Abstract
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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Acknowledgements
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.).
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J.E. and M.L. conceived the method, M.L. designed the vbSPT algorithm, M.L. and F.P. implemented and tested the algorithm, F.P. designed and implemented the image analysis and particle-tracking algorithms, and C.U. cloned and characterized the bacterial strains. F.P. and J.E. built the optical setup. F.P., C.U. and J.E. designed the experiments, and C.U. and F.P. performed the experiments. F.P., M.L., C.U. and J.E. wrote the manuscript.
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Supplementary Text and Figures
Supplementary Tables 1–7 and Supplementary Notes 1–5 (PDF 1053 kb)
Supplementary Software
vbSPT (variational Bayes single-particle tracking) software (ZIP 6389 kb)
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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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DOI: https://doi.org/10.1038/nmeth.2367
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