Single-Virus Fusion Measurements Reveal Multiple Mechanistically Equivalent Pathways for SARS-CoV-2 Entry.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) binds to cell surface receptors and is activated for membrane fusion and cell entry via proteolytic cleavage. Phenomenological data have shown that SARS-CoV-2 can be activated for entry at either the cell surface or in endosomes, but the relative roles in different cell types and mechanisms of entry have been debated. Here, we used single-virus fusion experiments and exogenously controlled proteases to probe activation directly. We found that plasma membrane and an appropriate protease are sufficient to support SARS-CoV-2 pseudovirus fusion. Furthermore, fusion kinetics of SARS-CoV-2 pseudoviruses are indistinguishable no matter which of a broad range of proteases is used to activate the virus. This suggests that the fusion mechanism is insensitive to protease identity or even whether activation occurs before or after receptor binding. These data support a model for opportunistic fusion by SARS-CoV-2 in which the subcellular location of entry likely depends on the differential activity of airway, cellsurface, and endosomal proteases, but all support infection. Inhibition of any single host protease may thus reduce infection in some cells but may be less clinically robust. IMPORTANCE SARS-CoV-2 can use multiple pathways to infect cells, as demonstrated recently when new viral variants switched dominant infection pathways. Here, we used single-virus fusion experiments together with biochemical reconstitution to show that these multiple pathways coexist simultaneously and specifically that the virus can be activated by different proteases in different cellular compartments with mechanistically identical effects. The consequences of this are that the virus is evolutionarily plastic and that therapies targeting viral entry should address multiple pathways at once to achieve optimal clinical effects.

Friends and relatives: insight into conformational regulation from orthologues and evolutionary lineages using KIF and KIN.

Noncovalent interaction networks provide a powerful means to represent and analyze protein structure. Such networks can represent both static structures and dynamic conformational ensembles. We have recently developed two tools for analyzing such interaction networks and generating hypotheses for protein engineering. Here, we apply these tools to the conformational regulation of substrate specificity in class A ß-lactamases, particularly the evolutionary development from generalist to specialist catalytic function and how that can be recapitulated or reversed by protein engineering. These tools, KIF and KIN, generate a set of prioritized residues and interactions as targets for experimental protein engineering.

Mechanistic dissection of antibody inhibition of influenza entry yields unexpected heterogeneity.

Neutralizing antibodies against influenza have generally been classified according to their recognition sites, with antibodies against the head domain of hemagglutinin thought to inhibit attachment and antibodies against the stalk region thought to inhibit fusion. Here, we report the development of a microfluidic assay to measure neutralization of viral entry that can clearly differentiate between effects on attachment and fusion. Testing multiple broadly neutralizing antibodies against the hemagglutinin stalk domain, we obtain a surprising result: some broadly neutralizing antibodies inhibit fusion only, while others inhibit both fusion and viral attachment. Antibodies binding the globular head domain primarily inhibit attachment but can also reduce the fusogenic capability of viral particles that nonetheless bind the receptor. These findings shed light on the unexpectedly heterogeneous mechanisms of antibody neutralization even within similar recognition sites. The assay we have developed also provides a tool to optimize vaccine design by permitting assessment of the elicited antibody response with greater mechanistic resolution.

gmxapi: A GROMACS-native Python interface for molecular dynamics with ensemble and plugin support.

Gmxapi provides an integrated, native Python API for both standard and advanced molecular dynamics simulations in GROMACS. The Python interface permits multiple levels of integration with the core GROMACS libraries, and legacy support is provided via an interface that mimics the command-line syntax, so that all GROMACS commands are fully available. Gmxapi has been officially supported since the GROMACS 2019 release and is enabled by default in current versions of the software. Here we describe gmxapi 0.3 and later. Beyond simply wrapping GROMACS library operations, the API permits several advanced operations that are not feasible using the prior command-line interface. First, the API allows custom user plugin code within the molecular dynamics force calculations, so users can execute custom algorithms without modifying the GROMACS source. Second, the Python interface allows tasks to be dynamically defined, so high-level algorithms for molecular dynamics simulation and analysis can be coordinated with loop and conditional operations. Gmxapi makes GROMACS more accessible to custom Python scripting while also providing support for high-level data-flow simulation algorithms that were previously feasible only in external packages.

