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Probabilistic modeling of rosette formation.

Mian Long1, Juan Chen, Ning Jiang

  • 1National Microgravity Laboratory, Institute of Mechanics, Chinese Academy of Sciences, Beijing 100080, People's Republic of China. mlong@imech.ac.cn

Biophysical Journal
|April 11, 2006
PubMed
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Rosette formation assays, used to study cell adhesion, can now quantify receptor-ligand binding. A new probabilistic model links rosette size to binding affinity, making it a semiquantitative tool for biophysical measurements.

Area of Science:

  • Biophysics
  • Immunology
  • Cell Biology

Background:

  • Rosetting assays, forming cell aggregates, are used to study cell adhesion via receptor-ligand interactions.
  • Commonly used for Fc gamma-receptors (FcgammaR) and IgG, the biophysical parameters of rosetting are not well understood.

Purpose of the Study:

  • To develop a probabilistic model for rosette size distribution.
  • To characterize the biophysical parameters of rosette formation.
  • To establish rosetting as a semiquantitative assay for receptor-ligand binding affinity.

Main Methods:

  • Developed a probabilistic model predicting Poissonian distribution of rosette sizes.
  • Experimentally validated the model using four distinct molecular interactions: FcgammaRIII-IgG, TCR-MHC, P-selectin-PSGL-1, and L-selectin-PSGL-1.

Related Experiment Videos

  • Fitted the model to experimental data to calculate effective two-dimensional binding affinities.

    • Main Results:

    • The model accurately describes rosette size distribution as Poissonian.
    • Average rosette size is proportional to binding affinity and site densities.
    • Quantified binding affinities for FcgammaRIII-IgG, P-selectin-PSGL-1, and L-selectin-PSGL-1 interactions.

    Conclusions:

    • Rosette formation biophysics are elucidated by the developed probabilistic model.
    • The model enables rosetting assays to be used as a semiquantitative tool for measuring receptor-ligand binding affinity.
    • This work provides a foundation for understanding and utilizing cell adhesion assays more effectively.