@article{305, abstract = {The hanging-drop network (HDN) is a technology platform based on a completely open microfluidic network at the bottom of an inverted, surface-patterned substrate. The platform is predominantly used for the formation, culturing, and interaction of self-assembled spherical microtissues (spheroids) under precisely controlled flow conditions. Here, we describe design, fabrication, and operation of microfluidic hanging-drop networks.}, author = {Misun, Patrick and Birchler, Axel and Lang, Moritz and Hierlemann, Andreas and Frey, Olivier}, journal = {Methods in Molecular Biology}, pages = {183 -- 202}, publisher = {Springer}, title = {{Fabrication and operation of microfluidic hanging drop networks}}, doi = {10.1007/978-1-4939-7792-5_15}, volume = {1771}, year = {2018}, } @article{306, abstract = {A cornerstone of statistical inference, the maximum entropy framework is being increasingly applied to construct descriptive and predictive models of biological systems, especially complex biological networks, from large experimental data sets. Both its broad applicability and the success it obtained in different contexts hinge upon its conceptual simplicity and mathematical soundness. Here we try to concisely review the basic elements of the maximum entropy principle, starting from the notion of ‘entropy’, and describe its usefulness for the analysis of biological systems. As examples, we focus specifically on the problem of reconstructing gene interaction networks from expression data and on recent work attempting to expand our system-level understanding of bacterial metabolism. Finally, we highlight some extensions and potential limitations of the maximum entropy approach, and point to more recent developments that are likely to play a key role in the upcoming challenges of extracting structures and information from increasingly rich, high-throughput biological data.}, author = {De Martino, Andrea and De Martino, Daniele}, journal = {Heliyon}, number = {4}, publisher = {Elsevier}, title = {{An introduction to the maximum entropy approach and its application to inference problems in biology}}, doi = {10.1016/j.heliyon.2018.e00596}, volume = {4}, year = {2018}, } @article{307, abstract = {Spontaneous emission spectra of two initially excited closely spaced identical atoms are very sensitive to the strength and the direction of the applied magnetic field. We consider the relevant schemes that ensure the determination of the mutual spatial orientation of the atoms and the distance between them by entirely optical means. A corresponding theoretical description is given accounting for the dipole-dipole interaction between the two atoms in the presence of a magnetic field and for polarizations of the quantum field interacting with magnetic sublevels of the two-atom system. }, author = {Redchenko, Elena and Makarov, Alexander and Yudson, Vladimir}, journal = { Physical Review A - Atomic, Molecular, and Optical Physics}, number = {4}, publisher = {American Physical Society}, title = {{Nanoscopy of pairs of atoms by fluorescence in a magnetic field}}, doi = {10.1103/PhysRevA.97.043812}, volume = {97}, year = {2018}, } @article{308, abstract = {Migrating cells penetrate tissue barriers during development, inflammatory responses, and tumor metastasis. We study if migration in vivo in such three-dimensionally confined environments requires changes in the mechanical properties of the surrounding cells using embryonic Drosophila melanogaster hemocytes, also called macrophages, as a model. We find that macrophage invasion into the germband through transient separation of the apposing ectoderm and mesoderm requires cell deformations and reductions in apical tension in the ectoderm. Interestingly, the genetic pathway governing these mechanical shifts acts downstream of the only known tumor necrosis factor superfamily member in Drosophila, Eiger, and its receptor, Grindelwald. Eiger-Grindelwald signaling reduces levels of active Myosin in the germband ectodermal cortex through the localization of a Crumbs complex component, Patj (Pals-1-associated tight junction protein). We therefore elucidate a distinct molecular pathway that controls tissue tension and demonstrate the importance of such regulation for invasive migration in vivo.