Stochastic simulation of hemagglutinin-mediated fusion pore formation

Modeling the Role of Epitope Arrangement on Antibody Binding Stoichiometry in Flaviviruses

Cryo-electron-microscopy (cryo-EM) structures of flaviviruses reveal significant variation in epitope occupancy across different monoclonal antibodies that have largely been attributed to epitope-level differences in conformation or accessibility that affect antibody binding. The consequences of these variations for macroscopic properties such as antibody binding and neutralization are the results of the law of mass action-a stochastic process of innumerable binding and unbinding events between antibodies and the multiple binding sites on the flavivirus in equilibrium-that cannot be directly imputed from structure alone. We carried out coarse-grained spatial stochastic binding simulations for nine flavivirus antibodies with epitopes defined by cryo-EM or x-ray crystallography to assess the role of epitope spatial arrangement on antibody-binding stoichiometry, occupancy, and neutralization. In our simulations, all epitopes were equally competent for binding, representing the upper limit of binding stoichiometry that results from epitope spatial arrangement alone. Surprisingly, our simulations closely reproduced the relative occupancy and binding stoichiometry observed in cryo-EM, without having to account for differences in epitope accessibility or conformation, suggesting that epitope spatial arrangement alone may be sufficient to explain differences in binding occupancy and stoichiometry between antibodies. Furthermore, we found that there was significant heterogeneity in binding configurations even at saturating antibody concentrations, and that bivalent antibody binding may be more common than previously thought. Finally, we propose a structure-based explanation for the stoichiometric threshold model of neutralization.

Mechanisms of influenza viral membrane fusion

Influenza viral particles are enveloped by a lipid bilayer. A major step in infection is fusion of the viral and host cellular membranes, a process with large kinetic barriers. Influenza membrane fusion is catalyzed by hemagglutinin (HA), a class I viral fusion protein activated by low pH. The exact nature of the HA conformational changes that deliver the energy required for fusion remains poorly understood. This review summarizes our current knowledge of HA structure and dynamics, describes recent single-particle experiments and modeling studies, and discusses their role in understanding how multiple HAs mediate fusion. These approaches provide a mechanistic picture in which HAs independently and stochastically insert into the target membrane, forming a cluster of HAs that is collectively able to overcome the barrier to membrane fusion. The new experimental and modeling approaches described in this review hold promise for a more complete understanding of other viral fusion systems and the protein systems responsible for cellular fusion.

Stochastic fusion simulations and experiments suggest passive and active roles of hemagglutinin during membrane fusion

Influenza enters the host cell cytoplasm by fusing the viral and host membrane together. Fusion is mediated by hemagglutinin (HA) trimers that undergo conformational change when acidified in the endosome. It is currently debated how many HA trimers, w, and how many conformationally changed HA trimers, q, are minimally required for fusion. Conclusions vary because there are three common approaches for determining w and q from fusion data. One approach correlates the fusion rate with the fraction of fusogenic HA trimers and leads to the conclusion that one HA trimer is required for fusion. A second approach correlates the fusion rate with the total concentration of fusogenic HA trimers and indicates that more than one HA trimer is required. A third approach applies statistical models to fusion rate data obtained at a single HA density to establish w or q and suggests that more than one HA trimer is required. In this work, all three approaches are investigated through stochastic fusion simulations and experiments to elucidate the roles of HA and its ability to bend the target membrane during fusion. We find that the apparent discrepancies among the results from the various approaches may be resolved if nonfusogenic HA participates in fusion through interactions with a fusogenic HA. Our results, based on H3 and H1 serotypes, suggest that three adjacent HA trimers and one conformationally changed HA trimer are minimally required to induce membrane fusion (w = 3 and q = 1).

Structured model of influenza virus replication in MDCK cells

Intracellular events that take place during influenza virus replication in animal cells are well understood qualitatively. However, to better understand the complex interaction of the virus with its host cell and to quantitatively analyze the use of cellular resources for virion formation or the overall dynamic for the entire infection cycle, a mathematical model for influenza virus replication has to be formulated. Here, we present a structured model for the single-cell reproductive cycle of influenza A virus in animal cells that accounts for the individual steps of the process such as attachment, internalization, genome replication and translation, and progeny virion assembly. The model describes an average cell surrounded by a small quantity of medium and infected by a low number of virus particles. The model allows estimation of the cellular resources consumed by virus replication. Simulation results show that the number of cellular surface receptors and endosomes, as well as other resources, such as the number of free nucleotides or amino acids, is not significantly influenced by influenza virus propagation. A factor that limits the growth rate of progeny viruses and their release is the total amount of matrix proteins (M1) in the nucleus while other newly synthesized viral proteins (e.g., nucleoprotein NP) and viral RNAs accumulate. During budding, synthesis of vRNPs (viral ribonucleoprotein complexes) represents another limiting factor. Based on this model it is also possible to analyze effects of parameter changes on the dynamics of virus replication, to identify possible targets for molecular engineering, or to develop strategies for improving yields in vaccine production processes. Furthermore, a better insight into the interactions of viruses and host cells might help to improve our understanding of virus-related diseases and to develop therapies.