Quantum dots reveal heterogeneous membrane diffusivity and dynamic surface density polarization of dopamine transporter

Abstract

The presynaptic dopamine transporter mediates rapid reuptake of synaptic dopamine. Although cell surface DAT trafficking recently emerged as an important component of DAT regulation, it has not been systematically investigated. Here, we apply our single quantum dot (Qdot) tracking approach to monitor DAT plasma membrane dynamics in several heterologous expression cell hosts with nanometer localization accuracy. We demonstrate that Qdot-tagged DAT proteins exhibited highly heterogeneous membrane diffusivity dependent on the local membrane topography. We also show that Qdot-tagged DATs were localized away from the flat membrane regions and were dynamically retained in the membrane protrusions and cell edges for the duration of imaging. Single quantum dot tracking of wildtype DAT and its conformation-defective coding variants (R60A and W63A) revealed a significantly accelerated rate of dysfunctional DAT membrane diffusion. We believe our results warrant an in-depth investigation as to whether compromised membrane dynamics is a common feature of brain disorder-derived DAT mutants.

Data_Sheet_1.DOCX

“…Analysis of SIM images of YFP-SERT distribution corroborated our preliminary observation that YFP-SERT density was markedly increased in the membrane edges and protrusions (Figure 9). This phenomenon is similar to conformationdependent preferential accumulation of dopamine transporter in membrane protrusions (filopodia) that was previously observed in several neuronal and non-neuronal heterologous expression hosts (Caltagarone et al, 2015;Kovtun et al, 2019). QD tracking of YFP-SERT localized to membrane protrusions revealed a simple Brownian, unrestricted pattern of diffusion that resembles surface dynamics of the extrasynaptic pool of neuronal receptors (Maynard and Triller, 2019).…”

“…In the case of simple diffusion, the average RD(N, n) should be 1 (Kusumi et al, 1993). Brownian trajectories with a diffusion coefficient of 0.1 µm 2 /s were generated by random walk simulations using experimentally relevant trajectory lengths (100, 200, 300, 400, 500, and 600 steps) to establish the effective cutoff values of RD at 25 frames (Kovtun et al, 2019). RD values within the 2.5th-97.5th percentile range were taken to represent statistical variations in Brownian motion, and those outside of the range taken as restricted diffusion.…”

“…A range of diffusive behavior was readily apparent from the reconstructed QD trajectory shape. Next, a Relative Deviation (RD) analysis was implemented to classify experimental QD trajectories as freely diffusing or restricted on the basis of mean square displacement (MSD)-t curve deviation compared to simulated trajectories undergoing simple Brownian motion (Kusumi et al, 1993;Kovtun et al, 2019). Additionally, QD trajectories diffusing at a rate slower than D cutoff = 5 × 10 −4 µm 2 /s (95th percentile of diffusion coefficient distribution of QDs dropcast onto a coverslip) were categorized as immobilized (Dahan et al, 2003;Kovtun et al, 2019).…”

Membrane Nanoscopic Organization of D2L Dopamine Receptor Probed by Quantum Dot Tracking

“…The diffusion coefficient D 2–5 was calculated from the slope of the first 2–5 points of the MSD plot versus time with the equation: where σ x is the spot localization accuracy in one direction (i.e., is the ordinate at the origin of the linear fit). Trajectories of Qdots greater than the previously determined immobile particle threshold 5 × 10 −4 μm 2 /s [ 14 , 53 ] were used for statistical comparison via the nonparametric Mann–Whitney U test and Kolmogorov–Smirnov test. Merge and split events occurring in Qdot time-lapse image series were determined by using the fully functional linear assignment problem tracker in TrackMate [ 47 , 48 ] while allowing the detection of Qdot signal splitting and merging with a maximum displacement of 1 μm.…”

A Novel Biotinylated Homotryptamine Derivative for Quantum Dot Imaging of Serotonin Transporter in Live Cells

“…In the case of simple diffusion, the average RD(N, n) should be 1 ( Kusumi et al, 1993 ). Brownian trajectories with a diffusion coefficient of 0.1 μm 2 /s were generated by random walk simulations using experimentally relevant trajectory lengths (100, 200, 300, 400, 500, and 600 steps) to establish the effective cutoff values of RD at 25 frames ( Kovtun et al, 2019 ). RD values within the 2.5th–97.5th percentile range were taken to represent statistical variations in Brownian motion, and those outside of the range taken as restricted diffusion.…”