Uncovering diffusive states of the yeast membrane protein, Pma1, and how labeling method can change diffusive behavior

The European physical journal. E, Soft matter(2023)

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摘要
We present and analyze video-microscopy-based single-particle-tracking measurements of the budding yeast ( Saccharomyces cerevisiae ) membrane protein, Pma1, fluorescently labeled either by direct fusion to the switchable fluorescent protein, mEos3.2, or by a novel, light-touch, labeling scheme, in which a 5 amino acid tag is directly fused to the C-terminus of Pma1, which then binds mEos3.2. The track diffusivity distributions of these two populations of single-particle tracks differ significantly, demonstrating that labeling method can be an important determinant of diffusive behavior. We also applied perturbation expectation maximization (pEMv2) (Koo and Mochrie in Phys Rev E 94(5):052412, 2016), which sorts trajectories into the statistically optimum number of diffusive states. For both TRAP-labeled Pma1 and Pma1-mEos3.2, pEMv2 sorts the tracks into two diffusive states: an essentially immobile state and a more mobile state. However, the mobile fraction of Pma1-mEos3.2 tracks is much smaller ( ∼ 0.16 ) than the mobile fraction of TRAP-labeled Pma1 tracks ( ∼ 0.43 ). In addition, the diffusivity of Pma1-mEos3.2’s mobile state is several times smaller than the diffusivity of TRAP-labeled Pma1’s mobile state. Thus, the two different labeling methods give rise to very different overall diffusive behaviors. To critically assess pEMv2’s performance, we compare the diffusivity and covariance distributions of the experimental pEMv2-sorted populations to corresponding theoretical distributions, assuming that Pma1 displacements realize a Gaussian random process. The experiment–theory comparisons for both the TRAP-labeled Pma1 and Pma1-mEos3.2 reveal good agreement, bolstering the pEMv2 approach. Graphic Abstract
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yeast membrane protein,diffusive states
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