Structural basis for pH-responsive amino acid transport via SLC7A4.

Domain: biology
Published: 2026-03-28
Editorial outcome: major_revision

Abstract
The transport of amino acids across cell membranes is essential for metabolism, neuronal signalling, and immune system function. The amino acid polyamine organocation (APC) superfamily controls amino acid transport via mechanisms including amino acid exchange, facilitative diffusion, and sodium- or proton -coupled transport. Although many mammalian APC members functioning as exchangers and sodium-coupled systems have been identified, the mechanisms underlying pH-regulated amino acid transport in mammalian cells remain unclear. Here, we show that the plasma membrane amino acid transporter SLC7A4 is regulated by low extracellular pH and functions as a leucine transporter in human cells. Using Cryo-EM structures of the plant homologue, CAT4, from Arabidopsis thaliana in outward-open apo and L-ornithine-bound states, as well as transport assays and molecular dynamics simulations based on homology models of the human transporter, we identify residues responsible for amino acid selectivity and support an allosteric mechanism that links ligand recognition to pH regulation. This mechanism is consistent with an evolutionary link to proton-coupled prokaryotic homologues. Overall, our findings provide a structural and functional basis for pH-gated leucine transport by the human SLC7A4 transporter and offer a framework for understanding amino acid selectivity within the wider SLC7 family.

Introduction
Amino acids are essential for protein synthesis and serve as precursors for nucleotides, lipids, and neurotransmitters, while also functioning as intermediates in energy production via the TCA cycle1,2. Branched-chain and cationic amino acids, such as leucine, arginine, and lysine, play a crucial role in regulating cellular metabolism by activating the mTOR complex3,4, supporting the immune system through T-cell activation, and facilitating cancer cell proliferation5. Understanding the molecular mechanisms underpinning amino acid transport within cells is therefore essential for developing new therapies for a range of human diseases, spanning immunology, oncology, metabolic, and neurological disorders6,7.

Currently, around 40 different amino acid transporters have been identified, which belong to seven distinct solute carrier (SLC) families8. Among these, the SLC7 family plays an essential role in regulating the uptake and distribution of all 20 canonical amino acids in the body9. Many SLC7 members are the focus of clinical studies evaluating inhibitors to treat various types of cancer10-14, neurological diseases15 and to enable targeted drug delivery across the blood-brain barrier16.

The SLC7 family comprises 13 members, and can be broadly divided into two subgroups: the cationic amino acid transporters (SLC7A1-A 4; CATs) and the heteromeric amino acid transporters (SLC7A5-A13; HATs)9,17. The HATs comprise a catalytic transporter, or light chain (LAT; e.g., SLC7A5/LAT1, SLC7A8/LAT2), a ssociated with a type-II glycoprotein heavy chain (SLC3A1 or SLC3A2) for trafficking. Both the CAT and HAT subfamilies are members of the larger APC superfamily18, which shares a common 12-transmembrane (TM) domain fold, commonly referred to as the LeuT fold19. Within this fold, the first five TM helices are related to the second five helices via a pseudo-two-fold symmetry axis running parallel to the plane of the membrane and characterised by TMs 1 and 6 adopting discontinuous regions in the middle of the transporter20,21. Structures of many eukaryotic HAT transporters have now been reported22-31. Interestingly, while these studies have revealed a nearly identical binding site for amino acids within the discontinuous regions of TMs 1 and 6, each specific member of the SLC7 family appears to have adopted a unique mechanism to select for specific pools of amino acids9, making detailed studies necessary to understand amino acid selectivity within this transporter family30.

The CATs and HATs share a close structural homology with amino acid transporters in the SLC36 and SLC38 families, which are often associated with pH-driven amino acid transport across organelle membranes, such as the endosome and lysosome3,32,33. However, to date, the role of pH in regulating transport within the mammalian SLC7 family remains understudied, as does the molecular mechanisms underpinning pH-regulated amino acid transport more generally within eukaryotic cells. Recently, we reported the mechanism of proton-coupled amino acid transport in a distantly related amino acid transporter from the hyperthermophilic bacterium Geobacillus kaustophilus34, GkApcT, and noted the close homology with CAT homologues in A. thaliana and the human transporter SLC7A4, which is currently considered an orphan transporter35.

Our previous study identified Glu115 on TM3, which, together with Asp237 on TM6, couples alanine transport in GkApcT to the proton electrochemical gradient34,36. Homologues of mammalian transporters in plants can provide valuable models for understanding human transporters37. Indeed, whereas mammalian CAT1, 2, and 3 operate as facilitators38,39, in plants they are pH-dependent40, similar to mammalian SLC36 and SLC38 organellar amino acid transporters41. A. thaliana has a cluster of nine CATs with close sequence similarity to mammalian CAT genes40,42-45, of which CAT1, CAT5 and CAT6 have been reported to mediate pH-dependent amino acid uptake46,47. Intriguingly, all of the CAT homologues in A. thaliana conserve the acidic residue on TM3, whereas in the human SLC7s, only SLC7A4 conserves an acidic side chain in this position in the transporter (Supplementary Fig. 1a-b), leading us to speculate whether SLC7A4 might also function as a pH-regulated amino acid transporter in plants and humans.

The human SLC7A4 gene was first identified in 1998 and mapped to chromosome 22q11.2, a region often deleted in patients with velocardiofacial syndrome (VCFS, also known as Shprintzen syndrome)48. Although the gene shares high sequence identity to SLC7A1 (CAT1) and SLC7A2 (CAT2),35 studies utilising Xenopus oocytes demonstrated that human SLC7A4 does not transport the cationic amino acids arginine or lys ine 35. Thus, many questions remained open concerning the function of SLC7A4, its mechanism of action and its links to human physiology and disease.

Here, we identify SLC7A4 as a pH-responsive plasma membrane leucine transporter in humans and demonstrate that its plant homologue can bind both cationic amino acids and leucine. Combining structural, biochemical and functional data, we further demonstrate the close evolutionary conservation between human and plant transporters and identify key side chains required for cationic amino acid recognition within the SLC7 family.

Results
Structure determination of SLC7A4/CAT4 from Arabidopsis thaliana.
To identify suitable proteins for biochemical analysis, we screened SLC7A4 homologues from five different species, encompassing mammals, fish, and plants (Supplementary Fig. 1c-d). Based on recombinant expression levels, we chose to pursue the purification and structural characterisation of SLC7A4/CAT4 from Arabidopsis thaliana, hereafter referred to as AtCAT4. AtCAT4 shares 35% identity and 57% similarity with human SLC7A4, increasing to 48% identity and 78% similarity for residues within 6 Å of the substrate-binding site. The plant CAT4 homologue was of particular interest, as it provided a closer evolutionary link to the human transporter than the bacterial counterpart, GkApcT (Supplementary Fig. 1b). Crucially, AtCAT4 retains conservation of a protonatable side chain at the equivalent position to Glu115 on TM3 in GkApcT (Supplementary Fig. 1a). Using differential scanning fluorimetry (nanoDSF) on detergent-purified AtCAT4, we screened the ability of all proteinogenic amino acids (excluding L-tryptophan, due to spectral overlap in the fluorescence signal), alongside non-proteinogenic amino acids L-ornithine and L-citrulline, to elicit thermal stabilisation (Fig. 1a). We observed notable stabilisation in the presence of cationic amino acids (CAAs) L-Arginine (2.0 ºC), L-Lysine (3.0 ºC) and L-Ornithine (3.2 ºC), in addition to the branched chain amino acid (BCAA) L-Leucine (1.9 ºC), demonstrating that AtCAT4 could recognise these AAs as ligands.

To gain further insight into how these AAs bind to AtCAT4, we next determined the cryo-EM structures in the apo state and in complex with L-Ornithine, which showed the largest thermal stabilisation, to final global resolutions of 3.3 Å for each structure (Fig. 1b, Supplementary Fig. 2a-b and Supplementary Table 1). The structures were determined in complex with a synthetic nanobody (sybody), which we generated to aid particle alignment during data processing (Supplementary Fig. 3). The structure of AtCAT4 adopts an outward open state, with the extracellular halves of TM1 and TM6 (named TM1b and TM6a) splayed apart from TMs 3 and 10 (Fig. 1b). The intracellular side of the binding site is tightly sealed through the packing of the intracellular halves of TM1 and TM6 (named TM1a and TM6b) against TMs 3 and 8, aided by the formation of salt bridges between TMs 1 and 5 and IL1 and TM8 (Supplementary Fig. 4a-b).

Although the apo AtCAT4 structure adopts the same outward-facing states observed in LAT1/SLC7A5 (PDB: 8KDP)22and y+LAT1/SLC7A7 (PDB: 9KJU)24, the root mean square deviation (r.m.s.d.) values indicate only moderate global similarity (4.5 Å over 280 Cα and 5.6 Å over 240 Cα, respectively). However, we chose to use these LAT structures for our comparison, as they are the most evolutionarily close reference structures available. In contrast, recent CAT-family structures of SLC7A1 from Mus musculus (hereafter referred to as MmCAT1) and GkApcT capture different conformational states (inward-facing apo and occluded)34,49,50.

Unlike the LAT1 and y+LAT1 transporters, AtCAT4 contains two additional helices, TMs 11 and 12 (Fig. 1b), which pack against TM13 and project outward from the side of the transporter. These two helices are located on the opposite side of the transporter from the single TM helices of SLC3A1 (rBAT) and SLC3A2 (CD98hc or 4F2hc), which form part of the heteromeric amino acid transporter (HAT) complexes and pack against TM429. Instead, the additional helices adopt a conformation similar to that observed in MmCAT1, suggesting that the other members of the CAT subfamily likely share this overall architecture.

Although the function of these additional helices is currently unclear, the placement of the CAT-specific TM helices (TM11-12) creates an extended hydrophobic surface compatible with protein–protein contacts and raises the possibility that CAT-family members may form higher-order assemblies. In related LeuT/APC-fold transporters that lack these extra helices (e.g., AdiC) and in SLC12 cotransporters (e.g., NKCC1 and KCC2), homodimers are formed via the terminal helical pair of the core fold (TM11–TM12), which corresponds to TM13–TM14 in eukaryotic CATs (Fig. 1b); in this architecture, the CAT-specific TMs 11–12 would flank and potentially support the TM13–TM14 dimerisation interface51,52. Given that SLC7 HATs already function as obligate heterodimers with an SLC3 heavy chain, it will be interesting to determine whether the CAT subfamily also employs oligomerisation as a regulatory mechanism.

Two additional structural differences are also observed in the apo structure of AtCAT4. The most notable being that TM1 adopts a continuous helical configuration and does not form the canonical break observed in all SLC7 and APC structures to date53 (Fig. 1b-c). The second is that extracellular loop 4 (EL4), which typically forms a short helical hairpin that packs against the transporter’s TM1 and points towards the substrate entry tunnel, has flipped out, with the loop sitting above the transporter (Supplementary Fig. 4c-d). The space vacated by the flipping away of EL4 has been occupied by a Lauryl-maltose neopentyl glycol (LMNG) detergent molecule (Supplementary Fig. 4e-f). The acyl chains of the detergent extend into two hydrophobic pockets between TMs 7 and 8, with the maltose head groups positioned near the extracellular part of TM1, where a conserved arginine, Arg55, makes a hydrogen bond to the C3 hydroxyl from the sugar headgroup and the bound sybody through it s amino terminus and CDR1 region.

The extension of TM7 to accommodate the new position of EL4 is recognised by the CDR3 loop of SybB5, which also packs against the TM5–TM6 loop of AtCAT4. The sybody further stabilises a bound cholesterol near TM6a via π-stacking with a conserved tryptophan in the scaffold region. To probe whether EL4 mobility or LMNG pushes the EL4 loop into the flipped-out state, we performed unbiased MD simulations starting from the outward-open cryo-EM structure of AtCAT4 (PDB:9HJK) and the inward-facing AlphaFold2 model, which places the EL4 loop in the canonical flipped-in position. Principal-component analysis of the pooled MD simulations reveals that the dominant component (>80% of the variance) corresponds to a flip-out-to-flip-in conformational change in EL4, supporting our hypothesis that EL4 is highly dynamic in AtCAT4 (Supplementary Fig. 5a).

Interestingly, the EL4 loop remained stable, either flipped in or flipped out, in the simulations. While we did not observe an EL4 transition event during the simulations to flipped-out-to-flipped-in (or vice versa), we noted higher backbone RMSF values for the loop region in the outward-open state (where the EL4 loop is solvent-exposed) compared to the flipped-in conformation (Supplementary Fig. 5a).

Given the nature of the sybody interaction near EL4, we considered the possibility that sybody binding may have induced the structural changes discussed above in EL4 and TM1. We therefore obtained a structure of AtCAT4 without the sybody, albeit at a lower global resolution of 4.2 Å (Supplementary Fig. 6 and Supplementary Table 1). The maps were of sufficient quality to trace the 14 TM helices but lacked sufficient information to build several loops reliably, including EL. However, the map clearly shows the presence of the symmetry-related loop region IL1, which forms the canonical hairpin with TM3. We thus conclude that whilst we cannot rule out the impact of the sybody on the position of EL4 in the higher-resolution structure, our data suggest that EL4 is dynamic and may flip away from the transporter in the outward-facing state. Further supporting this hypothesis, we note that focused 3D classification on sybody-free AtCAT4 yielded a minor class (34,329/120,868 particles, 28%) with low-resolution continuous density where we could model EL4 in flipped-in position packed against TM1b (Supplementary Fig. 5b). This minor structural class further indicates that EL4 is mobile in the WT structure in LMNG and, together with the unbiased MD results discussed above, indicates that EL4 can sample multiple conformations. Accordingly, the absence of interpretable density for EL4 in the sybody-free reconstruction is best explained by the conformational heterogeneity of EL4 rather than limited map quality, since other flexible elements and the full 14-TM architecture remain traceable at the same resolution.

We also used the sybody-free map to validate our observation regarding the helical nature of TM1. When compared internally, TM1 clearly adopts a helical structure. In contrast, the map reveals a break in the volume around Gly241 in TM6, which separates TM6a from TM6b (Fig. 1c). Taken together with the information from the higher resolution apo structure, our data further indicate that in the outward-facing state, TM1 forms a complete helix, rather than adopting a discontinuous configuration. As discussed below, this feature may play a crucial role in the amino acid recognition mechanism.

In the cryoEM map of the L-Orn-bound structure, we observed several densities consistent with lipid molecules (Supplementary Fig. 7a-b). On the extracellular leaflet, adjacent to the sybody, we observed density characteristic of sterol in a pocket formed between TM6 and TM13. This cholesterol was also observed in the apo structure. Additional cholesterol was added to the L-Orn sample, along with soy lipid extract; therefore, we have modelled this sterol as cholesterol in the cryo-EM maps. The sterol hydroxyl is located adjacent to the bulk solvent, near the sybody, and the aliphatic tail is inserted into a hydrophobic pocket formed by Leu229 and Ala233 from TM6 and Tyr546 from TM13. The steroid nucleus, in contrast, interacts with Trp57 on the sybody. A similar sterol pocket is observed in the L-Arg-bound structures of SLC7A150. However, the cholesterol molecule is modelled further down into the bilayer contacting region in AtCAT4 (Supplementary Fig. 7c). It is possible that the interaction with the sybody pulled the cholesterol up through the hydrophobic channel between TM6 and TM13. Cholesterol plays a role in the function and structure of SLC7 transporters, most notably SLC7A554,55, where it binds to specific sites, modulating their structural dynamics56 and transport activity54. The role of cholesterol in regulating the CAT subfamily, however, is underexplored. Our data indicate that this pocket is broadly conserved within the CAT subfamily and warrants further study to understand any regulatory role cholesterol might play in CAT transporter function.

Density for a second sterol was also observed at the opposite end of the transporter, interacting with a long extracellular loop between TM3 and TM4 (Supplementary Fig. 7a-b). This loop is also present in MmCAT1, where it forms an ordered alpha helix positioned above the membrane49,50. In contrast, in AtCAT4, this loop is disordered. This loop is a unique structural feature of the CAT subfamily, as the equivalent region in the HATs is much shorter, due to the presence of the heavy chain glycoprotein29. Several sterol molecules are also located in a similar region of SLC7A5, which appear to stabilise the interaction between the heavy chain and light chain of the transporter57 (Supplementary Fig. 7d). It thus appears as though sterol molecules play an important and potentially conserved role in stabilising the structures of both the HATs and the CATs in the membrane.

Structural basis for L-Ornithine recognition.
The structure of AtCAT4 bound to L-Ornithine (L-Orn) adopts an outward-open conformation that closely matches the apo structure (Supplementary Fig. 2b), with an r.m.s.d. of 1.16 Å over 512 Cα atoms. The structure provides valuable insight into the mechanisms of ligand capture in the CAT family when adopting an outward-open conformation. The cryo-EM map shows continuous, ligand-shaped density in the canonical substrate pocket. Its location and overall pose are consistent with the conserved α-amino-acid binding geometry described across SLC7 transporters in outward-facing substrate-bound states 24,53,58,59.

The most striking difference compared with the apo structure is that TM1 now adopts the discontinuous configuration observed in previous APC family transporters53. The regular alpha helix of TM1 observed in the Apo structure is broken at Ala44, which sits within a conserved di-glycine (43GAG45) motif on TM1 (Fig. 1c and Supplementary Fig. 1a). The break in TM1 results from interactions with the carboxyl group of L-Orn via the backbone amide groups. Specifically, the backbone amide groups of Ala44 and Gly45 move ~ 2.8 Å towards the extracellular space, relative to the Apo structure, forming a short π-helix that accommodates the amide group of the L-Orn ligand. L-Ornithine makes further interactions with the backbone carbonyl groups of Phe237, Ser238 and Ile240 on TM6a. However, the ε-amino group on the L-Orn side chain forms a salt bridge with the side chain of Asp116 on TM3 (heavy-atom distance 3.2 Å) and is positioned within 5.8 Å of Asp243 on TM6b (Fig. 1d and Supplementary Fig. 8a). Despite water-like densities present near Asp243 and Ser327 on TM8, at 3.3 Å global resolution, we do not attempt to assign individual water molecules.

Interestingly, the binding pose of L-Orn is different from that observed for the closely related CAT homologue, MmCAT1 (SLC7A1; PDB:9FQW, RMSD = 6.35 Å) (Supplementary Fig. 8b). In MmCAT1, the amino group on the side chain orientates towards TM1, interacting with a backbone carbonyl group on this helix and making a further hydrogen bond to a conserved serine on TM350. However, the binding pose observed in our structure is very similar to the reported pose for L-Arg bound to SLC7A1 (PDB:9FQU), wherein the guanidino group hydrogen bonds with the hydroxyl and carbonyl groups of Ser120 on TM3. Serine 120 in SLC7A1 corresponds to Asp116 in SLC7A4, which is consistent with our observations on the importance of this side chain in L-Orn recognition. The binding pose we observe for L-Orn in SLC7A4 is also consistent with the pose we reported previously for the more distantly related prokaryotic homologue, GkApcT (PDB 6F34), which was captured bound to L-Arginine. In the GkApcT L-Arg bound structure, we also observed an interaction of the side chain guanidino group with Glu115 on TM334 (Supplementary Fig. 8c). Our structural analysis, therefore, suggests that the presence of Asp116 on TM3 (Glu125 in human SLC7A4) results in a mechanism of L-Orn recognition that is more similar to GkApcT than SLC7A1. The hydrophobic gating residue, Phe237 in AtCAT4 (Tyr246 in human SLC7A4), is in an open conformation, i.e., not capping the substrate, similar to the L-arginine-bound y+LAT1 structure (PDB: 8YLP). Our structure reveals an equivalent conformation for the hydrophobic lid, a hallmark of the outward-open state in the APC fold transporter family 24,60,61.

Unfortunately, we were unable to observe CAA transport for AtCAT4 in either Xenopus oocytes or HeLa cells overexpressing the protein, in part due to low expression levels. No activity was observed following liposome reconstitution despite the protein being homogeneously purifiable, well-folded, and dose-responsive to increasing concentrations of L-Orn (Supplementary Fig. 3e-g). Therefore, to validate the L-Orn binding pose, we employed the previously used nano-DSF binding assay. To verify the observed stabilisation, we mutated the hydrophobic gating residue on TM6a, Phe237, to valine. In all currently reported APC family transporters, Phe237 occupies a strictly conserved aromatic position in TM6a known as the thin gate, and mutations of this position are known to generate transport-deficient mutants of SLC7 proteins22,30,34,62. We observed no detectable stabilisation in the nanoDSF assay with the Phe237Val mutant (Fig. 1e). Within the binding site, we also mutated Asp116 to serine, as this would remove the acidic side chain while retaining the hydrogen bonding potential observed in SLC7A1 and Ser327, which, as discussed above, was observed to interact with L-Orn in SLC7A1, to either leucine as observed in the human SLC7A4 structure, or methionine which was shown to modulate AA specificity in GkApcT34. All three mutations disrupted the stabilisation observed in the presence of L-Orn in the WT protein (Fig. 1e), supporting our conclusion that AtCAT4 specifically recognises CAAs and the BCAA L-leucine.

Amino acid-induced structural changes in TM helix 1.
The unwinding observed in TM1 following L-Orn binding prompted us to explore the possibility of an induced fit interaction between AtCAT4 and the ligand. We therefore employed molecular dynamics (MD) to study the impact of L-Orn binding on the geometry and dynamics of TM1. To ascertain the changes in TM1 geometry in the apo (PDB:9HJK) and L-Orn bound structures (PDB: 9SP8), we employed the HELANAL algorithm63, which measures the geometry of helices based solely on their Cα atoms (Fig. 2a). The benefit of this approach is that it allows us to map the deviation of the local twist of each Cα atom from an ideal α-helix (Δθ = θ - 100°; where θ is computed from a sliding 4-Cα window) along the length of TM1 over the course of the simulation and summarise the magnitude of these changes along the helix as the time-integrated deviation (∫ |Δθ| dt (º·μs)) from ideal α-helix geometry. The deviation of each Cα-atom can then be compared to the values obtained for TM1 in the apo state (Fig. 2b), offering a localised analysis of any structural changes that occur during the MD simulation.

