Surface Properties Determining Passage Rates of Proteins through Nuclear Pores.

Nuclear pore complexes (NPCs) conduct nucleocytoplasmic transport through an FG domain-controlled barrier. We now explore how surface-features of a mobile species determine its NPC passage rate. Negative charges and lysines impede passage. Hydrophobic residues, certain polar residues (Cys, His), and, surprisingly, charged arginines have striking translocation-promoting effects. Favorable cation-π interactions between arginines and FG-phenylalanines may explain this apparent paradox. Application of these principles to redesign the surface of GFP resulted in variants that show a wide span of transit rates, ranging from 35-fold slower than wild-type to ∼500 times faster, with the latter outpacing even naturally occurring nuclear transport receptors (NTRs). The structure of a fast and particularly FG-specific GFPNTR variant illustrates how NTRs can expose multiple regions for binding hydrophobic FG motifs while evading non-specific aggregation. Finally, we document that even for NTR-mediated transport, the surface-properties of the "passively carried" cargo can strikingly affect the translocation rate.

Simple and Highly Efficient Detection of PSD95 Using a Nanobody and Its Recombinant Heavy-Chain Antibody Derivatives.

The post-synaptic density protein 95 (PSD95) is a crucial scaffolding protein participating in the organization and regulation of synapses. PSD95 interacts with numerous molecules, including neurotransmitter receptors and ion channels. The functional dysregulation of PSD95 as well as its abundance and localization has been implicated with several neurological disorders, making it an attractive target for developing strategies able to monitor PSD95 accurately for diagnostics and therapeutics. This study characterizes a novel camelid single-domain antibody (nanobody) that binds strongly and with high specificity to rat, mouse, and human PSD95. This nanobody allows for more precise detection and quantification of PSD95 in various biological samples. We expect that the flexibility and unique performance of this thoroughly characterized affinity tool will help to further understand the role of PSD95 in normal and diseased neuronal synapses.

Reversible Immobilization of Proteins in Sensors and Solid-State Nanopores.

The controlled functionalization of surfaces with proteins is crucial for many analytical methods in life science research and biomedical applications. Here, a coating for silica-based surfaces is established which enables stable and selective immobilization of proteins with controlled orientation and tunable surface density. The coating is reusable, retains functionality upon long-term storage in air, and is applicable to surfaces of complex geometry. The protein anchoring method is validated on planar surfaces, and then a method is developed to measure the anchoring process in real time using silicon nitride solid-state nanopores. For surface attachment, polyhistidine tags that are site specifically introduced into recombinant proteins are exploited, and the yeast nucleoporin Nsp1 is used as model protein. Contrary to the commonly used covalent thiol chemistry, the anchoring of proteins via polyhistidine tag is reversible, permitting to take proteins off and replace them by other ones. Such switching in real time in experiments on individual nanopores is monitored using ion conductivity. Finally, it is demonstrated that silica and gold surfaces can be orthogonally functionalized to accommodate polyhistidine-tagged proteins on silica but prevent protein binding to gold, which extends the applicability of this surface functionalization method to even more complex sensor devices.

Systematic analysis of barrier-forming FG hydrogels from Xenopus nuclear pore complexes.

Nuclear pore complexes (NPCs) control the traffic between cell nucleus and cytoplasm. While facilitating translocation of nuclear transport receptors (NTRs) and NTR·cargo complexes, they suppress passive passage of macromolecules 30 kDa. Previously, we reconstituted the NPC barrier as hydrogels comprising S. cerevisiae FG domains. We now studied FG domains from 10 Xenopus nucleoporins and found that all of them form hydrogels. Related domains with low FG motif density also substantially contribute to the NPC's hydrogel mass. We characterized all these hydrogels and observed the strictest sieving effect for the Nup98-derived hydrogel. It fully blocks entry of GFP-sized inert objects, permits facilitated entry of the small NTR NTF2, but arrests importin ß-type NTRs at its surface. O-GlcNAc modification of the Nup98 FG domain prevented this arrest and allowed also large NTR·cargo complexes to enter. Solid-state NMR spectroscopy revealed that the O-GlcNAc-modified Nup98 gel lacks amyloid-like ß-structures that dominate the rigid regions in the S. cerevisiae Nsp1 FG hydrogel. This suggests that FG hydrogels can assemble through different structural principles and yet acquire the same NPC-like permeability.

