@misc{22234, abstract = {Lists of nontrivial integral points on some (families of) cubic surfaces. (2024-07-18)}, author = {Browning, Timothy D and Sutherland, Andrew}, publisher = {Göttingen Research Online Data}, title = {{Data and code for: Integral points on cubic surfaces: heuristics and numerics}}, doi = {10.25625/4FLFH8}, year = {2024}, } @article{17457, abstract = {Autoantibodies against the protein leucine-rich glioma inactivated 1 (LGI1) cause the most common subtype of autoimmune encephalitis with predominant involvement of the limbic system, associated with seizures and memory deficits. LGI1 and its receptor ADAM22 are part of a transsynaptic protein complex that includes several proteins involved in presynaptic neurotransmitter release and postsynaptic glutamate sensing. Autoantibodies against LGI1 increase excitatory synaptic strength, but studies that genetically disrupt the LGI1-ADAM22 complex report a reduction in postsynaptic glutamate receptor-mediated responses. Thus, the mechanisms underlying the increased synaptic strength induced by LGI1 autoantibodies remain elusive, and the contributions of presynaptic molecules to the LGI1-transsynaptic complex remain unclear. We therefore investigated the presynaptic mechanisms that mediate autoantibody-induced synaptic strengthening.}, author = {Ritzau-Jost, Andreas and Gsell, Felix and Sell, Josefine and Sachs, Stefan and Montanaro-Punzengruber, Jacqueline-Claire and Kirmann, Toni and Maaß, Sebastian and Irani, Sarosh R. and Werner, Christian and Geis, Christian and Sauer, Markus and Shigemoto, Ryuichi and Hallermann, Stefan}, issn = {2332-7812}, journal = {Neurology, Neuroimmunology & Neuroinflammation}, number = {5}, pages = {e200284}, publisher = {Wolters Kluwer}, title = {{LGI1 autoantibodies enhance synaptic transmission by presynaptic Kv1 loss and increased action potential broadening}}, doi = {10.1212/NXI.0000000000200284}, volume = {11}, year = {2024}, } @unpublished{19063, abstract = {Instruction-tuned Large Language Models (LLMs) show impressive results in numerous practical applications, but they lack essential safety features that are common in other areas of computer science, particularly an explicit separation of instructions and data. This makes them vulnerable to manipulations such as indirect prompt injections and generally unsuitable for safety-critical tasks. Surprisingly, there is currently no established definition or benchmark to quantify this phenomenon. In this work, we close this gap by introducing a formal measure for instruction-data separation and an empirical variant that is calculable from a model's outputs. We also present a new dataset, SEP, that allows estimating the measure for real-world models. Our results on various LLMs show that the problem of instruction-data separation is real: all models fail to achieve high separation, and canonical mitigation techniques, such as prompt engineering and fine-tuning, either fail to substantially improve separation or reduce model utility. The source code and SEP dataset are openly accessible at https://github.com/egozverev/Shold-It-Be-Executed-Or-Processed. }, author = {Zverev, Egor and Abdelnabi, Sahar and Tabesh, Soroush and Fritz, Mario and Lampert, Christoph}, booktitle = {arXiv}, title = {{Can LLMs separate instructions from data? And what do we even mean by that?}}, doi = {10.48550/arXiv.2403.06833}, year = {2024}, } @article{15401, abstract = {Amide-proton-detected magic-angle-spinning NMR of deuterated proteins has become a main technique in NMR-based structural biology. In standard deuteration protocols that rely on D2O-based culture media, non-exchangeable amide sites remain deuterated, making these sites unobservable. Here we demonstrate that proteins produced with a H2O-based culture medium doped with deuterated cell lysate allow scientists to overcome this “reprotonation bottleneck” while retaining a high level of deuteration (ca. 80 %) and narrow linewidths. We quantified coherence lifetimes of several proteins prepared with this labeling pattern over a range of magic-angle-spinning (MAS) frequencies (40–100 kHz). We demonstrate that under commonly used conditions (50–60 kHz MAS), the amide 1H linewidths with our labeling approach are comparable to those of perdeuterated proteins and better than those of protonated samples at 100 kHz. For three proteins in the 33–50 kDa size range, many previously unobserved amides become visible. We report how to prepare the deuterated cell lysate for our approach from fractions of perdeuterated cultures which are usually discarded, and we show that such media can be used identically to commercial media. The residual protonation of Hα sites allows for well-resolved Hα-detected spectra and Hα resonance assignment, exemplified by the de novo assignment of 168 Hα sites in a 39 kDa protein. The approach based on this H2O/cell-lysate deuteration and MAS frequencies compatible with 1.3 or 1.9 mm rotors presents a strong sensitivity benefit over 0.7 mm 100 kHz MAS experiments.