Triplicate 1-µs MD simulations, starting from the L-Orn bound cryo-EM structure, were run, and the helicity of TM1 was analysed (Supplementary Fig. 9a-c and Table 2). Across 3×1 µs unbiased replicas, the carboxylate of L-Orn unbound TM1 in 2 out of 3 simulations (rep2-3; Supplementary Fig. 9c). In the 1 μs repeat where L-Orn remained bound to TM1 (rep1), we observed an increase in the unwinding of TM1 centred at Ala44, which is sandwiched between the di-glycine GAG45 motif in TM1 (Fig. 2c). Presumably, the di-glycine motif provides the flexibility to unwind in this region of the helix. The deviation from helical geometry in this region is consistent with the cryo-EM structure of AtCAT4 bound to L-Orn and with previous APC family transporters that show a discontinuity in TM1 at this location53. Helix TM1 unwinding at the GAG motif facilitates better accommodation of the L-Orn ligand at the binding site. Specifically, in the MD simulation, we observe a water molecule entering the binding site and coordinating the interaction between the carboxylate group of L-Orn and Gly45 from TM1, as well as Tyr274 from TM7 (Supplementary Fig. 9d). A similar water molecule was previously observed in our GkApcT crystal structure, coordinating the L-Ala ligand34.

In the second and third repeats of the simulation, we observed L-Orn unbinding from TM1. We quantified the visually observed L-Orn unbinding by tracking its engagement with TM1 (as % H-bond occupancy) and minimum L-Orn distance from TM1 (Supplementary Fig. 9c). Interestingly, the TM1 unbinding events in replicates 2 and 3 were different. In simulation two, L-Orn unbound and diffused out of the binding site, whereas in simulation three, the L-Orn carboxylate group disengaged the GAG motif, along with the α-amino group disengaging TM6, with the ligand remaining in the binding site. The common observation in both of these simulation repeats, where L-Orn disengages TM1, is that TM1 reverts to the all helical configuration (Fig. 2d) of the apo state (Fig. 2b). Therefore, the helical break induced by L-Orn binding in TM1 appears reversible upon ligand-TM1 disengagement.

To investigate the coordination and stable binding of L-Orn in repeat 1, we clustered the sampled binding site configurations (defined as residues within 10 Å of L-Orn) from the 1 μs unbiased MD simulation and further seeded five independent 200 ns unbiased simulations (see Methods and Supplementary Table 2). These seeded simulations yielded stable L-Orn binding in 5/5 runs, allowing us to collect atomistic interaction fingerprint statistics (Supplementary Fig. 9d-e). Compared to the cryo-EM model, Ala44 is shifted by an additional ~1.7 Å over the span of the MD repeats, further drawing the ligand backbone carboxyl into the fully accessible GAG backbone pocket. Taken together, our results indicate that AtCAT4 undergoes an induced fit mechanism to recognise L-Orn, with TM1 undergoing an ordered-to-disordered transition to accommodate the carboxylate of the ligand. The ε-amino L-Orn side chain was stabilised through favourable interactions with polar binding site residues, including Asp116.

Across the five seeded simulation repeats, we consistently observe a water molecule occupying the gap between the L-Orn ε-amino group and Asp116, present for ~98% of the gross simulation time (Supplementary Fig. 9d-e). The presence of water in this position within the binding site is mechanistically reasonable, especially given that the interacting AtCAT4 side chain is an aspartate, which is shorter than glutamate, and the ligand is ornithine, which is shorter than either lysine or arginine. Thus, a water molecule can stabilise the bound L-Orn molecule, as observed with the shorter aspartate side chain in AtCAT4. Collectively, the MD data suggest a coordinated water network is likely to exist within the AtCAT4 binding site. However, due to the resolution of the cryo-EM dataset we obtained, we could not reliably model the water molecules into the structure. However, our observations are consistent with previous SLC7/HAT transporter structures, which are reported to function via an induced-fit mechanism30,62. It is therefore reasonable to conjecture that ligand-induced structural changes may constitute an essential part of ligand selection within the wider SLC7 family.

Human SLC7A4 is a pH-regulated leucine transporter.
Given that NanoDSF could be used to verify that AtCAT4 binds cationic amino acids, we used the same methodology to analyse the substrate specificity for the human homologue (Uniprot: O43246). Of the 20 canonical amino acids tested, we observed the greatest stabilisation in the presence of L-Leu (~6 °C), suggesting that SLC7A4 in humans may transport the BCAA leucine (Fig. 3a). We sought to verify this using cell-based transport studies. Many commonly used cell types exhibit high background uptake of L-Leu due to upregulation of SLC7A5 (LAT1). To reduce background transport, we used an SLC7A5 knock-out HCT-116 cell line to study the transport characteristics of SLC7A464. Having established that SLC7A4 is expressed at the plasma membrane (Supplementary Fig. 10a), we observed uptake of 14C L-Leu in cells transfected with SLC7A4 at pH 7.5 compared to cells transfected with empty plasmid (Fig. 3b). We initially focused on SLC7A4 as a potential pH regulated amino acid transporter due to the conservation of Glu125 on TM3 with GkApcT (Supplementary Fig. 1a-b). We therefore tested the effect of lowering external pH on leucine uptake in cells and in reconstituted proteoliposomes. Consistent with our hypothesis, we observed a substantial increase in L-Leu uptake at pH 6.5 and 5.5 compared to pH 7.5 in HCT-116 cells, indicating that SLC7A4 is activated at acidic pH (Fig. 3c). We also observed uptake of L-Leu into proteoliposomes under an acetate-induced pH gradient (Supplementary Fig. 10c-d).

After confirming that SLC7A4 facilitates L-leu uptake across a physiological pH range and that transport efficiency increases under acidic conditions, we proceeded to define the transporter's broader substrate profile. As nanoDSF indicated the ability to recognise L-Arg (Fig. 3a), we subsequently screened whether the 20 canonical amino acids could compete for 14C Leucine cell-based uptake (Fig. 3d). We observed that several non-polar amino acids could compete with leucine transport, suggesting that SLC7A4 may function as a pH-sensitive general non-polar amino acid transporter. However, when we tested the uptake of H3 L-Isoleucine (L-Ile), which is chemically very similar to leucine, or H3 L-Arg, which inhibited leucine uptake by 50%, we did not observe transport above a transport-deficient mutant (Tyr246Val) (Fig. 3e). Finally, we determined the IC50 for L-Leu as 24 ± 5 μM. The much lower IC50 value for L-Leu compared with the IC50 of 680 ± 19 μM for L-Arg (Fig. 3f) demonstrates a clear preference for L-Leu binding to SLC7A4, consistent with our transport data.

The structural basis for leucine selectivity in SLC7A4.
Compared to the HAT subfamily, much less is know concerning the molecular basis of amino acid selectivity within the CAT subfamily9. We therefore examined the structural basis for AA selectivity within SLC7A4. Despite collecting a large cryo-EM dataset of SLC7A4 in complex with L-Leu (ca. 30,000 movies), we were unable to solve the structure of the human transporter in complex with its ligand. We therefore used the cryo-EM structure of L-Orn-bound AtCAT4 to generate a homology model of the human transporter. L-Orn was mutated in silico to L-Leu, and the binding site was energy-minimised using the AMBER force field (see methods). The system was then equilibrated for 1 μs of unrestrained MD. We then monitored the stability of the complex using all-atom MD from triplicate 200 ns simulations seeded from the 1 μs MD (Fig. 4a-c, Supplementary Fig. 11a and Table 2). The MD data show that the carboxylate and amino group of L-Leu interact similarly with those observed with L-Orn, discussed above for AtCAT4, and the ligand pose was stable over three repeats of 200 ns of simulation (Supplementary Fig. 11b-c). Specifically, the carboxylate interacts with the backbone amides in Gly52, Ser53 and Gly54, which constitute the di-glycine motif in TM1 in the human transporter (Fig. 4a-c). The amino group of L-Leu interacts with the backbone carbonyl groups of Met50, Tyr246 and Val249. The L-Leu side chain is accommodated in a hydrophobic pocket formed predominantly by Val249, Val332, Leu336, and Tyr246, the latter of which forms the thin extracellular gate.

As a CAT-subfamily member, we reasoned that SLC7A4 might retain a latent evolutionary propensity for cationic amino-acid recognition, in line with the nanoDSF binding and competition assays (Fig. 3a,d). To investigate whether it was possible to switch SLC7A4 from binding L-Leu to L-Arg, we compared SLC7A4 to the binding site of MmCAT1 (PDB:9FQW), a specialised CAA transporter50. Within the binding site of SLC7A4, we identified three side chains - Val332Ser, Leu336Ser, and Leu394Met - that are unique to SLC7A1 but differ in SLC7A4/CAT4 (Supplementary Fig. 1a). Encouragingly, Val332 and Leu336 were also observed in our MD analysis of the homology model, while Leu394 on TM10 is within ~ 5 Å of the bound L-Leu.

To experimentally test our hypothesis that these side chains influence amino acid selectivity in SLC7A4, we created a triple mutant (Val332Ser, Leu336Ser, and Leu394Met), hereafter referred to as Tri-M. In our cell-based uptake assays using the HCT-116 SLC7A5 KO cell line, we observed robust uptake of 14C-Leu in the Tri-M comparable to the WT protein (Fig. 4d). After confirming that the Tri-M protein could recognise L-Leu, we then tested L-Arg recognition. Previously, we used a competition assay to determine the IC50 for L-Leu and L-Arg in the WT protein (Fig. 3e). The IC50 for L-Leu in the Tri-M increased slightly (65 μM ± 8.5 vs. 23.7 ± 5.3 μM for the WT), likely due to mutation of the hydrophobic pocket (Fig. 4e). However, there was a dramatic increase in affinity for L-Arg, with the IC50 decreasing from 680.2 ± 19.0 μM in the WT to 48.6 ± 2.3 μM in the Tri-M. The hydrophobic pocket, V332/L336/L394, is tuned for a branched side chain of leucine, providing a simple explanation for why closely related BCAAs can compete for access yet fail to show measurable uptake (e.g., isoleucine does not show detectable transport, (Fig. 3d-e), consistent with a balanced requirement for side-chain fit that couples binding to the conformational activation step.

Our data thus demonstrate that, as with the bacterial GkApcT transporter, amino acid selectivity in SLC7A4 can be modulated by tuning recognition of the ligand side chain. Our data, therefore, place SLC7A4 within the CAT subfamily in terms of structural homology with AtCAT4 but demonstrate that SLC7A4 diverged from the specialised human CAA transporters, CAT1, CAT2 and CAT3, to select for L-Leu. Strikingly, swapping just three residues (V332S/L336S/L394M) was sufficient to re-establish a preference for L-Arg recognition (Fig. 4d-e), demonstrating that amino acid specificity within the CAT subfamily is determined through only a small set of sidechains in the binding site.

Taken together, our data also explain why the Arabidopsis CAT4 and human SLC7A4 homologues have diverged towards preferential recognition of L-ornithine versus L-leucine, and why this divergence is physiologically coherent. In AtCAT4, the binding pocket remains highly polar and is organised around the conserved TM3 acidic residue (Asp116) and the surrounding hydrogen-bonding network. This network stabilises protonated, flexible side chains such as L-ornithine (and related CAAs), while still tolerating L-Leu binding as indicated by our nanoDSF screen. Prior work further reports that AtCAT4 localises predominantly to the tonoplast and is broadly expressed65. In this context, an Orn/CAA-biased pocket is most consistent with a role in vacuolar amino-acid buffering and nitrogen remobilisation66,67. It would help control cationic amino-acid pools that feed plant nitrogen metabolism and polyamine/arginine-ornithine metabolism during growth and reproductive transitions.

In contrast, HsSLC7A4 has remodelled the side-chain environment around the canonical TM1-TM6 motif into a predominantly hydrophobic pocket, centred on Val332, Leu336 and Leu394. This pocket tightly accommodates the branched side chain of L-Leu but disfavours the more extended and charged side chains of cationic amino acids. This structural feature is reflected functionally by ~30-fold lower IC50 values for L-Leu compared with L-Arg and by the absence of detectable L-Arg transport, despite measurable L-Arg binding. The Tri-M mutant, in which we introduce three CAT1-like residues into this pocket, re-establishes high-affinity L-Arg recognition and transport while modestly weakening L-Leu affinity. This result demonstrates that a small set of side chains can switch the SLC7A4/CAT4 scaffold between an Orn/CAA-biased state suited to plant vacuolar homeostasis and a Leu-biased state suited to mammalian leucine handling at specialised interfaces.

Glu125 functions as a pH sensor
To date, the pH dependence of amino acid transport via the SLC7 family remains unclear. However, proton-coupled homologues have been identified in the SLC36 family32 and in prokaryotic APC superfamily homologues34,68. Previously, we identified Glu115 in TM3 as important for proton coupling in GkApcT, with protonation favouring the occluded state and deprotonation driving the transition to the inward-open state34,36. SLC7A4 also has a glutamate, Glu125, at the same position, whereas SLC7 A1-3 in humans, which are not pH-regulated9, contain serines at the equivalent site (Supplementary Fig. 1a), while retaining Asp252 in TM6. Mutating Asp252 to Ala resulted in a transport-deficient mutant, similar to GkApcT34, suggesting that this residue is integral in the transport mechanism (Fig. 5a). We therefore aimed to understand the role of Glu125 in the transport mechanism of SLC7A4. We first mutated Glu125 to serine to mimic CAT1/2/3 members. In line with our hypothesis, the replacement of Glu125 with serine abolished the pH-induced activation at acidic pH. However, mutation of Glu125 to aspartate, which still can accept protons, remains pH-sensitive, showing increased activity at acidic pH. We also tested glutamine as it resembles a protonated glutamate, and since glutamine side chains can nucleate transient water wires, stabilising hydrogen-bonded networks that traverse hydrophobic pores69. Replacement of Glu125 with glutamine also abolished the observed pH response, suggesting that the acidic side chain of Glu125 serves as a titratable site. Overall, our data support a mechanism in which Glu125 is protonated under acidic conditions, thereby enhancing leucine transport in SLC7A4. Interestingly, all mutations involving a shorter side chain than glutamate result in higher transport, even after taking expression levels into account (Supplementary Fig. 10b). An explanation for this observation is discussed below in the context of the structural comparison between the cryo-EM structure AtCAT4 and our homology model of SLC7A4.

We next turned to our L-Leu-bound MD model of SLC7A4 (Fig. 4a) to rationalise these results. Interestingly, the stable pose adopted by Glu125 in the MD-refined model differs from that observed for the equivalent side chain, Asp116, in the L-Orn bound Cryo-EM structure of AtCAT4 (Fig. 5b). In SLC7A4, TM3 has rotated ~ 45º to bring Glu125 into proximity with TM10, where the side chain interacts with the discontinuous region, we observed in the outward-open AtCAT4 structure. A similar discontinuous region in TM10 is observed in recent outward-facing structures, such as SLC7A5 (LAT1)22, SLC7A8 (LAT2)24, SLC7A7 (y+LAT1; PDB: 9LDR)25, the g-aminobutyric acid transporter (GAT1; PDB: 8GNK), and the bacterial arginine-agmatine antiporter, AdiC, where it was shown to play a role in ligand selection and transport24,70,71. In SLC7A4, the carboxylate group of Glu125 interacts with the backbone amide groups of Ser395, Leu396, Gly397, and Thr398, as well as the hydroxyl group of Thr398. In this position, the central ligand binding site is still open to the extracellular side of the membrane, although it is less open than our AtCAT4 structure due to the movement of Tyr246 on TM6a over the ligand. Nevertheless, this conformation provides important clues to the function of Glu125. Supporting the protonation mechanism, PROPKA372 calculates the pKa of Glu125 as slightly elevated (5.0).

Most notable is that Glu125 forms part of a solvent accessible tunnel that connects the amino acid binding site to the exterior of the cell (Fig. 5c). In this position, Glu125 could function as a responsive conformational sensor. Under neutral conditions, Glu125 would be deprotonated, stabilising the interaction between TPM3 and the discontinuous region in TM10. However, under external acidic conditions, Glu125 would take up a proton, disrupting the interaction observed with the discontinuous region in TM10. It is plausible to consider that under these conditions, and in the presence of bound L-Leu, TM3 could then rotate to the position observed in the AtCAT4 cryo-EM structure and trigger the conformational changes that close the extracellular gate and transition the transporter into the inward open conformation observed for MmCAT1 (PDB: 9FQT)50 via an intermediate occluded state.

A key structural change within the SLC7 family is the movement of TM10 towards TMs 1a and 6b to close the extracellular side of the transporter during the transport mechanism22,24,73. Indeed, if we compare our model of SLC7A4 in the outward open state with SLC7A1, in the inward open state (PDB:9FQT), we observe that TM10 rotates towards TMs 1 and 6 by ~15º and moves inwards by ~ 5 Å (Fig. 5d). This is accompanied by a similar movement in TMs 13 and 14. At the opposite end of the binding pocket, TM1a rotates by ~25º and TM6b by ~23º, opening the central binding site to the cytoplasm by ~5-7 Å. In the inward open conformation in SLC7A1, TM10 adopts a straight conformation, with no unwound region. Our data thus provide further support for a mechanism, observed originally in SLC7A11 by us and subsequently in SLC7A5, where the transmembrane helices within the SLC7 family can undergo drastic structural transitions following ligand binding and transport22,30,58. Our data support a general role for TM1 and TM10 in ligand-induced conformational changes within the binding of SLC7A4, which may have important implications for developing targeted inhibitors for these transporters22. Our model also explains why substituting Glu125 with shorter side chains would increase transport (Fig. 5a); essentially, the shorter side chains are unable to stabilise the conformation of TM10 (Fig. 5b), potentially enabling SLC7A4 to undergo faster transport cycles. Supporting this hypothesis, we note that Glu125Gln, which is similar in length to glutamate, displayed transport activity comparable to WT but lacked pH dependence. A similar mechanism was proposed to explain why certain drugs are transported faster by SLC7A5 (LAT1); smaller drugs create a weaker steric hindrance to the movement of TM1022.

Methods
Cloning, expression, and purification of Arabidopsis thaliana SLC7A4
The gene encoding Arabidopsis thaliana CAT4 (Uniprot code Q8W4K3) was codon optimised, synthesised (Geneart) and cloned into pDDGFP-Leu2D79 (AddGene ID: 58352), carrying a C-terminal TEV protease cleavage sequence (ENLYFQG/S), yeast-enhanced green fluorescent protein (yeGFP) and a His tag for purification. Variant forms of AtCAT4 were created by site-directed mutagenesis using the overlap extension PCR method. S. cerevisiae BJ5460 cells (MATa ura3-52 trp1 lys2-801 leu2Δ1 his3Δ200 pep4::HIS3 prb1Δ1.6 can1 GAL) were transformed with sequence-verified AtCAT4-pDDGFP2-Leu2D plasmid using the lithium acetate method and plated onto auxotrophic media (Uracil and Leucine drop-out to increase plasmid copy number) sequentially until 70-80% saturation of plate surface with transformants. The yeast were seeded in 2×100 ml overnight cultures in synthetic-complete Leucine drop-out media (SC-LEU; 1.92 g/l; prepared in-house with -α-amino acids) supplemented with 2% glucose and yeast nitrogen base (YNB; 6.9 g/l) for 20-22 h or until OD600nm =3.0, after which cultures were upscaled to 2×700 ml in the same media, grown for another 24 h to an OD600nm of 5.0. Yeast was grown at 30 °C at 240 rpm in flasks. 1.2 L of overnight culture was inoculated into 9.6 L SC-LEU+YNB media with 2% lactate (aliquoted over 12 baffled Erlenmeyer flasks). The cultures were grown in lactate media for 17 h until OD600nm 2.0-2.5 and were induced with galactose (1.5% final) to express the protein. Cultures were harvested 18-20 h after induction, at an OD600nm routinely ranging between 4.0 and 4.5, depending on the preparation. The expression level was quantified by whole-cell GFP fluorescence (λexcitation = 488 nm, λemission = 512 nm) from 8 mL of culture resuspended in 150 μL of PBS, measured using a SpectraMax M3 Microplate Reader (Molecular Devices). Cells were harvested at 5,000×g for 25 min, and the pellet was resuspended in PBS pH 7.4 (5 ml·g-1 total volume) and stored at -80 °C until further use.

To isolate the membrane fraction, cells were lysed using a TS Series Continuous Cell Disruptor (Constant Systems) operated at 38 kpsi, with a NESLAB ThermoFlex 1400 Chiller (Thermo Fisher Scientific) maintaining a temperature of 4 °C. The lysate was clarified by centrifugation at 30,000×g for 30 min, and the supernatant was then ultracentrifuged at 235,872 g for 1.5 h to pellet the membranes. The pellet was washed in a high-salt buffer consisting of 20 mM HEPES·NaOH, pH 7.5, and 1.0 M potassium acetate, and Dounce-homogenised. The suspension was ultracentrifuged at 235,872 × g for 1 h, and the washed membrane pellet was resuspended in PBS (5 ml/g total volume).

