Analysis of the Diffusivity Change from Single-Molecule Trajectories on Living Cells

With the wide application of live-cell single-molecule imaging and tracking of biomolecules at work, deriving diffusion state changes of individual molecules is of particular interest as these changes reflect molecular oligomerization or interaction with other cellular components and thus correlate...

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Bibliographic Details
Published in:Analytical chemistry (Washington) 2019-11, Vol.91 (21), p.13390-13397
Main Authors: Zhao, Rong, Yuan, Jinghe, Li, Nan, Sun, Yahong, Xia, Tie, Fang, Xiaohong
Format: Article
Language:English
Subjects:
Biomolecules
Cells (biology)
Chemistry
Diffusion
Diffusion coefficient
Diffusivity
Fluorescence
Markov chains
Membrane proteins
Membranes
Molecular interactions
Oligomerization
Receptors
Trajectories
Transition probabilities
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Summary:With the wide application of live-cell single-molecule imaging and tracking of biomolecules at work, deriving diffusion state changes of individual molecules is of particular interest as these changes reflect molecular oligomerization or interaction with other cellular components and thus correlate with functional changes. We have developed a Rayleigh mixture distribution-based hidden Markov model method to analyze time-lapse diffusivity change of single molecules, especially membrane proteins, with unknown dynamic states in living cells. With this method, the diffusion parameters, including diffusion state number, state transition probability, diffusion coefficient, and state mixture ratio, can be extracted from the single-molecule diffusion trajectories accurately via easy computation. The validity of our method has been demonstrated with not only experiments on synthetic trajectories but also single-molecule fluorescence imaging data of two typical membrane receptors. Our method offers a new analytical tool for the investigation of molecular interaction kinetics at the single-molecule level.
ISSN:0003-2700
1520-6882
DOI:10.1021/acs.analchem.9b01005