155 research outputs found
Investigating the effects of palmitoylation on the dopamine 1 receptor (D1)
The dopamine D1 receptor (D1) is a G protein-coupled receptor (GPCR) which regulates various key brain functions like attention, movement, reward, and memory. Understanding D1 signalling may open the horizon for novel treatments for neurological disorders. Upon agonist activation, the heterotrimeric G proteins Gαs activate adenylyl cyclase to increase cAMP/PKA signalling. D1 also engages β-arrestin proteins leading to β-arrestin dependent signalling. The D1 has two palmitoylation sites on cysteines 347&351 in its C-tail domain. However, the distinct roles and implications of palmitoylation on the D1 signalling, trafficking and β-arrestins recruitment are still largely unexplored. A palmitoylation D1 mutant was generated and luminescent based techniques such as BRET and split-Nanoluc complementation assay were employed, to delineate D1 palmitoylation effects on its pharmacology and signalling. The D1 agonists induced 50% less cAMP production in the mutant compared to wildtype (WT) and WT showed a more efficient dissociation of its Gαs. Moreover, the mutant receptor failed to recruit β-arrestin1&2, induced less ERK1/2 activation and internalises in an agonist-independent process while showing an altered intracellular Golgi trafficking. Also, in β-arrestin 1&2 KO HEK 293 cells similar cAMP production levels were reported for D1 WT and palmitoylation mutant. β-arrestin 1&2 KO blocked agonist-induced WT D1 plasma membrane trafficking, indicating that these β-arrestins are driving the differences between WT and the palmitoylation mutant D1. Taken together, our studies indicate that Gαs is the main transducer for D1 cAMP and ERK1/2 signalling and that palmitoylation is essential for its β-arrestin 1&2 interactions and modulating D1 signalling cascades in a drug-dependant process
The art of PCR assay development: data-driven multiplexing
The present thesis describes the discovery and application of a novel methodology, named Data-Driven Multiplexing, which uses artificial intelligence and conventional molecular instruments to develop rapid, scalable and cost-effective clinical diagnostic tests.
Detection of genetic material from living organisms is a biologically engineered process where organic molecules interact with each other and with chemical components to generate a meaningful signal of the presence, quantity or quality of target nucleic acids. Nucleic acid detection, such as DNA or RNA detection, identifies a specific organism based on its genetic material. In particular, DNA amplification approaches, such as for antimicrobial resistance (AMR) or COVID-19 detection, are crucial for diagnosing and managing various infectious diseases. One of the most widely used methods is Polymerase Chain Reaction (PCR), which can detect the presence of nucleic acids rapidly and accurately. The unique interaction of the genetic material and synthetic short DNA sequences called primers enable this harmonious biological process. This thesis aims to bioinformatically modulate the interaction between primers and genetic material, enhancing the diagnostic capabilities of conventional PCR instruments by applying artificial intelligence processing to the resulting signals.
To achieve the goal mentioned above, experiments and data from several conventional platforms, such as real-time and digital PCR, are used in this thesis, along with state-of-the-art and innovative algorithms for classification problems and final application in real-world clinical scenarios. This work exhibits a powerful technology to optimise the use of the data, conveying the following message: the better use of the data in clinical diagnostics enables higher throughput of conventional instruments without the need for hardware modification, maintaining the standard practice workflows.
In Part I, a novel method to analyse amplification data is proposed. Using a state-of-the-art digital PCR instrument and multiplex PCR assays, we demonstrate the simultaneous detection of up to nine different nucleic acids in a single-well and single-channel format. This novel concept called Amplification Curve Analysis (ACA) leverages kinetic information encoded in the amplification curve to classify the biological nature of the target of interest. This method is applied to the novel design of PCR assays for multiple detections of AMR genes and further validated with clinical samples collected at Charing Cross Hospital, London, UK. The ACA showed a high classification accuracy of 99.28% among 253 clinical isolates when multiplexing. Similar performance is also demonstrated with isothermal amplification chemistries using synthetic DNA, showing a 99.9% of classification accuracy for detecting respiratory-related infectious pathogens.
