An innate antiviral pathway acting before interferons at epithelial surfaces.

Mucosal surfaces are exposed to environmental substances and represent a major portal of entry for microorganisms. The innate immune system is responsible for early defense against infections and it is believed that the interferons (IFNs) constitute the first line of defense against viruses. Here we identify an innate antiviral pathway that works at epithelial surfaces before the IFNs. The pathway is activated independently of known innate sensors of viral infections through a mechanism dependent on viral O-linked glycans, which induce CXCR3 chemokines and stimulate antiviral activity in a manner dependent on neutrophils. This study therefore identifies a previously unknown layer of antiviral defense that exerts its action on epithelial surfaces before the classical IFN response is operative.

TLR2 and TLR7 mediate distinct immunopathological and antiviral plasmacytoid dendritic cell responses to SARS-CoV-2 infection.

Understanding the molecular pathways driving the acute antiviral and inflammatory response to SARS-CoV-2 infection is critical for developing treatments for severe COVID-19. Here, we find decreasing number of circulating plasmacytoid dendritic cells (pDCs) in COVID-19 patients early after symptom onset, correlating with disease severity. pDC depletion is transient and coincides with decreased expression of antiviral type I IFNα and of systemic inflammatory cytokines CXCL10 and IL-6. Using an in vitro stem cell-based human pDC model, we further demonstrate that pDCs, while not supporting SARS-CoV-2 replication, directly sense the virus and in response produce multiple antiviral (interferons: IFNα and IFNλ1) and inflammatory (IL-6, IL-8, CXCL10) cytokines that protect epithelial cells from de novo SARS-CoV-2 infection. Via targeted deletion of virus-recognition innate immune pathways, we identify TLR7-MyD88 signaling as crucial for production of antiviral interferons (IFNs), whereas Toll-like receptor (TLR)2 is responsible for the inflammatory IL-6 response. We further show that SARS-CoV-2 engages the receptor neuropilin-1 on pDCs to selectively mitigate the antiviral interferon response, but not the IL-6 response, suggesting neuropilin-1 as potential therapeutic target for stimulation of TLR7-mediated antiviral protection.

The lncRNA LUCAT1 is elevated in inflammatory disease and restrains inflammation by regulating the splicing and stability of NR4A2.

The nuclear long non-coding RNA LUCAT1 has previously been identified as a negative feedback regulator of type I interferon and inflammatory cytokine expression in human myeloid cells. Here, we define the mechanistic basis for the suppression of inflammatory gene expression by LUCAT1. Using comprehensive identification of RNA-binding proteins by mass spectrometry as well as RNA immunoprecipitation, we identified proteins important in processing and alternative splicing of mRNAs as LUCAT1-binding proteins. These included heterogeneous nuclear ribonucleoprotein C, M, and A2B1. Consistent with this finding, cells lacking LUCAT1 have altered splicing of selected immune genes. In particular, upon lipopolysaccharide stimulation, the splicing of the nuclear receptor 4A2 (NR4A2) gene was particularly affected. As a consequence, expression of NR4A2 was reduced and delayed in cells lacking LUCAT1. NR4A2-deficient cells had elevated expression of immune genes. These observations suggest that LUCAT1 is induced to control the splicing and stability of NR4A2, which is in part responsible for the anti-inflammatory effect of LUCAT1. Furthermore, we analyzed a large cohort of patients with inflammatory bowel disease as well as asthma and chronic obstructive pulmonary disease. In these patients, LUCAT1 levels were elevated and in both diseases, positively correlated with disease severity. Collectively, these studies define a key molecular mechanism of LUCAT1-dependent immune regulation through post-transcriptional regulation of mRNAs highlighting its role in the regulation of inflammatory disease.

Virus-cell fusion as a trigger of innate immunity dependent on the adaptor STING.

The innate immune system senses infection by detecting either evolutionarily conserved molecules essential for the survival of microbes or the abnormal location of molecules. Here we demonstrate the existence of a previously unknown innate detection mechanism induced by fusion between viral envelopes and target cells. Virus-cell fusion specifically stimulated a type I interferon response with expression of interferon-stimulated genes, in vivo recruitment of leukocytes and potentiation of signaling via Toll-like receptor 7 (TLR7) and TLR9. The fusion-dependent response was dependent on the stimulator of interferon genes STING but was independent of DNA, RNA and viral capsid. We suggest that membrane fusion is sensed as a danger signal with potential implications for defense against enveloped viruses and various conditions of giant-cell formation.

