Evaluation of Serological Diagnostic Assays for Distinguishing Zika From Dengue Virus Infections in Thailand

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Dato, Pichamon Sittikul, Pimolpachr Sriburin, Jittraporn Rattanamahaphoom, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5057804/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Zika virus (ZIKV) is a mosquito-borne flavivirus that has recently emerged as a global health threat. The emergence of ZIKV has increased the incidence of neonates born with microcephaly or other neurological syndromes. The majority of ZIKV infections are mild or asymptomatic; however, clinical diagnosis is inaccurate. Moreover, Dengue virus cross-reacts with Zika antibodies, which creates problems for the serological diagnosis of ZIKV infections. Zika serological assays are often performed dismally in dengue-endemic areas because of this phenomenon. In this study, we established a Zika/Dengue ELISA Test to improve the differential diagnosis between Zika and Dengue samples. Sixty Zika-positive samples and 120 controls (20 Primary Dengue samples, 80 Secondary Dengue samples, and 20 healthy serum samples were tested using a ZNS1 and DNS1 Indirect ELISA and a commercial IgG ELISA Kit. Different Zika antigens (EDIII, MR766 NS1 and SV0127 NS1) were tested and ROC curves were compared. Among the antigens tested, NS1 yielded the best diagnostic potential with an AUC range of 0.84–0.88, compared with an AUC of 0.77–0.82 for EDIII. The Zika/Dengue OD Ratio also exhibited the best sensitivity (Sn) and specificity (Sp) (58.3% and 79.2% respectively) among the other parameters tested (Sn = 26.7%–28.3% and Sp = 59.2%–79.3%). It also performed better than the commercial kit, which yielded Sn and Sp values of only 26.7% and 74.2%, respectively. The Zika/Dengue OD Ratio has diagnostic potential and better performance compared with commercial ELISA test kits for detecting Zika infections. The combination of two simple ELISAs may be applied for ZIKV serosurveys and to monitor ZIKV infection during pregnancy to understand the epidemiology, pathogenesis, and complications of ZIKV in DENV-endemic areas. Biological sciences/Immunology Biological sciences/Microbiology Health sciences/Diseases Zika virus dengue virus nonstructural protein 1 Serological diagnosis cross-reactivity Figures Figure 1 Figure 2 Figure 3 Figure 4 INTRODUCTION The Zika outbreak of 2015–2016 was centered in Latin America and included Central America, South America, and the Caribbean. Zika is one of the re-emerging flavivirus infections of the Public Health Emergency of International Concern. Severe complications of the virus can occur in newborns, such as stillbirth, congenital malformations, such as microcephaly, and other congenital Zika syndromes (CZS) (Brady et al., 2019 ; Kindhauser, Allen, Frank, Santhana, & Dye, 2016 ). In the general population, neurologic complications, such as acute flaccid paralysis and Guillain–Barré syndrome (GBS), have also been associated with the disease (Bautista, 2019 ; Ioos et al., 2014 ; Theel & Hata, 2018 ). Zika outbreaks can also rapidly disseminate throughout a country or region, prompting the need for surveillance, particularly in hotspot areas. In endemic areas, such as Yap Island, an estimated 73% of the total population is infected (Duffy et al., 2009 ). In contrast, in Latin America, it has spread from one small municipality in Brazil to the entire region. It infected approximately 730,000 people with a 75.66/100,000 cumulative incidence from 2015 to 2016 (Kindhauser et al., 2016 ). Zika virus (ZIKV) is an enveloped RNA virus that belongs to the Flaviviridae family, genus Flavivirus, similar to other clinically relevant flaviviruses, including dengue virus (DENV), Japanese encephalitis virus (JEV), and yellow fever virus (YFV)(Plourde & Bloch, 2016 ).ZIKV is transmitted by mosquitoes, primarily Aedes aegypti and Aedes albopictus . ZIKV can also be transmitted sexually, from mother to fetus, or through blood transfusions (Shan et al., 2016 ). ZIKV is a positive-sense, single-stranded RNA virus, with a genome of approximately 11 kb. It contains three structural proteins: capsid (C), premembrane (prM), and envelope (E), and seven nonstructural proteins: NS1, NS2a, NS2b, NS3, NS4a, NS4b, and NS5b (Ayres et al., 2019 ). The E protein is further divided into domain I (EDI), which is responsible for conformational changes during viral entry, domain II (EDII) with a fusion loop, and domain III (EDIII) for cell receptor binding. The nonstructural protein 1 (NS1) protein is involved in viral replication, immune evasion, and pathogenesis, and is considered an important antigenic marker of ZIKV and other flaviviruses (Silva et al., 2020 ). Antibodies to NS1 are highly sensitive and show limited cross-reactivity. This suggests that NS1 may be used for a differential assay between DENV and ZIKV infections (Stettler et al., 2016 ). Zika virus was originally identified in the Zika Forest of Uganda in 1947 from a rhesus monkey. Subsequently, ZIKV has slowly spread throughout the African and Asian continents. The first outbreak of ZIKV infection occurred in 2007 in Yap State, Micronesia in the western Pacific Ocean (Duffy et al., 2009 ; Wikan & Smith, 2016 ). The first report of its presence in Thailand occurred in 1963 (Pond, 1963 ). In 2016, small outbreaks of ZIKV infection were reported in Singapore ("Outbreak of Zika virus infection in Singapore: an epidemiological, entomological, virological, and clinical analysis," 2017), and in the same year, several hundred cases occurred in Thailand (Khongwichit, Wikan, Auewarakul, & Smith, 2018 ). Some countries on the list are densely populated, such as Pakistan and China, which may result in potential outbreaks in the future. Given these factors, an estimated 2.21 billion people worldwide are still at a high risk of contracting Zika infection (Alaniz, Bacigalupo, & Cattan, 2017 ). According to Thailand's entomological studies, Zika is harbored by other mosquito species, including Culex spp. and Armigeres subalbatus (Phumee et al., 2019 ; Tawatsin et al., 2019 ). ZIKV infection generally causes mild and self-limited illness; however, it can cause Guillain–Barré syndrome in adults and microcephaly in infants born to ZIKV-infected women (Song, Yun, Woolley, & Lee, 2017 ). Therefore, screening for ZIKV infection has a significant impact on pregnancy, particularly during the first trimester (Khongwichit et al., 2018 ; Phatihattakorn et al., 2021 ). The diagnosis of ZIKV infection is challenging because of its homology with another prevalent flavivirus, DENV. Diagnosis of Zika is difficult, particularly in areas with Dengue coendemicity. The viral RNA load for ZIKV infections is lower than that for Dengue, and symptomatic ZIKV infections exhibit a lower viral RNA load than asymptomatic patients (Musso et al., 2017 ). This results in a low rate of detection by molecular testing. Relying on serological tests, however, requires caution because Dengue and Zika exhibit very high cross-reactivity with one another. The diagnostic guidelines from several agencies, such as the CDC (Sharp et al., 2019 ), consider the level of DENV and ZIKV antibodies in contrast with one another when indicating that an infection is truly Zika. RT-PCR for viral RNA is considered the gold standard for diagnosis, whereas the Plaque Reduction Neutralization Test (PRNT) against DENV and ZIKV is the standard serological confirmatory test; however, PRNT is laborious, time-consuming, and requires considerable laboratory expertise. There are a few studies (Chao et al., 2019 ; Denis et al., 2019 ; Tsai et al., 2017 ; Tyson et al., 2019 ) that have proposed simpler serological tests to distinguish Zika from Dengue infection using various measurements, such as the P/N ratio, relative OD, and OD Ratio. However, the applicability of these measurements in Thai samples with known high dengue antibody titers is unknown. In this study, we developed an efficient and practicable strategy that can be used for large-scale ZIKV seroprevalence studies. However, there is still an unmet need for fast, cheap, easy, and reliable diagnostic methods for evaluating Zika infection in Thailand and other Asian countries, particularly for monitoring and surveilling vulnerable pregnant women and neonates. Materials Serum samples We examined 30 pairs of ZIKV-positive acute and convalescent serum samples (60 samples) from a cohort study of the epidemiology of dengue in school-aged children in Ratchaburi province, Thailand, from 2006 to 2009 (Sabchareon et al., 2012 ; Sriburin et al., 2021 ). Furthermore, 60 pairs of ZIKV-negative samples (120 samples) with 10 pairs of primary DENV samples, 40 pairs of secondary DENV samples, and 10 pairs of non-flavivirus samples were included. All ZIKV- and DENV-positive samples were confirmed by reverse transcription PCR in acute sera. All procedures and usage of biobanked specimen were ethically approved before the study by the Ethics Committee of the Faculty of Tropical Medicine, Mahidol University with Ethics certificate number MUTM 2021-040-01. The biobanked samples housed at the TropMed Diagnostic Development Center (TDC), Faculty of Tropical Medicine, Mahidol University were de-identified and no personal information were utilized in the study. Performance of the ELISA validation tests utilizing the ROC curve and measures of sensitivity and specificity also followed STARD guidelines. Production of ZIKVNS1, DENV1-4 NS1, and ZIKV EDIII Full-length ZIKV NS1 genes strain SV0127, MR766 (NCBI