Structure of a pH-sensitive pentameric ligand-gated ion channel from the Sarcoptes scabies mite

Domain: biology
Published: 2026-03-13
Editorial outcome: major_revision

Abstract
Scabies is a skin infestation caused by the mite Sarcoptes scabiei and
represents a substantial global health burden exacerbated by emerging resistance to
ivermectin. An anionic pentameric ligand-gated ion channel from the mite, SsCl, shows
pH-sensitivity and is significantly modulated by ivermectin. Here, we use cryo-EM and
electrophysiology to explore the pH-sensing mechanisms of SsCl, and the impact of
ivermectin on channel activity. Structures of SsCl were resolved in closed (pH 6.5) and
desensitized (pH 9) states, alongside ivermectin-bound conformations. The
desensitized structure adopts an unexpected hourglass conformation, suggesting gating
mechanism closer related to cation-selective channels. Structural analysis and
mutagenesis identify extracellular histidine and glutamic acid residues that impact the
pH-sensitivity, likely contributing to a broader pH-sensing network. Ivermectin-bound
structures reveal pH-dependent modulation, enhancing open-state prevalence at pH 9
and enabling atypical activation at pH 6.5. These findings offer initial insights into SsCl’s
pH-sensitivity and ivermectin’s activity, informing next-generation antiparasitic design.

Introduction
pH-sensitive chloride channels (pHCls) are unique members of the pentameric
ligand-gated ion channel (pLGIC) family (for review, see1), which are primarily found in
invertebrates like insects2 and arachnids3. These channels are specifically activated by
changes in pH, which occur during metabolic shifts or stress responses4–6. When
activated by alkaline pH, they allow the passage of chloride ions through the cell
membrane, which helps regulate cellular homeostasis, maintain ionic balance, and
mediate signal transduction4,5,7. Unlike traditional ligand-gated receptors, which have
well-characterized binding cavities, the agonist-like region involved in the pH-sensing
and its associated gating mechanisms are not well known. Further research on pHCl
channels would not only contribute to our understanding of ion channel physiology but
also holds promise for the development of targeted treatments against parasitic
infections and agricultural pests, due to their selective expression in invertebrates8.
One of the most medically relevant parasitic infestations is scabies, a highly
contagious ectoparasitic skin condition caused by Sarcoptes scabiei (itch mite)9 . This
tiny mite penetrates the upper layer of the skin, where it lays eggs and induces an
immune response that leads to intense itching, inflammation, and characteristic skin
rashes. The infestation often causes severe discomfort and can lead to secondary
complications, such as impetigo, rheumatic fever, and chronic kidney diseases10,11, if left
untreated. Scabies is estimated to affect 200-300 million people worldwide, particularly
in impoverished communities or crowded environments, such as nursing homes,
schools, and dormitories9,12. The World Health Organization has therefore highlighted
scabies as a disease of public importance and lists it as a neglected tropical
disease13,14.
The standard treatment for scabies involves topical medications, such as
permethrin cream, or oral medications like Ivermectin (IVM)15. IVM is a broad-spectrum
antiparasitic medication originally developed in the late 1970s16,17. Due to its high
efficacy and low toxicity, it has since become a cornerstone in the treatment of parasitic
conditions in both humans and animals, and was recognized with the 2015 Nobel Prize
in Physiology or Medicine18. Its use in mass drug administration campaigns has
significantly reduced the prevalence of parasitic diseases and improved public health in
endemic regions19. However, the emergence of drug resistance in some parasitic
populations20 highlights the need for ongoing research into the activity of IVM at
pharmacologically relevant targets, while stimulating the development of new
treatments.
IVM binds to chloride channels in the nerve and muscle cells of parasites,
causing paralysis and death of the parasite while having minimal effects on human
cells21. Its activity was originally characterized using the invertebrate glutamate-gated
chloride channel GluCl22, but has since been shown to act on other pLGICs, including
GABA receptors23, glycine receptors24, and insect pHCl channels25. However, its exact
mechanism of action in Sarcoptes scabiei remains unknown.
One likely target is a pHCl channel identified in Sarcoptes scabiei, SsCl. This
channel is closely related to various glycine and pHCl channels from insects
(Supplementary Fig. 1 and 2). In particular, SecCl channels, which were originally
identified in Drosophila and have been shown to mediate hormone-induced fluid
secretion25. SsCl is activated by alkaline environments and modulated by IVM, which
acts slowly and pseudo-irreversibly, even at acidic pHs when the channel is closed2,3,7.
However, its functional role in Sarcoptes scabiei and how these mechanisms occur
remain unknown. SsCl presents an interesting target for future scabies treatments, and
an opportunity to explore the poorly understood mechanisms of pHCl channels.