}, author = {Napoli, Federico and Guan, Jia-Ying and Arnaud, Charles-Adrien and Macek, Pavel and Fraga, Hugo and Breyton, Cécile and Schanda, Paul}, issn = {2699-0016}, journal = {Magnetic Resonance}, number = {1}, pages = {33--49}, publisher = {Copernicus Publications}, title = {{Deuteration of proteins boosted by cell lysates: High-resolution amide and Ha magic-angle-spinning (MAS) NMR without the reprotonation bottleneck}}, doi = {10.5194/mr-5-33-2024}, volume = {5}, year = {2024}, } @phdthesis{15094, abstract = {Point sets, geometric networks, and arrangements of hyperplanes are fundamental objects in discrete geometry that have captivated mathematicians for centuries, if not millennia. This thesis seeks to cast new light on these structures by illustrating specific instances where a topological perspective, specifically through discrete Morse theory and persistent homology, provides valuable insights. At first glance, the topology of these geometric objects might seem uneventful: point sets essentially lack of topology, arrangements of hyperplanes are a decomposition of Rd, which is a contractible space, and the topology of a network primarily involves the enumeration of connected components and cycles within the network. However, beneath this apparent simplicity, there lies an array of intriguing structures, a small subset of which will be uncovered in this thesis. Focused on three case studies, each addressing one of the mentioned objects, this work will showcase connections that intertwine topology with diverse fields such as combinatorial geometry, algorithms and data structures, and emerging applications like spatial biology. }, author = {Cultrera di Montesano, Sebastiano}, issn = {2663-337X}, pages = {108}, publisher = {Institute of Science and Technology Austria}, title = {{Persistence and Morse theory for discrete geometric structures}}, doi = {10.15479/at:ista:15094}, year = {2024}, } @article{13182, abstract = {We characterize critical points of 1-dimensional maps paired in persistent homology geometrically and this way get elementary proofs of theorems about the symmetry of persistence diagrams and the variation of such maps. In particular, we identify branching points and endpoints of networks as the sole source of asymmetry and relate the cycle basis in persistent homology with a version of the stable marriage problem. Our analysis provides the foundations of fast algorithms for maintaining a collection of sorted lists together with its persistence diagram.}, author = {Biswas, Ranita and Cultrera Di Montesano, Sebastiano and Edelsbrunner, Herbert and Saghafian, Morteza}, issn = {2367-1734}, journal = {Journal of Applied and Computational Topology}, pages = {1101--1119}, publisher = {Springer Nature}, title = {{Geometric characterization of the persistence of 1D maps}}, doi = {10.1007/s41468-023-00126-9}, volume = {8}, year = {2024}, } @article{14826, abstract = {The plant-signaling molecule auxin triggers fast and slow cellular responses across land plants and algae. The nuclear auxin pathway mediates gene expression and controls growth and development in land plants, but this pathway is absent from algal sister groups. Several components of rapid responses have been identified in Arabidopsis, but it is unknown if these are part of a conserved mechanism. We recently identified a fast, proteome-wide phosphorylation response to auxin. Here, we show that this response occurs across 5 land plant and algal species and converges on a core group of shared targets. We found conserved rapid physiological responses to auxin in the same species and identified rapidly accelerated fibrosarcoma (RAF)-like protein kinases as central mediators of auxin-triggered phosphorylation across species. Genetic analysis connects this kinase to both auxin-triggered protein phosphorylation and rapid cellular response, thus identifying an ancient mechanism for fast auxin responses in the green lineage.}, author = {Kuhn, Andre and Roosjen, Mark and Mutte, Sumanth and Dubey, Shiv Mani and Carrillo Carrasco, Vanessa Polet and Boeren, Sjef and Monzer, Aline and Koehorst, Jasper and Kohchi, Takayuki and Nishihama, Ryuichi and Fendrych, Matyas and Sprakel, Joris and Friml, Jiří and Weijers, Dolf}, issn = {1097-4172}, journal = {Cell}, keywords = {General Biochemistry, Genetics and Molecular Biology}, number = {1}, pages = {130--148.e17}, publisher = {Elsevier}, title = {{RAF-like protein kinases mediate a deeply conserved, rapid auxin response}}, doi = {10.1016/j.cell.2023.11.021}, volume = {187}, year = {2024}, } @inproceedings{18702, abstract = {In this work we prove lower bounds on the (communication) cost of maintaining a shared key among a dynamic group of users. Being “dynamic” means one can add and remove users from the group. This captures important protocols like multicast encryption (ME) and continuous group-key agreement (CGKA), which is the primitive underlying many group messaging applications. We prove our bounds in a combinatorial setting where the state of the protocol progresses in rounds. The state of the protocol in each round is captured by a set system, with each of its elements specifying a set of users who share a secret key. We show this combinatorial model implies bounds in symbolic models for ME and CGKA that capture, as building blocks, PRGs, PRFs, dual PRFs, secret sharing, and symmetric encryption in the setting of ME, and PRGs, PRFs, dual PRFs, secret sharing, public-key