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Biophysical Modeling of Cas9 Target-searching and Recognition
Full text linkOkinawa Institute of Science and Technology Graduate UniversityDoctor of PhilosophyIn this thesis, I model the 1D diffusion and unbinding of Cas9 on/from DNA. Cas9 plays a key role in the CRISPR/Cas (CRISPR-associated protein) system. CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats) are regions of a prokaryote DNA in which palindromic sequences are interspaced by sequences of foreign origins. These foreign sequences can be transcribed into guide RNAs. Cas9 is an enzyme that combines with guide RNA and afterwards can recognize and cleave DNA strands that are complementary to the guide RNA. However, it is not clear how does Cas9 identify its target. The protospacer adjacent motif (PAM) is a “NGG” segment on DNA. The recognition of PAM is the initial stage of the target searching mechanism. Experiments suggest that Cas9 uses 3D diffusion combined with 1D diffusion along the DNA, a mechanism termed facilitated diffusion. My model explains the distribution of binding events observed in experiments and predicts biophysically relevant parameters. I then analyze the behavior of Cas9 on a generic DNA with disordered assortment of PAMs by using an analogy with Anderson localization in condensed matter physics. I then propose a model of the off-target behavior (specificity) of Cas9. From the measured rates, I determine the energy landscapes of on-target and off-target DNA sequences, and the thermodynamic parameters in double strand DNA and DNA-RNA hybrids. Finally, from a perspective of two-mode target recognition strategy, I investigate the effect of PAM and its binding energy on the efficiency of Cas9 in the facilitated diffusion process
Self-similarity in a Boundary-layer Flow over a Dynamic Boundary: Flow of Air Induced by a Falling Soap Film
Full text linkOkinawa Institute of Science and Technology Graduate UniversityDoctor of PhilosophyA wide range of dynamical phenomena in nature are self-similar. This remarkable property entails that scaled versions of a phenomenon conform onto themselves. It not only affords simplified mathematical analysis but also reveals the physical underpinnings of the phenomenon. In fluid flows, a textbook example of such phenomena is the boundary-layer flow over a rigid boundary---the Blasius boundary layer flow. In this thesis, we experimentally and theoretically study self-similarity in boundary-layer flow over a dynamic boundary, wherein the flow and the boundary are dynamically coupled. Our experimental setup is a soap-film channel, which is essentially a soapy waterfall---a planar film of soap-water solution falling under gravity. This setup has long been used to study quasi-two-dimensional flows in a laboratory setting. Unlike previous experiments, however, where the focus is on the flow in the film, we train attention on what surrounds the film: air. The falling film drags the surrounding air, inducing flow in a thin layer of air adjacent to the film. This flowing air, in turn, resists the motion of the falling film; thus, the film-air interface is a dynamic boundary. We measure the velocity profile of the airflow in the boundary-layer of this interface using super-resolution Particle Image Velocimetry. (To our knowledge, these are the first experiments to measure airflow induced by a soap film.) The downstream evolution of the air velocity profile manifests self-similarity, which we analyze using the framework of boundary-layer theory. Surprisingly, we find that the conditions of self-similarity of the airflow also shed light on the downstream evolution of the film. Beyond air-film interaction, our findings may bear on a broader class of flows over dynamic boundaries, e.g. ocean-air interaction
Naphthyridines as Versatile Ligand Scaffolds For Metal-Metal Cooperative Bond Activation and Photocatalysis
Full text linkOkinawa Institute of Science and Technology Graduate UniversityDoctor of PhilosophyThis thesis covers the application of naphthyridine-based ligands as binucleating or mononucleating ligands scaffolds for application in selective bond activation and photocatalysis. The first chapter introduces the literature review on controlled design and synthesis of heterobi and multimetallic complexes in an unsymmetrical ligand scaffolds. In the next part, I will discuss the design of new polynucleating ligands based on unsymmetrical substituted naphthyridines that were utilized for site-selective construction of bimetallic Pt/Cu or multimetallic Pd/Cu complexes. These complexes were then utilized for selective bond activation or transmetalation via metal-metal cooperation. The fourth chapter introduces the literature review on high valent nickel complexes, along with the synthesis of mononuclear NiIII complexes supported by simple unsubstituted or Me-substituted naphthyridines via aerobic oxidation. These complexes were utilized in photocatalyzed C-H bond trifluoromethylation reactions. The final chapters introduces the reactivity of Ni perfluoroalkyl complexes featuring longer perfluoroalkyl chains in oxidation and ligand-free perfluoroalkylation of C-H bonds at room temperature
Identification and Functional Analysis of Group A bHLH Transcription Factor in Ctenophore Bolinopsis mikado
Full text linkOkinawa Institute of Science and Technology Graduate UniversityDoctor of Philosoph
Spectroscopic Visualization of Surface Electronic State in High Temperature Superconducting Oxide Thin Films
