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Identifying protein environments at the virus-host cell interface can improve our understanding of viral entry and pathogenesis. SARS-CoV-2, the virus behind the ongoing COVID-19 pandemic, uses the cell surface ACE2 protein as a major receptor, but the contribution of other cellular proteins in the entry process is unknown. To probe the microenvironment of SARS-CoV-2 Spike-ACE2 protein interactomes on human cells, we developed a photocatalyst-based viral-host protein microenvironment mapping platform (ViraMap) employing iridium photocatalysts conjugated to Spike for visible-light driven proximity labelling on host cells. Application of ViraMap on ACE2-expressing cells captured ACE2, the established co-receptor NRP1, as well as other proteins implicated in host cell entry and immunomodulation. We further investigated these enriched proteins via loss-of-function and over-expression in pseudotype and authentic infection models and observed that the Ig receptor PTGFRN and tyrosine kinase ligand EFNB1 can serve as SARS-CoV-2 entry factors. Our results highlight additional host targets that participate infection and showcase ViraMap for interrogating virus-host cell surface interactomes.

Cell-cell interactions drive essential biological processes critical to cell and tissue development, function, pathology, and disease outcome. The growing appreciation of immune cell interactions within disease environments has led to significant efforts to develop protein- and cell-based therapeutic strategies. A better understanding of these cell-cell interactions will enable the development of effective immunotherapies. However, characterizing these complex cellular interactions at molecular resolution in their native biological contexts remains challenging. To address this, we introduce photocatalytic cell tagging (PhoTag), a modality agnostic platform for profiling cell-cell interactions. Using photoactivatable flavin-based cofactors, we generate phenoxy radical tags for targeted labeling at the cell surface. Through various targeting modalities (e.g. MHC-Multimer, antibody, single domain antibody (VHH)) we deliver a flavin photocatalyst for cell tagging within monoculture, co-culture, and peripheral blood mononuclear cells. PhoTag enables highly selective tagging of the immune synapse between an immune cell and an antigen-presenting cell through targeted labeling at the cell-cell junction. This allowed for the ability to profile gene expression-level differences between interacting and bystander cell populations. Given the modality agnostic and spatio-temporal nature of PhoTag, we envision its broad utilization to detect and profile intercellular interactions within an immune synapse and other confined cellular regions for any biological system.

SummaryCurrent therapeutic interventions to eradicate latent HIV (“reservoir”) and restore immune function in ART-treated HIV infection have yet to show efficacy. To explore mechanisms of HIV persistence, we apply an integrated systems biology approach and identify a distinct group of individuals with poor CD4 T-cell reconstitution (Immunologic non-responders, “INRs”) and high frequencies of cells with inducible HIV. Contrary to the prevailing notion that immune activation drives HIV persistence and immune dysfunction, peripheral blood leukocytes from these subjects have enhanced expression of a network of genes regulated by cellular senescence driving transcription factors (TFs) FOXO3, SMAD2 and IRF3. In these subjects, increased frequencies of regulatory T cells and expression of the TGF-β signaling cascade are complimented by the downregulation of cell cycle, metabolic and pro-inflammatory pathways. Lactobacillaceae family and metabolites (members of the butyrate family – i.e. α-ketobutyrate) were correlated with Treg frequencies in “Senescent-INRs”ex vivo,triggered the differentiation of TGF-β producing Tregs and promoted HIV latency establishmentin vitro.These cascades, downstream of PD-1/TGF-β, prevent memory T cell differentiation and are associated with an increase in frequencies of cells with inducible HIVex vivo.Our findings identify cellular senescence responses that can be targeted by PD-1 or TGF-β specific interventions that have shown safety and efficacy in cancer, and may prove to be crucial for HIV eradication.

SARS-CoV-2 research and antiviral discovery are hampered by the lack of a cell-based virus replication system that can be readily adopted without biosafety level 3 (BSL-3) restrictions. Here, the construction of a non-infectious SARS-CoV-2 reporter replicon and its application in deciphering viral replication mechanisms and evaluating SARS-CoV-2 inhibitors are presented. The replicon genome is replication competent but does not produce progeny virions. Its replication can be inhibited by RdRp mutations or by known SARS-CoV-2 antiviral compounds. Using this system, a high-throughput antiviral assay has also been developed. Significant differences in potencies of several SARS-CoV-2 inhibitors in different cell lines were observed, which highlights the challenges of discovering antivirals capable of inhibiting viral replication in vivo and the importance of testing compounds in multiple cell culture models. The generation of a SARS-CoV-2 replicon provides a powerful platform to expand the global research effort to combat COVID-19.

Natural products represent a rich reservoir of small molecule drug candidates utilized as antimicrobial drugs, anticancer therapies, and immunomodulatory agents. These molecules are microbial secondary metabolites synthesized by co-localized genes termed Biosynthetic Gene Clusters (BGCs). The increase in full microbial genomes and similar resources has led to development of BGC prediction algorithms, although their precision and ability to identify novel BGC classes could be improved. Here we present a deep learning strategy (DeepBGC) that offers more accurate BGC identification and an improved ability to extrapolate and identify novel BGC classes compared to existing tools. We supplemented this with downstream random forest classifiers that accurately predicted BGC product classes and potential chemical activity. Application of DeepBGC to bacterial genomes uncovered previously undetectable BGCs that may code for natural products with novel biologic activities. The improved accuracy and classification ability of DeepBGC represents a significant step forward forin-silicoBGC identification.

The most significant advance in the medical management of HIV-1 infection has been the treatment of patients with antiviral drugs, which can suppress HIV-1 replication to undetectable levels. The discovery of HIV-1 as the causative agent of AIDS together with an ever-increasing understanding of the virus replication cycle have been instrumental in this effort by providing researchers with the knowledge and tools required to prosecute drug discovery efforts focused on targeted inhibition with specific pharmacological agents. To date, an arsenal of 24 Food and Drug Administration (FDA)-approved drugs are available for treatment of HIV-1 infections. These drugs are distributed into six distinct classes based on their molecular mechanism and resistance profiles: (1) nucleoside-analog reverse transcriptase inhibitors (NNRTIs), (2) non-nucleoside reverse transcriptase inhibitors (NNRTIs), (3) integrase inhibitors, (4) protease inhibitors (PIs), (5) fusion inhibitors, and (6) coreceptor antagonists. In this article, we will review the basic principles of antiretroviral drug therapy, the mode of drug action, and the factors leading to treatment failure (i.e., drug resistance).