Publications

BACKGROUND & AIMS: The precise mechanisms by which IFN exerts its antiviral effect against HCV have not yet been elucidated. We sought to identify host genes that mediate the antiviral effect of IFN-α by conducting a whole-genome siRNA library screen.

METHODS: High throughput screening was performed using an HCV genotype 1b replicon, pRep-Feo. Those pools with replicate robust Z scores ≥2.0 entered secondary validation in full-length OR6 replicon cells. Huh7.5.1 cells infected with JFH1 were then used to validate the rescue efficacy of selected genes for HCV replication under IFN-α treatment.

RESULTS: We identified and confirmed 93 human genes involved in the IFN-α anti-HCV effect using a whole-genome siRNA library. Gene ontology analysis revealed that mRNA processing (23 genes, p=2.756e-22), translation initiation (nine genes, p=2.42e-6), and IFN signaling (five genes, p=1.00e-3) were the most enriched functional groups. Nine genes were components of U4/U6.U5 tri-snRNP. We confirmed that silencing squamous cell carcinoma antigen recognized by T cells (SART1), a specific factor of tri-snRNP, abrogates IFN-α's suppressive effects against HCV in both replicon cells and JFH1 infectious cells. We further found that SART1 was not IFN-α inducible, and its anti-HCV effector in the JFH1 infectious model was through regulation of interferon stimulated genes (ISGs) with or without IFN-α.

CONCLUSIONS: We identified 93 genes that mediate the anti-HCV effect of IFN-α through genome-wide siRNA screening; 23 and nine genes were involved in mRNA processing and translation initiation, respectively. These findings reveal an unexpected role for mRNA processing in generation of the antiviral state, and suggest a new avenue for therapeutic development in HCV.

Little is known about the mechanisms of persistent airflow obstruction that result from chronic occupational endotoxin exposure. We sought to analyze the inflammatory response underlying persistent airflow obstruction as a result of chronic occupational endotoxin exposure. We developed a murine model of daily inhaled endotoxin for periods of 5 days to 8 weeks. We analyzed physiologic lung dysfunction, lung histology, bronchoalveolar lavage fluid and total lung homogenate inflammatory cell and cytokine profiles, and pulmonary gene expression profiles. We observed an increase in airway hyperresponsiveness as a result of chronic endotoxin exposure. After 8 weeks, the mice exhibited an increase in bronchoalveolar lavage and lung neutrophils that correlated with an increase in proinflammatory cytokines. Detailed analyses of inflammatory cell subsets revealed an expansion of dendritic cells (DCs), and in particular, proinflammatory DCs, with a reduced percentage of macrophages. Gene expression profiling revealed the up-regulation of a panel of genes that was consistent with DC recruitment, and lung histology revealed an accumulation of DCs in inflammatory aggregates around the airways in 8-week-exposed animals. Repeated, low-dose LPS inhalation, which mirrors occupational exposure, resulted in airway hyperresponsiveness, associated with a failure to resolve the proinflammatory response, an inverted macrophage to DC ratio, and a significant rise in the inflammatory DC population. These findings point to a novel underlying mechanism of airflow obstruction as a result of occupational LPS exposure, and suggest molecular and cellular targets for therapeutic development.

The endoplasmic reticulum (ER) is the main site of protein and lipid synthesis, membrane biogenesis, xenobiotic detoxification and cellular calcium storage, and perturbation of ER homeostasis leads to stress and the activation of the unfolded protein response. Chronic activation of ER stress has been shown to have an important role in the development of insulin resistance and diabetes in obesity. However, the mechanisms that lead to chronic ER stress in a metabolic context in general, and in obesity in particular, are not understood. Here we comparatively examined the proteomic and lipidomic landscape of hepatic ER purified from lean and obese mice to explore the mechanisms of chronic ER stress in obesity. We found suppression of protein but stimulation of lipid synthesis in the obese ER without significant alterations in chaperone content. Alterations in ER fatty acid and lipid composition result in the inhibition of sarco/endoplasmic reticulum calcium ATPase (SERCA) activity and ER stress. Correcting the obesity-induced alteration of ER phospholipid composition or hepatic Serca overexpression in vivo both reduced chronic ER stress and improved glucose homeostasis. Hence, we established that abnormal lipid and calcium metabolism are important contributors to hepatic ER stress in obesity.