accession numbers KU681081.3, and MW143022.1), and full-length of DENV 1–4 NS1 genes from DENV serotypes 1, 2, 3, 4 (NCBI accession numbers AF180817.1, KU725663.1, KU725665.1, and M14931.2) were cloned into a pET28b vector. The EDIII sequence from the ZIKV stain MR766 was synthesized by GenScript (GenScript, Piscataway, NJ, USA) in the pET28a vector (Novagen, Madison, WI, USA). ZIKVNS1, DENV1-4 NS1, and ZIKV EDIII proteins were expressed in E. coli BL21 (DE3) at 25°C overnight, and induced with 1 mM IPTG (Bio Basic, Amherst, NY, USA). After expression, cells were harvested by centrifugation at 4,000 rpm for 30 min at 4°C, the pellets were resuspended in 1X PBS and lysed by sonication (Sonics Vibra cell VCX750, Newtown, CT, USA) for 30 min (pulse on, 5 s; pulse off 5 s). After sonication, the cell lysates were centrifuged at 10,000 rpm for 30 min at 4°C, and then the supernatant was discarded, inclusion bodies were solubilized in a denaturation buffer (50 mM Tris-HCl, pH 8, 0.5 M NaCl, 0.04 M imidazole, and 6 M urea). The proteins were purified using a Protino Ni-NTA (Macherey-Nagel, Düren, Germany) under denaturing conditions. The elution proteins were analyzed using 12% SDS-PAGE, then pooled, dialyzed using dialysis buffer (50 mM Tris-HCl, pH 8, 0.5 M NaCl, and 6 M urea), and kept at -20°C for further use. In-house Indirect IgG ELISA ZIKVNS1, DENVNS1, and EDIII proteins were coated on ELISA plates (Thermo Scientific, Waltham, MA, USA ) at 500ng/60 µl, then the ELISA plate was incubated at 37°C overnight. After incubation, the antigen was removed, and then the plate was washed by rinsing all wells with 200 µl of 1X PBS containing 0.05% Tween20, pH 7.4 six times using an automated ELISA washer (BioTek, Model ELx 50, Winooski, VT, USA). Then, nonspecific binding was blocked by adding 300 µl/well of 1X PBS containing 5% Skim milk, pH 7.4, and incubating at 4°C overnight. After incubation, the plate was washed by rinsing all wells with 200 µl of 1X PBS containing 0.05% Tween20, pH 7.4 six times using an automated ELISA washer (BioTek, Model ELx 50, Winooski, VT, USA). Then, 50 µl/well of test serum (dilute 1:100), positive control, and negative control were added, and incubated at 37°C for 1.30 h. After incubation, the antibody was removed, and the plate was washed by rinsing all wells with 200 µl of 1X PBS containing 0.05% Tween20, pH 7.4 six times using an automated ELISA washer (BioTek, Model ELx 50, Winooski, VT, USA). Then, 50 µl/well of the Goat-anti human IgG-HRP conjugate (dilute 1:20,000) was added, and incubated at 37°C for 1.30 h. After incubation, the plate was washed by rinsing all wells with 200 µl of 1X PBS containing 0.05% Tween20, pH 7.4 six times, then washed again with 200 µl of 1XPBS, pH 7.4 two times using an automated ELISA washer (BioTek, Model ELx 50, Winooski, VT, USA). Substrate (100 µl/well) (SureBlue™TMB Microwell Peroxidase Substrate, Sera care, Milford, MA.) were added and incubated at room temperature for 30 min. The reaction was stopped by adding 50 µl/well of 0.4M H 2 SO 4 . The absorbance was read at 450 nm within 30 min using an automated Elisa reader (Tecan Model Infinite F50, Austria, GmbH). The Zika/Dengue ratio was calculated using the following equations: Measurement Formula OD Ave (OD1 + OD2 + OD3) / 3 OD ratio (ODr) OD Average / OD No Antigen ZIKV/DENV Ratio ODr ZIKV / ODr DENV Interpretation: if Z/D ratio ≥ 2, positive of evidence ZIKV infection Z/D ratio < 2, negative of evidence ZIKV infection Commercial Zika IgG ELISA The EUROIMMUN ZIKV ELISA test kit (EUROIMMUN Co., Lubeck, Germany) is a semiquantitative in vitro assay used for the detection of human IgG-class antibodies against ZIKV in serum. The kit contains microtiter strips, each with eight break-off reagent wells coated with ZIKV antigens. First, 10 µl of the sample was diluted into 1.0 ml of sample buffer. The sample was then transferred to 100-µl calibrators, and the controls or diluted samples were added to individual microplate wells based on the manufacturer’s protocol. The test plate was covered with protective foil and incubated for 60 min at 37°C ± 1°C. After the foil was removed, the test plate was washed three times with a 300 µl/well of wash buffer. For the second step, the conjugate was incubated for 30 min at room temperature, and the plates were washed again. For the third step, the substrate was incubated for 15 min at room temperature, followed by the addition of a stop solution. For the final step, a photometric measurement of the color intensity was made 30 min after adding the stop solution using an ELISA plate reader. The results were evaluated by calculating the ratio of the extinction value of the control or sample to that of the calibrator. Plaque Reduction Neutralization Test (PRNT) LLC-MK2 cells were seeded in 12-well tissue culture plates (Jet Biofil, Guangzhou, China) with 1.5 ml/well (Seeding density ~ 1.5 × 10 5 cells/well). Plates were incubated in an incubator (35 ± 2°C and 5% CO 2 ) for 3 days or until the confluent monolayer of the cells was reached. The monolayer LLC-MK2 cells were washed with 500 µl/well of Hank’s Balance Salt Solution. Then, inoculated with 200 µl of each serum-virus mixture with four-fold serial dilution (1:40 to 1:25600), and incubated at room temperature (18°C to 30°C) on the rocker platform apparatus for 1 hour (± 15 min). After incubation, the serum-virus mixture was aspirated, then the 1 ml of first overlay medium (Hank's BSS, vitamins, amino acids, heat-inactivated bovine serum, L-glutamine, and 7.5% sodium bicarbonate) containing 1.8% low-melting point agarose (Condalab, Madrid, Spain) was added onto the cell monolayer. Plates were Incubated at 35 ± 2°C in a 5% CO2 incubator for 4–5 days. After incubation, plates were stained by adding 1 ml/well of second overlay medium the same as above without fetal bovine serum, and containing 4% Neutral Red (Sigma Aldrich, Burlington, MA, USA), and incubated at 35 ± 2°C in 5% CO 2 incubator overnight. Plaques were counted and PRNT50 was calculated using the probit model with SPSS version 18.0 software (SPSS, Inc., Chicago, IL, USA). If the PRNT50 titer is less than 10 ( 10) the test serum has ZIKV-neutralizing antibody activity. Statistical Tests and Data Processing Results of the ELISA and PRNT assays were tabulated using Excel and then analyzed using IBM SPSS Version 23. Visual graphs and data representations were generated using Prism GraphPad 9.0. a p-value of < 0.05 was considered significant in all the statistical tests done. Results Analysis of the diagnostic potential of Zika antigens for ELISA Three different antigens, SV0127 NS1, MR766 NS1, and EDIII, were used as capture antigens for the ELISA platform, and the diagnostic potential per serological test was measured by generating ROC curves as shown in Supplementary Data (Figure S1 A-C). Tabular data of the ROC curves can be seen in Supplementary Data (Table S1 ) as well. Among the three antigens tested, SV0127 NS1 (ZIKV Asian strain) consistently exhibited the highest AUC values (0.8264–0.8843) compared with MR766 NS1 (ZIKV African strain) (0.7190–0.7727) and EDIII (0.7769–0.8264). represented the best diagnostic potential among the three systems tested. Therefore, SV0127 NS1 (Asian strain) was selected as the capture antigen for the subsequent phase of diagnostic validation, as well as the cutoff points per serological test measurement determined in this step. Comparison of in-house Zika/Dengue ELISA IgG system with Commercial Zika IgG Test Kit After determining the best antigen for the Zika detection ELISA test (SV0127 NS1), the developed in-house Zika ELISA was compared with a commercial ELISA kit for Zika IgG antibody detection with regards to the magnitude of detection of IgG antibodies. A paired T-test of the mean difference in OD values was performed along with a correlation and Bland–Altman plot. In the Paired T-test ( Fig. 1 ) , the mean difference of the OD reading of the two tests for each sample revealed that OD reading of the commercial ELISA kit from in-house ELISA is 0.09997 (95% CI 0.06186 to 0.1381) or almost 0.1 and this difference is statistically significant (p < 0.001) meaning the commercial test kit has consistently higher OD reading of this magnitude for most of the samples. When it comes to diagnostic performance, the in-house Zika/Dengue ELISA system outperformed the commercial Zika IgG detection kit as seen in the comparison of the Area under the Receiver Operating Curve (ROC) as seen in Fig. 2 A and 2 B as well as comparison of sensitivity and specificity (Table 1 ). Table 1 Comparison of Diagnostic Parameters of In-house Zika/Dengue ELISA versus Commercial Zika IgG ELISA Test Parameter vs. Reference Diagnostic Assay RT-PCR (n = 180) Sensitivity Specificity Positive Predictive Value Negative Predictive Value Commercial ELISA 16/60 (26.7%) 89/120 (74.2%) 16/47 (34.0%) 89/133 (66.9%) Zika/Dengue ELISA 35/60 (58.3%) 95/120 (79.2%) 35/60 (58.3%) 95/120 (79.2%) The commercial Zika IgG ELISA only has a ROC curve of 0.5244 which means that there is no effective delineation between positive and negative samples, whereas the in-house Zika/Dengue ELISA has a ROC of 0.7083 denoting a good diagnostic potential. The developed Zika/Dengue ELISA also outperforms the commercial Zika IgG kit in all parameters with higher sensitivity, specificity, PPV and NPV values. Evaluation of the Zika/Dengue ELISA against Plaque Reduction Neutralization Test We conducted an exploratory evaluation of the diagnostic capacity of the Zika/Dengue ELISA against PRNT. However, because of the limited amount of serum and time constraints for performing PRNT, only 30 samples from Phase I were tested, which consisted of 5 pairs of Zika-positive sera, 5 pairs of primary DENV sera, and 5 pairs of secondary DENV sera. The samples were tested against DENV serotypes 1–4 and Zika Virus. Multiple comparison ANOVA for each log PRNT90 titer value per serum yielded a significant mean difference between the values of the mean titer for the secondary Dengue samples compared with Zika-positive and primary dengue sera, particularly for dengue-1 and dengue-2 viruses. Interestingly, the mean differences between the secondary Dengue samples and Zika samples were not significant for Dengue-4 and Zika virus, but titers are significantly higher for DENV-1 and DENV-2. These graphical representations of the Zika log PRNT titers indicate that the magnitude of neutralizing antibody titers against the Dengue viruses is highest in secondary dengue, as expected, followed by Zika-positive samples and primary dengue sera. It was interesting to find that neutralizing antibodies against the Zika virus were not present in primary dengue. In contrast, the number of Zika-neutralizing antibodies for both Zika and secondary dengue was present in almost the same magnitude (Fig. 3 ). The Zika PRNT titer was also correlated with the Zika/Dengue ELISA measurement of each sample. This shows the effectiveness of the Zika/Dengue ELISA in ruling out some dengue samples that register with high Zika-neutralizing antibody titers. A strong positive correlation (r = 0.801, p < 0.05) of Zika neutralizing antibodies (nAbs) and Zika/Dengue ELISA OD among Zika-positive samples is found. In contrast, for both primary and secondary dengue, the correlation was very weak. This is expected because some secondary dengue samples have very high Zika nAbs, but the Zika/Denge ELISA OD distinguishes or offsets these high readings by cross-diagnosing with the Dengue OD ratio. Thus, while some samples would have high nAbs based on PRNT, their Zika/Dengue OD will be low and will not reach the threshold value or cutoff point for a positive interpretation ( Fig. 4 ). The sensitivity, specificity of commercial Zika IgG kit and Zika/Dengue ELISA is also measured against PRNT results ( Tables 2 and 3 ) . It can be seen that none of the primary or secondary dengue samples were classified as Zika-positive by the PRNT criteria, yielding a perfect specificity; however, the sensitivity is very low. Conversely, the two ELISA systems had the same sensitivity, but the Zika/Dengue OD Ratio had better specificity compared with the commercial IgG test kit (80.95% vs. 76.47%) ( Table 3 ) . Table 2 Zika seropositivity of samples per serological criteria / test Serological diagnosis of Zika-positivity Serum category Zika positive (n = 10) Primary Dengue (n = 10) Secondary Dengue (n = 10) PRNT 90 WHO Criteria (PRNT90 titer of ≥ 20 against Zika, and/or a ratio of ≥ 4 compared to other flavivirus PRNT titers) 2/10 (20%) 0/10 0/10 PRNT 90 CDC Criteria (PRNT90 titer ≥ 10 against Zika, and <10 for Dengue or other flavivirus) 1/10 (10%) 0/10 0/10 Commercial Zika IgG ELISA 6/10 (60%) 0/10 7/10 (70%) In-house Zika/Dengue ELISA OD Ratio 6/10 (60%) 0/10 3/10 (30%) Table 3 Sensitivity, Specificity, PPV and NPV of Serological Tests versus RT-PCR Serological Test Diagnostic Validation against RT-PCR results (n = 30) Sensitivity Specificity PPV NPV PRNT 90 WHO Criteria (2/10) 20% (20/20) 100% (2/2) 100% (20/28) 71.43% PRNT 90 CDC Criteria (1/10) 10% (20/20) 100% (1/1) 100% (20/29) 68.97% EuroImmune Zika IgG (6/10) 60% (13/20) 65% (6/13) 46.15% (13/17) 76.47% Z/D ELISA OD Ratio (6/10) 60% (17/20) 85% (6/9) 66.67% (17/21) 80.95% Discussion Serological ZIKV diagnosis is challenging in dengue-endemic areas. This is highlighted in this study wherein cross-reactivity of dengue-positive sera affects accurate Zika diagnosis. Despite the best performing antigen (NS1) based on the phase 1 of the study was used in the in-house ELISA, there is still false positivity noted with dengue-positive samples. The low specificity may be explained by the cross-reactivity of the antibody between DENV and ZIKV (Silva et al., 2020 ). An interesting aspect of serological assays, specifically ELISA systems, is that there are multiple ways of analyzing and interpreting the results. In the present study, calculating the Zika/Dengue OD ratio proved that the established indirect ELISA is not inferior to the commercial test kit in terms of antibody detection. The performance was comparable, and yet, regarding diagnostic validity, the Zika/Dengue OD Ratio was far superior as it consistently outperformed the commercial test kit. This is understandable because the standalone detection of Zika antibodies can produce false-positive results, particularly in dengue-endemic areas. The commercial Zika IgG test kit used in this study is one of the best performing test kits with a manufacturer reported sensitivity and specificity of 100% and 97% respectively tested in European population. However, testing its performance against a dengue-endemic country such as Thailand shows a lower diagnostic performance which is in consistently found in other studies as well (Didye, 2020; Kikuti et al., 2018 ; Low et al., 2021 ; Machado Portilho et al., 2020 ; Morales et al., 2021 ). This indicates that the cross-reactivity of secondary dengue antibodies may be a challenge to the diagnostic validity of commercial serological tests. The lower specificity in the subjects after secondary DENV infection may be explained by the characteristic antibody response directed against the antigens of the flavivirus group after secondary DENV infection, whereas the antibody response after primary DENV infection is predominantly against a type-specific determinant (Sirinam et al., 2022 ). When it comes to serological assays, Plaque Reduction Neutralization Tests is the gold standard recognized. A comparison of PRNT and the Zika/Dengue OD ratio of the Zika antibody titers in acute and convalescent phase sera revealed no significant difference. Some studies have examined the kinetics of virology and antibody production in Zika infections and found that Zika has lower viral copies, particularly in dengue-primed or prior dengue-infected patients (Musso et al., 2014 ; Musso et al., 2017 ; Sánchez-Arcila et al., 2020 ; Santiago et al., 2019 ; Terzian et al., 2017 ), which results in a lower immune response (Collins et al., 2017 ; Langerak et al., 2021 ; Sánchez-Arcila et al., 2020 ; Terzian et al., 2017 ). As expected from a confirmatory test, the PRNT assay had a specificity of 100% for both the WHO and CDC criteria, and none of the dengue samples were misdiagnosed. The criteria set poses very low sensitivity; however, it causes us to question the usefulness or applicability of the current Zika PRNT interpretation cut-offs in dengue-endemic areas, such as Thailand and the rest of Southeast Asia. The strength of ZIKV PRNT is its high specificity (100%); however, it is laborious, time-consuming, and requires laboratory expertise. A test using the OD ratio of ZIKV-NS1 versus DENV-NS1 provides similar specificity to ZIKV PRNT and higher sensitivity (58.3%). Primary testing using an NS1-IgG ELISA assay, followed by a Zika/Dengue OD ratio of positive ELISA results, can decrease the cost of ZIKV PRNT but does not increase the sensitivity. Considering that ZIKV NS1-IgG ELISA is cost-effective because it uses an in-house NS1 protein and provides relatively high sensitivity and specificity, we propose this test as the test of choice for Zika sero-epidemiological studies. In areas where the incidence of ZIKV is very low and the incidence of DENV is very high, a confirmation of ZIKV infection using ZIKV PRNT or the OD ratio of ZIKV-NS1 versus DENV-NS1 may be used to increase the accuracy of the study. Conclusion The results of this study indicate that the combination of two simple ELISAs (DENV-NS1 and ZIKV-NS1) can be applied as a cost-effective methodology for ZIKV serosurveys. This methodology was not designed or intended for individual diagnosis. This represents a convenient, rapid, and cost-effective method to process a large series of samples to monitor ZIKV infection during pregnancy to understand the epidemiology, pathogenesis, and complications of ZIKV in DENV-endemic areas. Declarations ACKNOWLEDGMENTS : This study was supported by the Faculty of Tropical Medicine, Mahidol University, Thailand, and the German Academic Exchange Service (DAAD), Germany, Funding program: In-Country/In-Region Scholarships Program at SEAMEO TROPMED Network Regional Office Thailand. CONFLICT OF INTEREST STATEMENT : The authors declare no conflicts of interest. DATA AVAILABILITY STATEMENT: The datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request. AUTHOR CONTRIBUTIONS M.D. Conceptualization, Data curation, Formal analysis, Investigation, Methodology, and Writing – original draft. P.Si. 