Theses - Chemistry
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Item Embargo Beyond Suspension: Light and Growth Dynamics in Immobilised Algal CulturesChua, Sing TengWith growing commercial interest in algal biotechnology, immobilised cultures, such as biofilms and matrix encapsulation, have emerged as viable techniques with potential advantages for the commercial extraction of valuable metabolites and applications in functional photosynthetic materials. Nonetheless, little attention has been paid to the natural formation of algal aggregates within encapsulating matrices and the loss of cell motility in a biofilm setting. This thesis explores the physiological effect of mechanical confinement on unicellular flagellate Chlamydomonas reinhardtii, a model organism studied extensively in the laboratory. Serving as a study model of algal biofilm dynamics, the use of timelapse microscopy and single-cell tracking within microcolonies uncovered how external matrices and exogenous nutrient supply influence cell cycle and morphology. The findings revealed spatial heterogeneity among cells within colonies, providing insights into the effects of contact inhibition and micro-gradients of mass transfer. The radial propagation of ring-like oscillations, characterised by variations in parent cell size and chlorophyll autofluorescence emanating from the colony centre, indicated a complex spatio-temporal dynamic in the regulation of the cell cycle within a constrained cellular environment. Beyond the impact of confinement on a single-cell level within individual clusters, the collective environment and spatial distribution of algal aggregates within a gel matrix were also investigated. By microscopic investigation of the algal aggregates confined in the gels, a spatial gradient of their sizes depending on the distance from the gel-air interface was revealed. To better understand this distribution, we studied the interaction of light with such immobilised cultures. As the algal aggregates strongly affect the light distribution within the colony, a comparative study between the heterogeneous distribution of cell aggregates in a gel matrix and a flat, uniform biofilm was performed. The obtained findings not only allowed to better understand the properties of immobilised cultures in the context of biomass yield, but also provided a potential route for the enhancement of light harvesting efficiency, by simple incorporation of scattering particles within the hydrogel matrix. Finally, the last part of the thesis focuses on biomass characterisation, specifically the bulk analysis of macronutrients within algal biomass, and mainly on the lipid productivity. Macromolecular composition was assessed for cultures encapsulated within agar beads and for biofilms where cells were confined between membrane layers. These studies highlight the structural complexity and dynamic nature of cellular communities under confinement, where specific growth characteristics and population heterogeneity contribute to emergent cell functions.Item Open Access Non-Equilibrium Pattern Formation in Multi-Species Interacting Particle SystemsYu, Honghao; Yu, Honghao [0000-0002-9317-0433]Non-equilibrium systems can form complex patterns in their steady states. Examples are systems consisting of self-propelled particles or systems consisting of particles driven away from equilibrium by external energy sources. In steady states, the interacting particles spontaneously organise into complex spatial patterns. The patterns formed in steady states are sustained by the continuous energy input into the system, which is then dissipated as heat in the bulk. The formation and evolution of large coherent structures necessitate a stochastic description, using methods of non-equilibrium statistical physics. In this thesis, we study these fluctuating patterns in complex systems of multiple species of particles. We focus our study on three different types of non-equilibrium systems with complex pattern formation. In Chapter 3, we study several different lattice-based models where two species of diffusing particles are driven in opposite directions by an external force. We identify and characterise the dynamical phase transitions that involve phase separation into domains that may be parallel or perpendicular to a driving force. We also analyse how phase separations emerge from different microscopic interactions: The perpendicular state appears for weak driving, consistent with previous work. For strong driving, we introduce two models that support the parallel state. In one model, this state occurs because of the inclusion of dynamical rules that enhance lateral diffusion during collisions; in the other, it is a result of a nearest-neighbor attractive or repulsive interaction between particles of the same or opposite species. We discuss the connections between these results and the behavior found in off-lattice systems, including laning and freezing by heating. In Chapter 4, we study mixtures of oppositely driven particles, showing that their non-equilibrium steady states form lanes parallel to the drive, which coexist with transient jammed clusters where particles are temporarily immobilized. We analyze the interplay between these two types of non-equilibrium pattern formation, including their implications for macroscopic demixing perpendicular to the drive. Finite-size scaling analysis indicates that there is no critical driving force associated with demixing, which appears as a crossover in finite systems. We attribute this effect to the disruption of long-ranged order by the transient jammed clusters. In Chapter 5, we study a lattice model of three species with cyclic dominance that resembles a rock-paper-scissors game. We extend the existing rock-paper-scissors model to include natural death and hunger mechanisms. We identify a new extinction phase which happens at high natural death. The condition under which one “smart” species can increase its population and the well-known but counter-intuitive phenomenon the survival of the weakest is recovered. To understand how local environment affect the survivability of the “smart” species, we investigated four local adaptive strategies with which the “smart” species increases its population by choosing its dynamics based on its local environment. Among different local adaptive strategies, we identify the evading strategy where “smart” particles evade predators to be the best local adaptive strategy. We characterise these non-equilibrium pattern formations due to the fluctuation of different species of interacting particles. We focus on topics such as the microscopic origins of macroscopic pattern formation, the breaking of symmetry and phase transitions, long-ranged order, density fluctuations, etc. We show various theoretical and numerical tools that can be applied to characterise these systems and show these complex non-equilibrium systems share many similar features.Item Embargo Novel Magnetic Resonance Techniques as Applied to Metallic Phases in Lithium-Ion Battery ElectrodesInsinna, Teresa; Insinna, Teresa [0000-0001-6484-4323]Since their introduction in the late 1990s, lithium-ion batteries (LIBs) have played an increasingly important role in society, powering portable electronics, electric vehicles and grids. As such, they are critical in paving the way to net-zero carbon emissions. The prototypical anode and cathode in intercalation LIBs are graphite and lithium cobalt oxide (LCO), with the materials chemistry and battery communities treating them as “model compounds”. Despite this, the electronic properties of these electrodes remain unclear. Graphite is a semimetal which becomes metallic on intercalating lithium (when charging the battery), whilst LCO transitions from an insulating to a metallic phase on delithiation. Understanding the electronic structures of these systems—and how these structures impact the redox, degradation and failure mechanisms—is critical to the development of the next generation of LIB electrode materials. In this thesis, the nature of these semimetal/insulator to metal phase transitions and the electronic properties of the metallic phases were probed by magnetic resonance methods: Electron Paramagnetic Resonance (EPR), Nuclear Magnetic Resonance (NMR) and Dynamic Nuclear Polarisation (DNP), as well as magnetic property measurements, all at variable temperature (VT). In addition to providing insight about these materials’ electronic structures, the body of work presented here describes novel methods to study these complex materials. Firstly, graphite is examined using variable frequency EPR spectroscopy, for the first time directly revealing that conduction electrons occupy bands on the graphite sheets whilst undergoing semi-localised hyperfine interactions with Li ions. By measuring the EPR spectra as functions of microwave frequency, temperature and state of charge of the graphite anodes, skin effects and metalliticty can be successfully probed. Leveraging this knowledge, the nature and degradation of the surface layers of graphite formed upon cycling, the solid electrolyte interphase (SEI), were probed using DNP and NMR. To date, the SEI has been examined using several techniques, with many conflicting reports on its properties, composition and efficacy in preventing electrolyte degradation. A novel approach to examine the SEI was developed by introducing selectivity towards the graphite-SEI and the Li dendrite-SEI interphases by exploiting the enhancement of the NMR signal provided by the graphite/Li conduction electrons on microwave irradiation (i.e., Overhauser DNP). For the first time, LiOH was identified as the main degradation product at the interphase and that Li plating on graphite dramatically changes the SEI composition. Finally, metallic phase transformations in LCO were studied. LCO is a very different metal to graphite, as it contains both localised and delocalised electrons, as per Mott-Hubbard theory. To explore the metal-insulator transitions in LCO, ex situ 7Li, 59Co and 17O VT NMR were used to probe the local electronic structure of LCO on delithiation, with operando NMR providing information about the dynamics of these local structural changes. The local structure obtained was combined with bulk electronic and chemical structural information provided by magnetometry and operando X-ray diffraction, resulting in an electronic picture where conduction holes are delocalised over Li and O ions and more localised over the Co ions.Item Open Access Developing and Investigating the Scope of Quinone-Functionalised Carbons for Electrochemical Carbon Dioxide CaptureHartley, Niamh; Hartley, Niamh [0000-0003-1381-9026]The amount of CO2 emissions is rising exponentially, contributing to a global temperature increase beyond 1.5°C. To limit emission levels, the demand for cost-effective carbon capture technology is rapidly increasing. Current commercial carbon capture processes use amine molecules to capture CO2; however, these systems face high regeneration energy, high operational costs, and degradation issues. An electrochemical approach can avoid large energy losses via. heat and selectively uptake CO2 by utilising redox-active organic molecules. To compete with conventional chemical scrubbing, the electrochemical cell needs high CO2 uptake, long cycle stability and low energy consumption. Redox-active molecules such as quinone-based molecules have been utilised in this area but suffer from low cycling stability due to organic molecules leaking into the electrolyte. Anthraquinone is a common organic molecule for this process because it is highly stable under different conditions and exhibits electrochemically reversible redox behaviour. However, anthraquinones in solution can react with oxygen, suffer from electrolyte loss through evaporation and have low solubility in aqueous conditions. Therefore, immobilising anthraquinone onto conductive materials can combine the charge capacity of the conductive material and the redox activity of anthraquinone. Quinone-polymer electrodes have shown high efficiency for CO2 capture however are plagued by low active-material mass and quinone degradation, therefore a new alternative is needed. In this thesis, anthraquinone was synthetically grafted onto various carbon materials: CMK-3, BP-1300 and YP-80F. The carbon materials were extensively characterised, and a standardised workflow of techniques was developed, involving gas sorption analysis, solid-state NMR, and electrochemical methods. The characterisation techniques evidenced successful anthraquinone loading, and quantitative loadings were estimated from electrochemistry and solid-state NMR spectroscopy. The materials were tested for electrochemical CO2 capture and showed capture of CO2 during anthraquinone reduction and release of CO2 during anthraquinone oxidation. This was then tested in long cycling experiments, showing adsorption capacities of 0.1 – 0.3 mmol g–1 up to 200 cycles, comparable to reported electrochemical capture technologies. A stark difference in stability was observed under CO2 compared to N2, particularly for functionalised carbon materials with predominantly mesoporous environments, such as CMK-3 and BP-1300. In contrast, the predominantly microporous carbon YP-80F showed enhanced stability, with charge storage capacity retention of 80.0% after 1000 charge/discharge cycles under CO2. The reactivity of anthraquinone in the presence of oxygen was then investigated. To avoid the oxygen reduction reaction in solution, which occurs at negative potentials, electron-withdrawing groups were added to the anthraquinone molecular structure. However, this modification decreased the binding constant for CO2, creating an inversely proportional relationship. The CO2 capture performance of anthraquinone-functionalised carbons was then tested in the presence of oxygen. CO2 capture was observed at approximately 0.1 – 0.2 mmol g–1, similar to values seen under pure CO2, but the Faradaic efficiency lowered by 10%. The anthraquinone-mediated pH swing was also tested using the functionalised carbon materials, resulting in apparent CO2 capture at low energy consumptions. Overall, this thesis details the ease of synthesis and characterisation of anthraquinone-functionalised carbon materials. All materials demonstrate the ability to electrochemically capture CO2; however, functionalised carbon materials with microporous environments showed better stability and lower energy consumption. These materials were then tested for CO2 capture in the presence of oxygen and in a pH swing system. In both cases, promising results indicated that these materials are highly tuneable for CO2 capture, allowing for future development and implementation.Item Embargo Multiscale coarse-grained models for biological phase separation: Development and applicationsAguirre Gonzalez, AneMany proteins undergo liquid–liquid phase separation (LLPS) in order to generate