In Part II, two intelligent mathematical algorithms are proposed to solve two significant challenges when developing a Data-driven multiplex PCR assay. Chapter 7 illustrates the use of filtering algorithms to remove the presence of outliers in the amplification data. This demonstrates that the information contained in the kinetics of the reaction itself provides a novel way to remove non-specific and not efficient reactions. By extracting meaningful features and adding custom selection parameters to the amplification data, we increase the machine learning classifier performance of the ACA by 20% when outliers are removed. In Chapter 8, a patented algorithm called Smart-Plexer is presented. This allows the hybrid development of multiplex PCR assays by computing the optimal single primer set combination in a multiplex assay. The algorithm's effectiveness stands in using experimental laboratory data as input, avoiding heavy computation and unreliable predictions of the sigmoidal shape of PCR curves. The output of the Smart-Plexer is an optimal assay for the simultaneous detection of seven coronavirus-related pathogens in a single well, scoring an accuracy of 98.8% in identifying the seven targets correctly among 14 clinical samples. Moreover, Chapter 9 focuses on applying novel multiplex assays in point-of-care devices and developing a new strategy for improving clinical diagnostics.
In summary, inspired by the emerging requirement for more accurate, cost-effective and higher throughput diagnostics, this thesis shows that coupling artificial intelligence with assay design pipelines is crucial to address current diagnostic challenges. This requires crossing different fields, such as bioinformatics, molecular biology and data science, to develop an optimal solution and hence to maximise the value of clinical tests for nucleic acid detection, leading to more precise patient treatment and easier management of infectious control.Open Acces
Exploring QCD matter in extreme conditions with Machine Learning
In recent years, machine learning has emerged as a powerful computational
tool and novel problem-solving perspective for physics, offering new avenues
for studying strongly interacting QCD matter properties under extreme
conditions. This review article aims to provide an overview of the current
state of this intersection of fields, focusing on the application of machine
learning to theoretical studies in high energy nuclear physics. It covers
diverse aspects, including heavy ion collisions, lattice field theory, and
neutron stars, and discuss how machine learning can be used to explore and
facilitate the physics goals of understanding QCD matter. The review also
provides a commonality overview from a methodology perspective, from
data-driven perspective to physics-driven perspective. We conclude by
discussing the challenges and future prospects of machine learning applications
in high energy nuclear physics, also underscoring the importance of
incorporating physics priors into the purely data-driven learning toolbox. This
review highlights the critical role of machine learning as a valuable
computational paradigm for advancing physics exploration in high energy nuclear
physics.Comment: 146 pages,53 figure
Studium etiopatogeneze mitochondriálních onemocnění
Mitochondrial disorders are a clinically, biochemically and genetically heterogeneous group of inherited disorders with a prevalence of about 1:5 000 live births. A common sign of those disorders is disruption of mitochondrial energetic metabolism. To this day, more than 400 genes have been associated with mitochondrial disorders, but 45% of patients are still without a genetic diagnosis. Using next-generation sequencing, new candidate genes or variants are found. To confirm the causality of those newly found genes or variants, biochemical characterisation using a plethora of various methods is necessary. The first aim of this thesis was to study the function of ACBD3 protein on mitochondrial energetic metabolism in non-steroidogenic cells HEK293 and HeLa and to confirm the causality of the ACBD3 gene in a patient with combined oxidative phosphorylation (OXPHOS) deficit. The second aim was to confirm the causality of two novel variants in MT-ND1 and MT-ND5 genes, which encode structural subunits of complex I (CI) of the respiratory chain. The third aim of the thesis was to study the formation of supercomplexes (SCs) in patients with rare metabolic diseases. Using functional studies, we showed in this thesis that ACBD3 protein has no essential function in mitochondria but plays an important role in...Mitochondriální onemocnění představují klinicky, biochemicky i geneticky heterogenní skupinu dědičných onemocnění, jež prevalence je přibližně 1:5 000 živě narozených dětí. Společným znakem těchto onemocnění je narušení mitochondriálního energetického metabolismu. V současné době je známo více než 