encryption, and key-updatable public-key encryption in the setting of CGKA. The models are related to the ones used by Micciancio and Panjwani (Eurocrypt’04) and Bienstock et al. (TCC’20) to analyze ME and CGKA, respectively. We prove – using the Bollobás’ Set Pairs Inequality – that the cost (number of uploaded ciphertexts) for replacing a set of d users in a group of size n is Ω(dln(n/d)). Our lower bound is asymptotically tight and both improves on a bound of Ω(d) by Bienstock et al. (TCC’20), and generalizes a result by Micciancio and Panjwani (Eurocrypt’04), who proved a lower bound of Ω(log(n)) for d=1. }, author = {Anastos, Michael and Auerbach, Benedikt and Baig, Mirza Ahad and Cueto Noval, Miguel and Kwan, Matthew Alan and Pascual Perez, Guillermo and Pietrzak, Krzysztof Z}, booktitle = {22nd International Conference on Theory of Cryptography}, isbn = {9783031780103}, issn = {1611-3349}, location = {Milan, Italy}, pages = {413--443}, publisher = {Springer Nature}, title = {{The cost of maintaining keys in dynamic groups with applications to multicast encryption and group messaging}}, doi = {10.1007/978-3-031-78011-0_14}, volume = {15364}, year = {2024}, } @article{17373, abstract = {Scanning Kelvin probe microscopy (SKPM) is a powerful technique for investigating the electrostatic properties of material surfaces, enabling the imaging of variations in work function, topology, surface charge density, or combinations thereof. Regardless of the underlying signal source, SKPM results in a voltage image, which is spatially distorted due to the finite size of the probe, long-range electrostatic interactions, mechanical and electrical noise, and the finite response time of the electronics. In order to recover the underlying signal, it is necessary to deconvolve the measurement with an appropriate point spread function (PSF) that accounts the aforementioned distortions, but determining this PSF is difficult. Here, we describe how such PSFs can be determined experimentally and show how they can be used to recover the underlying information of interest. We first consider the physical principles that enable SKPM and discuss how these affect the system PSF. We then show how one can experimentally measure PSFs by looking at well-defined features, and that these compare well to simulated PSFs, provided scans are performed extremely slowly and carefully. Next, we work at realistic scan speeds and show that the idealized PSFs fail to capture temporal distortions in the scan direction. While simulating PSFs for these situations would be quite challenging, we show that measuring PSFs with similar scan conditions works well. Our approach clarifies the basic principles and inherent challenges to SKPM measurements and gives practical methods to improve results.}, author = {Lenton, Isaac C and Pertl, Felix and Shafeek, Lubuna B and Waitukaitis, Scott R}, issn = {1089-7550}, journal = {Journal of Applied Physics}, number = {4}, publisher = {AIP Publishing}, title = {{Beyond the blur: Using experimentally determined point spread functions to improve scanning Kelvin probe imaging}}, doi = {10.1063/5.0215151}, volume = {136}, year = {2024}, } @inbook{17425, abstract = {Mosaic Analysis with Double Markers (MADM) is a powerful genetic method typically used for lineage tracing and to disentangle cell autonomous and tissue-wide roles of candidate genes with single cell resolution. Given the relatively sparse labeling, depending on which of the 19 MADM chromosomes one chooses, the MADM approach represents the perfect opportunity for cell morphology analysis. Various MADM studies include reports of morphological anomalies and phenotypes in the central nervous system (CNS). MADM for any candidate gene can easily incorporate morphological analysis within the experimental workflow. Here, we describe the methods of morphological cell analysis which we developed in the course of diverse recent MADM studies. This chapter will specifically focus on methods to quantify aspects of the morphology of neurons and astrocytes within the CNS, but these methods can broadly be applied to any MADM-labeled cells throughout the entire organism. We will cover two analyses—soma volume and dendrite characterization—of physical characteristics of pyramidal neurons in the somatosensory cortex, and two analyses—volume and Sholl analysis—of astrocyte morphology.}, author = {Miranda, Osvaldo and Cheung, Giselle T and Hippenmeyer, Simon}, booktitle = {Neuronal Morphogenesis}, editor = {Toyooka, Kazuhito}, isbn = {9781071639689}, issn = {1940-6029}, pages = {283--299}, publisher = {Springer Nature}, title = {{Morphological Analysis of Neurons and Glia Using Mosaic Analysis with Double Markers}}, doi = {10.1007/978-1-0716-3969-6_19}, volume = {2831}, year = {2024}, } @phdthesis{17465, abstract = {In the modern age of machine learning, artificial neural networks have become an integral part of many practical systems. One of the key ingredients of the success of the deep learning approach is recent computational advances which allowed the training of models with billions of parameters on large-scale data. Such over-parameterized and data-hungry regimes pose a challenge for the theoretical analysis of modern models since “classical” statistical wisdom is no longer applicable. In this view, it is paramount to extend or develop new machinery that will allow tackling the neural network analysis under new challenging asymptotic regimes, which is the focus of this thesis. Large neural network systems are usually optimized via “local” search algorithms, such as stochastic gradient descent (SGD). However, given the high-dimensional nature of the parameter space, it is a priori not clear why such a crude “local” approach works so remarkably well in practice. We take a step towards demystifying this phenomenon by showing that the landscape of the SGD training dynamics exhibits a few beneficial properties for the optimization. First, we show that along the SGD trajectory an over-parameterized network is dropout stable. The emergence of dropout stability allows to conclude that the minima found by SGD are connected via a continuous path of small loss. This in turn means that the high-dimensional landscape of the neural network optimization problem is provably not so unfavourable to gradient-based training, due to mode connectivity. Next, we show that SGD for an over-parameterized network tends to find solutions that are functionally more “simple”. This in turn means that the SGD minima are more robust, since a less complicated solution will less likely overfit the data. More formally, for a prototypical example of a wide two-layer ReLU network on a 1d regression task we show that the SGD algorithm is implicitly selective in its choice of an interpolating solution. Namely, at convergence the neural network implements a piece-wise linear function with the number of linear regions depending only on the amount of training data. This is in contrast to a “smooth”-like behaviour which one would expect given such a severe over-parameterization of the model. Diverging from the generic supervised setting of classification and regression problems, we analyze an auto-encoder model that is commonly used for representation learning and data compression. Despite the wide applicability of the auto-encoding paradigm, the theoretical understanding of their behaviour is limited even in the simplistic shallow case. The related work is restricted to extreme asymptotic regimes in which the auto-encoder is either severely over-parameterized or under-parameterized. In contrast, we provide a tight characterization for the 1-bit compression of Gaussian signals in the challenging proportional regime, i.e., the input dimension and the size of the compressed representation obey the same asymptotics. We also show that gradient-based methods are able to find a globally optimal solution and that the predictions made for Gaussian data extrapolate beyond - to the case of compression of natural images. Next, we relax the Gaussian assumption and study more structured input sources. We show that the shallow model is sometimes agnostic to the structure of the data vii which results in a Gaussian-like behaviour. We prove that making the decoding component slightly less shallow is already enough to escape the “curse” of Gaussian performance. }, author = {Shevchenko, Aleksandr}, issn = {2663-337X}, pages = {232}, publisher = {Institute of Science and Technology Austria}, title = {{High-dimensional limits in artificial neural networks}}, doi = {10.15479/at:ista:17465}, year = {2024}, } @inproceedings{17469, abstract = {Autoencoders are a prominent model in many empirical branches of machine learning and lossy data compression. However, basic theoretical questions remain unanswered even in a shallow two-layer setting. In particular, to what degree does a shallow autoencoder capture the structure of the underlying data distribution? For the prototypical case of the 1-bit compression of sparse Gaussian data, we prove that gradient descent converges to a solution that completely disregards the sparse structure of the input. Namely, the performance of the algorithm is the same as if it was compressing a Gaussian source - with no sparsity. For general data distributions, we give evidence of a phase transition phenomenon in the shape of the gradient descent minimizer, as a function of the data sparsity: below the critical sparsity level, the minimizer is a rotation taken uniformly at random (just like in the compression of non-sparse data); above the critical sparsity, the minimizer is the identity (up to a permutation). Finally, by exploiting a connection with approximate message passing algorithms, we show how to improve upon Gaussian performance for the compression of sparse data: adding a denoising function to a shallow architecture already reduces the loss provably, and a suitable multi-layer decoder leads to a further improvement. We validate our findings on image datasets, such as CIFAR-10 and MNIST.