AtCAT4 membrane fractions were solubilised in 1% (w/v) detergent (LMNG; Anatrace), buffered with PBS pH 7.4, and supplemented with an additional 150 mM NaCl and 10% (v/v) glycerol for 1.5 h. The insoluble material was separated by ultracentrifugation at 235,872 x g for one hour. The solubilised fraction was supplemented with 20 mM imidazole. It was then incubated with HisPur Ni-NTA resin (Thermo Fisher Scientific) until the GFP-tagged protein bound to the resin plateaued, as monitored by GFP fluorescence, for up to 3.5 h. Purification proceeded via standard IMAC steps. Specifically, the resin was washed in a gravity column with PBS supplemented with 150 mM NaCl, 0.01% (w/v) LMNG, 10% (v/v) glycerol (buffer A) with 20 mM imidazole, for 20 column volumes (CVs), followed by a second wash step with 25 mM imidazole (10 CVs). Membrane protein was then eluted with buffer A supplemented with 250 mM imidazole in 4 CVs. The concentration of the eluted GFP fusion protein was estimated as described in 80. An equimolar amount of Tobacco Etch Virus (TEV) protease was added to the eluant and dialysed overnight at 4 °C against 4.0 L of buffer B (20 mM Tris·HCl, pH 7.5, 150 mM NaCl, and 0.003% LMNG) using a 3.5 kDa MWCO regenerated cellulose membrane (Spectra-Por tubing). The next morning, the dialysate was syringe-filtered through a 0.22 μm filter supplemented with 10 mM imidazole and passed through a 5 ml HisTrap column (Cytiva; pre-equilibrated in gel-filtration buffer) to remove the His-tagged TEV protease, liberating GFP-His8 with Ni-affinity. The flow-through was collected and spin-concentrated in a 100,000 MWCO concentrator (Vivaspin 20, Sartorius) to 0.4 mL and injected onto a Superdex 200 Increase 10/300 GL SEC column (Cytiva; pre-equilibrated with buffer B) and run at a flow rate of 0.4 mL/min. Fractions containing protein were analysed with SDS-PAGE for their purity, pooled accordingly and concentrated in a 50,000 MWCO concentrator (Vivaspin 2, Sartorius or Amicon® Ultra) to a concentration of 32.4 mg·ml-1. Protein concentration was determined with a NanoDrop ND-1000 spectrophotometer using extinction coefficients calculated with the Expasy ProtParam server for the purified protein (disulphides considered as reduced). C-terminally Avi-tagged (N-GLNDIFEAQKIEWHE-C) protein was purified as above to select binders against in the sybody pipeline. AtCAT4 biotin modification was carried out using the BirA ligase according to the manufacturer’s instructions (Avidity). All purification and protein handling steps were performed at 4 °C.

Cloning, expression, and purification of Human SLC7A4
The gene encoding HsSLC7A4-FLAG-stop (UniProt ID O43246) was synthesised (GeneArt) and cloned into pLexM with a C-terminal FLAG tag (AddGene ID: 167988). Variant forms of human SLC7A4 were created by site-directed mutagenesis of the gene in the pFAW vector using overlap PCR and then cloned into pLexM with a C-terminal FLAG tag. The plasmid DNA was syringe-filtered (0.22 μm) and stored at –20 °C, prior to transfection. Human embryonic kidney–293F (HEK293F) cells in FreeStyleTM 293 Expression Medium (Thermo Fisher Scientific) were used for transient transfection and expression. The cells were cultured in suspension phase at 37 °C and 8% CO2. Cells were split to 0.7 × 106 viable cells/ml 24 hours before transfection. 24 h later, the cells reached a density of 1.3-1.5×106 cells/ml, at which point they were transiently transfected. 1.0 L of cells was transfected with 1.1 mg plasmid DNA (diluted in serum-free DMEM; Thermo Fisher Scientific) complexed with linear polyethyleneimine (PEI) MAX (MW 40,000; Polysciences Inc., USA) at a 1:2 (w/w) ratio. Immediately after transfection, syringe-filtered (0.22 μm) sodium butyrate was added to a final concentration of 8.0 mM. Cells were returned to the incubator and harvested 40 hours after transfection. They were then washed in PBS (pH 7.4), pelleted, and stored at −80°C until use. Routinely, the cell biomass yield was 8 g/l culture.

The cell pellet was thawed and resuspended in cold PBS (3.125 ml·g-1 total volume) containing deoxyribonuclease and two tablets of protease inhibitors per l worth of cells (SIGMAFASTTM; each containing: 2 mM AEBSF, 0.3 μM Aprotinin, 130 μM Bestatin, 1.0 mM EDTA, 14 μM E-64, 1.0 μM Leupeptin). Cells were subsequently lysed on ice using sonication (Qsonica, USA), with an amplitude of 30% and a total sonication time of 2 min/l, consisting of 20 pulse cycles (2 s ON, followed by 4 s OFF). Unbroken cells and cell debris were pelleted at 12,000×g for 10 min at 4 °C, and the supernatant was ultracentrifuged at 235,872×g for 1 hour, washed with 15 mM HEPES·NaOH, pH 7.5 and 20 mM KCl and Dounce homogenised. The resuspended membranes were ultracentrifuged at 235,872×g for 1 hour, and the washed membranes were resuspended in PBS (10 ml·g-1 final volume) and snap-frozen for storage at −80 °C until purification. On the purification day, the membranes were solubilised in ice-cold PBS pH 7.4 supplemented with 150 mM NaCl, 10% (v/v) glycerol, and 1% (w/v) DDM – 0.2% (w/v) CHS for 1.5 h. The insoluble fraction was pelleted by ultracentrifugation at 235,872 x g for one hour. The supernatant was incubated in batch with 0.1 mL/L Pierce Anti-DYKDDDDK affinity resin (Thermo Fisher Scientific) for 2 hours and subjected to gravity flow. The flowthrough was collected and incubated with 0.07 ml/l culture Anti-DYKDDDDK resin for another 1.0-1.5 h to collect all protein. The detergent was exchanged to GDN during gravity chromatography. Specifically, the two resin pools were separately washed with 30 CV of buffer A (PBS, pH 7.4, 150 mM NaCl, 10% glycerol, 0.1% (w/v) GDN) supplemented with 10 mM ATP/20 mM MgCl2 followed by a 10 CV wash step in buffer A without ATP/MgCl2. The protein was eluted from each resin pool after 0.5-1.0 h incubation with 2.3 and 1.3 CV 0.5 mg/ml 3´FLAG peptide (MDYKDHDGDYKDHDIDYKDDDDK) in buffer A. The two elution steps from each resin pool were combined, concentrated with a 50,000 MWCO concentrator (Vivaspin 20, Sartorius) to 0.4-0.5 ml and injected on a Superdex 200 Increase 10/300 GL SEC column (Cytiva; pre-equilibrated with 20 mM Tris pH 7.5, 150 mM NaCl, 0.01% (w/v) GDN). SLC7A4 fractions were collected without further concentration to avoid concentrating the detergent. Pooled gel filtration fractions were routinely 0.5-1.0 mg/ml (varied across preparations) and suitable for downstream applications.

Thermal stability measurements
Differential scanning fluorimetry (DSF) measurements were performed with a NanoTemper Prometheus NT.48. Wildtype human SLC7A4 (purified in Glyco-diosgenin (GDN)), AtCAT4 (purified in LMNG) and mutants were investigated on their thermal stability in the presence and absence of 1 mM α-amino acids (from 10 mM stocks in water, filtered and stored at 4 °C). Protein was added at final concentrations of 0.5 mg·ml-1 (human construct) and 1.0 mg·ml-1 (Arabidopsis thaliana construct) and the pH was buffered (a) pH 7.5 with 20 mM Tris·HCl, or (b) pH 5.5 with 20 mM citrate. Other buffer components were 150 mM NaCl and 3× CMC of the selected detergent. AtCAT4, samples were supplemented with lipid (soybean polar extract: cholesterol, 9:1 w/w; Avanti Polar Lipids) prior to measurement to observe ligand-induced stabilisation. The lipid stock (20 mg·ml-1 in 20 mM Tris·HCl) was first disrupted with 15 mM sodium cholate until translucent to emulsify lipid vesicles and then incubated with the protein sample at a 1:1.2 (w/w) protein: lipid ratio for 15-30 min at room temperature before DSF measurements. 12 μl of each sample was loaded onto standard sensitivity capillaries (NanoTemper) and transferred to Prometheus NT.48 (NanoTemper). NanoDSF experiments were run at 30% (Arabidopsis thaliana construct) and 50% (human construct) intensity using 1°C min−1 increments in a range from 20 to 95 °C. The resulting melting curves were generated by plotting the first derivative of the fluorescence ratio at 330 nm/350 nm against temperature. The melting temperature (Tm) of the protein in the presence of the ligand was subtracted from that of the protein in the absence of the ligand to calculate the ΔTm of the protein induced by ligand binding.

Synthetic nanobody (Sybody) selection and purification
Sybody selection was performed against C-terminally Avi-tagged and biotinylated AtCAT4. The protocols for sybody selection have previously been described in detail 81. Five specific anti-AtCAT4 binders were identified from the loop sybody library. The binders were assessed by means of Ni-affinity pulldowns using His6-tagged binders (expressed from the pSb_init vector), followed by SDS-PAGE densitometry and ranked using biolayer interferometry. Biolayer interferometry was performed on an Octet Red 384 (Sartorius) to calculate KD. A high-affinity sybody (57.3 ± 10.5 nM), SybB5, was identified as the higher-affinity sybody, which formed a stable complex with the transporter and co-eluted from a Sepax SRT-C SEC-300 column (Chromex). The identified SybB5 was expressed as C-terminal Myc-His6-tagged binders using periplasmic extraction. Specifically, binder-transformed E. coli (MC1061; Lucigen) were grown in Terrific Broth with 100 μg·ml-1 chloramphenicol until an optical density at 600 nm (OD600) of 0.5 was reached, at which point the temperature was reduced to 22 °C and cultivation continued for an additional 120 min. Binder expression was induced with 0.02% -(+)-arabinose and left overnight at 22 °C and 180 rpm. Cells were harvested and immediately incubated in 50 ml/l culture of periplasmic extraction buffer (20% w/v sucrose, 50 mM Tris·HCl, pH 8.0, 0.5 mM EDTA and 0.5 μg/ml lysozyme, prepared fresh and used immediately) at 4 °C for 30 min with magnetic stirring. The suspension was diluted with 200 ml/L of 20 mM Tris·HCl (pH 7.5) containing 1 mM MgCl2 incubated on ice for an additional 30 min, and then clarified by centrifugation at 4,000×g for 30 min at 4 °C to obtain the periplasmic extract from the cell pellet. The periplasmic extract was supplemented with 15 mM imidazole and an additional 150 mM NaCl and incubated with HisPur Ni-NTA resin (Thermo Fisher Scientific) for one hour. The resin was washed with 20 CVs of 30 mM imidazole, 20 mM Tris·HCl, pH 7.5, 300 mM NaCl, before eluting the Myc-His6-tagged binder with 300 mM imidazole. The eluant was dialysed overnight against 4 L of 20 mM Tris·HCl, pH 7.5, 150 mM NaCl in a 3.5 kDa MWCO regenerated cellulose membrane (Spectra-Por tubing). Next morning, the dialysate was syringe-filtered (0.22 μm) to remove any visible precipitated Sybody and the filtrate was spin-concentrated to 1.0 ml with 5,000 MWCO concentrators (VivaSpin 20).

Cryo‐EM sample preparation and data acquisition
AtCAT4-(63.638 kDa) — SybB5 (15723 kDa) complexes were formed on the day of grid preparation by incubation of 0.3 mg·ml-1 purified AtCAT4 purified in LMNG (from a 32.4 mg·ml-1 stock) with 1:2 molar excess of the Myc-His6-tagged SybB5 for 60 min on ice in a 400 μl reaction volume buffered with 20 mM Tris·HCl pH 7.5, 150 mM NaCl and supplemented with 0.003% LMNG. The formed 1:1 complex was separated from excess sybody by gel filtration, injecting the reaction into a Sepax SRT-3C SEC300 (Cytiva) column at 0.4 ml·min-1. The pooled fractions were analysed by SDS-PAGE for complex formation before concentrating the sample in a 50 MWCO centrifugal concentrator (Amicon® Ultra) at 4,000×g and 4 °C until the desired complex concentration was achieved, as assessed spectrophotometrically using a NanoDrop ND-1000 spectrophotometer. The extinction coefficient was estimated using the AtCAT4 sequence (cleaved at the TEV site) and the corresponding Myc-His6-tagged sybody with the ExPASy ProtParam server. The final complex concentration was determined to be 3.4 mg·ml-1, and 3.5 μl of the sample was pipetted onto the grid for a blot time of 3.0 s. For the apo AtCAT4 without SybB5, the LMNG-purified protein was plunge-frozen at 4.7 mg·ml-1. For the SybB5+L-Orn-bound dataset, the preparation was similar, with minor modifications. Specifically, the AtCAT4 — SybB5 complex was relipidated 1:1 w/w AtCAT4:lipid with soy PC: cholesterol mix (9:1 w/w, from 20 mg·ml-1 stock in SEC buffer), followed by supplementation with 10 mM L-Orn (from 100 mM stock in water) before grid freezing 2.5 μl sample with blot time 1.5 s. The final complex concentration was determined at 5.0 mg·ml-1.

The grid preparation was performed at 100% humidity and room temperature. A Vitrobot Mark IV (Thermo Fisher Scientific) was used to prepare the grid samples. 2.5-3.5 μl (see above for specific sample conditions) of sample was dispensed onto glow-discharged holey carbon-coated grids (Quantifoil 300 mesh, Cu R1.2/1.3, Agar Scientific). Grids were blotted for 1.5-3.0 s (Vitrobot parameters: blot force of -5, 100% humidity, 4 °C) and then plunge-frozen into liquid ethane. Grid samples were screened, without dataset collection, on a Talos Arctica 200 kV Cryo-TEM (Thermo Fisher Scientific) equipped with a Falcon 3R Direct Electron Detector (Thermo Fisher Scientific). For data collection, micrographs were collected in counted super-resolution mode on a Titan Krios G3 (FEI) operating at 300 kV with a Bio Quantum imaging filter (Gatan) and K3 direct detection camera (Gatan) at 105,000× magnification, physical pixel size of 0.832 Å spanning a defocus range –2.0 to –1.0 μm, and beam -image shift acquisition. For the apo+SybB5 dataset, the total dose rate was 19.3 e-/Å2, exposure time 3.00 s, corresponding to a total dose of 58 e-/Å2 spread over 40 frames. The collection yielded a total of 17,271 movies, including 11,166,793 particles extracted at 256×256 pixel boxes. For the L-Orn+SybB5 dataset, the total dose rate was 25.0 e-/Å2, exposure time 2.00 s, corresponding to a total dose of 50 e-/Å2 spread over 50 frames, yielding a total of 13,942 movies, including 17,133,106 particles extracted at 288×288 pixel boxes. For the apo-SybB5 dataset, the total dose rate was 15.3 e-/Å2, exposure time 2.60 s, corresponding to a total dose 39.9 e-/Å2 spread over 50 frames, yielding a total of 30,511 movies including 8,226,459 particles extracted at 300×300 pixel boxes.

Cryo-EM data processing
Apo+SybB5 dataset: The dataset of 17,271 movies was processed on-the-fly in SIMPLE 3.082 for patched (15×10) motion correction, dose weighting, a patched contrast transfer function (CTF) estimate, and particle picking. 11,166,793 particles were picked in real time with SIMPLE from collected micrographs. All subsequent processing was performed in either cryoSPARC83 or RELION 3.184 interconverting between the two formats using the csparc2star.py script within UCSF pyem v0.5 (10.5281/zenodo.3576629). Two rounds of reference-free 2D classification were performed. In the 1st round (350 classes), all proteinaceous densities were selected (7,053,972 particles, 63.2% remaining). These were passed to a 2nd round with stricter selection criteria, i.e., AtCAT4-SybB5 imitating densities displaying characteristic Syb protrusions and helical densities (2,459,086 particles, 22.0% of total particles remaining). Most classes showed a top/bottom view of the complex (~70%), whereas the remaining were side views. The 2D class averages (2D-CAVG) calculated in cryoSPARC revealed discernible structural elements, the most pronounced being the protruding density of the putative Syb binder and α-helical-like signals in some 2D-CAVGs. Multi-class (N=6) ab-initio models were generated with particles from the 2nd 2D-CAVG round, one of which gave an apparent Syb-bound transporter-like architecture with discontinuous helical densities (509,029 particles, 4.6% remaining). The class particles were submitted to a further “high-resolution” ab-initio round to regenerate the model. Further in silico purification of the dataset disposed of compositional heterogeneity using decoy “junk” maps. Specifically, the classes corresponding to “junk” particles in the dataset (N=5, from the 1st ab-initio) were used as a reference along with the protein-target maps (from the 2nd ab-initio) to guide separation in distinct classes by cryoSPARC heterogeneous refinement (K=5), low-pass-filtered to 10 Å. This provided a clear AtCAT4—SybB5 class, without broken densities and with 14 intact TM helices. Subsequently, 2D-CAVG (927,049 particles, 8.3% remaining) were CTF-refined, followed by non-uniform refinement and, finally, masked-local refinement, yielding a reconstruction at a global FSC resolution of 3.8 Å. The particles were Bayesian-polished and classified in 2D to generate a subset of 642,385 cleaned and polished particles, followed by homogeneous refinement, non-uniform refinement, and, finally, masked-local refinement, yielding a final reconstruction at 3.27 Å (GS-FSC 0.143), with the local resolution varying between 2.8 and 4.4 Å. Both Bayesian polishing (per-particle, reference-based beam-induced motion correction) and CTF refinement (per-particle defocus, magnification, and higher-order aberration estimation) improved the resolution of the AtCAT4—SybB5 map. The final reconstruction showed a “tight” LMNG micelle encapsulating the AtCAT4—SybB5 complex, likely rigidifying it into the presented conformation. Resolution estimates were derived from gold-standard Fourier shell correlations (FSCs) using the 0.143 criterion as calculated within cryoSPARC. Local resolution estimations were calculated within cryoSPARC.

L-Orn+SybB5 dataset: 13,942 movies were processed entirely in cryoSPARC v4.4 using patch motion correction and patch CTF estimation, followed by template-based picking with circular templates (d = 140 Å; reference = apo+SybB5 AtCAT4 map), yielding 5,444,589 particle images. To enrich for AtCAT4–SybB5 views, we performed three rounds of heterogeneous refinement (C1) using a transporter reference map imported from the apo+SybB5 dataset together with “junk” decoy maps to steer separation; this retained a clean class of 693,677 particles (12.7%), which non-uniformly refined to 3.19 Å. However, -ornithine density was not clearly observed, requiring further classification. On this particle stack, a 2D cleanup was performed (N = 100), followed by ab initio reconstruction (K = 2) and non-uniform refinement of 376,110 particles to 2.86 Å. To isolate the ligand-bound subset, we then performed binding–site–focused 3D classification without alignment (K = 8) using a binding-site mask (defined to include residues within 10 Å of the canonical APC superfamily binding site) as the solvent mask. The 3D classification parameters were: hard classification ON; class similarity = 0.01; online-EM batch size = 10,000; online-EM learning rate = 1.0. This processing pipeline yielded a class with a clear density difference between TM1 and TM6 at the canonical APC binding site (44,789 particles). This particle stack was further refined with non-uniform refinement, reference-based CTF refinement, non-uniform refinement and reference-based motion correction (RBMC) to produce a ligand-positive reconstruction at 3.34 Å (GS-FSC 0.143). Continuing from the initial ligand-positive class (47,054 particles), we expanded the ligand-bound stack by (i) performing non-uniform refinement, then (ii) two successive rounds of binding-site–focused seeded 3D classification without alignment (K = 2) with duplicate removal (yielding 134,784 particles), followed by (iii) non-uniform refinement and an additional 2D cleanup (N = 50; force max over shift/poses OFF; selected 107,868 particles). We then carried out a further non-uniform refinement and a final TM-domain–focused 3D classification without alignment (K = 2) to remove classes with degraded TM density. Ligand-positive classes were pooled, duplicates removed, and non-uniformly refined, producing the final L-Orn–bound reconstruction (76,191 particles; 3.32 Å). FSC and local-resolution estimates were computed in cryoSPARC.

Focused 3D classification of the apo + SybB5 dataset as a negative control for ligand-density selection: To assess whether our binding-site–focused 3D classification procedure could generate spurious ligand-like density, we applied the same strategy used for the L-Orn+SybB5 dataset to the apo+SybB5 dataset (no added ligand), using the same aligned focus mask and identical classification settings (K = 8; filter resolution = 2 Å; online-EM batch size per class = 10,000; learning rate = 1; initialization = PCA; class similarity = 0.1; force hard classification = true). Classes were compared after identical normalization and low-pass filtering to 4.0 Å (class07 at 4.5 Å) and were contoured at a common level. Normalization enables comparison of maps at identical contour values, and low-pass filtering standardizes map sharpness across classes with different nominal resolutions for direct visual comparison. No class, including the most feature-rich and interpretable class, showed ligand-shaped density in the canonical substrate pocket (Supplementary Fig. 12) comparable to the density observed for L-Orn in Fig. 1d and Supplementary Fig. 2b-c.

For comparisons between maps from different datasets, the maps were normalised to zero mean and unit variance and contoured at identical σ values. This can be achieved in ChimeraX with measure mapStats #1 followed by volume scale #1 shift —‘mean’ factor ‘1/stdev’. Maps focused on the binding-site (reported in Supplementary Fig. 12) were multiplied by the focus mask using the command volume multiply #1 #2.

Apo (—SybB5) dataset: 30,514 movies were processed in cryoSPARC v4.4 using patch motion correction and patch CTF estimation. For particle picking, we first applied a blob picker to 1,000 representative micrographs, classified those particles in 2D to generate templates, and then ran the template picker, yielding 8,226,459 particles. Four rounds of reference-free 2D classification (N = 100) reduced the stack to 1,235,585 particles, which underwent two additional 2D rounds (N = 50; circular mask diameter = 150 Å) to 724,282 particles. A multi-class ab-initio (C1, K=3) identified a transporter-like class (239,837 particles; 33%). Two further ab-initio rounds (K=2) produced a high-quality seed subset (65,088 particles; 27%), which was refined by non-uniform refinement to 6.26 Å and was then used for seeded multi-class ab-initio searches against the raw pool. The raw particles were partitioned into non-overlapping batches and de-duplicated (20×62,667; 5×246,850; 4×291,438); each batch was processed with seeded multi-class ab-initio, followed by three rounds of ab-initio (K=2) and finally non-uniform refinement, yielding reconstructions at 4.79 Å (84,178 particles), 4.82 Å (152,676), and 4.89 Å (239,513). After removing duplicates, the merged stack (323,978 particles) underwent non-uniform refinement followed by local refinement to 4.53 Å. A final 3D classification without alignment (K = 3) isolated a single well-resolved class (120,868 particles; 37%), which, after local refinement, produced the final apo reconstruction at 4.23 Å (GS-FSC = 0.143). All steps, including FSC and local-resolution estimation, were performed in cryoSPARC.

