The actin cytoskeleton plays a vital role in various biological processes such as cell migration, morphogenesis, and intracellular trafficking. The polymerization of actin filaments at membranes provides the force for generating dynamic actin structures such as protrusions and invaginations that drive these processes. In filopodia, which are finger-like protrusions comprised of bundled actin filaments, actin regulatory proteins are believed to assemble a distal 'tip complex' which stimulates actin nucleation at the membrane. However how these regulators collectively behave in a macromolecular complex still remains poorly understood. To understand the macromolecular nature of these complexes, I investigated the dynamic properties and spatial organization of actin regulatory factors, using an in vitro reconstitution assay for filopodia-like structures (FLS) utilizing artificial lipid bilayers and Xenopus laevis egg extracts. FRAP analysis of seven actin regulatory factors (Toca-1, N-WASP, GTPase-binding domain, Ena, VASP, Diaph3, Fascin) revealed that the FLS tip complex has both dynamic and stable properties, with different proteins displaying distinct dynamics. Further analyses on the membrane-binding protein Toca-1 showed that its dynamic turnover is controlled by interactions with actin and exchange of molecules with solution. Single-molecule localization microscopy resolved the nanoscale organization of Toca-1, showing its arrangement into flat plaque-like and narrowly elevated tubular substructures. Plaque-like structures showed similarities to phase-transition patterns, while tubule-like structures closely resembled those previously found to decorate membrane tubules in vitro, which are thought to be involved in endocytic membrane remodeling. Endocytic accessory proteins such as SNX9 and Dynamin2 were also found to localize to FLS tips. This work provides new insights into the dynamics and organization of protein ensembles at actin nucleation sites, and proposes a novel link between endocytosis and filopodia formation, which is relevant to understanding how cells decide when and where to assemble actin at the membrane.

Synapses are the communication junctions of the nervous system and contain protein machinery necessary for cognitive functions such as learning and memory. Postsynaptic density protein-95 (PSD-95) is a key scaffolding molecule at the PSD of synapses, yet its sub-synaptic organisation in the mammalian brain remains poorly understood. This thesis presents the use of genetically labelled PSD-95 with super-resolution imaging to resolve its nano-architecture in the mouse brain. To visualize PSD-95, two knock-in mouse lines were generated where the fluorescent proteins eGFP or mEos2 was fused to the carboxyl terminus of the endogenous PSD- 95 protein (PSD-95-eGFP or PSD-95-mEos2). Methods were developed by which fixed tissue sections of PSD-95-eGFP mice were examined using gated-stimulated emission depletion (g-STED) microscopy and PSD-95-mEos2 sections were examined with photoactivatable localisation microscopy (PALM) and quantitative image analysis was developed for both methods. From these platforms it was demonstrated that PSD-95 has a two tiered organisation: it is assembled into nanoclusters (NCs) approximately 140 nm diameter, which form part of the greater envelope of the PSD within synapses. Synapse subtypes were observed as characterised by the number of NCs per PSD. Using double colour g- STED microscopy. It was then asked whether PSD-95 nano-architecture remained the same across different sub-regions of the brain. A survey of PSD-95 was performed from seven different sub-regions of the hippocampus, quantifying ~110,000 NCs within ~70,000 PSDs from across the two super-resolution platforms. It was found that synapses displayed structural diversity both within and between different brain subregions as a function of the number of NCs per PSD. PSD-95 NCs were structurally conserved across the hippocampus, but showed molecular diversity in the abundance of PSD-95 molecules within. The findings of this thesis are: 1) genetic labelling of endogenous proteins combined with super-resolution microscopy is a powerful tool to study synaptic protein organisation in tissue. 2) Synaptic structural diversity in the brain is underlined by the number of PSD-95 NC units per synapse 3) PSD-95 NCs are structurally conserved but molecularly diverse synaptic units of synapses throughout the brain. These findings suggest that cognitive processing at the synapse is based upon a conserved, fundamental, molecular architecture.

