Label-free chronopotentiometric glycoprofiling of prostate specific antigen using sialic acid recognizing lectins

Area of Science:

• Biochemistry
• Analytical Chemistry
• Biomarker Detection

Background:

• Protein glycosylation is crucial in health and disease, necessitating advanced diagnostic tools.
• Current methods for detecting protein glycosylation are often complex, slow, or expensive.
• There is a need for rapid, cost-effective methods for clinical applications, especially in cancer diagnostics.

Purpose of the Study:

• To develop and validate a label- and reagent-free electrochemical method for detecting interactions between sialylated prostate specific antigen (PSA) and specific lectins.
• To assess the potential of chronopotentiometric stripping (CPS) analysis for glycomics and proteomics applications.
• To differentiate interactions between PSA and Sambucus nigra agglutinin (SNA) versus Maackia amurensis agglutinin (MAA).

Main Methods:

• Utilized chronopotentiometric stripping (CPS) analysis with a hanging mercury drop electrode.
• Developed a PSA-modified electrode for interaction detection.
• Employed specific lectins, Sambucus nigra agglutinin (SNA) and Maackia amurensis agglutinin (MAA), for binding studies.
• Varied polarization current and temperature to distinguish lectin-PSA interactions.

Main Results:

• Observed an increase in CPS peak H upon incubation of PSA-modified electrode with SNA lectin, indicating complex formation.
• Demonstrated the ability to eliminate or distinguish PSA-MAA interactions from PSA-SNA interactions by adjusting experimental parameters.
• CPS results showed good agreement with complementary techniques like surface plasmon resonance and fluorescent lectin microarray.

Conclusions:

• The proposed label- and reagent-free electrochemical CPS method is effective for detecting sialylated protein biomarker interactions.
• This technique holds promise for applications in glycomics and proteomics, potentially improving disease diagnostics.
• The method offers a simple, fast, and inexpensive alternative for analyzing complex biological interactions.