Dynamic force microscopy for imaging of viruses under physiological conditions

Dynamic force microscopy (DFM) allows imaging of the structure and the assessment of the function of biological specimens in their physiological environment. In DFM, the cantilever is oscillated at a given frequency and touches the sample only at the end of its downward movement. Accordingly, the problem of lateral forces displacing or even destroying bio-molecules is virtually inexistent as the contact time and friction forces are reduced. Here, we describe the use of DFM in studies of human rhinovirus serotype 2 (HRV2) weakly adhering to mica surfaces. The capsid of HRV2 was reproducibly imaged without any displacement of the virus. Release of the genomic RNA from the virions was initiated by exposure to low pH buffer and snapshots of the extrusion process were obtained. In the following, the technical details of previous DFM investigations of HRV2 are summarized

Preparation and Characterization of Covalently Binding of Rat Anti-human IgG Monolayer on Thiol-Modified Gold Surface

The 16-mercaptohexadecanoic acid (MHA) film and rat anti-human IgG protein monolayer were fabricated on gold substrates using self-assembled monolayer (SAM) method. The surface properties of the bare gold substrate, the MHA film and the protein monolayer were characterized by contact angle measurements, atomic force microscopy (AFM), grazing incidence X-ray diffraction (GIXRD) method and X-ray photoelectron spectroscopy, respectively. The contact angles of the MHA film and the protein monolayer were 18° and 12°, respectively, all being hydrophilic. AFM images show dissimilar topographic nanostructures between different surfaces, and the thickness of the MHA film and the protein monolayer was estimated to be 1.51 and 5.53 nm, respectively. The GIXRD 2θ degrees of the MHA film and the protein monolayer ranged from 0° to 15°, significantly smaller than that of the bare gold surface, but the MHA film and the protein monolayer displayed very different profiles and distributions of their diffraction peaks. Moreover, the spectra of binding energy measured from these different surfaces could be well fitted with either Au4f, S2p or N1s, respectively. Taken together, these results indicate that MHA film and protein monolayer were successfully formed with homogeneous surfaces, and thus demonstrate that the SAM method is a reliable technique for fabricating protein monolayer

Batch effect confounding leads to strong bias in performance estimates obtained by cross-validation.

BACKGROUND: With the large amount of biological data that is currently publicly available, many investigators combine multiple data sets to increase the sample size and potentially also the power of their analyses. However, technical differences ("batch effects") as well as differences in sample composition between the data sets may significantly affect the ability to draw generalizable conclusions from such studies. FOCUS: The current study focuses on the construction of classifiers, and the use of cross-validation to estimate their performance. In particular, we investigate the impact of batch effects and differences in sample composition between batches on the accuracy of the classification performance estimate obtained via cross-validation. The focus on estimation bias is a main difference compared to previous studies, which have mostly focused on the predictive performance and how it relates to the presence of batch effects. DATA: We work on simulated data sets. To have realistic intensity distributions, we use real gene expression data as the basis for our simulation. Random samples from this expression matrix are selected and assigned to group 1 (e.g., 'control') or group 2 (e.g., 'treated'). We introduce batch effects and select some features to be differentially expressed between the two groups. We consider several scenarios for our study, most importantly different levels of confounding between groups and batch effects. METHODS: We focus on well-known classifiers: logistic regression, Support Vector Machines (SVM), k-nearest neighbors (kNN) and Random Forests (RF). Feature selection is performed with the Wilcoxon test or the lasso. Parameter tuning and feature selection, as well as the estimation of the prediction performance of each classifier, is performed within a nested cross-validation scheme. The estimated classification performance is then compared to what is obtained when applying the classifier to independent data

