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Related Experiment Videos

Sequential analysis of multiple analytes using a surface plasmon resonance (SPR) biosensor.

J W Chung1, R Bernhardt, J C Pyun

  • 1Korea Institute for Science and Technology Europe (KIST Europe fGmbH), Stuhlsatzenhausweg 97, 66123 Saarbruecken, Germany.

Journal of Immunological Methods
|April 4, 2006
PubMed
Summary

A novel sequential analysis method using a surface plasmon resonance (SPR) biosensor allows for the simultaneous detection of two analytes in a single sample. This method demonstrates high accuracy and no cross-reactivity, proving effective for analyzing biomarkers like human chorionic gonadotropin (hCG).

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Area of Science:

  • Analytical Chemistry
  • Biochemistry
  • Biosensing Technology

Background:

  • Multiplexed analysis of biological samples is crucial for accurate disease diagnosis.
  • Existing biosensing methods can face challenges with cross-reactivity and sample complexity.
  • Surface Plasmon Resonance (SPR) biosensors offer high sensitivity but require optimized methods for analyzing multiple analytes.

Purpose of the Study:

  • To develop and validate a sequential analysis method for detecting two analytes simultaneously using a single SPR biosensor.
  • To establish two distinct detection models to accommodate different analyte compositions and labeling requirements.
  • To optimize the immunoaffinity capacity for enhanced analyte binding and sensor response.

Main Methods:

  • Development of a sequential analysis protocol for a single SPR sensing region.

Related Experiment Videos

  • Design of two detection models: one with label-free and labeled detection, the other with dual labeled detection.
  • Preparation of standard curves for each model and sequential analysis of anti-bovine serum albumin (anti-BSA) antibodies and horseradish peroxidase (HRP).
  • Optimization of analyte binding capacity by adjusting molecular recognition element concentration ratios.
  • Main Results:

    • The sequential analysis method achieved errors of less than 6% for both models, indicating high accuracy.
    • No significant cross-reactivity was observed between participating antigens and antibodies in either model.
    • Optimization of immunoaffinity (IA) capacity using sensor response (R(max)) was successfully demonstrated.
    • Feasibility was confirmed by detecting human chorionic gonadotropin (hCG) and human albumin (hA) in human urine samples using Model 2.

    Conclusions:

    • The developed sequential SPR biosensor method provides a reliable and accurate approach for analyzing multiple analytes in a single sample.
    • This method minimizes cross-reactivity and allows for optimization of binding capacity, enhancing analytical performance.
    • The successful detection of pregnancy-related biomarkers (hCG and hA) in urine highlights its clinical diagnostic potential.