4.3 Review

What Can We Learn from Single Molecule Trajectories?

Journal

CURRENT PROTEIN & PEPTIDE SCIENCE
Volume 12, Issue 8, Pages 714-724

Publisher

BENTHAM SCIENCE PUBL LTD
DOI: 10.2174/138920311798841753

Keywords

Single particle tracking; 2D random walk; monte carlo simulation; diffusion models; confined diffusion; single molecule diffusion analysis; single molecule microscopy; statistical analysis of trajectories

Funding

  1. Austrian Science Fund (FWF) [Y250-B03, I 301-B12]
  2. Austrian Federal Ministry for Science and Research
  3. EMBO
  4. Austrian Science Fund (FWF) [I 301, Y 250] Funding Source: researchfish

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Diffusing membrane constituents are constantly exposed to a variety of forces that influence their stochastic path. Single molecule experiments allow for resolving trajectories at extremely high spatial and temporal accuracy, thereby offering insights into en route interactions of the tracer. In this review we discuss approaches to derive information about the underlying processes, based on single molecule tracking experiments. In particular, we focus on a new versatile way to analyze single molecule diffusion in the absence of a full analytical treatment. The method is based on comprehensive comparison of an experimental data set against the hypothetical outcome of multiple experiments performed on the computer. Since Monte Carlo simulations can be easily and rapidly performed even on state-of-the-art PCs, our method provides a simple way for testing various - even complicated - diffusion models. We describe the new method in detail, and show the applicability on two specific examples: firstly, kinetic rate constants can be derived for the transient interaction of mobile membrane proteins; secondly, residence time and corral size can be extracted for confined diffusion.

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