Model building and refinement
The AlphaFold2 model of AtCAT4 (CAT4; Alphafold2 PID AF-Q8W4K3-v3) was manually rigid-body fitted to the map using ChimeraX. A model of SybB5 was generated using ColabFold85 with default parameters and AMBER force field relaxation settings. The SybB5 model was then fitted to the map and merged with the AtCAT4 model. The apo and L-Orn-bound models of the AtCAT4—SybB5 complex (or AtCAT4 apo model without SybB5) were manually adjusted using Coot v0.9.886, and real-space refined using PHENIX87. Cholesterol (CLR) stereochemical parameters were generated with AceDRG,88 and -Ornithine (ORN) and POPC (LBN) parameters with ELBOW/PHENIX. The atomistic structural models were manually readjusted in Coot to set rotamers in a second round, followed by global real-space refinement in PHENIX. The +SybB5 and +SybB5+L-Orn models were further MDFF-refined in ISOLDE/ChimeraX89 using the AMBER ff14SB force field for protein and GAFF2/AM1-BCC for L-Orn and lipids, to relax the ligands’ geometries into their respective densities, resolve steric clashes, remove strain, and model TM kinks on both density and electrostatics. The ISOLDE-polished structures were real-space-refined to obtain final validation statistics. The figures depicting the molecular structures were prepared using ChimeraX90.

Proteoliposome reconstitution
SLC7A4 was reconstituted into liposomes consisting of 90:5:15 (w/w) E. coli polar extract:cholesterol:brain polar extract using biobeads. It was essential not to overconcentrate SLC7A4/GDN after the final gel-filtration step to avoid excess detergent. The lipids (Avanti) were solubilized in chloroform, evaporated on a rotary evaporator, and washed with n-pentane twice before being resuspended in 50 mM KH2PO4/K2HPO4 buffer pH 7.0 to final concentration of 20 mg/ml. These lipid vesicles were frozen and thawed five times in liquid nitrogen and stored at −80 °C until required. For protein reconstitution, purified SLC7A4 was diluted to 0.25-0.5 mg/ml in reconstitution buffer (20 mM KH2PO4/K2HPO4 pH 7.0, 150 mM NaCl). A lipid vesicle amount corresponding to a 1:80 protein-lipid ratio was thawed, diluted in reconstitution buffer to 10 mg/ml, and subsequently extruded through 0.8 μm and 0.4 μm filters 11 times. The extruded vesicles were then titrated with DDM:CHS (5:1 w/w) until 66% of A540nm was achieved; routinely, 0.025% (w/v) final DDM concentration was required. The disturbed lipid vesicles were batch-wise added to the protein over 1.5 h at room temperature, followed by 1 h incubation on ice. 250 μl biobeads were added (for a 300 μg reconstitution) and incubated for 1 h at 4 °C under 10 rpm rotation, followed by an additional 333 μl for 3 h, and a final exchange to 333 μl fresh biobeads overnight. Next morning, biobeads were discarded and replaced with fresh to 333 μl biobeads for 1 h before harvesting the proteoliposomes at 200,000g, 4°C, for 35 min, before resuspension in reconstitution buffer at a final protein concentration of 0.25 μg μl−1. The proteoliposomes were freeze-thawed three times in liquid nitrogen before storage at −80 °C. The amount of SLC7A4 (WT and mutants) successfully reconstituted into the liposomes was quantified by SDS–PAGE densitometry after solubilizing the liposomes with 1.5% DDM:CHS (5:1). Successfully reconstituted protein was considered as the fraction of the total DDM-extracted protein that did not precipitate after subjected to 200,000g, 4°C, for 35 min. Depending on the preparation, we found that 25-30% of SLC7A4 could be successfully reconstituted in liposomes and used this ratio to assign protein concentration to the proteoliposomes.

Liposome-based Radioactive transport assay
To observe concentrative transport of L-leucine in SLC7A4 proteoliposomes, an acetate-induced pH gradient was generated91. Proteoliposomes were thawed and the required amount for the assay (5.0 μg per time point) was harvested through ultracentrifugation (200,000g, 4 °C, 30 min) before resuspending in inside buffer (20 mM KH2PO4/K2HPO4 pH 6.5, 100 mM KAc, 2 mM MgSO4). The resuspended proteoliposomes were freeze-thawed five times to achieve buffer exchange and extruded via 0.4 μm filters 11 times, before being harvested again and resuspended in minimal amount of inside buffer, i.e. 25-fold less volume than transport reaction. To initiate transport, the proteoliposomes were 25-fold diluted in outside buffer (20 mM NaH2PO4/Na2HPO4 pH 6.5, 100 mM NaCl, 2 mM MgSO4) supplemented with 100 μM L-Leu, and trace amounts of 14C-L-Leu [(stock: 295.86 μM 338 mCi/mmol), 2.96 μM final assay concentration, 1:100 hot:cold dilution]. The transport reaction was incubated on a temperature-controlled heat block at 25 °C with periodical gentle mixing. Transport reaction time-points were taken by immediately halting transport by rapidly filtering onto 0.22 μm filters, which were then washed with 2 × 2 ml ice-cold 0.1 M LiCl. The amount of L-Leu transported into the liposomes was calculated by scintillation counting in Ultima Gold (PerkinElmer) and compared to a standard curve for the uptake mix.

Adherent Cell Transfection for Assays
HCT116-SLC7A5-KO cells (Resolute Cell line ID CE051H-164) were maintained in RPMI 1640 GlutaMAX medium (Thermo Fisher Scientific; Catalogue number 61870036) supplemented with 10% foetal bovine serum under 5% CO2 at 37°C. One day prior to transfection, 2.5 × 105 cells/ml were seeded into 12-well plates. On transfection day, the cells were monitored to be 65-70% confluent and had their media exchanged to 2% FBS media to allow transfection. 1 μg plasmid DNA (wild type SLC7A4 or mutants in pLexM, with a C-terminal FLAG tag) was complexed with 3 μg PEI-MAX in Opti-MEM Reduced Serum Medium and incubated for 5-10 minutes at room temperature. 100 μl of transfection mix per well was added dropwise to the cells and gently mixed. 16 h post-transfection, the media were changed to fresh media containing 10% FBS. Expression was allowed for 38-40 hours, after which the cells were used for transport assays, fluorescence microscopy, or expression analysis. Cells above 18 passages were discarded.

Cell-based Radioactive Transport Assay
Cells were washed twice with 1 ml of pre-warmed assay buffer. We used sodium-free buffers for the cell-based assay to reduce the background intrinsic transport activity of Na-dependent transport systems. The assay buffer composition was 10 mM HEPES×KOH, pH 7.5 or 10 mM MES×KOH, pH 5.5-6.5, 1 mM MgSO4, 2 mM CaCl2, 5 mM KCl, 137 mM choline chloride (as a sodium chloride substitute of equal ionic strength) and 10 mM D-glucose. The cells were gently washed with 0.3 ml/well assay buffer twice, before application of 0.3 ml of the assay buffer supplemented with 1 µM final 14C L-Leu concentration [(stock: 295.86 μM 338 mCi/mmol), 2.96 μM final assay concentration, 1:300 hot:cold dilution] and 10 µM cold L-Leu substrate (either L-Leu or any of the other amino acids, as indicated in the range from 0 µM to 1000 µM) onto the cells and incubated for 1, 3, 8, and 15 min at 37°C. After the desired time, the radioactive assay buffer was removed, and the cells were quickly washed twice with 0.3 ml ice-cold assay buffer without substrate. The cells were then lysed with 0.05% Triton X-100 (w/v) in PBS, pH 7.4, for 5 min and placed in scintillation vials with 0.3 ml scintillation fluid (Ultima Gold). The amount of transported 14C L-Leu inside the cells was calculated by scintillation counting (Perkin Elmer) and compared to a standard curve prepared from known amounts of uptake mix collected on the day of the experiment. To assay the pH dependence of the SLC7A4 mutants, time points at 15 min were measured. Total protein content of the cells was quantified using the BCA protein assay (Pierce™ BCA Protein Assay Kits Catalogue Number A55864), and 2 µg of samples were used to check expression of wild-type SLC7A4 and mutants using a Western blot with an anti-FLAG antibody (Merck F1804) at 10,000x dilution and anti-β-actin antibody (Merck A2228).

Statistical Comparisons
Analyses were performed in GraphPad Prism v10 (GraphPad Software). Bars show mean ± s.d. with overlaid points for each independent measurement; n denotes the number of independent measurements (technical replicates across biological replicates were averaged). All tests were two-sided with α = 0.05.

For Fig. 3d, we used a one-way ANOVA to compare uptake in the presence of each amino acid against the hot-only 14C-L-Leu control, followed by Dunnett’s multiple-comparisons test (familywise α = 0.05). For Fig. 5a, data were analysed with an ordinary two-way ANOVA with factors "mutant" and "pH" (5.5, 7.5) using Type III sums of squares, including the interaction term. Simple-effects comparisons of pH 5.5 vs pH 7.5 within each mutant were performed with Šídák adjustment for multiple testing (familywise α = 0.05).

Fluorescence Microscopy Localisation of SLC7A4 and Mutants
Immunofluorescence was used to check for plasma membrane localisation of SLC7A4. Cells were seeded as a monolayer on glass coverslips, transfected as described above with FLAG-tagged SLC7A4, media were changed 12 hr post-transfection, and cells were processed for immunofluorescence 36 hr post-transfection. Cells were washed in PBS pH 7.4 and fixed in 4% paraformaldehyde for 7 min. Following quenching in 50 mM ammonium chloride for 3 mins and further PBS washing, the cells were permeabilised with 0.5% saponin for 8 mins, and coverslips were washed with PBS-GSA (1x PBS with 10 mM Glycine and 0.2% sodium azide). Coverslips were then blocked in 1% bovine serum albumin (BSA) in PBS for 1 hr. Cells were stained with 50 µL each of mouse anti-FLAG (1:200 dilution) and rabbit anti- Na+/K+ ATPase (1:50 dilution) (plasma membrane marker) primary antibodies for 1 hr, washed, and further stained with 50 µL each of goat anti-mouse IgG AlexaFluor-488 (1:200) and anti-rabbit IgG AlexaFluor-647 (1:200) secondary antibody-fluorophore conjugates for 45 mins in the dark. Cells were then stained with DAPI for 10 minutes in the dark and washed 4-5 times with PBS. Coverslips were mounted on glass slides using a drop of Immu-Mount (Epredia™ 9990402). Experiments were performed on an LSM-980 confocal microscope (Zeiss) and images were processed in ZenBlue (v3.9, Zeiss) and Fiji.

Western Blot Expression Analysis of SLC7A4 and Mutants
HCT116-SLC7A5-KO cells were harvested from 12-well plates 36 hr post-transfection by first detaching cells using TrypLE™ Express Enzyme (1X) (Gibco™ 12604013) for 3 min at room temperature and then collecting the detached cells using 1X PBS in eppendorfs. Harvested cells were spun at 3000 rpm for 5 min at 4 °C, and the pellet was then lysed using lysis solution (1x PBS, 1% DDM:0.2%CHS, DNase, protease inhibitor) on ice for 30 min. The lysate was separated by centrifugation at 30,000 g for 20 minutes at 4 °C. Total cellular protein was estimated using the BCA assay (Pierce™ BCA Protein Assay Kits). Two micrograms of the sample were loaded onto a 12% SDS-PAGE gel, then transferred to a PVDF membrane (Immobilon). The membrane was blocked using 3% milk in PBST for 1 hour, cut across 55 kDa, and each section was then treated overnight with primary antibodies anti-FLAG (Merck F1804) at 1:10,000 for the target band and anti-beta actin (Merck A2228) at 1:10,000 for the loading control. After primary antibody incubation, the cut membranes were treated with goat anti-mouse antibody (Agilent P044701-2), HRP (1:10,000) for 45 min. The membranes were then treated with ECL solution (Cytiva) and developed on X-ray films.

Molecular Dynamics Simulations
Preparation of outward-open AtCAT4 for MD: The coordinates of SybB5 and cholesterols/PC lipids were deleted from the L-Orn-bound model. IL5 (residues 408-458 not resolved in cryoEM) were grafted from the AF2 predicted model (AlphafoldDB: AF-Q8W4K3-F1-v4) to fill in missing loops. A restrained geometry minimisation of residues within 6 Å of the binding site was performed using the conjugate gradient method in the gas phase until a convergence criterion of 0.01 kcal mol–1 Å–1 was reached, yielding the AtCAT4 MD model.

Preparation of outward-open human SLC7A4 for MD: We used the AtCAT4 MD model to build a homology model for human SLC7A4 in the outward-facing state. Specifically, the human SLC7A4 and AtCAT4 sequences were aligned with Clustal Omega, and the AtCAT4 coordinates were supplied as the template structure. MODELLER92 was used (with 10 models generated), and the model with the highest DOPE score (89.705) was selected. The model was superimposed onto the inward-open human LAT2 leucine-bound structure (PDB: 7CMI), and the leucine coordinates were used. Since SLC7A4 and LAT2 are in the outward and inward-facing states, respectively, the model superpositions were based on the scaffold domain residues (scaffold residues in human SLC7A4 numbering: 96-233, 291-414, 474-591), excluding the mobile bundle domain that moves between conformations. Tyr246 torsions were set to χ1 = +178.3° (trans) and χ2 = 74.1°, to cap the docked ligand via pi-cation interactions as seen in other occluded ligand-bound SLC7 structures. Coordinates for the TM1-6-7 binding site water molecule were copied from the GkApcT crystal structure (PDB:5OQT). A restrained geometry minimisation of residues within 6 Å of the binding site was performed using the conjugate gradient method in the gas phase until a convergence criterion of 0.01 kcal mol–1 Å–1 was reached, yielding the human SLC7A4 MD model.

Parameterisation and System Setup for MD: MD systems were set up as listed in Supplementary Table 2. For outward-facing simulations, we prepared (i) the human SLC7A4 homology model bound to L-leucine and (ii) AtCAT4 bound to L-ornithine (cryo-EM derived). Additional conditions (apo and/or alternative starting conformations) were prepared and simulated as described below and in Table 2. The protein-ligand complexes were assembled in fully solvated lipid bilayers with the CHARMM-GUI membrane builder93. The surrounding membrane was composed of a 4:1 POPC: cholesterol mixture of target size 12×12 nm². We removed CHARMM-GUI waters and ions and added ACE/NME capping residues using PyMOL. Protein topologies were generated using the Amber99SB-ILDN forcefield94 and lipids with Slipid forcefields95. The bound zwitterionic amino acid ligands were modelled with parm99SB atom types, as described by A.H.C. Horn96. The Horn parameters for L-leucine, available as .off file inputs (http://amber.manchester.ac.uk/), were loaded into AMBER18 tleap and subsequently converted to GROMACS-compatible .itp files via the acpype package97. The protein-lipid-ligand system was then solvated with 34,000 TIP3P98 water molecules (the precise number varies between different systems), neutralised to an ionic concentration of 0.15 M with NaCl using GROMACS99. Each system was subjected to two rounds of refinement with heavy atom restraints, using both steepest descent and conjugate gradient methods, until convergence was achieved with Fmax < 500 kJ/mol.

L-ornithine parameters were not available in the Horn force field set for proteinogenic zwitterionic amino acids (parm99SB-ILDN). They were therefore generated following the standard AMBER force field protocol for small molecules. The initial geometry of zwitterionic and protonated L-ornithine was optimised at the Hartree–Fock level with the 6-31G* basis set using Gaussian09. The electrostatic potential was computed at the same level of theory and used to derive atomic partial charges via the restrained electrostatic potential (RESP) fitting scheme. Atom types and bonded parameters were assigned using the General Amber Force Field 2 (GAFF2) as implemented in AmberTools18. The resulting ligand library and parameter/topology files were then converted to GROMACS-compatible .itp files using the acpype package. This approach is consistent with the parameterisation strategy applied by Horn for zwitterionic amino acids.

Molecular dynamics simulations in explicit solvent used GROMACS versions 2020.3 and 2021.4 as the MD engine (the slight version discrepancy is because of different installations on the two compute clusters we used). The electrostatic interactions were calculated using particle mesh Ewald100 with a short-range cutoff of 1.2 nm. The Lennard–Jones interaction cutoff was set to 1.2 nm, including the energy-pressure dispersion correction scheme implemented in GROMACS. Bonds involving hydrogen atoms were constrained by the LINCS algorithm, and a time step of 2 fs was used for the integration of the equations of motion. We assigned initial velocities and equilibrated each system according to the following protocol. The equilibration protocol used the weak-coupling Berendsen thermostat and barostat101 to achieve exponential convergence of pressure and temperature. The protocol was over seven successive steps, two in the NVT ensemble (2× 125 ps) and five in NPT (125, 500, 1000, 2× 10,000 ps), using a leap-frog integrator. We gradually reduced position restraints over the seven steps, starting from 1,000 kJ/mol for the ligand, 4,000 kJ/mol for the protein backbone, 2,000 kJ/mol for the sidechains, and 1,000 kJ/mol for POPC P atoms and cholesterol O atoms (see step6.x_equilibration.mdp files). After equilibration, a 10 ns unrestrained NPT run was performed under production parameters, with semi-isotropic Parinello-Rahman pressure coupling102 set to 1 bar and the modified v-rescale thermostat103 (with a stochastic term) set to 310 K, to fully relax the system.