}, author = {Ratheesh, Aparna and Biebl, Julia and Smutny, Michael and Veselá, Jana and Papusheva, Ekaterina and Krens, Gabriel and Kaufmann, Walter and György, Attila and Casano, Alessandra M and Siekhaus, Daria E}, journal = {Developmental Cell}, number = {3}, pages = {331 -- 346}, publisher = {Elsevier}, title = {{Drosophila TNF modulates tissue tension in the embryo to facilitate macrophage invasive migration}}, doi = {10.1016/j.devcel.2018.04.002}, volume = {45}, year = {2018}, } @inproceedings{309, abstract = {We present an efficient algorithm for a problem in the interface between clustering and graph embeddings. An embedding ' : G ! M of a graph G into a 2manifold M maps the vertices in V (G) to distinct points and the edges in E(G) to interior-disjoint Jordan arcs between the corresponding vertices. In applications in clustering, cartography, and visualization, nearby vertices and edges are often bundled to a common node or arc, due to data compression or low resolution. This raises the computational problem of deciding whether a given map ' : G ! M comes from an embedding. A map ' : G ! M is a weak embedding if it can be perturbed into an embedding ψ: G ! M with k' "k < " for every " > 0. A polynomial-time algorithm for recognizing weak embeddings was recently found by Fulek and Kyncl [14], which reduces to solving a system of linear equations over Z2. It runs in O(n2!) O(n4:75) time, where 2:373 is the matrix multiplication exponent and n is the number of vertices and edges of G. We improve the running time to O(n log n). Our algorithm is also conceptually simpler than [14]: We perform a sequence of local operations that gradually "untangles" the image '(G) into an embedding (G), or reports that ' is not a weak embedding. It generalizes a recent technique developed for the case that G is a cycle and the embedding is a simple polygon [1], and combines local constraints on the orientation of subgraphs directly, thereby eliminating the need for solving large systems of linear equations.}, author = {Akitaya, Hugo and Fulek, Radoslav and Tóth, Csaba}, location = {New Orleans, LA, USA}, pages = {274 -- 292}, publisher = {ACM}, title = {{Recognizing weak embeddings of graphs}}, doi = {10.1137/1.9781611975031.20}, year = {2018}, } @article{31, abstract = {Correlations in sensory neural networks have both extrinsic and intrinsic origins. Extrinsic or stimulus correlations arise from shared inputs to the network and, thus, depend strongly on the stimulus ensemble. Intrinsic or noise correlations reflect biophysical mechanisms of interactions between neurons, which are expected to be robust to changes in the stimulus ensemble. Despite the importance of this distinction for understanding how sensory networks encode information collectively, no method exists to reliably separate intrinsic interactions from extrinsic correlations in neural activity data, limiting our ability to build predictive models of the network response. In this paper we introduce a general strategy to infer population models of interacting neurons that collectively encode stimulus information. The key to disentangling intrinsic from extrinsic correlations is to infer the couplings between neurons separately from the encoding model and to combine the two using corrections calculated in a mean-field approximation. We demonstrate the effectiveness of this approach in retinal recordings. The same coupling network is inferred from responses to radically different stimulus ensembles, showing that these couplings indeed reflect stimulus-independent interactions between neurons. The inferred model predicts accurately the collective response of retinal ganglion cell populations as a function of the stimulus.}, author = {Ferrari, Ulisse and Deny, Stephane and Chalk, Matthew J and Tkacik, Gasper and Marre, Olivier and Mora, Thierry}, issn = {24700045}, journal = {Physical Review E}, number = {4}, publisher = {American Physical Society}, title = {{Separating intrinsic interactions from extrinsic correlations in a network of sensory neurons}}, doi = {10.1103/PhysRevE.98.042410}, volume = {98}, year = {2018}, } @inproceedings{310, abstract = {A model of computation that is widely used in the formal analysis of reactive systems is symbolic algorithms. In this model the access to the input graph is restricted to consist of symbolic operations, which are expensive in comparison to the standard RAM operations. We give lower bounds on the number of symbolic operations for basic graph problems such as the computation of the strongly connected components and of the approximate diameter as well as for fundamental problems in model checking such as safety, liveness, and coliveness. Our lower bounds are linear in the number of vertices of the graph, even for constant-diameter graphs. For none of these problems lower bounds on the number of symbolic operations were known before. The lower bounds show an interesting separation of these problems from the reachability problem, which can be solved with O(D) symbolic operations, where D is the diameter of the graph. Additionally we present an approximation algorithm for the graph diameter which requires Õ(n/D) symbolic steps to achieve a (1 +ϵ)-approximation for any constant > 0. This compares to O(n/D) symbolic steps for the (naive) exact algorithm and O(D) symbolic steps for a 2-approximation. Finally we also give a refined analysis of the strongly connected components algorithms of [15], showing that it uses an optimal number of symbolic steps that is proportional to the sum of the diameters of the strongly connected components.