membraneless organelles, by which the cell can organise its biomolecules and bioprocesses dynamically in space and time. Many of the experimental and theoretical methodologies used to study the formation of these condensates still struggles to capture the relation between microscopic, residue–level details of a protein with its phase behaviour in the bulk. In this thesis, we present three multiscale coarse-grained models with amino acid resolution aimed at studying phase separation of proteins. The Mpipi model balances the dominant role of π–π and hybrid cation–π/π–π interactions with the rest of the interactions, while keeping R–based interactions stronger than K–based ones. The parameterisation is based on atomistic PMF calculations and bioinformatics data on π-based contacts. The Mpipi Recharged model is a finer and more optimised version of Mpipi, that appropriately balances the electrostatic interactions on a pair-by-pair basis, since which all-atom simulations prove the asymmetry between samely-charged and oppositely-charged residues. Both Mpipi and Mpipi recharged are capable of reproducing ensemble averaged experimental observables with high accuracy, from single-molecule properties to phase diagrams of an extensive set of proteins (*i.e.* hnRNPA1, FUS, *Laf* 1, DDX4) and their corresponding mutations. Lastly, we also investigated the role of Mg2+ions in regulating LLPS of intranuclear proteins. Atomistic-resolution simulations proved that minimal quantities of Mg2+ions present in the media can significantly alter the phase behaviour of proteins, especially ones with a high number of charged residues. The MagPi model arises from this observations and bioinformatics analysis of the proteome, and can reproduce the phase behaviour of a set of intranuclear proteins (*i.e.* MED1 IDR, BRD4 IDR, Nanog CTD, and DDX4 and DDX3 variants) qualitatively. Overall, our multiscale modelling approach shows great potential at bridging the gap between atom-level observables, to single-molecule behaviour, to macroscopic phase transitions, as well as its ability to extend the range of the simulations to different solvent conditions or surroundings. Therefore, the work presented in this thesis poses a significant step towards the unification of experiments, computer simulations and real biological LLPS phenomena.Item Open Access Building a bridge between biophysics and neurobiology: A synergic approach to develop Alzheimer’s disease translational models and research toolsGonzalez Diaz, AliciaAlzheimer's disease (AD) is the most prevalent neurodegenerative disorder, accounting for 60-70% of dementia cases diagnosed worldwide. The impact of AD is rapidly increasing, with deaths more than doubling from 2000 to 2021. As populations age, especially in industrialized nations, the socio-economic burden of AD is massively escalating, necessitating the urgent development of effective treatments to delay, halt or reverse this fatal disease. In 1906, Dr. Alois Alzheimer identified the two main cardinal lesions of AD brains: (i) extracellular amyloid deposits or plaques; and (ii) intracellular neurofibrillary tangles (NFTs). We now know that these lesions result from the misfolding and aggregation of the intrinsically disordered proteins amyloid-β (Aβ) and tau, respectively. For decades, these proteins have been the focal point of research efforts and drug discovery initiatives. Recently, the U.S. Food and Drug Administration approved the first three disease-modifying drugs, which target amyloid plaques: aducanumab (2020), lecanemab (2021), and donanemab (2024). However, the scientific community remains divided over their clinical impact, given the limited cognitive improvements and severe side effects reported. The reduced efficacy of current therapeutics can be attributed to at least two critical factors. Firstly, treatment intervention often occurs at a late disease stage, when the patient's therapeutic window has already significantly narrowed. Secondly, the drugs target Aβ aggregate species that may not be one of the primary AD cytotoxic agents. The Aβ aggregation cascade involves a series of complex processes, wherein misfolded monomers transition through a wide range of intermediate oligomeric states to form assemblies such as protofibrils and mature fibrils, characterized by cross-β core secondary structures. Oligomers, rather than mature fibrils, are increasingly recognized as the primary toxic species in AD. However, due to their heterogeneous and transient nature, capturing these species to characterise their mechanisms of formation and cytotoxicity is a frustrating task. Moreover, Aβ can undergo heterogeneous nucleation and aggregation with other peptides and brain biomolecules, which increases the complexity of existing aggregate species. For these reasons, Aβ oligomers are often pushed to the periphery of drug discovery pipelines. In the first sections of this thesis, I present the development of tools and models to make Aβ oligomers more accessible targets for drug discovery and preclinical setups. To contribute new tools towards unravelling the structural determinants of the cytotoxicity of oligomer species, in Chapter 3, I introduce a step-by-step method to stabilize physiologically-relevant, off-pathway Aβ42 oligomers using Zn(II), a brain-enriched cation. This approach enables a robust analysis of oligomer structure-toxicity relationships and modeling AD-relevant phenotypes – such as calcium influx, reactive oxidative species (ROS) production, and mitochondrial dysfunction – in human cell systems. Additionally, I detail a workflow for fine-tuning experimental parameters to generate kinetically-trapped oligomers from any aggregation-prone peptide of interest. Traditional in vitro kinetic studies of Aβ aggregation inform on the microscopic mechanisms and rates of formation of on-pathway Aβ oligomers, but fail to capture the complexity of the cellular environment and the biological effects of oligomer formation. To address this limitation, in Chapter 4, I present a protocol to control the in situ formation of on-pathway Aβ42 oligomers via secondary nucleation (the microscopic mechanism that has the major impact in oligomer production) using human neuronal cultures. This is accomplished by seeding the aggregation of the Aβ42 monomer using pre-formed amyloid fibrils, directly on cells. This model bridges the gap between in vitro kinetic studies and cellular biology, providing an effective platform for studying Aβ oligomerization and testing potential inhibitors. To move from methods relying on exogenously-driven Aβ oligomerisation to approaches that mimic the endogenous Aβ aggregation cascade of human brain cells, in Chapter 5 I work on the development of robust and scalable human cell systems that can recapitulate endogenous Aβ production and aggregation, along with associated dysfunctional phenotypes. Creating human induced pluripotent stem cells (hiPSC)-derived neurons that accurately recapitulate endogenous Aβ aggregation and associated pathologies in a scalable, high-throughput and robust format, is challenging. This is due to the intrinsic variability of iPSC systems and the difficulties to mimic endogenous Aβ aggregation in neuronal systems without relying on complex three-dimensional cultures or artificial overexpression of several familial AD variants. To this aim, I established a robust hiPSC differentiation protocol with stringent quality control checkpoints to generate well-characterized