Myelin membrane assembly is driven by a phase transition of myelin basic proteins into a cohesive protein meshwork.

Rapid conduction of nerve impulses requires coating of axons by myelin. To function as an electrical insulator, myelin is generated as a tightly packed, lipid-rich multilayered membrane sheath. Knowledge about the mechanisms that govern myelin membrane biogenesis is required to understand myelin disassembly as it occurs in diseases such as multiple sclerosis. Here, we show that myelin basic protein drives myelin biogenesis using weak forces arising from its inherent capacity to phase separate. The association of myelin basic protein molecules to the inner leaflet of the membrane bilayer induces a phase transition into a cohesive mesh-like protein network. The formation of this protein network shares features with amyloid fibril formation. The process is driven by phenylalanine-mediated hydrophobic and amyloid-like interactions that provide the molecular basis for protein extrusion and myelin membrane zippering. These findings uncover a physicochemical mechanism of how a cytosolic protein regulates the morphology of a complex membrane architecture. These results provide a key mechanism in myelin membrane biogenesis with implications for disabling demyelinating diseases of the central nervous system.

Visual Analysis of Displacement Processes in Porous Media using Spatio-Temporal Flow Graphs.

We developed a new approach comprised of different visualizations for the comparative spatio-temporal analysis of displacement processes in porous media. We aim to analyze and compare ensemble datasets from experiments to gain insight into the influence of different parameters on fluid flow. To capture the displacement of a defending fluid by an invading fluid, we first condense an input image series to a single time map. From this map, we generate a spatio-temporal flow graph covering the whole process. This graph is further simplified to only reflect topological changes in the movement of the invading fluid. Our interactive tools allow the visual analysis of these processes by visualizing the graph structure and the context of the experimental setup, as well as by providing charts for multiple metrics. We apply our approach to analyze and compare ensemble datasets jointly with domain experts, where we vary either fluid properties or the solid structure of the porous medium. We finally report the generated insights from the domain experts and discuss our contribution's advantages, generality, and limitations.

Cohesiveness tunes assembly and morphology of FG nucleoporin domain meshworks - Implications for nuclear pore permeability.

Nuclear pore complexes control the exchange of macromolecules between the cytoplasm and the nucleus. A selective permeability barrier that arises from a supramolecular assembly of intrinsically unfolded nucleoporin domains rich in phenylalanine-glycine dipeptides (FG domains) fills the nuclear pore. There is increasing evidence that selective transport requires cohesive FG domain interactions. To understand the functional roles of cohesive interactions, we studied monolayers of end-grafted FG domains as a bottom-up nanoscale model system of the permeability barrier. Based on detailed physicochemical analysis of the model films and comparison of the data with polymer theory, we propose that cohesiveness is tuned to promote rapid assembly of the permeability barrier and to generate a stable and compact pore-filling meshwork with a small mesh size. Our results highlight the functional importance of weak interactions, typically a few kBT per chain, and contribute important information to understand the mechanism of size-selective transport.

FG/FxFG as well as GLFG repeats form a selective permeability barrier with self-healing properties.

The permeability barrier of nuclear pore complexes (NPCs) controls all nucleo-cytoplasmic exchange. It is freely permeable for small molecules. Objects larger than approximately 30 kDa can efficiently cross this barrier only when bound to nuclear transport receptors (NTRs) that confer translocation-promoting properties. We had shown earlier that the permeability barrier can be reconstituted in the form of a saturated FG/FxFG repeat hydrogel. We now show that GLFG repeats, the other major FG repeat type, can also form highly selective hydrogels. While supporting massive, reversible importin-mediated cargo influx, FG/FxFG, GLFG or mixed hydrogels remained firm barriers towards inert objects that lacked nuclear transport signals. This indicates that FG hydrogels immediately reseal behind a translocating species and thus possess 'self-healing' properties. NTRs not only left the barrier intact, they even tightened it against passive influx, pointing to a role for NTRs in establishing and maintaining the permeability barrier of NPCs.

Characterisation of the passive permeability barrier of nuclear pore complexes.

