Biology subjects

Kasson, P. M.

Publications and source records attributed to Kasson, P. M..

11 recordsLinked to original sources

bioRxiv2026

Tuning nanoscale lipid clustering controls influenza viral binding

Influenza virus attaches to cells by binding to sialylated glycans. Subsequent endocytosis of the virus and endosomal maturation leads to a conformational change in the hemagglutinin coat protein that ultimately results in membrane fusion and release of the viral genome into the host cytoplasm, where it is trafficked to the nucleus and commences replication. Individual hemagglutinin-glycan binding affinities are weak (Kd approximately mM), so multivalency is key to viral attachment. Receptor density or clustering has previously been shown to affect influenza binding, but the overall spatial heterogeneity of both plasma and endosomal membranes has not been fully addressed. Here, we show that nanoscale lipid clustering can increase local concentration of glycosphingolipids and greatly enhance influenza viral binding in a way that macroscopic phase separation does not, and that binding avidity is dependent on the spatiotemporal scales of this clustering. This clustering is driven by sphingolipids and cholesterol and the nanoscale lipid environment of these clusters persists to affect the viral entry process. This finding demonstrates how fine receptor patterning can drive infection and illustrates the importance of tuning spatial scale in liquid-liquid phase separation.

biophysics↗

bioRxiv2025

Influenza viral infection at the plasma membrane is restricted by lipid composition

Many enveloped viruses enter cells via fusion with the endosomal membrane, raising the question whether entry through the endosomal route confers a fitness advantage over fusion directly at the plasma membrane. We found that influenza A virus fusion at the plasma membrane of A549 cells resulted in a 7.6-fold reduction in productive cell infection, compared to infection through the physiological endosomal route. We hypothesized that this was partially explained by restrictive and permissive membrane factors at the plasma and endosomal membrane, respectively. To test this, we developed a single-viral content mixing assay with plasma membrane vesicles (PMVs), where a fluorescent content marker was loaded into purified PMVs at a quenched concentration, through freeze-thawing. We show that influenza fusion with the plasma membrane is 6-fold less efficient than with liposomes containing the endosome-enriched phospholipid BMP. Incorporating BMP into the PMVs with pre-loaded methyl--cyclodextrin (MCD) did not rescue full fusion, suggesting that the lack of BMP in the plasma membrane is not sufficient to explain decreased fusion with the plasma membrane. Depletion of cholesterol from PMVs enhanced lipid mixing rates and reduced membrane order. Lastly, modest depletion of cholesterol from A549 lung epithelial cells rescued influenza infection through fusion at the plasma membrane by 2.4-fold. We propose that for the endosome-adapted influenza virus, fusion directly at the plasma membrane is restricted by the liquid-ordered-like nature of the plasma membrane, raising the question whether the plasma membrane is broadly less permissive to viral entry than endosomes. ImportanceInfluenza virus normally enters cells via endosomes, yet it has been known for decades that acidic conditions can force it to enter via the plasma membrane. Here, we show that the plasma membrane route yields 9-fold worse infection of cells and, surprisingly, most of this effect can be attributed to the plasma membrane being less permissive to viral membrane fusion. This difference between plasma membrane and endosomes cannot be simply abolished by adding a key endosomal lipid that can boost fusion in synthetic membranes. The outer surface of the plasma membrane is known to be highly ordered, and disrupting this order does increase fusion as well as boost the ability of influenza virus to infect cells. We therefore conclude that the complex and ordered composition of cell membranes helps control when and where influenza virus can enter and infect.

biophysics↗

bioRxiv2023

Structural prediction of chimeric immunogens to elicit targeted antibodies against betacoronaviruses

Betacoronaviruses pose an ongoing pandemic threat. Antigenic evolution of the SARS-CoV-2 virus has shown that much of the spontaneous antibody response is narrowly focused rather than broadly neutralizing against even SARS-CoV-2 variants, let alone future threats. One way to overcome this is by focusing the antibody response against better-conserved regions of the viral spike protein. Here, we present a design approach to predict stable chimeras between SARS-CoV-2 and other coronaviruses, creating synthetic spike proteins that display a desired conserved region and vary other regions. We leverage AlphaFold to predict chimeric structures and create a new metric for scoring chimera stability based on AlphaFold outputs. We evaluated 114 candidate spike chimeras using this approach. Top chimeras were further evaluated using molecular dynamics simulation as an intermediate validation technique, showing good stability compared to low-scoring controls. Experimental testing of five predicted-stable and two predicted-unstable chimeras confirmed 5/7 predictions, with one intermediate result. This demonstrates the feasibility of the underlying approach, which can be used to design custom immunogens to focus the immune response against a desired viral glycoprotein epitope.

biophysics↗

bioRxiv2022

The ACE-2 receptor accelerates but is not biochemically required for SARS-CoV-2 membrane fusion.