cortical neuronal progenitor cells (NPCs) and derived cortical glutamatergic neurons. The protocol has been scaled up to produce batches of millions of high-quality cryopreserved progenitor cells, suitable for high-throughput applications. Using the pro-inflammatory stressor TNF-⍺, I developed a neuronal model with these standardized hiPSC cultures that demonstrates endogenous Aβ production and aggregation, along with dysfunctional phenotypes such as altered synapsis and hypermetabolism. The research presented in Chapters 3, 4, and 5, revealed that Aβ aggregates in the developed cell models mostly co-localize with cell membranes and progress from spherical to irregular, fibrillar structures over time. This morphological progression is typical of proteins undergoing phase separation, liquid-to-solid transition (LTST), and subsequent amyloid aggregation. Given that cell membranes are primarily composed of lipids, which have the ability to phase separate and bind to Aβ peptides, in Chapter 6, we investigated the role of lipids in regulating Aβ aggregation and phase separation. We show that Aβ forms biocondensates with lipids, a mechanism that favors primary nucleation and accelerates the conversion of monomers into fibrils. This process may dominate early amyloid-β aggregation and can form the basis for novel therapeutic intervention strategies. In the final sections of this thesis, I expand our focus from the pathological event of Aβ aggregation to a broader perspective on the nature of AD. While preclinical settings may benefit from translational tools to model Aβ aggregation and oligomer formation, it is crucial to recognize that AD extends beyond Aβ and tau pathologies. AD represents a highly complex and heterogeneous spectrum of disorders with multiple clinical and neuropathological manifestations that vary among patient subtypes, particularly in sporadic forms of the disease (sAD). We emphasize the importance of integrating this heterogeneity in preclinical settings to accelerate drug discovery programs towards more effective, personalized medicine. sAD accounts for approximately 90% of all AD cases and stems from a complex interplay of genetic and environmental factors that: (i) vary across patient groups, and (ii) propel cells towards a variety of early disease states. These disease states can be defined by transcriptomic fingerprints that functionally drive cells into the disease phenotype. Therefore, by integrating such fingerprints in human cells, one can generate panels of AD models. In Chapter 7, I worked towards disentangling the nature of such fingerprints and present a cell-based pipeline to identify early disease drivers from patient-derived transcriptomic signatures. This work resulted in the creation of a comprehensive model sporadic AD model in iPSC-derived neurons, based on the early downregulation of FBXO2, a gene encoding a subunit of the ubiquitin protein ligase complex SCF. This model captures key pathological features such as synaptic dysfunction, Aβ aggregation, and tau hyperphosphorylation. To accelerate the generation of AD preclinical models, in Chapter 8 I introduce the designs of a novel human cellular biological tool, the Recipient Line, that holds the essential orthogonal genetic elements to capture the complex and heterogenous molecular nature of AD in a standardised, time and cost-effective manner. The Recipient Line holds a well-characterised genetic background, the plasticity to be converted into the cell type from which patient-derived molecular fingerprints are predicted, and the genetic tools necessary to: (i) allow for a rapid and systematic site-specific insertion of fingerprint modulators without the need of applying cumbersome CRISPR gene editing approaches, and (ii) enable a temporal control of the manifestation of each molecular fingerprint, and therefore, the entry into patient-specific disease states. This approach aims to bridge the gap between computational predictions and biological validation, enhancing the translational value and predictive accuracy of artificial intelligence (AI) pipelines, ultimately accelerating the development of personalized therapeutics for AD.Item Open Access Advances in volumetric super-resolution microscopy and single-particle trackingDaly, Sam; Daly, Sam [0000-0002-8559-3161]Single-molecule localisation microscopy (SMLM) has enabled optical microscopy to probe biological structures and processes at the nanometer scale. To accommodate the inherently 3D nature of biological structures, 3D-SMLM techniques---such as the astigmatic and double-helix point spread functions (PSFs)---have been developed. These techniques encode the lateral and axial positions of single fluorophores into the PSF shape but at the cost of reduced spatial and temporal resolution. This limitation restricts the compatibility of 3D-SMLM with established labeling protocols, increases experimental duration and reduces biological throughput. Thus, accelerating 3D-SMLM is essential for broader applicability in the life sciences. Single-molecule light field microscopy (SMLFM) is a novel 3D-SMLM approach that uses a microlens array in the back focal plane of an optical microscope to capture fluorescence from multiple perspectives. Conceptually, SMLFM improves the density limit of SMLM through three key factors: 1. The PSF footprint resembles a simple and compact 2D Gaussian function that can be better distinguished at high density compared to complex engineered spatial patterns. 2. Laterally overlapping fluorophores can be better distinguished as a result of the parallax-based optical model. 3. An optical redundancy in the number of perspective views required for 3D reconstruction increases the range of working densities. This thesis documents the characterisation, validation, and application of the first hexagonal SMLFM platform. In brief, Chapter 3 describes a workflow for establishing SMLFM design parameters, useful for researchers looking to build their own platforms. Furthermore, optical validation and characterisation protocols benchmarked SMLFM in both static and dynamic imaging modes over an 8 μm axial range. Chapter 4 describes the quantitative comparison between SMLFM and other 3D PSFs, demonstrating similar resolving power and imaging speed between SMLFM and astigmatism, and a ten-fold speed improvement over the state-of-the-art double-helix PSF. Various imaging applications of SMLFM are then presented. Chapter 5 explores the stoichiometry of the B-cell receptor on primary mouse B cells and the spatial enrichment of the PD-1 receptor relative to the membrane morphology of T cells. Chapter 6 applies SMLFM in a single-particle tracking modality to quantify the diffusive states of Golgi-localised proteins, RAB6 and ACBD3, and reports on a biophysical investigation into the effect of transmembrane domain length on protein secretion.Item Restricted Polymerase-based approaches towards epigenetic DNA sequencing and de novo DNA synthesisSchmidl, David; Schmidl, David [0000-0003-1564-5584][Restricted]Item Embargo Investigating Layered Electrically Conductive Metal-Organic Frameworks For Supercapacitor ApplicationsGittins, James; Gittins, James [0000-0002-9106-8910]Supercapacitors are high-power energy storage devices that will play an important role in the transition to a low-carbon society. In recent years, layered electrically conductive metal-organic frameworks (MOFs) have emerged as one of the most promising electrode materials