KIF-Key Interactions Finder: A program to identify the key molecular interactions that regulate protein conformational changes.

Simulation datasets of proteins (e.g., those generated by molecular dynamics simulations) are filled with information about how a non-covalent interaction network within a protein regulates the conformation and, thus, function of the said protein. Most proteins contain thousands of non-covalent interactions, with most of these being largely irrelevant to any single conformational change. The ability to automatically process any protein simulation dataset to identify non-covalent interactions that are strongly associated with a single, defined conformational change would be a highly valuable tool for the community. Furthermore, the insights generated from this tool could be applied to basic research, in order to improve understanding of a mechanism of action, or for protein engineering, to identify candidate mutations to improve/alter the functionality of any given protein. The open-source Python package Key Interactions Finder (KIF) enables users to identify those non-covalent interactions that are strongly associated with any conformational change of interest for any protein simulated. KIF gives the user full control to define the conformational change of interest as either a continuous variable or categorical variable, and methods from statistics or machine learning can be applied to identify and rank the interactions and residues distributed throughout the protein, which are relevant to the conformational change. Finally, KIF has been applied to three diverse model systems (protein tyrosine phosphatase 1B, the PDZ3 domain, and the KE07 series of Kemp eliminases) in order to illustrate its power to identify key features that regulate functionally important conformational dynamics.

Influenza hemagglutinin drives viral entry via two sequential intramembrane mechanisms.

Enveloped viruses enter cells via a process of membrane fusion between the viral envelope and a cellular membrane. For influenza virus, mutational data have shown that the membrane-inserted portions of the hemagglutinin protein play a critical role in achieving fusion. In contrast to the relatively well-understood ectodomain, a predictive mechanistic understanding of the intramembrane mechanisms by which influenza hemagglutinin drives fusion has been elusive. We used molecular dynamics simulations of fusion between a full-length hemagglutinin proteoliposome and a lipid bilayer to analyze these mechanisms. In our simulations, hemagglutinin first acts within the membrane to increase lipid tail protrusion and promote stalk formation and then acts to engage the distal leaflets of each membrane and promote stalk widening, curvature, and eventual fusion. These two sequential mechanisms, one occurring before stalk formation and one after, are consistent with our experimental measurements of single-virus fusion kinetics to liposomes of different sizes. The resulting model also helps explain and integrate previous mutational and biophysical data, particularly the mutational sensitivity of the fusion peptide N terminus and the length sensitivity of the transmembrane domain. We hypothesize that entry by other enveloped viruses may also use sequential processes of acyl tail exposure, followed by membrane curvature and distal leaflet engagement.

Measuring single-virus fusion kinetics using an assay for nucleic acid exposure.

The kinetics by which individual enveloped viruses fuse with membranes provide an important window into viral-entry mechanisms. We have developed a real-time assay using fluorescent probes for single-virus genome exposure than can report on stages of viral entry including or subsequent to fusion pore formation and prior to viral genome trafficking. We accomplish this using oxazole yellow nucleic-acid-binding dyes, which can be encapsulated in the lumen of target membranes to permit specific detection of fusion events. Since increased fluorescence of the dye occurs only when it encounters viral genome via a fusion pore and binds, this assay excludes content leakage without fusion. Using this assay, we show that influenza virus fuses with liposomes of different sizes with indistinguishable kinetics by both testing liposomes extruded through pores of different radii and showing that the fusion kinetics of individual liposomes are uncorrelated with the size of the liposome. These results suggest that the starting curvature of such liposomes does not control the rate-limiting steps in influenza entry.

Precise Triggering and Chemical Control of Single-Virus Fusion within Endosomes.

