CiteULike: jyuh Grove

Effect of cell polarization on hepatitis C virus viral entry.

Christopher J Mee — 2007-11-01T09:14:23-00:00

J Virol (24 October 2007)

The primary reservoir for Hepatitis C virus (HCV) replication in vivo is believed to be hepatocytes within the liver. Three host cell molecules have been reported to be important entry factors for receptors for HCV: the tetraspanin CD81, scavenger receptor BI (SR-BI) and the tight junction (TJ) protein Claudin-1 (CLDN1). The recent discovery of a TJ protein as a critical co-receptor highlighted the importance of studying the effect(s) of TJ formation and cell polarization on HCV entry. The colorectal adenocarcinoma Caco-2 cell line forms polarized monolayers containing functional TJs and was found to express CD81, SR-BI and CLDN1 proteins. Viral receptor expression levels increased upon polarization and CLDN1 relocalized from the apical pole of the lateral cell membrane to the lateral cell-cell junction and basolateral domains. In contrast, expression and localization of the TJ proteins ZO-1 and Occludin-1 were unchanged upon polarization. HCV infected polarized and nonpolarized Caco-2 cells to comparable levels and entry was neutralized by anti-E2 monoclonal antibodies, demonstrating glycoprotein-dependent entry. HCV pseudoparticle infection and recombinant HCV E1E2 glycoprotein interaction with polarized Caco-2 cells occurred predominantly at the apical surface. Disruption of TJs significantly increased HCV entry. These data support a model where TJs provide a physical barrier for viral access to receptors expressed on lateral and basolateral cellular domains.

Scavenger receptor BI and BII expression levels modulate hepatitis C virus infectivity.

J Grove — 2007-10-19T04:21:26-00:00

J Virol, Vol. 81, No. 7. (April 2007), pp. 3162-3169.

Hepatitis C virus (HCV) enters cells via a pH- and clathrin-dependent endocytic pathway. Scavenger receptor BI (SR-BI) and CD81 are important entry factors for HCV internalization into target cells. The SR-BI gene gives rise to at least two mRNA splice variants, SR-BI and SR-BII, which differ in their C termini. SR-BI internalization remains poorly understood, but SR-BII is reported to endocytose via a clathrin-dependent pathway, making it an attractive target for HCV internalization. We demonstrate that HCV soluble E2 can interact with human SR-BI and SR-BII. Increased expression of SR-BI and SR-BII in the Huh-7.5 hepatoma cell line enhanced HCV strain J6/JFH and JFH infectivity, suggesting that endogenous levels of these receptors limit infection. Elevated expression of SR-BI, but not SR-BII, increased the rate of J6/JFH infection, which may reflect altered intracellular trafficking of the splice variants. In human plasma, HCV particles have been reported to be complexed with lipoproteins, suggesting an indirect interaction of the virus with SR-BI and other lipoprotein receptors. Plasma from J6/JFH-infected uPA-SCID mice transplanted with human hepatocytes demonstrates an increased infectivity for SR-BI/II-overexpressing Huh-7.5 cells. Plasma-derived J6/JFH infectivity was inhibited by an anti-E2 monoclonal antibody, suggesting that plasma virus interaction with SR-BI was glycoprotein dependent. Finally, anti-SR-BI antibodies inhibited the infectivity of cell culture- and plasma-derived J6/JFH, suggesting a critical role for SR-BI/II in HCV infection.

Pixel-based analysis of multiple images for the identification of changes: A novel approach applied to unravel proteome patters of 2-D electrophoresis gel images.

Ellen Mosleth Færgestad — 2007-09-23T04:08:45-00:00

Proteomics (28 August 2007)

A novel approach for revealing patterns of proteome variation among series of 2-DE gel images is presented. The approach utilises image alignment to ensure that each pixel represents the same information across all gels. Gel images are normalised, and background corrected, followed by unfolding of the images to 1-D pixel vectors and analysing pixel vectors by multivariate data modelling. Information resulting from the data analysis is refolded back to the image domain for visualisation and interpretation. The method is rapid and suitable for automatic routines applied after the gel alignment. The approach is compared with spot volume analysis to illustrate how this approach can solve persistent problems like mismatch of protein spots, erroneous missing values and failure to detect variation in overlapping proteins. The method may also detect variation in the border area of saturated proteins. The approach is given the name pixel-based analysis of multiple images for the identification of changes (PMC). The method can be used for multiple images in general. Effects of pretreatment of the images are discussed.

Multivariate analysis of 2-DE protein patterns--practical approaches.

S Jacobsen — 2007-07-11T07:01:14-00:00

Electrophoresis, Vol. 28, No. 8. (April 2007), pp. 1289-1299.

Practical approaches to the use of multivariate data analysis of 2-DE protein patterns are demonstrated by three independent strategies for the image analysis and the multivariate analysis on the same set of 2-DE data. Four wheat varieties were selected on the basis of their baking quality. Two of the varieties were of strong baking quality and hard wheat kernel and two were of weak baking quality and soft kernel. Gliadins at different stages of grain development were analyzed by the application of multivariate data analysis on images of 2-DEs. Patterns related to the wheat varieties, harvest times and quality were detected on images of 2-DE protein patterns for all the three strategies. The use of the multivariate methods was evaluated in the alignment and matching procedures of 2-DE gels. All the three strategies were able to discriminate the samples according to quality, harvest time and variety, although different subsets of protein spots were selected. The explorative approach of using multivariate data analysis and variable selection in the analyses of 2-DEs seems to be promising as a fast, reliable and convenient way of screening and transforming many gel images into spot quantities.