Secretion of Genome-Free Hepatitis B Virus – Single Strand Blocking Model for Virion Morphogenesis of Para-retrovirus

As a para-retrovirus, hepatitis B virus (HBV) is an enveloped virus with a double-stranded (DS) DNA genome that is replicated by reverse transcription of an RNA intermediate, the pregenomic RNA or pgRNA. HBV assembly begins with the formation of an “immature” nucleocapsid (NC) incorporating pgRNA, which is converted via reverse transcription within the maturing NC to the DS DNA genome. Only the mature, DS DNA-containing NCs are enveloped and secreted as virions whereas immature NCs containing RNA or single-stranded (SS) DNA are not enveloped. The current model for selective virion morphogenesis postulates that accumulation of DS DNA within the NC induces a “maturation signal” that, in turn, triggers its envelopment and secretion. However, we have found, by careful quantification of viral DNA and NCs in HBV virions secreted in vitro and in vivo, that the vast majority of HBV virions (over 90%) contained no DNA at all, indicating that NCs with no genome were enveloped and secreted as empty virions (i.e., enveloped NCs with no DNA). Furthermore, viral mutants bearing mutations precluding any DNA synthesis secreted exclusively empty virions. Thus, viral DNA synthesis is not required for HBV virion morphogenesis. On the other hand, NCs containing RNA or SS DNA were excluded from virion formation. The secretion of DS DNA-containing as well as empty virions on one hand, and the lack of secretion of virions containing single-stranded (SS) DNA or RNA on the other, prompted us to propose an alternative, “Single Strand Blocking” model to explain selective HBV morphogenesis whereby SS nucleic acid within the NC negatively regulates NC envelopment, which is relieved upon second strand DNA synthesis

Broadband Multi-wavelength Properties of M87 during the 2017 Event Horizon Telescope Campaign

Abstract: In 2017, the Event Horizon Telescope (EHT) Collaboration succeeded in capturing the first direct image of the center of the M87 galaxy. The asymmetric ring morphology and size are consistent with theoretical expectations for a weakly accreting supermassive black hole of mass ∼6.5 × 109 M ⊙. The EHTC also partnered with several international facilities in space and on the ground, to arrange an extensive, quasi-simultaneous multi-wavelength campaign. This Letter presents the results and analysis of this campaign, as well as the multi-wavelength data as a legacy data repository. We captured M87 in a historically low state, and the core flux dominates over HST-1 at high energies, making it possible to combine core flux constraints with the more spatially precise very long baseline interferometry data. We present the most complete simultaneous multi-wavelength spectrum of the active nucleus to date, and discuss the complexity and caveats of combining data from different spatial scales into one broadband spectrum. We apply two heuristic, isotropic leptonic single-zone models to provide insight into the basic source properties, but conclude that a structured jet is necessary to explain M87’s spectrum. We can exclude that the simultaneous γ-ray emission is produced via inverse Compton emission in the same region producing the EHT mm-band emission, and further conclude that the γ-rays can only be produced in the inner jets (inward of HST-1) if there are strongly particle-dominated regions. Direct synchrotron emission from accelerated protons and secondaries cannot yet be excluded

Estimating Free Energy Barriers for Heterogeneous Catalytic Reactions with Machine Learning Potentials and Umbrella Integration

Predicting the rate constants of elementary reaction steps is key for the computational modelling of catalytic processes. Within transition state theory (TST), this requires an accurate estimation of the corresponding free energy barriers. While sophisticated methods for estimating free energy differences exist, these typically require extensive (biased) molecular dynamics simulations that are computationally prohibitive with the first-principles electronic structure methods that are typically used in catalysis research. In this contribution, we show that machine-learning (ML) interatomic potentials can be trained in an automated iterative workflow to perform such free energy calculations at a much reduced computational cost as compared to a direct density-functional theory (DFT) based evaluation. For the decomposition of CHO on Rh(111), we find that thermal effects are substantial and lead to a decrease in the free energy barrier, which can be vanishingly small depending on the DFT functional used. This is in stark contrast to previously reported estimates based on a harmonic TST approximation, which predicted an increase of the barrier at elevated temperatures. Since CHO is the educt of the putative rate limiting reaction step in syngas conversion on Rh(111) and essential for the selectivity towards $\mathrm{C}_\mathrm{2+}$ oxygenates, our results call into question the reported mechanism established by microkinetic models

Estimating Free Energy Barriers for Heterogeneous Catalytic Reactions with Machine Learning Potentials and Umbrella Integration.