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ARTHROPOD-BORNE VIRUS ANTIBODIES IN SERA FROM RESIDENTS OF SOUTH-EAST ASIA. Trans R Soc Trop Med Hyg, 57 , 364-371. doi:10.1016/0035-9203(63)90100-7 Sabchareon, A., Sirivichayakul, C., Limkittikul, K., Chanthavanich, P., Suvannadabba, S., Jiwariyavej, V., . . . Letson, G. W. (2012). Dengue infection in children in Ratchaburi, Thailand: a cohort study. I. Epidemiology of symptomatic acute dengue infection in children, 2006-2009. PLoS Negl Trop Dis, 6 (7), e1732. doi:10.1371/journal.pntd.0001732 Sánchez-Arcila, J. C., Badolato-Correa, J., de Souza, T. M. A., Paiva, I. A., Barbosa, L. S., Nunes, P. C. G., . . . de Oliveira-Pinto, L. M. (2020). Clinical, Virological, and Immunological Profiles of DENV, ZIKV, and/or CHIKV-Infected Brazilian Patients. Intervirology, 63 (1-6), 33-45. doi:10.1159/000510223 Santiago, G. A., Sharp, T. M., Rosenberg, E., Sosa, C., II, Alvarado, L., Paz-Bailey, G., & Muñoz-Jordán, J. L. (2019). Prior Dengue Virus Infection Is Associated With Increased Viral Load in Patients Infected With Dengue but Not Zika Virus. Open Forum Infect Dis, 6 (7). doi:10.1093/ofid/ofz320 Shan, C., Xie, X., Barrett, A. D. T., Garcia-Blanco, M. A., Tesh, R. B., Vasconcelos, P. F. d. C., . . . Shi, P.-Y. (2016). Zika Virus: Diagnosis, Therapeutics, and Vaccine. ACS Infectious Diseases, 2 (3), 170-172. doi:10.1021/acsinfecdis.6b00030 Sharp, T. M., Fischer, M., Muñoz-Jordán, J. L., Paz-Bailey, G., Staples, J. E., Gregory, C. J., & Waterman, S. H. (2019). Dengue and Zika Virus Diagnostic Testing for Patients with a Clinically Compatible Illness and Risk for Infection with Both Viruses. MMWR Recomm Rep, 68 (1), 1-10. doi:10.15585/mmwr.rr6801a1 Silva, I. B. B., da Silva, A. S., Cunha, M. S., Cabral, A. D., de Oliveira, K. C. A., Gaspari, E., & Prudencio, C. R. (2020). Zika virus serological diagnosis: commercial tests and monoclonal antibodies as tools. J Venom Anim Toxins Incl Trop Dis, 26 , e20200019. doi:10.1590/1678-9199-jvatitd-2020-0019 Sirinam, S., Chatchen, S., Arunsodsai, W., Guharat, S., & Limkittikul, K. (2022). Seroprevalence of Zika Virus in Amphawa District, Thailand, after the 2016 Pandemic. Viruses, 14(3). doi:10.3390/v14030476 Song, B. H., Yun, S. I., Woolley, M., & Lee, Y. M. (2017). Zika virus: History, epidemiology, transmission, and clinical presentation. J Neuroimmunol, 308 , 50-64. doi:10.1016/j.jneuroim.2017.03.001 Sriburin, P., Sittikul, P., Kosoltanapiwat, N., Sirinam, S., Arunsodsai, W., Sirivichayakul, C., . . . Chatchen, S. (2021). Incidence of Zika Virus Infection from a Dengue Epidemiological Study of Children in Ratchaburi Province, Thailand. Viruses, 13 (9). doi:10.3390/v13091802 Stettler, K., Beltramello, M., Espinosa, D. A., Graham, V., Cassotta, A., Bianchi, S., . . . Corti, D. (2016). Specificity, cross-reactivity, and function of antibodies elicited by Zika virus infection. Science, 353 (6301), 823-826. doi:10.1126/science.aaf8505 Tawatsin, A., Phumee, A., Thavara, U., Sirisopa, P., Ritthison, W., Thammakosol, K., . . . Siriyasatien, P. (2019). High infection rate of Zika virus in mosquitoes collected from an area of active Zika virus transmission in eastern Thailand. The Thai Journal of Veterinary Medicine, 48 (4), 551-558. Retrieved from https://he01.tci-thaijo.org/index.php/tjvm/article/view/176923 Terzian, A. C. B., Schanoski, A. S., Mota, M. T. O., da Silva, R. A., Estofolete, C. F., Colombo, T. E., . . . Nogueira, M. L. (2017). Viral Load and Cytokine Response Profile Does Not Support Antibody-Dependent Enhancement in Dengue-Primed Zika Virus-Infected Patients. Clin Infect Dis, 65 (8), 1260-1265. doi:10.1093/cid/cix558 Theel, E. S., & Hata, D. J. (2018). Diagnostic Testing for Zika Virus: a Postoutbreak Update. J Clin Microbiol, 56 (4). doi:10.1128/jcm.01972-17 Tsai, W. Y., Youn, H. H., Brites, C., Tsai, J. J., Tyson, J., Pedroso, C., . . . Wang, W. K. (2017). Distinguishing Secondary Dengue Virus Infection From Zika Virus Infection With Previous Dengue by a Combination of 3 Simple Serological Tests. Clin Infect Dis, 65 (11), 1829-1836. doi:10.1093/cid/cix672 Tyson, J., Tsai, W. Y., Tsai, J. J., Brites, C., Mässgård, L., Ha Youn, H., . . . Wang, W. K. (2019). Combination of Nonstructural Protein 1-Based Enzyme-Linked Immunosorbent Assays Can Detect and Distinguish Various Dengue Virus and Zika Virus Infections. J Clin Microbiol, 57 (2). doi:10.1128/jcm.01464-18 Wikan, N., & Smith, D. R. (2016). Zika virus: history of a newly emerging arbovirus. Lancet Infect Dis, 16 (7), e119-e126. doi:10.1016/s1473-3099(16)30010-x Additional Declarations No competing interests reported. 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Comparison of Area under Receiver Operating Characteristic (ROC Curve) of the in-house Zika/Dengue ELISA system and a commercial Zika IgG test kit\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-5057804/v1/e9d02fc5a50bf27d68491214.png"},{"id":79905415,"identity":"b07efe9c-ec39-40e7-b97a-ba089b175ff1","added_by":"auto","created_at":"2025-04-04 10:54:30","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":57241,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMean Log PRNT\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e90\u003c/strong\u003e\u003c/sub\u003e\u003cstrong\u003e Titer per Virus and Serum Category\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-5057804/v1/042f3dd0cefdae737e6c6457.png"},{"id":79904211,"identity":"8a674ed0-89da-4657-b8bf-dffea05df97b","added_by":"auto","created_at":"2025-04-04 10:46:30","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":91093,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCorrelation of Zika PRNT\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e90 \u003c/strong\u003e\u003c/sub\u003e\u003cstrong\u003eand Zika/Dengue ELISA ratio values based on serum classification\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-5057804/v1/59ae559a837a0d3c3c7ddfd1.png"},{"id":88490932,"identity":"71337d62-6085-4da3-b191-a924ce453ad2","added_by":"auto","created_at":"2025-08-07 04:16:41","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1231975,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5057804/v1/67b2b544-a577-4a1f-bb52-153eaca251d5.pdf"},{"id":79904213,"identity":"1ed513ed-36cf-49b4-966b-2cc6ea5e2d25","added_by":"auto","created_at":"2025-04-04 10:46:30","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":175893,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryData.docx","url":"https://assets-eu.researchsquare.com/files/rs-5057804/v1/91ad388e61a370f75a7e7d5d.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eEvaluation of Serological Diagnostic Assays for Distinguishing Zika From Dengue Virus Infections in Thailand\u003c/p\u003e","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eThe Zika outbreak of 2015\u0026ndash;2016 was centered in Latin America and included Central America, South America, and the Caribbean. Zika is one of the re-emerging flavivirus infections of the Public Health Emergency of International Concern. Severe complications of the virus can occur in newborns, such as stillbirth, congenital malformations, such as microcephaly, and other congenital Zika syndromes (CZS) (Brady et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Kindhauser, Allen, Frank, Santhana, \u0026amp; Dye, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). In the general population, neurologic complications, such as acute flaccid paralysis and Guillain\u0026ndash;Barr\u0026eacute; syndrome (GBS), have also been associated with the disease (Bautista, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Ioos et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Theel \u0026amp; Hata, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Zika outbreaks can also rapidly disseminate throughout a country or region, prompting the need for surveillance, particularly in hotspot areas. In endemic areas, such as Yap Island, an estimated 73% of the total population is infected (Duffy et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). In contrast, in Latin America, it has spread from one small municipality in Brazil to the entire region. It infected approximately 730,000 people with a 75.66/100,000 cumulative incidence from 2015 to 2016 (Kindhauser et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eZika virus (ZIKV) is an enveloped RNA virus that belongs to the Flaviviridae family, genus Flavivirus, similar to other clinically relevant flaviviruses, including dengue virus (DENV), Japanese encephalitis virus (JEV), and yellow fever virus (YFV)(Plourde \u0026amp; Bloch, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).ZIKV is transmitted by mosquitoes, primarily \u003cem\u003eAedes aegypti\u003c/em\u003e and \u003cem\u003eAedes albopictus\u003c/em\u003e. ZIKV can also be transmitted sexually, from mother to fetus, or through blood transfusions (Shan et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). ZIKV is a positive-sense, single-stranded RNA virus, with a genome of approximately 11 kb. It contains three structural proteins: capsid (C), premembrane (prM), and envelope (E), and seven nonstructural proteins: NS1, NS2a, NS2b, NS3, NS4a, NS4b, and NS5b (Ayres et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The E protein is further divided into domain I (EDI), which is responsible for conformational changes during viral entry, domain II (EDII) with a fusion loop, and domain III (EDIII) for cell receptor binding. The nonstructural protein 1 (NS1) protein is involved in viral replication, immune evasion, and pathogenesis, and is considered an important antigenic marker of ZIKV and other flaviviruses (Silva et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Antibodies to NS1 are highly sensitive and show limited cross-reactivity. This suggests that NS1 may be used for a differential assay between DENV and ZIKV infections (Stettler et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Zika virus was originally identified in the Zika Forest of Uganda in 1947 from a rhesus monkey. Subsequently, ZIKV has slowly spread throughout the African and Asian continents. The first outbreak of ZIKV infection occurred in 2007 in Yap State, Micronesia in the western Pacific Ocean (Duffy et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Wikan \u0026amp; Smith, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). The first report of its presence in Thailand occurred in 1963 (Pond, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e1963\u003c/span\u003e). In 2016, small outbreaks of ZIKV infection were reported in Singapore (\"Outbreak of Zika virus infection in Singapore: an epidemiological, entomological, virological, and clinical analysis,\" 2017), and in the same year, several hundred cases occurred in Thailand (Khongwichit, Wikan, Auewarakul, \u0026amp; Smith, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSome countries on the list are densely populated, such as Pakistan and China, which may result in potential outbreaks in the future. Given these factors, an estimated 2.21\u0026nbsp;billion people worldwide are still at a high risk of contracting Zika infection (Alaniz, Bacigalupo, \u0026amp; Cattan, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). According to Thailand's entomological studies, Zika is harbored by other mosquito species, including \u003cem\u003eCulex spp.