações precisas sobre o tamanho das partículas, mas é difícil de se realizar em larga escala e é propensa a viés de amostragem. O Sensoriamento via Nanoporos pode, no entanto, medir propriedades físicas em cada partícula individualmente e em alta escala. Experiências foram bem-sucedidas na caracterização da concentração, tamanho e carga elétrica de nanopartículas. No entanto, os resultados experimentais nem sempre são facilmente interpretáveis. Ferramentas de modelagem e simulação são usadas para esclarecer as relações complexas provenientes do ambiente em nanoescala. Apesar do grande desenvolvimento nesta área, simulações dependentes de trajetória que possam efetivamente reproduzir os pulsos da translocação ainda são escassas. Aqui, o formalismo de Poisson-NernstPlanck foi combinado com aprendizagem de máquina e Monte-Carlo Dinâmico para formar uma ferramenta de simulação que captura o movimento de difusão e eletroforese, obtendo os pulsos de corrente correspondentes a essas trajetórias. Esferas e hastes foram simuladas translocando poros de diferentes dimensões. As simulações sugerem limitações inerentes na resolução devido ao efeito Browniano. Enquanto estudos anteriores conseguiram simular apenas algumas trajetórias ou estimar estatísticas usando argumentos teóricos, neste estudo foram calculadas centenas de trajetórias, calculando estatísticas diretamente da população de resultados. A estrutura desenvolvida nesta pesquisa pode ser expandida para investigar outros sistemas, auxiliando no desenvolvimento do sensoriamento via nanoporos. / [en] This dissertation focuses on the transport of nanoparticles through nanopores - nanoparticle translocation - and how this phenomenon can be used as a characterization tool known as nanopore sensing. Nanoparticles not only occur widely in nature but also have been extensively engineered in academic research and industrial development. Due to their unique properties, nanoparticles are used in several industrial applications. Characterization tools that are accessible, easy to use, and robust are key for both research and quality control in nanoparticle science and technology. Rarely all these desirable characteristics are encountered in a single characterization tool. For example, Dynamic Light Scattering (DLS) is known to provide easy measurements of nanoparticle size but is prone to errors when analyzing dispersed and mixed distributions. On the other hand, direct visualization of the particles by Transmission Electron Microscopy (TEM) provides accurate information on particle size but is difficult to perform with high throughput and is prone to sampling bias. Nanopore sensing can, however, measure physical properties both at a single particle level and with high throughput. Experiments were successful in characterizing particle concentration, size, and charge. However, the experimental results are not always readily interpretable. In response, modeling and simulation tools are used to shed light on the complex relationships coming from the nanoscale environment. Despite the great amount of development in this area, there is still a lack of trajectorydependent simulations that can effectively reproduce the pulses from the translocation of a freely interacting particle. Here, Poisson-Nernst-Planck formalism was combined with Machine Learning and Dynamic Monte-Carlo to form a simulation tool that captures the drift-diffusion motion of hard particles and the current pulses corresponding to these trajectories. Spheres and rods were simulated translocating pores of different dimensions. The simulations suggest inherent limitations in resolution due to the Brownian effect. Whereas previous studies were able to simulate only a few trajectories or estimated the statistics of the features using theoretical arguments, in this study hundreds of trajectories were simulated, calculating statistics directly from the population of results. The framework developed in this research can be expanded to investigate other nanopore systems, helping the development of nanopore sensing.

For over thirty years, Porcine Reproductive and Respiratory Syndrome Virus (PRRSV) has been a major contributor to morbidity and mortality in the commercial swine industry across the globe. This highly mutagenic RNA virus causes significant economic losses wherever it is prevalent, leading to $664 million in annual losses in the United States. Unfortunately, the current prevention and diagnostic techniques available have proven to be insufficient in controlling the spread of this disease. We describe an alternative diagnostic method exploiting the rapid turnaround time and long-read capacity of Oxford Nanopore Technology's MinION next-generation sequencer. We have developed a novel primer set designed to span Open Reading Frames 3 through 7 of the PRRSV genome, which has allowed for multiplexing of samples, thus reducing individual cost of testing, while yielding significantly more information than previously available. This novel primer pair and sequencing technique have distinguished mixed infections within individual animals and may be used to determine vaccination status. This new approach will help producers and veterinarians make better-informed decisions about co-mingling of animals and vaccination strategies, thus reducing the emergence of new, pathogenic strains of PRRSV. / Master of Science / Porcine reproductive and respiratory syndrome virus (PRRSV) is a common, economically important pathogen in commercial swine production. The virus was first identified in the late 1980's during outbreaks in the United States and Europe. In female pigs, the disease is characterized by abortion storms, and the delivery of mummified fetuses or very weak, ill piglets. Neonates often display signs of pneumonia, respiratory distress, and many die from hypoxia. Surviving piglets are highly susceptible to other diseases and are poor growers compared to other, unaffected piglets. Boars may show signs of respiratory disease and can also have decreased libido and reproductive success for months at a time. The virus is prone to mutating once a pig is infected, preventing herds from mounting sufficient immunity to protect against new, mutant strains. Identifying infected pigs early and accurately is crucial to managing PRRSV outbreaks. Currently available diagnostic tests for PRRSV have many limitations, thus we have developed a new diagnostic test using next-generation sequencing technology. Oxford Nanopore Technology provides a commercially available nanopore sequencer, the MinION, that can read long DNA strands in real-time. With this technology we have expanded the area of the PRRSV genome that can be sequenced, which allows us to better identify and distinguish strains of PRRSV in infected, and vaccinated pigs. This new testing method will allow veterinarians and practitioners across the country to better identify and predict outbreaks in their herds, helping them develop better management strategies against PRRSV.