Nuclear pore complexes (NPCs) restrict uncontrolled nucleocytoplasmic fluxes of inert macromolecules but permit facilitated translocation of nuclear transport receptors and their cargo complexes. We probed the passive barrier of NPCs and observed sieve-like properties with a dominating mesh or channel radius of 2.6 nm, which is narrower than proposed earlier. A small fraction of diffusion channels has a wider opening, explaining the very slow passage of larger molecules. The observed dominant passive diameter approximates the distance of adjacent hydrophobic clusters of FG repeats, supporting the model that the barrier is made of FG repeat domains cross-linked with a spacing of an FG repeat unit length. Wheat germ agglutinin and the dominant-negative importin beta(45-462) fragment were previously regarded as selective inhibitors of facilitated NPC passage. We now observed that they do not distinguish between the passive and the facilitated mode. Instead, their inhibitory effect correlates with the size of the NPC-passing molecule. They have little effect on small species, inhibit the passage of green fluorescent protein-sized objects >10-fold and virtually block the translocation of larger ones. This suggests that passive and facilitated NPC passage proceed through one and the same permeability barrier.

Amyloid-like interactions within nucleoporin FG hydrogels.

The 62 kDa FG repeat domain of the nucleoporin Nsp1p forms a hydrogel-based, sieve-like permeability barrier that excludes inert macromolecules but allows rapid entry of nuclear transport receptors (NTRs). We found that the N-terminal part of this domain, which is characterized by Asn-rich inter-FG spacers, forms a tough hydrogel. The C-terminal part comprises charged inter-FG spacers, shows low gelation propensity on its own, but binds the N-terminal part and passivates the FG hydrogel against nonselective interactions. It was previously shown that a hydrophobic collapse involving Phe residues is required for FG hydrogel formation. Using solid-state NMR spectroscopy, we now identified two additional types of intragel interactions, namely, transient hydrophobic interactions between Phe and methyl side chains as well as intermolecular beta-sheets between the Asn-rich spacer regions. The latter appear to be the kinetically most stable structures within the FG hydrogel. They are also a central feature of neuronal inclusions formed by Asn/Gln-rich amyloid and prion proteins. The cohesive properties of FG repeats and the Asn/Gln-rich domain from the yeast prion Sup35p appear indeed so similar to each other that these two modules interact in trans. Our data, therefore, suggest a fully unexpected cellular function of such interchain beta-structures in maintaining the permeability barrier of nuclear pores. They provide an explanation for how contacts between FG repeats might gain the kinetic stability to suppress passive fluxes through nuclear pores and yet allow rapid NTR passage.

A Hybrid in Situ Approach for Cost Efficient Image Database Generation.

The visualization of results while the simulation is running is increasingly common in extreme scale computing environments. We present a novel approach for in situ generation of image databases to achieve cost savings on supercomputers. Our approach, a hybrid between traditional inline and in transit techniques, dynamically distributes visualization tasks between simulation nodes and visualization nodes, using probing as a basis to estimate rendering cost. Our hybrid design differs from previous works in that it creates opportunities to minimize idle time from four fundamental types of inefficiency: variability, limited scalability, overhead, and rightsizing. We demonstrate our results by comparing our method against both inline and in transit methods for a variety of configurations, including two simulation codes and a scaling study that goes above 19 K cores. Our findings show that our approach is superior in many configurations. As in situ visualization becomes increasingly ubiquitous, we believe our technique could lead to significant amounts of reclaimed cycles on supercomputers.

Structural characterization of nanoscale meshworks within a nucleoporin FG hydrogel.

The permeability barrier of nuclear pore complexes (NPCs) controls all exchange of macromolecules between the cytoplasm and the cell nucleus. It consists of phenylalanine-glycine (FG) repeat domains apparently organized as an FG hydrogel. It has previously been demonstrated that an FG hydrogel derived from the yeast nucleoporin Nsp1p reproduces the selectivity of authentic NPCs. Here we combined time-resolved optical spectroscopy and X-ray scattering techniques to characterize such a gel. The data suggest a hierarchy of structures that form during gelation at the expense of unstructured elements. On the largest scale, protein-rich domains with a correlation length of ~16.5 nm are evident. On a smaller length scale, aqueous channels with an average diameter of ~3 nm have been found, which possibly represent the physical structures accounting for the passive sieving effect of nuclear pores. The protein-rich domains contain characteristic ß-structures with typical inter-ß-strand and inter-ß-sheet distances of 1.3 and 0.47 nm, respectively. During gelation, the formation of oligomeric associates is accompanied by the transfer of phenylalanines into a hydrophobic microenvironment, supporting the view that this process is driven by a hydrophobic collapse.