A simple biochemical method to isolate mRNAs pulled down with a transfected, biotinylated microRNA was used to identify direct target genes of miR-34a, a tumor suppressor gene. The method reidentified most of the known miR-34a regulated genes expressed in K562 and HCT116 cancer cell lines. Transcripts for 982 genes were enriched in the pull-down with miR-34a in both cell lines. Despite this large number, validation experiments suggested that  90% of the genes identified in both cell lines can be directly regulated by miR-34a. Thus miR-34a is capable of regulating hundreds of genes. The transcripts pulled down with miR-34a were highly enriched for their roles in growth factor signaling and cell cycle progression. These genes form a dense network of interacting gene products that regulate multiple signal transduction pathways that orchestrate the proliferative response to external growth stimuli. Multiple candidate miR-34a-regulated genes participate in RAS-RAF-MAPK signaling. Ectopic miR-34a expression reduced basal ERK and AKT phosphorylation and enhanced sensitivity to serum growth factor withdrawal, while cells genetically deficient in miR-34a were less sensitive. Fourteen new direct targets of miR-34a were experimentally validated, including genes that participate in growth factor signaling (ARAF and PIK3R2) as well as genes that regulate cell cycle progression at various phases of the cell cycle (cyclins D3 and G2, MCM2 and MCM5, PLK1 and SMAD4). Thus miR-34a tempers the proliferative and pro-survival effect of growth factor stimulation by interfering with growth factor signal transduction and downstream pathways required for cell division.

Combinatorial interactions among transcription factors are critical to directing tissue-specific gene expression. To build a global atlas of these combinations, we have screened for physical interactions among the majority of human and mouse DNA-binding transcription factors (TFs). The complete networks contain 762 human and 877 mouse interactions. Analysis of the networks reveals that highly connected TFs are broadly expressed across tissues, and that roughly half of the measured interactions are conserved between mouse and human. The data highlight the importance of TF combinations for determining cell fate, and they lead to the identification of a SMAD3/FLI1 complex expressed during development of immunity. The availability of large TF combinatorial networks in both human and mouse will provide many opportunities to study gene regulation, tissue differentiation, and mammalian evolution.

By combining genome-wide association data from 8,130 individuals with type 2 diabetes (T2D) and 38,987 controls of European descent and following up previously unidentified meta-analysis signals in a further 34,412 cases and 59,925 controls, we identified 12 new T2D association signals with combined P<5x10(-8). These include a second independent signal at the KCNQ1 locus; the first report, to our knowledge, of an X-chromosomal association (near DUSP9); and a further instance of overlap between loci implicated in monogenic and multifactorial forms of diabetes (at HNF1A). The identified loci affect both beta-cell function and insulin action, and, overall, T2D association signals show evidence of enrichment for genes involved in cell cycle regulation. We also show that a high proportion of T2D susceptibility loci harbor independent association signals influencing apparently unrelated complex traits.

UNLABELLED: The first open source software suite for experimentalists and curators that (i) assists in the annotation and local management of experimental metadata from high-throughput studies employing one or a combination of omics and other technologies; (ii) empowers users to uptake community-defined checklists and ontologies; and (iii) facilitates submission to international public repositories.

AVAILABILITY AND IMPLEMENTATION: Software, documentation, case studies and implementations at http://www.isa-tools.org.

The Alternative Splicing and Transcript Diversity database (ASTD) gives access to a vast collection of alternative transcripts that integrate transcription initiation, polyadenylation and splicing variant data. Alternative transcripts are derived from the mapping of transcribed sequences to the complete human, mouse and rat genomes using an extension of the computational pipeline developed for the ASD (Alternative Splicing Database) and ATD (Alternative Transcript Diversity) databases, which are now superseded by ASTD. For the human genome, ASTD identifies splicing variants, transcription initiation variants and polyadenylation variants in 68%, 68% and 62% of the gene set, respectively, consistent with current estimates for transcription variation. Users can access ASTD through a variety of browsing and query tools, including expression state-based queries for the identification of tissue-specific isoforms. Participating laboratories have experimentally validated a subset of ASTD-predicted alternative splice forms and alternative polyadenylation forms that were not previously reported. The ASTD database can be accessed at http://www.ebi.ac.uk/astd.

Using deep sequencing (deepCAGE), the FANTOM4 study measured the genome-wide dynamics of transcription-start-site usage in the human monocytic cell line THP-1 throughout a time course of growth arrest and differentiation. Modeling the expression dynamics in terms of predicted cis-regulatory sites, we identified the key transcription regulators, their time-dependent activities and target genes. Systematic siRNA knockdown of 52 transcription factors confirmed the roles of individual factors in the regulatory network. Our results indicate that cellular states are constrained by complex networks involving both positive and negative regulatory interactions among substantial numbers of transcription factors and that no single transcription factor is both necessary and sufficient to drive the differentiation process.