High-Definition Mapping of Four Spatially Distinct Neutralizing Epitope Clusters on RiVax, a Candidate Ricin Toxin Subunit Vaccine

RiVax is a promising recombinant ricin toxin A subunit (RTA) vaccine antigen that has been shown to be safe and immunogenic in humans and effective at protecting rhesus macaques against lethal-dose aerosolized toxin exposure. We previously used a panel of RTA-specific monoclonal antibodies (MAbs) to demonstrate, by competition enzyme-linked immunosorbent assay (ELISA), that RiVax elicits similar serum antibody profiles in humans and macaques. However, the MAb binding sites on RiVax have yet to be defined. In this study, we employed hydrogen exchange-mass spectrometry (HX-MS) to localize the epitopes on RiVax recognized by nine toxin-neutralizing MAbs and one nonneutralizing MAb. Based on strong protection from hydrogen exchange, the nine MAbs grouped into four spatially distinct epitope clusters (namely, clusters I to IV). Cluster I MAbs protected RiVax's α-helix B (residues 94 to 107), a protruding immunodominant secondary structure element known to be a target of potent toxin-neutralizing antibodies. Cluster II consisted of two subclusters located on the “back side” (relative to the active site pocket) of RiVax. One subcluster involved α-helix A (residues 14 to 24) and α-helices F-G (residues 184 to 207); the other encompassed β-strand d (residues 62 to 69) and parts of α-helices D-E (154 to 164) and the intervening loop. Cluster III involved α-helices C and G on the front side of RiVax, while cluster IV formed a sash from the front to back of RiVax, spanning strands b, c, and d (residues 35 to 59). Having a high-resolution B cell epitope map of RiVax will enable the development and optimization of competitive serum profiling assays to examine vaccine-induced antibody responses across species

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages