48 research outputs found

    Atomistic Simulations of Bicelle Mixtures

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    AbstractMixtures of long- and short-tail phosphatidylcholine lipids are known to self-assemble into a variety of aggregates combining flat bilayerlike and curved micellelike features, commonly called bicelles. Atomistic simulations of bilayer ribbons and perforated bilayers containing dimyristoylphosphatidylcholine (DMPC, di-C14 tails) and dihexanoylphosphatidylcholine (DHPC, di-C6 tails) have been carried out to investigate the partitioning of these components between flat and curved microenvironments and the stabilization of the bilayer edge by DHPC. To approach equilibrium partitioning of lipids on an achievable simulation timescale, configuration-bias Monte Carlo mutation moves were used to allow individual lipids to change tail length within a semigrand-canonical ensemble. Since acceptance probabilities for direct transitions between DMPC and DHPC were negligible, a third component with intermediate tail length (didecanoylphosphatidylcholine, di-C10 tails) was included at a low concentration to serve as an intermediate for transitions between DMPC and DHPC. Strong enrichment of DHPC is seen at ribbon and pore edges, with an excess linear density of ∌3 nm−1. The simulation model yields estimates for the onset of edge stability with increasing bilayer DHPC content between 5% and 15% DHPC at 300 K and between 7% and 17% DHPC at 323 K, higher than experimental estimates. Local structure and composition at points of close contact between pores suggest a possible mechanism for effective attractions between pores, providing a rationalization for the tendency of bicelle mixtures to aggregate into perforated vesicles and perforated sheets

    Structural Organization of DNA in Chlorella Viruses

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    Chlorella viruses have icosahedral capsids with an internal membrane enclosing their large dsDNA genomes and associated proteins. Their genomes are packaged in the particles with a predicted DNA density of ca. 0.2 bp nm−3. Occasionally infection of an algal cell by an individual particle fails and the viral DNA is dynamically ejected from the capsid. This shows that the release of the DNA generates a force, which can aid in the transfer of the genome into the host in a successful infection. Imaging of ejected viral DNA indicates that it is intimately associated with proteins in a periodic fashion. The bulk of the protein particles detected by atomic force microscopy have a size of ∌60 kDa and two proteins (A278L and A282L) of about this size are among 6 basic putative DNA binding proteins found in a proteomic analysis of DNA binding proteins packaged in the virion. A combination of fluorescence images of ejected DNA and a bioinformatics analysis of the DNA reveal periodic patterns in the viral DNA. The periodic distribution of GC rich regions in the genome provides potential binding sites for basic proteins. This DNA/protein aggregation could be responsible for the periodic concentration of fluorescently labeled DNA observed in ejected viral DNA. Collectively the data indicate that the large chlorella viruses have a DNA packaging strategy that differs from bacteriophages; it involves proteins and share similarities to that of chromatin structure in eukaryotes

    31st Annual Meeting and Associated Programs of the Society for Immunotherapy of Cancer (SITC 2016) : part two

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    Background The immunological escape of tumors represents one of the main ob- stacles to the treatment of malignancies. The blockade of PD-1 or CTLA-4 receptors represented a milestone in the history of immunotherapy. However, immune checkpoint inhibitors seem to be effective in specific cohorts of patients. It has been proposed that their efficacy relies on the presence of an immunological response. Thus, we hypothesized that disruption of the PD-L1/PD-1 axis would synergize with our oncolytic vaccine platform PeptiCRAd. Methods We used murine B16OVA in vivo tumor models and flow cytometry analysis to investigate the immunological background. Results First, we found that high-burden B16OVA tumors were refractory to combination immunotherapy. However, with a more aggressive schedule, tumors with a lower burden were more susceptible to the combination of PeptiCRAd and PD-L1 blockade. The therapy signifi- cantly increased the median survival of mice (Fig. 7). Interestingly, the reduced growth of contralaterally injected B16F10 cells sug- gested the presence of a long lasting immunological memory also against non-targeted antigens. Concerning the functional state of tumor infiltrating lymphocytes (TILs), we found that all the immune therapies would enhance the percentage of activated (PD-1pos TIM- 3neg) T lymphocytes and reduce the amount of exhausted (PD-1pos TIM-3pos) cells compared to placebo. As expected, we found that PeptiCRAd monotherapy could increase the number of antigen spe- cific CD8+ T cells compared to other treatments. However, only the combination with PD-L1 blockade could significantly increase the ra- tio between activated and exhausted pentamer positive cells (p= 0.0058), suggesting that by disrupting the PD-1/PD-L1 axis we could decrease the amount of dysfunctional antigen specific T cells. We ob- served that the anatomical location deeply influenced the state of CD4+ and CD8+ T lymphocytes. In fact, TIM-3 expression was in- creased by 2 fold on TILs compared to splenic and lymphoid T cells. In the CD8+ compartment, the expression of PD-1 on the surface seemed to be restricted to the tumor micro-environment, while CD4 + T cells had a high expression of PD-1 also in lymphoid organs. Interestingly, we found that the levels of PD-1 were significantly higher on CD8+ T cells than on CD4+ T cells into the tumor micro- environment (p < 0.0001). Conclusions In conclusion, we demonstrated that the efficacy of immune check- point inhibitors might be strongly enhanced by their combination with cancer vaccines. PeptiCRAd was able to increase the number of antigen-specific T cells and PD-L1 blockade prevented their exhaus- tion, resulting in long-lasting immunological memory and increased median survival