for next-generation supercapacitors. Their crystalline and tuneable structures facilitate structure-performance studies, which are challenging to conduct with traditional porous carbon electrodes. In this work, the electrochemical performances of layered conductive MOFs in supercapacitors are investigated to both improve our understanding of these materials and to develop structure-performance relationships. Having demonstrated that the layered conductive MOF Cu3(HHTP)2 (HHTP = 2,3,6,7,10,11-hexahydroxytriphenylene) exhibits good performance in supercapacitors, measurements on samples with different particle morphologies reveal that ‘flake’ particles, with small length-to-width aspect ratios, are optimal for these devices. This is due to improved ion accessibility and dynamics through the short pores of the ‘flake’ particles, resulting in a higher power performance compared to particle morphologies with longer pores. Electrochemical quartz crystal microbalance (EQCM) and three-electrode experiments are then performed with Cu3(HHTP)2 and a series of electrolytes with different cation sizes to investigate both the charging mechanism of this MOF and how electrolyte ion size impacts electrochemical performance. It is shown that cations are the dominant charge carriers in Cu3(HHTP)2, with co-ion desorption occurring upon positive charging and counterion adsorption during negative charging. Large ions lead to porosity saturation in MOF electrodes, reducing charge storage and forcing solvent molecules to participate in the charge storage mechanism. The impact of modifying MOF-electrolyte interactions on the electrochemical capacity of layered MOF supercapacitors is then investigated by altering both the electrolyte cation and the MOF electrode functionality. These experiments allow for the systematic probing of the influence of different functional groups on supercapacitor performance, and reveal that MOFs with hydroxy ligating groups, together with Li⁺ electrolytes, constitute the best electrode-electrolyte combination for maximising capacitive performance. Finally, an interlaboratory study is conducted to assess the variability in the reporting of performance metrics across different laboratories. Overall, this work provides unique insights into the performances of layered conductive MOFs for supercapacitor applications, and will guide the design of improved electrode materials for next-generation supercapacitors.Item Embargo Investigation of the factors contributing to the physical stability of biological therapeuticsBarber, Jack; Barber, Jack [0000-0003-2993-1397]Biological therapeutics, primarily peptides and proteins, are becoming increasingly commonly used due to their specificity and efficacy. Unfortunately, they can suffer from aggregation, resulting in immunogenicity and poor bioavailability. The mechanisms behind such losses in physical stability, which is itself sensitive to a wide range of factors, can result in batches of the same therapeutic displaying different aggregation behaviour. Glucagon-like peptide 1 (GLP-1) is 31-residue peptide that, along with its analogues, is used in the treatment of diabetes and obesity. Four batches of GLP-1 produced by a single supplier using solid-state synthesis were found to exhibit batch-to-batch variation in their physical stability. These were characterised by a myriad of techniques to measure properties ranging from secondary structure and alterations in chemical composition, to the presence of different oligomeric states. This was to attempt to determine potential origins of the batch-to-batch variation observed. Pertinent factors that may influence physical stability were examined more extensively to aid in this goal. Cu2+, Fe3+ and Zn2+ ions were found to be able to influence the physical stability of GLP-1 at concentrations as low as 1 μM. The metal ions affected either the compactness of the monomeric or other oligomeric states, or increased the population of oligomers, some of which were known to be off-pathway and inhibit aggregation. However, it was determined that in the GLP-1 batches studied, the amount of these metal ions was insufficient to account for the differences in physical stability observed. Varying water content in different samples of lyophilised protein and peptide samples has also been proposed to affect physical stability and lead to batch-to-batch variation. Here, a non-destructive method of measuring water content in pharmaceutical preparations using time-domain NMR was developed in collaboration with AstraZeneca. It was then used to investigate whether water content can alter the physical stability of a therapeutic peptide, however, results were somewhat inconclusive. Lastly, a method of producing GLP-1 by recombinant means was adapted to allow for a comparison of the physical stability of peptide produced recombinantly with the GLP-1 batches produced by synthetic means.Item Embargo Protein-lipid interactions in molecular pathways of Parkinson’s and Alzheimer’s diseasesŠneiderienė, Greta; Šneiderienė, Greta [0000-0002-4585-5091]Alzheimer’s and Parkinson’s (AD and PD) diseases, increasingly prevalent and currently incurable neurodegenerative disorders, are characterised by the accumulation of proteinaceous pathogenic inclusions in the central nervous system. The key proteins involved in the pathogenesis of AD and PD are amyloid β 1–42 (Aβ42) and α-synuclein (αS), which cause the toxicity in AD and PD through aberrant interactions with lipid membranes. Despite current significant effort, the link between αS-/Aβ42-membrane interactions and disease mechanisms remains elusive. In this work, I applied a set of bulk and microfluidic assays to address this problem by quantifying misfolded αS- and Aβ42-lipid membrane interactions. In the initial section of the thesis, I present the results of a study that delves into the interactions between oligomeric/monomeric αS and lipid membranes. The findings revealed striking differences in membrane binding affinity of the two species. Furthermore, misfolded oligomeric αS competes with monomeric αS for membrane binding, displacing the latter. Prompted by these findings, I investigated the possible mechanisms preventing aberrant aggregated αS-membrane binding. Results indicate that βS, a homologous protein from the synuclein family, can displace aggregated αS from lipid surfaces and mitigate compromised membrane integrity. The final sections of the thesis focus on AD-linked Aβ42 aggregation kinetics and mechanisms on lipid membranes. By applying chemical kinetics approach, I found that rates of distinct microscopic Aβ42 aggregation steps depend on the composition of cell membrane mimetic liposomes. Furthermore, the results show that lipid surfaces trigger Aβ42 primary nucleation by promoting liquid-liquid phase separation, which is an intermediate state in the amyloid cascade. These fundamental findings enhance the understanding of lipid-mediated molecular pathways in AD and PD, and provide insights that pave the way for future exploration of neurodegenerative disease pathology.Item Open Access Using Cell Painting and Chemical Data for Small-molecule Bioactivity and Toxicity PredictionSeal, Srijit; Seal, Srijit [0000-0003-2790-8679]High-content image-based assays have fueled significant discoveries in the life sciences in the past decade, including novel insights into disease etiology, mechanism of action, new therapeutics, and toxicology predictions. The most popular among them is the Cell Painting assay, has been used alone or in combination with other - omics data to decipher the mechanism of action of a compound, its toxicity profile, and many other biological effects. Traditional approaches in drug discovery primarily rely on chemical structure fingerprints, which do not capture biological responses to compounds. By integrating cell morphology data, models offer a more comprehensive view, improving the prediction and accuracy for various bioactivity endpoints and enhancing the interpretability of models. We present a comprehensive approach to improving the prediction of drug toxicity and understanding the underlying mechanisms by integrating chemical and biological data. We first demonstrate the advantages of combining cell morphology data from the Cell Painting assay, gene expression data, and chemical structural information to develop machine learning models that accurately predict mitochondrial toxicity and show comparable performance with dedicated in vitro assays. The applicability domain of machine learning models trained on structural fingerprints for the prediction of biological endpoints is often limited by the lack of diversity of chemical space of the training data. We developed similarity-based merger models which combined the outputs of individual models trained on cell morphology (based on Cell Painting) and chemical structure (based on chemical fingerprints) and the structural and morphological similarities of the compounds in the test dataset to compounds in the training dataset. The similarity-based merger models improved predictions across a wide range of biological assays from ChEMBL, PubChem and the Broad Institute. Cell Painting assays, however, faced a significant hurdle in the industry: complex image-based features needed to be more interpretable. To bridge the gap between high-dimensional morphological features and biologist-interpretable phenotypes, we introduce an algorithm that maps Cell Painting features to various readouts from the Cell Health assay. The BioMorph space revealed the mechanism of action for individual compounds, including dual-acting compounds such as emetine. This approach therefore offers a biologically relevant way to interpret the cell morphological features derived using software such as CellProfiler and to generate hypotheses for experimental validation. In summary, our work demonstrates the potential of combining chemical and biological data for enhanced prediction of drug safety endpoints with practical implications in drug discovery and predictive toxicology.Item Restricted Item Embargo Modular Approaches for the Synthesis of α-Azinyl Amines and Related ScaffoldsRafaniello, Alex A; Rafaniello, Alex [0000-0001-5311-2290]The work in this thesis comprises three projects all with a central focus on the synthesis of α-alkyl 2-azinyl amines and related scaffolds in a modular fashion. The first project describes the development of an operationally straightforward and general multicomponent carbonyl azinylative amination process. This protocol, which employs elemental indium as a reducing agent and a silyl triflate Lewis acid, facilitates access to a wide range of novel heterobenzylic amines from readily available aldehyde or ketone, amine and heteroaryl halide feedstocks. This work builds upon prior work carried out in the Gaunt group towards a general approach for complex amine synthesis and represents a significant and complementary advance and on our previously reported carbonyl alkylative amination platform. Here we also reveal the underexplored utility of a 2-azinyl anion equivalent that we believe manifests in the form of an organoindium species, identified through a series of mechanistic experiments. The reactivity of this putative intermediate is investigated through its reactions with other common electrophilic partners, enabling the efficient synthesis of functionalised tertiary alcohols, including an aza analogue of an antipsychotic drug haloperidol. To further demonstrate its synthetic utility, the carbonyl azinylative amination reaction was leveraged to enable the synthesis of nitrogen-rich and pharmaceutically-relevant α-azinyl piperidines. Proposed future work is also presented, including the realisation of a comprehensive platform for the assembly of heterocyclic scaffolds which contain the α-alkyl 2-azinyl amine motif, namely 7-aminopyrindans and tetrahydronaphthyridines.Item Embargo Designing New Pt-Based Catalysts: Dual Manipulation of Highly-Branched Structures and Intermixed CompositionsMing, Siyi; Ming, Siyi [0000-0001-8886-7722]This thesis investigates new design strategies for cost-efficiently fabricating Pt-based catalysts with exceptional oxygen reduction reaction (ORR) performance. Findings open new opportunities for developing next-generation, more cost-effective Pt-based catalysts, potentially advancing hydrogen fuel cell (HFC) technology by enhancing performance and addressing cost and energy security challenges through innovative catalyst design. The thesis is divided into four sections, with a particular emphasis on the control of two aspects of anisotropic nanoparticle (NP) growth; manipulating highly-branched morphologies and also composition. This dual control of properties promises to significantly reduce Pt reliance and synthesis cost and complexity while enhancing catalytic activity The first section explores the combination of Pt with Fe under various synthesis conditions, resulting in bimetallic NPs that provide insights into nanopod and nanodendrite formation. By finely controlling the reduction of metal precursors through the modulation of capping agents, reagents, and temperature, morphology control is then maintained while the composition is varied from Pt-rich to Pt-poor. Additionally, a methodology for promoting the collision-based branching of nanopod arms has been developed. This process is found to occur when the concentration of nanopods reaches a critical threshold, leading to diffusion-controlled collisions that induce nanodendrite formation. This allows the selective growth of compositionally controlled nanodendrites for the first time. The second section investigates the interplay between kinetic NP growth and thermodynamic reduction pathways, which opens opportunities for designing ultra-low-cost Pt-based catalysts. This part includes the synthesis of Pt/Fe nanopods that significantly reduce reliance on Pt through a simple one-pot synthesis protocol. This process is conducted over 30 minutes in an ambient pressure N2 environment at 250°C. The method significantly lowers Pt dependence and increases yield by optimising the input ratio of Fe to Pt precursors. A reducing in the Pt precursor input from an initial ratio of 0.5 (relative to Fe) to 0.2 and eventually to 0.1 may improve the yield of Pt/Fe nanopods from 55% to 78% and potentially up to 94%. Nanopods, made with a Pt:Fe ratio of 0.1, exhibit exceptional ORR performance, reaching a mass activity of 1.27 A/mgPt at 0.9 V versus RHE, almost 32 times more mass-efficient than the commercial 10 wt% Pt NP/C standard, at an electrode loading as low as 0.56 μgPt/cm². Furthermore, the design strategy for these nanopod catalysts offers extensive chemical flexibility, allowing for effective manipulation of arm density and composition across different raw materials. Building on the successful dual control over Pt/Fe morphology and composition, the third section extends the developed methodology to a