TY - JOUR AB - Poxviruses are among the largest double-stranded DNA viruses, with members such as variola virus, monkeypox virus and the vaccination strain vaccinia virus (VACV). Knowledge about the structural proteins that form the viral core has remained sparse. While major core proteins have been annotated via indirect experimental evidence, their structures have remained elusive and they could not be assigned to individual core features. Hence, which proteins constitute which layers of the core, such as the palisade layer and the inner core wall, has remained enigmatic. Here we show, using a multi-modal cryo-electron microscopy (cryo-EM) approach in combination with AlphaFold molecular modeling, that trimers formed by the cleavage product of VACV protein A10 are the key component of the palisade layer. This allows us to place previously obtained descriptions of protein interactions within the core wall into perspective and to provide a detailed model of poxvirus core architecture. Importantly, we show that interactions within A10 trimers are likely generalizable over members of orthopox- and parapoxviruses. AU - Datler, Julia AU - Hansen, Jesse AU - Thader, Andreas AU - Schlögl, Alois AU - Bauer, Lukas W AU - Hodirnau, Victor-Valentin AU - Schur, Florian KM ID - 14979 JF - Nature Structural & Molecular Biology KW - Molecular Biology KW - Structural Biology SN - 1545-9993 TI - Multi-modal cryo-EM reveals trimers of protein A10 to form the palisade layer in poxvirus cores ER - TY - JOUR AB - Post-translational histone modifications modulate chromatin activity to affect gene expression. How chromatin states underlie lineage choice in single cells is relatively unexplored. We develop sort-assisted single-cell chromatin immunocleavage (sortChIC) and map active (H3K4me1 and H3K4me3) and repressive (H3K27me3 and H3K9me3) histone modifications in the mouse bone marrow. During differentiation, hematopoietic stem and progenitor cells (HSPCs) acquire active chromatin states mediated by cell-type-specifying transcription factors, which are unique for each lineage. By contrast, most alterations in repressive marks during differentiation occur independent of the final cell type. Chromatin trajectory analysis shows that lineage choice at the chromatin level occurs at the progenitor stage. Joint profiling of H3K4me1 and H3K9me3 demonstrates that cell types within the myeloid lineage have distinct active chromatin but share similar myeloid-specific heterochromatin states. This implies a hierarchical regulation of chromatin during hematopoiesis: heterochromatin dynamics distinguish differentiation trajectories and lineages, while euchromatin dynamics reflect cell types within lineages. AU - Zeller, Peter AU - Yeung, Jake AU - Viñas Gaza, Helena AU - de Barbanson, Buys Anton AU - Bhardwaj, Vivek AU - Florescu, Maria AU - van der Linden, Reinier AU - van Oudenaarden, Alexander ID - 12158 JF - Nature Genetics KW - Genetics SN - 1061-4036 TI - Single-cell sortChIC identifies hierarchical chromatin dynamics during hematopoiesis VL - 55 ER - TY - GEN AU - Elefante, Stefano AU - Stadlbauer, Stephan AU - Alexander, Michael F AU - Schlögl, Alois ID - 13162 T2 - ASHPC23 - Austrian-Slovenian HPC Meeting 2023 TI - Cryo-EM software packages: A sys-admins point of view ER - TY - GEN AU - Schlögl, Alois AU - Elefante, Stefano AU - Hodirnau, Victor-Valentin ID - 13161 T2 - ASHPC23 - Austrian-Slovenian HPC Meeting 2023 TI - Running Windows-applications on a Linux HPC cluster using WINE ER - TY - JOUR AB - Regulation of chromatin states involves the dynamic interplay between different histone modifications to control gene expression. Recent advances have enabled mapping of histone marks in single cells, but most methods are constrained to profile only one histone mark per cell. Here, we present an integrated experimental and computational framework, scChIX-seq (single-cell chromatin immunocleavage and unmixing sequencing), to map several histone marks in single cells. scChIX-seq multiplexes two histone marks together in single cells, then computationally deconvolves the signal using training data from respective histone mark profiles. This framework learns