@phdthesis{12470, abstract = {The brain is an exceptionally sophisticated organ consisting of billions of cells and trillions of connections that orchestrate our cognition and behavior. To decode its complex connectivity, it is pivotal to disentangle its intricate architecture spanning from cm-sized circuits down to tens of nm-small synapses. To achieve this goal, I developed CATS – Comprehensive Analysis of nervous Tissue across Scales, a versatile toolbox for obtaining a holistic view of nervous tissue context with (superresolution) fluorescence microscopy. CATS combines comprehensive labeling of the extracellular space, that is compatible with chemical fixation, with information on molecular markers, superresolved data acquisition and machine-learning based data analysis for segmentation and synapse identification. I used CATS to analyze key features of nervous tissue connectivity, ranging from whole tissue architecture, neuronal in- and output-fields, down to synapse morphology. Focusing on the hippocampal circuitry, I quantified synaptic transmission properties of mossy fiber boutons and analyzed the connectivity pattern of dentate gyrus granule cells with CA3 pyramidal neurons. This shows that CATS is a viable tool to study hallmarks of neuronal connectivity with light microscopy.}, author = {Michalska, Julia M}, isbn = { 978-3-99078-026-8}, issn = {2663-337X}, pages = {201}, publisher = {Institute of Science and Technology Austria}, title = {{A versatile toolbox for the comprehensive analysis of nervous tissue organization with light microscopy}}, doi = {10.15479/at:ista:12470}, year = {2023}, } @phdthesis{12491, abstract = {The extracellular matrix (ECM) is a hydrated and complex three-dimensional network consisting of proteins, polysaccharides, and water. It provides structural scaffolding for the cells embedded within it and is essential in regulating numerous physiological processes, including cell migration and proliferation, wound healing, and stem cell fate. Despite extensive study, detailed structural knowledge of ECM components in physiologically relevant conditions is still rudimentary. This is due to methodological limitations in specimen preparation protocols which are incompatible with keeping large samples, such as the ECM, in their native state for subsequent imaging. Conventional electron microscopy (EM) techniques rely on fixation, dehydration, contrasting, and sectioning. This results in the alteration of a highly hydrated environment and the potential introduction of artifacts. Other structural biology techniques, such as nuclear magnetic resonance (NMR) spectroscopy and X-ray crystallography, allow high-resolution analysis of protein structures but only work on homogenous and purified samples, hence lacking contextual information. Currently, no approach exists for the ultrastructural and structural study of extracellular components under native conditions in a physiological, 3D environment. In this thesis, I have developed a workflow that allows for the ultrastructural analysis of the ECM in near-native conditions at molecular resolution. The developments I introduced include implementing a novel specimen preparation workflow for cell-derived matrices (CDMs) to render them compatible with ion-beam milling and subsequent high-resolution cryo-electron tomography (ET). To this end, I have established protocols to generate CDMs grown over several weeks on EM grids that are compatible with downstream cryo-EM sample preparation and imaging techniques. Characterization of these ECMs confirmed that they contain essential ECM components such as collagen I, collagen VI, and fibronectin I in high abundance and hence represent a bona fide biologically-relevant sample. I successfully optimized vitrification of these specimens by testing various vitrification techniques and cryoprotectants. In order to obtain high-resolution molecular insights into the ultrastructure and organization of CDMs, I established cryo-focused ion beam scanning electron microscopy (FIBSEM) on these challenging and complex specimens. I explored different approaches for the creation of thin cryo-lamellae by FIB milling and succeeded in optimizing the cryo-lift-out technique, resulting in high-quality lamellae of approximately 200 nm thickness. High-resolution Cryo-ET of these lamellae revealed for the first time the architecture of native CDM in the context of matrix-secreting cells. This allowed for the in situ visualization of fibrillar matrix proteins such as collagen, laying the foundation for future structural and ultrastructural characterization of these proteins in their near-native environment. In summary, in this thesis, I present a novel workflow that combines state-of-the-art cryo-EM specimen preparation and imaging technologies to permit characterization of the ECM, an important tissue component in higher organisms. This innovative and highly versatile workflow will enable addressing far-reaching questions on ECM architecture, composition, and reciprocal ECM-cell interactions.}, author = {Zens, Bettina}, isbn = {978-3-99078-027-5}, issn = {2663-337X}, keywords = {cryo-EM, cryo-ET, FIB milling, method development, FIBSEM, extracellular matrix, ECM, cell-derived matrices, CDMs, cell culture, high pressure freezing, HPF, structural biology, tomography, collagen}, pages = {187}, publisher = {Institute of Science and Technology Austria}, title = {{Ultrastructural characterization of natively preserved extracellular matrix by cryo-electron tomography}}, doi = {10.15479/at:ista:12491}, year = {2023}, } @phdthesis{12716, abstract = {The process of detecting and evaluating sensory information to guide behaviour is termed perceptual decision-making (PDM), and is critical for the ability of an organism to interact with its external world. Individuals with autism, a neurodevelopmental condition primarily characterised by social and communication difficulties, frequently exhibit altered sensory processing and PDM difficulties are widely reported. Recent technological advancements have pushed forward our understanding of the genetic changes accompanying this condition, however our understanding of how these mutations affect the function of specific neuronal circuits and bring about the corresponding behavioural changes remains limited. Here, we use an innate PDM task, the looming avoidance response (LAR) paradigm, to identify a convergent behavioural abnormality across three molecularly distinct genetic mouse models of autism (Cul3, Setd5 and Ptchd1). Although mutant mice can rapidly detect threatening visual stimuli, their responses are consistently delayed, requiring longer to initiate an appropriate response than their wild-type siblings. Mutant animals show abnormal adaptation in both their stimulus- evoked