A critical component in the interpretation of systems-level studies is the inference of enriched biological pathways and protein complexes contained within OMICs datasets. Successful analysis requires the integration of a broad set of current biological databases and the application of a robust analytical pipeline to produce readily interpretable results. Metascape is a web-based portal designed to provide a comprehensive gene list annotation and analysis resource for experimental biologists. In terms of design features, Metascape combines functional enrichment, interactome analysis, gene annotation, and membership search to leverage over 40 independent knowledgebases within one integrated portal. Additionally, it facilitates comparative analyses of datasets across multiple independent and orthogonal experiments. Metascape provides a significantly simplified user experience through a one-click Express Analysis interface to generate interpretable outputs. Taken together, Metascape is an effective and efficient tool for experimental biologists to comprehensively analyze and interpret OMICs-based studies in the big data era.

The infectious life cycle of the human immunodeficiency virus type 1 (HIV-1) is characterized by an ongoing battle between a compendium of cellular proteins that either promote or oppose viral replication. On the one hand, HIV-1 utilizes dependency factors to support and sustain infection and complete the viral life cycle. On the other hand, both inducible and constitutively expressed host factors mediate efficient and functionally diverse antiviral processes that counteract an infection. To shed light into the complex interplay between HIV-1 and cellular proteins, we previously performed a targeted siRNA screen to identify and characterize novel regulators of viral replication and identified Cullin 3 (Cul3) as a previously undescribed factor that negatively regulates HIV-1 replication. Cul3 is a component of E3-ubiquitin ligase complexes that target substrates for ubiquitin-dependent proteasomal degradation. In the present study, we show that Cul3 is expressed in HIV-1 target cells, such as CD4+ T cells, monocytes, and macrophages and depletion of Cul3 using siRNA or CRISPR/Cas9 increases HIV-1 infection in immortalized cells and primary CD4+ T cells. Conversely, overexpression of Cul3 reduces HIV-1 infection in single replication cycle assays. Importantly, the antiviral effect of Cul3 was mapped to the transcriptional stage of the viral life cycle, an effect which is independent of its role in regulating the G1/S cell cycle transition. Using isogenic viruses that only differ in their promotor region, we find that the NF-κB/NFAT transcription factor binding sites in the LTR are essential for Cul3-dependent regulation of viral gene expression. Although Cul3 effectively suppresses viral gene expression, HIV-1 does not appear to antagonize the antiviral function of Cul3 by targeting it for degradation. Taken together, these results indicate that Cul3 is a negative regulator of HIV-1 transcription which governs productive viral replication in infected cells.

The HIV-1 accessory protein Vpu modulates membrane protein trafficking and degradation to provide evasion of immune surveillance. Targets of Vpu include CD4, HLAs, and BST-2. Several cellular pathways co-opted by Vpu have been identified, but the picture of Vpu's itinerary and activities within membrane systems remains incomplete. Here, we used fusion proteins of Vpu and the enzyme ascorbate peroxidase (APEX2) to compare the ultrastructural locations and the proximal proteomes of wild type Vpu and Vpu-mutants. The proximity-omes of the proteins correlated with their ultrastructural locations and placed wild type Vpu near both retromer and ESCRT-0 complexes. Hierarchical clustering of protein abundances across the mutants was essential to interpreting the data and identified Vpu degradation-targets including CD4, HLA-C, and SEC12 as well as Vpu-cofactors including HGS, STAM, clathrin, and PTPN23, an ALIX-like protein. The Vpu-directed degradation of BST-2 was supported by STAM and PTPN23 and to a much lesser extent by the retromer subunits Vps35 and SNX3. PTPN23 also supported the Vpu-directed decrease in CD4 at the cell surface. These data suggest that Vpu directs targets from sorting endosomes to degradation at multi-vesicular bodies via ESCRT-0 and PTPN23.

Many machine learning applications in bioinformatics currently rely on matching gene identities when analyzing input gene signatures and fail to take advantage of preexisting knowledge about gene functions. To further enable comparative analysis of OMICS datasets, including target deconvolution and mechanism of action studies, we develop an approach that represents gene signatures projected onto their biological functions, instead of their identities, similar to how the word2vec technique works in natural language processing. We develop the Functional Representation of Gene Signatures (FRoGS) approach by training a deep learning model and demonstrate that its application to the Broad Institutes L1000 datasets results in more effective compound-target predictions than models based on gene identities alone. By integrating additional pharmacological activity data sources, FRoGS significantly increases the number of high-quality compound-target predictions relative to existing approaches, many of which are supported by in silico and/or experimental evidence. These results underscore the general utility of FRoGS in machine learning-based bioinformatics applications. Prediction networks pre-equipped with the knowledge of gene functions may help uncover new relationships among gene signatures acquired by large-scale OMICs studies on compounds, cell types, disease models, and patient cohorts.