the cell-type-specific correlation structure between histone marks, and therefore does not require a priori assumptions of their genomic distributions. Using scChIX-seq, we demonstrate multimodal analysis of histone marks in single cells across a range of mark combinations. Modeling dynamics of in vitro macrophage differentiation enables integrated analysis of chromatin velocity. Overall, scChIX-seq unlocks systematic interrogation of the interplay between histone modifications in single cells. AU - Yeung, Jake AU - Florescu, Maria AU - Zeller, Peter AU - De Barbanson, Buys Anton AU - Wellenstein, Max D. AU - Van Oudenaarden, Alexander ID - 12106 JF - Nature Biotechnology SN - 1087-0156 TI - scChIX-seq infers dynamic relationships between histone modifications in single cells VL - 41 ER - TY - JOUR AB - The rapid development of machine learning (ML) techniques has opened up the data-dense field of microbiome research for novel therapeutic, diagnostic, and prognostic applications targeting a wide range of disorders, which could substantially improve healthcare practices in the era of precision medicine. However, several challenges must be addressed to exploit the benefits of ML in this field fully. In particular, there is a need to establish “gold standard” protocols for conducting ML analysis experiments and improve interactions between microbiome researchers and ML experts. The Machine Learning Techniques in Human Microbiome Studies (ML4Microbiome) COST Action CA18131 is a European network established in 2019 to promote collaboration between discovery-oriented microbiome researchers and data-driven ML experts to optimize and standardize ML approaches for microbiome analysis. This perspective paper presents the key achievements of ML4Microbiome, which include identifying predictive and discriminatory ‘omics’ features, improving repeatability and comparability, developing automation procedures, and defining priority areas for the novel development of ML methods targeting the microbiome. The insights gained from ML4Microbiome will help to maximize the potential of ML in microbiome research and pave the way for new and improved healthcare practices. AU - D’Elia, Domenica AU - Truu, Jaak AU - Lahti, Leo AU - Berland, Magali AU - Papoutsoglou, Georgios AU - Ceci, Michelangelo AU - Zomer, Aldert AU - Lopes, Marta B. AU - Ibrahimi, Eliana AU - Gruca, Aleksandra AU - Nechyporenko, Alina AU - Frohme, Marcus AU - Klammsteiner, Thomas AU - Pau, Enrique Carrillo De Santa AU - Marcos-Zambrano, Laura Judith AU - Hron, Karel AU - Pio, Gianvito AU - Simeon, Andrea AU - Suharoschi, Ramona AU - Moreno-Indias, Isabel AU - Temko, Andriy AU - Nedyalkova, Miroslava AU - Apostol, Elena Simona AU - Truică, Ciprian Octavian AU - Shigdel, Rajesh AU - Telalović, Jasminka Hasić AU - Bongcam-Rudloff, Erik AU - Przymus, Piotr AU - Jordamović, Naida Babić AU - Falquet, Laurent AU - Tarazona, Sonia AU - Sampri, Alexia AU - Isola, Gaetano AU - Pérez-Serrano, David AU - Trajkovik, Vladimir AU - Klucar, Lubos AU - Loncar-Turukalo, Tatjana AU - Havulinna, Aki S. AU - Jansen, Christian AU - Bertelsen, Randi J. AU - Claesson, Marcus Joakim ID - 14449 JF - Frontiers in Microbiology TI - Advancing microbiome research with machine learning: Key findings from the ML4Microbiome COST action VL - 14 ER - TY - GEN AU - Schlögl, Alois AU - Hornoiu, Andrei AU - Elefante, Stefano AU - Stadlbauer, Stephan ID - 12894 SN - 978-3-200-08499-5 T2 - ASHPC22 - Austrian-Slovenian HPC Meeting 2022 TI - Where is the sweet spot? A procurement story of general purpose compute nodes ER - TY - GEN AU - Schlögl, Alois AU - Elefante, Stefano AU - Hornoiu, Andrei AU - Stadlbauer, Stephan ID - 12909 SN - 978-961-6980-77-7 T2 - ASHPC21 – Austrian-Slovenian HPC Meeting 2021 TI - Managing software on a heterogenous HPC cluster ER - TY - JOUR AB - Background: To understand information coding in single neurons, it is necessary to analyze subthreshold synaptic events, action potentials (APs), and their interrelation in different behavioral states. However, detecting excitatory postsynaptic potentials (EPSPs) or currents (EPSCs) in behaving animals remains challenging, because of unfavorable