escape responses and exploratory dynamics following repeated stimulus presentations. Similarly delayed behavioural responses are observed in wild-type animals when faced with more ambiguous threats, suggesting the mutant phenotype could arise from a dysfunction in the flexible control of this PDM process. Our knowledge of the core neuronal circuitry mediating the LAR facilitated a detailed dissection of the neuronal mechanisms underlying the behavioural impairment. In vivo extracellular recording revealed that visual responses were unaffected within a key brain region for the rapid processing of visual threats, the superior colliculus (SC), indicating that the behavioural delay was unlikely to originate from sensory impairments. Delayed behavioural responses were recapitulated in the Setd5 model following optogenetic stimulation of the excitatory output neurons of the SC, which are known to mediate escape initiation through the activation of cells in the underlying dorsal periaqueductal grey (dPAG). In vitro patch-clamp recordings of dPAG cells uncovered a stark hypoexcitability phenotype in two out of the three genetic models investigated (Setd5 and Ptchd1), that in Setd5, is mediated by the misregulation of voltage-gated potassium channels. Overall, our results show that the ability to use visual information to drive efficient escape responses is impaired in three diverse genetic mouse models of autism and that, in one of the models studied, this behavioural delay likely originates from differences in the intrinsic excitability of a key subcortical node, the dPAG. Furthermore, this work showcases the use of an innate behavioural paradigm to mechanistically dissect PDM processes in autism.}, author = {Burnett, Laura}, issn = {2663-337X}, pages = {178}, publisher = {Institute of Science and Technology Austria}, title = {{To flee, or not to flee? Using innate defensive behaviours to investigate rapid perceptual decision-making through subcortical circuits in mouse models of autism}}, doi = {10.15479/at:ista:12716}, year = {2023}, } @phdthesis{12726, abstract = {Most motions of many-body systems at any scale in nature with sufficient degrees of freedom tend to be chaotic; reaching from the orbital motion of planets, the air currents in our atmosphere, down to the water flowing through our pipelines or the movement of a population of bacteria. To the observer it is therefore intriguing when a moving collective exhibits order. Collective motion of flocks of birds, schools of fish or swarms of self-propelled particles or robots have been studied extensively over the past decades but the mechanisms involved in the transition from chaos to order remain unclear. Here, the interactions, that in most systems give rise to chaos, sustain order. In this thesis we investigate mechanisms that preserve, destabilize or lead to the ordered state. We show that endothelial cells migrating in circular confinements transition to a collective rotating state and concomitantly synchronize the frequencies of nucleating actin waves within individual cells. Consequently, the frequency dependent cell migration speed uniformizes across the population. Complementary to the WAVE dependent nucleation of traveling actin waves, we show that in leukocytes the actin polymerization depending on WASp generates pushing forces locally at stationary patches. Next, in pipe flows, we study methods to disrupt the self–sustaining cycle of turbulence and therefore relaminarize the flow. While we find in pulsating flow conditions that turbulence emerges through a helical instability during the decelerating phase. Finally, we show quantitatively in brain slices of mice that wild-type control neurons can compensate the migratory deficits of a genetically modified neuronal sub–population in the developing cortex.}, author = {Riedl, Michael}, issn = {2663-337X}, pages = {260}, publisher = {Institute of Science and Technology Austria}, title = {{Synchronization in collectively moving active matter}}, doi = {10.15479/at:ista:12726}, year = {2023}, } @phdthesis{12732, abstract = {Nonergodic systems, whose out-of-equilibrium dynamics fail to thermalize, provide a fascinating research direction both for fundamental reasons and for application in state of the art quantum devices. Going beyond the description of statistical mechanics, ergodicity breaking yields a new paradigm in quantum many-body physics, introducing novel phases of matter with no counterpart at equilibrium. In this Thesis, we address different open questions in the field, focusing on disorder-induced many-body localization (MBL) and on weak ergodicity breaking in kinetically constrained models. In particular, we contribute to the debate about transport in kinetically constrained models, studying the effect of $U(1)$ conservation and inversion-symmetry breaking in a family of quantum East models. Using tensor network techniques, we analyze the dynamics of large MBL systems beyond the limit of exact numerical methods. In this setting, we approach the debated topic of the coexistence of localized and thermal eigenstates separated by energy thresholds known as many-body mobility edges. Inspired by recent experiments, our work further investigates the localization of a small bath induced by the coupling to a large localized chain, the so-called MBL proximity effect. In the first Chapter, we introduce a family of particle-conserving kinetically constrained models, inspired by the quantum East model. The system we study features strong inversion-symmetry breaking, due to the nature of the correlated hopping. We show that these models host so-called quantum Hilbert space fragmentation, consisting of disconnected subsectors in an entangled basis, and further provide an analytical description of this phenomenon. We further probe its effect on dynamics of simple product states, showing revivals in fidelity and local observalbes. The study of dynamics within the largest subsector reveals an anomalous transient superdiffusive behavior crossing over to slow logarithmic dynamics at later times. This work suggests that particle conserving constrained models with inversion-symmetry breaking realize new universality classes of dynamics and invite their further theoretical and experimental studies. Next, we use kinetic constraints and disorder to design a model with many-body mobility edges in particle density. This feature allows to study the dynamics of localized and thermal states in large systems beyond the limitations of previous studies. The time-evolution shows typical signatures of localization at small densities, replaced by thermal behavior at larger densities. Our results provide evidence in favor of the stability of many-body mobility edges, which was recently challenged by a theoretical argument. To support our findings, we probe the mechanism proposed as a cause of delocalization in many-body localized systems with mobility edges suggesting its ineffectiveness in the model studied. In the last Chapter of this Thesis, we address the topic of many-body localization proximity effect. We study a model inspired by recent experiments, featuring Anderson localized coupled to a small bath of free hard-core bosons. The interaction among the two particle species results in non-trivial dynamics, which we probe using tensor network techniques. Our simulations show convincing evidence of many-body localization proximity effect when the bath is composed by a single free particle and interactions are strong. We furthter observe an anomalous entanglement dynamics, which we explain through a phenomenological theory. Finally, we extract highly excited eigenstates of large systems, providing supplementary evidence in favor of our findings.