"Shock and kill" strategies focus on purging the latent HIV-1 reservoir by treating infected individuals with therapeutics that activate the latent virus and subsequently eliminating infected cells. We have previously reported that induction of non-canonical nuclear factor κB (NF-κB) signaling through a class of small-molecule antagonists known as Smac mimetics can reverse HIV-1 latency. Here, we describe the development of Ciapavir (SBI-0953294), a molecule specifically optimized for HIV-1 latency reversal that was found to be more efficacious as a latency-reversing agent than other Smac mimetics under clinical development for cancer. Critically, this molecule induced activation of HIV-1 reservoirs in vivo in a bone marrow, liver, thymus (BLT) humanized mouse model without mediating systemic T cell activation. This study provides proof of concept for the in vivo efficacy and safety of Ciapavir and indicates that Smac mimetics can constitute a critical component of a safe and efficacious treatment strategy to eliminate the latent HIV-1 reservoir.

How transcription affects genome 3D organization is not well understood. We found that during influenza A (IAV) infection, rampant transcription rapidly reorganizes host cell chromatin interactions. These changes occur at the ends of highly transcribed genes, where global inhibition of transcription termination by IAV NS1 protein causes readthrough transcription for hundreds of kilobases. In these readthrough regions, elongating RNA polymerase II disrupts chromatin interactions by inducing cohesin displacement from CTCF sites, leading to locus decompaction. Readthrough transcription into heterochromatin regions switches them from the inert (B) to the permissive (A) chromatin compartment and enables transcription factor binding. Data from non-viral transcription stimuli show that transcription similarly affects cohesin-mediated chromatin contacts within gene bodies. Conversely, inhibition of transcription elongation allows cohesin to accumulate at previously transcribed intragenic CTCF sites and to mediate chromatin looping and compaction. Our data indicate that transcription elongation by RNA polymerase II remodels genome 3D architecture.

Abstract Background The increasing availability of HIV-host interaction datasets, including both physical and genetic interactions, has created a need for software tools to integrate and visualize the data. Because these host-pathogen interactions are extensive and interactions between human proteins are found within many different databases, it is difficult to generate integrated HIV-human interaction networks. Results We have developed a web-based platform, termed GPS-Prot http://www.gpsprot.org, that allows for facile integration of different HIV interaction data types as well as inclusion of interactions between human proteins derived from publicly-available databases, including MINT, BioGRID and HPRD. The software has the ability to group proteins into functional modules or protein complexes, generating more intuitive network representations and also allows for the uploading of user-generated data. Conclusions GPS-Prot is a software tool that allows users to easily create comprehensive and integrated HIV-host networks. A major advantage of this platform compared to other visualization tools is its web-based format, which requires no software installation or data downloads. GPS-Prot allows novice users to quickly generate networks that combine both genetic and protein-protein interactions between HIV and its human host into a single representation. Ultimately, the platform is extendable to other host-pathogen systems.

The human interferon (IFN)-induced MxA protein is a key antiviral host restriction factor exhibiting broad antiviral activity against many RNA viruses, including highly pathogenic avian influenza A viruses (IAV) of the H5N1 and H7N7 subtype. To date the mechanism for how MxA exerts its antiviral activity is unclear, however, additional cellular factors are believed to be essential for this activity. To identify MxA cofactors we performed a genome-wide siRNA-based screen in human airway epithelial cells (A549) constitutively expressing MxA using an H5N1 reporter virus. These data were complemented with a proteomic screen to identify MxA-interacting proteins. The combined data identified SMARCA2, the ATPase subunit of the BAF chromatin remodeling complex, as a crucial factor required for the antiviral activity of MxA against IAV. Intriguingly, our data demonstrate that although SMARCA2 is essential for expression of some IFN-stimulated genes (ISGs), and the establishment of an antiviral state, it is not required for expression of MxA, suggesting an indirect effect on MxA activity. Transcriptome analysis of SMARCA2-depleted A549-MxA cells identified a small set of SMARCA2-regulated factors required for activity of MxA, in particular IFITM2 and IGFBP3. These findings reveal that several virus-inducible factors work in concert to enable MxA restriction of IAV.

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has been fixed in the paper.