Many enveloped viruses infect cells within endocytic compartments. The pH drop that accompanies endosomal maturation, often in conjunction with proteolysis, triggers viral proteins to insert into the endosomal membrane and drive fusion. Fusion dynamics have been studied by tracking viruses within living cells, which limits the precision with which fusion can be synchronized and controlled, and reconstituting viral fusion to synthetic membranes, which introduces nonphysiological membrane curvature and composition. To overcome these limitations, we report chemically controllable triggering of single-virus fusion within endosomes. We isolated influenza (A/Aichi/68; H3N2) virus:endosome conjugates from cells, immobilized them in a microfluidic flow cell, and rapidly and controllably triggered fusion. Observed lipid-mixing kinetics were surprisingly similar to those of influenza virus fusion with model membranes of opposite curvature: 80% of single-virus events had indistinguishable kinetics. This result suggests that endosomal membrane curvature is not a key permissive feature for viral entry, at least lipid mixing. The assay preserved endosomal membrane asymmetry and protein composition, providing a platform to test how cellular restriction factors and altered endosomal trafficking affect viral membrane fusion.IMPORTANCE Many enveloped viruses infect cells via fusion to endosomes, but controlling this process within living cells has been challenging. We studied the fusion of influenza virus virions to endosomes in a chemically controllable manner. Extracting virus:endosome conjugates from cells and exogenously triggering fusion permits precise study of virus:endosome fusion kinetics. Surprisingly, endosomal curvature does not grossly alter fusion kinetics, although membrane deformability does. This supports a model for influenza virus entry where cells restrict or permit membrane fusion by changing deformability, for instance, using interferon-induced proteins.

Computational methods to study enveloped viral entry.

The protein-membrane interactions that mediate viral infection occur via loosely ordered, transient assemblies, creating challenges for high-resolution structure determination. Computational methods and in particular molecular dynamics simulation have thus become important adjuncts for integrating experimental data, developing mechanistic models, and suggesting testable hypotheses regarding viral function. However, the large molecular scales of virus-host interaction also create challenges for detailed molecular simulation. For this reason, continuum membrane models have played a large historical role, although they have become less favored for high-resolution models of protein assemblies and lipid organization. Here, we review recent progress in the field, with an emphasis on the insight that has been gained using a mixture of coarse-grained and atomic-resolution molecular dynamics simulations. Based on successes and challenges to date, we suggest a multiresolution strategy that should yield the best mixture of computational efficiency and physical fidelity. This strategy may facilitate further simulations of viral entry by a broader range of viruses, helping illuminate the diversity of viral entry strategies and the essential common elements that can be targeted for antiviral therapies.

Managing Coronavirus Disease 2019 Spread With Voluntary Public Health Measures: Sweden as a Case Study for Pandemic Control.

BACKGROUND: The coronavirus disease 19 (COVID-19) pandemic has spread globally, causing extensive illness and mortality. In advance of effective antiviral therapies, countries have applied different public health strategies to control spread and manage healthcare need. Sweden has taken a unique approach of not implementing strict closures, instead urging personal responsibility. We analyze the results of this and other potential strategies for pandemic control in Sweden. METHODS: We implemented individual-based modeling of COVID-19 spread in Sweden using population, employment, and household data. Epidemiological parameters for COVID-19 were validated on a limited date range; where substantial uncertainties remained, multiple parameters were tested. The effects of different public health strategies were tested over a 160-day period, analyzed for their effects on intensive care unit (ICU) demand and death rate, and compared with Swedish data for April 2020. RESULTS: Swedish mortality rates are intermediate between rates for European countries that quickly imposed stringent public health controls and those for countries that acted later. Models most closely reproducing reported mortality data suggest that large portions of the population voluntarily self-isolate. Swedish ICU use rates remained lower than predicted, but a large fraction of deaths occurred in non-ICU patients. This suggests that patient prognosis was considered in ICU admission, reducing healthcare load at a cost of decreased survival in patients not admitted. CONCLUSIONS: The Swedish COVID-19 strategy has thus far yielded a striking result: mild mandates overlaid with voluntary measures can achieve results highly similar to late-onset stringent mandates. However, this policy causes more healthcare demand and more deaths than early stringent control and depends on continued public will.