Generating Minimal Training Sets for Machine Learned Potentials.

This Letter presents a novel approach for identifying uncorrelated atomic configurations from extensive datasets with a nonstandard neural network workflow known as random network distillation (RND) for training machine-learned interatomic potentials (MLPs). This method is coupled with a DFT workflow wherein initial data are generated with cheaper classical methods before only the minimal subset is passed to a more computationally expensive ab initio calculation. This benefits training not only by reducing the number of expensive DFT calculations required but also by providing a pathway to the use of more accurate quantum mechanical calculations. The method's efficacy is demonstrated by constructing machine-learned interatomic potentials for the molten salts KCl and NaCl. Our RND method allows accurate models to be fit on minimal datasets, as small as 32 configurations, reducing the required structures by at least 1 order of magnitude compared to alternative methods. This reduction in dataset sizes not only substantially reduces computational overhead for training data generation but also provides a more comprehensive starting point for active-learning procedures.

Influence of bacterial swimming and hydrodynamics on attachment of phages.

Bacteriophages ("phages") are viruses that infect bacteria. Since they do not actively self-propel, phages rely on thermal diffusion to find target cells-but can also be advected by fluid flows, such as those generated by motile bacteria themselves in bulk fluids. How does the flow field generated by a swimming bacterium influence how it encounters phages? Here, we address this question using coupled molecular dynamics and lattice Boltzmann simulations of flagellated bacteria swimming through a bulk fluid containing uniformly-dispersed phages. We find that while swimming increases the rate at which phages attach to both the cell body and flagellar propeller, hydrodynamic interactions strongly suppress this increase at the cell body, but conversely enhance this increase at the flagellar bundle. Our results highlight the pivotal influence of hydrodynamics on the interactions between bacteria and phages, as well as other diffusible species, in microbial environments.

Modeling microgel swelling: Influence of chain finite extensibility.

Microgels exhibit the ability to undergo reversible swelling in response to shifts in environmental factors that include variations in temperature, concentration, and pH. While several models have been put forward to elucidate specific aspects of microgel swelling and its impact on bulk behavior, a consistent theoretical description that chains throughout the microscopic degrees of freedom with suspension properties and deepens into the full implications of swelling remains a challenge yet to be met. In this work, we extend the mean-field swelling model of microgels from Denton and Tang [J. Chem. Phys. 145, 164901 (2016)] to include the finite extensibility of the polymer chains. The elastic contribution to swelling in the original work is formulated for Gaussian chains. By using the Langevin chain model, we modify this elastic contribution in order to account for finite extensibility effects, which become prominent for microgels containing highly charged polyelectrolytes and short polymer chains. We assess the performance of both elastic models, namely for Gaussian and Langevin chains, comparing against coarse-grained bead-spring simulations of ionic microgels with explicit electrostatic interactions. We examine the applicability scope of the models under a variation of parameters, such as ionization degree, microgel concentration, and salt concentration. The models are also tested against experimental results. This work broadens the applicability of the microgel swelling model toward a more realistic description, which brings advantages when describing the suspensions of nanogels and weak-polyelectrolyte micro-/nanogels.

Ratcheting Charged Polymers through Symmetric Nanopores Using Pulsed Fields: Designing a Low Pass Filter for Concentrating Polyelectrolytes.

We present a new concept for the separation of DNA molecules by contour length that combines a nanofluidic ratchet, nanopore translocation, and pulsed fields. Using Langevin dynamics simulations, we show that it is possible to design pulsed field sequences to ratchet captured semiflexible molecules in such a way that only short chains successfully translocate, effectively transforming the nanopore process into a low pass molecular filter. We also show that asymmetric pulses can significantly enhance the device efficiency. The process itself can be performed with many pores in parallel, and it should be possible to integrate it directly into nanopore sequencing devices, increasing its potential utility.

Explaining Giant Apparent pK_{a} Shifts in Weak Polyelectrolyte Brushes.

