Immunohistochemical analysis of brain lesions using S100B and glial fibrillary acidic protein antibodies in arundic acid- (ONO-2506) treated stroke-prone spontaneously hypertensive rats

Stroke-prone spontaneously hypertensive rats (SHRSP) used as a model of essential hypertension cause a high incidence of brain stroke on the course of hypertension. Incidences and sizes of brain lesions are known to relate to the astrocyte activities. Therefore, relation between brain damage and the expression profile of the astrocytes was investigated with morphometric and immunohistochemical analyses using astrocyte marker antibodies of S100B and glial fibrillary acidic protein (GFAP) with or without arundic acid administration, a suppressor on the activation of astrocytes. Arundic acid extended the average life span of SHRSP. An increase in brain tissue weight was inhibited concomitant with a lower rate of gliosis/hemosiderin deposit/scarring in brain lesions. S100B- or GFAP-positive dot and filamentous structures were decreased in arundic acid-treated SHRSP, and this effect was most pronounced in the cerebral cortex, white matter, and pons, and less so in the hippocampus, diencephalon, midbrain, and cerebellum. Blood pressure decreased after administration of arundic acid in the high-dose group (100 mg/kg/day arundic acid), but not in the low-dose group (30 mg/kg/day). These data indicate that arundic acid can prevent hypertension-induced stroke, and may inhibit the enlargement of the stroke lesion by preventing the inflammatory changes caused by overproduction of the S100B protein in the astrocytes

Global Analysis of Genetic, Epigenetic and Transcriptional Polymorphisms in Arabidopsis thaliana Using Whole Genome Tiling Arrays

Whole genome tiling arrays provide a high resolution platform for profiling of genetic, epigenetic, and gene expression polymorphisms. In this study we surveyed natural genomic variation in cytosine methylation among Arabidopsis thaliana wild accessions Columbia (Col) and Vancouver (Van) by comparing hybridization intensity difference between genomic DNA digested with either methylation-sensitive (HpaII) or -insensitive (MspI) restriction enzyme. Single Feature Polymorphisms (SFPs) were assayed on a full set of 1,683,620 unique features of Arabidopsis Tiling Array 1.0F (Affymetrix), while constitutive and polymorphic CG methylation were assayed on a subset of 54,519 features, which contain a 5′CCGG3′ restriction site. 138,552 SFPs (1% FDR) were identified across enzyme treatments, which preferentially accumulated in pericentromeric regions. Our study also demonstrates that at least 8% of all analyzed CCGG sites were constitutively methylated across the two strains, while about 10% of all analyzed CCGG sites were differentially methylated between the two strains. Within euchromatin arms, both constitutive and polymorphic CG methylation accumulated in central regions of genes but under-represented toward the 5′ and 3′ ends of the coding sequences. Nevertheless, polymorphic methylation occurred much more frequently in gene ends than constitutive methylation. Inheritance of methylation polymorphisms in reciprocal F1 hybrids was predominantly additive, with F1 plants generally showing levels of methylation intermediate between the parents. By comparing gene expression profiles, using matched tissue samples, we found that magnitude of methylation polymorphism immediately upstream or downstream of the gene was inversely correlated with the degree of expression variation for that gene. In contrast, methylation polymorphism within genic region showed weak positive correlation with expression variation. Our results demonstrated extensive genetic and epigenetic polymorphisms between Arabidopsis accessions and suggested a possible relationship between natural CG methylation variation and gene expression variation

Computational Methods for Protein Identification from Mass Spectrometry Data

Protein identification using mass spectrometry is an indispensable computational tool in the life sciences. A dramatic increase in the use of proteomic strategies to understand the biology of living systems generates an ongoing need for more effective, efficient, and accurate computational methods for protein identification. A wide range of computational methods, each with various implementations, are available to complement different proteomic approaches. A solid knowledge of the range of algorithms available and, more critically, the accuracy and effectiveness of these techniques is essential to ensure as many of the proteins as possible, within any particular experiment, are correctly identified. Here, we undertake a systematic review of the currently available methods and algorithms for interpreting, managing, and analyzing biological data associated with protein identification. We summarize the advances in computational solutions as they have responded to corresponding advances in mass spectrometry hardware. The evolution of scoring algorithms and metrics for automated protein identification are also discussed with a focus on the relative performance of different techniques. We also consider the relative advantages and limitations of different techniques in particular biological contexts. Finally, we present our perspective on future developments in the area of computational protein identification by considering the most recent literature on new and promising approaches to the problem as well as identifying areas yet to be explored and the potential application of methods from other areas of computational biology

Stable transmission of reversible modifications: maintenance of epigenetic information through the cell cycle

Even though every cell in a multicellular organism contains the same genes, the differing spatiotemporal expression of these genes determines the eventual phenotype of a cell. This means that each cell type contains a specific epigenetic program that needs to be replicated through cell divisions, along with the genome, in order to maintain cell identity. The stable inheritance of these programs throughout the cell cycle relies on several epigenetic mechanisms. In this review, DNA methylation and histone methylation by specific histone lysine methyltransferases (KMT) and the Polycomb/Trithorax proteins are considered as the primary mediators of epigenetic inheritance. In addition, non-coding RNAs and nuclear organization are implicated in the stable transfer of epigenetic information. Although most epigenetic modifications are reversible in nature, they can be stably maintained by self-recruitment of modifying protein complexes or maintenance of these complexes or structures through the cell cycle