SARS-CoV-2 receptor networks in diabetic and COVID-19-associated kidney disease.

COVID-19 morbidity and mortality are increased via unknown mechanisms in patients with diabetes and kidney disease. SARS-CoV-2 uses angiotensin-converting enzyme 2 (ACE2) for entry into host cells. Because ACE2 is a susceptibility factor for infection, we investigated how diabetic kidney disease and medications alter ACE2 receptor expression in kidneys. Single cell RNA profiling of kidney biopsies from healthy living donors and patients with diabetic kidney disease revealed ACE2 expression primarily in proximal tubular epithelial cells. This cell-specific localization was confirmed by in situ hybridization. ACE2 expression levels were unaltered by exposures to renin-angiotensin-aldosterone system inhibitors in diabetic kidney disease. Bayesian integrative analysis of a large compendium of public -omics datasets identified molecular network modules induced in ACE2-expressing proximal tubular epithelial cells in diabetic kidney disease (searchable at hb.flatironinstitute.org/covid-kidney) that were linked to viral entry, immune activation, endomembrane reorganization, and RNA processing. The diabetic kidney disease ACE2-positive proximal tubular epithelial cell module overlapped with expression patterns seen in SARS-CoV-2-infected cells. Similar cellular programs were seen in ACE2-positive proximal tubular epithelial cells obtained from urine samples of 13 hospitalized patients with COVID-19, suggesting a consistent ACE2-coregulated proximal tubular epithelial cell expression program that may interact with the SARS-CoV-2 infection processes. Thus SARS-CoV-2 receptor networks can seed further research into risk stratification and therapeutic strategies for COVID-19-related kidney damage.

Detecting and Controlling Dye Effects in Single-Virus Fusion Experiments.

Fluorescent dye-dequenching assays provide a powerful and versatile means to monitor membrane fusion events. They have been used in bulk assays, for measuring single events in live cells, and for detailed analysis of fusion kinetics for liposomal, viral, and cellular fusion processes; however, the dyes used also have the potential to perturb membrane fusion. Here, using single-virus measurements of influenza membrane fusion, we show that fluorescent membrane probes can alter both the efficiency and the kinetics of lipid mixing in a dye- and illumination-dependent manner. R18, a dye that is commonly used to monitor lipid mixing between membranes, is particularly prone to these effects, whereas Texas Red is somewhat less sensitive. R18 further undergoes photoconjugation to viral proteins in an illumination-dependent manner that correlates with its inactivation of viral fusion. These results demonstrate how fluorescent probes can perturb measurements of biological activity and provide both data and a method for determining minimally perturbative measurement conditions.

gmxapi: a high-level interface for advanced control and extension of molecular dynamics simulations.

Summary: Molecular dynamics simulations have found use in a wide variety of biomolecular applications, from protein folding kinetics to computational drug design to refinement of molecular structures. Two areas where users and developers frequently need to extend the built-in capabilities of most software packages are implementing custom interactions, for instance biases derived from experimental data, and running ensembles of simulations. We present a Python high-level interface for the popular simulation package GROMACS that i) allows custom potential functions without modifying the simulation package code, ii) maintains the optimized performance of GROMACS and iii) presents an abstract interface to building and executing computational graphs that allows transparent low-level optimization of data flow and task placement. Minimal dependencies make this integrated API for the GROMACS simulation engine simple, portable and maintainable. We demonstrate this API for experimentally-driven refinement of protein conformational ensembles. Availability and implementation: LGPLv2.1 source and instructions are available at https://github.com/kassonlab/gmxapi. Supplementary information: Supplementary data are available at Bioinformatics online.

Refinement of Highly Flexible Protein Structures using Simulation-Guided Spectroscopy.