signal-to-noise ratio, high frequency, fluctuating amplitude, and variable time course of synaptic events. New method: We developed a method for synaptic event detection, termed MOD (Machine-learning Optimal-filtering Detection-procedure), which combines concepts of supervised machine learning and optimal Wiener filtering. Experts were asked to manually score short epochs of data. The algorithm was trained to obtain the optimal filter coefficients of a Wiener filter and the optimal detection threshold. Scored and unscored data were then processed with the optimal filter, and events were detected as peaks above threshold. Results: We challenged MOD with EPSP traces in vivo in mice during spatial navigation and EPSC traces in vitro in slices under conditions of enhanced transmitter release. The area under the curve (AUC) of the receiver operating characteristics (ROC) curve was, on average, 0.894 for in vivo and 0.969 for in vitro data sets, indicating high detection accuracy and efficiency. Comparison with existing methods: When benchmarked using a (1 − AUC)−1 metric, MOD outperformed previous methods (template-fit, deconvolution, and Bayesian methods) by an average factor of 3.13 for in vivo data sets, but showed comparable (template-fit, deconvolution) or higher (Bayesian) computational efficacy. Conclusions: MOD may become an important new tool for large-scale, real-time analysis of synaptic activity. AU - Zhang, Xiaomin AU - Schlögl, Alois AU - Vandael, David H AU - Jonas, Peter M ID - 9329 IS - 6 JF - Journal of Neuroscience Methods SN - 0165-0270 TI - MOD: A novel machine-learning optimal-filtering method for accurate and efficient detection of subthreshold synaptic events in vivo VL - 357 ER - TY - COMP AB - Pattern separation is a fundamental brain computation that converts small differences in input patterns into large differences in output patterns. Several synaptic mechanisms of pattern separation have been proposed, including code expansion, inhibition and plasticity; however, which of these mechanisms play a role in the entorhinal cortex (EC)–dentate gyrus (DG)–CA3 circuit, a classical pattern separation circuit, remains unclear. Here we show that a biologically realistic, full-scale EC–DG–CA3 circuit model, including granule cells (GCs) and parvalbumin-positive inhibitory interneurons (PV+-INs) in the DG, is an efficient pattern separator. Both external gamma-modulated inhibition and internal lateral inhibition mediated by PV+-INs substantially contributed to pattern separation. Both local connectivity and fast signaling at GC–PV+-IN synapses were important for maximum effectiveness. Similarly, mossy fiber synapses with conditional detonator properties contributed to pattern separation. By contrast, perforant path synapses with Hebbian synaptic plasticity and direct EC–CA3 connection shifted the network towards pattern completion. Our results demonstrate that the specific properties of cells and synapses optimize higher-order computations in biological networks and might be useful to improve the deep learning capabilities of technical networks. AU - Guzmán, José AU - Schlögl, Alois AU - Espinoza Martinez, Claudia AU - Zhang, Xiaomin AU - Suter, Benjamin AU - Jonas, Peter M ID - 10110 TI - How connectivity rules and synaptic properties shape the efficacy of pattern separation in the entorhinal cortex–dentate gyrus–CA3 network ER - TY - BOOK AB - This booklet is a collection of abstracts presented at the AHPC conference. ED - Schlögl, Alois ED - Kiss, Janos ED - Elefante, Stefano ID - 7474 SN - 978-3-99078-004-6 TI - Austrian High-Performance-Computing meeting (AHPC2020) ER - TY - JOUR AB - Dentate gyrus granule cells (GCs) connect the entorhinal cortex to the hippocampal CA3 region, but how they process spatial information remains enigmatic. To examine the role of GCs in spatial coding, we measured excitatory postsynaptic potentials (EPSPs) and action potentials (APs) in head-fixed mice running on a linear belt. Intracellular recording from morphologically identified GCs revealed that most cells were active, but activity level varied over a wide range. Whereas only ∼5% of GCs showed spatially tuned spiking, ∼50% received