Unbiased MD: Unbiased production runs were carried out as summarised in Table 2 (AtCAT4 apo: 3×1 µs; AtCAT4 + L-Orn: 3×1 µs; Hs SLC7A4 HM + L-Leu: 1×1 µs) using the same simulation parameters as the final 10 ns equilibration step and retaining velocities. Snapshots were recorded every 50 ps. Trajectories were aligned on the TM-core backbone to remove global translation/rotation prior to analysis. In the cases where we needed to obtain representative bound poses for downstream short-repeat sampling (5×200 ns for AtCAT4 + L-Orn and 3×200 ns for the Hs SLC7A4 HM + L-Leu systems), we clustered protein–ligand configurations using Gromacs gmx cluster on defining the binding site as all heavy atoms of the residues within 10 Å of the ligand. We clustered with an RMSD cutoff of 1 Å. Clusters were ranked by population, and the representative structure was chosen as the cluster median (central structure, i.e. frame with minimal RMSD to other cluster members) of the most populated cluster. From this representative structure, we initiated independent repeats (distinct random initial velocities) using production settings. The protein-ligand interactions were calculated with MDAnalysis v. 2.9.0104 and ProLIF v. 2.1.0105.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "The manuscript by Kolokouris et al. deals with a very important topic in the field of membrane transporters, that is, the resolution of a 3D structure of a 14TM membrane transporter. This finding is, per se, noteworthy. Moreover, the identification of substrate specificity of SLC7A4 from At and Hs triggers an advancement in the field with positive outcomes for human and plant physiology. The mechanism of induced fit changes in TM1 is also an interesting feature for the SLC7 family biology. Finally, the identification of a transport mechanism sensing protons is again a novelty in the field. For all the mentioned reasons the manuscript deserves to be published in Nat Comm. Only a few concerns arose which are listed below:\n1) The introduction lacks of background in plant. Considering that the 3D structure is of an At transporter, the relevance in plant physiology, besides that in humans, should be discussed with particular reference to H+-dependence. Moreover, is not clear if in At the protein as an intracellular localization (e.g. vacuolar) or is in plasma membrane as authors show with IF for Hs isoform. This information should be provided.\n2) In the introduction the reference to the result summary is not relevant in my opinion; I would rather substitute it with a rationale of the entire work.\n3) In the result section, I would add a 2D topology of the transporter to show how the 14TMs are distributed and which helices are involved in the harm, hash or bundle domains if this classification is maintained.\n4) The lack of activity for AtSLC7A4 in none of the used system may open question on the quality of the protein produced for CryoEM structure determination. Is that possible that the protein used for CryoEM is not functional and, hence, maybe in a folding state that is not stable enough?\n5) The IC50 for Leu and Arg in text are reported within a mM range, whereas in the figure are in uM range. Please correct.\n6) Taking together the reported data, how do authors explain the different specificity towards Ornithine or Leu of the two transporters from At and from Hs? This should be explained also considering plant physiology.\n7) Arg transport using the human transporter should be also tested to verify the hypothesis of a residual CAA transport activity. This is relevant also in terms of pH dependency to show if the pH dependency only occurs when neutral amino acids are transported or if it is conserved also in CAA.\n8) Which is the physiological explanation for a pH dependent Leu transport occurring at the plasma membrane? They mention placenta and sperm maturation but without a specific speculation on the role for this transporter-pH changes-leucine in these body districts\n9) In methods: information on the concentration of radioactive Leu used is missing, i.e. the Ci of the stock solution of 14C leucine.", "reviewer_2": "While general fold in this family is well explored, the SLC7A4 structure has a number of unique features that make this study novel and interesting. Helix 1 is straight but can unwind, the TM3/4 loop is elongated, and several lipids are found binding to the transporter. Moreover, the transporter is specific for leucine. The structure is that of Arabidopsis SLC7A4, while the human transporter was a homology model. The transporter mechanism appears plausible. Particularly interesting is the allosteric activation by acidic pH.\nI have only a couple of minor comments.\nFig. 1B, please indicate that Fig. 1b shows the apo-structure and explain LMNG in the legend.\nThe space vacated by the flipping away of\nPage 6: It is tempting to speculate that LMNG is replaced by a lipid in physiological circumstances. Have you seen any evidence of this?\nPage 7: The flexibility of EL4 could be addressed by MD simulations.\nPage 12: The units are wrong for the IC50. This should micromolar not millimolar.\nPage 16: Is there active Arginine transport in the tri-M mutation or just inhibition?\nDiscussion:\nPhysiologically, the transporter is difficult to understand. It is entirely specific for leucine but inhibited by other amino acids. It could be that this transporter is active in acidic compartments but for what purpose? Perhaps it is more a sensor than a transporter, but this would go too far for this study.", "reviewer_3": "Kolokouris et al. report on structural and functional aspects underlying pH-responsive amino acid transport mediated by SLC7A4, the cationic amino acid transporter CAT4. The authors determined three structures of a plant homolog from Arabidopsis thaliana, i.e., in the apo form at 4.2 Å resolution, the apo form bound to a sybody at 3.3 Å resolution and the L-ornithine-sybody complex at 3.3 Å resolution. In addition, the authors performed functional assays and molecular dynamics (MD) simulations using a human SLC7A4 homology model, constructed based on the newly obtained structure of the SLC7A4 homolog from plant (A. thaliana). They identify and describe a pH sensor conserved in the bacterial homolog GkApcT whose structure they previously solved and extrapolate this finding to human SLC7A4. They propose a model for pH sensing, although additional data are required to fully elucidate the underlying mechanism.\nIn general, the submitted manuscript is unsatisfactory: it is suboptimally written, poorly structured and contains several major flaws (as detailed below). Furthermore, the manuscript would benefit from thorough proofreading to eliminate typographical errors and inconsistencies.\nMajor points\n1. The manuscript is difficult to read and follow, as it lacks a clear and coherent structure. A major revision and thorough reorganization are required to improve its readability and logical flow. It is surprising, especially for a submission to a renowned journal such as Nature Communications, that the manuscript does not contain a distinct structure and clear red line. The section following the Introduction appears to combine elements of \"Results and Discussion\", yet a separate Discussion section is included later, creating confusion for the reader. Furthermore, some results (e.g., the pKa determination) are presented within the Discussion, which is unconventional and misleading. Overall, the current structure significantly detracts from the manuscript’s clarity, forcing the reviewer to focus on organizational issues rather than on evaluating the scientific content.\n2. As mentioned in my introductory paragraph above, this manuscript reports three structures of an SLC7A4 homolog from Arabidopsis thaliana. However, the authors do not explore in depth the structure or function of this protein. Instead, they use the obtained structure primarily as a template to build a homology model of the human SLC7A4, for which they did not determine the structure experimentally.\nAt this point, the reviewer is left wondering whether including the plant homolog’s structure was indeed necessary for this manuscript. The same modeling, molecular dynamics simulations and functional experiments could potentially have been carried out using existing structures of mouse CAT1 and GkApcT as templates or simply using an alphafold predicted model.\nBased on these considerations, the authors should generate homology models of human SLC7A4 using the published mouse CAT1 and GkApcT structures as well as the human SLC7A4 model from alphafold, and compare these to the model of human SLC7A4 derived from the Arabidopsis homolog structure. If these alternative models predict similar structural features, the inclusion of the new cryo-EM structure becomes questionable. If they differ, the authors should justify their choice of the plant homolog as a structural basis by including and discussing a comparative analysis of all human SLC7A4 models (obtained from the mouse CAT1, the Arabidopsis SLC7A4 homologue and GkApcT as well as the alphafold model) in the Supplementary Information.\n3. Cryo-EM density of the L-ornithin\n- Page 8, text: “The cryo-EM map reveals a well-resolved density for L-Orn in the canonical amino acid binding site…”\nThe statement “well-resolved” is a bold statement for a density, which basically fails to show atomistic features of L-ornithine nor nicely surrounds the molecule as shown in Fig. 1d. Please moderate such statements.\n- The density of the substrate in Fig. 1d and Extended Data Fig. 6a look to me \"carved\". Furthermore, only one viewing angle is shown, i.e., the same view in Fig. 1d and Extended Data Fig. 6a.\nIf the density was indeed carved, please include the uncarved density in Fig. 1a and Extended Data Fig. 6. In the latter, three different views of the uncarved density (substrate and surrounding interacting amino acids) should be provided to allow a comprehensive assessment of the quality of the obtained substrate density (and surrounding). Finally, please indicate in these two Figures at which threshold the density is displayed.\n- Major point: Based on Extended Data Fig. 2, only about 12% of particles of the “At SLC7A4-sybody-and-L-ornithine bound” structure apparently bound L-ornithine. This reviewer is not convinced by the final “3D-classification without alignment” run used to select the L-ornithine bound state.\nTo exclude the possibility of classification artifacts or spurious density being refined as ligand, the authors must verify their procedure with the apo structure. Briefly, perform the same analysis (as in Extended Data Fig. 2, e.g., using same number of 3D classes and same parameters) with the At SLC7A4-sybody apo structure (no L-ornithine) and prove that no comparable density is found in the substrate binding pocket arising from artefacts. This analysis should be included in Supplementary Information as a new Extended Data Figure.\nAlternatively, the authors could repeat the cryo-EM experiment using a higher concentration of L-ornithine to achieve improved occupancy of the substrate binding site, thereby providing a clearer and more convincing density for L-ornithine and enabling the reliable construction of a publishable structural model.\n4. After reading the manuscript, the claim that SLC7A4 proteins are, or could be, pH-responsive amino acid transporters remains somewhat hypothetical, indicating a lack of demonstrated novelty. Additional experimental evidence is needed to substantiate this assertion, which is strongly emphasized in the title but not sufficiently supported or demonstrated in the presented data.\nSignificant points to be addressed:\n5. The SLC nomenclature should be carefully verified and applied consistently. In my view, it is incorrect to refer to the Arabidopsis thaliana homolog of (human) SLC7A4 as “At SLC7A4”. For instance, solute carriers from mouse are written as Slc7a4 (in contrast to SLC7A4 for the human one). Therefore, in the context of this manuscript, the current “At SLC7A4” designation should be replaced with AtCAT4 or described as “the homolog from Arabidopsis thaliana (or plant) of (human) SLC7A4.”\nImportantly, this adjustment would eliminate the existing confusion in the manuscript, where it is not always clear whether the authors are referring to the plant homolog (AtCAT4) or to human SLC7A4.\n6. Abstract: The Abstract is written in very general terms, making it unclear what was actually accomplished in the present study. While this broad formulation may make the work sound more appealing, it omits key information such as the fact that the structure determined is that of a plant homolog of human SLC7A4, and that the subsequent analyses are based primarily on a homology model of human SLC7A4 derived from this plant structure.\nAs stated above, this raises serious questions about the necessity of including the AtCAT4 structure, since an equally strong homology model could likely have been built using the already published mouse CAT1 or GkApcT structures, or an SLC7A4 alphafold model. As it stands, the manuscript appears somewhat patchwork-like, combining datasets that do not fit seamlessly together.\nTherefore, the authors are encouraged to revise the Abstract so that it more realistically reflects the actual scope and content of the presented work, avoiding any impression of overselling.\nOther points, mainly minor:\n- General comment: Providing the manuscript with line numbering would have been helpful and would have facilitated the review process.\n- Page 2 “Structures of many eukaryotic HAT transporters...“: Please define the abbreviation HAT upon first use.\n- Page 3: “Nevertheless, we were intrigued by the close homology of SLC7A4 to GkApcT…”.\nAs the authors provided the amino acid sequence identity between SLC7A4 and SLC7A1/2, this reviewer suggests providing also the amino acid sequence identity between SLC7A4 and GkApcT.\n- Page 4, last paragraph: This section is written in an unclear manner. The authors report the structure determination of the apo and L-ornithine-bound AtCAT4 in complex with a sybody. However, Figure 1 also includes an apo structure without the sybody. The authors are therefore asked to align the text more precisely with the figure panels in Figure 1.\nIn addition, providing the individual resolutions of the obtained structures would strengthen the statement “…to aid particle alignment during data processing…” and help readers without a structural biology background better understand the rationale for using a sybody.\nFurthermore, I guess Extended Data Fig. 2 shows the processing workflow for the sybody-bound structures. Please clarify this point, for example by adding the corresponding information to the legend of Extended Data Fig. 2.\n- Page 5, paragraph below Fig. 1 caption (“Although the apo structure…”):\nFirst, the rationale for comparing At SLC7A4 with SLC7A5 and SLC7A7 is unclear - why were these transporters chosen instead of, for example, mouse CAT1 or GkApcT, which appear to be more closely related? Please clarify the reasoning behind the selected structural comparisons by providing pertinent information.\nSecond, the statement that the structure “…closely resembles…” these transporters is somewhat misleading given the reported RMSD values of 4.5-5.6 Å, which indicate only moderate structural similarity.\n- Page 5, Figure 1d: The reviewer requests visualizing the molecules and hydrogen bonds without including hydrogen atoms, as their positions cannot be assigned with confidence at the achieved resolution. To enable a clearer assessment of the substrate pose within the binding pocket, the reviewer further requests displaying distances (numbers, Å) measured between heavy atoms directly in the figure.\n- Page 6, \"The function of these additional helices is currently unclear. The most likely explanation is that they compensate for the absence of the heavy chain subunit and aid stability or folding of CAT family members.\"\nSince the heavy-chain subunit interacts with the opposite side of the transporter compared to TMs 11 and 12 of At SLC7A4 (as described in the manuscript), it is questionable whether such a compensatory effect can be rationalized.\n- Page 6, “…occupied by a Lauryl-maltose neopentyl glycol (LMNG) detergent molecule (Extended Data Fig. 3e). The acyl chains of the detergent…” and onward to the end of this paragraph.\nThe authors are asked to provide cryo-EM density proof for those statements in an Extended Data Figure.\n- Pages 6-7, \"We thus conclude that whilst we cannot rule out the impact of the sybody on the position of EL4 in the higher-resolution structure, our data suggest that EL4 is dynamic and may flip away from the transporter in the outward-facing state.\"\nThe authors have addressed the potential impact of sybody binding; however, was the possibility also considered that the observed “flipped-out” conformation of EL4 might result solely from its interaction with the LMNG molecule? The reviewer believes that this possibility should be examined before concluding with confidence that EL4 is inherently dynamic.\n- Page 7, “…well-defined densities for lipid molecules (Extended Data Fig. 5a-b).”\nBased on the information presented in Extended Data Fig. 5a, this reviewer remains unconvinced by the authors’ claim of “well-defined density.” Please clarify this statement and provide additional views of the corresponding density in an Extended Data Figure to substantiate the claim.\n- Page 7, “Our data indicate this pocket is a conserved cholesterol-binding site within the CAT sub-family and is worth further study to understand any regulatory role cholesterol might have on CAT transporter function.”\nReferring to the site as “conserved” appears to be an overstatement given that this conclusion is based on a single structure. Please revise the wording accordingly to avoid overinterpretation.\n- Page 8, \" In contrast, the ε-amino group on the L-Orn side chain interacts with Asp116 on TM3 via a salt bridge and to Asp243 on TM6b via a water-mediated hydrogen bond (W1) (Fig. 1d and Extended Data Fig. 6a).\"\nThis reviewer is concerned that, at the achieved resolution, reliable placement of water molecules may be challenging. Are the positions of the modeled water molecules supported by the MD simulations presented later in the manuscript? If not, please remove this statement since not support by well defined, high-resolution density.\n- Page 8, “The structure of SLC7A4 bound to L-Ornithine (L-Orn) exhibits…”\nI assume this structure corresponds to the sybody-bound form. Please clarify this point and revise the text accordingly, as it is not clearly stated in the current version\n- Page 8, “…forming a short π-helix bulge…”\nThis is an interesting structural feature; however, Fig. 1c appears to show an elongated helical element rather than a bulge. Please provide a more appropriate image to illustrate this feature accurately.\n- Page 8, “…water-mediated hydrogen bond…”.\nThe obtained resolution (>3 Å) is generally insufficient to support such detailed structural conclusions. Please revise the statement accordingly.\n- Page 9, \"The binding pose we observe for L-Orn in SLC7A4 is also consistent with the pose we reported previously for the more distantly related prokaryotic homologue, GkApcT (PDB 5OQT), which also involves an interaction of the side chain guanidino group with an acidic side chain on TM337 (Extended Data Fig. 6c).\"\nPlease rephrase this sentence to clearly indicate that the structure also includes GkApcT bound to L-arginine. In addition, note that the PDB code differs from that provided in Extended Data Fig. 6c and actually corresponds to the alanine-bound GkApcT (likely a typographical error). Considering the major concern raised regarding the ligand cryo-EM density, the authors are kindly requested to reassess whether the available density sufficiently supports the structural comparisons between the binding sites of SLC7A1 and GkApcT.\n- Page 11, \"Compared to the cryo-EM model, Ala44 is shifted by an additional ~1.7 Å over the span of the MD repeats, further drawing the ligand backbone carboxyl into the fully accessible GAG backbone pocket.\"\nThe MD simulations are presented as supporting evidence for the proposed induced-fit mechanism. However, this reviewer remains uncertain about the interpretation of the events observed during the simulations. Specifically, the further unwinding of TM1, the entry and coordination of a water molecule and the “better accommodation” of the substrate. Why are these features not observed in the cryo-EM data and what is their significance in the context of the proposed mechanism? Please adapt text and provide additional information and argumentation.\n- Page 11, Figure 2, panels b-d: The extent of the unwinding motion around the GAG-motif is a bit difficult to assess from the provided views of TM1 and TM6. Maybe superimposed structures of a closer view around the binding pocket would be helpful to improve assessment.\n- Pages 19-20: The description of the proposed transport model suffers from issues of sequencing and redundancy, which negatively affect readability and comprehension. The induced-fit binding of L-leucine is described after the transition from the outward-open, substrate-free state to the outward-facing occluded, L-leucine-bound state (i.e., the transition from state i to ii), which disrupts the logical flow. Additionally, protonation of Glu125 is mentioned twice (passages 1 and 2) and could be streamlined. The hypothesized rotation of TM3 into the position observed in the AtCAT4 structure is also described somewhat differently than on page 19. This reviewer therefore requests that this paragraph be restructured and improved for greater clarity and consistency.\n- Page 26, “Thermal stability measurements”.\nPlease report on the final protein concentration and buffer constituents used for the assay/measurement.\n-Extended Data: The Extended Data section does not include representative micrographs, 2D class averages or viewing direction (azimuthal angle) distribution plots. Please add these essential elements to provide a more complete overview of the cryo-EM data quality and processing.", "reviewer_4": "The manuscript by Kolokouris et al. focusses on the transport mechanism of SLC7A4, an amino acid transporter of the solute carrier protein family. Unlike homologous proteins some structural and functional features are unique, which are shown by means of cryoEM structures, MD simulations, and pharmacological experiments. In particular two aspects are interesting and deserve publication. First the unique profile of transported amino acids (selective for leucine). And second, the pH sensitivity of the transporter. I want to state that I am not an expert in the technical aspects of cryoEM, so I cannot fully judge on this particular part.\nGiven the interesting topic, the sound methodology used, and the way of presenting the results, I would like to recommend publication of this manuscript in Nature Communications. However, some aspects have to be improved by the authors before publication.\n1) While the MD simulations have been carried out in a sound manner, I was confused by their description. E.g., I assume that the Table 2 is right, but in the methods section the authors state they have simulated in triplicates rather than 5 independent 200 ns simulations. It is also not clear from the text how many µs MDs have been carried out and from which of those replicas the clusters where selected. Please make the method section consistent and describe in more details how the clustering and selection of the representative frame was done.\n2) As a minor point, the authors mix one-letter and three-letter code for amino acids. Since it makes sense for the figures to use one-letter code, please also apply this throughout the manuscript.\n3) I miss a detailed structural comparison with other SLCs/amino acid transporters. Since new structures are reported in this manuscript, it would be nice to compare them with previous structures and highlight the unique features in more detail.\n4) The section on structural basis for leucine selectivity in Hs SLC7A4 is quite interesting, but misses a detailed discussion on the molecular level. The authors show the lipophilic residues that are interacting with leucine’s side chain and then directly head to arginine. It would be beneficial to discuss more closely related amino acids, e.g. valine, isoleucine. Why is the binding site so prone to leucine?"}, "author_response": "Response to reviewers’ comments:\nWe appreciate and value the additional workload involved in reviewing our paper and thank\nthe reviewers for their time and feedback. We have extensively reworked the text to address\nqueries regarding clarifications, rationale, and interpretations of the data. Below, we outline\nthe major changes to the manuscript. Amendments to the main text are highlighted in green\nand included below to help identify key updates\nPlease note that, in light of the reviewer's comments, we have revised our nomenclature in\nthe paper and refer to the plant SLC7A4 protein as AtCAT4 and the recent structures of the\nMus Musculus SLC7A1 and MmCAT1 throughout.\nReviewer 1.\nThe manuscript by Kolokouris et al. deals with a very important topic in the field of membrane\ntransporters, that is, the resolution of a 3D structure of a 14TM membrane transporter. This\nfinding is, per se, noteworthy. Moreover, the identification of substrate specificity of SLC7A4\nfrom At and Hs triggers an advancement in the field with positive outcomes for human and\nplant physiology. The mechanism of induced fit changes in TM1 is also an interesting feature\nfor the SLC7 family biology. Finally, the identification of a transport mechanism sensing\nprotons is again a novelty in the field. For all the mentioned reasons the manuscript deserves\nto be published in Nat Comm. Only a few concerns arose which are listed below:\nWe thank the reviewer for their support and enthusiasm for our study.