Nanoparticle tracking analysis and statistical mixture distribution analysis to quantify nanoparticle–vesicle binding

Isabel U. Foreman-Ortiz, Ting Fung Ma, Brandon M. Hoover, Meng Wu, Catherine J. Murphy, Regina M. Murphy, Joel A. Pedersen

Research output: Contribution to journalArticlepeer-review

Abstract

Nanoparticle tracking analysis (NTA) is a single particle tracking technique that in principle provides a more direct measure of particle size distribution compared to dynamic light scattering (DLS). Here, we demonstrate how statistical mixture distribution analysis can be used in combination with NTA to quantitatively characterize the amount and extent of particle binding in a mixture of nanomaterials. The combined approach is used to study the binding of gold nanoparticles to two types of phospholipid vesicles, those containing and lacking the model ion channel peptide gramicidin A. This model system serves as both a proof of concept for the method and a demonstration of the utility of the approach in studying nano-bio interactions. Two diffusional models (Stokes–Einstein and Kirkwood–Riseman) were compared in the determination of particle size, extent of binding, and nanoparticle:vesicle binding ratios for each vesicle type. The combination of NTA and statistical mixture distributions is shown to be a useful method for quantitative assessment of the extent of binding between particles and determination of binding ratios.

Original languageEnglish (US)
Pages (from-to)50-58
Number of pages9
JournalJournal of Colloid And Interface Science
Volume615
DOIs
StatePublished - Jun 2022

Keywords

  • Aggregation
  • Heteroaggregation
  • Lipid membrane
  • Liposome
  • Membrane protein
  • Nano-bio interactions
  • Nanotechnology
  • Photon correlation spectroscopy
  • Single-particle tracking

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Surfaces, Coatings and Films
  • Biomaterials
  • Colloid and Surface Chemistry

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