Viral mechanisms of immune evasion

During the millions of years they have coexisted with their hosts, viruses have learned how to manipulate host immune control mechanisms. Viral gene functions provide an overview of many relevant principles in cell biology and immunology. Our knowledge of viral gene functions must be integrated into virus-host interaction networks to understand viral pathogenesis, and could lead to new anti-viral strategies and the ability to exploit viral functions as tools in medicine.     

Viral mechanisms of immune evasion

During the millions of years they have coexisted with their hosts, viruses have learned how to manipulate host immune control mechanisms. Viral gene functions provide an overview of many relevant principles in cell biology and immunology. Our knowledge of viral gene functions must be integrated into virus-host interaction networks to understand viral pathogenesis, and could lead to new anti-viral strategies and the ability to exploit viral functions as tools in medicine.     

Vaccinia Reporter Viruses for Quantifying Viral Function at All Stages of Gene Expression

Poxviruses are a family of double stranded DNA viruses that include active human pathogens such as monkeypox, molluscum contagiousum, and Contagalo virus. The family also includes the smallpox virus, Variola. Due to the complexity of poxvirus replication, many questions still remain regarding their gene expression strategy. In this article we describe the conceptualization and usage of recombinant vaccinia viruses that enable real-time measurement of single and multiple stages of viral gene expression in a high-throughput format. This is enabled through the use of spectrally distinct fluorescent proteins as reporters for each of three stages of viral replication. These viruses provide a high signal-to-noise ratio while retaining stage specific expression patterns, enabling plate-based assays and microscopic observations of virus propagation and replication. These tools have uses for antiviral discovery, studies of the virus-host interaction, and evolutionary biology.     

Environmental bacteriophage-host interactions: factors contribution to natural transduction

Over the past two decades the potential for the exchange of bacterial genes in natural environments through transduction (bacteriophage-mediated gene transfer) has been well established. Studies carried out by various laboratories throughout the world have demonstrated that both chromosomal and plasmid DNA can be successfully transduced in natural environments ranging from sewer plants to rivers and lakes. Transduction has been shown to take place in the gills of oysters and the kidneys of mice. Model studies have demonstrated the ability of transduction to maintain genetic material in bacterial gene pools that would otherwise be lost because of negative fitness. Thus, transduction may affect the course of bacterial evolution. Identification of natural transduction has led to the investigation of the dynamics of bacteriophage host interactions in natural aquatic environments and to the exploration of various environmental factors that affect virus-host interactions. Two important environmental factors which affect virus-host interactions are the metabolic state of the host and the exposure of the host to DNA-damaging stresses such as solar UV light. Recent researches on these two areas of virus-host relationships are reviewed.     

Viruses and interactomes in translation

A decade of high-throughput screenings for intraviral and virus-host protein-protein interactions led to the accumulation of data and to the development of theories on laws governing interactome organization for many viruses. We present here a computational analysis of intraviral protein networks (EBV, FLUAV, HCV, HSV-1, KSHV, SARS-CoV, VACV, and VZV) and virus-host protein networks (DENV, EBV, FLUAV, HCV, and VACV) from up-to-date interaction data, using various mathematical approaches. If intraviral networks seem to behave similarly, they are clearly different from the human interactome. Viral proteins target highly central human proteins, which are precisely the Achilles' heel of the human interactome. The intrinsic structural disorder is a distinctive feature of viral hubs in virus-host interactomes. Overlaps between virus-host data sets identify a core of human proteins involved in the cellular response to viral infection and in the viral capacity to hijack the cell machinery for viral replication. Host proteins that are strongly targeted by a virus seem to be particularly attractive for other viruses. Such protein-protein interaction networks and their analysis represent a powerful resource from a therapeutic perspective.     

Functional similarity analysis of human virus-encoded miRNAs

miRNAs are a class of small RNAs that regulate gene expression via RNA silencing machinery. Some viruses also encode miRNAs, contributing to the complex virus-host interactions. A better understanding of viral miRNA functions would be useful in designing new preventive strategies for treating diseases induced by viruses. To meet the challenge for how viruses module host gene expression by their encoded miRNAs, we measured the functional similarities among human viral miRNAs by using a method we reported previously. Higher order functions regulated by viral miRNAs were also identified by KEGG pathway analysis on their targets. Our study demonstrated the biological processes involved in virus-host interactions via viral miRNAs. Phylogenetic analysis suggested that viral miRNAs have distinct evolution rates compared with their corresponding genome.     

The Arabidopsis Information Resource (TAIR): a model organism database providing a centralized,curated gateway to Arabidopsis biology,research materials and community

Arabidopsis thaliana is the most widely-studied plant today. The concerted efforts of over 11 000 researchers and 4000 organizations around the world are generating a rich diversity and quantity of information and materials. This information is made available through a comprehensive on-line resource called the Arabidopsis Information Resource (TAIR) (http://arabidopsis.org), which is accessible via commonly used web browsers and can be searched and downloaded in a number of ways. In the last two years, efforts have been focused on increasing data content and diversity, functionally annotating genes and gene products with controlled vocabularies, and improving data retrieval, analysis and visualization tools. New information include sequence polymorphisms including alleles, germplasms and phenotypes, Gene Ontology annotations, gene families, protein information, metabolic pathways, gene expression data from microarray experiments and seed and DNA stocks. New data visualization and analysis tools include SeqViewer, which interactively displays the genome from the whole chromosome down to 10 kb of nucleotide sequence and AraCyc, a metabolic pathway database and map tool that allows overlaying expression data onto the pathway diagrams. Finally, we have recently incorporated seed and DNA stock information from the Arabidopsis Biological Resource Center (ABRC) and implemented a shopping-cart style on-line ordering system.     