}, author = {Kögler, Kevin and Shevchenko, Aleksandr and Hassani, Hamed and Mondelli, Marco}, booktitle = {Proceedings of the 41st International Conference on Machine Learning}, location = {Vienna, Austria}, pages = {24964--25015}, publisher = {ML Research Press}, title = {{Compression of structured data with autoencoders: Provable benefit of nonlinearities and depth}}, volume = {235}, year = {2024}, } @phdthesis{17881, abstract = {This work can be broadly classified into the study of critical phenomena in a one dimensional array of Josephson junctions. While we study quantum criticality when the array is in thermal equilibrium at zero bias, the non-equilibrium study involves understanding the bistability of the array at a critical non-zero bias. This work furthers our knowledge in understanding quantum critical behaviour at finite temperatures in a one dimensional Josephson array, while also establishing relaxation behaviour dual to that observed in a single Josephson junction. Chapter 1 briefly introduces the model to understand superconductor-insulator phase transition in a one dimensional Josephson array and points out the state of the field from where we started our zero-bias experiments. In this context it discusses the phase-charge duality observed in a Josephson array and its dual hysteretic behaviour to that of a single junction, setting the ground for our non-equilibrium study of the array. Chapter 2 shows the experimental setup and the chip layout of the device we measured. In chapter 3 we show that, unlike the typical quantum-critical broadening scenario, in one dimensional Josephson arrays temperature dramatically shifts the critical region. This shift leads to a regime of superconductivity at high temperature, arising from the melted zero-temperature insulator. Our results quantitatively explain the low-temperature onset of superconductivity in nominally insulating regimes, and the transition to the strongly insulating phase. We further present, to our knowledge, the first understanding of the onset of anomalous-metallic resistance saturation [30]. This work demonstrates a non-trivial interplay between thermal effects and quantum criticality. A practical consequence is that, counterintuitively, the coherence of high-impedance quantum circuits is expected to be stabilized by thermal fluctuations. In chapter 4, we show relaxation oscillations in a current-biased one dimensional array of Josephson junctions. These oscillations are well described by a circuit model, dual to the ordinary Josephson relaxation oscillations [72]. Injection locking these oscillations results in current plateaux. The relaxation step is found to obey a characteristic self-consistent relation, suggesting that it is governed by overheating effects. Chapter 5 describes the various checks and analysis we performed to support our conclusions made in chapters 3 and 4. Finally, chapter 6 describes the nanofabrication steps and the finite element electromagnetic simulations we performed to fabricate our devices.}, author = {Mukhopadhyay, Soham}, isbn = {978-3-99078-043-5}, issn = {2663-337X}, pages = {82}, publisher = {Institute of Science and Technology Austria}, title = {{Thermal effects in one dimensional Josephson chains}}, doi = {10.15479/at:ista:17881}, year = {2024}, } @unpublished{18057, abstract = {We report relaxation oscillations in a one-dimensional array of Josephson junctions. The oscillations are circuit-dual to those ordinarily observed in single junctions. The dual circuit quantitatively accounts for temporal dynamics of the array, including the dependence on biasing conditions. Injection locking the oscillations results in well-developed current plateaux. A thermal model explains the relaxation step of the oscillations.}, author = {Mukhopadhyay, Soham and Lancheros Naranjo, Diego A and Senior, Jorden L and Higginbotham, Andrew P}, booktitle = {arXiv}, title = {{Dual relaxation oscillations in a Josephson junction array}}, doi = {10.48550/arXiv.2408.07829}, year = {2024}, } @article{17890, abstract = {Our understanding of the molecular pathways that regulate oogenesis and define cellular identity in the Arthropod female reproductive system and the extent of their conservation is currently very limited. This is due to the focus on model systems, including Drosophila and Daphnia, which do not reflect the observed diversity of morphologies, reproductive modes, and sex chromosome systems. We use single-nucleus RNA and ATAC sequencing to produce a comprehensive single nucleus atlas of the adult Artemia franciscana female reproductive system. We map our data to the Fly Cell Atlas single-nucleus dataset of the Drosophila melanogaster ovary, shedding light on the conserved regulatory programs between the two distantly related Arthropod species. We identify the major cell types known to be present in the Artemia ovary, including germ cells, follicle cells, and ovarian muscle cells. Additionally, we use the germ cells to explore gene regulation and expression of the Z chromosome during meiosis, highlighting its unique regulatory dynamics and allowing us to explore the presence of meiotic sex chromosome silencing in this group.