The ICP4 binding sites in the herpes simplex virus type 1 glycoprotein D (gD) promoter are not essential for efficient gD transcription during virus infection

Activation of the early and late genes of herpes simplex virus type 1 during infection in tissue culture requires functional immediate-early regulatory protein ICP4. ICP4 is a specific DNA-binding protein which recognizes a variety of DNA sequences, many of which contain the consensus ATCGTC. In general, mutations which impair the ability of ICP4 to bind to DNA also eliminate its ability to activate viral early and late promoters both in transfection assays and in the infected cell. However, the role of ICP4 binding sites in the viral genome is unclear; many early and late promoters do not contain consensus binding sites in their vicinity. The glycoprotein D (gD) gene contains two well-characterized ICP4 binding sites upstream of its promoter and a third downstream of the transcription start site. Multimerization of one of these sites has been shown to increase the response of the gD promoter to ICP4 in transfection assays, while their removal reduces stimulation of the gD promoter by ICP4 in vitro. To assess the role of these binding sites during virus infection, we have constructed a recombinant viral genome which has mutations affecting all three. Comparison of the amounts of gD RNA synthesized by the recombinant and wild-type viruses indicated that the mutations had little or no effect on the activity of the gD promoter. Therefore, either the sites have no essential role in gD promoter regulation in the presence of all of the herpes simplex virus type 1 IE polypeptides during a normal infection or they can be functionally substituted by other ICP4 binding sites elsewhere in the genome

ICP4-binding sites in the promoter and coding regions of the herpes simplex virus gD gene contribute to activation of in vitro transcription by ICP4

The herpes simplex virus immediate-early gene product ICP4 activates the transcription of viral early and late genes. We characterized the DNA sequence elements of the early glycoprotein D (gD) gene that play a role in the response to ICP4 in vitro. Using gel mobility shift assays and DNase I footprinting, we identified three ICP4-binding sites, two 5' to the mRNA start site and a third within the coding region. Site II, which gave a footprint between nucleotides -75 and -111 relative to the RNA start site, was previously identified by Faber and Wilcox and contained the reported consensus ICP4-binding site. Site III, which was located between nucleotides +122 and +163, was very similar to the site II sequence, including a core consensus binding sequence, TCGTC. The site I sequence (nucleotides -308 to -282), however, did not share significant homology with either site II or site III. In vitro transcription experiments from mutant constructs of the gD promoter indicated that all three ICP4-binding sites contribute to the stimulation of transcription by ICP4. DNase I footprinting of the gD promoter with uninfected nuclear extracts of HeLa cells showed protection of two very G-rich sequences between nucleotides -33 and -75. We propose that optimal transcription of the gD gene depends on the interaction of ICP4 with multiple binding sites across the gene and cellular factors that recognize specific sequence elements in the promoter

Multiscale Active Contours

Abstract. We propose a new multiscale image segmentation model, based on the active contour/snake model and the Polyakov action. The concept of scale, general issue in physics and signal processing, is introduced in the active contour model, which is a well-known image segmentation model that consists of evolving a contour in images toward the boundaries of objects. The Polyakov action, introduced in image processing by Sochen-Kimmel-Malladi in Sochen et al. (1998), provides an efficient mathematical framework to define a multiscale segmentation model because it generalizes the concept of harmonic maps embedded in higher-dimensional Riemannian manifolds such as multiscale images. Our multiscale segmentation model, unlike classical multiscale segmentations which work scale by scale to speed up the segmentation process, uses all scales simultaneously, i.e. the whole scale space, to introduce the geometry of multiscale images in the segmentation process. The extracted multiscale structures will be useful to efficiently improve the robustness and the performance of standard shape analysis techniques such as shape recognition and shape registration. Another advantage of our method is to use not only the Gaussian scale space but also many other multiscale spaces such as the Perona-Malik scale space, the curvature scale space or the Beltrami scale space. Finally, this multiscale segmentation technique is coupled with a multiscale edge detecting function based on the gradient vector flow model, which is able to extract convex and concave object boundaries independent of the initial condition. We apply our multiscale segmentation model on a synthetic image and a medical image