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. 2022 Sep 2;40(37):5529-5536.
doi: 10.1016/j.vaccine.2022.08.006. Epub 2022 Aug 9.

Functional profiling of Covid 19 vaccine candidate by flow virometry

Affiliations

Functional profiling of Covid 19 vaccine candidate by flow virometry

Ashley Prout et al. Vaccine. .

Abstract

Vaccine development is a complex process, starting with selection of a promising immunogen in the discovery phase, followed by process development in the preclinical phase, and later by clinical trials in tandem with process improvements and scale up. A large suite of analytical techniques is required to gain understanding of the vaccine candidate so that a relevant immunogen is selected and subsequently manufactured consistently throughout the lifespan of the product. For viral vaccines, successful immunogen production is contingent on its maintained antigenicity and/or infectivity, as well as the ability to characterize these qualities within the context of the process, formulation, and clinical performance. In this report we show the utility of flow virometry during preclinical development of a Covid 19 vaccine candidate based on SARS-CoV-2 spike (S) protein expressed on vesicular stomatitis virus (VSV). Using a panel of monoclonal antibodies, we were able to detect the S protein on the surface of the recombinant VSV virus, monitor the expression levels, detect differences in the antigen based on S protein sequence and after virus inactivation, and monitor S protein stability. Collectively, flow virometry provided important data that helped to guide preclinical development of this vaccine candidate.

Keywords: Covid 19 vaccine; Flow virometry; SARS-CoV-2 spike protein; Vaccine development; Vesicular stomatitis virus.

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Conflict of interest statement

Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Josef Vlasak reports financial support was provided by US Department of Health and Human Services.

Figures

None
Graphical abstract
Fig. 1
Fig. 1
Representative cryo-TEM image and flow virometry histograms. Left panel – cryo-TEM image. Right panel – side scatter (SSC) histograms scaled identically. Top right – examples of buffer and samples run with the threshold set to reveal electronics noise. Bottom right – a typical analysis, with the threshold set such that the electronics noise was excluded. Background particles present in the buffer control are negligible (not apparent in the buffer histogram). All data pictured was replicated across numerous independent runs.
Fig. 2
Fig. 2
S-protein detection of VSV virions by flow virometry. Top panel – three-dimensional scatter plots representing antigen content via fluorescence intensity (y-axis) versus SSC, with particle abundance (z-axis) depicted via a heatmap color scale (color scale indicated in the left panel). The gate for antigen-positive particles is drawn based on the control with no primary antibody. The broad fluorescence signal and the narrow LS signal of FL-negative particles are indicated with green arrows. Top right image, cryo-TEM image at 30,000x showing high S-protein density VSV particles (HD) and low S-protein density VSV particles (LD). Bottom panel – assessment of particle aggregation during antibody labelling. A series of sample concentrations was incubated with a constant concentration of antibodies and the % of S-protein positive particles was evaluated.
Fig. 3
Fig. 3
S-protein quantification in vaccine candidate samples across clones and lots. Top panel from left to right – representative examples of flow virometry data (stained with AM91351 anti-S1 antibody) showing a sample with high S-protein expression (clone A) and a sample with low S-protein expression (clone B). Flow virometry (FV) quantification of anti-S1 (orange bars) and anti-S2 (blue bars) normalized to clone A lot 1 for ease of comparison. Error bars indicate standard deviations from duplicate independent runs. Bottom panel from left to right– example of a Simple Western (SW) electropherogram generated using a recombinant S protein (without the transmembrane domain) and a representative vaccine candidate sample, a 5-point standard curve generated with the recombinant S protein (Abclonal, catalog RP01260). Simple Western quantification of S protein per particle (grey bars). S-protein concentrations in the sample was divided by the particle count and normalized to clone A lot 1 for ease of comparison. Error bars indicate standard deviations from duplicate measurements from a single run using a validated method.
Fig. 4
Fig. 4
Comparison of S protein antigenicity by binding studies. Left panel – representative examples of flow virometry data showing reactivity of two S-protein constructs with ACE2-Fc, anti-S2, and anti-S1 antibodies. Right panel – the ratio between the % positive particles in the vaccine candidate and the 2P construct. The x-axis indicates catalog numbers of antibodies used. Error bars indicate standard deviations from duplicate independent runs.
Fig. 5
Fig. 5
Impact of heat treatment and gamma irradiation on the antigenicity of S protein. Treatment conditions are indicated on the x-axis. Neutralizing antibodies are indicated with open symbols. Duplicate independent runs are pictured.
Fig. 6
Fig. 6
S1 dissociation from virions after one month of 4 °C storage. Top panel – flow virometry of a sample before and after approximately one month of 4⁰C storage, labeled with anti-S1 and anti-S2 antibodies. Bottom panel – example anti-S1 Simple Western electropherogram overlay of a sample fresh versus post-storage (left). Peak areas were used for relative S1 and S2 quantitation (using anti-S1 or anti-S2 antibodies) between the supernatant and pellet, then normalized to the sample before centrifugation (right). Data from two lots are shown; error bars indicate standard deviations from duplicate measurements in a single run.

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