Recent experiments on weak polyelectrolyte brushes found marked shifts in the effective pK_{a} that are linear in the logarithm of the salt concentration. Comparing explicit-particle simulations with mean-field calculations we show that for high grafting densities the salt concentration effect can be explained using the ideal Donnan theory, but for low grafting densities the full shift is due to a combination of the Donnan effect and the polyelectrolyte effect. The latter originates from electrostatic correlations that are neglected in the Donnan picture and that are only approximately included in the mean-field theory. Moreover, we demonstrate that the magnitude of the polyelectrolyte effect is almost invariant with respect to salt concentration but depends on the grafting density of the brush. This invariance is due to a complex cancellation of multiple effects. Based on our results, we show how the experimentally determined pK_{a} shifts may be used to infer the grafting density of brushes, a parameter that is difficult to measure directly.

Solvent Effects on Structure and Screening in Confined Electrolytes.

Using classical density functional theory, we investigate the influence of solvent on the structure and ionic screening of electrolytes under slit confinement and in contact with a reservoir. We consider a symmetric electrolyte with implicit and explicit solvent models and find that spatially resolving solvent molecules is essential for the ion structure at confining walls, excess ion adsorption, and the pressure exerted on the walls. Despite this, we observe only moderate differences in the period of oscillations of the pressure with the slit width and virtually coinciding decay lengths as functions of the scaling variable σ_{ion}/λ_{D}, where σ_{ion} is the ion diameter and λ_{D} the Debye length. Moreover, in the electrostatic-dominated regime, this scaling behavior is practically independent of the relative permittivity and its dependence on the ion concentration. In contrast, the crossover to the hard-core-dominated regime depends sensitively on all three factors.

NMR Investigation of Water in Salt Crusts: Insights from Experiments and Molecular Simulations.

The evaporation of water from bare soil is often accompanied by the formation of a layer of crystallized salt, a process that must be understood in order to address the issue of soil salinization. Here, we use nuclear magnetic relaxation dispersion measurements to better understand the dynamic properties of water within two types of salt crusts: sodium chloride (NaCl) and sodium sulfate (Na2SO4). Our experimental results display a stronger dispersion of the relaxation time T1 with frequency for the case of sodium sulfate as compared to sodium chloride salt crusts. To gain insight into these results, we perform molecular dynamics simulations of salt solutions confined within slit nanopores made of either NaCl or Na2SO4. We find a strong dependence of the value of the relaxation time T1 on pore size and salt concentration. Our simulations reveal the complex interplay between the adsorption of ions at the solid surface, the structure of water near the interface, and the dispersion of T1 at low frequency, which we attribute to adsorption-desorption events.

A screening of results on the decay length in concentrated electrolytes.

Screening of electrostatic interactions in room-temperature ionic liquids and concentrated electrolytes has recently attracted much attention as surface force balance experiments have suggested the emergence of unanticipated anomalously large screening lengths at high ion concentrations. Termed underscreening, this effect was ascribed to the bulk properties of concentrated ionic systems. However, underscreening under experimentally relevant conditions is not predicted by classical theories and challenges our understanding of electrostatic correlations. Despite the enormous effort in performing large-scale simulations and new theoretical investigations, the origin of the anomalously long-range screening length remains elusive. This contribution briefly summarises the experimental, analytical and simulation results on ionic screening and the scaling behaviour of screening lengths. We then present an atomistic simulation approach that accounts for the solvent and ion exchange with a reservoir. We find that classical density functional theory (DFT) for concentrated electrolytes under confinement reproduces ion adsorption at charged interfaces surprisingly well. With DFT, we study confined electrolytes using implicit and explicit solvent models and the dependence on the solvent's dielectric properties. Our results demonstrate how the absence vs. presence of solvent particles and their discrete nature affect the short and long-range screening in concentrated ionic systems.

A novel model for biofilm initiation in porous media flow.

Bacteria often form biofilms in porous environments where an external flow is present, such as soil or filtration systems. To understand the initial stages of biofilm formation, one needs to study the interactions between cells, the fluid and the confining geometries. Here, we present an agent based numerical model for bacteria that takes into account the planktonic stage of motile cells as well as surface attachment and biofilm growth in a lattice Boltzmann fluid. In the planktonic stage we show the importance of the interplay between complex flow and cell motility when determining positions of surface attachment. In the growth stage we show the applicability of our model by investigating how external flow and biofilm stiffness determine qualitative colony morphologies as well as quantitative measurements of, e.g., permeability.

