Uncovering diffusive states of the yeast proton pump, Pma1, and how labeling method can change diffusive behavior

TL;DR

This study compares how different labeling methods affect the observed diffusive behavior of yeast membrane protein Pma1, revealing that labeling can significantly alter mobility measurements and demonstrating the effectiveness of the pEMv2 analysis method.

Contribution

It introduces a novel light-touch labeling scheme for Pma1 and evaluates how labeling impacts diffusion, using pEMv2 to classify diffusive states and validate results against theoretical models.

Findings

Labeling method significantly influences Pma1 diffusion measurements.

pEMv2 classifies Pma1 into immobile and mobile states with different fractions.

Experimental data aligns well with Gaussian random process models.

Abstract

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 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) [Physical Review E 94, 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 (0.1) than the mobile fraction of TRAP-labeled Pma1 tracks (0.5). 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. 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.