400 genů asociovaných s mitochondriálním onemocněním, avšak 45 % pacientů s podezřením na mitochondriální onemocnění je stále bez potvrzené genetické příčiny. Pomocí sekvenování nové generace nacházíme nové kandidátní geny anebo varianty, které by mohly stát za příčinou onemocnění. Abychom mohli potvrdit kauzalitu těchto nově nalezených genů a variant, je třeba charakterizovat deficit pomocí řady biochemických metod. Cílem této práce bylo studovat funkci proteinu ACBD3 na úrovni mitochondriálního energetického metabolismu v ne-steroidních buňkách HEK293 a HeLa a potvrdit tak kauzalitu genu ACBD3 u pacientky s kombinovaným deficitem systému oxidativní fosforylace (OXPHOS). Druhým cílem bylo potvrdit kauzalitu dvou nových variant v genech MT-ND1 a MT-ND5, kódujících strukturní podjednotky komplexu I (KI) dýchacího řetězce. Třetím cílem práce bylo studovat tvorbu superkomplexů u pacientů se vzácnými dědičnými metabolickými poruchami. V předkládané dizertační práci se podařilo pomocí funkční studie proteinu...Klinika pediatrie a dědičných poruch metabolismu 1. LF UK a VFNDepartment of Pediatrics and Inherited Metabolic Disorders First Faculty of Medicine Charles University and General University Hospital in PragueFirst Faculty of Medicine1. lékařská fakult
Novel fluorescence-based tools and applications for characterizing emerging pathways of α-synuclein amyloid aggregation, disaggregation and inhibition
Habitualmente se denomina agregación amiloide a aquel proceso de malplegamiento proteico que comprende la transición de una proteína soluble y funcional a especies oligoméricas intermedias y, en última instancia, fibras insolubles con una estructura característica llamada de lámina β cruzada. Varias enfermedades neurodegenerativas se encuentran asociadas a este proceso, entre las que se encuentra la enfermedad de Párkinson (PD en inglés). Esta se caracteriza por unos depósitos intracelulares, denominados cuerpos o neuritas de Lewy, ricos en α-sinucleína (αS) en forma de agregados amiloides. αS es una proteína intrínsecamente desordenada de 140 aminoácidos que se expresa ampliamente en el cuerpo humano, especialmente en el sistema nervioso central. Su agregación amiloide también está vinculada con otras sinucleinopatías como demencia con cuerpos de Lewy, atrofia sistémica múltiple y enfermedad de Alzheimer (AD en inglés). A pesar de que los factores que provocan el autoensamblado amiloide de αS in vivo son desconocidos, algunos estudios in vitro son capaces de reproducir tal agregación. Habitualmente, lo hacen mediante el uso de interfases de carácter hidrofóbico/hidrofílico que catalizan los primeros contactos entre proteínas en un proceso llamado nucleación primaria. Las estructuras amiloides formadas mediante este mecanismo de nucleación heterogénea poseen una disposición inter-molecular paralela. En este trabajo, hemos logrado inducir y analizar el autoensamblado amiloide de αS en ausencia de interfases bajo condiciones de hidratación limitada. La agregación ocurre en el seno de la disolución mediante una nucleación, por tanto, homogénea. Mediante el empleo de la espectroscopia de fluorescencia de pireno hemos demostrado que, siguiendo este nuevo mecanismo de nucleación, los agregados adoptan una topología antiparalela. Además, hemos observado que este tipo de nucleación podría estar favorecida en el interior de condensados biomoleculares de αS generados a través de separación de fases líquido líquido (LLPS en inglés), donde la hidratación de la proteína se ve reducida. Aplicando una combinación de técnicas biofísicas, hemos estudiado cuantitativamente la capacidad de αS y de la proteína Tau para sufrir LLPS. Entre estas técnicas, hemos empleado microscopía de tiempo de vida fluorescente (FLIM en inglés), al nivel de condensados individuales, para demostrar la maduración en el tiempo de estos, gracias a la exquisita resolución temporal y espacial de FLIM. Hemos descubierto que αS y Tau sí forman condensados biomoleculares mixtos y que, con el tiempo, forman heteroagregados amiloides en el interior de estos coacervados mediante la denominada transición de fases líquido-solido (LSPT en inglés). Cabe destacar que hemos esclarecido que el principal factor que regula esta LSPT es la valencia y ocupación de las interacciones heterotípicas,y no la dinámica de las cadenas polipeptídicas como se ha descrito frecuentemente paraotros sistemas. Nuestros resultados ayudan a establecer un escenario relevante para la co-agregación de ambas proteínas que podría explicar el hecho de que se observen, conjuntamente, tanto en PD como en AD. Además, hemos contribuido al campo de LLPS-LSPT proporcionando una descripción detallada y cuantitativa de sistemas αS/policatión con técnicas avanzadas y complementarias, incluyendo el estudio de coacervados individuales. Esto podría servir como base para el estudio de una amplia variedad de condensados biomoleculares y de