Seroprevalence and correlates of SARS-CoV-2 neutralizing antibodies from a population-based study in Bonn, Germany.

To estimate the seroprevalence and temporal course of SARS-CoV-2 neutralizing antibodies, we embedded a multi-tiered seroprevalence survey within an ongoing community-based cohort study in Bonn, Germany. We first assessed anti-SARS-CoV-2 immunoglobulin G levels with an immunoassay, followed by confirmatory testing of borderline and positive test results with a recombinant spike-based immunofluorescence assay and a plaque reduction neutralization test (PRNT). Those with a borderline or positive immunoassay result were retested after 4 to 5 months. At baseline, 4771 persons participated (88% response rate). Between April 24th and June 30th, 2020, seroprevalence was 0.97% (95% CI: 0.72-1.30) by immunoassay and 0.36% (95% CI: 0.21-0.61) when considering only those with two additional positive confirmatory tests. Importantly, about 20% of PRNT+ individuals lost their neutralizing antibodies within five months. Here, we show that neutralizing antibodies are detectable in only one third of those with a positive immunoassay result, and wane relatively quickly.

Packing Density of the Amyloid Precursor Protein in the Cell Membrane.

Plasma membrane proteins organize into structures named compartments, microdomains, rafts, phases, crowds, or clusters. These structures are often smaller than 100 nm in diameter. Despite their importance in many cellular functions, little is known about their inner organization. For instance, how densely are molecules packed? Being aware of the protein compaction may contribute to our general understanding of why such structures exist and how they execute their functions. In this study, we have investigated plasma membrane crowds formed by the amyloid precursor protein (APP), a protein well known for its involvement in Alzheimer's disease. By combining biochemical experiments with conventional and super-resolution stimulated emission depletion microscopy, we quantitatively determined the protein packing density within APP crowds. We found that crowds occurring with reasonable frequency contain between 20 and 30 molecules occupying a spherical area with a diameter between 65 and 85 nm. Additionally, we found the vast majority of plasmalemmal APP residing in these crowds. The model suggests a high molecular density of protein material within plasmalemmal APP crowds. This should affect the protein's biochemical accessibility and processing by nonpathological α-secretases. As clustering of APP is a prerequisite for endocytic entry into the pathological processing pathway, elucidation of the packing density also provides a deeper understanding of this part of APP's life cycle.

Oligomerization of the Tetraspanin CD81 via the Flexibility of Its δ-Loop.

Tetraspanins are master organizers in the plasma membrane, forming tetraspanin-enriched microdomains with one another and other surface molecules. Their rod-shaped structure includes a large extracellular loop (LEL) that plays a pivotal role in tetraspanin network formation. We performed comparative atomistic and coarse-grain molecular-dynamics simulations of the LEL in isolation and full-length CD81, and reproduced LEL flexibility patterns known from wet-lab experiments in which the LEL δ-loop region showed a pronounced flexibility. In a 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine lipid bilayer and a plasma membrane environment, the conformational flexibility of the δ-loop initiates CD81-CD81 contacts for oligomerization. Furthermore, in the plasma membrane, CD81-ganglioside bridges arising from preformed glycolipid patches cross-link the complexes. The data suggest that exposing a flexible domain enables binding to interaction partners by circumventing the restriction of orientation and conformational freedom of membrane proteins.

Concentration Dependent Ion-Protein Interaction Patterns Underlying Protein Oligomerization Behaviours.

Salts and proteins comprise two of the basic molecular components of biological materials. Kosmotropic/chaotropic co-solvation and matching ion water affinities explain basic ionic effects on protein aggregation observed in simple solutions. However, it is unclear how these theories apply to proteins in complex biological environments and what the underlying ionic binding patterns are. Using the positive ion Ca(2+) and the negatively charged membrane protein SNAP25, we studied ion effects on protein oligomerization in solution, in native membranes and in molecular dynamics (MD) simulations. We find that concentration-dependent ion-induced protein oligomerization is a fundamental chemico-physical principle applying not only to soluble but also to membrane-anchored proteins in their native environment. Oligomerization is driven by the interaction of Ca(2+) ions with the carboxylate groups of aspartate and glutamate. From low up to middle concentrations, salt bridges between Ca(2+) ions and two or more protein residues lead to increasingly larger oligomers, while at high concentrations oligomers disperse due to overcharging effects. The insights provide a conceptual framework at the interface of physics, chemistry and biology to explain binding of ions to charged protein surfaces on an atomistic scale, as occurring during protein solubilisation, aggregation and oligomerization both in simple solutions and membrane systems.

Computer simulations suggest direct and stable tip to tip interaction between the outer membrane channel TolC and the isolated docking domain of the multidrug RND efflux transporter AcrB.

One way by which bacteria achieve antibiotics resistance is preventing drug access to its target molecule for example through an overproduction of multi-drug efflux pumps of the resistance nodulation division (RND) protein super family of which AcrAB-TolC in Escherichia coli is a prominent example. Although representing one of the best studied efflux systems, the question of how AcrB and TolC interact is still unclear as the available experimental data suggest that either both proteins interact in a tip to tip manner or do not interact at all but are instead connected by a hexamer of AcrA molecules. Addressing the question of TolC-AcrB interaction, we performed a series of 100 ns - 1 µs-molecular dynamics simulations of membrane-embedded TolC in presence of the isolated AcrB docking domain (AcrB(DD)). In 5/6 simulations we observe direct TolC-AcrB(DD) interaction that is only stable on the simulated time scale when both proteins engage in a tip to tip manner. At the same time we find TolC opening and closing freely on extracellular side while remaining closed at the inner periplasmic bottleneck region, suggesting that either the simulated time is too short or additional components are required to unlock TolC.

Where Biology Meets Physics--A Converging View on Membrane Microdomain Dynamics.

