- Microarray immunoassay is an advanced, high-throughput technique used to simultaneously detect and quantify multiple biomolecules—such as proteins, antibodies, or antigens—on a single, miniaturized platform. This method combines the specificity of immunoassays with the parallel analysis capability of microarrays, enabling researchers to evaluate a vast array of targets in a single experiment with high sensitivity and minimal sample consumption.
- In a typical microarray immunoassay, capture antibodies or antigens are immobilized onto a solid substrate such as a glass slide or silicon chip in an organized grid pattern. These immobilized probes are spatially separated, each targeting a specific analyte. Once the microarray is prepared, the sample—often a biological fluid like serum or plasma—is applied over the surface, allowing analytes to bind specifically to their corresponding capture probes. Detection is usually achieved using a secondary antibody conjugated to a fluorescent dye or another reporter molecule, enabling signal generation that can be measured using specialized scanners or imaging systems.
- One of the main advantages of microarray immunoassays is their capacity for multiplexing, allowing the simultaneous analysis of dozens to thousands of targets. This makes them particularly useful in biomarker discovery, disease profiling, vaccine response analysis, and diagnostics. Because the format is miniaturized, microarrays also require only small volumes of sample and reagents, making them cost-effective and suitable for limited or precious samples.
- However, microarray immunoassays also present some challenges. The immobilization process must preserve the bioactivity of the capture molecules, and non-specific binding can affect signal quality if not properly controlled. Additionally, careful calibration and normalization are essential to ensure quantitative accuracy across different spots and arrays.
- Despite these challenges, microarray immunoassays represent a powerful analytical tool in both research and clinical settings. Their ability to generate large volumes of data rapidly and efficiently supports systems biology, personalized medicine, and high-throughput screening applications.
