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Abstract
The primary immunological target of COVID-19 vaccines is the SARS-CoV-2 spike (S) protein. S is exposed on the viral surface and mediates viral entry into the host cell. To identify possible antibody binding sites, we performed multi-microsecond molecular dynamics simulations of a 4.1 million atom system containing a patch of viral membrane with four full-length, fully glycosylated and palmitoylated S proteins. By mapping steric accessibility, structural rigidity, sequence conservation, and generic antibody binding signatures, we recover known epitopes on S and reveal promising epitope candidates for structure-based vaccine design. We find that the extensive and inherently flexible glycan coat shields a surface area larger than expected from static structures, highlighting the importance of structural dynamics. The protective glycan shield and the high flexibility of its hinges give the stalk overall low epitope scores. Our computational epitope-mapping procedure is general and should thus prove useful for other viral envelope proteins whose structures have been characterized.
Author summary
The SARS-CoV-2 virus has caused a global health crisis. The spike protein exposed at its surface is key for infection and the primary antibody target. However, spike is covered by highly mobile glycan molecules that could impair antibody binding. To identify accessible epitopes, we performed molecular dynamics simulations of an atomistic model of glycosylated spike embedded in a membrane. By combining extensive simulations with bioinformatics analyses, we recovered known antibody binding sites and identified several epitope candidates as targets for further vaccine development.
More than 75% of surface and secreted proteins are modified by covalent addition of complex sugars through N- and O-glycosylation. Unlike proteins, glycans do not typically adopt specific secondary structures and remain very mobile, influencing protein dynamics and interactions with other molecules. Glycan conformational freedom impairs complete structural elucidation of glycoproteins. Computer simulations may be used to model glycan structure and dynamics. However, such simulations typically require thousands of computing hours on specialized supercomputers, thus limiting routine use. Here, we describe a reductionist method that can be implemented on personal computers to graft ensembles of realistic glycan conformers onto static protein structures in a matter of minutes. Using this open-source pipeline, we reconstructed the full glycan cover of SARS-CoV-2 Spike protein (S-protein) and a human GABAA receptor. Focusing on S-protein, we show that GlycoSHIELD recapitulates key features of extended simulations of the glycosylated protein, including epitope masking, and provides new mechanistic insights on N-glycan impact on protein structural dynamics.
Transient receptor potential (TRP) ion channels are among the most well-studied classes of temperature-sensing molecules. Yet, the molecular mechanism and thermodynamic basis for the temperature sensitivity of TRP channels remains to this day poorly understood. One hypothesis is that the temperature-sensing mechanism can simply be described by a difference in heat capacity between the closed and open channel states. While such a two-state model may be simplistic it nonetheless has descriptive value, in the sense that it can be used to to compare overall temperature sensitivity between different channels and mutants. Here, we introduce a mathematical framework based on the two-state model to reliably extract temperature-dependent thermodynamic potentials and heat capacities from measurements of equilibrium constants at different temperatures. Our framework is implemented in an open-source data analysis package that provides a straightforward way to fit both linear and nonlinear van ‘t Hoff plots, thus avoiding some of the previous, potentially erroneous, assumptions when extracting thermodynamic variables from TRP channel electrophysiology data.
Seit hundert Jahren ist bekannt, dass die mikroskopische Welt der Atome und Moleküle von den Gesetzen der Quantenphysik regiert wird. Lange Zeit galten Quantenphänomene als verworren und unkontrollierbar. Heute arbeiten Physikerinnen und Physiker daran, unter Nutzung quantenphysikalischer Effekte Materialien mit neuartigen Eigenschaften zu kreieren.
Am Teilchenbeschleuniger in Darmstadt werden die extremen Bedingungen unseres Universums im Labor erforscht. Dabei gelang es den Physikerinnen und Physikern, eine Technologie zu entwickeln, die Energie zur Teilchenbeschleunigung wiederverwendet und einspart. Der Teilchenbeschleuniger ist eingebunden in das Clusterprojekt ELEMENTS, das gemeinsam von der Goethe-Universität Frankfurt und der TU Darmstadt geleitet wird.
