Selective Activation of Src Family Kinases by the HIV-1 Nef Protein

Nef is a critical HIV-1 accessory factor shown to promote viral pathogenesis by altering host cell signaling pathways. Nef has been shown to bind several members of the Src family of protein-tyrosine kinases, and these interactions have been implicated in the pathogenesis of HIV/AIDS. The studies summarized below investigated this key interaction between virus and host cell proteins. We explored the direct effect of Nef interaction on Src family kinases (SFKs) using Saccharomyces cerevisiae, a well-defined system in which c-Src expression arrests yeast cell growth in a kinase-dependent manner. The seven SFKs found in HIV target cells wre expressed in yeast; each was found to be active alone, but repressed by co-expression of the negative regulatory kinase Csk. We then co-expressed each SFK with both Csk and HIV-1 Nef and found that Nef selectively activated Hck, Lyn, and c-Src among SFKs.We then used our yeast-based system to identify small molecule inhibitors of the active Nef:Hck complex using the auto-dowregulated Hck-YEEI molecule. Yeast expressing the Nef:Hck-YEEI complex were used to screen a library of small heterocyclic compounds based on their ability to rescue growth inhibition. Two compounds identified in this screen potently blocked Nef-dependent HIV replication, indicating Nef:SFK complexes as valid targets for anti-HIV drug therapy. Finally, we used the yeast assay to identify novel mechanisms of Nef:SFK interactions. We screened a panel of primary Nef alleles containing the known SH3-binding elements and discovered four alleles whose proteins demonstrated altered activation of SFKs. Sequence examination revealed the existence of amino acid changes in regions not previously suspected to be involved in SH3-mediated interaction. Particularly intriguing are residues in a large unstructured loop that projects from the Nef core. These findings suggest that critical residues outside of the known SH3-binding motifs may affect SFK binding and activation. Together, the results presented here advance the field of HIV research by furthering our understanding of the interaction between the HIV-1 Nef virulence factor and the Src kinase family, as well as validating this virus:host cell interaction as a rational target for anti-HIV drug discovery

Dynamic Actin Polymerization Drives T Cell Receptor–Induced Spreading A Role for the Signal Transduction Adaptor LAT

AbstractT cell activation induces functional changes in cell shape and cytoskeletal architecture. To facilitate the collection of dynamic, high-resolution images of activated T cells, we plated T cells on coverslips coated with antibodies to the T cell receptor (TCR). Using these images, we were able to quantitate the morphological responses of individual cells over time. Here, we show that TCR engagement triggers the formation and expansion of contacts bounded by continuously remodeled actin-rich rings. These processes are associated with the extension of lamellipodia and require actin polymerization, tyrosine kinase activation, cytoplasmic calcium increases, and LAT, an important hematopoietic adaptor. In addition, the maintenance of the resulting contact requires sustained calcium influxes, an intact microtubule cytoskeleton, and functional LAT

Discovery of a diaminoquinoxaline benzenesulfonamide antagonist of HIV-1 Nef function using a yeast-based phenotypic screen

Background: HIV-1 Nef is a viral accessory protein critical for AIDS progression. Nef lacks intrinsic catalytic activity and binds multiple host cell signaling proteins, including Hck and other Src-family tyrosine kinases. Nef binding induces constitutive Hck activation that may contribute to HIV pathogenesis by promoting viral infectivity, replication and downregulation of cell-surface MHC-I molecules. In this study, we developed a yeast-based phenotypic screen to identify small molecules that inhibit the Nef-Hck complex. Results: Nef-Hck interaction was faithfully reconstituted in yeast cells, resulting in kinase activation and growth arrest. Yeast cells expressing the Nef-Hck complex were used to screen a library of small heterocyclic compounds for their ability to rescue growth inhibition. The screen identified a dihydrobenzo-1,4-dioxin-substituted analog of 2-quinoxalinyl-3-aminobenzene-sulfonamide (DQBS) as a potent inhibitor of Nef-dependent HIV-1 replication and MHC-I downregulation in T-cells. Docking studies predicted direct binding of DQBS to Nef which was confirmed in differential scanning fluorimetry assays with recombinant purified Nef protein. DQBS also potently inhibited the replication of HIV-1 NL4-3 chimeras expressing Nef alleles representative of all M-group HIV-1 clades.Conclusions: Our findings demonstrate the utility of a yeast-based growth reversion assay for the identification of small molecule Nef antagonists. Inhibitors of Nef function discovered with this assay, such as DQBS, may complement the activity of current antiretroviral therapies by enabling immune recognition of HIV-infected cells through the rescue of cell surface MHC-I. © 2013 Trible et al.; licensee BioMed Central Ltd

