Conformational transitions in the glycine-bound GluN1 NMDA receptor LBD via single-molecule FRET

Abstract

The N-methyl-D-aspartate receptor (NMDAR) is a member of the glutamate receptor family of proteins and is responsible for excitatory transmission. Activation of the receptor is thought to be controlled by conformational changes in the ligand binding domain (LBD); however, glutamate receptor LBDs can occupy multiple conformations even in the activated form. This work probes equilibrium transitions among NMDAR LBD conformations by monitoring the distance across the glycine-bound LBD cleft using single-molecule Förster resonance energy transfer (smFRET). Recent improvements in photoprotection solutions allowed us to monitor transitions among the multiple conformations. Also, we applied a recently developed model-free algorithm called "step transition and state identification" to identify the number of states, their smFRET efficiencies, and their interstate kinetics. Reversible interstate conversions, corresponding to transitions among a wide range of cleft widths, were identified in the glycine-bound LBD, on much longer timescales compared to channel opening. These transitions were confirmed to be equilibrium in nature by shifting the distribution reversibly via denaturant. We found that the NMDAR LBD proceeds primarily from one adjacent smFRET state to the next under equilibrium conditions, consistent with a cleft-opening/closing mechanism. Overall, by analyzing the state-to-state transition dynamics and distributions, we achieve insight into specifics of long-lived LBD equilibrium structural dynamics, as well as obtain a more general description of equilibrium folding/unfolding in a conformationally dynamic protein. The relationship between such long-lived LBD dynamics and channel function in the full receptor remains an open and interesting question.

Figure 1

Measured ensemble smFRET distribution for the NMDAR LBD with glycine bound. (Dashed curves) Gaussian fits for each state; (solid magenta curve) total sum of Gaussians to provide a visual estimate for the goodness of fits of the seven-state model. (Inset) Structure of the NMDAR GluN1 isolated LBD bound to glycine, based on the PDB:1PB7 crystal structure. The protein strand was mutated at T193 (red marker) and S115 (blue marker) to cysteine to attach the acceptor and donor fluorophores. A His-tag was added to the protein at the N-terminus (yellow marker) to allow for immobilization. (Green-dashed line) FRET distance, which changes as the protein opens and closes the cleft.

Figure 2

The STaSI method determines the number and location of the states based on the denoised data. (a) All of the denoised smFRET trajectories were combined after local background subtraction and blink filtering, to provide a sufficiently large basis for the STaSI method to accurately locate the states, a 100× downsampled portion of which is shown. (b) The percentage assigned to each state from the total data set. FRET efficiency can be tracked horizontally from the data trajectory to the histogram. The contour of the distribution reflects the distribution of the measured FRET efficiency in Fig. 1.

Figure 3

Low-resolution raster-scanned image analysis shows how the average smFRET value from a single population of NMDAR LBD proteins changes as a function of GdmCl concentration. (a) A shift from high FRET efficiency to low FRET efficiency as denaturant concentration is increased can be seen in the histograms for the calculated FRET efficiency for identified molecules under each condition. (b) Combined average FRET efficiency for all of the areas as a function of GdmCl concentration. (c) Replotting the calculated average FRET efficiency against time elapsed for the denaturation experiment shows that by lowering the denaturant concentration the protein was able to recover, and that the denaturant’s effect on the NMDAR LBD is a reversible process; however, time-dependent photobleaching of the acceptor dye is also observed. The error bars plotted represent the distribution in the average among the different areas.

Figure 4

Two example single-molecule trajectories with the calculated FRET efficiency and state distribution. (a and d) The acceptor and donor signal for a single identified NMDAR LBD. The signal has been background-corrected and blink-filtered and shows a strong anticorrelation between the donor and acceptor, which is indicative of smFRET. (b and e) The corresponding apparent FRET efficiency for the signal in (a) and (d), respectively. The STaSI state at each time point is overlaid. (c and f) The smFRET histogram for each individual trajectory. The STaSI state histogram has also been overlaid and rescaled so that the maximum peak is the same height as the denoised maximum. (a–c) Example protein that remained stable in a high FRET efficiency state before transitioning into a stable lower FRET efficiency state and thus a more open-cleft conformation. (d–f) State-to-state movement is not one-directional and the NMDAR LBD can recover into the original state after visiting the open-cleft conformation.

Figure 5

Matrix of transition counts between the STaSI states. The state of the protein before the transition point defines the vertical axis, and the state that the NMDAR LBD transitions to is the horizontal axis. State transitions cannot occur between a state and itself, which nullifies the diagonal. (Color) Total number of transitions for that state pair.