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Quantifying Antibody Binding Kinetics on Fixed Cells and Tissues via Fluorescence Lifetime Imaging
Prerit Mathur1,2, Anna Fomitcheva Khartchenko1,2, Stavros Stavrakis1
1Institute for Chemical and Bioengineering, Department of Chemistry & Applied Biosciences, Eidgenössische Technische Hochschule (ETH Zürich), Vladimir-Prelog-Weg 1-5/10, 8093 Zürich, Switzerland.
We developed a fluorescence imaging method to monitor antigen-antibody binding on cells and tissues. This technique measures binding kinetics, revealing differences in p53 expression in ovarian cancer tissues.
Area of Science:
- Biophysics
- Biochemistry
- Immunology
Background:
- Monitoring antigen-antibody interactions is crucial for understanding biological processes and disease.
- Existing methods often lack spatial resolution or are limited to specific sample types.
- Accurate measurement of binding kinetics on physiological substrates remains a challenge.
Purpose of the Study:
- To present a novel method for monitoring spatially localized antigen-antibody binding events.
- To measure binding kinetics on physiologically relevant substrates like cell and tissue sections.
- To investigate p53 kinetics in ovarian cancer tissue sections with differential biomarker expression.
Main Methods:
- Utilizing fluorescence lifetime imaging to differentiate between free and bound fluorescently tagged antibodies.
- Employing a microfluidic probe format to minimize mass transport effects and localize analysis.
- Measuring binding constants (kon) on surface-bound antigens, cell blocks, and ovarian cancer tissue sections.
Main Results:
- The method successfully monitors spatially localized antigen-antibody binding events.
- Binding constants (kon) were measured on model biomarkers and in ovarian cancer tissue.
- p53 kinetics correlated with biomarker expression levels, with distinct kon values for high and low expression.
Conclusions:
- Fluorescence lifetime imaging with a microfluidic probe offers a robust method for studying antigen-antibody binding kinetics on biological substrates.
- The technique provides insights into biomarker expression and its impact on molecular interactions in cancer tissues.
- This approach has potential applications in diagnostics and drug development.
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