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DNA probes are fragments of DNA labeled with a reporter tag to enable their detection or purification. The resulting labeled DNA probes can then hybridize to target nucleic acid sequences through complementary base-pairing, and may be used to recover or identify these regions.
Radioisotopes, fluorophores, or small molecule binding partners like biotin or digoxigenin, are the most widely used reporter tags for labeling DNA probes. These labels can be attached to the probe DNA molecule via...
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Related Experiment Video

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Bacterial Peptide Display for the Selection of Novel Biotinylating Enzymes
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Streptavidin Coverage on Biotinylated Surfaces.

P H Erik Hamming1, Jurriaan Huskens1

  • 1Molecular Nanofabrication Group, MESA+ Institute, Faculty of Science and Technology, University of Twente, P.O. Box 217, 7500 AE Enschede, The Netherlands.

ACS Applied Materials & Interfaces
|November 23, 2021
PubMed
Summary
This summary is machine-generated.

This study presents a predictive model for streptavidin (SAv) coverage on biotinylated surfaces. This method quantifies SAv density, crucial for biosensor development and surface functionalization applications.

Keywords:
biotinlocalized surface plasmon resonance (LSPR)quartz crystal microbalance (QCM)self-assembled monolayer (SAM)streptavidin (SAv)supported lipid bilayer (SLB)surface coverage

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Area of Science:

  • Biotechnology
  • Surface Chemistry
  • Biosensor Development

Background:

  • Biosensor and biological platform technologies rely on surface functionalization with receptors for improved affinity and selectivity.
  • Controlling receptor functionalization density is essential for tuning platform properties.
  • Streptavidin (SAv) monolayers are commonly used for immobilizing biotinylated molecules, but predictable density control remains a challenge.

Purpose of the Study:

  • To develop a quantitative method for predicting streptavidin coverage on biotinylated surfaces.
  • To establish a model for understanding and controlling streptavidin density for biosensor applications.

Main Methods:

  • Validation using supported lipid bilayers with varying biotin content and lipid compositions.
  • Utilizing quartz crystal microbalance and localized surface plasmon resonance for SAv coverage measurement.
  • Developing a predictive model for biotin-dependent SAv coverage without fit parameters.

Main Results:

  • A method to quantitatively predict streptavidin coverage on biotinylated surfaces was demonstrated.
  • The predictive model accurately describes SAv coverage across low- and high-density regimes based on biotin coverage.
  • Experimental validation was performed on supported lipid bilayers using advanced surface-sensitive techniques.

Conclusions:

  • The developed model provides a predictable framework for controlling streptavidin surface density.
  • This quantitative prediction is vital for applications requiring precise control over surface receptor density, such as multivalent binding assays.
  • The findings advance the rational design and optimization of biosensors and bio-interfaces.