The COVID-19 pandemic has generated intense interest in the rapid development and evaluation of vaccine candidates for this disease and other emerging diseases. Several novel methods for preparing vaccine candidates are currently undergoing clinical evaluation in response to the urgent need to prevent the spread of COVID-19. In many cases, these methods rely on new approaches for vaccine production and immune stimulation. We report on the use of a novel method (SolaVAX) for production of an inactivated vaccine candidate and the testing of that candidate in a hamster animal model for its ability to prevent infection upon challenge with SARS-CoV-2 virus. The studies employed in this work included an evaluation of the levels of neutralizing antibody produced post-vaccination, levels of specific antibody sub-types to RBD and spike protein that were generated, evaluation of viral shedding post-challenge, flow cytometric and single cell sequencing data on cellular fractions and histopathological evaluation of tissues post-challenge. The results from this preliminary evaluation provide insight into the immunological responses occurring as a result of vaccination with the proposed vaccine candidate and the impact that adjuvant formulations, specifically developed to promote Th1 type immune responses, have on vaccine efficacy and protection against infection following challenge with live SARS-CoV-2. This data may have utility in the development of effective vaccine candidates broadly. Furthermore, the results of this preliminary evaluation suggest that preparation of a whole virion vaccine for COVID-19 using this specific photochemical method may have potential utility in the preparation of one such vaccine candidate.
script took 2.7 minutes running time. Half of this was spent on the gating steps (1.01 min). The running time was also evaluated based on the number of input cells to the feature engineering algorithm (Supplementary Fig. S5). It analyzes roughly 10,000 cells per second.
With new high-throughput flow cytometry, data analysis has become highly complex. Using opensource software, it is now possible to explore these large datasets, simplifying the seemingly complex data. However, in order to perform these analyses, sample preparation, staining procedure, and use of controls must follow rigorous protocols. In this Current Protocols article, we describe the best practices for preparation and acquisition of spectral flow cytometry samples. Following this protocol will lead to clean results that can be used with the cyto-feature engineering data analysis pipeline described previously (Fox et al., Under Revision).
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