range of anisotropically grown Pt/Ni and Pt/Co bimetallic NPs. The Pt/Fe system is used to develop a method to promote collision-based branching of nanopod arms at critical nanopod concentrations, leading to diffusion-controlled collisions and subsequent nanodendrite formation. Leveraging this established protocol, the synthesis parameters for Pt/Ni and Pt/Co systems have been fine-tuned to replicate the controlled environment that facilitates similar branching behaviours. By ensuring the critical nanopod concentration is achieved in each case, the formation of nanodendrites is induced. This demonstrates the versatility and effectiveness of the original methodology across different bimetallic combinations, allowing a detailed understanding of how adjusting individual synthetic parameters affects the formation of Pt/M nanopods and nanodendrites with composition control. The obtained catalysts demonstrate superior ORR performance at an electrode loading as low as 2.2 μgPt/cm². Notably, nanodendritic Pt/Ni achieves a mass activity of 0.55 A/mgPt at 0.9 V versus RHE, making it 87 times more efficient in terms of Pt content than a commercial 10 wt% Pt/C NP standard. The final section extends the success in preparing anisotropic bimetallics to the synthesis of Pt/M1/M2 (M = Fe, Co, Ni) nanopods and nanodendrites with uniformly intermixed compositions. The resulting catalysts exhibit superior ORR performance. Particularly, Fe/Co/Pt nanopods achieve a mass activity of 1.01 A/mgPt at 0.9 V versus RHE at an electrode loading as low as 0.76 μgPt/cm², making them 28 times more efficient by mass than a commercial 10 wt% Pt/C NP standard. In contrast to previous reports, this study demonstrates the use of a non-empirical synthetic strategy to achieve a range of trimetallic compositions with different morphologies, addressing the critical issue of phase segregation in such systems and paving the way for new levels of catalyst design in this area.Item Open Access The application of low-cost sensors to monitor and characterise particulate matter air pollutionFleming, JessicaParticulate matter air pollution is a major threat to health and the environment. Accordingly, monitoring networks have been established to record particle mass concentrations under fixed conditions. However, monitoring sites are sparsely distributed due to the expense, size and calibration requirements of regulatory-grade instruments. Very limited information is available on the particle number, sizes and composition, and how these may vary under typical ambient conditions. Low-cost sensors can improve the spatial resolution and range of deployment sites of particle measurements as they are cheaper to buy and run, and require less space, energy and specialist skills to operate. However, their scope has been mainly limited to measurement of particle mass and number concentrations, the accuracy of which can be variable. The three-channel optical particle counter (3COPC) is a new instrument that uses low-cost sensors to measure the particle number size distribution at different temperatures. This work describes the instrument and demonstrates its use, with the aim of showing how low-cost sensors can provide accurate information including but also beyond the particle mass concentration. It is hoped this will guide and inspire further developments in low-cost particle characterisation. In heated mode, the 3COPC measures particle number size distributions which, after calibration, are equivalent to regulatory-grade instruments in the fine particle size range. These data reveal information about the sources and processes affecting ambient aerosol. For instance, sub-micron particles were associated with aged vehicle and cooking emissions, and secondary inorganic aerosol. At larger diameters, the instrument was sensitive to fog droplets which were not removed by heating. This work describes the first use of low-cost sensors to measure and compare the particle number size distribution at variable temperatures, in order to quantify particle size changes due to both hygroscopic growth and evaporation of semi-volatile components. The 3COPC growth factor provides a marker for higher proportions of hygroscopic and/or volatile components, especially NH4NO3. The findings from applying a similar measurement technique to a regulatory-grade OPC are also explored. In laboratory experiments, the 3COPC was used to measure the hygroscopicity (via the κ parameter) of (NH4)2SO4, NaCl and a 1:1 mixture of the two compounds. The derived values mostly overlapped with the literature range, although with some uncertainty. The instrument also measured the saturation vapour pressure of three dicarboxylic acids (succinic, adipic and pimelic acids) to within an order of magnitude accuracy. In both cases, a kinetic model was developed to simulate the air temperature and gas/particle concentrations inside the 3COPC conditioning system. This is the first such kinetic model to directly use the κ parameter to simulate hygroscopic growth. The 3COPC is a novel prototype instrument. As such, its modes of operation and capabilities are evaluated throughout. Clear recommendations are made for future deployments of the instrument. Learnings to inform the next-phase prototype are also set out. Overall, this work aims to promote more innovative applications of low-cost sensors and to take the first steps towards this.Item Open Access Light field microscopy for 3D imaging flow cytometryCollins, AlexanderCapturing cellular morphology on a population level requires technologies enabling high speed imaging and sample throughput. This has motivated the evolution of flow cytometry, which uses microfluidics to measure the fluorescence and scattering signals of thousands of cells per second, towards imaging flow cytometry, which allows spatial information to be collected at extremely high throughput. However, most existing systems are limited to 2D imaging, which can be unable to answer certain biological questions. Light field microscopy is a computational imaging technique that captures 3D information in a single camera shot. In contrast to many other methods of 3D imaging, light field requires only a simple optical setup and no moving parts—making it ideally suited to fast volumetric imaging. This thesis presents the development and characterisation of the first light field-based 3D imaging flow cytometry platform and its application to characterising cellular heterogeneity when imaging protein trafficking in live cells. The development of an optical system suited to large depth-of-field, multi-channel 3D imaging of flowing samples is presented. Design considerations in the excitation optics and the use of a light sheet in conjunction with light field imaging optics are explored, and methods of characterising the optical performance and 3D resolution in flow are presented. It is shown that the setup presented here achieves sub-cellular resolution across a 30 µm depth-range at a throughput-equivalent of > 100 cells per second. The performance of novel and established 3D reconstruction techniques is characterised, and methods of optimising for imaging in flow are explored. Additionally, the development of microfluidic devices and experimental methods aiming to maximise throughput are presented. Finally, the instrumentation developed here was applied to live-cell imaging in flow to track protein trafficking in 3D. The spatial distribution of a type-1 membrane protein (LAMP-1) was