Dados do Trabalho

Título

SARS -CoV-2 Focus Reduction Neutralization Test (FRNT): a standardized and automated approach to raise throughput and data integrity

Introdução

The Plaque Reduction Neutralization Test (PRNT) is still the gold standard for studying Neutralizing Antibodies (NAbs), but other approaches have shown more scalability and suitability to automate data analysis, improving data integrity. The Focus Reduction Neutralization Test (FRNT) is executed on 96 well-plates and reveals an antibody-specific cytopathic effect, allowing a higher sample throughput and development of automated methods to acquire images and quantify virus Focus Forming Units (FFUs).

Objetivo (s)

We aim to use SARS-CoV-2 as a model to develop and standardize FRNT and set robust methods for image acquisition and automated counting of FFUs.

Material e Métodos

To standardize FRNT, experimental parameters were set to generate the most homogeneous cell monolayers and to optimize FFUs number and shape. Samples from donors (CAAE 34728920.4.0000.5262), screened previously by PRNT, were used to assemble a panel to be tested by FRNT, with the defined experimental parameters, to monitor NAb titers for control-sera definition and comparison to PRNT-generated titers. Automation equipment and their software were adopted to improve the image acquisition and analysis of FRNT plates. Images generated from the settings were used to teach the software FFU morphological patterns. To verify the teaching effectiveness, images were run, and the data were compared to the manual counting. 

Resultados e Conclusão

The experimental parameters for 96 well-plates were standardized in 200.000 cell/well for density, 70-100 FFU/well for viral input, CMC 2% for semi-solid overlay medium, 15 min with 4% PFA 24h post-infection for cell fixation and 1:1000 as antibody dilution, unambiguously resulting in identifiable FFU. Results from control sera were qualitatively equivalent to those observed by PRNT with the same samples. The image acquisition method demonstrated to generate images in high resolution with proper signal-noise ratio. The comparison between FFU number from automated and manual counting showed that the quantification method is equivalent to the human job, but it mitigates inherent operator biases, provides data integrity, and enables faster release of results. The standardized FRNT-SARS-CoV-2 has shown to be a trustful and high-performance tool to quantify NAb, and its associated methods for image acquisition and analysis have shown to be in line with the data integrity from Good Clinical Practice (GCP) guidelines, being capable to support studies that monitor vaccine responses.

Palavras Chave

Neutralizing antibodies; FRNT; automation