Interplay between steric and hydrodynamic interactions for ellipsoidal magnetic nanoparticles in a polymer suspension.

Magnetic nanoparticles couple to polymeric environments by several mechanisms. These include van der Waals, steric, hydrodynamic and electrostatic forces. This leads to numerous interesting effects and potential applications. Still, the details of the coupling are often unknown. In a previous work, we showed that, for spherical particles, hydrodynamic coupling alone can explain experimentally observed trends in magnetic AC susceptibility spectra [P. Kreissl, C. Holm and R. Weeber, Soft Matter, 2021, 17, 174-183]. Non-spherical, elongated particles are of interest because an enhanced coupling to the surrounding polymers is expected. In this publication we study the interplay of steric and hydrodynamic interactions between those particles and a polymer suspension. To this end, we obtain rotational friction coefficients, relaxation times for the magnetic moment, and AC susceptibility spectra, and compare these for simulations with and without hydrodynamic interactions considered. We show that, even if the particle is ellipsoidal, its hydrodynamic interactions with the surrounding polymers are much stronger than the steric ones due to the shape-anisotropy of the particle.

Reply to the 'Comment on "Simulations of ionization equilibria in weak polyelectrolyte solutions and gels"' by J. Landsgesell, L. Nová, O. Rud, F. Uhlík, D. Sean, P. Hebbeker, C. Holm and P. Kosovan, Soft Matter, 2019, 15, 1155-1185.

Levin and Bakhshandeh suggested in their comment that (1), we stated in our recent review that pH-pKA is a universal parameter for titrating systems, that (2), we omitted to mention in our review the broken symmetry of the constant pH algorithm, and that (3), a constant pH simulation must include a grand-canonical exchange of ions with the reservoir. As a reply to (1), we point out that Levin and Bakhshandeh misquoted and hence invalidated our original statement. We therefore explain in detail under which circumstances pH-pKA can be a universal parameter, and also demonstrate why their numerical example is not in contradiction to our statement. Moreover, the fact that pH-pKA is not a universal parameter for titrating systems is well known in the pertinent literature. Regarding (2), we admit that the symmetry-breaking feature of the constant pH algorithm has escaped our attention at the time of writing the review. We added some clarifying remarks to this behavior. Concerning (3), we point out that the grand-canonical coupling and the resultant Donnan potential are not features of single-phase systems, but are essential for two-phase systems, as was shown in a recent paper by some of us, see J. Landsgesell et al., Macromolecules, 2020, 53, 3007-3020.

Renormalized charge and dielectric effects in colloidal interactions: a numerical solution of the nonlinear Poisson-Boltzmann equation for unknown boundary conditions.

 The Derjaguin-Landau-Verwey-Overbeek (DLVO) theory, introduced more than 70 years ago, is a hallmark of colloidal particle modeling. For highly charged particles in the dilute regime, it is often supplemented by Alexander's prescription (Alexander et al. in J Chem Phys 80:5776, 1984) for using a renormalized charge. Here, we solve the problem of the interaction between two charged colloids at finite ionic strength, including dielectric mismatch effects, using an efficient numerical scheme to solve the nonlinear Poisson-Boltzmann (NPB) equation with unknown boundary conditions. Our results perfectly match the analytical predictions for the renormalized charge by Trizac and coworkers (Aubouy et al. in J Phys A 36:5835, 2003). Moreover, they allow us to reinterpret previous molecular dynamics (MD) simulation results by Kreer et al. (Phys Rev E 74:021401, 2006), rendering them now in agreement with the expected behavior. We furthermore find that the influence of polarization becomes important only when the Debye layers overlap significantly.

A generalized grand-reaction method for modeling the exchange of weak (polyprotic) acids between a solution and a weak polyelectrolyte phase.