\n1) The introduction lacks of background in plant. Considering that the 3D structure is of an At\ntransporter, the relevance in plant physiology, besides that in humans, should be discussed\nwith particular reference to H+-dependence. Moreover, is not clear if in At the protein as an\nintracellular localization (e.g. vacuolar) or is in plasma membrane as authors show with IF for\nHs isoform. This information should be provided.\nWe thank the reviewer for pointing out this omission. We have added a paragraph introducing\nthe Arabidopsis thaliana CAT homologues to the introduction. From the literature, it is unclear\nwhether AtCAT4 is pH dependent, as, to the best of our knowledge, no one has functionally\ncharacterised this protein prior to our study. Nevertheless, in Arabidopsis, CAT1, CAT5 and\nCAT6 are reported to localise to the plasma membrane and to mediate pH-dependent amino-\nacid uptake, as we now highlight in the main text and in the references, and these sequences\nare included in an updated Extended Data Fig. 1a-b.\n2) In the introduction the reference to the result summary is not relevant in my opinion; I would\nrather substitute it with a rationale of the entire work.\nWe have removed the standalone results-summary paragraph and replaced it with a\nmotivation-focused paragraph that outlines the rationale for the study:\nHere, we identify SLC7A4 as a pH-responsive plasma membrane leucine transporter in\nhumans and demonstrate that its plant homologue can bind both cationic amino acids and\nleucine. Combining structural, biochemical and functional data, we further demonstrate the\nclose evolutionary conservation between human and plant transporters and identify key side\nchains required for cationic amino acid recognition within the SLC7 family. (lines 103-108).\n1\n3) In the result section, I would add a 2D topology of the transporter to show how the 14TMs\nare distributed and which helices are involved in the harm, hash or bundle domains if this\nclassification is maintained.\nWe have now included a 2D topology map of AtCAT4, the binding epitope of SybB5 in the\nvicinity of the density modelled as an LMNG molecule, and AtCAT4 + SybB5 dissociation\nconstant determination and size-exclusion co-purification (Extended Data Fig. 3).\nRevised Extended Data Fig. 3. Cryo-EM structure of AtCAT4 bound to sybody B5\n(SybB5). a. Cryo-EM structure of apo AtCAT4 bound to SybB5 coloured from the N-terminus\n(blue) to the C-terminus (red). The topology diagram for the structure is shown to the right.\nThe inverted topology repeats (TMs 1-5 & 6-10) are shown as inverted triangles. b.\nElectrostatic surface representation of AtCAT4 showing the structural epitope recognised by\nSybB5. c. LMNG binding interface on apo AtCAT4 bound to SybB5. The cryo-EM density for\nthe bound LMNG molecule is shown (blue and threshold 0.3). d. Binding affinity (K )\nd\nmeasurement for SybB5, n=2 independent measurements. e. Size Exclusion Chromatography\n(SEC) profile for the AtCAT4-SybB5 complex using a Superdex S200 10/300 GL Increase\ncolumn. Inset, SDS-PAGE analysis of the fractions highlighted in the chromatogram. f. Circular\nDichroism (CD) spectra for the LMNG purified sample used in the cryo-EM experiments. g.\nThermal stabilisation of the LMNG purified AtCAT4 in the presence of increasing\n2\nconcentrations of L-Ornithine. Increasing concentrations of L-Alanine were used as a negative\ncontrol.\n4) The lack of activity for AtSLC7A4 in none of the used system may open question on the\nquality of the protein produced for CryoEM structure determination. Is that possible that the\nprotein used for CryoEM is not functional and, hence, maybe in a folding state that is not stable\nenough?\nWe thank the reviewer for raising the important question of whether the AtCAT4 protein used\nfor cryo-EM could be non-functional due to misfolding or poor stability. Several independent\nobservations argue against the misfolding/instability of the purified proteins used in this study.\nFirst, the circular dichroism (CD) spectra of AtCAT4 in the detergent used for cryo-EM (LMNG,\nLMNG + lipids) show predominantly α-helical secondary structure with characteristic minima\nat 208 and 222 nm. We have added this as new panel f in the revised Extended Data Fig. 3.\nAdditionally, the thermal stability nanoDSF measurements demonstrate ligand-selective\nstabilisation. Indeed, AtCAT4 shows a titratable increase in Tm upon L-Orn addition (0-40 mM)\nbut not upon L-alanine addition (Extended Data Fig. 3g). The nanoDSF assay has been\nvalidated as a reliable indicator for functional transporters1.\nConsistent with adopting the correctly folded state, WT AtCAT4 shows a strong thermal\nresponse to L-Orn, as shown in Fig. 1e (~4.5 °C), whereas binding-site mutants show\nmarkedly reduced responses (≤1 °C), including F237V. Notably, mutation of the homologous\naromatic position has been reported to abolish transport in related SLC7 transporters (e.g.,\nY244A in System Xc-2. We are confident these data support our conclusion that AtCAT4 is\nstabily folded in LMNG and able to bind cationic amino acids.\nSecondly, although we attempted to reconstitute the AtCAT4 transporter into proteoliposomes\nand to perform liposome-based transport assays. However, as shown in Figure 1 below, the\nreconstitution efficiency was <20%, and the transporter did not show any activity under\ncounterflow conditions or under an acetate-induced pH gradient.\nAtCAT4\n15% insertion eff.\nReconstitution of AtCAT4 in proteoliposomes. Left - 12 % SDS-PAGE gel showing the\nreconstitution of AtCAT4 from DDM-CHS.SN-supernatant. Right – 3[H] Amino Acid uptake\nassay using counterflow driven uptake.\n3\nreddaL gμ\n5.0\ngμ\n0.1\ngμ\n0.2\n\"gμ\n5.0\"\n\"gμ\n0.1\"\n\"gμ\n0.2\"\n\"gμ\n0.4\"\n\"gμ\n0.2\"\n\"gμ\n0.4\"\nytpme\ntellep\n.losni reddaL gμ\n5.0\ngμ\n0.1\ngμ\n0.2\n\"gμ\n5.0\"\n\"gμ\n0.1\"\n\"gμ\n0.2\"\n\"gμ\n0.4\"\n\"gμ\n0.2\"\n\"gμ\n0.4\"\nytpme\ntellep\n.losni\n180 -\n130 -\n100 -\n70 -\n55 -\n40 -\n35 -\n25 -\n15 -\nAt SLC7A4 sol. liposomes sol. SN GkApcT DDM sol. liposomes sol. SN\nDDM-CHS loading std.\nloading std.\nIn parallel, we reconstituted the bacterial transporter GkApcT as a positive control under\nidentical conditions3. We suspect the lower reconstitution efficiency is due to the poor stability\nin the DDM-CHS detergent mix. Unfortunately, we have found that LMNG is a poor detergent\nfor liposome reconstitution assays because it cannot be fully removed, resulting in leaky\nliposomes in our hands. Our conclusion from these experiments is that AtCAT4 is not suitable\nfor liposome reconstitution assays without considerable additional optimisation.\nHowever, we successfully reconstituted the human SLC7A4 protein and observed acetate-\ninduced uptake across a pH gradient. We have included this new data in Extended Data Fig.\n10c-d.\nTogether, our new biophysical and biochemical data support the interpretation that the AtCAT4\ncryo-EM sample was folded and ligand-responsive, and that human SLC7A4 can transport L-\nLeucine into proteoliposomes.\n5) The IC50 for Leu and Arg in text are reported within a mM range, whereas in the figure are\nin uM range. Please correct.\nDone.\n6) Taking together the reported data, how do authors explain the different specificity towards\nOrnithine or Leu of the two transporters from At and from Hs? This should be explained also\nconsidering plant physiology.\nWe have added a dedicated paragraph in our results section “The structural basis for leucine\nselectivity in SLC7A4” to address this.\nTaken together, our data explain why the Arabidopsis CAT4 and human SLC7A4\nhomologues have diverged towards preferential recognition of L-ornithine versus L-leucine,\nand why this divergence is physiologically coherent. In AtCAT4, the binding pocket remains\nhighly polar and is organised around the conserved TM3 acidic residue (Asp116) and\nsurrounding hydrogen-bonding network. This network stabilises protonated, flexible side\nchains such as L-ornithine (and related cationic amino acids), while still tolerating L-Leu\nbinding as indicated by our nanoDSF screen. Prior work further reports that AtCAT4 localises\npredominantly to the tonoplast and is broadly expressed. In this context, an Orn/CAA-biased\npocket is most consistent with a role in vacuolar amino-acid buffering and nitrogen\nremobilisation. It would help control cationic amino-acid pools that feed plant nitrogen\neconomy and polyamine/arginine-ornithine metabolism during growth and reproductive\ntransitions. In contrast, HsSLC7A4 has remodelled the side-chain environment around the\ncanonical TM1/TM6 motif into a predominantly hydrophobic pocket, centred on Val332,\nLeu336 and Leu394. This pocket tightly accommodates the branched side chain of L-Leu but\ndisfavours the more extended and charged side chains of cationic amino acids. This is\nreflected functionally by a ~30-fold lower IC50 for L-Leu compared with L-Arg and the absence\nof detectable L-Arg transport, despite measurable L-Arg binding. The Tri-M mutant, in which\nwe introduce three CAT1-like residues into this pocket, re-establishes high-affinity L-Arg\nrecognition and transport while modestly weakening L-Leu affinity. This demonstrates that a\nsmall set of side chains can switch the CAT4 scaffold between an Orn/CAA-biased state suited\nto plant vacuolar homeostasis and a Leu-biased state suited to mammalian leucine handling\nat specialised interfaces.\n4\n7) Arg transport using the human transporter should be also tested to verify the hypothesis of\na residual CAA transport activity. This is relevant also in terms of pH dependency to show if\nthe pH dependency only occurs when neutral amino acids are transported or if it is conserved\nalso in CAA.\nWe agree that assessing arginine transport would be informative, especially for establishing\nthe transport characteristics of the Tri-M.\nWe attempted to establish an arginine-uptake assay for human SLC7A4 in our HCT116 LAT1-\nknockout background, but basal [3H]-L-Arginine uptake remained high and prevented robust\nseparation of SLC7A4-dependent signal from endogenous transport. Indeed, we also\ntransfected the currently available cell line with human CAT1 and did not record robust\ntransport above background under assay conditions, despite CAT1 being a well-known\narginine transporter. We turned to HeLa cells for the same assay but also observed high levels\nof arginine background noise across time points. This observation is consistent with\nquantitative transporter data in the literature, showing that arginine uptake in cells is largely\nmediated by y+LAT2 (system y+L) and CAT transporters, with y+LAT2 accounting for the\nmajority of the flux4.\nWe therefore considered using a combination of pharmacological tools to reduce the\nbackground signal. However we could not find a clean way to suppress the endogenous\nbackground uptake without simultaneously confounding the activity for SLC7A4: N-\nethylmaleimide (NEM) inhibits CAT family transporters (system y+; potentially including\nSLC7A4) but not y+LAT isoforms5 and thus cannot eliminate the dominant y+LAT2\ncomponent; conversely, competitive suppression of y+LAT2 with neutral amino acids such as\nleucine is not diagnostic because leucine is also the primary substrate/inhibitor for SLC7A4\n(IC for L-Leu 24 ± 5 μM, Fig. 3f). Other neutral amino acids also inhibit SLC7A4 transport as\n50\nshown in Fig. 3d.\nTherefore, a definitive cellular arginine-transport assay for SLC7A4 would require additional\ngenetic removal of the major endogenous arginine transporters (e.g., CAT1 and y+LAT2) in\naddition to LAT1 KO in HCT116 cells, which is challenging and beyond the scope of the current\nstudy.\nAs noted above, we successfully reconstituted human SLC7A4 into liposomes. However, the\nlevel of reconstitution was ~ 25 % and the activity, whilst significantly above background\n(Extended Data Fig. 9c-d), is too low for the detailed biochemical studies asked for by the\nreferee. It is our intention to follow up on this line of questioning once we have optimised the\nliposome reconstitution assay to enable robust activity measurements. In the meantime, we\nhave revised the manuscript to state that our results support the role of V332S/L336S/L394M\nin amino acid recognition, and to leave the question of whether the triple mutant can transport\narginine for a follow-up study.\n8) Which is the physiological explanation for a pH dependent Leu transport occurring at the\nplasma membrane? They mention placenta and sperm maturation but without a specific\nspeculation on the role for this transporter-pH changes-leucine in these body districts\nWe have revised our final discussion paragraph to reflect our current hypothesis for the role\nof SLC7A4-mediated pH-dependent leucine transport at the plasma membrane. Specifically:\nMore broadly, our study uncovers an additional plasma membrane leucine transporter\nwithin the SLC7 family, but with the distinctive feature that it has evolved to respond to changes\nin extracellular pH. Gene expression data report SLC7A4 enrichment in the choroid plexus\n(blood–brain barrier) and testis, with secondary expression reported in placental trophoblasts.\nThese tissues share a common physiological property: they function as highly regulated\nnutrient exchange interfaces, where acid–base handling plays an integral role6,7. In this\nphysiological setting, a pH-gated leucine transport system could be advantageous as it would\nharness local acidity changes as an activation mechanism that promotes cellular leucine\nuptake.\n9) In methods: information on the concentration of radioactive Leu used is missing, i.e. the Ci\nof the stock solution of 14C leucine.\nWe thank the reviewer for noting this and have now included the information in the Methods\nin lined 1122-1123 and 1154-1155:\n…14C-L-leucine [(stock: 295.86 μM 338 mCi/mmol), 2.96 μM final assay concentration, 1:100\nhot:cold dilution].\nReviewer 2.\nWe thank the reviewer for their comments, which have benefited our manuscript, and have\nfully implemented their recommendations in this version.\nWhile general fold in this family is well explored, the SLC7A4 structure has a number of unique\nfeatures that make this study novel and interesting. Helix 1 is straight but can unwind, the\nTM3/4 loop is elongated, and several lipids are found binding to the transporter. Moreover, the\ntransporter is specific for leucine. The structure is that of Arabidopsis SLC7A4, while the\nhuman transporter was a homology model. The transporter mechanism appears plausible.\nParticularly interesting is the allosteric activation by acidic pH.\nI have only a couple of minor comments.\nFig. 1B, please indicate that Fig. 1b shows the apo-structure and explain LMNG in the legend.\nWe have added an updated Fig. 1b legend with: “b. Cryo-EM structure of apo AtCAT4 with\nTMs 1 and 6 highlighted and an LMNG and cholesterol molecules bound to the extracellular\nside of the outward-open transporter shown as blue sticks.”\nPage 6: It is tempting to speculate that LMNG is replaced by a lipid in physiological\ncircumstances. Have you seen any evidence of this?\nWe agree this is an attractive idea, but we do not have direct evidence that LMNG is replaced\nby a specific endogenous lipid under physiological conditions.\nWhat we do observe is a well-defined non-protein density in the TM1/TM7/EL4 region where\nthe “flipped-in” EL4 should occupy during the transport cycle. Our density is best explained by\nan LMNG molecule (Extended Data Fig. 4f): (i) its size/shape is consistent with an LMNG-like\ndetergent headgroup plus hydrophobic tails, (ii) it is present across all LMNG-containing\ndatasets we collected (±L-Orn, +SybB5), and (iii) in all these conditions the transporter\nremains outward-open, consistent with LMNG occupying the space normally taken by the\n“flipped-in” EL4 conformation during the transport cycle. In our samples, LMNG was present\nat ~30 μM (0.003% w/v), which is sufficient to populate such a hydrophobic cavity and stabilise\na single conformational state. Notably, TM7 in SLC7A4 is elongated relative to other APC-fold\nmembers, resulting in a shorter EL4, which may facilitate the flipped-out configuration captured\nin our cryo-EM reconstructions.\nWhile we have no direct evidence that an endogenous lipid occupies the cavity formed by the\nflipping out of EL4 in SLC7A4, structurally analogous vestibule pockets in SLC6 transporters\ncan accommodate lipid-like allosteric ligands (e.g., oleoyl-D-lysine in GlyT28,9) supporting the\nplausibility that detergent can mimic occupation of a hydrophobic site.\nPage 7: The flexibility of EL4 could be addressed by MD simulations.\nWe have now addressed EL4 flexibility directly using the MD simulations we already\nperformed. Specifically, we analysed six independent all-atom trajectories of the outward-open\ncryo-EM starting model (apo, n = 3; +L-Orn, n = 3) and, for comparison, trajectories initiated\nfrom an inward-facing AlphaFold2-derived model in which EL4 is “flipped-in” (n = 3; +L-Orn).\nWe summarise these results in a new Extended Data Fig. 5.\nAcross the combined MD ensemble, starting from our cryo-EM structures, we observed EL4\nstably in the flipped-out conformation. Principal component analysis on backbone atoms of\nEL4 (including the inward-facing flipped-in MD AF2-derived ensemble) shows that the\ndominant mode (PC1; >80% of the variance) corresponds to a reaction coordinate describing\nEL4 “flip-out to flip-in” motion. This coordinate clearly separates the outward-open (apo and\n+L-Orn; cryo-EM-derived) simulations from the inward-facing (AF2-derived) simulations,\nconsistent with EL4 adopting distinct conformational states throughout the transport cycle.\nImportantly, within the outward-open state, EL4 dynamics are not detectably altered by ligand,\ni.e. per-residue RMSF profiles show no statistically significant differences between apo and\n+L-Orn trajectories. As expected, EL4 RMSF is higher in the outward-open simulations (where\nthe loop is solvent-exposed) than in the inward-facing simulations (where EL4 is more\nconstrained by contacts with TM1b). Overall, these MD results are consistent with our\nproposed mechanism in which EL4 is flipped out in the outward-open conformation and\nsubsequently stabilises downstream TM1 rearrangements required for occluded/inward-\nfacing states, as observed for the mouse CAT1 transporter captured in inward-facing\nconformations10,11.\nThe MD data on EL4 prompted us to re-examine the low-resolution Syb dataset (also collected\nin LMNG) with a specific focus on EL4. As noted in the main text, this reconstruction shows\nclear density for all 14 transmembrane helices and for the structured, symmetry-related loop\nregion IL1, but no interpretable density for EL4, consistent with substantial mobility. The MD\nsimulations further indicate that both “flipped-out” and “flipped-in” EL4 configurations can be\nstable endpoints of the transition, motivating us to test whether multiple EL4 states could be\nresolved from our cryo-EM data. Consistent with this hypothesis, focused classification of the\nfinal particle stack of the -Syb dataset yields a minor class with an alternative, more “flipped-\nin” EL4 placement packed against TM1b (Extended Data Fig. 12), supporting that EL4 can\nsample multiple conformations even under identical detergent conditions. It is thus our\nconclusion that LMNG in the pocket in the +Syb datasets results from EL4 physiologically\nadopting its flipped-out conformation. The void left is then likely occupied by an LMNG\nmolecule.\nconformational heterogeneity observed in the EL4 loop. a, Essential-dynamics/PCA of\nEL4 backbone coordinates using a shared basis across simulations of the outward-open cryo-\nEM starting model (apo, n = 3; +L-Orn, n = 3) and an inward-facing AlphaFold2-derived model\nwith EL4 “flipped-in” (+L-Orn, n = 3). 2D projections (PC1/PC2) show that the dominant mode\n(PC1; >80% variance) corresponds to an EL4 flip-out → flip-in coordinate, separating the\noutward-open ensembles from the inward-facing ensemble. The PC1 mean is similar for apo\nand +L-Orn outward-open simulations. Per-residue EL4 Cα RMSF (mean ± SD across\nrepeats) is not detectably changed by ligand in the outward-open state, and is higher than in\nthe inward-facing ensemble, consistent with solvent exposure when EL4 is flipped out and\nconstraint against TM1b when flipped in. The PCA variance spectrum is shown for the pooled\ntrajectories. b, Structural context for the EL4 states. Representative outward-open cryo-EM\nmodel shows EL4 flipped out and a detergent-sized cavity adjacent to TM1/TM7. The low-\nresolution −Syb dataset (LMNG) lacks interpretable EL4 density, consistent with mobility.\nPreliminary EL4-focused 3D classification of the −Syb particle stack yields a minor class\n(34,329/120,868 particles, 28%) with an alternative, more flipped-in EL4 placement packed\nagainst TM1b. Density threshold shown at 0.1.\nDone.\nPage 16: Is there active Arginine transport in the tri-M mutation or just inhibition?\nDue to high arginine background noise in the SLC7A5-KO HCT116 cells we used for our\nassays, we were not able to robustly quantify arginine transport in the Tri-M. A future direction\nfor achieving arginine tracking would be to optimise our HCT-116 cell line by serially testing\nCAT1-3 knockouts until a minimal background could be achieved with an empty plasmid\ncontrol. Indeed, we also transfected the currently available cell line with CAT1 and did not\nrecord robust transport above background under assay conditions, despite CAT1 being a well-\nknown arginine transporter. We turned to HeLa cells for the same assay but also observed\nhigh levels of arginine background noise across time points. We reserve this optimisation for\nfuture work.\nDiscussion:\nPhysiologically, the transporter is difficult to understand. It is entirely specific for leucine but\ninhibited by other amino acids. It could be that this transporter is active in acidic compartments\nbut for what purpose? Perhaps it is more a sensor than a transporter, but this would go too far\nfor this study.\nWe thank the reviewer for highlighting the need to clarify the physiological relevance of our\nfindings. While defining a specific in vivo role will require dedicated in vivo studies beyond the\nscope of this work, the mechanistic insights we report, together with recently published\nResolute expression data, point to SLC7A4 functioning as a leucine transporter in epithelia\ncharacterised by tightly regulated acid-base microenvironments and a need to maintain\nnutrient-rich intracellular amino acid pools. Accordingly, we have revised the Discussion to first\npresent the proposed transport mechanism (as before) and then to add the following\nphysiological clarifications to contextualise these molecular findings (lines 755-763):\nMore broadly, our study uncovers a new plasma membrane leucine transporter within\nthe SLC7 family, with the distinctive ability to respond to changes in extracellular pH. Gene\nexpression data indicate SLC7A4 enrichment in the choroid plexus (blood–brain barrier)12 and\ntestis13, with secondary expression reported in placental trophoblasts14. These tissues share\na common physiological property: they function as highly regulated nutrient-exchange\ninterfaces, where acid–base handling plays an integral role6,7. In this physiological setting, a\npH-gated leucine transport system could be advantageous as it would harness local acidity\nchanges as an activation mechanism that promotes cellular leucine uptake.\nKolokouris et al. report on structural and functional aspects underlying pH-responsive amino\nacid transport mediated by SLC7A4, the cationic amino acid transporter CAT4. The authors\ndetermined three structures of a plant homolog from Arabidopsis thaliana, i.e., in the apo form\nat 4.2 Å resolution, the apo form bound to a sybody at 3.3 Å resolution and the L-ornithine-\nsybody complex at 3.3 Å resolution. In addition, the authors performed functional assays and\nmolecular dynamics (MD) simulations using a human SLC7A4 homology model, constructed\nbased on the newly obtained structure of the SLC7A4 homolog from plant (A. thaliana). They\nidentify and describe a pH sensor conserved in the bacterial homolog GkApcT whose structure\nthey previously solved and extrapolate this finding to human SLC7A4. They propose a model\nfor pH sensing, although additional data are required to fully elucidate the underlying\nmechanism.\nIn general, the submitted manuscript is unsatisfactory: it is suboptimally written, poorly\nstructured and contains several major flaws (as detailed below). Furthermore, the manuscript\nwould benefit from thorough proofreading to eliminate typographical errors and\ninconsistencies.\nWe thank the reviewer for the detailed critique. We have revised the manuscript extensively\nto address the readability, organisation, and substantiation concerns raised and to ensure that\nall statements are appropriately supported by the data presented.\nMajor points\n1. The manuscript is difficult to read and follow, as it lacks a clear and coherent structure. A\nmajor revision and thorough reorganization are required to improve its readability and\nlogical flow. It is surprising, especially for a submission to a renowned journal such as\nNature Communications, that the manuscript does not contain a distinct structure and clear\nred line. The section following the Introduction appears to combine elements of \"Results\nand Discussion\", yet a separate Discussion section is included later, creating confusion\nfor the reader. Furthermore, some results (e.g., the pKa determination) are presented\nwithin the Discussion, which is unconventional and misleading. Overall, the current\nstructure significantly detracts from the manuscript’s clarity, forcing the reviewer to focus\non organizational issues rather than on evaluating the scientific content.