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Optimizing Upconversion Nanoparticles for FRET Biosensing.

Federico Pini1,2,3, Laura Francés-Soriano1,4, Vittoria Andrigo2,3

  • 1Laboratoire COBRA, Université de Rouen Normandie, CNRS, INSA Rouen, Normandie Université, 76000 Rouen, France.

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|March 3, 2023
PubMed
Summary
This summary is machine-generated.

We developed a rapid analytical model to optimize upconversion nanoparticle (UCNP) Förster resonance energy transfer (FRET) systems for sensitive biomolecule detection. This approach significantly enhances biosensing performance with minimal experimental effort.

Keywords:
DNAFRETenergy transferneodymiumsensitivityupconverting nanocrystals

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Area of Science:

  • Nanomaterials Science
  • Biomedical Engineering
  • Analytical Chemistry

Background:

  • Upconversion nanoparticles (UCNPs) show great promise for bioanalytical and biomedical applications.
  • Optimizing UCNPs for Förster resonance energy transfer (FRET) biosensing and bioimaging remains a challenge due to complex architectures and energy transfer pathways.
  • Achieving highly sensitive, wash-free, multiplexed, accurate, and precise quantitative analysis of biomolecules is critical.

Purpose of the Study:

  • To develop a rapid analytical model for determining the ideal UCNP-FRET configuration for optimal biosensing performance.
  • To overcome the experimental challenges in identifying optimal UCNP-FRET systems.
  • To enable highly sensitive and efficient quantitative analysis of biomolecules and interactions.

Main Methods:

  • Developed a fully analytical model requiring minimal experimental configurations to identify optimal UCNP-FRET systems.
  • Verified the model using nine different Nd-, Yb-, and Er-doped core-shell-shell UCNP architectures.
  • Utilized a prototypical DNA hybridization assay with Cy3.5 as an acceptor dye for validation.

Main Results:

  • The model rapidly determined the optimal UCNP configuration from numerous theoretical possibilities.
  • Experimental validation confirmed the model's accuracy in selecting the best UCNP-FRET system.
  • Achieved significant sensitivity increases in the DNA hybridization assay.

Conclusions:

  • Combining limited experiments with rapid modeling efficiently identifies ideal UCNP-FRET biosensors.
  • This approach offers extreme economy in time, effort, and materials.
  • The developed method significantly enhances biosensing sensitivity and performance.