The recent Zika virus (ZIKV) outbreak demonstrates that cost-effective clinical diagnostics are urgently needed to detect and distinguish viral infections to improve patient care. Unlike dengue virus (DENV), ZIKV infections during pregnancy correlate with severe birth defects, including microcephaly and neurological disorders. Because ZIKV and DENV are related flaviviruses, their homologous proteins and nucleic acids can cause cross-reactions and false-positive results in molecular, antigenic, and serologic diagnostics. We report the characterization of monoclonal antibody pairs that have been translated into rapid immunochromatography tests to specifically detect the viral nonstructural 1 (NS1) protein antigen and distinguish the four DENV serotypes (DENV1-4) and ZIKV without cross-reaction. To complement visual test analysis and remove user subjectivity in reading test results, we used image processing and data analysis for data capture and test result quantification. Using a 30-μl serum sample, the sensitivity and specificity values of the DENV1-4 tests and the pan-DENV test, which detects all four dengue serotypes, ranged from 0.76 to 1.00. Sensitivity/specificity for the ZIKV rapid test was 0.81/0.86, respectively, using a 150-μl serum input. Serum ZIKV NS1 protein concentrations were about 10-fold lower than corresponding DENV NS1 concentrations in infected patients; moreover, ZIKV NS1 protein was not detected in polymerase chain reaction-positive patient urine samples. Our rapid immunochromatography approach and reagents have immediate application in differential clinical diagnosis of acute ZIKV and DENV cases, and the platform can be applied toward developing rapid antigen diagnostics for emerging viruses.

Zika and dengue are mosquito-borne diseases that present similar nonspecific symptoms but possess dramatically different outcomes. The first line of defense in epidemic outbreaks are rapid point-of-care diagnostics. Because many outbreaks occur in areas that are resource poor, assays that are easy to use, inexpensive, and require no power have become invaluable in patient treatment, quarantining, and surveillance. Paper-based sandwich immunoassays such as lateral flow assays (LFAs) are attractive as point-of-care solutions as they have the potential for wider deployability than lab-based assays such as PCR. However, their low sensitivity imposes limitations on their ability to detect low biomarker levels and early diagnosis. Here, we exploit the high sensitivity of surface-enhanced Raman spectroscopy (SERS) in a multiplexed assay that can distinguish between Zika and dengue nonstructural protein 1 (NS1) biomarkers. SERS-encoded gold nanostars were conjugated to specific antibodies for both diseases and used in a dipstick immunoassay, which exhibited 15-fold and 7-fold lower detection limits for Zika NS1 and dengue NS1, respectively. This platform combines the simplicity of a LFA with the high sensitivity of SERS and could not only improve Zika diagnosis but also detect diseases sooner after infection when biomarker levels are low.

We investigated the effect of the protein corona on the function of nanoparticle (NP) antibody (Ab) conjugates in dipstick sandwich immunoassays. Ab specific for Zika virus nonstructural protein 1 (NS1) were conjugated to gold NPs, and another anti-NS1 Ab was immobilized onto the nitrocellulose membrane. Sandwich immunoassay formation was influenced by whether the strip was run in corona forming conditions, i.e., in human serum. Strips run in buffer or pure solutions of bovine serum albumin exhibited false positives, but those run in human serum did not. Serum pretreatment of the nitrocellulose also eliminated false positives. Corona formation around the NP-Ab in serum was faster than the immunoassay time scale. Langmuir binding analysis determined how the immobilized Ab affinity for the NP-Ab/NS1 was impacted by corona formation conditions, quantified as an effective dissociation constant, KDeff. Results show that corona formation mediates the specificity and sensitivity of the antibody–antigen interaction of Zika biomarkers in immunoassays, and plays a critical but beneficial role.