}, author = {Brighi, Pietro}, issn = {2663-337X}, pages = {158}, publisher = {Institute of Science and Technology Austria}, title = {{Ergodicity breaking in disordered and kinetically constrained quantum many-body systems}}, doi = {10.15479/at:ista:12732}, year = {2023}, } @phdthesis{12781, abstract = {Most energy in humans is produced in form of ATP by the mitochondrial respiratory chain consisting of several protein assemblies embedded into lipid membrane (complexes I-V). Complex I is the first and the largest enzyme of the respiratory chain which is essential for energy production. It couples the transfer of two electrons from NADH to ubiquinone with proton translocation across bacterial or inner mitochondrial membrane. The coupling mechanism between electron transfer and proton translocation is one of the biggest enigma in bioenergetics and structural biology. Even though the enzyme has been studied for decades, only recent technological advances in cryo-EM allowed its extensive structural investigation. Complex I from E.coli appears to be of special importance because it is a perfect model system with a rich mutant library, however the structure of the entire complex was unknown. In this thesis I have resolved structures of the minimal complex I version from E. coli in different states including reduced, inhibited, under reaction turnover and several others. Extensive structural analyses of these structures and comparison to structures from other species allowed to derive general features of conformational dynamics and propose a universal coupling mechanism. The mechanism is straightforward, robust and consistent with decades of experimental data available for complex I from different species. Cyanobacterial NDH (cyanobacterial complex I) is a part of broad complex I superfamily and was studied as well in this thesis. It plays an important role in cyclic electron transfer (CET), during which electrons are cycled within PSI through ferredoxin and plastoquinone to generate proton gradient without NADPH production. Here, I solved structure of NDH and revealed additional state, which was not observed before. The novel “resting” state allowed to propose the mechanism of CET regulation. Moreover, conformational dynamics of NDH resembles one in complex I which suggest more broad universality of the proposed coupling mechanism. In summary, results presented here helped to interpret decades of experimental data for complex I and contributed to fundamental mechanistic understanding of protein function. }, author = {Kravchuk, Vladyslav}, isbn = {978-3-99078-029-9}, issn = {2663-337X}, pages = {127}, publisher = {Institute of Science and Technology Austria}, title = {{Structural and mechanistic study of bacterial complex I and its cyanobacterial ortholog}}, doi = {10.15479/at:ista:12781}, year = {2023}, } @phdthesis{12885, abstract = {High-performance semiconductors rely upon precise control of heat and charge transport. This can be achieved by precisely engineering defects in polycrystalline solids. There are multiple approaches to preparing such polycrystalline semiconductors, and the transformation of solution-processed colloidal nanoparticles is appealing because colloidal nanoparticles combine low cost with structural and compositional tunability along with rich surface chemistry. However, the multiple processes from nanoparticle synthesis to the final bulk nanocomposites are very complex. They involve nanoparticle purification, post-synthetic modifications, and finally consolidation (thermal treatments and densification). All these properties dictate the final material’s composition and microstructure, ultimately affecting its functional properties. This thesis explores the synthesis, surface chemistry and consolidation of colloidal semiconductor nanoparticles into dense solids. In particular, the transformations that take place during these processes, and their effect on the material’s transport properties are evaluated. }, author = {Calcabrini, Mariano}, isbn = {978-3-99078-028-2}, issn = {2663-337X}, pages = {82}, publisher = {Institute of Science and Technology Austria}, title = {{Nanoparticle-based semiconductor solids: From synthesis to consolidation}}, doi = {10.15479/at:ista:12885}, year = {2023}, } @phdthesis{12897, abstract = {Inverse design problems in fabrication-aware shape optimization are typically solved on discrete representations such as polygonal meshes. This thesis argues that there are benefits to treating these problems in the same domain as human designers, namely, the parametric one. One reason is that discretizing a parametric model usually removes the capability of making further manual changes to the design, because the human intent is captured by the shape parameters. Beyond this, knowledge about a design problem can sometimes reveal a structure that is present in a smooth representation, but is fundamentally altered by discretizing. In this case, working in the parametric domain may even simplify the optimization task. We present two lines of research that explore both of these aspects of fabrication-aware shape optimization on parametric representations. The first project studies the design of plane elastic curves and Kirchhoff rods, which are common mathematical models for describing the deformation of thin elastic rods such as beams, ribbons, cables, and hair. Our main contribution is a characterization of all curved shapes that can be attained by bending and twisting elastic rods having a stiffness that is allowed to vary across the length. Elements like these can be manufactured using digital fabrication devices such as 3d printers and digital cutters, and have applications in free-form architecture and soft robotics. We show that the family of curved shapes that can be produced this way admits geometric description that is