}, author = {Elkrewi, Marwan N and Vicoso, Beatriz}, issn = {1553-7404}, journal = {PLoS Genetics}, number = {8}, publisher = {Public Library of Science}, title = {{Single-nucleus atlas of the Artemia female reproductive system suggests germline repression of the Z chromosome}}, doi = {10.1371/journal.pgen.1011376}, volume = {20}, year = {2024}, } @phdthesis{17119, abstract = {Genomes are shaped by natural selection at the level of the organism, as genomic variants that have a beneficial effect on the viability or fecundity of their carriers are on average expected to be passed on to more offspring than less beneficial alleles. However, selection also favors genomic variants that drive their own transmission to the next generation above the mendelian expectation of 50 percent in heterozygotes, even if these self-promoting variants are less beneficial to the organism than other variants at the same locus. Such variants, called meiotic drivers, are found in diverse taxa, and often impose fitness costs on their host organisms. As meiotic drivers often require multiple genes and sequences for transmission ratio distortion, they are often found in regions of low recombination, such as inversions, which prevent their recombination with the non-driving homologous regions. Reduced recombination rates are expected to lead to the accumulation of deleterious mutations, which may affect hundreds of genes trapped in the inversions of meiotic drivers. Although the observed fitness costs of self-promoting haplotypes are thought to possibly reflect sequence degeneration, no study has systematically investigated the level of degeneration on a meiotic driver. Further, the low rates of recombination between driving and non-driving haplotypes have limited the power of traditional genetic studies in uncovering the gene content of meiotic drivers, and made the the identification of the genes causing transmission ratio distortion difficult. After an introduction to meiotic drivers in Chapter 1, this thesis presents three studies that make use of next generation sequencing data to characterize the sequence and expression evolution of genes on the t-haplotype, a large and ancient meiotic driver in house mice that is transmitted to up to 100% of the offspring in males heterozygous for it. Chapter 2 presents a comprehensive assessment of the t-haplotype’s sequence evolution, which shows signs of sequence degeneration counteracted by occasional recombination with the non-driving homolog over large parts of the meiotic driver, proposing an explanation for its long-term survival. Chapter 3 investigates the sequence and expression evolution of genes on the t-haplotype, and finds widespread expression and copy number changes and signs of less efficient purifying selection compared to the genes on the non-driving homolog. Further, this chapter finds candidates for involvment in drive: two positively selected genes on the t-haplotype, and the discovery of a t-specific gene duplicate, which was gained from another chromosome, and which acquired novel sequence and testis-specific expression on the t-haplotype. Finally, Chapter 4 provides unprecedented insights into the gene expression landscape in testes of t-carrier mice, using single nucleus sequencing. Cell-resolved RNA-sequencing allows the comparison of expression in spermatids carrying or not carrying the t-haplotype as well as the timing of t-haplotype-induced expression changes along spermatogenesis. This study shows the timing of previously found drive-associated genes, and uncovers novel candidate genes and biological processes that may underlie the complex biology of transmission ratio distortion of the t-haplotype. Chapter 5 synthesizes the findings of the three studies, and discusses them in the context of the current state of meiotic drive research.}, author = {Kelemen, Réka K}, isbn = {978-3-99078-039-8}, issn = {2663-337X}, keywords = {meiotic driver, neofunctionalization, single nucleus sequencing}, pages = {105}, publisher = {Institute of Science and Technology Austria}, title = {{Characterizing the sequence and expression evolution of the t-haplotype, a model meiotic driver}}, doi = {10.15479/at:ista:17119}, year = {2024}, } @phdthesis{18477, abstract = {ADAR1 is broadly expressed across various tissues and is vital in regulating pathways associated with innate immune responses. ADAR1 marks double-stranded RNA as "self" through its A-to-I editing activity, effectively repressing autoimmunity and maintaining immune tolerance. This editing process has been detected at millions of sites across the human genome. However, the mechanism underlying ADAR1's substrate selectivity properties remains largely unclear, with much of the current knowledge derived from comparisons to its more extensively studied homolog, ADAR2. By studying ADAR1 in complex with its RNA substrates and applying a combination of biochemical techniques and structural studies using CryoEM, we aim to gain a more comprehensive understanding of the substrate selectivity characteristics of ADAR1. In this thesis, the purification protocol for ADAR1 was successfully optimized, resulting in the first report in the literature to achieve high protein purity and activity. This advancement enabled the investigation of complex formation between ADAR1 and various RNA substrates, leading to the identification of optimal conditions for preparing the cryoEM sample. However, despite comprehensive optimization of the cryo-EM conditions, the resulting data lacked the desired quality, highlighting the need for similar rigorous optimization of the RNA substrates to facilitate structural studies of the ADAR1-RNA complex. The study was complemented by AlphaFold predictions, which provided some insights