Probing genetic control of swine responses to PRRSV infection: current progress of the PRRS host genetics consortium

<p>Abstract</p> <p>Background</p> <p>Understanding the role of host genetics in resistance to porcine reproductive and respiratory syndrome virus (PRRSV) infection, and the effects of PRRS on pig health and related growth, are goals of the PRRS Host Genetics Consortium (PHGC).</p> <p>Methods</p> <p>The project uses a nursery pig model to assess pig resistance/susceptibility to primary PRRSV infection. To date, 6 groups of 200 crossbred pigs from high health farms were donated by commercial sources. After acclimation, the pigs were infected with PRRSV in a biosecure facility and followed for 42 days post infection (dpi). Blood samples were collected at 0, 4, 7, 10, 14, 21, 28, 35 and 42 dpi for serum and whole blood RNA gene expression analyses; weekly weights were recorded for growth traits. All data have been entered into the PHGC relational database. Genomic DNAs from all PHGC1-6 pigs were prepared and genotyped with the Porcine SNP60 SNPchip.</p> <p>Results</p> <p>Results have affirmed that all challenged pigs become PRRSV infected with peak viremia being observed between 4-21 dpi. Multivariate statistical analyses of viral load and weight data have identified PHGC pigs in different virus/weight categories. Sera are now being compared for factors involved in recovery from infection, including speed of response and levels of immune cytokines. Genome-wide association studies (GWAS) are underway to identify genes and chromosomal locations that identify PRRS resistant/susceptible pigs and pigs able to maintain growth while infected with PRRSV.</p> <p>Conclusions</p> <p>Overall, the PHGC project will enable researchers to discover and verify important genotypes and phenotypes that predict resistance/susceptibility to PRRSV infection. The availability of PHGC samples provides a unique opportunity to continue to develop deeper phenotypes on every PRRSV infected pig.</p

Active/Passive, ‘Diminished’/‘Beautiful’, ‘Light’ from Above and Below: Rereading Shekhinah’s Sexual Desire in Zohar al Shir ha-Shirim (Song of Songs)

In Zohar al Shir ha-Shirim, the Zohar’s reading of Song of Songs, Shekhinah, echoing themes associated with the Shulamite of the biblical text, consistently initiates cosmic union. Sexual desire in the zoharic texts is a form of capital necessary to facilitate sefirotic intercourse, although scholarly readings of the zoharic corpus often identify Shekhinah as a passive receptacle. This, however, is only true if the endemic contradictions within the texts are glossed over. In Song of Songs, the Shulamite’s sexual ‘initiative’ is core. This was not lost on the author(s) of Zohar al Shir ha-Shirim, who, in struggling to explain Shekhinah’s sefirotic role in line with the erotics of Song of Songs, inescapably echoed the ‘depatriarchalizing’ themes of the biblical text. As this article demonstrates, in Zohar al Shir ha-Shirim, Shekhinah is active and repeatedly encourages and frustrates cosmic sexual intercourse. Zohar al Shir ha-Shirim shows that it is possible to reread Shekhinah’s role beyond the androcentrism of the authors as well as scholarly assumptions about her passivity

Sequence- and Interactome-Based Prediction of Viral Protein Hotspots Targeting Host Proteins: A Case Study for HIV Nef

