SERS based rapid and ultrasensitive detection of Japanese Encephalitis Virus

Label-free detection of virus based on surface-enhanced Raman scattering

Due to the background interference from biological samples, detecting viruses using surface-enhanced Raman scattering (SERS) in clinical samples is challenging. This study is based on SERS by reducing sodium borohydride and aggregating silver nanoparticles to develop suitable virus detection "hot spot." The monkeypox virus and human papillomavirus fingerprints were quickly obtained, tested, and identified in serum and artificial vaginal discharge, respectively, by combining the principal component analysis method. Therefore, these viruses were successfully identified in the biological background. In addition, the lowest detection limit was 100 copies/mL showing good reproducibility and signal-to-noise ratio. The concentration-dependent curve of the monkeypox virus had a good linear relationship. This method helps solve the SERS signal interference problem in complex biological samples, with low detection limits and high selectivity in virus characterization and quantitative analysis. Therefore, this method has a reasonable prospect of clinical application.

A novel approach for rapid and sensitive detection of Zika virus utilizing silver nanoislands as SERS platform

To control the spread of the disease, the Zika virus (ZIKV), a flavivirus infection spread by mosquitoes and common in across the world, needs to be accurately and promptly diagnosed. This endeavour gets challenging when early-stage illnesses have low viral loads. As a result, we have created a biosensor based on surface-enhanced Raman scattering (SERS) for the quick, accurate, and timely diagnosis of the Zika virus. In this study, a glass coverslip was coated with silver nanoislands, which were then utilized as the surface for creating the sensing platform. Silver nanoislands exhibit strong plasmonic activity and good conductive characteristics. It enhances the Raman signals as a result and gives the SERS platform an appropriate surface. The created platform has been applied to Zika virus detection. With a limit of detection (LOD) of 0.11 ng/mL, the constructed sensor exhibits a linear range from 5 ng/mL to 1000 ng/mL. Hence, even at the nanogram scale, this technique may be a major improvement over clinical diagnosis approaches for making proper, precise, and accurate Zika virus detection.

Point-of-care detection of Japanese encephalitis virus biomarker in clinical samples using a portable smartphone-enabled electrochemical "Sensit" device

Japanese encephalitis (JE), a neglected tropical zoonotic disease prevalent in south-east Asian and western pacific countries, caused by the flavivirus JE virus (JEV), has a dearth of electrochemical point-of-care (PoC) diagnostic tools available to manage endemic breakouts. To overcome this, we have developed a screen-printed carbon electrode (SPCE) immunosensor for rapid PoC detection of JEV nonstructural 1 (NS1) antigen (Ag), found circulating in serum of infected individuals using a smartphone based portable "Sensit" device. The modification of SPCE surface with JEV NS1 antibody (Ab) was confirmed via observation of globular protein structures via scanning electron microscopy (SEM), increase in electrode surface hydrophilicity via contact angle measurement and decrease in current via differential pulse voltammetry (DPV). The fabrication and testing parameters were optimized based on highest current output obtained using DPV. The SPCE was tested for detection limit of target JEV NS1 Ag ranging from 1 fM to 1 μM, which was determined as 0.45 fM in spiked serum. The disposable immunosensor was also found to be highly specific in detecting JEV NS1 Ag over other flaviviral NS1 Ag. Finally, the modified SPCE was clinically validated by testing 62 clinical JEV samples using both a portable miniaturized electrochemical "Sensit" device coupled with a smartphone and a laboratory-based potentiostat. The results were corroborated with gold-standard RT-PCR and showed 96.77% accuracy, 96.15% sensitivity, and 97.22% specificity. Hence, this technique may further be developed into a one-step rapid diagnostic tool for JEV, especially in rural areas.

Immuno-chromatic probe based lateral flow assay for point-of-care detection of Japanese encephalitis virus NS1 protein biomarker in clinical samples using a smartphone-based approach

Lateral flow assays (LFAs) are one of the most economical, point-of-care (PoC) diagnostic assays that exploit the colorimetric properties of gold nanoparticles (AuNPs). Up to the best of our knowledge, no rapid antigen-based LFA exists for Japanese Encephalitis Virus (JEV) detection. Herein, we have reported a novel portable sandwich-type LFA for on-site detection of the non-structural 1 (NS1) secretory protein of JEV. In-house JEV NS1 antibodies (Abs) were generated and labelled with AuNPs as immunoprobes. A glass fibre membrane conjugate pad was soaked with AuNPs-Ab solution, while the JEV NS1 Ab and anti-rabbit IgG 2° Ab were coated as the test and control lines, respectively, on a nitrocellulose (NC) membrane. Different layers of the LFA were fabricated and various parameters were standardised for optimum colour intensity development. JEV negative serum samples spiked with JEV NS1 Ags (linear range - 1 pg ml-1 to 1 μg ml-1) were applied onto the sample pad and the intensity of the red colour developed on the test line increased with increasing concentration of Ag. The visual limit of detection (LOD) determined from the LFA was 10 pg ml-1, which corresponded to the LOD determined by the graphical data obtained from ImageJ software and the Colorimeter smartphone application. Furthermore, the colorimetric based immunosensor showed minimal non-specific detection of other closely related flaviviral NS1 Ags in the spiked serum, provided a rapid result within 10 min, showed storage stability up to a month at 4 °C, successfully detected the JEV NS1 protein in clinically infected pig serum samples, and hence, may be developed into a PoC screening diagnostic kit for JEV.