    Simulation and Theory of Self-Assembled Networks:  Ends, Junctions, and Loops †

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    Accounting for Finite-Number Effects on Cluster Size Distributions in Simulations of Equilibrium Aggregation

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    An approach is given to analyze aggregate size distributions obtained from simulations of a fixed number <i>N</i> of monomers undergoing reversible self-assembly. Equilibrium distributions are derived from size-dependent equilibrium association constants by appropriately weighted sums over all partitions of <i>N</i> monomers into aggregates. Conversely, equilibrium association constants can be obtained from an iterative fit to a finite-<i>N</i> equilibrium distribution. Model data for a micelle-forming system are used to show how results from simulations containing few micelles can yield infinite-<i>N</i> limiting distributions. A strategy is also suggested to exploit small-<i>N</i> effects on aggregate size distributions to enhance sampling of critical clusters in determination of nucleation free energy functions

    Simulation Study of the Permeability of a Model Lipid Membrane at the Fluid–Solid Phase Transition

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    When a range of lipid bilayers are melted to the disordered fluid phase from the (much less permeable) ordered gel phase, their permeability to a variety of permeants shows a peak at the transition temperature and drops off with increasing temperature, rather than just rising as melting proceeds. To explore this anomalous behavior, a simulated coarse-grained lipid membrane model that exhibits a phase transition upon expansion or compression was studied to determine how the permeation rate of a simple particle depends on the phase composition in the two-phase region and on particle size. The permeation rate and each phase’s area fraction and area density could be directly calculated, along with the probability that the permeant would cross in either phase or in interfacial regions. For large permeants and system sizes, conditions could be found where permeability increases upon compression of the bilayer. Permeation was negligible in the gel phase and, in contrast to the predictions of the “leaky interface” hypothesis, was not enriched in interfacial regions. The anomalous effect could instead be attributed to an increase in the area per lipid of fluid-phase domains. This result motivated a model for the decrease in effective permeability barrier through fluid-phase domains arising from a decrease in the length of the gel/fluid interface at the midpoint of a permeation event

    Cluster Free Energies from Simple Simulations of Small Numbers of Aggregants: Nucleation of Liquid MTBE from Vapor and Aqueous Phases

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    We introduce a global fitting analysis method to obtain free energies of association of noncovalent molecular clusters using equilibrated cluster size distributions from unbiased constant-temperature molecular dynamics (MD) simulations. Because the systems simulated are small enough that the law of mass action does not describe the aggregation statistics, the method relies on iteratively determining a set of cluster free energies that, using appropriately weighted sums over all possible partitions of <i>N</i> monomers into clusters, produces the best-fit size distribution. The quality of these fits can be used as an objective measure of self-consistency to optimize the cutoff distance that determines how clusters are defined. To showcase the method, we have simulated a united-atom model of methyl <i>tert</i>-butyl ether (MTBE) in the vapor phase and in explicit water solution over a range of system sizes (up to 95 MTBE in the vapor phase and 60 MTBE in the aqueous phase) and concentrations at 273 K. The resulting size-dependent cluster free energy functions follow a form derived from classical nucleation theory (CNT) quite well over the full range of cluster sizes, although deviations are more pronounced for small cluster sizes. The CNT fit to cluster free energies yielded surface tensions that were in both cases lower than those for the simulated planar interfaces. We use a simple model to derive a condition for minimizing non-ideal effects on cluster size distributions and show that the cutoff distance that yields the best global fit is consistent with this condition
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