}, author = {Chatterjee, Krishnendu and Dvorák, Wolfgang and Henzinger, Monika H and Loitzenbauer, Veronika}, location = {New Orleans, Louisiana, United States}, pages = {2341 -- 2356}, publisher = {ACM}, title = {{Lower bounds for symbolic computation on graphs: Strongly connected components, liveness, safety, and diameter}}, doi = {10.1137/1.9781611975031.151}, year = {2018}, } @inproceedings{311, abstract = {Smart contracts are computer programs that are executed by a network of mutually distrusting agents, without the need of an external trusted authority. Smart contracts handle and transfer assets of considerable value (in the form of crypto-currency like Bitcoin). Hence, it is crucial that their implementation is bug-free. We identify the utility (or expected payoff) of interacting with such smart contracts as the basic and canonical quantitative property for such contracts. We present a framework for such quantitative analysis of smart contracts. Such a formal framework poses new and novel research challenges in programming languages, as it requires modeling of game-theoretic aspects to analyze incentives for deviation from honest behavior and modeling utilities which are not specified as standard temporal properties such as safety and termination. While game-theoretic incentives have been analyzed in the security community, their analysis has been restricted to the very special case of stateless games. However, to analyze smart contracts, stateful analysis is required as it must account for the different program states of the protocol. Our main contributions are as follows: we present (i)~a simplified programming language for smart contracts; (ii)~an automatic translation of the programs to state-based games; (iii)~an abstraction-refinement approach to solve such games; and (iv)~experimental results on real-world-inspired smart contracts.}, author = {Chatterjee, Krishnendu and Goharshady, Amir and Velner, Yaron}, location = {Thessaloniki, Greece}, pages = {739 -- 767}, publisher = {Springer}, title = {{Quantitative analysis of smart contracts}}, doi = {10.1007/978-3-319-89884-1_26}, volume = {10801}, year = {2018}, } @article{312, abstract = {Motivated by biological questions, we study configurations of equal spheres that neither pack nor cover. Placing their centers on a lattice, we define the soft density of the configuration by penalizing multiple overlaps. Considering the 1-parameter family of diagonally distorted 3-dimensional integer lattices, we show that the soft density is maximized at the FCC lattice.}, author = {Edelsbrunner, Herbert and Iglesias Ham, Mabel}, issn = {08954801}, journal = {SIAM J Discrete Math}, number = {1}, pages = {750 -- 782}, publisher = {Society for Industrial and Applied Mathematics }, title = {{On the optimality of the FCC lattice for soft sphere packing}}, doi = {10.1137/16M1097201}, volume = {32}, year = {2018}, } @article{314, abstract = {The interface of physics and biology pro-vides a fruitful environment for generatingnew concepts and exciting ways forwardto understanding living matter. Examplesof successful studies include the estab-lishment and readout of morphogen gra-dients during development, signal pro-cessing in protein and genetic networks,the role of fluctuations in determining thefates of cells and tissues, and collectiveeffects in proteins and in tissues. It is nothard to envision that significant further ad-vances will translate to societal benefitsby initiating the development of new de-vices and strategies for curing disease.However, research at the interface posesvarious challenges, in particular for youngscientists, and current institutions arerarely designed to facilitate such scientificprograms. In this Letter, we propose aninternational initiative that addressesthese challenges through the establish-ment of a worldwide network of platformsfor cross-disciplinary training and incuba-tors for starting new collaborations.