We introduce a Monte-Carlo method that allows for the simulation of a polymeric phase containing a weak polyelectrolyte, which is coupled to a reservoir at a fixed pH, salt concentration, and total concentration of a weak polyprotic acid. The method generalizes the established grand-reaction method by Landsgesell et al. [Macromolecules 53, 3007-3020 (2020)] and, thus, allows for the simulation of polyelectrolyte systems coupled to reservoirs with a more complex chemical composition. In order to set the required input parameters that correspond to a desired reservoir composition, we propose a generalization of the recently published chemical potential tuning algorithm of Miles et al. [Phys. Rev. E 105, 045311 (2022)]. To test the proposed tuning procedure, we perform extensive numerical tests for both ideal and interacting systems. Finally, as a showcase, we apply the method to a simple test system that consists of a weak polybase solution that is coupled to a reservoir containing a small diprotic acid. The complex interplay of the ionization of various species, the electrostatic interactions, and the partitioning of small ions leads to a non-monotonous, stepwise swelling behavior of the weak polybase chains.

Implicit-Solvent Coarse-Grained Simulations of Linear-Dendritic Block Copolymer Micelles.

The design of nanoassemblies can be conveniently achieved by tuning the strength of the hydrophobic interactions of block copolymers in selective solvents. These block copolymer micelles form supramolecular aggregates, which have attracted great attention in the area of drug delivery and imaging in biomedicine due to their easy-to-tune properties and straightforward large-scale production. In the present work, we have investigated the micellization process of linear-dendritic block copolymers in order to elucidate the effect of branching on the micellar properties. We focus on block copolymers formed by linear hydrophobic blocks attached to either dendritic neutral or charged hydrophilic blocks. We have implemented a simple protocol for determining the equilibrium micellar size, which permits the study of linear-dendritic block copolymers in a wide range of block morphologies in an efficient and parallelizable manner. We have explored the impact of different topological and charge properties of the hydrophilic blocks on the equilibrium micellar properties and compared them to predictions from self-consistent field theory and scaling theory. We have found that, at higher degrees of branching in the corona and for short polymer chains, excluded volume interactions strongly influence the micellar aggregation as well as their effective charge.

Hybrid Molecules Consisting of Lysine Dendrons with Several Hydrophobic Tails: A SCF Study of Self-Assembling.

In this article, we used the numerical self-consistent field method of Scheutjens-Fleer to study the micellization of hybrid molecules consisting of one polylysine dendron with charged end groups and several linear hydrophobic tails attached to its root. The main attention was paid to spherical micelles and the determination of the range of parameters at which they can appear. A relationship has been established between the size and internal structure of the resulting spherical micelles and the length and number of hydrophobic tails, as well as the number of dendron generations. It is shown that the splitting of the same number of hydrophobic monomers from one long tail into several short tails leads to a decrease in the aggregation number and, accordingly, the number of terminal charges in micelles. At the same time, it was shown that the surface area per dendron does not depend on the number of hydrophobic monomers or tails in the hybrid molecule. The relationship between the structure of hybrid molecules and the electrostatic properties of the resulting micelles has also been studied. It is found that the charge distribution in the corona depends on the number of dendron generations G in the hybrid molecule. For a small number of generations (up to G=3), a standard double electric layer is observed. For a larger number of generations (G=4), the charges of dendrons in the corona are divided into two populations: in the first population, the charges are in the spherical layer near the boundary between the micelle core and shell, and in the second population, the charges are near the periphery of the spherical shell. As a result, a part of the counterions is localized in the wide region between them. These results are of potential interest for the use of spherical dendromicelles as nanocontainers for drug delivery.

SARS-CoV-2 evades immune detection in alveolar macrophages.

Respiratory infections, like the current COVID-19 pandemic, target epithelial cells in the respiratory tract. Alveolar macrophages (AMs) are tissue-resident macrophages located within the lung. They play a key role in the early phases of an immune response to respiratory viruses. AMs are likely the first immune cells to encounter SARS-CoV-2 during an infection, and their reaction to the virus will have a profound impact on the outcome of the infection. Interferons (IFNs) are antiviral cytokines and among the first cytokines produced upon viral infection. In this study, AMs from non-infectious donors are challenged with SARS-CoV-2. We demonstrate that challenged AMs are incapable of sensing SARS-CoV-2 and of producing an IFN response in contrast to other respiratory viruses, like influenza A virus and Sendai virus, which trigger a robust IFN response. The absence of IFN production in AMs upon challenge with SARS-CoV-2 could explain the initial asymptotic phase observed during COVID-19 and argues against AMs being the sources of pro-inflammatory cytokines later during infection.