Repurposing Old Antibodies for New Diseases by Exploiting Cross-Reactivity and Multicolored Nanoparticles

Area of Science:

• * Virology and Immunology
• * Biosensor Development
• * Medical Diagnostics

Background:

• * Accurate detection of flaviviruses like dengue (DENV), Zika (ZIKV), and yellow fever virus (YFV) is crucial for public health.
• * Existing diagnostic methods can be limited in specificity and accessibility.
• * Nonstructural protein 1 (NS1) is a key biomarker for flavivirus infections.

Purpose of the Study:

• * To develop a selective sensor for detecting yellow fever virus (YFV) nonstructural protein 1 (NS1).
• * To leverage the cross-reactivity of dengue (DENV) and Zika (ZIKV) virus antibodies for enhanced flavivirus detection.
• * To create a rapid, paper-based immunoassay for distinguishing between DENV, ZIKV, and YFV NS1 biomarkers.

Main Methods:

• * Screening of DENV and ZIKV polyclonal antibodies for binding affinity to DENV, ZIKV, and YFV NS1 using ELISA.
• * Development of a paper immunoassay with strategically arranged antibodies conjugated to distinctively colored gold nanoparticles (AuNPs).
• * Application of machine learning algorithms to analyze RGB values from test areas for biomarker identification and quantification.

Main Results:

• * Achieved 100% and 87% accuracy in detecting pure NS1 and DENV/YFV mixtures, respectively, using a two-spot configuration.
• * Demonstrated 92% accuracy in differentiating between all four DENV serotypes through additional image preprocessing.
• * Successfully adapted a commercial DENV test to detect YFV and ZIKV by incorporating specific antibodies.

Conclusions:

• * The developed sensor effectively utilizes antibody cross-reactivity for selective flavivirus NS1 detection.
• * The paper-based immunoassay coupled with machine learning offers a promising approach for rapid and accurate diagnostics.
• * This technique can be extended to repurpose existing diagnostic kits for broader flavivirus surveillance.