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Pseudovirus-Based Neutralization Assays as Customizable and Scalable Tools for Serological Surveillance and Immune Profiling

Year: 2025
Type: article
Abstract: Neutralizing antibodies (nAbs) are key indicators of protection against SARS-CoV-2, and their measurement remains essential for monitoring vaccine responses and population immunity. While the plaque reduction neutralization test (PRNT) is the gold standard, it relies on replicative viruses and is not suited for high-throughput applications. Here, both an in-house and a commercial pseudovirus-based neutralization (PBN) assay were standardized and compared with PRNT to assess performance and concordance. The in-house PBN employed a VSV-ΔG pseudovirus encoding NanoLuc and displaying the SARS-CoV-2 Spike from the Wuhan or Omicron BA.1 variants in HEK293T-hACE2 cells, whereas the commercial assay (Integral Molecular, Philadelphia, PA, USA) used a lentiviral backbone with Renilla or GFP reporters and Wuhan or Omicron XBB.1.5/XBB.1.9 Spikes in Vero E6-ACE2-TMPRSS2 cells. Both assays showed strong correlations with PRNT, the commercial assay; moreover, they offered superior reproducibility and scalability, while the in-house version provided a cost-effective alternative suitable for BSL-2 settings. A total of 600 serum samples from vaccinated individuals were analyzed by commercial PBN at collection time points, from pre-vaccination to twelve months post–second dose, enabling large-scale screening, revealing marked differences in neutralization between Wuhan and Omicron XBB.1.5/1.9, and allowing unbiased classification of low, medium, and high responders using k-means clustering. The geometric mean titers (log10 GMT) highlighted a ~1.5 log10 (eightfold) reduction in neutralizing activity against Omicron, reflecting antibody waning and antigenic drift. Altogether, this study integrates assay standardization, PRNT comparison, and large-scale immune profiling, establishing a robust framework for harmonized pseudovirus-based neutralization testing.
Source: Pathogens
Language: English
Field: Medicine
Open Access status: gold
Estimated APC paid: $2,654
OpenAlex ID: W4415955198
FWCI: 4.234
Cites: 50
Cited by: 6
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