spatially tuned input. Thus, the GC population broadly encodes spatial information, but only a subset relays this information to the CA3 network. Fourier analysis indicated that GCs received conjunctive place-grid-like synaptic input, suggesting code conversion in single neurons. GC firing was correlated with dendritic complexity and intrinsic excitability, but not extrinsic excitatory input or dendritic cable properties. Thus, functional maturation may control input-output transformation and spatial code conversion. AU - Zhang, Xiaomin AU - Schlögl, Alois AU - Jonas, Peter M ID - 8261 IS - 6 JF - Neuron SN - 0896-6273 TI - Selective routing of spatial information flow from input to output in hippocampal granule cells VL - 107 ER - TY - GEN AU - Schlögl, Alois AU - Kiss, Janos AU - Elefante, Stefano ID - 12901 T2 - AHPC19 - Austrian HPC Meeting 2019 TI - Is Debian suitable for running an HPC Cluster? ER - TY - CONF AB - Background: Standards have become available to share semantically encoded vital parameters from medical devices, as required for example by personal healthcare records. Standardised sharing of biosignal data largely remains open. Objectives: The goal of this work is to explore available biosignal file format and data exchange standards and profiles, and to conceptualise end-To-end solutions. Methods: The authors reviewed and discussed available biosignal file format standards with other members of international standards development organisations (SDOs). Results: A raw concept for standards based acquisition, storage, archiving and sharing of biosignals was developed. The GDF format may serve for storing biosignals. Signals can then be shared using FHIR resources and may be stored on FHIR servers or in DICOM archives, with DICOM waveforms as one possible format. Conclusion: Currently a group of international SDOs (e.g. HL7, IHE, DICOM, IEEE) is engaged in intensive discussions. This discussion extends existing work that already was adopted by large implementer communities. The concept presented here only reports the current status of the discussion in Austria. The discussion will continue internationally, with results to be expected over the coming years. AU - Sauermann, Stefan AU - David, Veronika AU - Schlögl, Alois AU - Egelkraut, Reinhard AU - Frohner, Matthias AU - Pohn, Birgit AU - Urbauer, Philipp AU - Mense, Alexander ID - 630 SN - 978-161499758-0 TI - Biosignals standards and FHIR: The way to go VL - 236 ER - TY - GEN AU - Schlögl, Alois AU - Kiss, Janos ID - 12905 T2 - AHPC17 – Austrian HPC Meeting 2017 TI - Scientific Computing at IST Austria ER - TY - JOUR AB - The hippocampal CA3 region plays a key role in learning and memory. Recurrent CA3–CA3 synapses are thought to be the subcellular substrate of pattern completion. However, the synaptic mechanisms of this network computation remain enigmatic. To investigate these mechanisms, we combined functional connectivity analysis with network modeling. Simultaneous recording fromup to eight CA3 pyramidal neurons revealed that connectivity was sparse, spatially uniform, and highly enriched in disynaptic motifs (reciprocal, convergence,divergence, and chain motifs). Unitary connections were composed of one or two synaptic contacts, suggesting efficient use of postsynaptic space. Real-size modeling indicated that CA3 networks with sparse connectivity, disynaptic motifs, and single-contact connections robustly generated pattern completion.Thus, macro- and microconnectivity contribute to efficient memory storage and retrieval in hippocampal networks. AU - Guzmán, José AU - Schlögl, Alois AU - Frotscher, Michael AU - Jonas, Peter M ID - 1350 IS - 6304 JF - Science TI - Synaptic mechanisms of pattern completion in the hippocampal CA3 network VL - 353 ER - TY - GEN AU - Schlögl, Alois AU - Stadlbauer, Stephan ID - 12903 T2 - AHPC16 - Austrian HPC Meeting 2016 TI - High performance computing at IST Austria: Modelling the human hippocampus ER - TY - JOUR AB - To search for a target in a complex environment is an everyday behavior that ends with finding the target. When we search for two identical targets, however, we must continue the search after finding