Highly flexible proteins present a special challenge for structure determination because they are multi-structured yet not disordered, so their conformational ensembles are essential for understanding function. Because spectroscopic measurements of multiple conformational populations often provide sparse data, experiment selection is a limiting factor in conformational refinement. A molecular simulations- and information-theory based approach to select which experiments best refine conformational ensembles has been developed. This approach was tested on three flexible proteins. For proteins where a clear mechanistic hypothesis exists, experiments that test this hypothesis were systematically identified. When available data did not yield such mechanistic hypotheses, experiments that significantly outperform structure-guided approaches in conformational refinement were identified. This approach offers a particular advantage when refining challenging, underdetermined protein conformational ensembles.

Excess positional mutual information predicts both local and allosteric mutations affecting beta lactamase drug resistance.

MOTIVATION: Bacterial resistance to antibiotics, particularly plasmid-encoded resistance to beta lactam drugs, poses an increasing threat to human health. Point mutations to beta-lactamase enzymes can greatly alter the level of resistance conferred, but predicting the effects of such mutations has been challenging due to the large combinatorial space involved and the subtle relationships of distant residues to catalytic function. Therefore we desire an information-theoretic metric to sensitively and robustly detect both local and distant residues that affect substrate conformation and catalytic activity. RESULTS: Here, we report the use of positional mutual information in multiple microsecond-length molecular dynamics (MD) simulations to predict residues linked to catalytic activity of the CTX-M9 beta lactamase. We find that motions of the bound drug are relatively isolated from motions of the protein as a whole, which we interpret in the context of prior theories of catalysis. In order to robustly identify residues that are weakly coupled to drug motions but nonetheless affect catalysis, we utilize an excess mutual information metric. We predict 31 such residues for the cephalosporin antibiotic cefotaxime. Nine of these have previously been tested experimentally, and all decrease both enzyme rate constants and empirical drug resistance. We prospectively validate our method by testing eight high-scoring mutations and eight low-scoring controls in bacteria. Six of eight predicted mutations decrease cefotaxime resistance greater than 2-fold, while only one control shows such an effect. The ability to prospectively predict new variants affecting bacterial drug resistance is of great interest to clinical and epidemiological surveillance. AVAILABILITY AND IMPLEMENTATION: Excess mutual information code is available at https://github.com/kassonlab/positionalmi CONTACT: kasson@virginia.edu.

Disentangling Viral Membrane Fusion from Receptor Binding Using Synthetic DNA-Lipid Conjugates.

Enveloped viruses must bind to a receptor on the host membrane to initiate infection. Membrane fusion is subsequently initiated by a conformational change in the viral fusion protein, triggered by receptor binding, an environmental change, or both. Here, we present a strategy to disentangle the two processes of receptor binding and fusion using synthetic DNA-lipid conjugates to bind enveloped viruses to target membranes in the absence of receptor. This permits direct testing of whether receptor engagement affects the fusion mechanism as well as a comparison of fusion behavior across viruses with different receptor binding specificities. We demonstrate this approach by binding X-31 influenza virus to target vesicles and measuring the rates of individual pH-triggered lipid mixing events using fluorescence microscopy. Influenza lipid mixing kinetics are found to be independent of receptor binding, supporting the common yet previously unproven assumption that receptor binding does not produce any clustering or spatial rearrangement of viral hemagglutinin, which affects the rate-limiting step of pH-triggered fusion. This DNA-lipid tethering strategy should also allow the study of viruses where challenging receptor reconstitution has previously prevented single-virus fusion experiments.

Hemagglutinin Spatial Distribution Shifts in Response to Cholesterol in the Influenza Viral Envelope.

