High-throughput imaging surface plasmon resonance biosensing based on an adaptive spectral-dip tracking scheme

Area of Science:

• Biomedical Engineering
• Analytical Chemistry
• Optics

Background:

• Imaging-based spectral surface plasmon resonance (λSPR) biosensing faces limitations in data throughput due to large data volumes from 2D sensor arrays and detailed absorption dip measurements.
• High data acquisition requirements hinder the real-time application of λSPR in complex biological analyses.

Purpose of the Study:

• To develop and demonstrate an adaptive feedback approach to significantly improve data throughput in λSPR biosensing.
• To enable faster and more efficient real-time label-free biosensing using λSPR technology.

Main Methods:

• Implemented an adaptive feedback loop to continuously track the absorption dip location during target-molecule binding.
• Utilized an adaptive windowing strategy to reduce data points captured per pixel without sacrificing accuracy.
• Employed a liquid crystal tunable filter (LCTF) for rapid wavelength scanning.

Main Results:

• The developed system achieved dip measurement in as little as 700ms.
• The adaptive feedback approach effectively reduced data acquisition time while maintaining measurement accuracy.
• Demonstrated suitability for real-time micro-array label-free biosensing.

Conclusions:

• The adaptive feedback λSPR biosensing approach overcomes previous data throughput limitations.
• This method is highly suitable for real-time, label-free detection in micro-array formats.
• The enhanced speed and efficiency open new possibilities for rapid biological analysis.