Contemporary Insights into the Biological Mechanisms of .

For a long time, traditional medicine has relied on the use of medicinal plants and herbal products which have served as the basis for numerous pharmaceuticals. (Jacq) R.Br.

Profiling metals in by using inductively coupled plasma mass spectrometry.

() is a natural product that has diverse nutritional and medicinal values. Since the availability of natural becomes limited its authentication and quality control is of high significance. Herein we report on profiling of metals in by using inductively coupled plasma mass spectrometry (ICP-MS).

The Association between Gene-Environment Interactions and Diseases Involving the Human GST Superfamily with SNP Variants.

Exposure to environmental hazards has been associated with diseases in humans. The identification of single nucleotide polymorphisms (SNPs) in human populations exposed to different environmental hazards, is vital for detecting the genetic risks of some important human diseases. Several studies in this field have been conducted on glutathione S-transferases (GSTs), a phase II detoxification superfamily, to investigate its role in the occurrence of diseases.

Cycling Transcriptional Networks Optimize Energy Utilization on a Genome Scale.

Genes expressing circadian RNA rhythms are enriched for metabolic pathways, but the adaptive significance of cyclic gene expression remains unclear. We estimated the genome-wide synthetic and degradative cost of transcription and translation in three organisms and found that the cost of cycling genes is strikingly higher compared to non-cycling genes. Cycling genes are expressed at high levels and constitute the most costly proteins to synthesize in the genome.

FoxP1 orchestration of ASD-relevant signaling pathways in the striatum.

Mutations in the transcription factor Forkhead box p1 (FOXP1) are causative for neurodevelopmental disorders such as autism. However, the function of FOXP1 within the brain remains largely uncharacterized. Here, we identify the gene expression program regulated by FoxP1 in both human neural cells and patient-relevant heterozygous Foxp1 mouse brains.

ChIP-seq and RNA-seq methods to study circadian control of transcription in mammals.

Genome-wide analyses have revolutionized our ability to study the transcriptional regulation of circadian rhythms. The advent of next-generation sequencing methods has facilitated the use of two such technologies, ChIP-seq and RNA-seq. In this chapter, we describe detailed methods and protocols for these two techniques, with emphasis on their usage in circadian rhythm experiments in the mouse liver, a major target organ of the circadian clock system.

C57BL/6N mutation in cytoplasmic FMRP interacting protein 2 regulates cocaine response.

The inbred mouse C57BL/6J is the reference strain for genome sequence and for most behavioral and physiological phenotypes. However, the International Knockout Mouse Consortium uses an embryonic stem cell line derived from a related C57BL/6N substrain. We found that C57BL/6N has a lower acute and sensitized response to cocaine and methamphetamine.

An immunological fingerprint differentiates muscular lymphatics from arteries and veins.

The principal function of the lymphatic system is to transport lymph from the interstitium to the nodes and then from the nodes to the blood. In doing so lymphatics play important roles in fluid homeostasis, macromolecular/antigen transport and immune cell trafficking. To better understand the genes that contribute to their unique physiology, we compared the transcriptional profile of muscular lymphatics (prenodal mesenteric microlymphatics and large, postnodal thoracic duct) to axillary and mesenteric arteries and veins isolated from rats.

Transcriptional architecture and chromatin landscape of the core circadian clock in mammals.

The mammalian circadian clock involves a transcriptional feed back loop in which CLOCK and BMAL1 activate the Period and Cryptochrome genes, which then feedback and repress their own transcription. We have interrogated the transcriptional architecture of the circadian transcriptional regulatory loop on a genome scale in mouse liver and find a stereotyped, time-dependent pattern of transcription factor binding, RNA polymerase II (RNAPII) recruitment, RNA expression, and chromatin states. We find that the circadian transcriptional cycle of the clock consists of three distinct phases: a poised state, a coordinated de novo transcriptional activation state, and a repressed state.

UNAC tetraloops: to what extent do they mimic GNRA tetraloops?

The structures of four small RNAs each containing a different version of the UNAC loop were determined in solution using NMR spectroscopy and restrained molecular dynamics. The UMAC tetraloops (where M is A or C) exhibited a typical GNRA fold including at least one hydrogen bond between the first U and fourth C. In contrast, UGAC and UUAC tetraloops have a different orientation of the first and fourth residues, such that they do not closely mimic the GNRA fold.

Discovering disease-specific biomarker genes for cancer diagnosis and prognosis.

The large amounts of microarray data provide us a great opportunity to identify gene expression profiles (GEPs) in different tissues or disease states. Disease-specific biomarker genes likely share GEPs that are distinct in disease samples as compared with normal samples. The similarity of the GEPs may be evaluated by Pearson Correlation Coefficient (PCC) and the distinctness of GEPs may be assessed by Kolmogorov-Smirnov distance (KSD).

