| Literature DB >> 34267520 |
Bijon Kumar Sil1, Mohd Raeed Jamiruddin2, Md Ahsanul Haq1, Mohib Ullah Khondoker3, Nowshin Jahan1, Shahad Saif Khandker1, Tamanna Ali1, Mumtarin Jannat Oishee1, Taku Kaitsuka4, Masayasu Mie5, Kazuhito Tomizawa6, Eiry Kobatake5, Mainul Haque7, Nihad Adnan8.
Abstract
BACKGROUND: Serological tests detecting severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) are widely used in seroprevalence studies and evaluating the efficacy of the vaccination program. Some of the widely used serological testing techniques are enzyme-linked immune-sorbent assay (ELISA), chemiluminescence immunoassay (CLIA), and lateral flow immunoassay (LFIA). However, these tests are plagued with low sensitivity or specificity, time-consuming, labor-intensive, and expensive. We developed a serological test implementing flow-through dot-blot assay (FT-DBA) for SARS-CoV-2 specific IgG detection, which provides enhanced sensitivity and specificity while being quick to perform and easy to use.Entities:
Keywords: AuNP; COVID-19; SARS-CoV-2; dot-blot immunoassay; gold nanoparticle; nucleocapsid; receptor binding domain; serosurveillance
Mesh:
Substances:
Year: 2021 PMID: 34267520 PMCID: PMC8277418 DOI: 10.2147/IJN.S313140
Source DB: PubMed Journal: Int J Nanomedicine ISSN: 1176-9114
Figure 1Design concept of the rapid flow-through dot-blot immunoassay (FT-DBA). The gold nanoparticle (AuNP) with antibody conjugated onto the surface can bind to the SARS-CoV-2 antigen. At the same time, the AuNP with goat anti-mouse within the same solution can bind to mouse polyclonal antibody, which is the control dot.
Figure 2Interpretation of the test result- (A) positive: both the dots are visible whereby implicating that the AuNP solution is in perfectly working condition; (B) negative: the presence of the only control dot signifies that there is an absence of anti-SARS-CoV-2 antibody while the AuNP is perfect working condition; (C) and (D) invalid test: the absence of control dot signifies that the AuNP is not in working condition, henceforth the test should not be interpreted but should be repeated.
Figure 3Dot intensity and scale of measurement. (A) 3+: test dot is present at 8-fold dilution but may be absent or present in 16-fold dilution; (B) 2+: test dot is present at 4-fold dilution but absent at 8-fold dilution; (C) 1+: test dot is present at 2-fold dilution but absent at 4-fold dilution; (D) 0.5+: test dot is absent at 2-fold dilution; (E) test dot is absent. It should be ensured that the control dot is present in every experiment, or else the test would be void.
Formula for Sensitivity, Specificity, Positive Predictive Value (PPV), Negative Predictive Value (NPV) Calculation
| Positive test result | True Positive (TP) | False Positive (FP) | |
| Negative test result | False Negative (FN) | True Negative (TN) | |
Figure 4Mean difference in the positive (<14 and > 14 days) and negative samples in in-house ELISA to detect RBD (A) and NCP (B) specific IgG against SARS-CoV-2. The linear regression model was used to estimate the p-value, and the data were represented as mean with standard deviation (S.D.).
Comparison Between FT-DBA with FDA Approved Commercial Antibody Immunoassay
| Commercial Immunoassay (Elecsys SARS-CoV-2 Assay) | ||||||
|---|---|---|---|---|---|---|
| Positive | Negative | Total | Sensitivity, (95% CI) | Specificity, (95% CI) | ||
| FT-DBA | Positive | 15 | 0 | 15 | 100%(78.3%, 100%) | 100%(83.2%, 100%) |
| Negative | 0 | 20 | 20 | |||
| Total | 15 | 20 | 35 | |||
Note: Test agreement was evaluated by Kappa statistics.