Using 10.1 × 109 J/ψ events produced by the Beijing Electron Positron Collider (BEPCII) at a center-of-mass energy √s = 3.097 GeV and collected with the BESIII detector, we present a search for the rare semi-leptonic decay J/ψ → D−e+νe + c.c. No excess of signal above background is observed, and an upper limit on the branching fraction ℬ(J/ψ → D−e+νe + c. c.) < 7.1 × 10−8 is obtained at 90% confidence level. This is an improvement of more than two orders of magnitude over the previous best limit.
We derive the thermal noise spectrum of the longitudinal and transverse electric field operator of a given wave vector starting from the quantum-statistical definitions and relate it to the frequency and wave vector dependent complex conductivity in a homogeneous, isotropic system of electromagnetic interacting charged particles in the frame of the non-relativistic QED. No additional assumptions except the validity of linear response are used in the proof. The Nyquist formula for vanishing frequency, as well as the noise spectral density of Callen-Welton follow as byproduct. Furthermore we discuss also the noise of the photon occupation numbers.
As part of the research for this thesis, a momentum spectrometer was set up and initial measurements on accelerated ions were performed. For this purpose, the necessary hardware for the operation of the spectrometer and for high-precision measurements was were assembled. A control system for remote operation was developed and the spectrometer was installed at the used beamline.
There, measurements of low-energy ion beams in superposition with electrons confined in a Gabor lens can be carried out.
Investigations were made on both the Gabor lens-generated ions and the beam ions, leading to first results regarding the charge changes of beam ions during propagation through an electron atmosphere.
In order to understand the origin of the elements in the universe, one must understand the nuclear reactions by which atomic nuclei are transformed. There are many different astrophysical environments that fulfill the conditions of different nucleosynthesis processes. Even though great progress has been made in recent decades in understanding the origin of the elements in the universe, some questions remain unanswered. In order to understand the processes, it is necessary to measure cross sections of the involved reactions and constrain theoretical model predictions. A variety of methods have been developed to measure nuclear reaction cross sections relevant for nuclear astrophysics. In this thesis, two different experiments and their results, both using the well-established activation method, are presented.
A measurement of the proton capture cross section on the p-nuclide 96Ru was performed at the Institute of Structure and Nuclear Astrophysics ISNAP - Notre Dame, USA. The main goal of this experiment was to compare the results with those obtained by Mei et al. in a pioneering experiment using the method of inverse kinematics at the GSI Helmholtzzentrum für Schwerionenforschung GmbH - Darmstadt, Germany. Therefore, the activations were taken out at the same center of mass energies of 9 MeV, 10 MeV and 11 MeV. Another activation was taken out at an energy of 3.2 MeV to compare the result to a measurement of Bork et al. who also used the activation method. While the results at 3.2 MeV agree quite well with those of Bork et al., the results at higher energies show significantly smaller cross sections than those measured by Mei et al.. Experimental details, the data analysis and sources of uncertainties are discussed.
The second part of this thesis describes a neutron capture cross section experiment. At the Institut für Kernphysik - Goethe Universtität Frankfurt an experimental setup allows to produce quasi maxwell-distributed neutron fields to measure maxwell-averaged cross sections (MACS) relevant for s-process nucleosynthesis. The setup was upgraded by a fast electric linear guide to transport samples from the activation to the detection site. The cyclic activation of the sample allows to increase the signal-to-noise ratio and to measure neutron captures that lead to nuclei with
half-lives on the order of seconds. In a first campaign, MACS of the reactions 51V(n,γ), 107,109Ag(n,γ) and 103Rh(n,γ) were measured. The new components of the setup aswell as the data analysis framework are described and the results of the measurements are discussed.
We study the polarization of relativistic fluids using the relativistic density operator at global and local equilibrium. In global equilibrium, a new technique to compute exact expectation values is introduced, which is used to obtain the exact polarization vector for fields of any spin. The same result has been extended to the case of massless fields. Furthermore, it is demonstrated that at local equilibrium not only the thermal vorticity but also the thermal shear contribute to the polarization vector. It is shown that assuming an isothermal local equilibrium, the new term can solve the polarization sign puzzle in heavy ion collisions.