concise and computationally convenient. In the case of plane curves, the geometric description is intuitive enough to allow a designer to determine whether a curved shape is physically achievable by visual inspection alone. We also present shape optimization algorithms that convert a user-defined curve in the plane or in three dimensions into the geometry of an elastic rod that will naturally deform to follow this curve when its endpoints are attached to a support structure. Implemented in an interactive software design tool, the rod geometry is generated in real time as the user edits a curve and enables fast prototyping. The second project tackles the problem of general-purpose shape optimization on CAD models using a novel variant of the extended finite element method (XFEM). Our goal is the decoupling between the simulation mesh and the CAD model, so no geometry-dependent meshing or remeshing needs to be performed when the CAD parameters change during optimization. This is achieved by discretizing the embedding space of the CAD model, and using a new high-accuracy numerical integration method to enable XFEM on free-form elements bounded by the parametric surface patches of the model. Our simulation is differentiable from the CAD parameters to the simulation output, which enables us to use off-the-shelf gradient-based optimization procedures. The result is a method that fits seamlessly into the CAD workflow because it works on the same representation as the designer, enabling the alternation of manual editing and fabrication-aware optimization at will.}, author = {Hafner, Christian}, isbn = {978-3-99078-031-2}, issn = {2663-337X}, pages = {180}, publisher = {Institute of Science and Technology Austria}, title = {{Inverse shape design with parametric representations: Kirchhoff Rods and parametric surface models}}, doi = {10.15479/at:ista:12897}, year = {2023}, } @phdthesis{12964, abstract = {Pattern formation is of great importance for its contribution across different biological behaviours. During developmental processes for example, patterns of chemical gradients are established to determine cell fate and complex tissue patterns emerge to define structures such as limbs and vascular networks. Patterns are also seen in collectively migrating groups, for instance traveling waves of density emerging in moving animal flocks as well as collectively migrating cells and tissues. To what extent these biological patterns arise spontaneously through the local interaction of individual constituents or are dictated by higher level instructions is still an open question however there is evidence for the involvement of both types of process. Where patterns arise spontaneously there is a long standing interest in how far the interplay of mechanics, e.g. force generation and deformation, and chemistry, e.g. gene regulation and signaling, contributes to the behaviour. This is because many systems are able to both chemically regulate mechanical force production and chemically sense mechanical deformation, forming mechano-chemical feedback loops which can potentially become unstable towards spatio and/or temporal patterning. We work with experimental collaborators to investigate the possibility that this type of interaction drives pattern formation in biological systems at different scales. We focus first on tissue-level ERK-density waves observed during the wound healing response across different systems where many previous studies have proposed that patterns depend on polarized cell migration and arise from a mechanical flocking-like mechanism. By combining theory with mechanical and optogenetic perturbation experiments on in vitro monolayers we instead find evidence for mechanochemical pattern formation involving only scalar bilateral feedbacks between ERK signaling and cell contraction. We perform further modeling and experiment to study how this instability couples with polar cell migration in order to produce a robust and efficient wound healing response. In a following chapter we implement ERK-density coupling and cell migration in a 2D active vertex model to investigate the interaction of ERK-density patterning with different tissue rheologies and find that the spatio-temporal dynamics are able to both locally and globally fluidize a tissue across the solid-fluid glass transition. In a last chapter we move towards lower spatial scales in the context of subcellular patterning of the cell cytoskeleton where we investigate the transition between phases of spatially homogeneous temporal oscillations and chaotic spatio-temporal patterning in the dynamics of myosin and ROCK activities (a motor component of the actomyosin cytoskeleton and its activator). Experimental evidence supports an intrinsic chemical oscillator which we encode in a reaction model and couple to a contractile active gel description of the cell cortex. The model exhibits phases of chemical oscillations and contractile spatial patterning which reproduce many features of the dynamics seen in Drosophila oocyte epithelia in vivo. However, additional pharmacological perturbations to inhibit myosin contractility leaves the role of contractile instability unclear. We discuss alternative hypotheses and investigate the possibility of reaction-diffusion instability.}, author = {Boocock, Daniel R}, isbn = {978-3-99078-032-9}, issn = {2663-337X}, pages = {146}, publisher = {Institute of Science and Technology Austria}, title = {{Mechanochemical pattern formation across biological scales}}, doi = {10.15479/at:ista:12964}, year = {2023}, } @phdthesis{13074, abstract = {Deep learning has become an integral part of a large number of important applications, and many of the recent breakthroughs have been enabled by the ability to train very large models, capable to capture complex patterns and relationships from the data. At the same time, the massive sizes of modern deep learning models have made their deployment to smaller devices more challenging; this is particularly important, as in many applications the users rely on accurate deep learning predictions, but they only have access to devices with limited memory and compute power. One solution to this problem is to prune neural networks, by setting as many of their parameters as possible to zero, to obtain accurate sparse models with lower memory footprint. Despite the great research progress in obtaining sparse models that preserve accuracy, while satisfying memory and computational constraints, there are still many challenges associated with efficiently training sparse models, as well as understanding their generalization properties. The focus of this thesis is to investigate how the training process of sparse models can be made more efficient, and to understand the differences between sparse and dense