Chalmers Conferences, 9th European Conference on Mathematical and Theoretical Biology

Benchmarking analysis methods for live cell single particle tracking using simulated microscopy
Martin Lindén, Johan Elf

Last modified: 2014-06-09

Abstract


Single particle tracking in live cells is emerging as a quantitative and non-invasive tool for systems biology. A particularly promising direction is the possibility to monitor chemical reactions in vivo by exploiting the fact that small molecules diffuse slower than large ones, so that a fluorescently tagged ligand will change diffusion constant as it associates and dissociates from its binding partners. We have developed an analysis suite, vbspt.sourceforce.net (1), that uses a Bayesian treatment of hidden Markov models to learn the number of diffusive states and their interconversion rates from position trajectories of diffusing particles with random jumps in diffusion constant.

However, limitations in microscopy and fluorescence labeling techniques influence the resolution of the method, and live cells are more complex than the model assumptions used by vbSPT. To learn more about how such effects influences our analysis and limits the kind of mechanisms that can be resolved, we are developing computational tools to simulate live cell microscopy, using a combination of reaction-diffusion kinetics and photophysics models. The simulations include more physical realism than the models on which vbSPT are based, and are thus suitable for benchmarking, and for optimizing experimental conditions.

In this talk, I will give a brief introduction to single particle tracking, describe the mathematics and models underlying the vbSPT analysis suite, and show some preliminary results and lessons from our analysis of simulated data.

1. Persson F*, Lindén M*, Unoson C, Elf J (2013) Extracting intracellular diffusive states and transition rates from single-molecule tracking data. Nat Methods 10:265–269. * Equal contributions.


Keywords


hidden markov model;bayesian statistics;single particle tracking;superresolution microscopy