Using combined data from the Relativistic Heavy Ion and Large Hadron Colliders, we constrain the shear and bulk viscosities of quark-gluon plasma (QGP) at temperatures of ∼150–350 MeV. We use Bayesian inference to translate experimental and theoretical uncertainties into probabilistic constraints for the viscosities. With Bayesian model averaging we propagate an estimate of the model uncertainty generated by the transition from hydrodynamics to hadron transport in the plasma’s final evolution stage, providing the most reliable phenomenological constraints to date on the QGP viscosities.
Tracking influenza a virus infection in the lung from hematological data with machine learning
(2022)
The tracking of pathogen burden and host responses with minimal-invasive methods during respiratory infections is central for monitoring disease development and guiding treatment decisions. Utilizing a standardized murine model of respiratory Influenza A virus (IAV) infection, we developed and tested different supervised machine learning models to predict viral burden and immune response markers, i.e. cytokines and leukocytes in the lung, from hematological data. We performed independently in vivo infection experiments to acquire extensive data for training and testing purposes of the models. We show here that lung viral load, neutrophil counts, cytokines like IFN-γ and IL-6, and other lung infection markers can be predicted from hematological data. Furthermore, feature analysis of the models shows that blood granulocytes and platelets play a crucial role in prediction and are highly involved in the immune response against IAV. The proposed in silico tools pave the path towards improved tracking and monitoring of influenza infections and possibly other respiratory infections based on minimal-invasively obtained hematological parameters.
Intrinsically disordered regions (IDRs) are essential for membrane receptor regulation but often remain unresolved in structural studies. TRPV4, a member of the TRP vanilloid channel family involved in thermo- and osmosensation, has a large N-terminal IDR of approximately 150 amino acids. With an integrated structural biology approach, we analyze the structural ensemble of the TRPV4 IDR and identify a network of regulatory elements that modulate channel activity in a hierarchical lipid-dependent manner through transient long-range interactions. A highly conserved autoinhibitory patch acts as a master regulator by competing with PIP2 binding to attenuate channel activity. Molecular dynamics simulations show that loss of the interaction between the PIP2-binding site and the membrane reduces the force exerted by the IDR on the structured core of TRPV4. This work demonstrates that IDR structural dynamics are coupled to TRPV4 activity and highlights the importance of IDRs for TRP channel function and regulation.
During infection the SARS-CoV-2 virus fuses its viral envelope with cellular membranes of its human host. Initial contact with the host cell and membrane fusion are both mediated by the viral spike (S) protein. Proteolytic cleavage of S at the S2′ site exposes its 40 amino acid long fusion peptide (FP). Binding of the FP to the host membrane anchors the S2 domain of S in both the viral and the host membrane. The reorganization of S2 then pulls the two membranes together. Here we use molecular dynamics (MD) simulations to study the two core functions of the SARS-CoV-2 FP: to attach quickly to cellular membranes and to form an anchor strong enough to withstand the mechanical force during membrane fusion. In eight 10 μs-long MD simulations of FP in proximity to endosomal and plasma membranes, we find that FP binds spontaneously to the membranes and that binding proceeds predominantly by insertion of two short amphipathic helices into the membrane interface. Connected via a flexible linker, the two helices can bind the membrane independently, yet binding of one promotes the binding of the other by tethering it close to the target membrane. By simulating mechanical pulling forces acting on the C-terminus of the FP we then show that the bound FP can bear forces up to 250 pN before detaching from the membrane. This detachment force is more than ten-fold higher than an estimate of the force required to pull host and viral membranes together for fusion. We identify a fully conserved disulfide bridge in the FP as a major factor for the high mechanical stability of the FP membrane anchor. We conclude, first, that the sequential binding of two short amphipathic helices allows the SARS-CoV-2 FP to insert quickly into the target membrane, before the virion is swept away after shedding the S1 domain connecting it to the host cell receptor. Second, we conclude that the double attachment and the conserved disulfide bridge establish the strong anchoring required for subsequent membrane fusion. Multiple distinct membrane-anchoring elements ensure high avidity and high mechanical strength of FP-membrane binding.