the first target and memorize its location. We used fixation-related potentials to investigate the neural correlates of different stages of the search, that is, before and after finding the first target. Having found the first target influenced subsequent distractor processing. Compared to distractor fixations before the first target fixation, a negative shift was observed for three subsequent distractor fixations. These results suggest that processing a target in continued search modulates the brain's response, either transiently by reflecting temporary working memory processes or permanently by reflecting working memory retention. AU - Körner, Christof AU - Braunstein, Verena AU - Stangl, Matthias AU - Schlögl, Alois AU - Neuper, Christa AU - Ischebeck, Anja ID - 1890 IS - 4 JF - Psychophysiology TI - Sequential effects in continued visual search: Using fixation-related potentials to compare distractor processing before and after target detection VL - 51 ER - TY - JOUR AB - Intracellular electrophysiological recordings provide crucial insights into elementary neuronal signals such as action potentials and synaptic currents. Analyzing and interpreting these signals is essential for a quantitative understanding of neuronal information processing, and requires both fast data visualization and ready access to complex analysis routines. To achieve this goal, we have developed Stimfit, a free software package for cellular neurophysiology with a Python scripting interface and a built-in Python shell. The program supports most standard file formats for cellular neurophysiology and other biomedical signals through the Biosig library. To quantify and interpret the activity of single neurons and communication between neurons, the program includes algorithms to characterize the kinetics of presynaptic action potentials and postsynaptic currents, estimate latencies between pre- and postsynaptic events, and detect spontaneously occurring events. We validate and benchmark these algorithms, give estimation errors, and provide sample use cases, showing that Stimfit represents an efficient, accessible and extensible way to accurately analyze and interpret neuronal signals. AU - Guzmán, José AU - Schlögl, Alois AU - Schmidt Hieber, Christoph ID - 2230 IS - FEB JF - Frontiers in Neuroinformatics SN - 16625196 TI - Stimfit: Quantifying electrophysiological data with Python VL - 8 ER - TY - JOUR AB - Spontaneous postsynaptic currents (PSCs) provide key information about the mechanisms of synaptic transmission and the activity modes of neuronal networks. However, detecting spontaneous PSCs in vitro and in vivo has been challenging, because of the small amplitude, the variable kinetics, and the undefined time of generation of these events. Here, we describe a, to our knowledge, new method for detecting spontaneous synaptic events by deconvolution, using a template that approximates the average time course of spontaneous PSCs. A recorded PSC trace is deconvolved from the template, resulting in a series of delta-like functions. The maxima of these delta-like events are reliably detected, revealing the precise onset times of the spontaneous PSCs. Among all detection methods, the deconvolution-based method has a unique temporal resolution, allowing the detection of individual events in high-frequency bursts. Furthermore, the deconvolution-based method has a high amplitude resolution, because deconvolution can substantially increase the signal/noise ratio. When tested against previously published methods using experimental data, the deconvolution-based method was superior for spontaneous PSCs recorded in vivo. Using the high-resolution deconvolution-based detection algorithm, we show that the frequency of spontaneous excitatory postsynaptic currents in dentate gyrus granule cells is 4.5 times higher in vivo than in vitro. AU - Pernia-Andrade, Alejandro AU - Goswami, Sarit AU - Stickler, Yvonne AU - Fröbe, Ulrich AU - Schlögl, Alois AU - Jonas, Peter M ID - 2954 IS - 7 JF - Biophysical Journal TI - A deconvolution based method with high sensitivity and temporal resolution for detection of spontaneous synaptic currents in vitro and in vivo VL - 103 ER -