Viscoelasticity of thin biomolecular films: a case study on nucleoporin phenylalanine-glycine repeats grafted to a histidine-tag capturing QCM-D sensor.

Immobilization of proteins onto surfaces is useful for the controlled generation of biomolecular assemblies that can be readily characterized with in situ label-free surface-sensitive techniques. Here we analyze the performance of a quartz crystal microbalance with dissipation monitoring (QCM-D) sensor surface that enables the selective and oriented immobilization of histidine-tagged molecules for morphological and interaction studies. More specifically, we characterize monolayers of natively unfolded nucleoporin domains that are rich in phenylalanine-glycine repeats (FGRDs). An FGRD meshwork is thought to be responsible for the selectivity of macromolecular transport across the nuclear pore complex between the cytosol and the nucleus of living cells. We demonstrate that nucleoporin FGRD films can be formed on His-tag Capturing Sensors with properties comparable to a previously reported immobilization platform based on supported lipid bilayers (SLB). Approaches to extract the film thickness and viscoelastic properties in a time-resolved manner from the QCM-D response are described, with particular emphasis on the practical implementation of viscoelastic modeling and a detailed analysis of the quality and reliability of the fit. By comparing the results with theoretical predictions for the viscoelastic properties of polymer solutions and gels, and experimental data from an atomic force microscopy indentation assay, we demonstrate that detailed analysis can provide novel insight into the morphology and dynamics of FG repeat domain films. The immobilization approach is simple and versatile, and can be easily extended to other His-tagged biomolecules. The data analysis procedure should be useful for the characterization of other ultrathin biomolecular and polymer films.

Ultrathin nucleoporin phenylalanine-glycine repeat films and their interaction with nuclear transport receptors.

Nuclear pore complexes (NPCs) are highly selective gates that mediate the exchange of all proteins and nucleic acids between the cytoplasm and the nucleus. Their selectivity relies on a supramolecular assembly of natively unfolded nucleoporin domains containing phenylalanine-glycine (FG)-rich repeats (FG repeat domains), in a way that is at present poorly understood. We have developed ultrathin FG domain films that reproduce the mode of attachment and the density of FG repeats in NPCs, and that exhibit a thickness that corresponds to the nanoscopic dimensions of the native permeability barrier. By using a combination of biophysical characterization techniques, we quantified the binding of nuclear transport receptors (NTRs) to such FG domain films and analysed how this binding affects the swelling behaviour and mechanical properties of the films. The results extend our understanding of the interaction of FG domain assemblies with NTRs and contribute important information to refine the model of transport across the permeability barrier.

S4: Self-Supervised Learning of Spatiotemporal Similarity.

We introduce an ML-driven approach that enables interactive example-based queries for similar behavior in ensembles of spatiotemporal scientific data. This addresses an important use case in the visual exploration of simulation and experimental data, where data is often large, unlabeled and has no meaningful similarity measures available. We exploit the fact that nearby locations often exhibit similar behavior and train a Siamese Neural Network in a self-supervised fashion, learning an expressive latent space for spatiotemporal behavior. This space can be used to find similar behavior with just a few user-provided examples. We evaluate this approach on several ensemble datasets and compare with multiple existing methods, showing both qualitative and quantitative results.

Local Prediction Models for Spatiotemporal Volume Visualization.

We present a machine learning-based approach for detecting and visualizing complex behavior in spatiotemporal volumes. For this, we train models to predict future data values at a given position based on the past values in its neighborhood, capturing common temporal behavior in the data. We then evaluate the model's prediction on the same data. High prediction error means that the local behavior was too complex, unique or uncertain to be accurately captured during training, indicating spatiotemporal regions with interesting behavior. By training several models of varying capacity, we are able to detect spatiotemporal regions of various complexities. We aggregate the obtained prediction errors into a time series or spatial volumes and visualize them together to highlight regions of unpredictable behavior and how they differ between the models. We demonstrate two further volumetric applications: adaptive timestep selection and analysis of ensemble dissimilarity. We apply our technique to datasets from multiple application domains and demonstrate that we are able to produce meaningful results while making minimal assumptions about the underlying data.

