Inferring transient particle transport dynamics in live cells

Abstract

Live-cell imaging and particle tracking provide rich information on mechanisms of intracellular transport. However, trajectory analysis procedures to infer complex transport dynamics involving stochastic switching between active transport and diffusive motion are lacking. We applied Bayesian model selection to hidden Markov modeling to infer transient transport states from trajectories of mRNA-protein complexes in live mouse hippocampal neurons and metaphase kinetochores in dividing human cells. The software is available at http://hmm-bayes.org/.

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Figure 1: Particle-trajectory analysis methods applied to neuronal mRNPs.
Figure 2: HMM-Bayes analysis of neuronal mRNPs.
Figure 3: HMM-Bayes analysis of oscillating metaphase kinetochores.

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Acknowledgements

Research reported in this publication was supported by grants from the US National Institutes of Health (NIH) National Institute of Mental Health (U01 MH106011) and the US National Science Foundation Physics of Living Systems (PHY 1305537) to M.B., an NIH grant from the National Institute of Neurological Diseases and Stroke (NS083085-19) to R.H.S., a Scholar award from the Leukemia & Lymphoma Society and an NIH grant from the National Institute of General Medical Sciences (GM088313) to I.M.C., and a Schroedinger fellowship from the Austrian Science Fund to K.-C.S. We also thank M. Linden for helpful discussions.

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Authors

Contributions

N.M. and M.B. conceived the method; N.M., A.D., K.P. and M.B. developed the theory; N.M. and Z.B. implemented the method; H.Y.P., Z.K., B.P.E. and R.H.S. collected mRNP data sets and advised on their analysis; K.-C.S. and I.M.C. collected kinetochore data sets and advised on their analysis; Z.B. and N.M. analyzed experimental data sets; N.M., Z.B. and M.B. wrote the paper.

Corresponding author

Correspondence to Mark Bathe.

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Competing interests

The authors declare no competing financial interests.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–27, Supplementary Table 1 and Supplementary Notes 1–7 (PDF 8120 kb)

Motion of neuronal mRNP #1 from Fig. 1

Raw fluorescence images of the mRNP from Fig. 1 in a live neuron. The left panel also shows the tracked particle positions (pink circles) and the resulting trajectory annotated with HMM-Bayes as in Fig. 1d. (AVI 1226 kb)

Motion of neuronal mRNP #2 from Fig. 2a

Raw fluorescence images of the mRNP from Fig. 2a in a live neuron. The left panel also shows the tracked particle positions (pink circles) and the resulting trajectory annotated with HMM-Bayes as in Fig. 2a. (AVI 4225 kb)

Motion of neuronal mRNP #3 from Fig. 2b

Raw fluorescence images of the mRNP from Fig. 2b in a live neuron. The left panel also shows the tracked particle positions (pink circles) and the resulting trajectory annotated with HMM-Bayes as in Fig. 2b. (AVI 5417 kb)

Supplementary Software

HMM-Bayes analysis package and associated documentation. (ZIP 10511 kb)

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Monnier, N., Barry, Z., Park, H. et al. Inferring transient particle transport dynamics in live cells. Nat Methods 12, 838–840 (2015). https://doi.org/10.1038/nmeth.3483

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