Predicting the rate constants of elementary reaction steps is key for the computational modeling of catalytic processes. Within transition state theory (TST), this requires an accurate estimation of the corresponding free energy barriers. While sophisticated methods for estimating free energy differences exist, these typically require extensive (biased) molecular dynamics simulations that are computationally prohibitive with the first-principles electronic structure methods that are typically used in catalysis research. In this contribution, we show that machine-learning (ML) interatomic potentials can be trained in an automated iterative workflow to perform such free energy calculations at a much reduced computational cost as compared to a direct density functional theory (DFT) based evaluation. For the decomposition of CHO on Rh(111), we find that thermal effects are substantial and lead to a decrease in the free energy barrier, which can be vanishingly small, depending on the DFT functional used. This is in stark contrast to previously reported estimates based on a harmonic TST approximation, which predicted an increase in the barrier at elevated temperatures. Since CHO is the reactant of the putative rate limiting reaction step in syngas conversion on Rh(111) and essential for the selectivity toward oxygenates containing multiple carbon atoms (C2+ oxygenates), our results call into question the reported mechanism established by microkinetic models

Development and Validation of a ReaxFF Reactive Force Field for Fe/Al/Ni Alloys: Molecular Dynamics Study of Elastic Constants, Diffusion, and Segregation

We have developed a ReaxFF force field for Fe/Al/Ni binary alloys based on quantum mechanical (QM) calculations. In addition to the various bulk phases of the binary alloys, the (100), (110) and (111) surface energies and adatom binding energies were included in the training set for the force field parametrization of the Fe/Al/Ni binary alloys. To validate these optimized force fields, we studied (i) elastic constants of the binary alloys at finite temperatures, (ii) diffusivity of alloy components in Al/Ni alloy, and (iii) segregation on the binary alloy surfaces. First, we calculated linear elastic constants of FeAl, FeNi₃, and Ni₃Al in the temperature range 300 to 1100 K. The temperature dependences of the elastic constants of these three alloys, showing a decrease in <i>C</i>₁₁, <i>C</i>₁₂, and <i>C</i>₄₄ as temperature increases, were in good agreement with the experimental results. We also performed ReaxFF molecular dynamics (MD) simulations for Al or Ni diffusion in the system modeled as Al/Ni mixed layers with the linear composition gradients. At 1000 K, Al diffusivity at the pure Al end was 2 orders of magnitude larger than that in the Al trace layers, probably explaining the nature of different diffusion behavior between molten metals and alloys. However, the diffusivity of Ni at the pure Ni end was only slightly larger than that in the Ni trace layers at the system temperature much lower than the melting temperature of Ni. Third, we investigated the surface segregation in L1₂–Fe₃Al, Fe₃Ni, and Ni₃Al clusters at high temperature (2500 K). From the analysis of composition distribution of the alloy components from the bulk to the surface layer, it was found that the degree of segregation depended on the chemical composition of the alloy. Al surface segregation occurred most strongly in Fe₃Al, whereas it occurred most weakly in Ni₃Al. These results may support the segregation mechanism that surface segregation results from the interplay between the energetic stability of the ordered bulk phase and the surface reconstruction. In addition, the surface segregation induced the depletion layers of segregating metal species (Al in Fe₃Al and Ni₃Al, and Ni in Fe₃Ni) next to the segregation layers. These simulation results qualitatively agreed with early experimental observations of segregation in Fe/Al/Ni binary alloys