Applying Perturbation Expectation-Maximization to Protein Trajectories of Rho GTPases
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Single-particle tracking (SPT) enables the ability to noninvasively probe the diffusive motions of individual proteins inside living cells at sub-diffraction-limit resolution. The stochastic motions of diffusing Rho GTPases encode information concerning its interactions with binding partners and with its local environment. By identifying Rho GTPases’ diffusive states, insight can thus be gained into the spatiotemporal in vivo biochemistry inside live cells at a single-molecule resolution. Here we present perturbation expectation-maximization (pEM), a computational method which simultaneously analyzes a population of protein trajectories to uncover the system of diffusive behaviors: (1) the number of diffusive states, (2) the properties of each such diffusive state, and (3) the probabilities of each trajectory to a respective diffusive state. We provide a step-by-step guide to pEM and discuss considerations for its practical applications, including pEM’s capabilities and limitations.
Key wordsDiffusion Diffusive states Perturbation expectation-maximization pEM Rho GTPase Single-particle tracking
This work was supported by National Science Foundation Grant No. PHY1305509, and by the Raymond and Beverly Sackler Institute for Physical and Engineering Biology.
- 8.Koo PK and Mochrie SG (2015) Perturbation Expectation-Maximization MATLAB Code. https://github.com/mochrielab/pEM
- 9.Chenouard N, Smal I, de Chaumont F, Maska M, Sbalzarini IF, Gong Y, Cardinale J, Carthel C, Coraluppi S, Winter M, Cohen AR, Godinez WJ, Rohr K, Kalaidzidis Y, Liang L, Duncan J, Shen H, Xu Y, Magnusson KE, Jalden J, Blau HM, Paul-Gilloteaux P, Roudot P, Kervrann C, Waharte F, Tinevez JY, Shorte SL, Willemse J, Celler K, van Wezel GP, Dan HW, Tsai YS, Ortiz de Solorzano C, Olivo-Marin JC, Meijering E (2014) Objective comparison of particle tracking methods. Nat Methods 11:281–289CrossRefPubMedPubMedCentralGoogle Scholar
- 11.Blair D and Dufresne E (2008) The MATLAB particle tracking code repository. http://site.physics.georgetown.edu/matlab/
- 13.Bishop CM (2006) Pattern recognition and machine learning. Springer, New YorkGoogle Scholar
- 14.Koo PK and Mochrie SG (2016) mleBIC MATLAB Code. https://github.com/mochrielab/mleBIC
- 15.Koo PK and Mochrie SG (2016) pEMv2 MATLAB Code. https://github.com/mochrielab/pEMv2