especial interés para caracterizar la relación entre estos y la agregación amiloide.Por otra parte, encontrar moléculas con potencial terapéutico o diagnóstico en enfermedades neurodegenerativas es de una importancia extrema. Sin embargo, la complejidad y heterogeneidad en el paisaje conformacional de la agregación amiloide hacen de esta una diana destacablemente complicada para los estudios habituales de cribado de fármacos basados en ensayos de interacción molecular. En esta tesis hemos establecido una estrategia experimental que combina la espectroscopia de correlación cruzada de fluorescencia y la espectroscopia de fluorescencia de partícula individual de dos colores (dcFCCS/dcSPFS en inglés), y la hemos empleado para investigar la unión de pequeñas moléculas a especies amiloides neurotóxicas de αS con resolución de partícula individual y con independencia de las heterogeneidades moleculares del sistema de estudio. Gracias a la observación de los eventos de interacción de uno en uno, hemos resuelto de manera directa la especificidad, afinidad y estequiometría de unión de varios pequeños péptidos inhibidores de la agregación amiloide de αS, entre los cuales se incluye un péptido humano. Hemos descrito en detalle su mecanismo molecular de actuación y desentrañado las propiedades físico-químicas que respaldan la interacción, contribuyendo al diseño racional de otros péptidos candidatos a fármaco.El uso dcFCCS/dcSPFS puede ampliarse a otras situaciones de interacción multiligando/ receptor multimérico y convertirse en una plataforma experimental para el descubrimiento de nuevos fármacos y marcadores diagnósticos específicos de amiloide. Por último, además de inhibir el proceso de autoensamblado, la desagregación de fibras amiloides puede ser una herramienta para combatir la neurodegeneración. Dentro de las células, esta tarea es llevada a cabo sobre fibras de αS por una maquinaria especializada de chaperonas conocida como la desagregasa humana. Sin embargo, el mecanismo preciso por el cual este complejo proteico procesa las fibras, así como el posible vínculo entre la toxicidad y estructura de un agregado y la actividad desagregasa sobre el mismo es un tema todavía bajo intenso debate. Uno de los principales retos es la obtención de datos cinéticos fiables y de calidad de la reacción de desensamblado, debido a artefactos de la técnica más extensamente usada: la fluorescencia de la sonda tioflavina-T. En nuestro trabajo hemos aplicado la fluorescencia de pireno junto con la desextinción de fluorescencia para afrontar este problema. Hemos logrado probar un mecanismo de desagregación de todo o nada, por el cual cada fibra se desensambla y libera monómeros solubles de αS mediante un mecanismo de cremallera. Nuestros datos cinéticos han permitido el modelado cuantitativo del mecanismo de desagregación sobre diferentes estructuras amiloides de αS. Estos resultados han revelado que, probablemente, la desagregasa humana ha evolucionado para actuar específicamente sobre agregados pequeños y citotóxicos.En resumen, hemos implementado nuevas herramientas y aplicaciones de fluorescencia, incluyendo técnicas de fluorescencia resueltas en el tiempo y de partícula única de dos colores, para el estudio detallado de la agregación amiloide, transición de fases, inhibición y desagregación de αS. En conjunto, nuestros resultados contribuyen a responder preguntas clave de la agregación amiloide de αS y de la búsqueda de estrategias terapéuticas contra las sinucleinopatías. Además, los enfoques experimentales presentados en esta tesis se pueden aplicar para comprender y actuar sobre otros sistemas amiloides, siendo por tanto herramientas metodológicas relevantes en el campo de la agregación amiloide y la neurodegeneración.Amyloid aggregation is typically referred to as a protein misfolding process involving the transition from a functional, soluble protein into oligomeric intermediates and, eventually, insoluble fibrils with a hallmark cross-β structure. A number of neurodegenerative diseases are associated to this process, including Parkinson’s disease (PD), which is characterized by intracellular deposits rich in α-synuclein (αS) in the form of amyloid aggregates, which are referred to as Lewy bodies (LB) or neurites. αS is an intrinsically disordered 140-aminoacid protein widely expressed throughout the body, particularly in the central nervous system. Its amyloid aggregation is also associated with other synucleinopathies such as dementia with Lewy bodies (DLB), multiple system atrophy (MSA) or Alzheimer’s disease (AD). While the factors triggering the amyloid self-assembly of αS in vivo are still obscure, in vitro studies are able to reproduce the aggregation, typically using hydrophobic/hydrophilic interfaces to trigger the first protein-protein contacts, a process termed primary nucleation. The amyloid structures resulting from this (heterogeneous) nucleation