SPECTROSCOPY, IMAGING, OTHER TECHNIQUES |
Bayesian Inference for Improved Single Molecule Fluorescence Tracking
Ji Won Yoon 1, Andreas Bruckbauer 1, William J. Fitzgerald 1 and David Klenerman 2*
1 University of Cambridge
2 cambridge university
* To whom correspondence should be addressed. E-mail: dk10012{at}cam.ac.uk.
Submitted on June 27, 2007
Revised on September 1, 2007
Accepted on 8 February 2008
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Abstract |
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Single molecule tracking is widely used to monitor the change in position of lipids and proteins in living cells. In many experiments, where molecules are tagged with a single or small number of fluorophores, the signal-to-noise ratio may be limiting, the number of molecules is not known and fluorophore blinking and photobleaching can occur. All these factors make accurate tracking over long trajectories difficult and hence there is still a pressing need to develop better algorithms to extract the maximum information from a sequence of fluorescence images. We describe here a Bayesian based inference approach, based on a trans-dimensional Sequential Monte Carlo method that utilizes both the spatial and temporal information present in the image sequences. We show using model data, where the real trajectory of the molecule is known, that our method allows accurate tracking of molecules over long trajectories even with low signal-to-noise ratio and in the presence of fluorescence blinking and photobleaching. The method is then applied to real experimental data.
Key Words:
Sequential Monte Carlo method, cell imaging, fluorophore blinking, photobleaching, spatial and temporal information