into this mechanism. Moreover, during this project I established a collaboration with a research group focused on studying ADAR homologs. Notably ADAR homologs were identified in bivalve species, and it was further demonstrated that ADAR and its A-to-I editing activity are upregulated in Pacific oysters during infections with Ostreid herpesvirus-1—a highly infectious virus that leads to significant losses in oyster populations globally. I successfully purified oyster ADAR and prepared in vitro edited RNA for nanopore sequencing—a direct sequencing technology capable of detecting modified nucleotides without the need for reverse transcription. The collaborators initiated optimization of this nanopore-based approach. However, current technological limitations still constrain the reliable detection of modified nucleotides. The project also examined the impact of RNA editing on RNA binding and filament formation by MDA5, a key cytosolic dsRNA sensor that triggers an interferon response. A primary target of ADAR1's editing activity is RNA derived from repetitive elements present in the genome, particularly Alu elements forming double-stranded RNA. When unedited, these RNA sequences are recognized by MDA5. However, the mechanisms by which MDA5 interacts with Alu RNAs, as well as the role of A-to-I editing in influencing this binding, are still not well understood. The interaction between MDA5 and Alu elements, was successfully established. This was achieved through the testing of different RNA variants and the evaluation of filament formation using binding techniques and electron microscopy imaging. This groundwork has set the conditions for further evaluation using CryoEM. Furthermore, the effects of A-to-I editing on the binding properties of MDA5 with Alu RNA were investigated. Given the recent research that has provided new insights into MDA5's interaction with dsRNA, it is essential to revise the experimental setup to integrate these findings before moving forward with the CryoEM sample analysis.}, author = {Kaczmarek, Beata M}, isbn = {978-3-99078-045-9}, issn = {2663-337X}, pages = {124}, publisher = {Institute of Science and Technology Austria}, title = {{Biochemical and structural insights into ADAR1 RNA editing}}, doi = {10.15479/at:ista:18477}, year = {2024}, } @phdthesis{15352, abstract = {Epilepsy affects about 50 to 65 million people globally. It summarizes a spectrum of neurological disorders that have in common a hyperactivity of the neuronal network resulting in seizures. A common assumption is that an imbalance between neuronal excitation and inhibition is a key mechanism in seizure generation and epileptogeneisis. In at least one-third of the patients, current therapies have proven unsuccessful in treating seizure progression. One potential reason could be that the therapies only focus on neurons. Recent studies suggest that neuronal hyperactivity causes a microglial response, which reinstates brain homeostasis. Additionally, interactions between microglia and neurons have been shown to inhibit neuronal firing and dampen seizure activity. However, the exact relationship between microglia and seizure progression in epilepsy is yet to be elucidated. A main bottleneck is that several studies investigate microglia dynamics in ex vivo slice models, which can severely affect the microglia dynamics due to their rapid response to environmental changes. On the other hand, in vivo studies focus mostly on behavior characterization of the epileptic seizure phenotype and their long-term consequences on microglia activity leaving out the direct consequences of acute seizure activity on microglia dynamics. Here, we perform a pilot study to combine electroencephalography (EEG) and in vivo live imaging to directly monitor and correlate the onset of seizure activity with microglia response. To induce seizures, we take advantage of the kainic acid (KA) model, which represents similar neuropathological and electroencephalographic features seen in human patients with temporal lobe epilepsy (TLE). After confirmation of induction of the seizure and microglia activity in the hippocampus as a focal point, we investigated whether these changes also reached the primary visual cortex (V1) as a secondary generalized seizure activity. Indeed, we found that microglia changed their morphology at high doses of KA in the V1. Next, we optimized each of the two methodological components: for the EEG recording, our initial attempts under the microscope suffered from extensive electrical noise, which overlaid the actual signal. Thus, we built a customized Faraday-cage and confirmed that the signal-to-noise ratio was sufficiently reduced to be able to record brain oscillatory activity. For the in vivo live imaging of microglia, we had to optimize the imaging parameters, so that we would be able to detect microglial processes in a sufficient resolution to track their process changes. Finally, we combined both methodologies with the KA model. We confirmed that KA induced seizure activity and found first indication that those correlate with microglia volume changes. Overall, we have developed a first methodological approach, which allows the analysis of the acute effects of seizure onset on