Comparison of AUC, Sensitivity, Specificity, and Kappa of Dot Blot with RBD-IgG and S1-IgG at Different Time Points with RT-PCR Positive and Negative Samples
| AUC (95% CI) | Sensitivity, % (95% CI) | Specificity (95% CI) | Kappa | p-value | |
|---|---|---|---|---|---|
| <14 Days | |||||
| NCP-IgG | 0.90(0.81, 0.99) | 80.0(56.3, 94.3) | 100(96.4, 100) | 0.800 | <0.001 |
| RBD-IgG | 0.90(0.81, 0.99) | 80.0(56.3, 94.3) | 99.0(94.6, 100) | 0.840 | <0.001 |
| Dot blot | 0.92(0.83, 1.00) | 85.0(62.1, 96.8) | 98.0(93.0, 99.8) | 0.845 | <0.001 |
| >14 days | |||||
| NCP-IgG | 0.99(0.98, 1.00) | 98.4(91.2, 100) | 100(94.1, 100.0) | 0.987 | <0.001 |
| RBD-IgG | 0.99(0.98, 1.00) | 98.4(91.2, 100) | 99.0(94.6, 100) | 0.974 | <0.001 |
| Dot blot | 0.99(0.98, 1.00) | 100(94.1, 100.0) | 98.0(93.0, 99.8) | 0.948 | <0.001 |
| Overall | |||||
| NCP-IgG | 0.96(0.93, 0.99) | 93.8(86.2, 98.0) | 100(96.4, 100) | 0.921 | <0.001 |
| RBD-IgG | 0.96(0.94, 0.99) | 93.8(86.2, 98.0) | 99.0(94.6, 100) | 0.933 | <0.001 |
| Dot blot | 0.97(0.95, 1.00) | 96.3(89.6, 99.2) | 98.0(93.0, 99.8) | 0.944 | <0.001 |
Positive and Negative Predicted Value and Test Agreement of the Assay Procedure of Rapid Dot Blot at Different Time Points
| Days | PPV, % (95% CI) | NPV, % (95% CI) |
|---|---|---|
| <14 days | 89.5(66.9, 98.7) | 97.0(91.6, 99.4) |
| >14 days | 96.8(89.0, 100) | 100(96.3, 100) |
| Overall | 97.5(91.3, 99.7) | 97.0(91.6, 99.4) |
Abbreviations: PPV, positive predictive value; NPV, negative predictive value.
Comparison of AUC, Sensitivity, Specificity, and Kappa of Dot-Blot with Seropositive or Seronegative Samples at Different Times
| AUC (95% CI) | Sensitivity, % (95% CI) | Specificity (95% CI) | Kappa | p-value | |
|---|---|---|---|---|---|
| <14 days | 0.97(0.92, 1.0) | 94.7(74, 99.9) | 98.0(93.0, 99.8) | 0.943 | <0.001 |
| >14 days | 0.99(0.98, 1.00) | 100(94.1, 100.0) | 98.0(93.0, 99.8) | 0.948 | <0.001 |
| Overall | 0.98(0.97, 1.0) | 98.8(93.3, 100) | 98.0(93.0, 99.8) | 0.946 | <0.001 |
Positive and Negative Predicted Value and Test Agreement of the Dot-Blot Assay with Characterized Seropositive and Seronegative Samples
| Days | PPV, % (95% CI) | NPV, % (95% CI) |
|---|---|---|
| <14 days | 94.4(72.7, 99.9) | 98.8(93.6, 100) |
| >14 days | 96.8(89.0, 100) | 100(96.3, 100) |
| Overall | 99.6(93.5, 100) | 99.0(94.5, 100) |
Abbreviations: PPV, positive predictive value; NPV, negative predictive value; 95% CI, 95% confidence interval.
Figure 5Mean difference in RBD and NCP specific IgG (Cut off) in contrast with intensity scale. The linear regression model was used to estimate the p-value, and the data were shown as mean with a 95% confidence interval.
Figure 6Comparison between dot-blot assay with ELISA and LFIA. The dot blot immunoassay has the advantage of higher sensitivity and specificity while being cost-effective and time-efficient.