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Updated: Jun 22, 2026

Activated Cross-linked Agarose for the Rapid Development of Affinity Chromatography Resins - Antibody Capture as a Case Study
Published on: August 16, 2019
Optimization of antibody immobilization for on-line or off-line immunoaffinity chromatography
Natascha Helena Beyer1, Morten Zoega Hansen, Christian Schou
1Department of Clinical Biochemistry and Immunology, Statens Serum Institute, Copenhagen S., Denmark.
Abstract:
The covalent immobilization of antibodies to solid supports for immunoaffinity (IA) purification is widely used in the biological sciences. However, relative immobilization yields, immobilization stability, and antigen-binding capacity vary significantly with the antibody and protocol used. A systematic study was conducted to determine the most versatile antibody immobilization method for use in on-line and off-line IA chromatography applications using commonly accessible immobilization methods. Four chemistries were examined using polyclonal and monoclonal antibodies and antibody fragments. We evaluated a method to survey optimal elution conditions and estimated immobilization yields, matrix stability, antigen binding capacities, and antigen recovery of different IA matrices. Some mAbs were sensitive to aminogroup-based immobilization, i.e., losing antigen binding capabilities after immobilization especially using epoxy chemistry. In general, the most optimal covalent antibody immobilization for on-line IA-LC-MS was achieved using aminogroup immobilization of intact antibodies by epoxy- or aldehyde-activated POROS R20-matrices and in some cases by chemical crosslinking to Protein G-POROS. Protein G-based matrices are very stable showing essentially no decline in performance after 50 application-wash-elution-reequilibration cycles and being easily prepared within 2-3 h of working time with a typical antibody coupling yield of above 80%. In off-line applications where constant flow conditions are not used, covalent crosslinking onto Protein G-POROS or Protein G-agarose is to be recommended.
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