models in terms of how well they can generalize to changes in the data distribution. We first study a method for co-training sparse and dense models, at a lower cost compared to regular training. With our method we can obtain very accurate sparse networks, and dense models that can recover the baseline accuracy. Furthermore, we are able to more easily analyze the differences, at prediction level, between the sparse-dense model pairs. Next, we investigate the generalization properties of sparse neural networks in more detail, by studying how well different sparse models trained on a larger task can adapt to smaller, more specialized tasks, in a transfer learning scenario. Our analysis across multiple pruning methods and sparsity levels reveals that sparse models provide features that can transfer similarly to or better than the dense baseline. However, the choice of the pruning method plays an important role, and can influence the results when the features are fixed (linear finetuning), or when they are allowed to adapt to the new task (full finetuning). Using sparse models with fixed masks for finetuning on new tasks has an important practical advantage, as it enables training neural networks on smaller devices. However, one drawback of current pruning methods is that the entire training cycle has to be repeated to obtain the initial sparse model, for every sparsity target; in consequence, the entire training process is costly and also multiple models need to be stored. In the last part of the thesis we propose a method that can train accurate dense models that are compressible in a single step, to multiple sparsity levels, without additional finetuning. Our method results in sparse models that can be competitive with existing pruning methods, and which can also successfully generalize to new tasks.}, author = {Peste, Elena-Alexandra}, issn = {2663-337X}, pages = {147}, publisher = {Institute of Science and Technology Austria}, title = {{Efficiency and generalization of sparse neural networks}}, doi = {10.15479/at:ista:13074}, year = {2023}, } @phdthesis{14058, abstract = {Females and males across species are subject to divergent selective pressures arising from di↵erent reproductive interests and ecological niches. This often translates into a intricate array of sex-specific natural and sexual selection on traits that have a shared genetic basis between both sexes, causing a genetic sexual conflict. The resolution of this conflict mostly relies on the evolution of sex-specific expression of the shared genes, leading to phenotypic sexual dimorphism. Such sex-specific gene expression is thought to evolve via modifications of the genetic networks ultimately linked to sex-determining transcription factors. Although much empirical and theoretical evidence supports this standard picture of the molecular basis of sexual conflict resolution, there still are a few open questions regarding the complex array of selective forces driving phenotypic di↵erentiation between the sexes, as well as the molecular mechanisms underlying sexspecific adaptation. I address some of these open questions in my PhD thesis. First, how do patterns of phenotypic sexual dimorphism vary within populations, as a response to the temporal and spatial changes in sex-specific selective forces? To tackle this question, I analyze the patterns of sex-specific phenotypic variation along three life stages and across populations spanning the whole geographical range of Rumex hastatulus, a wind-pollinated angiosperm, in the first Chapter of the thesis. Second, how do gene expression patterns lead to phenotypic dimorphism, and what are the molecular mechanisms underlying the observed transcriptomic variation? I address this question by examining the sex- and tissue-specific expression variation in newly-generated datasets of sex-specific expression in heads and gonads of Drosophila melanogaster. I additionally used two complementary approaches for the study of the genetic basis of sex di↵erences in gene expression in the second and third Chapters of the thesis. Third, how does intersex correlation, thought to be one of the main aspects constraining the ability for the two sexes to decouple, interact with the evolution of sexual dimorphism? I develop models of sex-specific stabilizing selection, mutation and drift to formalize common intuition regarding the patterns of covariation between intersex correlation and sexual dimorphism in the fourth Chapter of the thesis. Alltogether, the work described in this PhD thesis provides useful insights into the links between genetic, transcriptomic and phenotypic layers of sex-specific variation, and contributes to our general understanding of the dynamics of sexual dimorphism evolution.}, author = {Puixeu Sala, Gemma}, isbn = {978-3-99078-035-0}, issn = {2663-337X}, pages = {230}, publisher = {Institute of Science and Technology Austria}, title = {{The molecular basis of sexual dimorphism: Experimental and theoretical characterization of phenotypic, transcriptomic and genetic patterns of sex-specific adaptation}}, doi = {10.15479/at:ista:14058}, year = {2023}, } @phdthesis{14280, abstract = {Cell division in Escherichia coli is performed by the divisome, a multi-protein complex composed of more than 30 proteins. The divisome spans from the cytoplasm through the inner membrane to the cell wall and the outer membrane. Divisome assembly is initiated by a cytoskeletal structure, the so-called Z-ring, which localizes at the center of the E. coli cell and determines the position of the future cell septum. The Z-ring is composed of the highly conserved bacterial tubulin homologue FtsZ, which forms treadmilling filaments. These filaments are recruited to the inner membrane by FtsA, a highly conserved bacterial actin homologue. FtsA interacts with other proteins in the periplasm and thus connects the cytoplasmic and periplasmic components of the divisome. A previous model postulated that FtsA regulates maturation of the divisome by switching from an oligomeric, inactive state to a monomeric and active state. This model was based mostly on in vivo studies, as a biochemical characterization of FtsA has been hampered by difficulties in purifying the protein. Here, we studied FtsA using an in vitro reconstitution approach and aimed to answer two questions: (i) How are dynamics from cytoplasmic, treadmilling FtsZ filaments coupled to proteins acting in the periplasmic space and (ii) How does FtsA regulate the maturation of the divisome? We found that the cytoplasmic peptides of the transmembrane proteins FtsN and FtsQ interact directly with FtsA and can follow the spatiotemporal signal of FtsA/Z filaments. When we investigated the underlying mechanism by imaging single molecules of FtsNcyto, we found the peptide