Full text linkOkinawa Institute of Science and Technology Graduate UniversityOkinawa Institute of Science and Technology Graduate UniversityThe study of strongly correlated electron systems is one of the central topics in condensed matter physics. The phenomena occurring in these systems are so complicated that the unifying theory is far from complete, but their applications, such as high-temperature superconductors (HTSCs), have become an integral part of everyday life. The study of strongly correlated systems therefore bridges the gap between fundamental physics and the application of cutting-edge technology. Angle-resolved photoemission spectroscopy (ARPES) has proven to be a powerful tool to study surface electronic states. Thus, we study the HTSCs- YBa2Cu3O7−x (YBCO) and the spinel superconductor LiTi2O4 (LTO) in thin őlms using ARPES. Despite their potential importance, the non-cleavable nature of both materials hinders the study of ARPES, and the electronic states on the surface have not yet been fully revealed. For YBCO, we show that the doping of Y with Ca in YBCO exhibits anomalous carrier doping associated with the appearance of a folded chain-derived band dispersion, implying the possibility of controlling the surface state. On the other hand, the LTO has demonstrated its potential as an intriguing platform for exploring novel exotic states with geometrically frustrated pyrochlore lattices. Thus, our results open a rich playground for the future development of HTSC heterointerfaces with atomic design
Stochastic Spatial Modeling of Vesicle Trafficking of AMPA Receptors to Understand Roles in Synaptic Plasticity
Full text linkOkinawa Institute of Science and Technology Graduate UniversityDoctor of PhilosophyThe regulation of AMPA-type glutamate receptors (AMPARs) in the synapse is central for maintaining the normal functioning of hippocampal synapses, and sustaining long-term storage of memories. Within post-synaptic neurons, an intracellular trafficking system of vesicles and endosomal structures exists that transports and delivers AMPARs to and from synapses. This trafficking system is believed to have an essential role in modulating synaptic plasticity. However, it remains challenging to directly observe these fine processes in intact neurons during synaptic plasticity. In this thesis, I present a computational model that considers stochastic-spatial properties and biochemical signaling pathways of the intracellular trafficking system of AMPARs. I use the model to study vesicular-endosomal processes involved in the trafficking of AMPARs during synaptic plasticity. Our model suggests (1) a time-delay in the contribution of endosomal-vesicle processes in enhancing synaptic strength, (2) an alternative source of AMPARs to endosomes is required to sustain increased synaptic strength, and (3) endosomes serve as storage sites to support multiple spines during synaptic plasticity
Metamaterial Plasmonic Tweezers for Enhanced Nanoparticle Trapping
Full text linkOkinawa Institute of Science and Technology Graduate UniversityDoctor of PhilosophyOptical tweezers have gained significant attention in many research fields as the only technique that provides immobilisation (trapping) and manipulation of micro- and nanoparticles. Moving from the conventional, free-space configuration to plasmonic structures using strong near-field forces, resulted in many more avenues towards the exploration of the nanoworld. However, with that, many challenges also appeared, as is usually the case when pushing the boundaries of the unknown. In this thesis, we focus on how to achieve an efficient trap for particles of just a few nanometres in size, such as colloidal quantum dots and gold nanoparticles. For this purpose, we investigate a novel metamaterial plasmonic design that exhibits a sharp plasmonic Fano resonance feature, which is very sensitive to refractive index changes of its environment. Three main projects are presented. In the first one, we work on the optimisation of the basic characteristics of the metamaterial, to ensure it has the desired plasmonic resonance and exhibits strong optical forces. We test its efficiency by trapping 20 nm polystyrene particles, yielding very high trap stiffness values. We also perform sequential trapping, revealing the ability of the structure for on-demand, particle nanopositioning. In the second project, we study the mechanism of self-induced back-action trapping. Under certain conditions, the particle can contribute to its own trap through an optomechanical coupling of its motion with the intracavity light intensity of the plasmonic nanocavity. For this experiment, gold nanoparticles were used and successfully trapped with extremely low laser intensities. Finally, the third project addresses the trapping of semiconductor quantum dots and custom-synthesised organic molecule nanoparticles that can be tuned to the desired size and emission wavelength ac-cording to the expected application. Photoluminescence measurements are also performed and an overall evaluation of the applicability and potential uses of these nanoparticles is discussed
Imaging Electronic States in the Charge Density Wave Material CeTe3