Focused ion beam induced deposition (FIBID) is a direct-write technique enabling the growth of individual nanostructures of any shape and dimension with high lateral resolution. Moreover, the fast and reliable writing of periodically arranged nanostructures can be used to fabricate devices for the investigation of collective phenomena and to design novel functional metamaterials. Here, FIBID is employed to prepare dc-Josephson junction arrays (dc-JJA) consisting of superconducting NbC dots coupled through the proximity effect via a granular metal layer. The fabrication is straightforward and allows the preparation of dc-JJA within a few seconds. Microstructure and composition of the arrays are investigated by transmission electron microscopy and energy dispersive X-ray spectroscopy. The superconductor-to-metal transition of the prepared dc-JJA is studied in a direct way, by tuning the Josephson junction resistance in 70 nm-spaced superconducting NbC dots. The observed magnetoresistance oscillations with a period determined by the flux quantum give evidence for the coherent charge transport by paired electrons. Moreover, the measured resistance minima correspond to two fundamental matching configurations of fluxons in the dc-JJA, caused by magnetic frustration. The robust properties of the prepared dc-JJA demonstrate the opportunities for a fast preparation of complex device configurations using direct-write approaches.
Changes in the efficacies of synapses are thought to be the neurobiological basis of learning and memory. The efficacy of a synapse depends on its current number of neurotransmitter receptors. Recent experiments have shown that these receptors are highly dynamic, moving back and forth between synapses on time scales of seconds and minutes. This suggests spontaneous fluctuations in synaptic efficacies and a competition of nearby synapses for available receptors. Here we propose a mathematical model of this competition of synapses for neurotransmitter receptors from a local dendritic pool. Using minimal assumptions, the model produces a fast multiplicative scaling behavior of synapses. Furthermore, the model explains a transient form of heterosynaptic plasticity and predicts that its amount is inversely related to the size of the local receptor pool. Overall, our model reveals logistical tradeoffs during the induction of synaptic plasticity due to the rapid exchange of neurotransmitter receptors between synapses.
Changes in the efficacies of synapses are thought to be the neurobiological basis of learning and memory. The efficacy of a synapse depends on its current number of neurotransmitter receptors. Recent experiments have shown that these receptors are highly dynamic, moving back and forth between synapses on time scales of seconds and minutes. This suggests spontaneous fluctuations in synaptic efficacies and a competition of nearby synapses for available receptors. Here we propose a mathematical model of this competition of synapses for neurotransmitter receptors from a local dendritic pool. Using minimal assumptions, the model produces a fast multiplicative scaling behavior of synapses. Furthermore, the model explains a transient form of heterosynaptic plasticity and predicts that its amount is inversely related to the size of the local receptor pool. Overall, our model reveals logistical tradeoffs during the induction of synaptic plasticity due to the rapid exchange of neurotransmitter receptors between synapses.
Transport of lipids across membranes is fundamental for diverse biological pathways in cells. Multiple ion-coupled transporters participate in lipid translocation, but their mechanisms remain largely unknown. Major facilitator superfamily (MFS) lipid transporters play central roles in cell wall synthesis, brain development and function, lipids recycling, and cell signaling. Recent structures of MFS lipid transporters revealed overlapping architectural features pointing towards a common mechanism. Here we used cysteine disulfide trapping, molecular dynamics simulations, mutagenesis analysis, and transport assays in vitro and in vivo, to investigate the mechanism of LtaA, a proton-dependent MFS lipid transporter essential for lipoteichoic acids synthesis in the pathogen Staphylococcus aureus. We reveal that LtaA displays asymmetric lateral openings with distinct functional relevance and that cycling through outward- and inward-facing conformations is essential for transport activity. We demonstrate that while the entire amphipathic central cavity of LtaA contributes to lipid binding, its hydrophilic pocket dictates substrate specificity. We propose that LtaA catalyzes lipid translocation by a ‘trap-and-flip’ mechanism that might be shared among MFS lipid transporters.