The high-energy transition state of the glutamate transporter homologue GltPh

Abstract

Membrane transporters mediate cellular uptake of nutrients, signaling molecules, and drugs. Their overall mechanisms are often well understood, but the structural features setting their rates are mostly unknown. Earlier single-molecule fluorescence imaging of the archaeal model glutamate transporter homologue Glt_Ph from Pyrococcus horikoshii suggested that the slow conformational transition from the outward- to the inward-facing state, when the bound substrate is translocated from the extracellular to the cytoplasmic side of the membrane, is rate limiting to transport. Here, we provide insight into the structure of the high-energy transition state of Glt_Ph that limits the rate of the substrate translocation process. Using bioinformatics, we identified Glt_Ph gain-of-function mutations in the flexible helical hairpin domain HP2 and applied linear free energy relationship analysis to infer that the transition state structurally resembles the inward-facing conformation. Based on these analyses, we propose an approach to search for allosteric modulators for transporters.

Keywords: conformational dynamics; glutamate transporter; single-molecule fluorescence; static disorder; transition-state structure.

Figure 1. Gain‐of‐function Glt_Ph variants

1. A

   A Glt_Ph protomer in the OFS and IFS is shown in semitransparent surface representation with the scaffold and transport domains colored wheat and blue, respectively. HP1 (yellow) and HP2 (red) are emphasized as cartoons. Bound l‐Asp and Na⁺ ions are shown as green sticks and spheres, respectively. Select amino acids mutated in this study are shown as black spheres.

2. B

   Schematic representation of the Glt_Ph transport cycle showing one protomer. Comparatively rapid and slow steps of the cycle are shaded pink and blue, respectively.

3. C

   The topology of a Glt_Ph protomer showing tested mutation sites (circles) with filled circles corresponding to those shown in (A).

4. D, E

   Representative examples of dose–response curves and time courses. Lines through the dose–response curves are fits to the Michaelis–Menten equation; time courses are fitted to linear equations. Shown are means and standard errors over at least three independent repeats.

5. F

   Fold increase (positive values) or decrease (negative values) in the initial uptake rates of the variants relative to WT Glt_Ph. Circles are averages of technical triplicates. Bars are means over independent repeats (as indicated). The dashed line marks a fourfold increase in the initial rate.

Data information: Color coding is the same in all panels. In (D–F), data are colored according to the structural elements where the mutations are located; combination mutants are colored purple. See also Appendix Fig S1 and Appendix Tables S1 and S2.

Figure 2. Transport domain dynamics under apo (A) and transport (B) conditions

1. A, B

   Schematic representations of the experimental conditions are shown on the far left. Data are shown for WT Glt_Ph and select gain‐of‐function mutants, as indicated above the panels. Transition density plots (top of each panel) show the frequency of transitions between the E_FRET values. The number of trajectories analyzed (N) and the population‐wide mean frequency of transitions are shown on the panels. Representative 50‐s sections of single‐molecule E_FRET trajectories (middle) with raw data in black and idealizations in brown. Scale bar and the conformational states corresponding to the low and intermediate E_FRET values are shown to the left of the panels. Dwell‐time distributions for the OFS in blue and the IFS in red (bottom). Mean dwell times are shown on the panels in corresponding colors. Black lines represent photobleaching survival plots normalized from 1 to 0. Shown are means and standard errors over at least three independent repeats. See also Appendix Figs S2–S4.

Figure 3. Correlations between activity, dynamics, and substrate affinity

1. Changes in the initial rates of substrate uptake (gray bars), transport domain dynamics (black bars), and l‐Asp dissociation constant (white bars) of the mutant Glt_Ph variants relative to the WT transporter. The transition frequencies were measured under non‐equilibrium transport conditions, and frequencies obtained in the presence of d,l‐TBOA were subtracted from the data. Error bars represent standard errors for at least three independent measurements.

2. Cartoon representation of the crystal structure of Y204L/A345V/V366A Glt_Ph in the presence of saturating concentrations of Na⁺ ions and l‐Asp (colored as in Fig 1A; PDB accession number: 6V8G) superimposed onto the structure of WT Glt_Ph in the OFS (gray, PDB accession number: 2NWX). l‐Asp and Na⁺ are shown as spheres and colored by atom type.

3. Close‐up of the substrate‐binding site. Green mesh represents an omit electron density map for l‐Asp contoured at 4σ. Substrate‐coordinating residues are shown as sticks.

4. Superimposition of the mutant (colors) and the WT (gray) hairpins aligned on HP1. See also Appendix Figs S4 and S5 and Appendix Tables S2–S4.

Figure 4. Kinetic heterogeneity of the transport domain dynamics

1. Dwell‐time distributions of the OFS (blue) and the IFS (red) for WT (top) and K290A (bottom) Glt_Ph observed under equilibrium conditions in saturating Na⁺/l‐Asp (left). Lines are fits to three exponentials. Data are averages and standard errors of at least three independent measurements.

2. Representative E_FRET trajectories of WT Glt_Ph showing different transition frequencies. Raw data are in black, and idealizations are in brown. Scale bar is above the trajectories.