}, author = {Bauer, Guntram and Fakhri, Nikta and Kicheva, Anna and Kondev, Jané and Kruse, Karsten and Noji, Hiroyuki and Riveline, Daniel and Saunders, Timothy and Thatta, Mukund and Wieschaus, Eric}, issn = {2405-4712}, journal = {Cell Systems}, number = {4}, pages = {400 -- 402}, publisher = {Cell Press}, title = {{The science of living matter for tomorrow}}, doi = {10.1016/j.cels.2018.04.003}, volume = {6}, year = {2018}, } @article{315, abstract = {More than 100 years after Grigg’s influential analysis of species’ borders, the causes of limits to species’ ranges still represent a puzzle that has never been understood with clarity. The topic has become especially important recently as many scientists have become interested in the potential for species’ ranges to shift in response to climate change—and yet nearly all of those studies fail to recognise or incorporate evolutionary genetics in a way that relates to theoretical developments. I show that range margins can be understood based on just two measurable parameters: (i) the fitness cost of dispersal—a measure of environmental heterogeneity—and (ii) the strength of genetic drift, which reduces genetic diversity. Together, these two parameters define an ‘expansion threshold’: adaptation fails when genetic drift reduces genetic diversity below that required for adaptation to a heterogeneous environment. When the key parameters drop below this expansion threshold locally, a sharp range margin forms. When they drop below this threshold throughout the species’ range, adaptation collapses everywhere, resulting in either extinction or formation of a fragmented metapopulation. Because the effects of dispersal differ fundamentally with dimension, the second parameter—the strength of genetic drift—is qualitatively different compared to a linear habitat. In two-dimensional habitats, genetic drift becomes effectively independent of selection. It decreases with ‘neighbourhood size’—the number of individuals accessible by dispersal within one generation. Moreover, in contrast to earlier predictions, which neglected evolution of genetic variance and/or stochasticity in two dimensions, dispersal into small marginal populations aids adaptation. This is because the reduction of both genetic and demographic stochasticity has a stronger effect than the cost of dispersal through increased maladaptation. The expansion threshold thus provides a novel, theoretically justified, and testable prediction for formation of the range margin and collapse of the species’ range.}, author = {Polechova, Jitka}, issn = {15449173}, journal = {PLoS Biology}, number = {6}, publisher = {Public Library of Science}, title = {{Is the sky the limit? On the expansion threshold of a species’ range}}, doi = {10.1371/journal.pbio.2005372}, volume = {16}, year = {2018}, } @article{316, abstract = {Self-incompatibility (SI) is a genetically based recognition system that functions to prevent self-fertilization and mating among related plants. An enduring puzzle in SI is how the high diversity observed in nature arises and is maintained. Based on the underlying recognition mechanism, SI can be classified into two main groups: self- and non-self recognition. Most work has focused on diversification within self-recognition systems despite expected differences between the two groups in the evolutionary pathways and outcomes of diversification. Here, we use a deterministic population genetic model and stochastic simulations to investigate how novel S-haplotypes evolve in a gametophytic non-self recognition (SRNase/S Locus F-box (SLF)) SI system. For this model the pathways for diversification involve either the maintenance or breakdown of SI and can vary in the order of mutations of the female (SRNase) and male (SLF) components. We show analytically that diversification can occur with high inbreeding depression and self-pollination, but this varies with evolutionary pathway and level of completeness (which determines the number of potential mating partners in the population), and in general is more likely for lower haplotype number. The conditions for diversification are broader in stochastic simulations of finite population size. However, the number of haplotypes observed under high inbreeding and moderate to high self-pollination is less than that commonly observed in nature. Diversification was observed through pathways that maintain SI as well as through self-compatible intermediates. Yet the lifespan of diversified haplotypes was sensitive to their level of completeness. By examining diversification in a non-self recognition SI system, this model extends our understanding of the evolution and maintenance of haplotype diversity observed in a self recognition system common in flowering plants.