SKM 2021 – scientific programme
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DY: Fachverband Dynamik und Statistische Physik
DY 1: Statistical physics of biological systems (joint session BP/DY)
DY 1.4: Talk
Monday, September 27, 2021, 11:00–11:15, H1
Maximum likelihood estimates of diffusion coefficients from single-particle tracking experiments — •Jakob Tómas Bullerjahn1 and Gerhard Hummer1,2 — 1Department of Theoretical Biophysics, MPI of Biophysics, Frankfurt am Main, Germany — 2Institute of Biophysics, Goethe University, Frankfurt am Main, Germany
Single-molecule localization microscopy allows practitioners to locate and track labeled molecules in biological systems. When extracting diffusion coefficients from the resulting trajectories, it is common practice to perform a linear fit on mean-squared-displacement curves. However, this strategy is suboptimal and prone to errors. Recently, it was shown that the increments between the observed positions provide a good estimate for the diffusion coefficient, and their statistics are well-suited for likelihood-based analysis methods. Here, we revisit the problem of extracting diffusion coefficients from single-particle tracking experiments subject to static noise and dynamic motion blur using the principle of maximum likelihood. Taking advantage of an efficient real-space formulation, we extend the model to mixtures of subpopulations differing in their diffusion coefficients, which we estimate with the help of the expectation-maximization algorithm. This formulation naturally leads to a probabilistic assignment of trajectories to subpopulations. We employ the theory to analyze experimental tracking data that cannot be explained with a single diffusion coefficient, and test how well the data conform to the model assumptions. https://doi.org/10.1063/5.0038174