బయోసెన్సర్లు & బయోఎలక్ట్రానిక్స్

AgNPs-based Label-Free Colloidal SERS Nanosensor for the Rapid and Sensitive Detection of Stress-Proteins Expressed in Response to Environmental-Toxins

Abstract

Vinay Bhardwaj, Supriya Srinivasan and Anthony J McGoron

Among several physical, chemical and immunoassay-based methods for the detection of biomolecules, the Enzyme-Linked Immuno-Sorbent Assay (ELISA) is the standard technique that is routinely used for quantification of known proteins. However, it is a label-based, end-point sensor technique that is time-consuming, labor-intensive and fairly costly. This sandwich assay typically involves a series of peptide binding and washing steps. Here, we report a Surface-Enhanced Raman Spectroscopy (SERS) immuno-nanosensor technique that allows rapid and label-free extracellular detection of proteins compared to ELISA, and can potentially be used for intracellular detection. Our study shows that the silver nanoparticles (AgNPs) based SERS sensor can detect the stress-proteins, HSP70 and RAD54 expressed by yeast in response to environmental-toxins, in a dose dependent manner. As compared to the multi-step sandwich ELISA technique, the detection of stress-proteins using the SERS sensor is a simple two-step process. The simplicity of the SERS nanosensor design allowed the rapid detection of proteins within two hours in a fairly cost-effective and user-friendly approach. The SERS sensor we reported has an edge over ELISA as it directly quantifies the proteins without using any label (label-free) and also gives qualitative information about the antigen-antibody interaction. The SERS sensor showed good correlation and comparable sensitivity with ELISA. However, SERS was found to be less reproducible. Compared to previous reports on SERS-based protein detection techniques, our colloidal SERS sensor is easy to fabricate, offers improved biocompatibility, and allows rapid detection of the proteins in a cellular environment at picogram-levels. As a result, the SERS sensor demonstrates great potential for biomedical and environmental sensor technology (BEST) allowing label-free, rapid and sensitive detection, and could possibly replace ELISA.