}, author = {Bodova, Katarina and Priklopil, Tadeas and Field, David and Barton, Nicholas H and Pickup, Melinda}, journal = {Genetics}, number = {3}, pages = {861--883}, publisher = {Genetics Society of America}, title = {{Evolutionary pathways for the generation of new self-incompatibility haplotypes in a non-self recognition system}}, doi = {10.1534/genetics.118.300748}, volume = {209}, year = {2018}, } @article{317, abstract = {We replace the established aluminium gates for the formation of quantum dots in silicon with gates made from palladium. We study the morphology of both aluminium and palladium gates with transmission electron microscopy. The native aluminium oxide is found to be formed all around the aluminium gates, which could lead to the formation of unintentional dots. Therefore, we report on a novel fabrication route that replaces aluminium and its native oxide by palladium with atomic-layer-deposition-grown aluminium oxide. Using this approach, we show the formation of low-disorder gate-defined quantum dots, which are reproducibly fabricated. Furthermore, palladium enables us to further shrink the gate design, allowing us to perform electron transport measurements in the few-electron regime in devices comprising only two gate layers, a major technological advancement. It remains to be seen, whether the introduction of palladium gates can improve the excellent results on electron and nuclear spin qubits defined with an aluminium gate stack.}, author = {Brauns, Matthias and Amitonov, Sergey and Spruijtenburg, Paul and Zwanenburg, Floris}, journal = {Scientific Reports}, number = {1}, publisher = {Nature Publishing Group}, title = {{Palladium gates for reproducible quantum dots in silicon}}, doi = {10.1038/s41598-018-24004-y}, volume = {8}, year = {2018}, } @article{318, abstract = {The insect’s fat body combines metabolic and immunological functions. In this issue of Developmental Cell, Franz et al. (2018) show that in Drosophila, cells of the fat body are not static, but can actively “swim” toward sites of epithelial injury, where they physically clog the wound and locally secrete antimicrobial peptides.}, author = {Casano, Alessandra M and Sixt, Michael K}, journal = {Developmental Cell}, number = {4}, pages = {405 -- 406}, publisher = {Cell Press}, title = {{A fat lot of good for wound healing}}, doi = {10.1016/j.devcel.2018.02.009}, volume = {44}, year = {2018}, } @article{32, abstract = {The functional role of AMPA receptor (AMPAR)-mediated synaptic signaling between neurons and oligodendrocyte precursor cells (OPCs) remains enigmatic. We modified the properties of AMPARs at axon-OPC synapses in the mouse corpus callosum in vivo during the peak of myelination by targeting the GluA2 subunit. Expression of the unedited (Ca2+ permeable) or the pore-dead GluA2 subunit of AMPARs triggered proliferation of OPCs and reduced their differentiation into oligodendrocytes. Expression of the cytoplasmic C-terminal (GluA2(813-862)) of the GluA2 subunit (C-tail), a modification designed to affect the interaction between GluA2 and AMPAR-binding proteins and to perturb trafficking of GluA2-containing AMPARs, decreased the differentiation of OPCs without affecting their proliferation. These findings suggest that ionotropic and non-ionotropic properties of AMPARs in OPCs, as well as specific aspects of AMPAR-mediated signaling at axon-OPC synapses in the mouse corpus callosum, are important for balancing the response of OPCs to proliferation and differentiation cues. In the brain, oligodendrocyte precursor cells (OPCs) receive glutamatergic AMPA-receptor-mediated synaptic input from neurons. Chen et al. show that modifying AMPA-receptor properties at axon-OPC synapses alters proliferation and differentiation of OPCs. This expands the traditional view of synaptic transmission by suggesting neurons also use synapses to modulate behavior of glia.}, author = {Chen, Ting and Kula, Bartosz and Nagy, Balint and Barzan, Ruxandra and Gall, Andrea and Ehrlich, Ingrid and Kukley, Maria}, journal = {Cell Reports}, number = {4}, pages = {852 -- 861.e7}, publisher = {Elsevier}, title = {{In Vivo regulation of Oligodendrocyte processor cell proliferation and differentiation by the AMPA-receptor Subunit GluA2}}, doi = {10.1016/j.celrep.2018.09.066}, volume = {25}, year = {2018}, } @article{320, abstract = {Fast-spiking, parvalbumin-expressing GABAergic interneurons (PV+-BCs) express a complex machinery of rapid signaling mechanisms, including specialized voltage-gated ion channels to generate brief action potentials (APs). However, short APs are associated with overlapping Na+ and K+ fluxes and are therefore energetically expensive. How the potentially vicious combination of high AP frequency and inefficient spike generation can be reconciled with limited energy supply is presently unclear. To address this question, we performed direct recordings from the PV+-BC axon, the subcellular structure where active conductances for AP initiation and propagation are located. Surprisingly, the energy required for the AP was, on average, only ∼1.6 times the theoretical minimum. High