For several decades, the phenomenon of membrane component segregation into microdomains has been a well-known and highly debated subject, and varying concepts including the raft hypothesis, the fence-and-picket model, hydrophobic-mismatch, and specific protein-protein interactions have been offered as explanations. Here, we review the level of insight into the molecular architecture of membrane domains one is capable of obtaining through biological experimentation. Using SNARE proteins as a paradigm, comprehensive data suggest that several dozens of molecules crowd together into almost circular spots smaller than 100 nm. Such clusters are highly dynamical as they constantly capture and lose molecules. The organization has a strong influence on the functional availability of proteins and likely provides a molecular scaffold for more complex protein networks. Despite this high level of insight, fundamental open questions remain, applying not only to SNARE protein domains but more generally to all types of membrane domains. In this context, we explain the view of physical models and how they are beneficial in advancing our concept of micropatterning. While biological models generally remain qualitative and descriptive, physics aims towards making them quantitative and providing reproducible numbers, in order to discriminate between different mechanisms which have been proposed to account for experimental observations. Despite the fundamental differences in biological and physical approaches as far as cell membrane microdomains are concerned, we are able to show that convergence on common points of views is in reach.

Structural dynamics of the cell wall precursor lipid II in the presence and absence of the lantibiotic nisin.

Representing a physiological "Achilles' heel", the cell wall precursor lipid II (LII) is a prime target for various classes of antibiotics. Over the years LII-binding agents have been recognized as promising candidates and templates in the search for new antibacterial compounds to complement or replace existing drugs. To elucidate the molecular structural basis underlying LII functional mechanism and to better understand if and how lantibiotic binding alters the molecular behavior of LII, we performed molecular dynamics (MD) simulations of phospholipid membrane-embedded LII in the absence and presence of the LII-binding lantibiotic nisin. In a series of 2×4 independent, unbiased 100ns MD simulations we sampled the conformational dynamics of nine LII as well as nine LII-nisin complexes embedded in an aqueous 150mM NaCl/POPC phospholipid membrane environment. We found that nisin binding to LII induces a reduction of LII mobility and flexibility, an outward shift of the LII pentapeptide, an inward movement of the LII disaccharide section, and an overall deeper insertion of the LII tail group into the membrane. The latter effect might indicate an initial step in adopting a stabilizing, scaffold-like structure in the process of nisin-induced membrane leakage. At the same time nisin conformation and LII interaction remain similar to the 1WCO LII-nisin NMR solution structure.

The extracellular δ-domain is essential for the formation of CD81 tetraspanin webs.

CD81 is a ubiquitously expressed member of the tetraspanin family. It forms large molecular platforms, so-called tetraspanin webs that play physiological roles in a variety of cellular functions and are involved in viral and parasite infections. We have investigated which part of the CD81 molecule is required for the formation of domains in the cell membranes of T-cells and hepatocytes. Surprisingly, we find that large CD81 platforms assemble via the short extracellular δ-domain, independent from a strong primary partner binding and from weak interactions mediated by palmitoylation. The δ-domain is also essential for the platforms to function during viral entry. We propose that, instead of stable binary interactions, CD81 interactions via the small δ-domain, possibly involving a dimerization step, play the key role in organizing CD81 into large tetraspanin webs and controlling its function.

Efflux pump-mediated antibiotics resistance: insights from computational structural biology.

The continuous rise of bacterial resistance against formerly effective pharmaceuticals is a major challenge for biomedical research. Since the first computational studies published seven years ago the simulation-based investigation of antibiotics resistance mediated by multidrug efflux pumps of the resistance nodulation division (RND) protein super family has grown into a vivid field of research. Here we review the employment of molecular dynamics computer simulations to investigate RND efflux pumps focusing on our group's recent contributions to this field studying questions of energy conversion and substrate transport in the inner membrane antiporter AcrB in Escherichia coli as well as access regulation and gating mechanism in the outer membrane efflux ducts TolC and OprM in E. coli and Pseudomonas aeruginosa.

LAMBADA and InflateGRO2: efficient membrane alignment and insertion of membrane proteins for molecular dynamics simulations.

At the beginning of each molecular dynamics membrane simulation stands the generation of a suitable starting structure which includes the working steps of aligning membrane and protein and seamlessly accommodating the protein in the membrane. Here we introduce two efficient and complementary methods based on pre-equilibrated membrane patches, automating these steps. Using a voxel-based cast of the coarse-grained protein, LAMBADA computes a hydrophilicity profile-derived scoring function based on which the optimal rotation and translation operations are determined to align protein and membrane. Employing an entirely geometrical approach, LAMBADA is independent from any precalculated data and aligns even large membrane proteins within minutes on a regular workstation. LAMBADA is the first tool performing the entire alignment process automatically while providing the user with the explicit 3D coordinates of the aligned protein and membrane. The second tool is an extension of the InflateGRO method addressing the shortcomings of its predecessor in a fully automated workflow. Determining the exact number of overlapping lipids based on the area occupied by the protein and restricting expansion, compression and energy minimization steps to a subset of relevant lipids through automatically calculated and system-optimized operation parameters, InflateGRO2 yields optimal lipid packing and reduces lipid vacuum exposure to a minimum preserving as much of the equilibrated membrane structure as possible. Applicable to atomistic and coarse grain structures in MARTINI format, InflateGRO2 offers high accuracy, fast performance, and increased application flexibility permitting the easy preparation of systems exhibiting heterogeneous lipid composition as well as embedding proteins into multiple membranes. Both tools can be used separately, in combination with other methods, or in tandem permitting a fully automated workflow while retaining a maximum level of usage control and flexibility. To assess the performance of both methods, we carried out test runs using 22 membrane proteins of different size and transmembrane structure.