to interact transiently with FtsA. An in depth analysis of the single molecule trajectories helped to postulate a model where PG synthases follow the dynamics of FtsZ by a diffusion and capture mechanism. Following up on these findings we were interested in how the self-interaction of FtsA changes when it encounters FtsNcyto and if we can confirm the proposed oligomer-monomer switch. For this, we compared the behavior of the previously identified, hyperactive mutant FtsA R286W with wildtype FtsA. The mutant outperforms WT in mirroring and transmitting the spatiotemporal signal of treadmilling FtsZ filaments. Surprisingly however, we found that this was not due to a difference in the self-interaction strength of the two variants, but a difference in their membrane residence time. Furthermore, in contrast to our expectations, upon binding of FtsNcyto the measured self-interaction of FtsA actually increased. We propose that FtsNcyto induces a rearrangement of the oligomeric architecture of FtsA. In further consequence this change leads to more persistent FtsZ filaments which results in a defined signalling zone, allowing formation of the mature divisome. The observed difference between FtsA WT and R286W is due to the vastly different membrane turnover of the proteins. R286W cycles 5-10x faster compared to WT which allows to sample FtsZ filaments at faster frequencies. These findings can explain the observed differences in toxicity for overexpression of FtsA WT and R286W and help to understand how FtsA regulates divisome maturation.}, author = {Radler, Philipp}, isbn = {978-3-99078-033-6}, issn = {2663-337X}, keywords = {Cell Division, Reconstitution, FtsZ, FtsA, Divisome, E.coli}, pages = {156}, publisher = {Institute of Science and Technology Austria}, title = {{Spatiotemporal signaling during assembly of the bacterial divisome}}, doi = {10.15479/at:ista:14280}, year = {2023}, } @phdthesis{14510, author = {Gnyliukh, Nataliia}, isbn = {978-3-99078-037-4}, issn = {2663-337X}, keywords = {Clathrin-Mediated Endocytosis, vesicle scission, Dynamin-Related Protein 2, SH3P2, TPLATE complex, Total internal reflection fluorescence microscopy, Arabidopsis thaliana}, pages = {180}, publisher = {Institute of Science and Technology Austria}, title = {{Mechanism of clathrin-coated vesicle formation during endocytosis in plants}}, doi = {10.15479/at:ista:14510}, year = {2023}, } @phdthesis{12358, abstract = {The complex yarn structure of knitted and woven fabrics gives rise to both a mechanical and visual complexity. The small-scale interactions of yarns colliding with and pulling on each other result in drastically different large-scale stretching and bending behavior, introducing anisotropy, curling, and more. While simulating cloth as individual yarns can reproduce this complexity and match the quality of real fabric, it may be too computationally expensive for large fabrics. On the other hand, continuum-based approaches do not need to discretize the cloth at a stitch-level, but it is non-trivial to find a material model that would replicate the large-scale behavior of yarn fabrics, and they discard the intricate visual detail. In this thesis, we discuss three methods to try and bridge the gap between small-scale and large-scale yarn mechanics using numerical homogenization: fitting a continuum model to periodic yarn simulations, adding mechanics-aware yarn detail onto thin-shell simulations, and quantitatively fitting yarn parameters to physical measurements of real fabric. To start, we present a method for animating yarn-level cloth effects using a thin-shell solver. We first use a large number of periodic yarn-level simulations to build a model of the potential energy density of the cloth, and then use it to compute forces in a thin-shell simulator. The resulting simulations faithfully reproduce expected effects like the stiffening of woven fabrics and the highly deformable nature and anisotropy of knitted fabrics at a fraction of the cost of full yarn-level simulation. While our thin-shell simulations are able to capture large-scale yarn mechanics, they lack the rich visual detail of yarn-level simulations. Therefore, we propose a method to animate yarn-level cloth geometry on top of an underlying deforming mesh in a mechanics-aware fashion in real time. Using triangle strains to interpolate precomputed yarn geometry, we are able to reproduce effects such as knit loops tightening under stretching at negligible cost. Finally, we introduce a methodology for inverse-modeling of yarn-level mechanics of cloth, based on the mechanical response of fabrics in the real world. We compile a database from physical tests of several knitted fabrics used in the textile industry spanning diverse physical properties like stiffness, nonlinearity, and anisotropy. We then develop a system for approximating these mechanical responses with yarn-level cloth simulation, using homogenized shell models to speed up computation and adding some small-but-necessary extensions to yarn-level models used in computer graphics. }, author = {Sperl, Georg}, isbn = {978-3-99078-020-6}, issn = {2663-337X}, pages = {138}, publisher = {Institute of Science and Technology Austria}, title = {{Homogenizing yarn simulations: Large-scale mechanics, small-scale detail, and quantitative fitting}}, doi = {10.15479/at:ista:12103}, year = {2022}, } @phdthesis{12364, abstract = {Autism spectrum disorders (ASDs) are a group of neurodevelopmental disorders characterized by behavioral symptoms such as problems in social communication and interaction, as well as repetitive, restricted behaviors and interests. These disorders show a high degree of heritability and hundreds of risk genes have been identifed using high throughput sequencing technologies. This genetic heterogeneity has hampered eforts in understanding the pathogenesis of ASD but at the same time given rise to the concept of convergent mechanisms. Previous studies have identifed that risk genes for ASD broadly converge onto specifc functional categories with transcriptional regulation being one of the biggest groups. In this thesis, I focus on this subgroup of genes and investigate the gene regulatory consequences of some of them in the context of neurodevelopment. First, we showed that mutations in the ASD and intellectual disability risk gene Setd5 lead to perturbations of gene regulatory programs in early cell fate specifcation. In addition, adult animals display abnormal learning behavior which is mirrored at the transcriptional level by altered activity dependent regulation of postsynaptic gene expression. Lastly, we link the regulatory function of Setd5 to its interaction with the Paf1 and the NCoR complex. Second, by modeling the heterozygous loss of the top ASD gene CHD8 in human cerebral organoids we demonstrate profound changes in the developmental trajectories of both inhibitory and excitatory neurons using single cell RNA-sequencing. While the former were generated earlier in CHD8+/- organoids, the generation of the latter was shifted to later times in favor of a prolonged progenitor expansion phase and ultimately increased organoid size. Finally, by modeling heterozygous mutations for four ASD associated chromatin modifers, ASH1L, KDM6B, KMT5B, and SETD5 in human cortical spheroids we show evidence of regulatory convergence across three of those genes. We observe a shift from dorsal cortical excitatory neuron fates towards partially ventralized cell types resembling cells from the lateral ganglionic eminence. As this project is still ongoing at the time of writing, future experiments will aim at elucidating the regulatory mechanisms underlying this shift with the aim of linking these three ASD risk genes through biological convergence.