In recent years, microlenses (ML), which are micro-scale spheres, have been used to overcome physical diffraction limit of optical microscopy (~200 nm). Although the use of such ML has provided highly resolved images of objects beyond the Abbe optical diffraction limit, the process needs to be refined before it can be applied widespread in materials, biological and clinical research. In this research work, we have implemented experiments on super-resolution imaging utilizing MLs of different refractive indices (n) and diameters to provide the scientific and engineering communities with practical guidelines for obtaining high resolution images with ease. With the support from experimental imaging data as well as FDTD simulations, we have shown that optimal super-resolution imaging with microspheres was accomplished under specific parameter range. We have identified ML with n=1.51 as a preferable choice over those MLs with n=1.4, 1.93, and 2.2, because of high reliability and high magnification for ML with n=1.51. With n=1.51 in mind, we have identified a diameter range from 15 μm to 50 μm provides high resolution and magnification for practical purposes. We show that other ML diameters provided high resolution as well; we believe that ML diameters between 15 μm and 50 μm are practically preferred. We were able to achieve <150 nm resolution and further refinement of this tool can potentially yield higher quality imaging results. Ideally, MLs will eventually be directly incorporated as a modular device in an optical microscope providing the researchers an effective, noninvasive, and economical alternative to complex super resolution microscopy techniques. To improve scanning efficiency, we also proposed microtubule (MT) based imaging. With the demonstration of theoretical optics, we conclude, at present time, that there are some practical concerns for MT-based imaging technique that may limit its application as super-resolution imaging technique. For example, MT-based imaging appears to possess a lower contrast than ML-based technique. Thus, although the concept of MT-based imaging is theoretically possible, we think that more work is needed to utilization of this tool for practical applications.

The development of single-molecule and super-resolution fluorescence techniques has revolutionised biological imaging. Nano-scale cellular structures and heterogeneous dynamic processes are now able to be visualised with unprecedented resolution in both time and space. The achievable localisation precision and therefore the resolution is fundamentally limited by the number of photons a single-fluorophore can emit. The ideal super-resolution dye would emit a large number of photons over a short period of time. On the contrary, an optimal single-molecule tracking probe would be highly photostable and undergo no transient dark-state transitions. Single-molecule instrument development is beginning to reach technological saturation and as the frontiers of bioimaging expand, exorbitant demands are placed on the gamut of available probes that often cannot be met. Thus, the next key challenge in the field is the development of the better fluorophores that underlie these techniques; this includes both the synthesis of new chemical derivatives and alternative novel strategies to augment existing technologies. The results of this thesis are divided into two distinct parts; Project One details the development of new synthetic fluorescent probes for the study of amyloid protein aggregates implicated in neurodegenerative diseases. This includes a study of the photophysical and binding properties of a novel fluorophore library based on the amyloid dye Thioflavin-T. Following on from this, is the presentation of novel bifunctional dyes capable of simultaneously identifying hydrogen peroxide and amyloid aggregates by combining existing tools for the independent detection of these species. The sensing capabilities of these dyes are explored at the bulk and single-molecule levels. Project Two describes a new photo-modulatable fluorescent-protein fusion construct that can undergo Förster resonance energy transfer (FRET) to an organic dye molecule. This FRET cassette is comprised of a photoconvertible fluorescent protein donor, mEos3.2 and acceptor fluorophore, JF646. This strategy imparts a strong photostabilising effect on the fluorescent protein and a resistance to photobleaching. The functionality of this approach is demonstrated with in vitro single-molecule fluorescence studies and its biological applicability shown by tracking single proteins in the nuclei of live embryonic stem cells. Furthermore, initial characterisations of the excited state dynamics in effect are presented through the systematic modification of parameters.

Human Natural Killer (NK) cells are regulated by a variety of germ-line encoded activating and inhibitory receptors. Broadly, activating receptors detect ligands that are expressed or up-regulated on cancerous or infected cells, while inhibitory receptors bind self-molecules to induce tolerance against healthy cells. Highly homologous pairs of activating and inhibitory receptors are also expressed on NK cells, including Killer Ig-like Receptors KIR2DL1 and KIR2DS1, which bind the same ligands, class I MHC proteins from the C2 group. Here, two super-resolution microscopy techniques, stimulated emission depletion (STED) and ground state depletion microscopy followed by individual molecule return (GSDIM) were used to examine the nanometre-scale organization of KIR2DL1 and KIR2DS1, as well as molecules engaged in their signalling. Both receptors were observed to constitutively assemble in nanometre-scale clusters at the surface of NK cells but displayed differential patterns of clustering - the activating receptor KIR2DS1 formed nanoclusters 2.3-fold larger than its inhibitory counterpart KIR2DL1. Site-directed mutagenesis established that the size of nanoclusters was controlled by transmembrane amino-acid 233, a lysine in KIR2DS1. Mutated variant of KIR2DS1 in which lysine 233 was substituted with alanine formed significantly smaller clusters than the wild-type KIR2DS1. Reciprocally, substitution of isoleucine found at position 233 in KIR2DL1 sequence with lysine resulted in the receptor assembling into larger clusters. Super-resolution microscopy also revealed two ways in which KIR nanoclusters impact signalling. First, KIR2DS1 and DAP12 nanoclusters were juxtaposed in the resting-cell state but coalesced upon receptor ligation. Second, quantitative super-resolution microscopy revealed that membrane-proximal clusters of the kinase ZAP-70 or phosphatase SHP-1, as well as their phosphorylated active forms, were more often found in contact with larger KIR nanoclusters. Together, this work has established that size of KIR nanoclusters depends on the transmembrane sequence and impacts downstream signalling.