\u003c/em\u003e and \u003cem\u003eArmigeres subalbatus\u003c/em\u003e (Phumee et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Tawatsin et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eZIKV infection generally causes mild and self-limited illness; however, it can cause Guillain\u0026ndash;Barr\u0026eacute; syndrome in adults and microcephaly in infants born to ZIKV-infected women (Song, Yun, Woolley, \u0026amp; Lee, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Therefore, screening for ZIKV infection has a significant impact on pregnancy, particularly during the first trimester (Khongwichit et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Phatihattakorn et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe diagnosis of ZIKV infection is challenging because of its homology with another prevalent flavivirus, DENV. Diagnosis of Zika is difficult, particularly in areas with Dengue coendemicity. The viral RNA load for ZIKV infections is lower than that for Dengue, and symptomatic ZIKV infections exhibit a lower viral RNA load than asymptomatic patients (Musso et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). This results in a low rate of detection by molecular testing. Relying on serological tests, however, requires caution because Dengue and Zika exhibit very high cross-reactivity with one another. The diagnostic guidelines from several agencies, such as the CDC (Sharp et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), consider the level of DENV and ZIKV antibodies in contrast with one another when indicating that an infection is truly Zika. RT-PCR for viral RNA is considered the gold standard for diagnosis, whereas the Plaque Reduction Neutralization Test (PRNT) against DENV and ZIKV is the standard serological confirmatory test; however, PRNT is laborious, time-consuming, and requires considerable laboratory expertise.\u003c/p\u003e \u003cp\u003eThere are a few studies (Chao et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Denis et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Tsai et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Tyson et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) that have proposed simpler serological tests to distinguish Zika from Dengue infection using various measurements, such as the P/N ratio, relative OD, and OD Ratio. However, the applicability of these measurements in Thai samples with known high dengue antibody titers is unknown. In this study, we developed an efficient and practicable strategy that can be used for large-scale ZIKV seroprevalence studies. However, there is still an unmet need for fast, cheap, easy, and reliable diagnostic methods for evaluating Zika infection in Thailand and other Asian countries, particularly for monitoring and surveilling vulnerable pregnant women and neonates.\u003c/p\u003e"},{"header":"Materials","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eSerum samples\u003c/h2\u003e \u003cp\u003eWe examined 30 pairs of ZIKV-positive acute and convalescent serum samples (60 samples) from a cohort study of the epidemiology of dengue in school-aged children in Ratchaburi province, Thailand, from 2006 to 2009 (Sabchareon et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Sriburin et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Furthermore, 60 pairs of ZIKV-negative samples (120 samples) with 10 pairs of primary DENV samples, 40 pairs of secondary DENV samples, and 10 pairs of non-flavivirus samples were included. All ZIKV- and DENV-positive samples were confirmed by reverse transcription PCR in acute sera. All procedures and usage of biobanked specimen were ethically approved before the study by the Ethics Committee of the Faculty of Tropical Medicine, Mahidol University with Ethics certificate number MUTM 2021-040-01. The biobanked samples housed at the TropMed Diagnostic Development Center (TDC), Faculty of Tropical Medicine, Mahidol University were de-identified and no personal information were utilized in the study. Performance of the ELISA validation tests utilizing the ROC curve and measures of sensitivity and specificity also followed STARD guidelines.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eProduction of ZIKVNS1, DENV1-4 NS1, and ZIKV EDIII\u003c/h2\u003e \u003cp\u003eFull-length ZIKV NS1 genes strain SV0127, MR766 (NCBI accession numbers KU681081.3, and MW143022.1), and full-length of DENV 1\u0026ndash;4 NS1 genes from DENV serotypes 1, 2, 3, 4 (NCBI accession numbers AF180817.1, KU725663.1, KU725665.1, and M14931.2) were cloned into a pET28b vector. The EDIII sequence from the ZIKV stain MR766 was synthesized by GenScript (GenScript, Piscataway, NJ, USA) in the pET28a vector (Novagen, Madison, WI, USA). ZIKVNS1, DENV1-4 NS1, and ZIKV EDIII proteins were expressed in \u003cem\u003eE. coli\u003c/em\u003e BL21 (DE3) at 25\u0026deg;C overnight, and induced with 1 mM IPTG (Bio Basic, Amherst, NY, USA). After expression, cells were harvested by centrifugation at 4,000 rpm for 30 min at 4\u0026deg;C, the pellets were resuspended in 1X PBS and lysed by sonication (Sonics Vibra cell VCX750, Newtown, CT, USA) for 30 min (pulse on, 5 s; pulse off 5 s). After sonication, the cell lysates were centrifuged at 10,000 rpm for 30 min at 4\u0026deg;C, and then the supernatant was discarded, inclusion bodies were solubilized in a denaturation buffer (50 mM Tris-HCl, pH 8, 0.5 M NaCl, 0.04 M imidazole, and 6 M urea). The proteins were purified using a Protino Ni-NTA (Macherey-Nagel, D\u0026uuml;ren, Germany) under denaturing conditions. The elution proteins were analyzed using 12% SDS-PAGE, then pooled, dialyzed using dialysis buffer (50 mM Tris-HCl, pH 8, 0.5 M NaCl, and 6 M urea), and kept at -20\u0026deg;C for further use.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eIn-house Indirect IgG ELISA\u003c/h2\u003e \u003cp\u003eZIKVNS1, DENVNS1, and EDIII proteins were coated on ELISA plates (Thermo Scientific, Waltham, MA, USA ) at 500ng/60 \u0026micro;l, then the ELISA plate was incubated at 37\u0026deg;C overnight. After incubation, the antigen was removed, and then the plate was washed by rinsing all wells with 200 \u0026micro;l of 1X PBS containing 0.05% Tween20, pH 7.4 six times using an automated ELISA washer (BioTek, Model ELx 50, Winooski, VT, USA). Then, nonspecific binding was blocked by adding 300 \u0026micro;l/well of 1X PBS containing 5% Skim milk, pH 7.4, and incubating at 4\u0026deg;C overnight. After incubation, the plate was washed by rinsing all wells with 200 \u0026micro;l of 1X PBS containing 0.05% Tween20, pH 7.4 six times using an automated ELISA washer (BioTek, Model ELx 50, Winooski, VT, USA). Then, 50 \u0026micro;l/well of test serum (dilute 1:100), positive control, and negative control were added, and incubated at 37\u0026deg;C for 1.30 h. After incubation, the antibody was removed, and the plate was washed by rinsing all wells with 200 \u0026micro;l of 1X PBS containing 0.05% Tween20, pH 7.4 six times using an automated ELISA washer (BioTek, Model ELx 50, Winooski, VT, USA). Then, 50 \u0026micro;l/well of the Goat-anti human IgG-HRP conjugate (dilute 1:20,000) was added, and incubated at 37\u0026deg;C for 1.30 h. After incubation, the plate was washed by rinsing all wells with 200 \u0026micro;l of 1X PBS containing 0.05% Tween20, pH 7.4 six times, then washed again with 200 \u0026micro;l of 1XPBS, pH 7.4 two times using an automated ELISA washer (BioTek, Model ELx 50, Winooski, VT, USA). Substrate (100 \u0026micro;l/well) (SureBlue\u0026trade;TMB Microwell Peroxidase Substrate, Sera care, Milford, MA.) were added and incubated at room temperature for 30 min. The reaction was stopped by adding 50 \u0026micro;l/well of 0.4M H\u003csub\u003e2\u003c/sub\u003eSO\u003csub\u003e4\u003c/sub\u003e. The absorbance was read at 450 nm within 30 min using an automated Elisa reader (Tecan Model Infinite F50, Austria, GmbH). The Zika/Dengue ratio was calculated using the following equations:\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMeasurement\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFormula\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOD\u003csub\u003eAve\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(OD1\u0026thinsp;+\u0026thinsp;OD2\u0026thinsp;+\u0026thinsp;OD3) / 3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOD ratio (ODr)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOD\u003csub\u003eAverage\u003c/sub\u003e / OD \u003csub\u003eNo Antigen\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eZIKV/DENV Ratio\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eODr \u003csub\u003eZIKV\u003c/sub\u003e / ODr \u003csub\u003eDENV\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eInterpretation:\u003c/p\u003e \u003cp\u003eif Z/D ratio\u0026thinsp;\u0026ge;\u0026thinsp;2, positive of evidence ZIKV infection\u003c/p\u003e \u003cp\u003eZ/D ratio\u0026thinsp;\u0026lt;\u0026thinsp;2, negative of evidence ZIKV infection\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eCommercial Zika IgG ELISA\u003c/h2\u003e \u003cp\u003eThe EUROIMMUN ZIKV ELISA test kit (EUROIMMUN Co., Lubeck, Germany) is a semiquantitative in vitro assay used for the detection of human IgG-class antibodies against ZIKV in serum. The kit contains microtiter strips, each with eight break-off reagent wells coated with ZIKV antigens. First, 10 \u0026micro;l of the sample was diluted into 1.0 ml of sample buffer. The sample was then transferred to 100-\u0026micro;l calibrators, and the controls or diluted samples were added to individual microplate wells based on the manufacturer\u0026rsquo;s protocol. The test plate was covered with protective foil and incubated for 60 min at 37\u0026deg;C\u0026thinsp;\u0026plusmn;\u0026thinsp;1\u0026deg;C. After the foil was removed, the test plate was washed three times with a 300 \u0026micro;l/well of wash buffer. For the second step, the conjugate was incubated for 30 min at room temperature, and the plates were washed again. For the third step, the substrate was incubated for 15 min at room temperature, followed by the addition of a stop solution. For the final step, a photometric measurement of the color intensity was made 30 min after adding the stop solution using an ELISA plate reader. The results were evaluated by calculating the ratio of the extinction value of the control or sample to that of the calibrator.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003ePlaque Reduction Neutralization Test (PRNT)\u003c/h2\u003e \u003cp\u003eLLC-MK2 cells were seeded in 12-well tissue culture plates (Jet Biofil, Guangzhou, China) with 1.5 ml/well (Seeding density\u0026thinsp;~\u0026thinsp;1.5 \u0026times; 10\u003csup\u003e5\u003c/sup\u003e cells/well). Plates were incubated in an incubator (35\u0026thinsp;\u0026plusmn;\u0026thinsp;2\u0026deg;C and 5% CO\u003csub\u003e2\u003c/sub\u003e) for 3 days or until the confluent monolayer of the cells was reached. The monolayer LLC-MK2 cells were washed with 500 \u0026micro;l/well of Hank\u0026rsquo;s Balance Salt Solution. Then, inoculated with 200 \u0026micro;l of each serum-virus mixture with four-fold serial dilution (1:40 to 1:25600), and incubated at room temperature (18\u0026deg;C to 30\u0026deg;C) on the rocker platform apparatus for 1 hour (\u0026plusmn;\u0026thinsp;15 min). After incubation, the serum-virus mixture was aspirated, then the 1 ml of first overlay medium (Hank's BSS, vitamins, amino acids, heat-inactivated bovine serum, L-glutamine, and 7.5% sodium bicarbonate) containing 1.8% low-melting point agarose (Condalab, Madrid, Spain) was added onto the cell monolayer. Plates were Incubated at 35\u0026thinsp;\u0026plusmn;\u0026thinsp;2\u0026deg;C in a 5% CO2 incubator for 4\u0026ndash;5 days. After incubation, plates were stained by adding 1 ml/well of second overlay medium the same as above without fetal bovine serum, and containing 4% Neutral Red (Sigma Aldrich, Burlington, MA, USA), and incubated at 35\u0026thinsp;\u0026plusmn;\u0026thinsp;2\u0026deg;C in 5% CO\u003csub\u003e2\u003c/sub\u003e incubator overnight. Plaques were counted and PRNT50 was calculated using the probit model with SPSS version 18.0 software (SPSS, Inc., Chicago, IL, USA). If the PRNT50 titer is less than 10 (\u0026lt;\u0026thinsp;10) the test serum has no ZIKV neutralizing antibody whereas if the PRNT50 titer is more than 10 (\u0026gt;\u0026thinsp;10) the test serum has ZIKV-neutralizing antibody activity.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Tests and Data Processing\u003c/h2\u003e \u003cp\u003eResults of the ELISA and PRNT assays were tabulated using Excel and then analyzed using IBM SPSS Version 23. Visual graphs and data representations were generated using Prism GraphPad 9.0. a p-value of \u0026lt;\u0026thinsp;0.05 was considered significant in all the statistical tests done.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\n \u003ch2\u003eAnalysis of the diagnostic potential of Zika antigens for ELISA\u003c/h2\u003e\n \u003cp\u003eThree different antigens, SV0127 NS1, MR766 NS1, and EDIII, were used as capture antigens for the ELISA platform, and the diagnostic potential per serological test was measured by generating ROC curves as shown in Supplementary Data (Figure \u003cspan class=\"InternalRef\"\u003eS1\u003c/span\u003e A-C). Tabular data of the ROC curves can be seen in Supplementary Data (Table \u003cspan class=\"InternalRef\"\u003eS1\u003c/span\u003e) as well. Among the three antigens tested, SV0127 NS1 (ZIKV Asian strain) consistently exhibited the highest AUC values (0.8264\u0026ndash;0.8843) compared with MR766 NS1 (ZIKV African strain) (0.7190\u0026ndash;0.7727) and EDIII (0.7769\u0026ndash;0.8264). represented the best diagnostic potential among the three systems tested. Therefore, SV0127 NS1 (Asian strain) was selected as the capture antigen for the subsequent phase of diagnostic validation, as well as the cutoff points per serological test measurement determined in this step.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n \u003ch2\u003eComparison of in-house Zika/Dengue ELISA IgG system with Commercial Zika IgG Test Kit\u003c/h2\u003e\n \u003cp\u003eAfter determining the best antigen for the Zika detection ELISA test (SV0127 NS1), the developed in-house Zika ELISA was compared with a commercial ELISA kit for Zika IgG antibody detection with regards to the magnitude of detection of IgG antibodies. A paired T-test of the mean difference in OD values was performed along with a correlation and Bland\u0026ndash;Altman plot. In the Paired T-test \u003cstrong\u003e(\u003c/strong\u003eFig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e\u003cstrong\u003e)\u003c/strong\u003e, the mean difference of the OD reading of the two tests for each sample revealed that OD reading of the commercial ELISA kit from in-house ELISA is 0.09997 (95% CI 0.06186 to 0.1381) or almost 0.1 and this difference is statistically significant (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) meaning the commercial test kit has consistently higher OD reading of this magnitude for most of the samples.\u003c/p\u003e\n \u003cp\u003eWhen it comes to diagnostic performance, the in-house Zika/Dengue ELISA system outperformed the commercial Zika IgG detection kit as seen in the comparison of the Area under the Receiver Operating Curve (ROC) as seen in Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eA and \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eB as well as comparison of sensitivity and specificity (Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eComparison of Diagnostic Parameters of In-house Zika/Dengue ELISA versus Commercial Zika IgG ELISA\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"5\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eTest Parameter\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"4\"\u003e\n \u003cp\u003evs. Reference Diagnostic Assay RT-PCR\u003c/p\u003e\n \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;180)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSensitivity\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSpecificity\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePositive Predictive Value\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNegative Predictive Value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCommercial ELISA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e16/60 (26.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e89/120 (74.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e16/47 (34.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e89/133 (66.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eZika/Dengue ELISA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e35/60 (58.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e95/120 (79.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e35/60 (58.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e95/120 (79.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003eThe commercial Zika IgG ELISA only has a ROC curve of 0.5244 which means that there is no effective delineation between positive and negative samples, whereas the in-house Zika/Dengue ELISA has a ROC of 0.7083 denoting a good diagnostic potential. The developed Zika/Dengue ELISA also outperforms the commercial Zika IgG kit in all parameters with higher sensitivity, specificity, PPV and NPV values.