microglia. Future studies will have to continue to optimize the drift during imaging recording and the post-image analysis. }, author = {Murmann, Julie Stefanie}, issn = {2791-4585}, pages = {54}, publisher = {Institute of Science and Technology Austria}, title = {{Investigating acute microglia response to seizure activity in vivo: Combining 2-Photon imaging and EEG recording}}, doi = {10.15479/at:ista:15352}, year = {2024}, } @phdthesis{14821, abstract = {The hippocampus is central to memory formation, storage and retrieval over many timescales. Neurons in this brain area are highly selective to spatial position as well as to many other variables of the environment. It is believed that the selectivity patterns of hippocampal neurons reflect the structure of tasks an animal performs. However, especially at timescales longer than a few minutes or hours it is not fully known how these representations evolve, nor how they map to behaviour in the process. In this thesis, I monitored the evolution of hippocampal representations in a novel spatial-associative memory task for rats. Reward locations were associated with global sensory cues (i.e. context); animals had to remember the associations and dig for food in those locations only. I used in vivo electrophysiology to record the activity of the hippocampus dorsal CA1 neurons during the learning period of a few days. I report here a novel and simple method to classify behaviour performance to account for individual variability in learning speed and spurious performance unrelated to true task rule learning. Using this classification I was then able to investigate neural responses on different stages of learning matched across animals. On the first day of learning, I observed a fast formation of single-cell selectivity to task variables which remained stable over days. I also observed that reward tuning was not a single process but dependent on task-related cognitive load. At the population level, a linear decoding approach revealed a hierarchy in the representation of task variables that changed with learning. In the high-dimensional space of population activity, the representation of contexts was specific to each position in the maze, and could thus be better decoded if the position was known. The decoding of position did not improve with knowledge of other variables. As learning progressed, the hippocampal code underwent a reorganisation of high-variance directions in population activity, identified by principal component analysis. I found that dominant dimensions started carrying increasing amounts of information about task context specifically at those positions where it mattered for task performance. When I contrasted this with variables less relevant to task performance (e.g. movement direction), I did not observe differences in decoding quality over positions nor a reduction of dimensionality with learning. Overall, the largest changes in CA1 neural response with task learning happened in a matter of a few trials; over days, changes undetectable in single-cell statistics were responsible for re-structuring the hierarchy of neural representations at the population level; these changes were task-specific and reflected different stages of learning. This indicates that complex task learning may involve different magnitudes of response modulation in CA1, which happen at specific time scales linked to behaviour.}, author = {Chiossi, Heloisa}, issn = {2663-337X}, pages = {89}, publisher = {Institute of Science and Technology Austria}, title = {{Adaptive hierarchical representations in the hippocampus}}, doi = {10.15479/at:ista:14821}, year = {2024}, } @article{14843, abstract = {The coupling between Ca2+ channels and release sensors is a key factor defining the signaling properties of a synapse. However, the coupling nanotopography at many synapses remains unknown, and it is unclear how it changes during development. To address these questions, we examined coupling at the cerebellar inhibitory basket cell (BC)-Purkinje cell (PC) synapse. Biophysical analysis of transmission by paired recording and intracellular pipette perfusion revealed that the effects of exogenous Ca2+ chelators decreased during development, despite constant reliance of release on P/Q-type Ca2+ channels. Structural analysis by freeze-fracture replica labeling (FRL) and transmission electron microscopy (EM) indicated that presynaptic P/Q-type Ca2+ channels formed nanoclusters throughout development, whereas docked vesicles were only clustered at later developmental stages. Modeling suggested a developmental transformation from a more random to a more clustered coupling nanotopography. Thus, presynaptic signaling developmentally approaches a point-to-point configuration, optimizing speed, reliability, and energy efficiency of synaptic transmission.}, author = {Chen, JingJing and Kaufmann, Walter and Chen, Chong and Arai, Itaru and Kim, Olena and Shigemoto, Ryuichi and Jonas, Peter M}, issn = {1097-4199}, journal = {Neuron}, number = {5}, pages = {755--771.e9}, publisher = {Elsevier}, title = {{Developmental transformation of Ca2+ channel-vesicle nanotopography at a central GABAergic synapse}}, doi = {10.1016/j.neuron.2023.12.002}, volume = {112}, year = {2024}, }