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Engineered single chain variable fragments (scFvs) with improved pH-dependent kinetics for use in continuous

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Researchers engineered a pH-sensitive antibody fragment to improve continuous insulin monitoring. This enhanced biological recognition element offers better biosensor regeneration for dynamic conditions.

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Area of Science:

  • Biotechnology
  • Biosensor Development
  • Antibody Engineering

Background:

  • Continuous in vivo insulin monitoring requires high-affinity biological recognition elements (BREs) with suitable kinetic parameters.
  • Existing BREs often lack the necessary kinetic properties to accurately track fluctuating insulin levels.
  • Engineering BREs to respond to external signals, like pH changes, can overcome these limitations.

Purpose of the Study:

  • To engineer an anti-insulin single chain variable fragment (scFv) with improved pH-dependent binding kinetics.
  • To evaluate the impact of specific mutations on the pH-sensitivity and binding affinity of the scFv.
  • To assess the utility of the modified scFv in a biosensor for tracking dynamic insulin concentrations.

Main Methods:

  • Computational prediction of scFv-insulin complex structure.
  • Site-directed mutagenesis of scFv residues involved in insulin binding, focusing on histidine substitution.
  • Bio-layer interferometry (BLI) assay to measure binding kinetics (KD) at different pH values (7.4 and 6.0).
  • Evaluation of biosensor regeneration using the engineered scFv in dynamic pH conditions.

Main Results:

  • Identified a T32H mutation in the anti-insulin scFv that significantly enhances pH-sensitivity.
  • The T32H mutant exhibited an 8.4× difference in KD between pH 7.4 (145.5 ± 83.1 nM) and pH 6.0 (17.4 ± 5.1 nM).
  • This represents a 3.8× increase in pH-sensitivity compared to the wild-type (WT) scFv.
  • The improved pH-sensitivity facilitated enhanced biosensor regeneration in dynamic pH environments.

Conclusions:

  • Engineered pH-sensitive antibodies can significantly improve the performance of biosensors for continuous monitoring.
  • The T32H mutant demonstrates potential as a superior biological recognition element for in vivo insulin sensing.
  • This approach offers a promising strategy for developing next-generation continuous monitoring systems, particularly for diabetes management.