Sites and Determinants of Early Cleavages in the Proteolytic Processing Pathway of Reovirus Surface Protein σ3

Entry of mammalian reovirus virions into target cells requires proteolytic processing of surface protein σ3. In the virion, σ3 mostly covers the membrane-penetration protein μ1, appearing to keep it in an inactive form and to prevent it from interacting with the cellular membrane until the proper time in infection. The molecular mechanism by which σ3 maintains μ1 in this inactive state and the structural changes that accompany σ3 processing and μ1 activation, however, are not well understood. In this study we characterized the early steps in σ3 processing and determined their effects on μ1 function and particle infectivity. We identified two regions of high protease sensitivity, “hypersensitive” regions located at residues 208 to 214 and 238 to 244, within which all proteases tested selectively cleaved σ3 as an early step in processing. Further processing of σ3 was required for infection, consistent with the fact that the fragments resulting from these early cleavages remained bound to the particles. Reovirus type 1 Lang (T1L), type 3 Dearing (T3D), and T1L × T3D reassortant virions differed in the sites of early σ3 cleavage, with T1L σ3 being cleaved mainly at residues 238 to 244 and T3D σ3 being cleaved mainly at residues 208 to 214. These virions also differed in the rates at which the early cleavages occurred, with cleavage of T1L σ3 occurring faster than cleavage of T3D σ3. Analyses using chimeric and site-directed mutants of recombinant σ3 identified carboxy-proximal residues 344, 347, and 353 as the primary determinants of these strain differences. The spatial relationships between these more carboxy-proximal residues and the hypersensitive regions were discerned from the σ3 crystal structure. The results indicate that proteolytic processing of σ3 during reovirus disassembly is a multistep pathway with a number of molecular determinants

Structure of the reovirus outer capsid and dsRNA-binding protein σ3 at 1.8 Å resolution

The crystallographically determined structure of the reovirus outer capsid protein σ3 reveals a two-lobed structure organized around a long central helix. The smaller of the two lobes includes a CCHC zinc-binding site. Residues that vary between strains and serotypes lie mainly on one surface of the protein; residues on the opposite surface are conserved. From a fit of this model to a reconstruction of the whole virion from electron cryomicroscopy, we propose that each σ3 subunit is positioned with the small lobe anchoring it to the protein µ1 on the surface of the virion, and the large lobe, the site of initial cleavages during entry-related proteolytic disassembly, protruding outwards. The surface containing variable residues faces solvent. The crystallographic asymmetric unit contains two σ3 subunits, tightly associated as a dimer. One broad surface of the dimer has a positively charged surface patch, which extends across the dyad. In infected cells, σ3 binds dsRNA and inhibits the interferon response. The location and extent of the positively charged surface patch suggest that the dimer is the RNA-binding form of σ3

The Human Tumor Atlas Network: Charting Tumor Transitions across Space and Time at Single-Cell Resolution.

Crucial transitions in cancer-including tumor initiation, local expansion, metastasis, and therapeutic resistance-involve complex interactions between cells within the dynamic tumor ecosystem. Transformative single-cell genomics technologies and spatial multiplex in situ methods now provide an opportunity to interrogate this complexity at unprecedented resolution. The Human Tumor Atlas Network (HTAN), part of the National Cancer Institute (NCI) Cancer Moonshot Initiative, will establish a clinical, experimental, computational, and organizational framework to generate informative and accessible three-dimensional atlases of cancer transitions for a diverse set of tumor types. This effort complements both ongoing efforts to map healthy organs and previous large-scale cancer genomics approaches focused on bulk sequencing at a single point in time. Generating single-cell, multiparametric, longitudinal atlases and integrating them with clinical outcomes should help identify novel predictive biomarkers and features as well as therapeutically relevant cell types, cell states, and cellular interactions across transitions. The resulting tumor atlases should have a profound impact on our understanding of cancer biology and have the potential to improve cancer detection, prevention, and therapeutic discovery for better precision-medicine treatments of cancer patients and those at risk for cancer

Expansion sequencing: Spatially precise in situ transcriptomics in intact biological systems

Methods for highly multiplexed RNA imaging are limited in spatial resolution and thus in their ability to localize transcripts to nanoscale and subcellular compartments. We adapt expansion microscopy, which physically expands biological specimens, for long-read untargeted and targeted in situ RNA sequencing. We applied untargeted expansion sequencing (ExSeq) to the mouse brain, which yielded the readout of thousands of genes, including splice variants. Targeted ExSeq yielded nanoscale-resolution maps of RNAs throughout dendrites and spines in the neurons of the mouse hippocampus, revealing patterns across multiple cell types, layer-specific cell types across the mouse visual cortex, and the organization and position-dependent states of tumor and immune cells in a human metastatic breast cancer biopsy. Thus, ExSeq enables highly multiplexed mapping of RNAs from nanoscale to system scale

Next-generation characterization of the Cancer Cell Line Encyclopedia

Large panels of comprehensively characterized human cancer models, including the Cancer Cell Line Encyclopedia (CCLE), have provided a rigorous framework with which to study genetic variants, candidate targets, and small-molecule and biological therapeutics and to identify new marker-driven cancer dependencies. To improve our understanding of the molecular features that contribute to cancer phenotypes, including drug responses, here we have expanded the characterizations of cancer cell lines to include genetic, RNA splicing, DNA methylation, histone H3 modification, microRNA expression and reverse-phase protein array data for 1,072 cell lines from individuals of various lineages and ethnicities. Integration of these data with functional characterizations such as drug-sensitivity, short hairpin RNA knockdown and CRISPR-Cas9 knockout data reveals potential targets for cancer drugs and associated biomarkers. Together, this dataset and an accompanying public data portal provide a resource for the acceleration of cancer research using model cancer cell lines