imaged at multiple time points and analysed to reveal the heterogeneity in trafficking rate across large numbers of cells. In summary, this thesis charts the development, characterisation, optimisation, and application of a novel 3D imaging flow cytometry system, with the aim of advancing our understanding of cellular morphological heterogeneity.Item Open Access Single-molecule orientation estimation using a polarisation cameraBruggeman, Ezra; Bruggeman, Ezra [0000-0001-6100-1443]This thesis presents the development of a new optical imaging method for measuring the orientation and position of single fluorescent molecules. The method - named POLCAM - is based on the use of a polarisation camera. Current methods for single-molecule orientation estimation require optical setups and algorithms that can be prohibitively slow and complex, limiting the widespread adoption of these methods for biological applications. In this work, a polarisation camera is used to dramatically simplify the experimental setup required for single-molecule orientation estimation; the method can be easily implemented on any wide-field fluorescence microscope, making it highly accessible to biological research labs. As polarisation cameras are not designed with highly sensitive applications like single-molecule detection in mind, this work includes an in-depth characterisation of a commercial polarisation camera, and a comparison with the state-of-the-art cameras that are typically used in single-molecule microscopy. This work also includes the development of optical simulation software to generate realistic single-molecule polarisation camera images. This simulation software is then used to validate and test the limits of the data analysis software developed as part of this work, including a fast algorithm based on Stokes parameter estimation. The developed algorithm can operate over 1.000-fold faster than the state of the art, enabling near instant determination of molecular orientation. Finally, to illustrate the potential of POLCAM in the life sciences, we applied our method to study alpha-synuclein fibrils and the actin cytoskeleton of mammalian cells.Item Embargo The Atom Surface Site Interaction Point Approach to Non-Covalent InteractionsZator, KatarzynaAdvances in theoretical chemistry allowed us to discover the equations that describe the electronic structure of the atoms but also informed us that such accurate calculations are very expensive indeed. To look at larger supramolecular or biomolecular systems, or to investigate the effects of solvent, simplifications needed to be introduced that compromise the quality of the result, and the henceforth arising errors ought to be carefully considered. Furthermore, for many molecular design campaigns, the aim is not merely in learning about a single system, but the discovery of one with desirable properties, hence we need a reliable way of canvassing chemical space to find a molecule of interest. We have used DFT to develop the Atom Surface Site Interaction Point (AIP) approach to quantify all non-covalent interactions (NCIs) a molecule is capable of making with the environment, including solvent or any other binding partner in the liquid phase. The approach consists of an AIP description of molecules and a function that considers interactions between them. The description relies on linear fits between molecular electrostatic potential values and experimen tally determined hydrogen bonding parameters and has been extended to describe the molecules whole. The description has been tested with the free energy of transfer from n-hexadecane to water and showed good systematic prediction of phase transfer (RMSD of 5.2 kJ mol-1). To consider interactions between two small molecules, we developed a custom pairing algorithm which identifies AIPs that are interacting at molecular interfaces and calculates the free energy of binding by summing over all pairwise interactions. Each such interaction has associated electrostatic and non-polar components and includes desolvation free energy. The method was optimised using experimentally measured free energies for aromatic interactions to test the predictive power of the approach in a simple well-defined system. The method is fast and produces interpretable binding free energies, as well as a graphical representation of the NCIs as Interaction Maps, that allow interpretation of the key contributions to the binding. The method has been applied to host-guest complexes in a variety of solvents. We also investigated protein-ligand scoring to assess the usability of the AIP approach in drug discovery. Using the CASF framework and dataset of diverse X-ray protein-ligand structures, we evaluated the AIP approach as a scoring function. It performs on par with the best available functions in the field and, furthermore, gives physical and accurate estimates of free energies of binding (RMSD of 10.3 kJ mol-1). For a protein-ligand system of many ligands against a single EPHB4 protein, the AIP approach performed comparably to state-of-the-art free energy perturbation calculations. Therefore, the knowledge of non-covalent interactions obtained using the AIP approach can be used not only to judge promising ligand leads but also to design better binding ligands overall.Item Embargo Dissecting the Architectural Properties of Chromatin and the Influence of the H1 Linker Histone on Chromatin RegulationPhillips, Charles; Phillips, Charles [0000-0002-1417-842X]In this research, I used an existing coarse-grained chromatin model from the Collepardo Lab to study the binding of the H1 linker histone to chromatin and delve into the intrinsic properties of chromatin that regulate its architecture. The primary aim is to decipher the factors modulating chromatin organisation using a chemically-specific molecular model. I first analysed chromatin’s architecture in relation to nucleosome repeat lengths and salt concentration. A key distinction between chromatin structures with DNA linker lengths of 10n and 10n + 5 base pairs is the uniquely ordered zig-zag conformation in specific 10n systems. Consistent with the paramount physicochemical diversity of chromatin and the paradigm of phase separation, the organisation of chromatin inside the nucleus, from the nanoscale to the whole nucleus scale, has been shown to be highly heterogenous and dynamic. At the nanoscale, the heterogenous behaviour of chromatin is termed “liquid-like”. I explore how local organisation of chromatin results in liquid-like chromatin behaviour. The next section of my work explores the function of the H1 linker histone and its impact on nucleosomal interactions governing chromatin structural fluctuations. The study explores H1’s interaction with mononucleosomes, elucidating the roles of core histone tails in defining H1 mobility and illustrating how H1 governs chromatin architecture under varying conditions. I also examine the effect of different H1 variants on chromatin architecture. In collaboration with Professor Kazushiro Maeshima at the National Institute of Genetics, I further studied H1 mobility in H1 and HMGA1-rich settings. Through advanced modelling techniques and multi-disciplinary collaborations, my research provides a valuable contribution to the field of chromatin biology and beyond. My findings could have profound implications for our understanding of life at the molecular level, opening up new avenues of inquiry and potential applications in biotechnology and medicine.