\nWe take on board the reviewer comments, although we also appreciate, as will the reviewer,\nthat every researcher has a particular style when writing and presenting their research. While\nour manuscript follows the standard structure (Introduction, Results, Discussion, Methods) we\nhave now strengthened the “red line” through the Results/Discussion.\nWe also moved results-style content out of the Discussion (including the pKa analysis and\nother quantitative/technical statements), reserving the Discussion for interpretation in the\nbroader amino-acid transporter literature.\nHowever, we chose not to undertake a wholesale reordering of the Results because we\nconsider the existing sequence to provide a coherent progression from the AtCAT4 structures\nto functional measurements and mechanistic interpretation of human SLC7A4. Nevertheless,\nwe made targeted edits throughout to improve clarity, reduce redundancy, and sharpen\ntransitions. This overall presentation strategy is consistent with prior Nature Communications\ntransporter studies that use a plant homologue structure to inform mechanism and human\nfunctional determinants (e.g., the Arabidopsis cystinosin structures alongside human\ncystinosin functional/mutational analysis)15.\n2. As mentioned in my introductory paragraph above, this manuscript reports three structures\nof an SLC7A4 homolog from Arabidopsis thaliana. However, the authors do not explore in\n10\ndepth the structure or function of this protein. Instead, they use the obtained structure primarily\nas a template to build a homology model of the human SLC7A4, for which they did not\ndetermine the structure experimentally. At this point, the reviewer is left wondering whether\nincluding the plant homolog’s structure was indeed necessary for this manuscript. The same\nmodeling, molecular dynamics simulations and functional experiments could potentially have\nbeen carried out using existing structures of mouse CAT1 and GkApcT as templates or simply\nusing an alphafold predicted model. Based on these considerations, the authors should\ngenerate homology models of human SLC7A4 using the published mouse CAT1 and GkApcT\nstructures as well as the human SLC7A4 model from alphafold, and compare these to the\nmodel of human SLC7A4 derived from the Arabidopsis homolog structure. If these alternative\nmodels predict similar structural features, the inclusion of the new cryo-EM structure becomes\nquestionable. If they differ, the authors should justify their choice of the plant homolog as a\nstructural basis by including and discussing a comparative analysis of all human SLC7A4\nmodels (obtained from the mouse CAT1, the Arabidopsis SLC7A4 homologue and GkApcT\nas well as the alphafold model) in the Supplementary Information.\nWe carefully noted and considered the reviewers points in these comments. The Arabidopsis\nthaliana homologue (AtCAT4; Q8W4K3) was selected from a panel of SLC7A4 homologues\n(Extended Data Fig. 1c-d; Rn, Mm, Dr, Hs) because it is a eukaryotic CAT-family member\nclosely related to human SLC7A4, showed superior biochemical stability for cryo-EM, and\nretains CAT-subfamily features absent from the prokaryotic template GkApcT (notably TM11–\nTM12 and the conserved IL5 region) that are relevant to the eukaryotic architecture and\ntransport cycle.\nThe importance of protein stability presents important practical benefits, such as the ability to\nwithstand the generation and selection of sybodies16. Indeed, we could not improve the\nresolution of the AtCAT4 dataset without sybody SybB5, and despite collecting a large cryo-\nEM dataset for human SLC7A4 in leucine (~30,000 movies) we did not obtain a structure,\nconsistent with the broader difficulty of solving human CAT-family proteins relative to stable\northologues. This is consistent with the broader pattern that CAT-family structures have more\ncommonly been obtained from non-human orthologues (e.g., MmCAT1 rather than HsCAT111\nand with the use of viral proteins to stabilise the mouse CAT1 transporter for structural\nstudies10.\nAvailable CAT-family templates also represent different conformational endpoints (AtCAT4\noutward-open vs. MmCAT1 inward-open and GkApcT inward-facing occluded) and are\ntherefore complementary rather than redundant for understanding the conformational\nlandscape of the SLC7 cationic amino acid transporters. Notably, no existing structure\nprovided an experimentally determined outward-open CAT framework for residue-level\nhypotheses central to our study (e.g., E125-unwound TM10 and Tri-M effects), so we use the\nAtCAT4 cryo-EM structures as the primary basis for mechanistic inference and for\ndesigning/interpreting human SLC7A4 mutagenesis and transport assays, while referencing\nMmCAT1- and GkApcT-based homology models where they inform other states (summarised\nin Fig. 6).\nFinally, while additional homology models built from more distant templates in different\nconformations could be informative for other stages of the transport cycle, they would\nnecessarily differ by construction and would not alter the conclusions anchored in the\nexperimentally determined outward-open AtCAT4 structures.\n3. Cryo-EM density of the L-ornithine\n- Page 8, text: “The cryo-EM map reveals a well-resolved density for L-Orn in the canonical\namino acid binding site…”The statement “well-resolved” is a bold statement for a density,\nwhich basically fails to show atomistic features of L-ornithine nor nicely surrounds the molecule\nas shown in Fig. 1d. Please moderate such statements.\n(lines 283-307):\nThe structure of AtCAT4 bound to L-Ornithine (L-Orn) adopts an outward-open conformation\nthat closely matches the apo structure (Extended Data Fig. 2b), with an r.m.s.d. of 1.16 Å over\na\nin the CAT family when adopting an outward-open conformation. The cryo-EM map shows\ncontinuous, ligand-shaped density in the canonical substrate pocket. Its location and overall\npose are consistent with the conserved α-amino-acid binding geometry described across\nSLC7 transporters in outward-facing substrate-bound states 17-20.\nThe L-ornithine ligand is located between TMs 1 and 6 from the helix bundle domain and TMs\n3, 10 and 8 from the scaffold domain (Fig. 1d and Extended Data Fig. 2c). While the local\nresolution in the pocket (3.06 Å; measured within 5 Å of L-Orn) does not support atom-by-\natom features of L-ornithine, the assignment is supported by the surrounding binding-site\ngeometry and complementary biochemical evidence (Fig. 1d-e, Extended Data Fig. 3g).\n- The density of the substrate in Fig. 1d and Extended Data Fig. 6a look to me \"carved\".\nFurthermore, only one viewing angle is shown, i.e., the same view in Fig. 1d and Extended\nData Fig. 6a. If the density was indeed carved, please include the uncarved density in Fig. 1a\nand Extended Data Fig. 6. In the latter, three different views of the uncarved density (substrate\nand surrounding interacting amino acids) should be provided to allow a comprehensive\nassessment of the quality of the obtained substrate density (and surrounding). Finally, please\nindicate in these two Figures at which threshold the density is displayed.\nThe density shown in Fig. 1d and the now Extended Data Fig. 8a was not artificial; however,\nto enable a more direct assessment of the ligand density and its surroundings, we now provide\ntwo unmasked density views of the substrate pocket. We kept Fig. 1d and Extended Data Fig.\n8 (we removed hydrogens from both), which focused on interaction geometry and cross-\ntransporter comparisons (AtCAT4, GkApcT, MmCAT1), because overlaying all-atom residues\nwith the full pocket density substantially reduces readability in those panels.\nTo address the reviewer’s point without overloading these figures, we added further\ninformation to our Extended Data Fig. 2 and cite it in the L-ornithine structure section.\nExtended Data Fig. 2c shows the complete atomistic modelling of L-Orn-AtCAT4 with focused\nelements on each protein domain. We included a section focusing on the density around L-\nOrn, including the surrounding binding-site residues, in two views (the original “top” view used\nin Fig. 1d and an additional 90-degree orientation). We report the density contour threshold\nused. We additionally include a panel with hydrogens omitted and heavy-atom distances\nannotated for the key contacts to demonstrate that the H-bonds are within the usual H-bond\ndistance criteria. (Map contoured at 6.5σ).\n- Major point: Based on Extended Data Fig. 2, only about 12% of particles of the “At SLC7A4-\nsybody-and-L-ornithine bound” structure apparently bound L-ornithine. This reviewer is not\nconvinced by the final “3D-classification without alignment” run used to select the L-ornithine\nbound state.\nTo exclude the possibility of classification artifacts or spurious density being refined as ligand,\nthe authors must verify their procedure with the apo structure. Briefly, perform the same\nanalysis (as in Extended Data Fig. 2, e.g., using same number of 3D classes and same\nparameters) with the At SLC7A4-sybody apo structure (no L-ornithine) and prove that no\ncomparable density is found in the substrate binding pocket arising from artefacts. This\nanalysis should be included in Supplementary Information as a new Extended Data Figure.\nof L-ornithine to achieve improved occupancy of the substrate binding site, thereby providing\na clearer and more convincing density for L-ornithine and enabling the reliable construction of\na publishable structural model.\nWe thank the reviewer for this request. We have implemented all the suggested changes and\nwe thank the reviewer for enhancing the robustness of our `L-Orn` bound structural data\nthrough their recommendations. Below, we list the modifications we have made:\nValidation of the focused 3D classification protocol by an apo negative control:\nWe repeated the identical focused 3D classification protocol (same binding site-focused mask, K\n= 8, identical parameters) on the apo + SybB5 dataset and observed no ligand-shaped density\nin the canonical substrate pocket in any class, including the best-resolved class. We have\nconstructed a new Extended Data Fig. 11 summarising the classification results. This supports\nthat the ligand density observed in the L-Orn dataset is not a classification artefact. All volumes\nwere low-pass filtered to 4 Å, normalised to zero mean and unit variance, and contoured at\nidentical σ values. The chimera commands used for this processing are described in the\nMethods. Collectively, the methods section now includes the following description (starting at\nline 1066):\nFocused 3D classification of the apo + SybB5 dataset as a negative control for ligand-\ndensity selection: To assess whether our binding-site–focused 3D classification procedure\ncould generate spurious ligand-like density, we applied the same strategy used for the L-\nOrn+SybB5 dataset to the apo+SybB5 dataset (no added ligand), using the same aligned\nfocus mask and identical classification settings (K = 8; filter resolution = 2 Å; online-EM batch\nsize per class = 10,000; learning rate = 1; initialization = PCA; class similarity = 0.1; force hard\nclassification = true). Classes were compared after identical normalization and low-pass\nfiltering to 4.0 Å (class07 at 4.5 Å) and were contoured at a common level. Normalization\nenables comparison of maps at identical contour values, and low-pass filtering standardizes\nmap sharpness across classes with different nominal resolutions for direct visual comparison.\nNo class, including the most feature-rich and interpretable class, showed ligand-shaped\ndensity in the canonical substrate pocket (Extended Data Fig. 12) comparable to the density\nobserved for L-Orn in Fig. 1d and Extended Data Fig. 2b-c.\nFor comparisons between maps from different datasets, the maps were normalised to zero\nmean and unit variance and contoured at identical σ values. This can be achieved in ChimeraX\nwith measure mapStats #1 followed by volume scale #1 shift —‘mean’ factor ‘1/stdev’. Maps\nfocused on the binding-site (reported in ED Figure R3) were multiplied by the focus mask\nusing the command volume multiply #1 #2. (lines 1066-1086)\nLow Orn-bound particle numbers concern: We clarify that the originally cited ~12% refers\nto the focused-classification step (44,789 / 376,110 AtCAT4 particles that refine well), not the\nfull dataset. To increase ligand-class particle count we have extended the processing and\nhave managed to increase the final ligand-bound reconstruction from 47k to 76k particles\n(76,191; 3.32 Å), corresponding to ~20% at the focused-classification stage (now presented\nin the revised version of Extended Data Fig. 2b). Although not a massive improvement we\nobserve and increase in L-Orn side chain density compared to the first submission. The\napparently low occupancy is also consistent with biochemical data for L-Orn on purified\nprotein. Specifically, with 10 mM L-Orn added to ~64 µM AtSLC7A4 (5 mg/mL complex with\nSybB5) for cryo-EM, the 20% occupancy is consistent with the apparent binding behaviour\nfrom our L-Orn titration experiment in nanoDSF (presented in Extended Data Fig. 3g). We\nhave updated the cryo-EM maps presenting the L-Orn binding site with the latest map (Fig.\n1d, Extended Data Fig. 2b-c, and Extended Data Fig. 8a).\n13\n4. After reading the manuscript, the claim that SLC7A4 proteins are, or could be, pH-\nresponsive amino acid transporters remains somewhat hypothetical, indicating a lack of\ndemonstrated novelty. Additional experimental evidence is needed to substantiate this\nassertion, which is strongly emphasized in the title but not sufficiently supported or demonstrated in the\npresented data.\nWe have now included additional liposome assay data showing that SLC7A4 transports L-\nLeucine under an acetate-induced pH gradient (Extended Data Fig. 9c-d). However, we do\nacknowledge that more in-depth biochemical assays are needed to fully understand the\nrelationship between pH and leucine transport via SLC7A4. However, we do consider our data\nsufficiently robust to support our statement that SLC7A4 is a leucine transporter, which is the\nfirst such report in the literature, and is activated under acidic external conditions, which is\nalso the first report that pH regulates human SLC7A1-4/CAT transporter activity.\nSignificant points to be addressed:\n5. The SLC nomenclature should be carefully verified and applied consistently. In my view, it\nis incorrect to refer to the Arabidopsis thaliana homolog of (human) SLC7A4 as “At SLC7A4”.\nFor instance, solute carriers from mouse are written as Slc7a4 (in contrast to SLC7A4 for the\nhuman one). Therefore, in the context of this manuscript, the current “At SLC7A4” designation\nshould be replaced with AtCAT4 or described as “the homolog from Arabidopsis thaliana (or\nplant) of (human) SLC7A4.”\nImportantly, this adjustment would eliminate the existing confusion in the manuscript, where it\nis not always clear whether the authors are referring to the plant homolog (AtCAT4) or to\nhuman SLC7A4.\nAs the reviewer no doubt appreciates, nomenclature is tricky when different fields work on the\nsame proteins and use different names. Our rationale was to stick with the SLC nomenclature,\nas our main aim was to study the human transporter. However, we appreciate that, within the\nfield of plant biology, the CAT nomenclature is still widely used.\nWe have therefore revised the nomenclature throughout to eliminate ambiguity: the\nArabidopsis thaliana transporter is now referred to as AtCAT4 (CAT4; UniProt Q8W4K3),\nwhich is consistent with the plant physiology field21 and the human transporter as SLC7A4,\nconsistent with recent studies on human SLC transporters12. Where relevant, we explicitly\ndescribe AtCAT4 as “the Arabidopsis (plant) homologue of human SLC7A4” at first mention\nand in figure legends, and we have corrected all instances where “At SLC7A4” could be\nmisconstrued. Similarly, we have included ‘human SLC7A4’ in the Figure titles.\n6. Abstract: The Abstract is written in very general terms, making it unclear what was actually\naccomplished in the present study. While this broad formulation may make the work sound\nmore appealing, it omits key information such as the fact that the structure determined is that\nof a plant homolog of human SLC7A4, and that the subsequent analyses are based primarily\non a homology model of human SLC7A4 derived from this plant structure.\nAs stated above, this raises serious questions about the necessity of including the AtCAT4\nstructure, since an equally strong homology model could likely have been built using the\nalready published mouse CAT1 or GkApcT structures, or an SLC7A4 alphafold model. As it\nstands, the manuscript appears somewhat patchwork-like, combining datasets that do not fit\nseamlessly together. Therefore, the authors are encouraged to revise the Abstract so that it\nmore realistically reflects the actual scope and content of the presented work, avoiding any\nimpression of overselling.\nWe appreciate the reviewer’s point here. Our aim in the first submission was to write a general\nabstract that would appeal to the general science audience of Nature Communications.\nwhat new data we have generated, the methods used and the conclusions drawn.\nRegarding the necessity of our structures in the outward-open state (not captured before for\na CAT family member), we do not agree that existing templates (MmCAT1, GkApcT, or even\npredicted AlphaFold structures) are interchangeable for the questions addressed within our\nstudy: these alternatives represent different conformational endpoints (inward-facing or\noccluded) and therefore cannot substitute for an experimentally determined outward-open\nstructure, which is the state that anchors our residue-level mechanistic interpretation and the\ndesign/interpretation of the human mutagenesis and functional assays. We clarify this point in\nthe revised text while keeping the Abstract appropriately concise.\nOther points, mainly minor:\n- General comment: Providing the manuscript with line numbering would have been helpful\nand would have facilitated the review process.\nWe have added numbering to the revised manuscript.\n- Page 2 “Structures of many eukaryotic HAT transporters...“: Please define the abbreviation\nHAT upon first use.\nWe have defined HATs in line 57.\n- Page 3: “Nevertheless, we were intrigued by the close homology of SLC7A4 to GkApcT…”.\nAs the authors provided the amino acid sequence identity between SLC7A4 and SLC7A1/2,\nthis reviewer suggests providing also the amino acid sequence identity between SLC7A4 and\nGkApcT.\nOur revised Extended Data Fig. 1 now shows a multiple sequence alignment of CAT\ntransporters (AtCAT1, 4, 5, 6), the bacterial GkApcT, Human CAT1, CAT2, CAT3, Human\nLAT1 (SLC7A5; another leucine transporter), all compared to human SLC7A4 as the reference\nas per the reviewer’s request. To demonstrate that AtCAT4 is a close eukaryotic CAT\nhomologue to SLC7A4, we used our multiple sequence alignment to build the phylogenetic\nrelationship between GkApcT, AtCAT4 and SLC7A4 (Extended Data Fig. 1b), which showed\nthat AtCAT4 is an evolutionary closer homologue to human SLC7A4 than the distant bacterial\nGkApcT homologue. We have referenced this figure in the main results section “The plant\nCAT4 homologue was of particular interest, as it provided a closer evolutionary link to the\nhuman transporter than the bacterial counterpart, GkApcT (Extended Data Fig. 1b).” (lines\n120-122).\n- Page 4, last paragraph: This section is written in an unclear manner. The authors report the\nstructure determination of the apo and L-ornithine-bound AtCAT4 in complex with a sybody.\nHowever, Figure 1 also includes an apo structure without the sybody. The authors are\ntherefore asked to align the text more precisely with the figure panels in Figure 1.\nIn addition, providing the individual resolutions of the obtained structures would strengthen the\nstatement “…to aid particle alignment during data processing…” and help readers without a\nstructural biology background better understand the rationale for using a sybody.\nFurthermore, I guess Extended Data Fig. 2 shows the processing workflow for the sybody-\nbound structures. Please clarify this point, for example by adding the corresponding\ninformation to the legend of Extended Data Fig. 2.\nWe thank the reviewer for this comment. We have revised the text in the Results section to\nclosely align the described structures with the panels in Fig. 1, clearly distinguishing the\nsybody-bound apo and L-ornithine-bound reconstructions from the sybody-free apo\nreconstruction. We also now report the individual global resolutions for each reconstruction at\n15\nfirst mention to clarify the rationale for using SybB5 to aid particle alignment during data\nprocessing. Finally, we have updated the legend of Extended Data Fig. 2 to state explicitly\nthat it shows the processing workflow for the sybody-bound datasets, and we direct the reader\nto the corresponding figure for the sybody-free apo processing/workflow. However, due to the\ncomplexity of the narrative in the study, we felt that an explicit strict adherence to the panel\norder in Fig. 1 would disrupt the flow of the paper.\n- Page 5, paragraph below Fig. 1 caption (“Although the apo structure…”):\nFirst, the rationale for comparing At SLC7A4 with SLC7A5 and SLC7A7 is unclear - why were\nthese transporters chosen instead of, for example, mouse CAT1 or GkApcT, which appear to\nbe more closely related? Please clarify the reasoning behind the selected structural\ncomparisons by providing pertinent information.\nSecond, the statement that the structure “…closely resembles…” these transporters is\nsomewhat misleading given the reported RMSD values of 4.5-5.6 Å, which indicate only\nmoderate structural similarity.\nWe agree that our original wording and the rationale for the comparison required clarification.\nWe compared AtCAT4 to SLC7A5/LAT1 and SLC7A7/y+LAT1 because these HAT light\nchains are among the few eukaryotic SLC7 members with substrate-bound outward-\nopen/outward-facing cryo-EM structures, thus providing the most appropriate structural\nreference set for an outward-open binding-pocket comparison.\nBy contrast, the two available CAT subfamily structures capture different conformational\nendpoints (i.e., mouse CAT1 is inward-facing10, while GkApcT is occluded3), making them\ncomplementary for understanding the transport cycle but less suitable for direct comparison\nwith an outward-open structure, as reported here for AtCAT4.\nWe have therefore revised the text to (i) explicitly state that the LAT1/y+LAT1 comparisons\nare made to benchmark the outward-open/outward-facing state and conserved SLC7 binding-\npocket geometry, and (ii) moderate the similarity language: we now state that AtCAT4 shares\nthe conserved APC/LeuT-like fold with these transporters rather than “closely resembles”\nthem, consistent with the reported RMSD values (4.5-5.6 Å) indicating moderate global\nsimilarity.\nAlthough the apo AtCAT4 structure adopts the same outward-facing states observed in\nLAT1/SLC7A5 (PDB: 8KDP)22and y+LAT1/SLC7A7 (PDB: 9KJU)20, the root mean square\ndeviation (r.m.s.d.) values indicate only moderate global similarity (4.5 Å over 280 Cα and 5.6\nÅ over 240 Cα, respectively). However, we chose to use these LAT structures for our\ncomparison, as they are the most evolutionarily close reference structures available. In\ncontrast, recent CAT-family structures of SLC7A1 from Mus musculus, hereafter referred to as\nMmCAT1, and GkApcT capture different conformational states (inward-facing apo and\noccluded)3,10,11. (lines 164-171).\n- Page 5, Figure 1d: The reviewer requests visualizing the molecules and hydrogen bonds\nwithout including hydrogen atoms, as their positions cannot be assigned with confidence at\nthe achieved resolution. To enable a clearer assessment of the substrate pose within the\nbinding pocket, the reviewer further requests displaying distances (numbers, Å) measured\nbetween heavy atoms directly in the figure.\nWe thank the reviewer for this suggestion. We have removed hydrogen atoms from Fig. 1d\nand Extended Data Fig. 8. In addition, we now provide an Extended Data panel (Extended\nData Fig. 2c) showing the L-Orn binding pocket with hydrogen atoms omitted and with the\nrelevant heavy-atom distances (Å) annotated for the key ligand-protein contacts. We did not\n16\nadd these distance labels to Fig. 1d because the panel is already information-dense and\nbecame visually cluttered when annotated.\n- Page 6, \"The function of these additional helices is currently unclear. The most likely\nexplanation is that they compensate for the absence of the heavy chain subunit and aid\nstability or folding of CAT family members.\"\nSince the heavy-chain subunit interacts with the opposite side of the transporter compared to\nTMs 11 and 12 of At SLC7A4 (as described in the manuscript), it is questionable whether such\na compensatory effect can be rationalized.\nWe thank the reviewer for this point and agree that “compensation for the heavy chain” was\nimprecise, given that the SLC3 heavy-chain transmembrane helix contacts the opposite face\nof the transporter.\nWe have removed this statement and now describe the additional helices (TMs 11-12 in\neukaryotic CATs) more conservatively as CAT-subfamily features that may contribute to\nstability and/or higher-order assembly. Importantly, in many LeuT/APC-fold transporters that\nlack these extra helices (e.g., AdiC) and in SLC12 cotransporters (e.g., NKCC1 and KCC2),\nthe homodimer interface is formed by the terminal helical pair of the core fold (TM11-TM12 in\nthose proteins), which corresponds to TM13-TM14 in eukaryotic CATs. In this architecture,\nthe CAT-specific TMs 11-12 sit adjacent to, and could flank or support, the TM13-TM14 face\nrather than directly substituting for the SLC3 heavy-chain interaction. We conclude by\nsuggesting a potential hypothetical role in homodimerization of CAT transporters, currently\nbeyond the scope of this work.