In this thesis, we discuss several phenomena exhibiting `limiting behaviour' in physics. This includes the duality principle, delegated quantum computation, and super-resolution. The duality principle places a limit on the coexistence of wave and particle behaviours. We develop a framework that explains apparent violations of this principle while staying within the scope of quantum mechanics. In addition, we relate the duality principle to the sub-fidelity and weak-values. We also show that the maximum recoverable coherence of a qubit has a sharp transition from 0 to 1 when we have access to half of the environment to which the qubit is correlated. Delegated quantum computation consists of a computational weak client who wishes to delegate a complex quantum computation to a powerful quantum server. We develop a new protocol for delegated quantum computation requiring less quantum power than its predecessor. Finally, we develop and test a new theory for eigenmode super-resolution.

The diffraction limit restricts conventional light microscopes to approximately 250 nm laterally and 500 nm axially, these limits being first proposed by Abbe in 1873. Despite this, optical microscopes have found many applications in biological research and single cells that are 10 - 100 um in size. Furthermore by coupling the non-invasive nature of a light microscope with highly sensitive fluorescent probes, fluorescence microscopy has also become a standard imaging technique. Recent advances in fluorescence microscopy now provide a number of methods to circumvent the Abbe diffraction limit, with many techniques becoming prevalent over the last 10 years including direct Stochastic Optical Reconstruction Microscopy (dSTORM). A dSTORM system has been constructed and calibrated using a commercially available inverted florescence microscope and total internal reflection florescence (TIRF) imaging. dSTORM relies on the ability to switch sparse subsets of fluorophores and temporally separate them. Provided the spatial separation is sufficient between any member of a subset, the average error with which the emission can be localized is much less than size of the emission profile itself. The underlying mechanism for this switching is detailed based on the principle of photoinduced electron transfer (PET). The switching characteristics of the common florescent dye Alexa Fluor 568 are investigated and shown to be controlled by a number of factors including the excitation intensity and concentration of the primary thiol cysteamine beta-MEA. A number of parameters are defined, including the dye switching rate, for a given set of physical parameters. U2OS cells are labelled for the microtubule protein Tubulin using immunofluorescent labelling strategies. A direct comparison is made between diffraction limited TIRF images and dSTORM reconstructed images, with an average width for microtubules determined to (58.2 ± 8.1) nm. Further measurements are made by labelling the Rab5 effector Early Endosome Antigen 1 (EEA1). From this the aspect ratio for early endosomes is determined to be 1.68 ± 0.7 with an average radius of (45.8 ± 18.8) nm. The point spatial distribution of EEA1 is investigated by using the linearised form of Ripley's K-function H(r) and the null hypothesis of complete spatial randomness tested. EEA1 is shown to cluster at radius of 58.7 nm on individual endosomes, thought to be due to the well defined binding domains present on early endosomes for EEA1. Further evidence suggests that clustering is also exhibited at another maximum of approximately 500 nm when looking at an ensemble of EEA1 and early endosomes.