}, author = {Dotter, Christoph}, issn = {2663-337X}, pages = {152}, publisher = {Institute of Science and Technology Austria}, title = {{Transcriptional consequences of mutations in genes associated with Autism Spectrum Disorder}}, doi = {10.15479/at:ista:12094}, year = {2022}, } @phdthesis{12366, abstract = {Recent substantial advances in the feld of superconducting circuits have shown its potential as a leading platform for future quantum computing. In contrast to classical computers based on bits that are represented by a single binary value, 0 or 1, quantum bits (or qubits) can be in a superposition of both. Thus, quantum computers can store and handle more information at the same time and a quantum advantage has already been demonstrated for two types of computational tasks. Rapid progress in academic and industry labs accelerates the development of superconducting processors which may soon fnd applications in complex computations, chemical simulations, cryptography, and optimization. Now that these machines are scaled up to tackle such problems the questions of qubit interconnects and networks becomes very relevant. How to route signals on-chip between diferent processor components? What is the most efcient way to entangle qubits? And how to then send and process entangled signals between distant cryostats hosting superconducting processors? In this thesis, we are looking for solutions to these problems by studying the collective behavior of superconducting qubit ensembles. We frst demonstrate on-demand tunable directional scattering of microwave photons from a pair of qubits in a waveguide. Such a device can route microwave photons on-chip with a high diode efciency. Then we focus on studying ultra-strong coupling regimes between light (microwave photons) and matter (superconducting qubits), a regime that could be promising for extremely fast multi-qubit entanglement generation. Finally, we show coherent pulse storage and periodic revivals in a fve qubit ensemble strongly coupled to a resonator. Such a reconfgurable storage device could be used as part of a quantum repeater that is needed for longer-distance quantum communication. The achieved high degree of control over multi-qubit ensembles highlights not only the beautiful physics of circuit quantum electrodynamics, it also represents the frst step toward new quantum simulation and communication methods, and certain techniques may also fnd applications in future superconducting quantum computing hardware. }, author = {Redchenko, Elena}, isbn = {978-3-99078-024-4}, issn = {2663-337X}, pages = {168}, publisher = {Institute of Science and Technology Austria}, title = {{Controllable states of superconducting Qubit ensembles}}, doi = {10.15479/at:ista:12132}, year = {2022}, } @phdthesis{12368, abstract = {Metazoan development relies on the formation and remodeling of cell-cell contacts. The binding of adhesion receptors and remodeling of the actomyosin cell cortex at cell-cell interaction sites have been implicated in cell-cell contact formation. Yet, how these two processes functionally interact to drive cell-cell contact expansion and strengthening remains unclear. Here, we study how primary germ layer progenitor cells from zebrafish bind to supported lipid bilayers (SLB) functionalized with E-cadherin ectodomains as an assay system for monitoring cell-cell contact formation at high spatiotemporal resolution. We show that cell-cell contact formation represents a two-tiered process: E-cadherinmediated downregulation of the small GTPase RhoA at the forming contact leads to both depletion of Myosin-2 and decrease of F-actin. This is followed by centrifugal actin network flows at the contact triggered by a sharp gradient of Myosin-2 at the rim of the contact zone, with Myosin-2 displaying higher cortical localization outside than inside of the contact. These centrifugal cortical actin flows, in turn, not only further dilute the actin network at the contact disc, but also lead to an accumulation of both F-actin and Ecadherin at the contact rim. Eventually, this combination of actomyosin downregulation and flows at the contact contribute to the characteristic molecular organization implicated in contact formation and maintenance: depletion of cortical actomyosin at the contact disc, driving contact expansion by lowering interfacial tension at the contact, and accumulation of both E-cadherin and F-actin at the contact rim, mechanically linking the contractile cortices of the adhering cells. Thus, using a biomimetic assay, we exemplify how adhesion signaling and cell mechanics function together to modulate the spatial organization of cell-cell contacts.}, author = {Arslan, Feyza N}, isbn = { 978-3-99078-025-1 }, issn = {2663-337X}, pages = {113}, publisher = {Institute of Science and Technology Austria}, title = {{Remodeling of E-cadherin-mediated contacts via cortical flows}}, doi = {10.15479/at:ista:12153}, year = {2022}, } @phdthesis{12378, abstract = {Environmental cues influence the highly dynamic morphology of microglia. Strategies to characterize these changes usually involve user-selected morphometric features, which preclude the identification of a spectrum of context-dependent morphological phenotypes. Here, we develop MorphOMICs, a topological data analysis approach, which enables semiautomatic mapping of microglial morphology into an atlas of cue-dependent phenotypes, overcomes feature-selection bias and minimizes biological variability. First, with MorphOMICs we derive the morphological spectrum of microglia across seven brain regions during postnatal development and in two distinct Alzheimer’s disease degeneration mouse models. We uncover region-specific and sexually dimorphic morphological trajectories, with females showing an earlier morphological shift than males in the degenerating brain. Overall, we demonstrate that both long primary- and short terminal processes provide distinct insights to morphological phenotypes. Moreover, using machine learning to map novel condition on the spectrum, we observe that microglia morphologies reflect a dose-dependent adaptation upon ketamine anesthesia and do not recover to control morphologies. Next, we took advantage of MorphOMICs to build a high-resolution and layer-specific map of microglial morphological spectrum in the retina, covering postnatal development and rd10 degeneration. Here, following photoreceptor death, microglia assume an early developmentlike morphology. Finally, we map microglial morphology following optic nerve crush on the retinal spectrum and observe a layer- and sex-dependent response. Overall, MorphOMICs opens a new perspective to analyze microglial morphology across multiple conditions, and provides a novel tool to characterize microglial morphology beyond the traditionally dichotomized view of microglia.