Discovery and Characterization of an ALFA-Tag-Specific Affinity Resin Optimized for Protein Purification at Low Temperatures in Physiological Buffer.

Epitope tags are widely employed as tools to detect, purify and manipulate proteins in various experimental systems. We recently introduced the ALFA-tag together with two ALFA-specific single-domain antibodies (sdAbs), NbALFA and NbALFAPE, featuring high or intermediate affinity, respectively. Together, the ALFA system can be employed for a broad range of applications in microscopy, cell biology and biochemistry requiring either extraordinarily stable binding or mild competitive elution at room temperature. In order to further enhance the versatility of the ALFA system, we, here, aimed at developing an sdAb optimized for efficient elution at low temperatures. To achieve this, we followed a stringent selection scheme tailored to the specific application. We found candidates combining a fast capture of ALFA-tagged proteins with an efficient competitive elution at 4 °C in physiological buffer. Importantly, by employing a structure-guided semisynthetic library based on well-characterized NbALFA variants, the high specificity and consistent binding of proteins harboring ALFA-tags at either terminus could be maintained. ALFA SelectorCE, a resin presenting the cold-elutable NbALFACE, is an ideal tool for the one-step purification of sensitive protein complexes or temperature-labile enzymes. We believe that the general approach followed during the selection and screening can be transferred to other challenging sdAb discovery projects.

Foveated Encoding for Large High-Resolution Displays.

Collaborative exploration of scientific data sets across large high-resolution displays requires both high visual detail as well as low-latency transfer of image data (oftentimes inducing the need to trade one for the other). In this work, we present a system that dynamically adapts the encoding quality in such systems in a way that reduces the required bandwidth without impacting the details perceived by one or more observers. Humans perceive sharp, colourful details, in the small foveal region around the centre of the field of view, while information in the periphery is perceived blurred and colourless. We account for this by tracking the gaze of observers, and respectively adapting the quality parameter of each macroblock used by the H.264 encoder, considering the so-called visual acuity fall-off. This allows to substantially reduce the required bandwidth with barely noticeable changes in visual quality, which is crucial for collaborative analysis across display walls at different locations. We demonstrate the reduced overall required bandwidth and the high quality inside the foveated regions using particle rendering and parallel coordinates.

2019 IEEE Scientific Visualization Contest Winner: Visual Analysis of Structure Formation in Cosmic Evolution.

Simulations of cosmic evolution are a means to explain the formation of the universe as we see it today. The resulting data of such simulations comprise numerous physical quantities, which turns their analysis into a complex task. Here, we analyze such high-dimensional and time-varying particle data using various visualization techniques from the fields of particle visualization, flow visualization, volume visualization, and information visualization. Our approach employs specialized filters to extract and highlight the development of so-called active galactic nuclei and filament structures formed by the particles. Additionally, we calculate X-ray emission of the evolving structures in a preprocessing step to complement visual analysis. Our approach is integrated into a single visual analytics framework to allow for analysis of star formation at interactive frame rates. Finally, we lay out the methodological aspects of our work that led to success at the 2019 IEEE SciVis Contest.

On Evaluating Runtime Performance of Interactive Visualizations.

As our field matures, evaluation of visualization techniques has extended from reporting runtime performance to studying user behavior. Consequently, many methodologies and best practices for user studies have evolved. While maintaining interactivity continues to be crucial for the exploration of large data sets, no similar methodological foundation for evaluating runtime performance has been developed. Our analysis of 50 recent visualization papers on new or improved techniques for rendering volumes or particles indicates that only a very limited set of parameters like different data sets, camera paths, viewport sizes, and GPUs are investigated, which make comparison with other techniques or generalization to other parameter ranges at least questionable. To derive a deeper understanding of qualitative runtime behavior and quantitative parameter dependencies, we developed a framework for the most exhaustive performance evaluation of volume and particle visualization techniques that we are aware of, including millions of measurements on ten different GPUs. This paper reports on our insights from statistical analysis of this data, discussing independent and linear parameter behavior and non-obvious effects. We give recommendations for best practices when evaluating runtime performance of scientific visualization applications, which can serve as a starting point for more elaborate models of performance quantification.