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\n \u003ch2\u003eEvaluation of the Zika/Dengue ELISA against Plaque Reduction Neutralization Test\u003c/h2\u003e\n \u003cp\u003eWe conducted an exploratory evaluation of the diagnostic capacity of the Zika/Dengue ELISA against PRNT. However, because of the limited amount of serum and time constraints for performing PRNT, only 30 samples from Phase I were tested, which consisted of 5 pairs of Zika-positive sera, 5 pairs of primary DENV sera, and 5 pairs of secondary DENV sera. The samples were tested against DENV serotypes 1\u0026ndash;4 and Zika Virus. Multiple comparison ANOVA for each log PRNT90 titer value per serum yielded a significant mean difference between the values of the mean titer for the secondary Dengue samples compared with Zika-positive and primary dengue sera, particularly for dengue-1 and dengue-2 viruses. Interestingly, the mean differences between the secondary Dengue samples and Zika samples were not significant for Dengue-4 and Zika virus, but titers are significantly higher for DENV-1 and DENV-2. These graphical representations of the Zika log PRNT titers indicate that the magnitude of neutralizing antibody titers against the Dengue viruses is highest in secondary dengue, as expected, followed by Zika-positive samples and primary dengue sera. It was interesting to find that neutralizing antibodies against the Zika virus were not present in primary dengue. In contrast, the number of Zika-neutralizing antibodies for both Zika and secondary dengue was present in almost the same magnitude (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003eThe Zika PRNT titer was also correlated with the Zika/Dengue ELISA measurement of each sample. This shows the effectiveness of the Zika/Dengue ELISA in ruling out some dengue samples that register with high Zika-neutralizing antibody titers. A strong positive correlation (r\u0026thinsp;=\u0026thinsp;0.801, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) of Zika neutralizing antibodies (nAbs) and Zika/Dengue ELISA OD among Zika-positive samples is found. In contrast, for both primary and secondary dengue, the correlation was very weak. This is expected because some secondary dengue samples have very high Zika nAbs, but the Zika/Denge ELISA OD distinguishes or offsets these high readings by cross-diagnosing with the Dengue OD ratio. Thus, while some samples would have high nAbs based on PRNT, their Zika/Dengue OD will be low and will not reach the threshold value or cutoff point for a positive interpretation \u003cstrong\u003e(\u003c/strong\u003eFig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e\u003cstrong\u003e).\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eThe sensitivity, specificity of commercial Zika IgG kit and Zika/Dengue ELISA is also measured against PRNT results \u003cstrong\u003e(\u003c/strong\u003eTables \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e and \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e\u003cstrong\u003e)\u003c/strong\u003e. It can be seen that none of the primary or secondary dengue samples were classified as Zika-positive by the PRNT criteria, yielding a perfect specificity; however, the sensitivity is very low. Conversely, the two ELISA systems had the same sensitivity, but the Zika/Dengue OD Ratio had better specificity compared with the commercial IgG test kit (80.95% vs. 76.47%) \u003cstrong\u003e(\u003c/strong\u003eTable \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e\u003cstrong\u003e)\u003c/strong\u003e.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eZika seropositivity of samples per serological criteria / test\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"4\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eSerological diagnosis of Zika-positivity\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eSerum category\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eZika positive\u003c/p\u003e\n \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;10)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePrimary Dengue (n\u0026thinsp;=\u0026thinsp;10)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSecondary Dengue (n\u0026thinsp;=\u0026thinsp;10)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ePRNT\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e90\u003c/strong\u003e\u003c/sub\u003e \u003cstrong\u003eWHO Criteria\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e(PRNT90 titer of \u0026ge;\u0026thinsp;20 against Zika, and/or\u003c/p\u003e\n \u003cp\u003ea ratio of \u0026ge;\u0026thinsp;4 compared to other flavivirus PRNT titers)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2/10 (20%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0/10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0/10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ePRNT\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e90\u003c/strong\u003e\u003c/sub\u003e \u003cstrong\u003eCDC Criteria\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e(PRNT90 titer\u0026thinsp;\u0026ge;\u0026thinsp;10 against Zika, and \u0026lt;10 for Dengue or other flavivirus)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1/10 (10%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0/10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0/10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCommercial Zika IgG ELISA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6/10 (60%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0/10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7/10 (70%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIn-house Zika/Dengue ELISA OD Ratio\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6/10 (60%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0/10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3/10 (30%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"char\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\u0026nbsp;\u003ctable id=\"Tab4\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eSensitivity, Specificity, PPV and NPV of Serological Tests versus RT-PCR\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"5\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eSerological Test\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"4\"\u003e\n \u003cp\u003eDiagnostic Validation against RT-PCR results\u003c/p\u003e\n \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;30)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSensitivity\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSpecificity\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePPV\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNPV\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePRNT\u003csub\u003e90\u003c/sub\u003e WHO Criteria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(2/10) 20%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(20/20) 100%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(2/2) 100%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e(20/28) 71.43%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePRNT\u003csub\u003e90\u003c/sub\u003e CDC Criteria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(1/10) 10%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(20/20) 100%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(1/1) 100%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e(20/29) 68.97%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEuroImmune Zika IgG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(6/10) 60%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(13/20) 65%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(6/13) 46.15%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e(13/17) 76.47%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eZ/D ELISA OD Ratio\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(6/10) 60%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(17/20) 85%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(6/9) 66.67%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e(17/21) 80.95%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eSerological ZIKV diagnosis is challenging in dengue-endemic areas. This is highlighted in this study wherein cross-reactivity of dengue-positive sera affects accurate Zika diagnosis. Despite the best performing antigen (NS1) based on the phase 1 of the study was used in the in-house ELISA, there is still false positivity noted with dengue-positive samples. The low specificity may be explained by the cross-reactivity of the antibody between DENV and ZIKV (Silva et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). An interesting aspect of serological assays, specifically ELISA systems, is that there are multiple ways of analyzing and interpreting the results. In the present study, calculating the Zika/Dengue OD ratio proved that the established indirect ELISA is not inferior to the commercial test kit in terms of antibody detection. The performance was comparable, and yet, regarding diagnostic validity, the Zika/Dengue OD Ratio was far superior as it consistently outperformed the commercial test kit. This is understandable because the standalone detection of Zika antibodies can produce false-positive results, particularly in dengue-endemic areas. The commercial Zika IgG test kit used in this study is one of the best performing test kits with a manufacturer reported sensitivity and specificity of 100% and 97% respectively tested in European population. However, testing its performance against a dengue-endemic country such as Thailand shows a lower diagnostic performance which is in consistently found in other studies as well (Didye, 2020; Kikuti et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Low et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Machado Portilho et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Morales et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). This indicates that the cross-reactivity of secondary dengue antibodies may be a challenge to the diagnostic validity of commercial serological tests. The lower specificity in the subjects after secondary