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

We present and analyze video-microscopy-based single-particle-tracking measurements of thebudding yeast (Saccharomyces cerevisiae) membrane protein, Pma1, fluorescently labeled either by directfusion to the switchable fluorescent protein, mEos3.2, or by a novel, light-touch, labeling scheme, in whicha 5 amino acid tag is directly fused to the C-terminus of Pma1, which then binds mEos3.2. The trackdiffusivity distributions of these two populations of single-particle tracks differ significantly, demonstratingthat labeling method can be an important determinant of diffusive behavior. We also applied perturbationexpectation maximization (pEMv2) (Koo and Mochrie in Phys Rev E 94(5):052412, 2016), which sortstrajectories into the statistically optimum number of diffusive states. For both TRAP-labeled Pma1 andPma1-mEos3.2, pEMv2 sorts the tracks into two diffusive states: an essentially immobile state and a moremobile state. However, the mobile fraction of Pma1-mEos3.2 tracks is much smaller (∼ 0.16) than themobile fraction of TRAP-labeled Pma1 tracks (∼ 0.43). In addition, the diffusivity of Pma1-mEos3.2’smobile 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 assesspEMv2’s performance, we compare the diffusivity and covariance distributions of the experimental pEMv2-sorted populations to corresponding theoretical distributions, assuming that Pma1 displacements realizea Gaussian random process. The experiment–theory comparisons for both the TRAP-labeled Pma1 andPma1-mEos3.2 reveal good agreement, bolstering the pEMv2 approach.