\nAlthough the function of these additional helices is currently unclear, the placement of the\nCAT-specific TM helices (TM11-12) creates an extended hydrophobic surface compatible with\nprotein–protein contacts and raises the possibility that CAT-family members may form higher-\norder assemblies. In related LeuT/APC-fold transporters that lack these extra helices (e.g.,\nAdiC) and in SLC12 cotransporters (e.g., NKCC1 and KCC2), homodimers are formed via the\nterminal helical pair of the core fold (TM11–TM12), which corresponds to TM13–TM14 in\neukaryotic CATs (Fig. 1b); in this architecture, the CAT-specific TMs 11–12 would flank and\npotentially support the TM13–TM14 dimerisation interface23,24. Given that SLC7 HATs already\nfunction as obligate heterodimers with an SLC3 heavy chain, it will be interesting to determine\nwhether the CAT subfamily also employs oligomerisation as a regulatory mechanism. (lines\n180-191).\n- Page 6, “…occupied by a Lauryl-maltose neopentyl glycol (LMNG) detergent molecule\n(Extended Data Fig. 3e). The acyl chains of the detergent…” and onward to the end of this\nparagraph.The authors are asked to provide cryo-EM density proof for those statements in an\nExtended Data Figure.\nWe have now included the requested cryo-EM density of the LMNG molecule we find bound\non AtCAT4+Syb Orn-bound complex, which we have included in Extended Data Fig. 4f. The\nequivalent site for the apo AtCAT4+Syb dataset is shown in Extended Data Fig. 3c. In both\ncase the map threshold is stated in the figure legend.\n17\n- Pages 6-7, \"We thus conclude that whilst we cannot rule out the impact of the sybody on the\nposition of EL4 in the higher-resolution structure, our data suggest that EL4 is dynamic and\nmay flip away from the transporter in the outward-facing state.\"\nThe authors have addressed the potential impact of sybody binding; however, was the\npossibility also considered that the observed “flipped-out” conformation of EL4 might result\nsolely from its interaction with the LMNG molecule? The reviewer believes that this possibility\nshould be examined before concluding with confidence that EL4 is inherently dynamic.\nWe thank the reviewer for raising this point, and as they note, we are acutely aware of\noverinterpretation in cryo-EM experiments. As described above in our response to the\nflexibility of EL4 and summarised in the new Extended Data Fig. 5a, our new MD analysis\nsupports our original hypothesis regarding the flexibility of EL4. Our interpretation of the data\nis that EL4 exists in dynamic equilibrium between flipped-in and flipped-out states, with the\nLMNG molecule stabilising the latter state.\nWe therefore interpret the LMNG density as occupying and stabilising a pre-existing\nhydrophobic cavity that becomes available when EL4 disengages in the outward-open state,\nrather than as the primary driver of EL4 displacement.\nThis interpretation is supported by the MD simulations shown in Extended Data Fig. 5a, which\nwere performed without LMNG yet still show substantial EL4 mobility/outward-open EL4\nbehaviour. Consistent with this interpretation, focused classification of the low-resolution Syb\ndataset (also in LMNG) yields a minor class with an alternative, more “flipped-in” EL4\nplacement (Extended Data Fig. 5b), supporting the idea that EL4 can sample multiple\nconfigurations even under identical detergent conditions. We have revised the main text to\nexplain and cite the data presented in Extended Data Fig. 5.\n- Page 7, “…well-defined densities for lipid molecules (Extended Data Fig. 5a-b).”\nBased on the information presented in Extended Data Fig. 5a, this reviewer remains\nunconvinced by the authors’ claim of “well-defined density.” Please clarify this statement and\nprovide additional views of the corresponding density in an Extended Data Figure to\nsubstantiate the claim.\nWe have now modified the language to ‘In the cryoEM map for the L-Orn-bound structure, we\nobserved several densities, which are consistent with lipid molecules (Extended Data Fig. 7a-\nb)’. We have shown the density we discuss in Extended Data Fig. 7a.\n- Page 7, “Our data indicate this pocket is a conserved cholesterol-binding site within the CAT\nsub-family and is worth further study to understand any regulatory role cholesterol might have\non CAT transporter function.”\nReferring to the site as “conserved” appears to be an overstatement given that this conclusion\nis based on a single structure. Please revise the wording accordingly to avoid\noverinterpretation.\nWe thank the reviewer for this point. We have revised the text to: “Our data indicate that this\npocket is broadly conserved within the CAT subfamily and warrants further study to\nunderstand any regulatory role cholesterol might play in CAT transporter function” and now\nstate that we observe cholesterol in this cavity in AtCAT4, while broader sterol occupancy and\nfunctional relevance remain to be established.\nWe additionally note two lines of support for describing the pocket as conserved at the level\nof pocket chemistry: (i) the residues lining the cavity are broadly conserved across CAT-family\nhomologues by BLOSUM62 similarity scoring relative to AtCAT4 (e.g., MmCAT1 83%\nsimilarity; human CAT1/SLC7A1 83%; human SLC7A4 78%; table shown), consistent with\n18\npreservation of a hydrophobic sterol-compatible surface; and (ii) an equivalent sterol ester\n(CHS) has been modelled in the corresponding pocket in the MmCAT1 structure (PDB: 9FQT),\nalbeit in an inward-open conformation, indicating that this cavity can accommodate sterols in\nanother CAT-family member and in a distinct state of the transport cycle.\nNote: We report BLOSUM62 similarity (not strict identity) for residues aligned to the AtCAT4\npocket (F66-A72, P222-A233, I543, Y546, L547, N550), which is appropriate for lipid-binding\ncavities where conservative hydrophobic/aromatic substitutions are expected to preserve\npocket geometry and chemistry.\nAtCAT4 reference\nAtCAT4 -\nSLC7A4 78\nSLC7A1 83\nMmCAT1 83\nAtCAT1 78\nHsCAT2B 74\nHsCAT3 74\nAtCAT2 91\nAtCAT3 91\nAtCAT5 70\nAtCAT6 74\nAtCAT7 83\nAtCAT8 78\nAtCAT9 57\nTable 1 Similarity matrix for residues aligned to AtCAT4 residues F66-A72, P222-A233, I543,\nY546, L547, N550 (SLC7A4 residues: F75-A81, P231-A242, L555, C558, L559, K562) that\nwere identified to interact with cholesterol in PDB 9HJK using ChimeraX.\n- Page 8, \" In contrast, the ε-amino group on the L-Orn side chain interacts with Asp116 on\nTM3 via a salt bridge and to Asp243 on TM6b via a water-mediated hydrogen bond (W1) (Fig.\n1d and Extended Data Fig. 6a).\"\nThis reviewer is concerned that, at the achieved resolution, reliable placement of water\nmolecules may be challenging. Are the positions of the modeled water molecules supported\nby the MD simulations presented later in the manuscript? If not, please remove this statement\nsince not support by well defined, high-resolution density.\nWe thank the reviewer for raising this point. We agree that at the nominal and local resolution\nof the L-Orn map, explicit placement of individual water molecules is not sufficiently supported\n19\nby the density alone. In the revised model, we have therefore removed W1/W2 and deleted\nthe statement about a “water-mediated hydrogen bond” in the main text.\nAt the same time, our MD simulations consistently support the presence of a bridging water at\nthis position: in five independent 200-ns repeats, a single water molecule occupying the gap\nbetween the L-Orn ε-amino group and Asp116 is present for ~98% of the simulation time\n(Extended Data Fig. 9d-e), which is mechanistically reasonable given that the side chain is an\nAsp (rather than a longer Glu) and the ligand is ornithine (shorter than Lys/Arg). We now\nmention this as supportive mechanistic evidence only in the MD section, making clear that the\nwater is inferred from simulation rather than directly resolved in the updated cryo-EM map.\nAcross the five seeded simulation repeats, we consistently observe a water molecule\noccupying the gap between the L-Orn ε-amino group and Asp116, present for ~98% of the\ngross simulation time (Extended Data Fig. 9d-e). The presence of water in this position within\nthe binding site is mechanistically reasonable, especially given that the interacting AtCAT4\nside chain is an aspartate, which is shorter than glutamate, and the ligand is ornithine, which\nis shorter than either lysine or arginine. Thus, a water molecule can stabilise the bound L-Orn\nmolecule, as observed with the shorter aspartate side chain in AtCAT4. Collectively, the MD\ndata suggest a coordinated water network is likely to exist within the AtCAT4 binding site.\nHowever, due to the resolution of the cryo-EM dataset we obtained, we could not reliably\nmodel the water molecules into the structure. (lines 409-419)\n- Page 8, “The structure of SLC7A4 bound to L-Ornithine (L-Orn) exhibits…”\nI assume this structure corresponds to the sybody-bound form. Please clarify this point and\nrevise the text accordingly, as it is not clearly stated in the current version.\nWe have addressed this by changing the protein nomenclature.\n- Page 8, “…forming a short π-helix bulge…”\nThis is an interesting structural feature; however, Fig. 1c appears to show an elongated helical\nelement rather than a bulge. Please provide a more appropriate image to illustrate this feature\naccurately.\nWe have removed the word ‘bulge’ from the text.\n- Page 8, “…water-mediated hydrogen bond…”.\nThe obtained resolution (>3 Å) is generally insufficient to support such detailed structural\nconclusions. Please revise the statement accordingly.\nWe thank the reviewer for this point. Our original interpretation was guided by both extra\ndensity features near L-Orn and MD simulations, which consistently show long-lived water\nbridges between the L-Orn ε-amino group and nearby acidic residues, making a water-\nmediated interaction mechanistically plausible, especially for the shorter ligand L-Orn\n(compared to L-Lys and L-Arg). However, we agree that at the local resolution of the L-Orn\nsite (3.0 Å) these waters cannot be assigned with sufficient confidence from the cryo-EM map\nalone. In line with the reviewer’s recommendation, we have therefore removed explicit “water-\nmediated hydrogen bond” claims and the modelled waters from the EM description, and now\nonly discuss these bridging waters in the MD section as simulation-derived mechanistic\ninsight, not as directly resolved structural features. We provided the revised passages above.\n- Page 9, \"The binding pose we observe for L-Orn in SLC7A4 is also consistent with the pose\nwe reported previously for the more distantly related prokaryotic homologue, GkApcT (PDB\n5OQT), which also involves an interaction of the side chain guanidino group with an acidic\nside chain on TM337 (Extended Data Fig. 6c).\"\nbound to L-arginine. In addition, note that the PDB code differs from that provided in Extended\nData Fig. 6c and actually corresponds to the alanine-bound GkApcT (likely a typographical\nerror). Considering the major concern raised regarding the ligand cryo-EM density, the authors\nare kindly requested to reassess whether the available density sufficiently supports the\nstructural comparisons between the binding sites of SLC7A1 and GkApcT.\nWe have changed the description to the following to make this clear. “The binding pose we\nobserve for L-Orn in SLC7A4 is also consistent with the pose we reported previously for the\nmore distantly related prokaryotic homologue, GkApcT (PDB 6F34), which was captured\nbound to L-Arginine. In the GkApcT L-Arg bound structure we also observed an interaction of\nthe side chain guanidino group with Glu115 on TM33 (Extended Data Fig. 8c)”.\n- Page 11, \"Compared to the cryo-EM model, Ala44 is shifted by an additional ~1.7 Å over the\nspan of the MD repeats, further drawing the ligand backbone carboxyl into the fully accessible\nGAG backbone pocket.\" The MD simulations are presented as supporting evidence for the\nproposed induced-fit mechanism. However, this reviewer remains uncertain about the\ninterpretation of the events observed during the simulations. Specifically, the further unwinding\nof TM1, the entry and coordination of a water molecule and the “better accommodation” of the\nsubstrate. Why are these features not observed in the cryo-EM data and what is their\nsignificance in the context of the proposed mechanism? Please adapt text and provide\nadditional information and argumentation.\nWe thank the reviewer for this point. Our MD simulations were performed after embedding the\ncryo-EM starting model in an explicit lipid bilayer and solvent and removing the sybody and\ndetergent, so local relaxation and sampling of nearby minima is expected. The additional TM1\nunwinding, water entry/coordination, and the ~1.7 Å shift around Ala44 therefore represent\nMD-observed relaxation within the outward-open ensemble under a membrane environment,\nnot a separate structural state we claim is resolved by cryo-EM. At ~3.2–3.3 Å nominal\nresolution and with local heterogeneity, small-amplitude backbone adjustments and\ndynamic/partial-occupancy waters are expected to be averaged out and thus not appear as\ndistinct density features. These simulations used the widely applied AMBER ff99SB-ILDN\nprotein force field and the SLipids membrane force field, both of which have been extensively\nbenchmarked and used for membrane-protein dynamics and local conformational\ntransitions25,26.\n- Page 11, Figure 2, panels b-d: The extent of the unwinding motion around the GAG-motif is\na bit difficult to assess from the provided views of TM1 and TM6. Maybe superimposed\nstructures of a closer view around the binding pocket would be helpful to improve assessment.\nWe appreciate the reviewers’ comments regarding Fig. 2. However, the style we chose aligns\nwith previous representations of the SLC7 fold in the literature27, so we hope to retain it in the\nfinal version.\n- Pages 19-20: The description of the proposed transport model suffers from issues of\nsequencing and redundancy, which negatively affect readability and comprehension. The\ninduced-fit binding of L-leucine is described after the transition from the outward-open,\nsubstrate-free state to the outward-facing occluded, L-leucine-bound state (i.e., the transition\nfrom state i to ii), which disrupts the logical flow. Additionally, protonation of Glu125 is\nmentioned twice (passages 1 and 2) and could be streamlined. The hypothesized rotation of\nTM3 into the position observed in the AtCAT4 structure is also described somewhat differently\nthan on page 19. This reviewer therefore requests that this paragraph be restructured and\nimproved for greater clarity and consistency.\nin the “transport model” block immediately before Fig. 6 (lines 699-737).\n- Page 26, “Thermal stability measurements”. Please report on the final protein concentration\nand buffer constituents used for the assay/measurement.\nThe concentrations we reported in our original submission were actually the final protein\nconcentrations, but we have rephrased it in the Methods section to say “final concentrations\nof…” to make the final concentrations used in the assay clear.\n-Extended Data: The Extended Data section does not include representative micrographs, 2D\nclass averages or viewing direction (azimuthal angle) distribution plots. Please add these\nessential elements to provide a more complete overview of the cryo-EM data quality and\nprocessing.\nDone.\nReviewer 4.\nThe manuscript by Kolokouris et al. focusses on the transport mechanism of SLC7A4, an\namino acid transporter of the solute carrier protein family. Unlike homologous proteins some\nstructural and functional features are unique, which are shown by means of cryoEM structures,\nMD simulations, and pharmacological experiments. In particular two aspects are interesting\nand deserve publication. First the unique profile of transported amino acids (selective for\nleucine). And second, the pH sensitivity of the transporter. I want to state that I am not an\nexpert in the technical aspects of cryoEM, so I cannot fully judge on this particular part.\nGiven the interesting topic, the sound methodology used, and the way of presenting the\nresults, I would like to recommend publication of this manuscript in Nature Communications.\nHowever, some aspects have to be improved by the authors before publication.\nWe thank the reviewer for their positive assessment and recommendation.\n1) While the MD simulations have been carried out in a sound manner, I was confused\nby their description. E.g., I assume that the Table 2 is right, but in the methods section\nthe authors state they have simulated in triplicates rather than 5 independent 200 ns\nsimulations. It is also not clear from the text how many µs MDs have been carried out\nand from which of those replicas the clusters where selected. Please make the method\nsection consistent and describe in more details how the clustering and selection of the\nrepresentative frame was done.\nWe thank the reviewer for their comment. We have rephrased the Methods section on the MD\nsimulations we ran to align with the information presented in Extended Data Table 2. We also\nrephrased the relevant main text section to clearly state the purpose of each simulation and\nhow seeded runs were generated to allow multi-repeat fingerprint sampling.\n22\n2) As a minor point, the authors mix one-letter and three-letter code for amino acids.\nSince it makes sense for the figures to use one-letter code, please also apply this\nthroughout the manuscript.\nWe appreciate the reviewer’s perspective, but after discussion with colleagues, we believe\nthat using the three-letter code in the main text enhances readability. If the reviewer feels\nstrongly, we can revise the manuscript accordingly, but our preference is to retain the three-\nletter code in the main text and use the single-letter codes in the figures.\n3) I miss a detailed structural comparison with other SLCs/amino acid transporters. Since\nnew structures are reported in this manuscript, it would be nice to compare them with\nprevious structures and highlight the unique features in more detail.\nWe appreciate the reviewer’s comment and, in principle, agree. Indeed, we have included\nseveral sections in the paper that directly compare our AtCAT4 structure with closely related\nmembers of the SLC7 and APC family of transporters, as illustrated in Extended Data Figures\n4, 7, and 8. However, we feel that including any further comparisons could confuse the paper's\nnarrative. We are currently working on a review paper that places our work in the context of\nthe wider SLC7/APC family, which will hopefully address this point.\n4) The section on structural basis for leucine selectivity in Hs SLC7A4 is quite interesting but\nmisses a detailed discussion on the molecular level. The authors show the lipophilic residues\nthat are interacting with leucine’s side chain and then directly head to arginine. It would be\nbeneficial to discuss more closely related amino acids, e.g. valine, isoleucine. Why is the\nbinding site so prone to leucine?\nSeveral closely related α-amino acids can access the conserved SLC7 pocket and\ncompetitively inhibit leucine uptake, but our data indicate that transport is much more selective\nthan binding. In particular, although non-polar amino acids can compete in the assay context,\ndirect ³H-L-isoleucine uptake is indistinguishable from the transport-deficient mutant, and L-\nLeu shows markedly higher apparent affinity than L-Arg (IC₅₀ 24 ± 5 µM vs 680 ± 19 µM). This\npattern is consistent with a balanced requirement for side-chain fit that couples binding to the\nconformational activation step: very small side chains (e.g., Ala) may under-occupy the\nhydrophobic cavity and fail to stabilise the induced-fit network, whereas bulkier branched side\nchains (e.g., Ile) can still block access yet impose a packing mismatch that prevents\nprogression through the transport cycle. Structurally, the leucine side chain is accommodated\nby a hydrophobic pocket centred on Val249, Val332, Leu336, L394 and Tyr246 (the thin\nextracellular gate), providing a concrete basis for why leucine is uniquely positioned to support\ntransport rather than binding.\nWe added this clarification in the main text:\nThe hydrophobic pocket, V332/L336/L394, is tuned for a branched side chain of leucine,\nproviding a simple explanation for why closely related BCAAs can compete for access yet fail\nto show measurable uptake (e.g., isoleucine does not show detectable transport, (Fig. 3d-e),\nconsistent with a balanced requirement for side-chain fit that couples binding to the\nconformational activation step. (lines 555-560)\nReferences.\n23\n1. Majd, H. et al. Screening of candidate substrates and coupling ions of transporters\nby thermostability shift assays. Elife 7(2018).\n2. Parker, J.L. et al. Molecular basis for redox control by the human cystine/glutamate\nantiporter system xc(). Nat Commun 12, 7147 (2021).\n3. Jungnickel, K.E.J., Parker, J.L. & Newstead, S. Structural basis for amino acid\ntransport by the CAT family of SLC7 transporters. Nat Commun 9, 550 (2018).\n4. Gauthier-Coles, G. et al. Quantitative modelling of amino acid transport and\nhomeostasis in mammalian cells. Nat Commun 12, 5282 (2021).\n5. Beyer, S.R. et al. Identification of cysteine residues in human cationic amino acid\ntransporter hCAT-2A that are targets for inhibition by N-ethylmaleimide. J Biol\nChem 288, 30411-30419 (2013).\n6. Christensen, H.L. et al. The choroid plexus sodium-bicarbonate cotransporter\nNBCe2 regulates mouse cerebrospinal fluid pH. J Physiol 596, 4709-4728 (2018).\n7. Bernardino, R.L., Carrageta, D.F., Sousa, M., Alves, M.G. & Oliveira, P.F. pH and\nmale fertility: making sense on pH homeodynamics throughout the male\nreproductive tract. Cell Mol Life Sci 76, 3783-3800 (2019).\n8. Wang, Y. et al. Mechanisms of transport and analgesic compounds recognition by\nglycine transporter 2. Proc Natl Acad Sci U S A 122, e2506722122 (2025).\n9. Mostyn, S.N. et al. Identification of an allosteric binding site on the human glycine\ntransporter, GlyT2, for bioactive lipid analgesics. Elife 8(2019).\n10. Xia, L. et al. Structural insights into cationic amino acid transport and viral\nreceptor engagement by CAT1. Nat Commun (2025).\n11. Mingda, Y. et al. Amino acid and viral binding by the high-aeinity Cationic Amino\nacid Transporter 1 (CAT1) from Mus musculus. Research Square (2024).\n12. Wiedmer, T. et al. Accelerating SLC Transporter Research: Streamlining\nKnowledge and Validated Tools. Clin Pharmacol Ther 112, 439-442 (2022).\n13. Goldmann, U. et al. Data- and knowledge-derived functional landscape of human\nsolute carriers. Mol Syst Biol 21, 599-631 (2025).\n14. Jansson, T. Amino acid transporters in the human placenta. Pediatr Res 49, 141-7\n(2001).\n15. Lobel, M. et al. 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Membranes (Basel) 11(2021).\n25"}, {"round": 2, "reviewer_comments": {"reviewer_1": "Authors addressed all my concerns\nThen, manu script Is suitable for pubblication", "reviewer_2": "The authors have addressed all concerns raised by this assessor.", "reviewer_3": "The corrected manuscript version of Kolokouris et al. reads substantially more clearly, and the authors have addressed the points raised by the reviewer. The abstract now more accurately reflects the scope of the work. The implementation of the suggested protein nomenclature enhances readability, and section transitions were refined through targeted edits while the overall structure was retained. The discussion has been clarified, with previously noted issues in logical flow largely resolved, particularly with respect to the proposed transport model.\nGeneral concerns regarding the rationale of the work remain. Nevertheless, the authors now provide a clearer and more consistent argument for the relevance of the AtCAT4 structure in the context of residue-level analyses of SLC7A4, which is sufficient to justify the approach taken.\nTo assess whether the limited quality of the ligand density might represent an artefact, the authors performed the suggested negative control experiment for ligand-density selection. This analysis supports the modelling of L-ornithine. Furthermore, the additional functional data on SLC7A4 support pH-dependent regulation of transport activity; however, the proposed proton-sensing model remains speculative and will require further validation beyond the present study.\nOverall, while the manuscript does not fully overcome its intrinsic limitations, the authors have adequately addressed the reviewer’s concerns, and the study is suitable for publication in its current form. Minor improvements to the presentation, such as providing better-resolved images in Extended Data Fig. 2c and Extended Data Fig. 3 and clarifying the description of the particle stacks used for the second refinement round in the Methods and Extended Data Fig. 2b, would further improve clarity.", "reviewer_4": "The authors have revised the manuscript and adressed all points raised during review.\nWhile I still belive that a more detailed structural comparison of the new cryoEM structure with previous ones or closely related transporters would strenghten the manuscript, it dosn't represent a point that should hinder publication of this manuscript. I also understand the rationale of using three-letter code in the text and one-letter code in the figures."}, "author_response": ""}]

Decision letter