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Systems Biology-Based Investigation of Cellular Antiviral Drug Targets Identified by Gene-Trap Insertional Mutagenesis.

PLoS computational biology | 2016

Viruses require host cellular factors for successful replication. A comprehensive systems-level investigation of the virus-host interactome is critical for understanding the roles of host factors with the end goal of discovering new druggable antiviral targets. Gene-trap insertional mutagenesis is a high-throughput forward genetics approach to randomly disrupt (trap) host genes and discover host genes that are essential for viral replication, but not for host cell survival. In this study, we used libraries of randomly mutagenized cells to discover cellular genes that are essential for the replication of 10 distinct cytotoxic mammalian viruses, 1 gram-negative bacterium, and 5 toxins. We herein reported 712 candidate cellular genes, characterizing distinct topological network and evolutionary signatures, and occupying central hubs in the human interactome. Cell cycle phase-specific network analysis showed that host cell cycle programs played critical roles during viral replication (e.g. MYC and TAF4 regulating G0/1 phase). Moreover, the viral perturbation of host cellular networks reflected disease etiology in that host genes (e.g. CTCF, RHOA, and CDKN1B) identified were frequently essential and significantly associated with Mendelian and orphan diseases, or somatic mutations in cancer. Computational drug repositioning framework via incorporating drug-gene signatures from the Connectivity Map into the virus-host interactome identified 110 putative druggable antiviral targets and prioritized several existing drugs (e.g. ajmaline) that may be potential for antiviral indication (e.g. anti-Ebola). In summary, this work provides a powerful methodology with a tight integration of gene-trap insertional mutagenesis testing and systems biology to identify new antiviral targets and drugs for the development of broadly acting and targeted clinical antiviral therapeutics.

Pubmed ID: 27632082 RIS Download

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R Project for Statistical Computing (tool)

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Software environment and programming language for statistical computing and graphics. R is integrated suite of software facilities for data manipulation, calculation and graphical display. Can be extended via packages. Some packages are supplied with the R distribution and more are available through CRAN family.It compiles and runs on wide variety of UNIX platforms, Windows and MacOS.

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RRID:SCR_003032

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RRID:SCR_008117

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RRID:SCR_001672

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RRID:SCR_002110

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RRID:SCR_006714

Publicly available database of the genes, proteins, experimentally-verified interactions and signaling pathways involved in the innate immune response of humans, mice and bovines to microbial infection. The database captures coverage of the innate immunity interactome by integrating known interactions and pathways from major public databases together with manually-curated data into a centralized resource. The database can be mined as a knowledgebase or used with the integrated bioinformatics and visualization tools for the systems level analysis of the innate immune response. Although InnateDB curation focuses on innate immunity-relevant interactions and pathways, it also incorporates detailed annotation on the entire human, mouse and bovine interactomes by integrating data (178,000+ interactions & 3,900+ pathways) from several of the major public interaction and pathway databases. InnateDB also has integrated human, mouse and bovine orthology predictions generated using Ortholgue software. Ortholgue uses a phylogenetic distance-based method to identify possible paralogs in high-throughput orthology predictions. Integrated human and mouse conserved gene order and synteny information has also been determined to provide further support for orthology predictions. InnateDB Capabilities: * View statistics for manually-curated innate immunity relevant molecular interactions. New manually curated interactions are submitted weekly. * Search for genes and proteins of interest. * Search for experimentally-verified molecular interactions by gene/protein name, interaction type, cell type, etc. * Search genes/interactions belonging to 3,900 pathways. * Visualize interactions using an intuitive subcellular localization-based layout in Cerebral. * Upload your own list of genes along with associated gene expression data (from up to 10 experimental conditions) to interactively analyze this data in a molecular interaction network context. Once you have uploaded your data, you will be able to interactively visualize interaction networks with expression data overlaid; carry out Pathway, Gene Ontology and Transcription Factor Binding Site over-representation analyses; construct orthologous interaction networks in other species; and much more. * Access curated interaction data via a dedicated PSICQUIC webservice.

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RRID:SCR_002639

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RRID:SCR_002689

Database and central repository for genetic, genomic, molecular and cellular phenotype data and clinical information about people who have participated in pharmacogenomics research studies. The data includes, but is not limited to, clinical and basic pharmacokinetic and pharmacogenomic research in the cardiovascular, pulmonary, cancer, pathways, metabolic and transporter domains. PharmGKB welcomes submissions of primary data from all research into genes and genetic variation and their effects on drug and disease phenotypes. PharmGKB collects, encodes, and disseminates knowledge about the impact of human genetic variations on drug response. They curate primary genotype and phenotype data, annotate gene variants and gene-drug-disease relationships via literature review, and summarize important PGx genes and drug pathways. PharmGKB is part of the NIH Pharmacogenomics Research Network (PGRN), a nationwide collaborative research consortium. Its aim is to aid researchers in understanding how genetic variation among individuals contributes to differences in reactions to drugs. A selected subset of data from PharmGKB is accessible via a SOAP interface. Downloaded data is available for individual research purposes only. Drugs with pharmacogenomic information in the context of FDA-approved drug labels are cataloged and drugs with mounting pharmacogenomic evidence are listed.

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RRID:SCR_002700

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RRID:SCR_004750

A controlled vocabulary thesaurus that consists of sets of terms naming descriptors in a hierarchical structure that permits searching at various levels of specificity. MeSH, in machine-readable form, is provided at no charge via electronic means. MeSH descriptors are arranged in both an alphabetic and a hierarchical structure. At the most general level of the hierarchical structure are very broad headings such as Anatomy or Mental Disorders. More specific headings are found at more narrow levels of the twelve-level hierarchy, such as Ankle and Conduct Disorder. There are 27,149 descriptors in 2014 MeSH. There are also over 218,000 entry terms that assist in finding the most appropriate MeSH Heading, for example, Vitamin C is an entry term to Ascorbic Acid. In addition to these headings, there are more than 219,000 headings called Supplementary Concept Records (formerly Supplementary Chemical Records) within a separate thesaurus. The MeSH thesaurus is used by NLM for indexing articles from 5,400 of the world''''s leading biomedical journals for the MEDLINE/PubMED database. It is also used for the NLM-produced database that includes cataloging of books, documents, and audiovisuals acquired by the Library. Each bibliographic reference is associated with a set of MeSH terms that describe the content of the item. Similarly, search queries use MeSH vocabulary to find items on a desired topic.

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RRID:SCR_005748

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