In this study, we employ a combination of structural and functional methods to
characterize the molecular mechanism of the pH-sensitive SsCl channel and its
modulation by IVM. Using single-particle cryo-electron microscopy (cryo-EM), we
determine structures of the receptor in closed, desensitized, and open conformations
bound to IVM. Our findings reveal that SsCl adopts the classical architectural fold for a
pLGIC; however, its desensitization mechanisms surprisingly resemble cationic
channels. Structural analysis identifies possible residues that contribute to the pH-
sensing mechanism of SsCl, which are functionally explored using site-directed
mutagenesis and electrophysiology. Based on this analysis, a site that we term the
binding-like region is interpreted to represent an agonist-like functional region that may
form part of a broader network of residues collectively sensing changes in pH and
driving associated conformational transitions. This region does not correspond exactly
to the traditional orthosteric binding site of other pLGICs26, but is instead located in a
proximal area of the extracellular domain known to bind cations in other channels27.

Results
Structure determination
The pH-sensitive chloride channel identified in the mite Sarcoptes scabiei
(SsCl)3, was engineered to facilitate structural studies. The entire intracellular loop was
truncated (131 residues) and replaced with a SQPARAA linker from the prokaryote
homologue GLIC, which is the most well-characterised proton-sensitive
pLGIC28,29 (Supplementary Fig. 1 and 3). This construct is termed SsCl . An N-
terminal eGFP fusion variant was also employed to screen for expression and
solubilization conditions, by using fluorescence-detection size-exclusion
chromatography (FSEC)30. This identified n-undecyl-β-D-maltoside (UDM) as the
optimal detergent for solubilization (Supplementary Fig. 4).
Functional assays using two-electrode voltage clamp (TEVC) electrophysiology
(see methods) confirm that SsCl is activated by alkaline pH. Experiments were also
conducted using SsCl
EM
and produced similar results (Supplementary Fig. 5).
Therefore, SsCl was used as the background construct for all additional experiments.
SsCl is activated by alkaline pH in a concentration-dependent manner, remaining
closed at pH 6.5 with a half-maximal activation (pH ) at pH 8.5, similar to previous
50
studies3.
To capture different functional states of SsCl, pH 6.5 and pH 9 were selected for
structural analysis based on its pH-dependent activation profile. In this study, SsCl
structures in four distinct states were determined by cryo-EM (Supplementary Fig. 6,
Supplementary Table 1): (1) SsCl pH 6.5, (2) SsCl pH 9, (3) SsCl pH 6.5 IVM, and (4)
SsCl pH 9 IVM; the latter two resolved in the presence of the allosteric agonist
ivermectin (IVM) (Figure 1). The estimated resolutions for these structures are 4.2 Å, 3.1
Å, 3.1 Å, and 3.6 Å, respectively (Supplementary Fig. 7). Cryo-EM density maps were
used for interactive model building of a single subunit for each structure. Since SsCl
assembles as a homopentamer, an initial subunit was built and refined before applying
symmetry to reconstruct the complete pentameric structure. Additional model-building
and refinement steps were then performed on the assembled pentamer to further
improve structural accuracy and consistency. Despite the lower resolution of the cryo-
EM map for SsCl pH 6.5, all four maps allowed nearly the entire protein to be built for
each structure, except for a few residues at the N-terminus and/or in the M3-M4 loop
(Supplementary Fig. 8, 9). Notably, the TMD of SsCl pH 6.5 shows limited resolution,
making detailed side-chain interpretation difficult and warranting careful consideration
when analysing this region (Supplementary Fig. 8a).
Additionally, in the SsCl structures at pH 9, pH-dependent conformational
changes cause the M4 helix to shift closer to the detergent micelle, compromising the
resolution in this region. The M4 helices could therefore not be resolved in the pH 9
structures; however, their presence is still visible in the density maps (Supplementary
Fig. 10). In general, the M4 helices are flexible and highly exposed to the detergent
micelle, leading to lower-resolution densities for this region. Despite this, the M4 helices
were built for structures at pH 6.5 (Supplementary Fig. 8a, b). For all structural
analyses, the unsharpened cryo-EM raw density maps were examined to minimize bias.
Architecture of the SsCl channel
As observed for all members of the pLGIC family, SsCl forms a cylindrical-
shaped receptor composed of five subunits that form a homopentamer. The symmetrical
arrangement of subunits creates a central ion-conducting pore, essential for the
channel’s function. Each subunit features a large N-terminus that adopts a twisted β-
sandwich structure (β1-β10), constituting the extracellular domain (ECD). A conserved
disulfide bond between the β6 and β7 strands, a signature of the Cys-loop receptor
family31, stabilizes the β-sandwich and aids the overall stability and function of the
channel. An additional disulfide bond is also present at the top of the channel, within the
first β-sheet. The transmembrane domain (TMD), following the ECD, consists of four α-
helical segments (M1–M4) interconnected by loops. The M2 helices line the channel
pore and are directly involved in ion conduction and the channel's gating (Figure 1a,
Supplementary Fig. 11).