Classification of genes and putative biomarker identification using distribution metrics on expression profiles.

Background: Identification of genes with switch-like properties will facilitate discovery of regulatory mechanisms that underlie these properties, and will provide knowledge for the appropriate application of Boolean networks in gene regulatory models. As switch-like behavior is likely associated with tissue-specific expression, these gene products are expected to be plausible candidates as tissue-specific biomarkers.

Methodology/principal Findings: In a systematic classification of genes and search for biomarkers, gene expression profiles (GEPs) of more than 16,000 genes from 2,145 mouse array samples were analyzed.

Cluster analysis of hydration waters around the active sites of bacterial alanine racemase using a 2-ns MD simulation.

Structural data produced by a 2-ns molecular dynamics (MD) simulation on Geobacillus alanine racemase (AlaR; PDB: 1SFT) was used to study hydration around the two AlaR active sites. AlaR is a crucial enzyme for bacterial cell wall biosynthesis. It has been shown previously that the potency of an inhibitor can be increased by incorporating a functional group or atom that displaces hydration sites close to the substrate binding pocket of its target enzyme.

Biomarker discovery and visualization in gene expression data with efficient generalized matrix approximations.

In most real-world gene expression data sets, there are often multiple sample classes with ordinals, which are categorized into the normal or diseased type. The traditional feature or attribute selection methods consider multiple classes equally without paying attention to the up/down regulation across the normal and diseased types of classes, while the specific gene selection methods particularly consider the differential expressions across the normal and diseased, but ignore the existence of multiple classes. In this paper, to improve the biomarker discovery, we propose to make the best use of these two aspects: the differential expressions (that can be viewed as the domain knowledge of gene expression data) and the multiple classes (that can be viewed as a kind of data set characteristic).

Dynamical systems for discovering protein complexes and functional modules from biological networks.

Recent advances in high throughput experiments and annotations via published literature have provided a wealth of interaction maps of several biomolecular networks, including metabolic, protein-protein, and protein-DNA interaction networks. The architecture of these molecular networks reveals important principles of cellular organization and molecular functions. Analyzing such networks, i.

Efficient generalized matrix approximations for biomarker discovery and visualization in gene expression data.

In most real-life gene expression data sets, there are often multiple sample classes with ordinals, which are categorized into the normal or diseased type. The traditional feature or attribute selection methods consider multiple classes equally without paying attention to the up/down regulation across the normal and diseased types of classes, while the specific gene selection methods particularly consider the differential expressions across the normal and diseased, but ignore the existence of multiple classes. In this paper, for improving the biomarker discovery, we propose to make the best use of these two aspects: the differential expressions (that can be viewed as the domain knowledge of gene expression data) and the multiple classes (that can be viewed as a kind of data set characteristic).

Modeling nonlinearity in dilution design microarray data.

Motivation: Dilution design (Mixed tissue RNA) has been utilized by some researchers to evaluate and assess the performance of multiple microarray platforms. Current microarray data analysis approaches assume that the quantified signal intensities are linearly related to the expression of the corresponding genes in the sample. However, there are sources of nonlinearity in microarray expression measurements.

NMR structure and Mg2+ binding of an RNA segment that underlies the L7/L12 stalk in the E.coli 50S ribosomal subunit.

Helix 42 of Domain II of Escherichia coli 23S ribosomal RNA underlies the L7/L12 stalk in the ribosome and may be significant in positioning this feature relative to the rest of the 50S ribosomal subunit. Unlike the Haloarcula marismortui and Deinococcus radiodurans examples, the lower portion of helix 42 in E.coli contains two consecutive G*A oppositions with both adenines on the same side of the stem.

The application of cluster analysis in the intercomparison of loop structures in RNA.

We have developed a computational approach for the comparison and classification of RNA loop structures. Hairpin or interior loops identified in atomic resolution RNA structures were intercompared by conformational matching. The root-mean-square deviation (RMSD) values between all pairs of RNA fragments of interest, even if from different molecules, are calculated.

The association between a negatively charged ligand and the electronegative binding pocket of its receptor.

Many examples exist of charged amino acids that play a role in attracting or holding a charged ligand toward or inside an oppositely charged binding pocket of the protein. For example, the enzymes superoxide dismutase, triose-phosphate isomerase, and acetylcholinesterase can steer ligands toward their oppositely charged binding pockets or gorges. Interestingly, in our Brownian dynamics simulations of a phosphate-binding protein, we discovered that negatively charged phosphate (HPO(2-)(4)) could make its way into the negatively charged binding pocket.