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1.  Discovery of Insect and Human Dengue Virus Host Factors 
Nature  2009;458(7241):1047-1050.
Dengue fever (DF) is the most frequent arthropod-borne viral disease of humans, with almost half of the world's population at risk of infection1. The high prevalence, lack of an effective vaccine, and absence of specific treatment conspire to make DF a global public health threat1, 2. Given their compact genomes, dengue viruses (DENV 1-4) and other flaviviruses likely require an extensive number of host factors; however, only a limited number of human, and an even smaller number of insect host factors have been identified3-10. To discover insect host factors required for DENV-2 propagation, we carried out a genome-wide RNA interference screen in Drosophila melanogaster cells using a well-established 22,632 dsRNA library. This screen identified 116 candidate dengue virus host factors (DVHFs) (Supplementary Fig. 1). While some were previously associated with flaviviruses (e.g., V-ATPases and alpha-glucosidases)3-5, 7, 9, 10, most DVHFs were newly implicated in DENV propagation. The dipteran DVHFs had eighty-two readily recognizable human homologues and, using a targeted siRNA screen, we showed that forty-two of these are human DVHFs. This indicates remarkable conservation of required factors between dipteran and human hosts. This work suggests novel approaches to control infection in the insect vector and the mammalian host.
PMCID: PMC3462662  PMID: 19396146
2.  G Protein-Coupled Receptor Kinase 2 Promotes Flaviviridae Entry and Replication 
Flaviviruses cause a wide range of severe diseases ranging from encephalitis to hemorrhagic fever. Discovery of host factors that regulate the fate of flaviviruses in infected cells could provide insight into the molecular mechanisms of infection and therefore facilitate the development of anti-flaviviral drugs. We performed genome-scale siRNA screens to discover human host factors required for yellow fever virus (YFV) propagation. Using a 2×2 siRNA pool screening format and a duplicate of the screen, we identified a high confidence list of YFV host factors. To find commonalities between flaviviruses, these candidates were compared to host factors previously identified for West Nile virus (WNV) and dengue virus (DENV). This comparison highlighted a potential requirement for the G protein-coupled receptor kinase family, GRKs, for flaviviral infection. The YFV host candidate GRK2 (also known as ADRBK1) was validated both in siRNA-mediated knockdown HuH-7 cells and in GRK−/− mouse embryonic fibroblasts. Additionally, we showed that GRK2 was required for efficient propagation of DENV and Hepatitis C virus (HCV) indicating that GRK2 requirement is conserved throughout the Flaviviridae. Finally, we found that GRK2 participates in multiple distinct steps of the flavivirus life cycle by promoting both entry and RNA synthesis. Together, our findings identified GRK2 as a novel regulator of flavivirus infection and suggest that inhibition of GRK2 function may constitute a new approach for treatment of flavivirus associated diseases.
Author Summary
The Flavivirus genus includes several emergent and reemergent viruses, such as dengue and yellow fever viruses, which cause severe diseases in humans for which there is no approved treatment. Flaviviruses are transmitted to humans by arthropods and they rely on scores of vertebrate and invertebrate factors to replicate in these disparate hosts. Identifying the host factors involved in viral propagation is critical to understanding the molecular mechanisms of infection and the development of new therapeutics. To identify human host factors required for yellow fever virus propagation, we completed two genome-scale siRNA screens. Among the candidates discovered were the G protein-coupled receptor kinases GRK2 and GRK4. We focused on the protein GRK2, a kinase first identified for its role in cellular signal transduction. We found that GRK2 was a host factor needed for productive infection by yellow fever, dengue and hepatitis C viruses and was required for both viral entry and efficient replication of the viral genome. GRKs, which are considered druggable, may be used as targets to develop broadspectrum anti-flavivirals.
PMCID: PMC3441407  PMID: 23029581
3.  Factors affecting reproducibility between genome-scale siRNA-based screens 
Journal of biomolecular screening  2010;15(7):735-747.
RNA interference-based screening is a powerful new genomic technology which addresses gene function en masse. To evaluate factors influencing hit list composition and reproducibility, we performed two identically designed small interfering RNA (siRNA)-based, whole genome screens for host factors supporting yellow fever virus infection. These screens represent two separate experiments completed five months apart and allow the direct assessment of the reproducibility of a given siRNA technology when performed in the same environment. Candidate hit lists generated by sum rank, median absolute deviation, z-score, and strictly standardized mean difference were compared within and between whole genome screens. Application of these analysis methodologies within a single screening dataset using a fixed threshold equivalent to a p-value ≤ 0.001 resulted in hit lists ranging from 82 to 1,140 members and highlighted the tremendous impact analysis methodology has on hit list composition. Intra- and inter-screen reproducibility was significantly influenced by the analysis methodology and ranged from 32% to 99%. This study also highlighted the power of testing at least two independent siRNAs for each gene product in primary screens. To facilitate validation we conclude by suggesting methods to reduce false discovery at the primary screening stage.
In this study we present the first comprehensive comparison of multiple analysis strategies, and demonstrate the impact of the analysis methodology on the composition of the “hit list”. Therefore, we propose that the entire dataset derived from functional genome-scale screens, especially if publicly funded, should be made available as is done with data derived from gene expression and genome-wide association studies.
PMCID: PMC3149892  PMID: 20625183
RNA interference; analysis; RNAi screen analysis; siRNA; RNAi; siRNA screening; sum rank; median absolute deviation; strictly standardized mean difference; genome-wide; whole-genome; comparison; overlap; hit list
4.  SplicerAV: a tool for mining microarray expression data for changes in RNA processing 
BMC Bioinformatics  2010;11:108.
Over the past two decades more than fifty thousand unique clinical and biological samples have been assayed using the Affymetrix HG-U133 and HG-U95 GeneChip microarray platforms. This substantial repository has been used extensively to characterize changes in gene expression between biological samples, but has not been previously mined en masse for changes in mRNA processing. We explored the possibility of using HG-U133 microarray data to identify changes in alternative mRNA processing in several available archival datasets.
Data from these and other gene expression microarrays can now be mined for changes in transcript isoform abundance using a program described here, SplicerAV. Using in vivo and in vitro breast cancer microarray datasets, SplicerAV was able to perform both gene and isoform specific expression profiling within the same microarray dataset. Our reanalysis of Affymetrix U133 plus 2.0 data generated by in vitro over-expression of HRAS, E2F3, beta-catenin (CTNNB1), SRC, and MYC identified several hundred oncogene-induced mRNA isoform changes, one of which recognized a previously unknown mechanism of EGFR family activation. Using clinical data, SplicerAV predicted 241 isoform changes between low and high grade breast tumors; with changes enriched among genes coding for guanyl-nucleotide exchange factors, metalloprotease inhibitors, and mRNA processing factors. Isoform changes in 15 genes were associated with aggressive cancer across the three breast cancer datasets.
Using SplicerAV, we identified several hundred previously uncharacterized isoform changes induced by in vitro oncogene over-expression and revealed a previously unknown mechanism of EGFR activation in human mammary epithelial cells. We analyzed Affymetrix GeneChip data from over 400 human breast tumors in three independent studies, making this the largest clinical dataset analyzed for en masse changes in alternative mRNA processing. The capacity to detect RNA isoform changes in archival microarray data using SplicerAV allowed us to carry out the first analysis of isoform specific mRNA changes directly associated with cancer survival.
PMCID: PMC2838864  PMID: 20184770

Results 1-4 (4)