Surface-enhanced Raman spectroscopy for protein detection: Challenges and countermeasures

Area of Science:

• Biochemistry and Molecular Biology
• Analytical Chemistry
• Biomedical Engineering

Background:

• Proteins are crucial biomarkers for disease diagnosis.
• Low protein concentrations in biological fluids hinder accurate detection.
• Surface-enhanced Raman spectroscopy (SERS) offers a promising solution due to its sensitivity and label-free nature.

Purpose of the Study:

• To systematically review the application progress of SERS technology in protein detection.
• To cover breakthroughs in SERS substrates, single-molecule detection, and multi-component analysis.
• To analyze challenges and future directions of SERS in disease diagnosis.

Main Methods:

• Review of recent literature on SERS for protein analysis.
• Elaboration on novel SERS substrate development.
• Discussion of single-molecule detection and multi-analyte SERS strategies.
• Exploration of SERS combined with other technologies and machine learning applications.

Main Results:

• Significant advancements in SERS substrates enabling enhanced sensitivity.
• Demonstration of single-molecule protein detection capabilities.
• Progress in simultaneous detection of multiple proteins.
• Integration of machine learning for improved spectral data interpretation.

Conclusions:

• SERS technology shows great potential for sensitive and specific protein detection in disease diagnosis.
• Further research into novel substrates, advanced techniques, and clinical integration is warranted.
• SERS combined with machine learning offers a powerful platform for future biomedical applications.