The advancement of computer architecture and chip design has set the stage for the deep learning revolution by supplying enormous computational power. In general, deep learning is built upon neural networks that can be regarded as a universal approximator of any mathematical function. In contrast to model-based machine learning where the representative features are designed by human engineers, deep learning enables the automatic discovery of desirable feature representations based on a data-driven manner. In this thesis, the applications of deep learning to visual content processing and analysis are discussed. For visual content processing, two novel approaches, named LCVSR and RawVSR, are proposed to address the common issues in the filed of Video Super-Resolution (VSR). In LCVSR, a new mechanism based on local dynamic filters via Locally Connected (LC) layers is proposed to implicitly estimate and compensate motions. It avoids the errors caused by the inaccurate explicit estimation of flow maps. Moreover, a global refinement network is proposed to exploit non-local correlations and enhance the spatial consistency of super-resolved frames. In RawVSR, the superiority of camera raw data (where the primitive radiance information is recorded) is harnessed to benefit the reconstruction of High-Resolution (HR) frames. The developed network is in line with the real imaging pipeline, where the super-resolution process serves as a pre-processing unit of ISP. Moreover, a Successive Deep Inference (SDI) module is designed in accordance with the architectural principle suggested by a canonical decomposition result for Hidden Markov Model (HMM) inference, and a reconstruction module is built with elaborately designed Attention based Residual Dense Blocks (ARDBs). For visual content analysis, a new approach, named PSCC-Net, is proposed to detect and localize image manipulations. It consists of two paths: a top-down path that extracts the local and global features from an input image, and a bottom-up path that first distinguishes manipulated images from pristine ones via a detection head, and then localizes forged regions via a progressive mechanism, where manipulation masks are estimated from small scales to large ones, each serving as a prior of the next-scale estimation. Moreover, a Spatio-Channel Correlation Module (SCCM) is proposed to capture both spatial and channel-wise correlations among extracted features, enabling the network to cope with a wide range of manipulation attacks. Extensive experiments validate that the proposed methods in this thesis have achieved the SOTA results and partially addressed the existing issues in previous works. / Dissertation / Doctor of Philosophy (PhD)

As the major component of the plant cell wall, cellulose is produced by all plant species at an annual rate of over a hundred billion tonnes, making it the most abundant biopolymer on Earth. The hierarchical assembly of cellulose glucan chains into crystalline fibrils, bundles and higher-order networks endows cellulose with its high mechanical strength, but makes it challenging to breakdown and produce cellulose-based nanomaterials and renewable biofuels. In order to fully leverage the potential of cellulose as a sustainable resource, it is important to study the supramolecular structure and hydrolysis of this biomaterial from the nano- to the microscale. In this thesis, we develop new chemical strategies for fluorescently labeling cellulose and employ advanced imaging techniques to study its supramolecular structure at the singlefibril level. The developed labeling method provides a simple and efficient route for fluorescently tagging cellulose nanomaterials with commercially available dyes, yielding high degrees of labeling without altering the native properties of the nanocelluloses. This allowed the preparation of samples that were optimal for super-resolution fluorescence microscopy (SRFM), which was used to provide for the first time, a direct visualization of periodic disorder along the crystalline structure of individual cellulose fibrils. The alternating disordered and crystalline structure observed in SFRM was corroborated with time-lapsed acid hydrolysis experiments to propose a mechanism for the acid hydrolysis of cellulose fibrils. To gain insight on the ultrastructural origin of these regions, we applied a correlative super-resolution light and electron microscopy (SR-CLEM) workflow and observed that the disordered regions were associated nanostructural defects present along cellulose fibrils. Overall, the findings presented in this work provide significant advancements in our understanding of the hierarchical structure and depolymerization of cellulose, which will be useful for the development of new and efficient ways of breaking down this polymer for the production of renewable nanomaterials and bio-based products like biofuels and bioplastics. / Thesis / Doctor of Philosophy (PhD) / In this dissertation, we have studied in unprecedented detail the structure of cellulose – a polymer that is found in every plant. As the main structural component of the plant cell wall, cellulose endows trees with their strength and resilience while storing sunlight energy in its chemical bonds. Since plant biomass represents eighty percent of all living matter on Earth, cellulose is an abundant resource that can be used to produce sustainable and environmentally benign nanomaterials and bioproducts, like biofuels and bioplastics. Our ability to use cellulose as a renewable source of structural materials and energy is intimately linked to our capacity to break apart its tight structural packing. Deconstructing cellulose into various forms demands that we understand the multi-level organization of its structure and the susceptible regions within it. To gain this information, in this thesis we develop new labeling methods and apply state-of-the-art microscopy tools to directly visualize the arrangement of cellulose fibrils at the nanoscale (comparable to 1/10,000 the width of a human hair) and study their breakdown by acid treatment. The findings presented in this work furthers our fundamental understanding of the natural structure of cellulose, which has important implications on the development of industrial strategies to break down this abundant and renewable biomaterial.

<p dir="ltr">This dissertation contains conceptual and practical innovations in the field of super-resolution microscopy and applies super-resolution microscopy in the study of chromatin structure at the nanoscale</p>