Poxvirus Proteomics and Virus-Host Protein Interactions

Summary: Studies of the functional proteins encoded by the poxvirus genome provide information about the composition of the virus as well as individual virus-virus protein and virus-host protein interactions, which provides insight into viral pathogenesis and drug discovery. Widely used proteomic techniques to identify and characterize specific protein-protein interactions include yeast two-hybrid studies and coimmunoprecipitations. Recently, various mass spectrometry techniques have been employed to identify viral protein components of larger complexes. These methods, combined with structural studies, can provide new information about the putative functions of viral proteins as well as insights into virus-host interaction dynamics. For viral proteins of unknown function, identification of either viral or host binding partners provides clues about their putative function. In this review, we discuss poxvirus proteomics, including the use of proteomic methodologies to identify viral components and virus-host protein interactions. High-throughput global protein expression studies using protein chip technology as well as new methods for validating putative protein-protein interactions are also discussed.     

Viral proteomics.

Viruses have long been studied not only for their pathology and associated disease but also as model systems for molecular processes and as tools for identifying important cellular regulatory proteins and pathways. Recent advances in mass spectrometry methods coupled with the development of proteomic approaches have greatly facilitated the detection of virion components, protein interactions in infected cells, and virally induced changes in the cellular proteome, resulting in a more comprehensive understanding of viral infection. In addition, a rapidly increasing number of high-resolution structures for viral proteins have provided valuable information on the mechanism of action of these proteins as well as aided in the design and understanding of specific inhibitors that could be used in antiviral therapies. In this paper, we discuss proteomic studies conducted on all eukaryotic viruses and bacteriophages, covering virion composition, viral protein structures, virus-virus and virus-host protein interactions, and changes in the cellular proteome upon viral infection.     

Performance comparison and evaluation of software tools for microRNA deep-sequencing data analysis

With the development of next-generation sequencing (NGS) techniques, many software tools have emerged for the discovery of novel microRNAs (miRNAs) and for analyzing the miRNAs expression profiles. An overall evaluation of these diverse software tools is lacking. In this study, we evaluated eight software tools based on their common feature and key algorithms. Three deep-sequencing data sets were collected from different species and used to assess the computational time, sensitivity and accuracy of detecting known miRNAs as well as their capacity for predicting novel miRNAs. Our results provide useful information for researchers to facilitate their selection of the optimal software tools for miRNA analysis depending on their specific requirements, i.e. novel miRNAs discovery or miRNA expression profile analysis of sequencing data sets.     

Individual-based model highlights the importance of trade-offs for virus-host population dynamics and long-term co-existence

Viruses play diverse and important roles in ecosystems. In recent years, trade-offs between host and virus traits have gained increasing attention in viral ecology and evolution. However, microbial organism traits, and viral population parameters in particular, are challenging to monitor. Mathematical and individual-based models are useful tools for predicting virus-host dynamics. We have developed an individual-based evolutionary model to study ecological interactions and evolution between bacteria and viruses, with emphasis on the impacts of trade-offs between competitive and defensive host traits on bacteria-phage population dynamics and trait diversification. Host dynamics are validated with lab results for different initial virus to host ratios (VHR). We show that trade-off based, as opposed to random bacteria-virus interactions, result in biologically plausible evolutionary outcomes, thus highlighting the importance of trade-offs in shaping biodiversity. The effects of nutrient concentration and other environmental and organismal parameters on the virus-host dynamics are also investigated. Despite its simplicity, our model serves as a powerful tool to study bacteria-phage interactions and mechanisms for evolutionary diversification under various environmental conditions.     

Expressed sequence tags and their application for plant research

Expressed Sequence Tags (ESTs) are short, usually unedited sequences obtained by single-pass sequencing of cDNA clones from any cDNA library. Analyzing and comparing ESTs can provide information on gene expression, function and evolution. Large-scale EST sequencing has become an attractive alternative to plant genome sequencing. Currently, plant EST collections comprise over 3.8 million sequences from about 200 species. They have proved to be a valuable tool for gene discovery and plant metabolism analysis. Several plant-specific EST databases have been created which provide access to sequence data and bioinformatics-based tools for data mining. Searching EST collections allows pre-selection of genes for preparing cDNA arrays, targeted to bring maximum information on specialized processes, like stress response, symbiotic nitrogen fixation etc. Also, ESt-based molecular markers such as SNP, SSR, and indels are fast developing tools for breeders and researchers.     

Saccharomyces Genome Database provides tools to survey gene expression and functional analysis data

Upon the completion of the SACCHAROMYCES: cerevisiae genomic sequence in 1996 [Goffeau,A. et al. (1997) NATURE:, 387, 5], several creative and ambitious projects have been initiated to explore the functions of gene products or gene expression on a genome-wide scale. To help researchers take advantage of these projects, the SACCHAROMYCES: Genome Database (SGD) has created two new tools, Function Junction and Expression Connection. Together, the tools form a central resource for querying multiple large-scale analysis projects for data about individual genes. Function Junction provides information from diverse projects that shed light on the role a gene product plays in the cell, while Expression Connection delivers information produced by the ever-increasing number of microarray projects. WWW access to SGD is available at genome-www.stanford. edu/Saccharomyces/.     

DRAGON View: information visualization for annotated microarray data

The DRAGON View information visualization tools aid in the comprehensive analysis of large-scale gene expression data that has been annotated with biologically relevant information through the generation of three types of complementary graphical outputs.