3. Distribution of the WT (top) and the K290A Glt_Ph (bottom) molecules with different mean transition frequencies (white bars). N is the number of trajectories longer than 90 s used in the analysis. The stacked black bars are fractions of trajectories without transitions. Pink bars show the expected binomial distribution if all trajectories shared the mean transition frequency of 0.04 s^‐1 for the WT and 0.34 s^‐1 for the K290A. Data are averages and standard errors of at least three independent measurements.

4. 2D histograms of the consecutive dwell lengths in the OFS (top) and the IFS (bottom). From left to right: calculated distribution of dwell times randomly selected from the distributions in panel A; measured distribution for WT Glt_Ph and the K290A mutant.

5. Representative trajectories of the WT (left) and the K290A (right) Glt_Ph molecules showing switching between dynamic modes. Raw data are in black, and idealizations are in brown (top). Black and gray bars under the trajectories indicate apparent slower and faster dynamic modes. Survival plots for the OFS and the IFS (middle). Solid lines are fits to a single (IFS) and double (OFS) exponentials. Dashed lines (OFS only) are rejected fits to single exponentials. Autocorrelation plots of the sequential dwell durations (bottom). Solid lines are fits to single exponentials to guide the eye. See also Appendix Figs S6–S9.

Figure 5. Distributions of the OFS and the IFS lifetime pairs for individual molecules

1. A, B

   2D histograms of lifetime pairs obtained for trajectories exhibiting single‐exponential behavior. N is the number of traces used. Scale bar shows relative density normalized by the number of molecules. Above and to the right of each panel are stacked histograms of, respectively, the OFS and the IFS lifetimes of the analyzed molecules (open bars) and the photobleaching time of molecules showing no transitions (black bars). Data from three independent measurements were combined for presentation.

2. C

   The mean lifetimes of the molecules falling within 30% of the most populated bins of the 2D histograms (yellow to red; see Appendix Figure S11 for details). The open blue bar represents the calculated mean OFS lifetime for WT Glt_Ph (see main text for details). Shown are means and standard errors of the mean of at least three independent measurements.

Figure 6

Transition‐state analysis

1. A

   Schematic representation of the expected Leffler α‐values if the transition state is structurally similar to the OFS (left) or the IFS (right) or if it assumes an intermediate structure (middle). Color coding is the same as in Fig 1.

2. B–H

   LFER analysis. Free energy changes plotted in units of ‐RT. The activation free energies of the OFS‐to‐IFS transitions (blue) and the IFS‐to‐OFS transitions (red) were calculated by subtracting the energies of the reference states (black, at the origin) from the energies of the mutated protein variants. The K290A mutation was introduced into the WT, Y204L, A345V/V366A, and Y204/A345V/V366A backgrounds, either substrate‐bound or apo (B and G, respectively). R276S/M395R and M362V mutations were introduced into the WT background (C, E, and H). For the transition from Na⁺/l‐Asp‐bound to apo state, the free energies measured for the transporters in the presence of Na⁺ and l‐Asp were subtracted from those measured for the apo transporters (D). Mutations at A345, V366, and Y204 sites and their combinations were introduced within the WT and K290A backgrounds (E). LFERs for the perturbations introduced within the WT background use back‐calculated WT transition rates (see main text, open symbols). Data are averages over at least three independent repeats and errors are propagated from the standard error of the means in each replicate. (F) Schematic summary of sites where perturbations led to changes in the transition‐state energy that scaled with the IFS energy (blue) and where they affected only the transition state (gray). See also Appendix Figs S11–S14.

Figure 7. Proposed model for allosteric modulation

1. A, B

   A free energy diagram of the transport cycle (black) and its modulation (colors) by positive or negative allosteric modulators, PAMs (A) or NAMs (B), respectively. Cartoon representations of the low‐energy states are below the diagrams and are colored as in Fig 1. The barrier heights are not to scale to the measured rates. Substrate binding to the apo OFS precedes isomerization into the IFS via the highest energy TS (‡) that structurally resembles the IFS. Substrate release and recycling into the OFS complete the cycle. PAMs, shown as squares in the cartoons of the states, bind with higher affinity to the IFS (dark cyan squares) than to the OFS (light cyan squares). Therefore, they stabilize all IFS‐like states, including the TS, and smoothen the energy landscape (cyan line). PAMs that bind too tightly to the IFS may become inhibitory, as apo OFS becomes a high‐energy state (dotted blue line). NAMs bind tighter to the OFS ((B), dark magenta squares) than to the IFS (light magenta squares), increase the ruggedness of the landscape (magenta line), and slow down transport.

2. C

   Simulations of the transport rates in the absence and presence of PAMs. The left panel shows the transport cycle with the used rate constants (Materials and Methods). PAM effects were considered equal on both OFS‐to‐IFS isomerizations (blue rate constants). The acceleration of transport becomes rate‐limited by the IFS‐to‐OFS isomerization of the apo transporter as PAM action increases OFS‐to‐IFS isomerizations (red rate constant). Middle and right panels show simulated uptake and fold increase in the initial rates, respectively, in the presence of PAMs that increase k_{OFS to IFS} by the indicated number of folds (from cyan to dark blue). Simulations of cycles with = $k_{\mathit{OFStoIFS}}^{\mathit{bound}}$0.1 s^‐1 illustrate higher PAM potency (gray).