DENV infection may be explained by the characteristic antibody response directed against the antigens of the flavivirus group after secondary DENV infection, whereas the antibody response after primary DENV infection is predominantly against a type-specific determinant (Sirinam et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eWhen it comes to serological assays, Plaque Reduction Neutralization Tests is the gold standard recognized. A comparison of PRNT and the Zika/Dengue OD ratio of the Zika antibody titers in acute and convalescent phase sera revealed no significant difference. Some studies have examined the kinetics of virology and antibody production in Zika infections and found that Zika has lower viral copies, particularly in dengue-primed or prior dengue-infected patients (Musso et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Musso et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; S\u0026aacute;nchez-Arcila et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Santiago et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Terzian et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), which results in a lower immune response (Collins et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Langerak et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; S\u0026aacute;nchez-Arcila et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Terzian et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). As expected from a confirmatory test, the PRNT assay had a specificity of 100% for both the WHO and CDC criteria, and none of the dengue samples were misdiagnosed. The criteria set poses very low sensitivity; however, it causes us to question the usefulness or applicability of the current Zika PRNT interpretation cut-offs in dengue-endemic areas, such as Thailand and the rest of Southeast Asia. The strength of ZIKV PRNT is its high specificity (100%); however, it is laborious, time-consuming, and requires laboratory expertise. A test using the OD ratio of ZIKV-NS1 versus DENV-NS1 provides similar specificity to ZIKV PRNT and higher sensitivity (58.3%). Primary testing using an NS1-IgG ELISA assay, followed by a Zika/Dengue OD ratio of positive ELISA results, can decrease the cost of ZIKV PRNT but does not increase the sensitivity. Considering that ZIKV NS1-IgG ELISA is cost-effective because it uses an in-house NS1 protein and provides relatively high sensitivity and specificity, we propose this test as the test of choice for Zika sero-epidemiological studies. In areas where the incidence of ZIKV is very low and the incidence of DENV is very high, a confirmation of ZIKV infection using ZIKV PRNT or the OD ratio of ZIKV-NS1 versus DENV-NS1 may be used to increase the accuracy of the study.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe results of this study indicate that the combination of two simple ELISAs (DENV-NS1 and ZIKV-NS1) can be applied as a cost-effective methodology for ZIKV serosurveys. This methodology was not designed or intended for individual diagnosis. This represents a convenient, rapid, and cost-effective method to process a large series of samples to monitor ZIKV infection during pregnancy to understand the epidemiology, pathogenesis, and complications of ZIKV in DENV-endemic areas.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eACKNOWLEDGMENTS\u003c/strong\u003e\u003cem\u003e:\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by the Faculty of Tropical Medicine, Mahidol University, Thailand, and the German Academic Exchange Service (DAAD), Germany, Funding program: In-Country/In-Region Scholarships Program at SEAMEO TROPMED Network Regional Office Thailand.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCONFLICT OF INTEREST STATEMENT\u003c/strong\u003e\u003cem\u003e:\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no conflicts of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDATA AVAILABILITY STATEMENT:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAUTHOR CONTRIBUTIONS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eM.D.\u003c/strong\u003e Conceptualization, Data curation, Formal analysis, Investigation, Methodology, and Writing \u0026ndash; original draft.\u0026nbsp;\u003cstrong\u003eP.Si.\u003c/strong\u003e Data curation, Formal analysis, Investigation and Methodology.\u0026nbsp;\u003cstrong\u003eP.Sr.\u003c/strong\u003e Data curation, Formal analysis, Investigation, and Methodology.\u0026nbsp;\u003cstrong\u003eJ.R.\u003c/strong\u003e Data curation, Formal analysis, Investigation, and Methodology.\u0026nbsp;\u003cstrong\u003eP.M.\u003c/strong\u003e Formal analysis, Investigation, Writing \u0026ndash; review \u0026amp; editing.\u0026nbsp;\u003cstrong\u003eK.J.\u003c/strong\u003e Conceptualization, Investigation, Methodology, Supervision, Writing \u0026ndash; review \u0026amp; editing.\u0026nbsp;\u003cstrong\u003eS.C.\u003c/strong\u003e Conceptualization, Funding acquisition, Methodology, Project administration, Supervision, Visualization, Writing \u0026ndash; original draft, Writing \u0026ndash; review \u0026amp; editing.\u0026nbsp;\u003cstrong\u003eP.L.\u003c/strong\u003e Conceptualization, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Supervision, Visualization, Writing \u0026ndash; review \u0026amp; editing.All authors reviewed the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eAlaniz, A. J., Bacigalupo, A., \u0026amp; Cattan, P. E. (2017). Spatial quantification of the world population potentially exposed to Zika virus. \u003cem\u003eInt J Epidemiol, 46\u003c/em\u003e(3), 966-975. doi:10.1093/ije/dyw366\u003c/li\u003e\n \u003cli\u003eAyres, C. F. J., Guedes, D. R. D., Paiva, M. H. S., Morais-Sobral, M. C., Krokovsky, L., Machado, L. C., . . . Wallau, G. L. (2019). Zika virus detection, isolation and genome sequencing through Culicidae sampling during the epidemic in Vit\u0026oacute;ria, Esp\u0026iacute;rito Santo, Brazil. \u003cem\u003eParasit Vectors, 12\u003c/em\u003e(1), 220. doi:10.1186/s13071-019-3461-4\u003c/li\u003e\n \u003cli\u003eBautista, L. E. (2019). Zika virus infection and risk of Guillain-Barr\u0026eacute; syndrome: A meta-analysis. \u003cem\u003eJ Neurol Sci, 403\u003c/em\u003e, 99-105. doi:10.1016/j.jns.2019.06.019\u003c/li\u003e\n \u003cli\u003eBrady, O. J., Osgood-Zimmerman, A., Kassebaum, N. J., Ray, S. E., de Ara\u0026uacute;jo, V. E. 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Zika virus: history of a newly emerging arbovirus. \u003cem\u003eLancet Infect Dis, 16\u003c/em\u003e(7), e119-e126. doi:10.1016/s1473-3099(16)30010-x\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Zika virus, dengue virus, nonstructural protein 1, Serological diagnosis, cross-reactivity","lastPublishedDoi":"10.21203/rs.3.rs-5057804/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5057804/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eZika virus (ZIKV) is a mosquito-borne flavivirus that has recently emerged as a global health threat. The emergence of ZIKV has increased the incidence of neonates born with microcephaly or other neurological syndromes. The majority of ZIKV infections are mild or asymptomatic; however, clinical diagnosis is inaccurate. Moreover, Dengue virus cross-reacts with Zika antibodies, which creates problems for the serological diagnosis of ZIKV infections. Zika serological assays are often performed dismally in dengue-endemic areas because of this phenomenon. In this study, we established a Zika/Dengue ELISA Test to improve the differential diagnosis between Zika and Dengue samples. Sixty Zika-positive samples and 120 controls (20 Primary Dengue samples, 80 Secondary Dengue samples, and 20 healthy serum samples were tested using a ZNS1 and DNS1 Indirect ELISA and a commercial IgG ELISA Kit. Different Zika antigens (EDIII, MR766 NS1 and SV0127 NS1) were tested and ROC curves were compared. Among the antigens tested, NS1 yielded the best diagnostic potential with an AUC range of 0.84–0.88, compared with an AUC of 0.77–0.82 for EDIII. The Zika/Dengue OD Ratio also exhibited the best sensitivity (Sn) and specificity (Sp) (58.3% and 79.2% respectively) among the other parameters tested (Sn = 26.7%–28.3% and Sp = 59.2%–79.3%). It also performed better than the commercial kit, which yielded Sn and Sp values of only 26.7% and 74.2%, respectively. The Zika/Dengue OD Ratio has diagnostic potential and better performance compared with commercial ELISA test kits for detecting Zika infections. The combination of two simple ELISAs may be applied for ZIKV serosurveys and to monitor ZIKV infection during pregnancy to understand the epidemiology, pathogenesis, and complications of ZIKV in DENV-endemic areas.\u003c/p\u003e","manuscriptTitle":"Evaluation of Serological Diagnostic Assays for Distinguishing Zika From Dengue Virus Infections in Thailand","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-04 10:46:25","doi":"10.21203/rs.3.rs-5057804/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"6879bfd9-c960-4544-99b8-b27b9fe13e01","owner":[],"postedDate":"April 4th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":46620669,"name":"Biological sciences/Immunology"},{"id":46620670,"name":"Biological sciences/Microbiology"},{"id":46620671,"name":"Health sciences/Diseases"}],"tags":[],"updatedAt":"2025-08-07T04:08:34+00:00","versionOfRecord":[],"versionCreatedAt":"2025-04-04 10:46:25","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5057804","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5057804","identity":"rs-5057804","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}