Optimization of the Small Glycan Presentation for Binding a Tumor-Associated Antibody: Application to the Construction of an Ultrasensitive Glycan Biosensor

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The main aim of the study was to optimize the interfacial presentation of a small antigen-a Tn antigen (N-acetylgalactosamine)-for binding to its analyte anti-Tn antibody. Three different methods for the interfacial display of a small glycan are compared here, including two methods based on the immobilization of the Tn antigen on a mixed self-assembled monolayer (SAM) (2D biosensor) and the third one utilizing a layer of a human serum albumin (HSA) for the immobilization of a glycan forming a 3D interface. Results showed that the 3D interface with the immobilized Tn antigen is the most effective bioreceptive surface for binding its analyte. The 3D impedimetric glycan biosensor exhibited a limit of detection of 1.4 aM, a wide linear range (6 orders of magnitude), and high assay reproducibility with an average relative standard deviation of 4%. The buildup of an interface was optimized using various techniques with the visualization of the glycans on the biosensor surface by atomic force microscopy. The study showed that the 3D biosensor is not only the most sensitive compared to other two biosensor platforms but that the Tn antigen on the 3D biosensor surface is more accessible for antibody binding with better kinetics of binding (t50% = 137 s, t50% = the time needed to attain 50% of a steady-state signal) compared to the 2D biosensor configuration with t50% = 354 s. The 3D glycan biosensor was finally applied for the analysis of a human serum sample spiked with an analyte.


  • Filip Kveton
  • Anna Blšáková
  • Andras Hushegyi
  • Pavel Damborsky
  • Ola Blixt
  • Bo Jansson
  • Jan Tkac
Enheter & grupper
Externa organisationer
  • University of Copenhagen
  • Institute of Chemistry, Slovak Academy of Sciences

Ämnesklassifikation (UKÄ) – OBLIGATORISK

  • Läkemedelskemi
Sidor (från-till)2709-2716
Antal sidor8
StatusPublished - 2017 mar 21
Peer review utfördJa