In pLGICs, three structural regions coordinate channel activation: (1) the binding
pocket within the ECD: including loop C, β-strands of the complementary subunit and
loop F; (2) the coupling region at the ECD-TMD interface, including the Cys-loop, pre-
M1 segment and M2-M3 linker; and (3) the gating region within the TMD, involving the
M2 helices (Supplementary Fig. 11). Typically, agonist binding at the orthosteric binding
pocket generates structural changes which induces closure of loop C. This initiates a
cascade that transmits through the coupling region to the TMD, where rearrangement of
the pore-lining helices ultimately leads to channel opening (for review, see 32).
SsCl stands apart from conventional receptors as it lacks a classical small-
molecule agonist. Instead, its activation is governed by changes in pH. This raises a
fundamental question: how do shifts in proton concentration translate into
conformational changes that activate the receptor?
SsCl undergoes significant conformational rearrangements in response to
different protonation states. Comparisons between the structures obtained at pH 6.5
and pH 9 reveal structural differences within or surrounding loop C, suggesting that this
region remains important for the activation mechanisms of the channel (Supplementary
Fig. 12). Residues in SsCl likely participating in pH-sensing have also been identified
within the ECD, as described below.
SsCl also features an allosteric binding site for IVM, which closely resembles the
IVM-binding site originally identified in the Caenorhabditis elegans glutamate-gated
chloride channel (GluCl)22, indicating a conserved binding mechanism33 (Supplementary
Fig. 13).
Allosteric activation by IVM and its dependency on pH
IVM is a semi-synthetic compound originating from the discovery of avermectins,
a group of natural macrocyclic lactones produced by the bacterium Streptomyces
avermitilis with potent nematicidal activity 34. IVM has been shown to modulate a variety
of Cys-loop receptors, acting as a potent allosteric agonist and modulator depending on
the specific receptor and context22,33,35–37
The SsCl construct used for structural analyses (Supplementary Fig. 3) was
expressed in Xenopus laevis oocytes and functionally characterized using TEVC. IVM
was shown to activate the channel at pH 6.5 and produce positive modulation at pH 9,
though with notable differences. At pH 6.5, where the channel remains closed, IVM acts
as an allosteric agonist and produces a very slow activation of the channel, consistent
with previous literature3. In contrast, co-application of IVM with pH 9 elicits a robust and
rapid current that reaches 448% of the current induced by pH 9 alone, thus significantly
enhancing channel opening under alkaline conditions (Figure 2). There is an additional
rebound current that occurs upon the return to pH 5.35 that is greater than the co-
application of both agonists. This rebound reaches 711% of the current induced at pH 9
alone (Figure 2). IVM is known to act pseudo-irreversibly at pLGICs, and thus, when pH
5.35 is restored, IVM is likely to stay bound for an extended period. This rebound
current may be due to IVM transiently stabilising an exaggerated open state that arises
following the removal of activating pH.
SsCl structures at both pH 6.5 and 9 reveal IVM binding at the subunit interface
in the upper TMD. It occupies a pocket formed by M2 and M3 of a principal subunit (+)
and M1 of a complementary subunit (-) (Figure 3a). This binding mode closely
resembles that observed in the GluCl channel22 (Supplementary Fig. 13), glycine
receptors36–39 and 7 nAChR35, suggesting a conserved binding mechanism across
Cys-loop receptors22,33.
The IVM binding pocket is primarily comprised of hydrophobic residues, which
interact with IVM through van der Waals forces. Two key conserved residues, a
hydrophobic L218 and a polar uncharged S260, known for their role in IVM binding in
GluCl22, are also present in SsCl and contribute to IVM binding and stabilization. L218
contributes with its backbone forming a hydrogen bond with O(13) of the benzofuran
moiety of IVM, while its side chain engages in van der Waals interactions with C37, near
the benzofuran (Figure 3b-f, Supplementary Fig.14). In GluCl, a third conserved
residue, T285, forms a hydrogen bond with the spiroketal group of IVM22. However,
SsCl has a valine (V285) at this position, which engages in a van der Waals interaction
with C7 of the spiroketal (Figure 3b-f).
