Protein Quantification and Imaging by Surface-Enhanced Raman Spectroscopy and Similarity Analysis

Area of Science:

• Biochemistry
• Spectroscopy
• Nanotechnology

Background:

• Immunoassays are common for protein quantification but have limitations like low sensitivity and time-consuming steps.
• Direct surface-enhanced Raman spectroscopy (SERS) offers intrinsic signal detection but faces challenges in signal complexity and reliability for quantification without purified proteins.

Purpose of the Study:

• To develop an efficient and effective direct SERS-based immunoassay (SERSIA) for protein quantification and imaging.
• To overcome the limitations of traditional protein detection methods by utilizing intrinsic SERS signals.

Main Methods:

• SERSIA utilizes uniform gold nanoparticle (GNP) coating on a protein-immobilized substrate via centrifugation.
• Centrifugation ensures close contact between GNPs and target proteins for intrinsic signal detection.
• Protein levels are quantified using similarity analysis comparing antibody-only and protein-conjugated samples.

Main Results:

• The SERSIA technique achieves protein quantification with a sub-picomolar detection limit.
• The method demonstrates reliable protein level estimation in cell lysates.
• Quantitative imaging of immobilized proteins at a micrometer range is enabled.

Conclusions:

• SERSIA is a fast, sensitive, and antibody-efficient technique for protein detection.
• This approach provides a valuable tool for protein quantification and imaging in biological samples.
• The direct SERS-based immunoassay offers a promising alternative to conventional protein detection methods.