energy efficiency emerged from the combination of fast inactivation of Na+ channels and delayed activation of Kv3-type K+ channels, which minimized ion flux overlap during APs. Thus, the complementary tuning of axonal Na+ and K+ channel gating optimizes both fast signaling properties and metabolic efficiency. Hu et al. demonstrate that action potentials in parvalbumin-expressing GABAergic interneuron axons are energetically efficient, which is highly unexpected given their brief duration. High energy efficiency emerges from the combination of fast inactivation of voltage-gated Na+ channels and delayed activation of Kv3 channels in the axon. }, author = {Hu, Hua and Roth, Fabian and Vandael, David H and Jonas, Peter M}, journal = {Neuron}, number = {1}, pages = {156 -- 165}, publisher = {Elsevier}, title = {{Complementary tuning of Na+ and K+ channel gating underlies fast and energy-efficient action potentials in GABAergic interneuron axons}}, doi = {10.1016/j.neuron.2018.02.024}, volume = {98}, year = {2018}, } @article{321, abstract = {The twelve papers in this special section focus on learning systems with shared information for computer vision and multimedia communication analysis. In the real world, a realistic setting for computer vision or multimedia recognition problems is that we have some classes containing lots of training data and many classes containing a small amount of training data. Therefore, how to use frequent classes to help learning rare classes for which it is harder to collect the training data is an open question. Learning with shared information is an emerging topic in machine learning, computer vision and multimedia analysis. There are different levels of components that can be shared during concept modeling and machine learning stages, such as sharing generic object parts, sharing attributes, sharing transformations, sharing regularization parameters and sharing training examples, etc. Regarding the specific methods, multi-task learning, transfer learning and deep learning can be seen as using different strategies to share information. These learning with shared information methods are very effective in solving real-world large-scale problems.}, author = {Darrell, Trevor and Lampert, Christoph and Sebe, Nico and Wu, Ying and Yan, Yan}, journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence}, number = {5}, pages = {1029 -- 1031}, publisher = {IEEE}, title = {{Guest editors' introduction to the special section on learning with Shared information for computer vision and multimedia analysis}}, doi = {10.1109/TPAMI.2018.2804998}, volume = {40}, year = {2018}, } @article{322, abstract = {We construct quantizations of multiplicative hypertoric varieties using an algebra of q-difference operators on affine space, where q is a root of unity in C. The quantization defines a matrix bundle (i.e. Azumaya algebra) over the multiplicative hypertoric variety and admits an explicit finite étale splitting. The global sections of this Azumaya algebra is a hypertoric quantum group, and we prove a localization theorem. We introduce a general framework of Frobenius quantum moment maps and their Hamiltonian reductions; our results shed light on an instance of this framework.}, author = {Ganev, Iordan V}, journal = {Journal of Algebra}, pages = {92 -- 128}, publisher = {World Scientific Publishing}, title = {{Quantizations of multiplicative hypertoric varieties at a root of unity}}, doi = {10.1016/j.jalgebra.2018.03.015}, volume = {506}, year = {2018}, } @phdthesis{323, abstract = {In the here presented thesis, we explore the role of branched actin networks in cell migration and antigen presentation, the two most relevant processes in dendritic cell biology. Branched actin networks construct lamellipodial protrusions at the leading edge of migrating cells. These are typically seen as adhesive structures, which mediate force transduction to the extracellular matrix that leads to forward locomotion. We ablated Arp2/3 nucleation promoting factor WAVE in DCs and found that the resulting cells lack lamellipodial protrusions. Instead, depending on the maturation state, one or multiple filopodia were formed. By challenging these cells in a variety of migration assays we found that lamellipodial protrusions are dispensable for the locomotion of leukocytes and actually dampen the speed of migration. However, lamellipodia are critically required to negotiate complex environments that DCs experience while they travel to the next draining lymph node. Taken together our results suggest that leukocyte lamellipodia have rather a sensory- than a force transducing function. Furthermore, we show for the first time structure and dynamics of dendritic cell F-actin at the immunological