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. 2022 Aug;2(3):100101.
doi: 10.1016/j.jcvp.2022.100101. Epub 2022 Aug 6.

Development and validation of an enzyme-linked immunoassay kit for diagnosis and surveillance of COVID-19

Flávia F Bagno  1   2 , Sarah A R Sérgio  1 , Maria Marta Figueiredo  1   3 , Lara C Godoi  1 , Luis A F Andrade  1 , Natália C Salazar  1 , Camila P Soares  4 , Andressa Aguiar  5 , Flávia Jaqueline Almeida  6 , Edimilson D da Silva  2 , Antônio G P Ferreira  2 , Edison Luiz Durigon  4 , Ricardo T Gazzinelli  1   7 , Santuza M R Teixeira  1   8 , Ana Paula S M Fernandes  1   9 , Flavio G da Fonseca  1   10
Affiliations

Development and validation of an enzyme-linked immunoassay kit for diagnosis and surveillance of COVID-19

Flávia F Bagno et al. J Clin Virol Plus. 2022 Aug.

Abstract

There is a massive demand to identify alternative methods to detect new cases of COVID-19 as well as to investigate the epidemiology of the disease. In many countries, importation of commercial kits poses a significant impact on their testing capacity and increases the costs for the public health system. We have developed an ELISA to detect IgG antibodies against SARS-CoV-2 using a recombinant viral nucleocapsid (rN) protein expressed in E. coli. Using a total of 894 clinical samples we showed that the rN-ELISA was able to detect IgG antibodies against SARS-CoV-2 with high sensitivity (97.5%) and specificity (96.3%) when compared to a commercial antibody test. After three external validation studies, we showed that the test accuracy was higher than 90%. The rN-ELISA IgG kit constitutes a convenient and specific method for the large-scale determination of SARS-CoV-2 antibodies in human sera with high reliability.

Keywords: COVID-19; Diagnosis; ELISA; Prototyping; SARS-CoV-2; Serological assay.

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Conflict of interest statement

The authors declare no conflict of interest. Funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

Figures

Fig. 1
Fig. 1
Sera samples used during rN-ELISA validation. Experiments are categorized and showed in gray, positive samples (qPCR or DPP) in red, negative samples (negative PCR or pre-pandemic) in green and suspected cases (negative or no PCR data, but that had contact with confirmed COVID-19 individuals) in orange. The rN-ELISA sensitivity and specificity during internal validation included samples from healthy donors (n = 81) and qPCR positive samples from hospitalized (n = 11) and non-hospitalized individual (n = 43). Agreement between rN-ELISA and DPP included: all qPCR+ samples (n = 176), suspected cases (n = 62) and 23 healthy donors tested by DPP. The positive agreement to qPCR was calculated using samples from 43 individuals (n =  157 samples, with information about the time after the qPCR confirmation).
Fig. 2
Fig. 2
Evaluation of the accuracy of anti-SARS-CoV-2 rN-ELISA IgG kit. (a) The sensitivity and specificity of the rN antigen were calculated according to the index in ELISA and confirmed by ROC curve. A comparison between qPCR positive patients and healthy donors showed significant differences between groups (p < 0,0001, by Mann Whitney test). Grey zone (Index ranging from 0.8 to 1,09) indicates borderline results. (b) ROC curve considering all PCR positive results, including antibody non detected by DPP. (c) Analysis considering PCR positive patients with positive antibody confirmation by DPP (serological reference test).
Fig. 3:
Fig. 3
Comparison between ELISA and DPP (serologial reference). A: Linear regression of ELISA index and DPP signal with 261 samples, including COVID-19 patients and healthy donors. B: Follow up of 43 patients after confirmation of COVID-19 by nasal swab PCR using ELISA and DPP.
See this image and copyright information in PMC

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