Influenza virus delivers its genome to the host cytoplasm via a process of membrane fusion mediated by the viral hemagglutinin protein. Optimal fusion likely requires multiple hemagglutinin trimers, so the spatial distribution of hemagglutinin on the viral envelope may influence fusion mechanism. We have previously shown that moderate depletion of cholesterol from the influenza viral envelope accelerates fusion kinetics even though it decreases fusion efficiency, both in a reversible manner. Here, we use electron cryo-microscopy to measure how the hemagglutinin lateral density in the viral envelope changes with cholesterol extraction. We extract this information by measuring the radial distribution function of electron density in >4000 viral images per sample, assigning hemagglutinin density by comparing images with and without anti-HA Fab bound. On average, hemagglutinin trimers move closer together: we estimate that the typical trimer-trimer spacing reduces from 94 to 84 Å when ∼90% of cholesterol is removed from the viral membrane. Upon restoration of viral envelope cholesterol, this spacing once again expands. This finding can qualitatively explain the observed changes to fusion kinetics: contemporary models from single-virus microscopy are that fusion requires the engagement of several hemagglutinin trimers in close proximity. If removing cholesterol increases the lateral density of hemagglutinin, this should result in an increase in the rate of fusion.

Coupled diffusion in lipid bilayers upon close approach.

Biomembrane interfaces create regions of slowed water dynamics in their vicinity. When two lipid bilayers come together, this effect is further accentuated, and the associated slowdown can affect the dynamics of larger-scale processes such as membrane fusion. We have used molecular dynamics simulations to examine how lipid and water dynamics are affected as two lipid bilayers approach each other. These two interacting fluid systems, lipid and water, both slow and become coupled when the lipid membranes are separated by a thin water layer. We show in particular that the water dynamics become glassy, and diffusion of lipids in the apposed leaflets becomes coupled across the water layer, while the "outer" leaflets remain unaffected. This dynamic coupling between bilayers appears mediated by lipid-water-lipid hydrogen bonding, as it occurs at bilayer separations where water-lipid hydrogen bonds become more common than water-water hydrogen bonds. We further show that such coupling occurs in simulations of vesicle-vesicle fusion prior to the fusion event itself. Such altered dynamics at membrane-membrane interfaces may both stabilize the interfacial contact and slow fusion stalk formation within the interface region.

Ebolavirus entry requires a compact hydrophobic fist at the tip of the fusion loop.

UNLABELLED: Ebolavirus is an enveloped virus causing severe hemorrhagic fever. Its surface glycoproteins undergo proteolytic cleavage and rearrangements to permit membrane fusion and cell entry. Here we focus on the glycoprotein's internal fusion loop (FL), critical for low-pH-triggered fusion in the endosome. Alanine mutations at L529 and I544 and particularly the L529 I544 double mutation compromised viral entry and fusion. The nuclear magnetic resonance (NMR) structures of the I544A and L529A I544A mutants in lipid environments showed significant disruption of a three-residue scaffold that is required for the formation of a consolidated fusogenic hydrophobic surface at the tip of the FL. Biophysical experiments and molecular simulation revealed the position of the wild-type (WT) FL in membranes and showed the inability of the inactive double mutant to reach this position. Consolidation of hydrophobic residues at the tip of FLs may be a common requirement for internal FLs of class I, II, and III fusion proteins. IMPORTANCE: Many class I, II, and III viral fusion proteins bear fusion loops for target membrane insertion and fusion. We determined structures of the Ebolavirus fusion loop and found residues critical for forming a consolidated hydrophobic surface, membrane insertion, and viral entry.

Structure of the Neisserial outer membrane protein Opa60: loop flexibility essential to receptor recognition and bacterial engulfment.

The structure and dynamics of Opa proteins, which we report herein, are responsible for the receptor-mediated engulfment of Neisseria gonorrheae or Neisseria meningitidis by human cells and can offer deep understanding into the molecular recognition of pathogen-host receptor interactions. Such interactions are vital to understanding bacterial pathogenesis as well as the mechanism of foreign body entry to a human cell, which may provide insights for the development of targeted pharmaceutical delivery systems. The size and dynamics of the extracellular loops of Opa60 required a hybrid refinement approach wherein membrane and distance restraints were used to generate an initial NMR structural ensemble, which was then further refined using molecular dynamics in a DMPC bilayer. The resulting ensemble revealed that the extracellular loops, which bind host receptors, occupy compact conformations, interact with each other weakly, and are dynamic on the nanosecond time scale. We predict that this conformational sampling is critical for enabling diverse Opa loop sequences to engage a common set of receptors.