synapse with naïve T cells. Dendritic cell F-actin appears as dynamic foci that are nucleated by the Arp2/3 complex. WAVE ablated dendritic cells show increased membrane tension, leading to an altered ultrastructure of the immunological synapse and severe T cell priming defects. These results point towards a previously unappreciated role of the cellular mechanics of dendritic cells in T cell activation. Additionally, we present a novel cell culture based system for the differentiation of dendritic cells from conditionally immortalized hematopoietic precursors. These precursor cells are genetically tractable via the CRISPR/Cas9 system while they retain their ability to differentiate into highly migratory dendritic cells and other immune cells. This will foster the study of all aspects of dendritic cell biology and beyond. }, author = {Leithner, Alexander F}, issn = {2663-337X}, pages = {99}, publisher = {Institute of Science and Technology Austria}, title = {{Branched actin networks in dendritic cell biology}}, doi = {10.15479/AT:ISTA:th_998}, year = {2018}, } @phdthesis{324, abstract = {Neuronal networks in the brain consist of two main types of neuron, glutamatergic principal neurons and GABAergic interneurons. Although these interneurons only represent 10–20% of the whole population, they mediate feedback and feedforward inhibition and are involved in the generation of high-frequency network oscillations. A hallmark functional property of GABAergic interneurons, especially of the parvalbumin‑expressing (PV+) subtypes, is the speed of signaling at their output synapse across species and brain regions. Several molecular and subcellular factors may underlie the submillisecond signaling at GABAergic synapses. Such as the selective use of P/Q type Ca2+ channels and the tight coupling between Ca2+ channels and Ca2+ sensors of exocytosis. However, whether the molecular identity of the release sensor contributes to these signaling properties remains unclear. Besides, these interneurons are mainly show depression in response to train of stimuli. How could they keep sufficient release to control the activity of postsynaptic principal neurons during high network activity, is largely elusive. For my Ph.D. work, we firstly examined the Ca2+ sensor of exocytosis at the GABAergic basket cell (BC) to Purkinje cell (PC) synapse in the cerebellum. Immunolabeling suggested that BC terminals selectively expressed synaptotagmin 2 (Syt2), whereas synaptotagmin 1 (Syt1) was enriched in excitatory terminals. Genetic elimination of Syt2 reduced action potential-evoked release to ~10% compared to the wild-type control, identifying Syt2 as the major Ca2+ sensor at BC‑PC synapses. Differential adenovirus-mediated rescue revealed Syt2 triggered release with shorter latency and higher temporal precision, and mediated faster vesicle pool replenishment than Syt1. Furthermore, deletion of Syt2 severely reduced and delayed disynaptic inhibition following parallel fiber stimulation. Thus, the selective use of Syt2 as the release sensor at BC–PC synapse ensures fast feedforward inhibition in cerebellar microcircuits. Additionally, we tested the function of another synaptotagmin member, Syt7, for inhibitory synaptic transmission at the BC–PC synapse. Syt7 is thought to be a Ca2+ sensor that mediates asynchronous transmitter release and facilitation at synapses. However, it is strongly expressed in fast-spiking, PV+ GABAergic interneurons and the output synapses of these neurons produce only minimal asynchronous release and show depression rather than facilitation. How could Syt7, a facilitation sensor, contribute to the depressed inhibitory synaptic transmission needs to be further investigated and understood. Our results indicated that at the BC–PC synapse, Syt7 contributes to asynchronous release, pool replenishment and facilitation. In combination, these three effects ensure efficient transmitter release during high‑frequency activity and guarantee frequency independence of inhibition. Taken together, our results confirmed that Syt2, which has the fastest kinetic properties among all synaptotagmin members, is mainly used by the inhibitory BC‑PC synapse for synaptic transmission, contributing to the speed and temporal precision of transmitter release. Furthermore, we showed that Syt7, another highly expressed synaptotagmin member in the output synapses of cerebellar BCs, is used for ensuring efficient inhibitor synaptic transmission during high activity.}, author = {Chen, Chong}, issn = {2663-337X}, pages = {110}, publisher = {Institute of Science and Technology Austria}, title = {{Synaptotagmins ensure speed and efficiency of inhibitory neurotransmitter release}}, doi = {10.15479/AT:ISTA:th_997}, year = {2018}, }