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.
Human immunodeficiency virus (HIV) has a small genome and therefore relies heavily on the host cellular machinery to replicate. Identifying which host proteins and complexes come into physical contact with the viral proteins is crucial for a comprehensive understanding of how HIV rewires the host’s cellular machinery during the course of infection. Here we report the use of affinity tagging and purification mass spectrometry1-3 to determine systematically the physical interactions of all 18 HIV-1 proteins and polyproteins with host proteins in two different human cell lines (HEK293 and Jurkat). Using a quantitative scoring system that we call MiST, we identified with high confidence 497 HIV–human protein–protein interactions involving 435 individual human proteins, with ~40% of the interactions being identified in both cell types. We found that the host proteins hijacked by HIV, especially those found interacting in both cell types, are highly conserved across primates. We uncovered a number of host complexes targeted by viral proteins, including the finding that HIV protease cleaves eIF3d, a subunit of eukaryotic translation initiation factor 3. This host protein is one of eleven identified in this analysis that act to inhibit HIV replication. This data set facilitates a more comprehensive and detailed understanding of how the host machinery is manipulated during the course of HIV infection.
Summary The emergence of the novel SARS coronavirus 2 (SARS-CoV-2) in 2019 has triggered an ongoing global pandemic of severe pneumonia-like disease designated as coronavirus disease 2019 (COVID-19) 1 . The development of a vaccine is likely to require at least 12-18 months, and the typical timeline for approval of a novel antiviral therapeutic can exceed 10 years. Thus, repurposing of known drugs could significantly accelerate the deployment of novel therapies for COVID-19. Towards this end, we profiled a library of known drugs encompassing approximately 12,000 clinical-stage or FDA-approved small molecules. We report the identification of 100 molecules that inhibit viral replication, including 21 known drugs that exhibit dose response relationships. Of these, thirteen were found to harbor effective concentrations likely commensurate with achievable therapeutic doses in patients, including the PIKfyve kinase inhibitor apilimod 2 – 4 , and the cysteine protease inhibitors MDL-28170, Z LVG CHN2, VBY-825, and ONO 5334. Notably, MDL-28170, ONO 5334, and apilimod were found to antagonize viral replication in human iPSC-derived pneumocyte-like cells, and the PIKfyve inhibitor also demonstrated antiviral efficacy in a primary human lung explant model. Since most of the molecules identified in this study have already advanced into the clinic, the known pharmacological and human safety profiles of these compounds will enable accelerated preclinical and clinical evaluation of these drugs for the treatment of COVID-19.
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