Key factors of scanning a plant virus with AFM in air and aqueous solution

Image histogram decomposition method for particle sizing - A numerical simulation study

Scanning probe microscopy is a useful tool in nanoscience. The effective application of nanotechnologies in various fields requires a knowledge of the characteristic attributes of nanoparticles such as shape, dimensions and statistical distribution, and a wide spectrum of experimental and theoretical methods based on various principles have been developed to determine these characteristics. Image histograms offer a global overview of the characteristics of an image. Their shape can encode specific statistical properties of displayed objects such as the distribution function in the case of similar and scalable objects. The model of height histogram presented here proposes a method which solves the long-term problem of processing images of extremely dense particle distributions. The method is based on the principle of the superposition of histograms of individual particles whose topographic surface is described by a parametric model. The resulting height histogram is defined by a convolution of the model of the particle histogram with the distribution function of particle size, with this construction forming the basis of the regression model. The parameters of the distribution function can be obtained via the optimization of the model. The method has been tested on artificially generated configurations of particles of various shapes and size distributions. Each of these configurations creates a topographic surface which is transformed into an image, and the heights obtained from the image allow a histogram to be calculated. Firstly, various configurations of particles are simulated without the presence of any disruptive influences. Next, several experimental effects are evaluated separately (for example, the background, particle shape irregularity and particle overlap). The decomposition of the histogram by the regression model on artificially generated images shows the robustness of the method with respect to particle density, partial horizontal overlap, randomly generated backgrounds and random fluctuations in particle shape. However, the method is sensitive to uniform changes in particle shape, a factor which limits its use to particles with known parametric models of their shape which allow the means of their parameters to be estimated.

Influenza A virus hemagglutinin prevents extensive membrane damage upon dehydration

While the molecular mechanisms of virus infectivity are rather well known, the detailed consequences of environmental factors on virus biophysical properties are poorly understood. Seasonal influenza outbreaks are usually connected to the low winter temperature, but also to the low relative air humidity. Indeed, transmission rates increase in cold regions during winter. While low temperature must slow degradation processes, the role of low humidity is not clear. We studied the effect of relative humidity on a model of Influenza A H1N1 virus envelope, a supported lipid bilayer containing the surface glycoprotein hemagglutinin (HA), which is present in the viral envelope in very high density. For complete cycles of hydration, dehydration and rehydration, we evaluate the membrane properties in terms of structure and dynamics, which we assess by combining confocal fluorescence microscopy, raster image correlation spectroscopy, line-scan fluorescence correlation spectroscopy and atomic force microscopy. Our findings indicate that the presence of HA prevents macroscopic membrane damage after dehydration. Without HA, fast membrane disruption is followed by irreversible loss of lipid and protein mobility. Although our model is principally limited by the membrane composition, the macroscopic effects of HA under dehydration stress reveal new insights on the stability of the virus at low relative humidity.

Virus Isoelectric Point Determination Using Single-Particle Chemical Force Microscopy

Virus colloidal behavior is governed by the interaction of the viral surface and the surrounding environment. One method to characterize the virus surface charge is the isoelectric point (pI). Traditional determination of virus pI has focused on the bulk characterization of a viral solution. However, virus capsids are extremely heterogeneous, and a single-particle method may give more information on the range of surface charge observed across a population. One method to measure the virus pI is chemical force microscopy (CFM). CFM is a single-particle technique that measures the adhesion force of a functionalized atomic force microscope (AFM) probe and, in this case, a virus covalently bound to a surface. Non-enveloped porcine parvovirus (PPV) and enveloped bovine viral diarrhea virus (BVDV) were used to demonstrate the use of CFM for viral particles with different surface properties. We have validated the CFM to determine the pI of PPV to be 4.8-5.1, which has a known pI value of 5.0 in the literature, and to predict the unknown pI of BVDV to be 4.3-4.5. Bulk measurements, ζ-potential, and aqueous two-phase system (ATPS) cross-partitioning methods were also used to validate the new CFM method for the virus pI. Most methods were in good agreement. CFM can detect the surface charge of viral capsids at a single-particle level and enable the comparison of surface charge between different types of viruses.