show a parallel inter-molecular arrangement. In this work, we were able to induce and analyze the amyloid self-assembly of αS in the absence of interfaces in the bulk of the solution (homogeneous nucleation) under limited hydration conditions. By using pyrene fluorescence spectroscopy we proved that, via this new type of nucleation, the aggregates adopt an antiparallel topology. Moreover, we have observed that this type of nucleation could be favorable in the interior of αS condensates generated by liquid-liquid phase separation (LLPS). By using a combination of biophysical techniques, we quantitatively interrogated the ability of αS and the protein Tau to undergo LLPS. Among these techniques, we used fluorescence lifetime imaging microscopy (FLIM) down to the single-coacervate level, to resolve their maturation without ambiguity, owing to the exquisite temporal and spatial resolution of FLIM. We found that, indeed, αS and Tau form mixed biomolecular condensates by complex elecotrostatic coacervation and, over time, they form amyloid heteroaggregates through liquid-to-solid phase transition (LSPT) in the interior of the condensates. Interestingly, we proved that the valence and occupancy of the heterotypic interactions, and not the polypeptide dynamics, are the main factor governing LSPT. Our results help establishing a relevant scenario for the co-aggregation of both proteins which could explain their joint presence in both PD and AD. Besides, we have contributed to the LLPS-LSPT field by providing a thourough, quantitative description of αS/polycation systems with advanced and complementary techniques and by looking at single coacervates. This could serve as a framework to be used in a wide array of biomolecular condensates, and of particular interest for characterizing the link between these and amyloid aggregation. Finding molecules with therapeutic or diagnosic potential in neurodegenerative disorders is of utter importance. However, the complexity and heterogeneity of the amyloid conformational landscape, makes amyloid aggregation a tremendously challenging target for typical drug screens based in molecular interaction assays. Here, we established an experimental strategy which combines dual-color fluorescence correlation spectroscopy and single-particle fluorescence spectroscopy (dcFCCS/dcSPFS) to investigate the binding of small molecules to amyloid species of αS with single-particle resolution and regardless of molecular heterogeneity. By observing binding events individually, we gained direct access to the binding specificity, affinity and stoichiometry of several small amyloid inhibitory peptides, including a human peptidic molecule. We demonstrated its molecular mechanism of action and disentangled the minimum physico-chemical properties behind the binding properties, thus aiding in the rational design of other peptide drug candidates. dcFCCS/dcSPFS could be extended to other multi-ligand/multimeric receptor interaction scenarios and serve as a platform for finding new drugs and amyloid-specific diagnostic probes. Besides inhibiting the self-assembly process, the disaggregation of amyloid fibrils can be a tool for fighting neurodegeneration. In the cell, such task is performed on αS fibrils by an evolutionary refined chaperone machinery termed the human disaggregase. However, the exact mechanism by which this proteic complex processes the fibrils as well as what is the relationship between aggregate toxicity, structure and disaggregase activity remains under debate. A major challenge is to obtain reliable kinetic data of the disassembly reaction due to artifacts related to the most commonly used amyloid probe, thioflavin-T (ThT). In our work, we have applied pyrene fluorescence together with fluorescence dequenching to solving this problem. We demonstrated an all-or-none disassembly mechanism, where a fibril disassembles entirely into soluble monomers by an unzipping mechanism. Our kinetic data enabled to quantitatively model the disaggregation mechanism on different amyloid assemblies of αS. Our results revealed that the chaperone machinery has likely evolved to tackle small cytotoxic aggregates specifically. In summary, we have implemented new fluorescence-based tools and applications, including time-resolved and single-particle dual-color fluorescence techniques, to the detailed investigation of amyloid aggregation, phase separation, inhibition and disaggregation of αS. Collectively, our results help to understand key questions of αS amyloid aggregation and potential therapeutic strategies against synucleinopathies. In addition, the experimental approaches presented in this thesis can be also easily extended to understand and tackle other amyloid systems, representing important methodological tools in the fields of amyloid aggregation and neurodegeneration.<br /
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