The SARS-CoV-2 coronavirus infects human cells via the ACE-2 receptor. Circumstantial evidence suggests that ACE-2 may not just serve as an attachment factor but also help activate the SARS-CoV-2 spike protein for membrane fusion. Here, we test that hypothesis directly, using DNA-lipid tethering as a synthetic attachment factor in the place of ACE-2. We find that SARS-CoV-2 pseudovirus and viruslike particles are both capable of membrane fusion if attached in the absence of ACE-2 and activated with an appropriate protease. However, addition of soluble ACE-2 speeds the fusion reaction. This is observed for both the Wuhan strain and the B.1.1.529 Omicron variant. Kinetic analysis suggests that there are at least two rate-limiting steps for SARS-CoV-2 membrane fusion, one of which is ACE-2 dependent and one of which is not. These data establish that, in the presence of an alternative attachment factor, ACE-2 is not biochemically required for SARS-CoV-2 membrane fusion. Since ACE-2 serves as the high-affinity attachment factor on human cells, the possibility to replace it with other factors has implications for the evolvability of SARS-CoV-2 and the fitness landscape for future related coronaviruses.

microbiology↗

bioRxiv2022

Influenza virus membrane fusion is promoted by the endosome-resident phospholipid bis(monoacylglycero)phosphate

The phospholipid bis(monoacylglycero)phosphate (BMP) is enriched in late endosomal and endo-lysosomal membranes and is believed to be involved in membrane deformation and generation of intralumenal vesicles within late endosomes. Previous studies have demonstrated that BMP promotes membrane fusion of several enveloped viruses, but a limited effect has been found on influenza virus. Here, we report the use of single-virus fusion assays to dissect BMPs effect on influenza virus fusion in greater depth. In agreement with prior reports, we found that hemifusion kinetics and efficiency were unaffected by the addition of 10-20 mol % BMP to the target membrane. However, using an assay for fusion pore formation and genome exposure, we found full fusion efficiency to be substantially enhanced by the addition of 10-20 mol % BMP to the target membrane, while the kinetics remained unaffected. By comparing BMP to other negatively charged phospholipids, we found the effect on fusion efficiency mainly attributable to headgroup charge, although we also hypothesize a role for BMPs unusual chemical structure. Our results suggest that BMP function as a permissive factor for a wider range of viruses than previously reported. We hypothesize that BMP may be a general co-factor for endosomal entry of enveloped viruses.

biophysics↗

bioRxiv2020

Simulation-guided engineering of antibiotics for improved bacterial uptake

The Gram-negative bacterial outer membrane poses a major obstacle to the development of much-needed antibiotics against drug-resistant infections. Its chemical composition and porin proteins differ from Gram-positive bacteria and mammalian cells, and heuristics developed for mammalian cell uptake apply poorly. Recently, machinelearning methods have predicted small-molecule uptake into Gram-negative bacteria, offering the possibility to rationally optimize this aspect of antibiotic lead development. Here, we report physics-based methods to prospectively predict Gram-negative bacterial uptake, select, and synthesize promising chemical derivatives targeting E. coli DNA gyrase B. Our methods do not require empirical parameterization and are readily adaptable to new chemical scaffolds. These physics-based predictions well capture experimentally measured uptake (r > 0.95) and are indeed predictive of antimicrobial activity (r > 0.92). These methods can be used prospectively in combination with target-binding simulations to optimize both bacterial uptake and target binding, overcoming important barriers to antibiotic lead generation before small-molecule synthesis.

microbiology↗

bioRxiv2020

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 have 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 prior to stalk formation and one after, are consistent with experimental measurements we report of single-virus fusion kinetics to liposomes of different sizes. The resulting model also helps explain and integrate prior 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 utilize sequential processes of acyl tail exposure followed by membrane curvature and distal leaflet engagement.

biophysics↗

bioRxiv2019

Hybrid refinement of heterogeneous conformational ensembles using spectroscopic data

Multi-structured biomolecular systems play crucial roles in a wide variety of cellular processes but have resisted traditional methods of structure determination which often resolve only a few low-energy states. High-resolution structure determination using experimental methods that yield distributional data remains extremely difficult, especially when the underlying conformational ensembles are quite heterogeneous. We have therefore developed a method to integrate sparse, multi-multimodal spectroscopic data to obtain high-resolution estimates of conformational ensembles. We have tested our method by incorporating double electron-electron resonance data on the SNARE protein syntaxin-1a into biased molecular dynamics simulations. We find that our method substantially outperforms existing state-of-the-art methods in capturing syntaxins open/closed conformational equilibrium and further yields new conformational states that are both consistent with experimental data and may help in understanding syntaxins function. Our improved methods for refining heterogeneous conformational ensembles from spectroscopic data will greatly accelerate the structural understanding of such systems.

biophysics↗

bioRxiv2019

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, while 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.\n\nStatement of SignificanceFluorescent dyes are powerful tools for labeling membranes and tracking subcellular objects, and fluorescence dequenching has further been used as a sensitive assay for membrane fusion. Here we show how incorporation of membrane dyes can perturb membrane fusion by influenza virus in a light-dependent manner. We provide a strategy to mitigate this by minimizing dye and light exposure. Finally, we show how in some cases these effects can be due to covalent reaction of some dyes with viral proteins upon illumination. These phenomena may be general and should be carefully controlled for in experiments using such labels.

biophysics↗

bioRxiv2018

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, and the resulting conformational ensembles are essential for understanding function. Determining such ensembles is difficult because many measurements that capture multiple conformational populations provide sparse data. A powerful opportunity exists to leverage molecular simulations for spectroscopic experiment selection. We have developed an information-theoretic approach to guide experiments by identifying which measurements best refine the underlying conformational ensemble. We have tested this approach on three flexible bacterial proteins. For proteins where a clear mechanistic hypothesis drives label selection, our approach systematically identifies labels that would test this hypothesis. Furthermore, when available data do not yield an obvious mechanistically-guided label selection strategy, our approach guides label selection and produces conformational refinement that significantly outperforms standard structure-guided approaches. Our information-theoretic approach to label selection thus offers a particular advantage when refining challenging, underdetermined protein conformational ensembles.

bioinformatics↗

bioRxiv2018

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

SummaryMolecular 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 1) allows custom potential functions without modifying the simulation package code, 2) maintains the optimized performance of GROMACS, and 3) 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.\n\nAvailabilitySource and installation instructions are available at https://github.com/kassonlab/gmxapi.

biophysics↗