Virus proteins alter protein pathways of the host toward the synthesis of viral particles by breaking and making edges via binding to host proteins. In this study, we developed a computational approach to predict viral sequence hotspots for binding to host proteins based on sequences of viral and host proteins and literature-curated virus-host protein interactome data. We use a motif discovery algorithm repeatedly on collections of sequences of viral proteins and immediate binding partners of their host targets and choose only those motifs that are conserved on viral sequences and highly statistically enriched among binding partners of virus protein targeted host proteins. Our results match experimental data on binding sites of Nef to host proteins such as MAPK1, VAV1, LCK, HCK, HLA-A, CD4, FYN, and GNB2L1 with high statistical significance but is a poor predictor of Nef binding sites on highly flexible, hoop-like regions. Predicted hotspots recapture CD8 cell epitopes of HIV Nef highlighting their importance in modulating virus-host interactions. Host proteins potentially targeted or outcompeted by Nef appear crowding the T cell receptor, natural killer cell mediated cytotoxicity, and neurotrophin signaling pathways. Scanning of HIV Nef motifs on multiple alignments of hepatitis C protein NS5A produces results consistent with literature, indicating the potential value of the hotspot discovery in advancing our understanding of virus-host crosstalk

Exploring genetic control of swine responses to viral diseases.

Our goal is to understand genomic control of viral disease responses focusing on the economically most important disease of pigs, porcine reproductive and respiratory syndrome

Quantitative Analysis of Porcine Reproductive and Respiratory Syndrome (PRRS) Viremia Profiles from Experimental Infection: A Statistical Modelling Approach

Porcine reproductive and respiratory syndrome (PRRS) is one of the most economically significant viral diseases facing the global swine industry. Viremia profiles of PRRS virus challenged pigs reflect the severity and progression of infection within the host and provide crucial information for subsequent control measures. In this study we analyse the largest longitudinal PRRS viremia dataset from an in-vivo experiment. The primary objective was to provide a suitable mathematical description of all viremia profiles with biologically meaningful parameters for quantitative analysis of profile characteristics. The Wood's function, a gamma-type function, and a biphasic extended Wood's function were fit to the individual profiles using Bayesian inference with a likelihood framework. Using maximum likelihood inference and numerous fit criteria, we established that the broad spectrum of viremia trends could be adequately represented by either uni- or biphasic Wood's functions. Three viremic categories emerged: cleared (uni-modal and below detection within 42 days post infection(dpi)), persistent (transient experimental persistence over 42 dpi) and rebound (biphasic within 42 dpi). The convenient biological interpretation of the model parameters estimates, allowed us not only to quantify inter-host variation, but also to establish common viremia curve characteristics and their predictability. Statistical analysis of the profile characteristics revealed that persistent profiles were distinguishable already within the first 21 dpi, whereas it is not possible to predict the onset of viremia rebound. Analysis of the neutralizing antibody(nAb) data indicated that there was a ubiquitous strong response to the homologous PRRSV challenge, but high variability in the range of cross-protection of the nAbs. Persistent pigs were found to have a significantly higher nAb cross-protectivity than pigs that either cleared viremia or experienced rebound within 42 dpi. Our study provides novel insights into the nature and degree of variation of hosts' responses to infection as well as new informative traits for subsequent genomic and modelling studies

An integrative approach for a network based meta-analysis of viral RNAi screens.

BACKGROUND: Big data is becoming ubiquitous in biology, and poses significant challenges in data analysis and interpretation. RNAi screening has become a workhorse of functional genomics, and has been applied, for example, to identify host factors involved in infection for a panel of different viruses. However, the analysis of data resulting from such screens is difficult, with often low overlap between hit lists, even when comparing screens targeting the same virus. This makes it a major challenge to select interesting candidates for further detailed, mechanistic experimental characterization. RESULTS: To address this problem we propose an integrative bioinformatics pipeline that allows for a network based meta-analysis of viral high-throughput RNAi screens. Initially, we collate a human protein interaction network from various public repositories, which is then subjected to unsupervised clustering to determine functional modules. Modules that are significantly enriched with host dependency factors (HDFs) and/or host restriction factors (HRFs) are then filtered based on network topology and semantic similarity measures. Modules passing all these criteria are finally interpreted for their biological significance using enrichment analysis, and interesting candidate genes can be selected from the modules. CONCLUSIONS: We apply our approach to seven screens targeting three different viruses, and compare results with other published meta-analyses of viral RNAi screens. We recover key hit genes, and identify additional candidates from the screens. While we demonstrate the application of the approach using viral RNAi data, the method is generally applicable to identify underlying mechanisms from hit lists derived from high-throughput experimental data, and to select a small number of most promising genes for further mechanistic studies. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13015-015-0035-7) contains supplementary material, which is available to authorized users