}, author = {Colombo, Gloria}, issn = {2663-337X}, pages = {142}, publisher = {Institute of Science and Technology Austria}, title = {{MorphOMICs, a tool for mapping microglial morphology, reveals brain region- and sex-dependent phenotypes}}, doi = {10.15479/at:ista:12378}, year = {2022}, } @phdthesis{12390, abstract = {The scope of this thesis is to study quantum systems exhibiting a continuous symmetry that is broken on the level of the corresponding effective theory. In particular we are going to investigate translation-invariant Bose gases in the mean field limit, effectively described by the Hartree functional, and the Fröhlich Polaron in the regime of strong coupling, effectively described by the Pekar functional. The latter is a model describing the interaction between a charged particle and the optical modes of a polar crystal. Regarding the former, we assume in addition that the particles in the gas are unconfined, and typically we will consider particles that are subject to an attractive interaction. In both cases the ground state energy of the Hamiltonian is not a proper eigenvalue due to the underlying translation-invariance, while on the contrary there exists a whole invariant orbit of minimizers for the corresponding effective functionals. Both, the absence of proper eigenstates and the broken symmetry of the effective theory, make the study significantly more involved and it is the content of this thesis to develop a frameworks which allows for a systematic way to circumvent these issues. It is a well-established result that the ground state energy of Bose gases in the mean field limit, as well as the ground state energy of the Fröhlich Polaron in the regime of strong coupling, is to leading order given by the minimal energy of the corresponding effective theory. As part of this thesis we identify the sub-leading term in the expansion of the ground state energy, which can be interpreted as the quantum correction to the classical energy, since the effective theories under consideration can be seen as classical counterparts. We are further going to establish an asymptotic expression for the energy-momentum relation of the Fröhlich Polaron in the strong coupling limit. In the regime of suitably small momenta, this asymptotic expression agrees with the energy-momentum relation of a free particle having an effectively increased mass, and we find that this effectively increased mass agrees with the conjectured value in the physics literature. In addition we will discuss two unrelated papers written by the author during his stay at ISTA in the appendix. The first one concerns the realization of anyons, which are quasi-particles acquiring a non-trivial phase under the exchange of two particles, as molecular impurities. The second one provides a classification of those vector fields defined on a given manifold that can be written as the gradient of a given functional with respect to a suitable metric, provided that some mild smoothness assumptions hold. This classification is subsequently used to identify those quantum Markov semigroups that can be written as a gradient flow of the relative entropy. }, author = {Brooks, Morris}, issn = {2663-337X}, pages = {196}, publisher = {Institute of Science and Technology Austria}, title = {{Translation-invariant quantum systems with effectively broken symmetry}}, doi = {10.15479/at:ista:12390}, year = {2022}, } @phdthesis{12401, abstract = {Detachment of the cancer cells from the bulk of the tumor is the first step of metastasis, which is the primary cause of cancer related deaths. It is unclear, which factors contribute to this step. Recent studies indicate a crucial role of the tumor microenvironment in malignant transformation and metastasis. Studying cancer cell invasion and detachments quantitatively in the context of its physiological microenvironment is technically challenging. Especially, precise control of microenvironmental properties in vivo is currently not possible. Here, I studied the role of microenvironment geometry in the invasion and detachment of cancer cells from the bulk with a simplistic and reductionist approach. In this approach, I engineered microfluidic devices to mimic a pseudo 3D extracellular matrix environment, where I was able to quantitatively tune the geometrical configuration of the microenvironment and follow tumor cells with fluorescence live imaging. To aid quantitative analysis I developed a widely applicable software application to automatically analyze and visualize particle tracking data. Quantitative analysis of tumor cell invasion in isotropic and anisotropic microenvironments showed that heterogeneity in the microenvironment promotes faster invasion and more frequent detachment of cells. These observations correlated with overall higher speed of cells at the edge of the bulk of the cells. In heterogeneous microenvironments cells preferentially passed through larger pores, thus invading areas of least resistance and generating finger-like invasive structures. The detachments occurred mostly at the tips of these structures. To investigate the potential mechanism, we established a two dimensional model to simulate active Brownian particles representing the cell nuclei dynamics. These simulations backed our in vitro observations without the need of precise fitting the simulation parameters. Our model suggests the importance of the pore heterogeneity in the direction perpendicular to the orientation of bias field (lateral heterogeneity), which causes the interface roughening.}, author = {Tasciyan, Saren}, issn = {2663-337X}, pages = {105}, publisher = {Institute of Science and Technology Austria}, title = {{Role of microenvironment heterogeneity in cancer cell invasion}}, doi = {10.15479/at:ista:12401}, year = {2022}, }