We provide an analytical tool based on a variational Bayesian treatment of hidden Markov models to combine the information from thousands of short single-molecule trajectories of intracellularly diffusing proteins. The method identifies the number of diffusive states and the state transition rates. Using this method we have created an objective interaction map for Hfq, a protein that mediates interactions between small regulatory RNAs and their mRNA targets.
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We thank I. Barkefors for her careful and critical reading of the manuscript. M.L. is grateful to C.H. Wiggins and J.-W. van de Meent for insightful discussions. This work was supported by the European Research Council (J.E.), the Knut and Alice Wallenberg Foundation (J.E.), Vetenskapsrådet (J.E.), the Göran Gustafsson Foundation (J.E.), the Wenner-Gren Foundations (M.L.) and the Center for Biomembrane Research (M.L.).
The authors declare no competing financial interests.
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Persson, F., Lindén, M., Unoson, C. et al. Extracting intracellular diffusive states and transition rates from single-molecule tracking data. Nat Methods 10, 265–269 (2013). https://doi.org/10.1038/nmeth.2367
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