Automated Force Volume Image Processing for Biological Samples

Atomic force microscopy (AFM) has now become a powerful technique for investigating on a molecular level, surface forces, nanomechanical properties of deformable particles, biomolecular interactions, kinetics, and dynamic processes. This paper specifically focuses on the analysis of AFM force curves collected on biological systems, in particular, bacteria. The goal is to provide fully automated tools to achieve theoretical interpretation of force curves on the basis of adequate, available physical models. In this respect, we propose two algorithms, one for the processing of approach force curves and another for the quantitative analysis of retraction force curves. In the former, electrostatic interactions prior to contact between AFM probe and bacterium are accounted for and mechanical interactions operating after contact are described in terms of Hertz-Hooke formalism. Retraction force curves are analyzed on the basis of the Freely Jointed Chain model. For both algorithms, the quantitative reconstruction of force curves is based on the robust detection of critical points (jumps, changes of slope or changes of curvature) which mark the transitions between the various relevant interactions taking place between the AFM tip and the studied sample during approach and retraction. Once the key regions of separation distance and indentation are detected, the physical parameters describing the relevant interactions operating in these regions are extracted making use of regression procedure for fitting experiments to theory. The flexibility, accuracy and strength of the algorithms are illustrated with the processing of two force-volume images, which collect a large set of approach and retraction curves measured on a single biological surface. For each force-volume image, several maps are generated, representing the spatial distribution of the searched physical parameters as estimated for each pixel of the force-volume image

AFM study of morphology and mechanical properties of a chimeric 2 spider silk and bone sialoprotein protein for bone regeneration

Atomic force microscopy (AFM) was used to assess a new chimeric protein consisting of a fusion protein of the consensus repeat for Nephila clavipes spider dragline protein and bone sialoprotein (6merþBSP). The elastic modulus of this protein in film form was assessed through force curves, and film surface roughness was also determined. The results showed a significant difference among the elastic modulus of the chimeric silk protein, 6merþBSP, and control films consisting of only the silk component (6mer). The behavior of the 6merþBSP and 6mer proteins in aqueous solution in the presence of calcium (Ca) ions was also assessed to determine interactions between the inorganic and organic components related to bone interactions, anchoring, and biomaterial network formation. The results demonstrated the formation of protein networks in the presence of Ca2þ ions, characteristics that may be important in the context of controlling materials assembly and properties related to bone formation with this new chimeric silk-BSP protein.Silvia Games thanks the Foundation for Science and Technology (FCT) for supporting her Ph.D. grant, SFRH/BD/28603/2006. This work was carried out under the scope of the European NoE EXPERTISSUES (NMP3-CT-2004-500283), the Chimera project (PTDC/EBB-EBI/109093/2008) funded by the FCT agency, the NIH (P41 EB002520) Tissue Engineering Resource Center, and the NIH (EB003210 and DE017207)

Cell–Matrix De-Adhesion Dynamics Reflect Contractile Mechanics

Measurement of the mechanical properties of single cells is of increasing interest both from a fundamental cell biological perspective and in the context of disease diagnostics. In this study, we show that tracking cell shape dynamics during trypsin-induced de-adhesion can serve as a simple but extremely useful tool for probing the contractility of adherent cells. When treated with trypsin, both SW13−/− epithelial cells and U373 MG glioma cells exhibit a brief lag period followed by a concerted retraction to a rounded shape. The time–response of the normalized cell area can be fit to a sigmoidal curve with two characteristic time constants that rise and fall when cells are treated with blebbistatin and nocodazole, respectively. These differences can be attributed to actomyosin-based cytoskeletal remodeling, as evidenced by the prominent buildup of stress fibers in nocodazole-treated SW13−/− cells, which are also two-fold stiffer than untreated cells. Similar results observed in U373 MG cells highlights the direct association between cell stiffness and the de-adhesion response. Faster de-adhesion is obtained with higher trypsin concentration, with nocodazole treatment further expediting the process and blebbistatin treatment blunting the response. A simple finite element model confirms that faster contraction is achieved with increased stiffness

Imaging aspects of cardiovascular disease at the cell and molecular level

Cell and molecular imaging has a long and distinguished history. Erythrocytes were visualized microscopically by van Leeuwenhoek in 1674, and microscope technology has evolved mightily since the first single-lens instruments, and now incorporates many types that do not use photons of light for image formation. The combination of these instruments with preparations stained with histochemical and immunohistochemical markers has revolutionized imaging by allowing the biochemical identification of components at subcellular resolution. The field of cardiovascular disease has benefited greatly from these advances for the characterization of disease etiologies. In this review, we will highlight and summarize the use of microscopy imaging systems, including light microscopy, electron microscopy, confocal scanning laser microscopy, laser scanning cytometry, laser microdissection, and atomic force microscopy in conjunction with a variety of histochemical techniques in studies aimed at understanding mechanisms underlying cardiovascular diseases at the cell and molecular level