Full text linkOkinawa Institute of Science and Technology Graduate UniversityDoctor of PhilosophyThe study of condensed phases plays a crucial role in our understanding of physics. In particular, Charge Density Waves (CDWs) are an important phenomenon due to their close connection with a material's fermiology, in addition to their coexistence and competition with superconducting, magnetic, and other exotic phases. Rare earth tritellurides (RTe3) are a prototypical 2D material system which provide an excellent test platform for investigating these phases and the interplay between them. In this thesis, I will present the rst low temperature STM study of CeTe3, with the rst comprehensive discussion and simulation of quasiparticle interference (QPI) in any RTe3 compound. At 4.2 K, we conrm that CeTe3 shows the unidirectional CDW that is present at higher temperatures. We then use SX-ARPES to t an interacting tight binding model and demonstrate that the observed QPI can be interpreted with JDOS simulations based on this model band structure. We reveal the unexpected result that the QPI arises mainly from scattering between the original bands and their shadow band replicas, with backscattering being relatively suppressed. This pioneering study can be powerfully extended in the future to use QPI measurements to understand the interaction of the CDW state and other phases
The Role of Connectivity in Structuring Community Composition and Diversity at Hydrothermal Vents Across the Northwest Pacific
Full text linkOkinawa Institute of Science and Technology Graduate UniversityDoctor of PhilosophyConnectivity, or the movement of individuals among isolated habitat patches, promotes local and regional biodiversity, and its resilience to disturbances both natural and anthropogenic. Species associated with seafloor hydrothermal vent habitats are distinctly reliant on connectivity due to their spatial restriction to the point source of chemical energy from vent chimneys that fuels their chemosynthetic food web. Measuring connectivity among hydrothermal vents is particularly urgent in regions where mining of these ecosystems is imminent. Our understanding of connectivity is limited by the scarcity of observational data from these inaccessible deep-sea ecosystems. Modelling is a viable alternative to the study of connectivity, as the dispersal that facilitates connectivity is mostly dictated by predictable ocean currents, which can be reliably simulated. This thesis combines empirical observations of species’ distributions and environmental conditions at hydrothermal vents with
simulations of dispersal, to model connectivity among vent sites in the Northwest Pacific. First, I curate a regional dataset of hydrothermal vent species distributions to infer connectivity in the form of a species assemblage network (Chapter 1). I then simulate how the planktonic larvae of vent species disperse among the vent sites in this region using Lagrangian particle tracking methods within an Ocean General Circulation Model (Chapter2). Finally, I combine the among-site dispersal estimates with observations of local environmental parameters to create a simulated species assemblage network using a metacommunity model (Chapter 3). This metacommunity model accurately recreated the empirical observations from chapter 1 and gives crucial insight into the interacting effects of dispersal barriers and environmental niche on driving diversity and community composition patterns at hydrothermal vents. Furthermore, I used the combination of observed and simulated connectivity results to quantitatively evaluate the relative role each individual hydrothermal vent plays in maintaining connectivity and biodiversity in the region. Such an evaluation has critical and timely implications for proposed mining and the spatial management of hydrothermal vents in this region. Lastly, we demonstrate that hydrothermal vents are natural laboratories for the advancement of metacommunity theory and conservation ecology due to their characteristic isolation and discrete nature
Multi-Agent Reinforcement Learning for Distributed Solar-Battery Energy Systems
Full text linkOkinawa Institute of Science and Technology Graduate UniversityDoctor of PhilosophyEfficient utilization of renewable energy sources, such as solar energy, is crucial for achieving sustainable development goals. As solar energy production varies in time and space depending on weather conditions, how to combine it with distributed energy storage and exchange systems with intelligent control is an important research issue.
In this thesis, I explore the use of reinforcement learning (RL) for adaptive control of energy storage in local batteries and energy sharing through energy grids. I first test multiple RL algorithms for energy storage control of single houses. I then extend the Autonomous Power Interchange System (APIS) from SONY to combine it with reinforcement learning algorithms in each house. I consider different design decisions in applying RL: whether to use centralized or distributed control, at what level of detail actions should be learned, what information is used by each agent, and how much information is shared across agents. Based on these considerations, I implemented deep Q-network (DQN) and prioritized DQN to set the parameters of real-time energy exchange protocol of APIS and tested it using the actual data collected from OIST DC-based Open Energy System (DCOES). The simulation results showed that DQN agents outperform rule-based control on energy sharing and that prioritized experience replay further improves the performance of DQN. Simulation results also suggest that sharing average energy production, storage and usage within the community helps the performance. The results contribute to future designs of distributed intelligent agents and effective operations of energy grid systems