Interestingly, a lysine residue (K264) located near the IVM binding pocket alters
orientation significantly with pH. At pH 9, K264 orients toward the pocket and likely
forms a hydrogen bond with atom O(9) of IVM’s cyclic ether moiety. This interaction
draws the IVM’s cyclohexene ring closer to S260, enabling it to form a hydrogen bond
with atom O(10) of the cyclohexene. At pH 6.5, K264 adopts an opposing orientation
and no longer interacts with IVM. This causes S260 to instead interact with O(9) rather
than O(10). These pH-dependent conformational changes result in a stronger
interaction between S260 and IVM at pH 9 (1.93 Å) compared to pH 6.5 (2.61 Å) (Figure
3d, e, g, Supplementary Fig. 15). This may contribute to the increased efficacy of IVM
under alkaline conditions (Figure 2). Moreover, the IVM binding pocket becomes more
electronegative under alkaline conditions, specifically in the deepest cavity where the
cyclohexene and cyclic ether interact (Supplementary Fig. 16). This may also contribute
to the pH-dependent effects of IVM.
Ion-conducting pathway and selectivity
SsCl features a central ion-conducting pathway along its five-fold symmetric axis
lined by the M2 helical segments from each subunit. Changes in pH and IVM binding
both significantly impact the overall conformation of the pore, leading to distinct ion
conduction behaviours (Figure 4, Supplementary Fig. 17).
At pH 6.5, the channel adopts an hourglass conformation, with the narrowest
constriction occurring in the center of the TMD near position 9’ (L254), with a pore
radius of 1.9 Å (Figure 4a, b, f). As a chloride ion has a Pauling radius of 1.8 Å and a
radius of 3.2 Å when fully solvated40, a pore radius of this size is insufficient for chloride
permeation. Accordingly, we assign this structure to the closed state. Importantly, the
pore region of this structure was interpreted with caution due to limited detail at 4 Å
global resolution, with the local resolution of the TMD region, including the M2 helices,
being lower, around 5 Å (Supplementary Fig. 7a). As a result, side-chain placements in
this region could not be confidently assigned, and both raw and sharpened maps were
considered to guide careful interpretation of pore radius.
At pH 9, the narrowest constriction point remains at position 9’ but increases
slightly to 2 Å (Figure 4a, c, g), also insufficient for ion permeation. Given that the
channel is functionally active at pH 9 (Supplementary Fig. 5), yet the structure exhibits a
constricted pore, this conformation likely represents a desensitized state resulting from
prolonged exposure (>1 day) to activating pH during purification.
When the desensitized structure is viewed from the extracellular side, the M2
helices exhibit a rotational movement relative to the closed state: L254 (9′) rotates
clockwise, while P243 (–2′) rotates counterclockwise. This local rotation causes an
‘unwinding’ effect at P243, producing the widest pore radius (5.8 Å) observed among all
SsCl conformational states (Supplementary Movie 1). Despite this localized movement,
the M2 helices largely remain in place, showing minimal translational displacement.
Interestingly, the ECD, M1, and M3 helices undergo a concerted compression resulting
in a global compaction of the channel that is distinct to the desensitized state
(Supplementary Movie 2, Supplementary Fig. 17).
Strikingly, the desensitization mechanism in SsCl differs from the canonical
behaviour reported for other anionic Cys-loop receptors41,42. These receptors typically
display a V-shaped TMD pore, with a bottom-up constriction-to-expansion profile. In
contrast, SsCl at pH 9 adopts an hourglass shape, with its narrowest constriction at the
midpoint of the TMD (9’) and expanding toward both the ECD and the bottom of the
TMD, resembling the closed state (Figure 4b, c). A similar conformation was recently
reported for the desensitized state of 7 nAChR, in which the desensitization gate
occurs at position 9' 35,43. These findings suggest the desensitized conformation of SsCl
closely resembles that of the cationic 7 nAChR, rather than the desensitized
conformations reported for other chloride channels.
The impact of IVM on the pore was also examined and was found to significantly
increase the overall pore radius at both pHs. This is due to the intercalation of IVM
between adjacent M1 (-) and M3 (+) subunits that causes a physical separation of the
TMD. Comparing the two structures at pH 6.5, the pore radius at position 9’ increases
markedly from 1.9 Å to 5.6 Å in the presence of IVM (Figure 4a, b, d, f, h), which is
sufficient to accommodate chloride ions. In the presence of IVM, the channel exhibits its
narrowest constriction at the bottom of the pore, specifically at the selectivity filter at
P243 (–2’), where the radius narrows to 2.6 Å (Figure 4a, d). Although this is below the
radius typically required for a fully solvated chloride ion, we hypothesize that the positive
electrostatic potential from the M2 helix dipole may reduce the energy barrier at this
site, thereby allowing limited ion permeation. A similar constriction is observed in GlyR
structures resolved in complex with glycine and IVM, where the narrowest pore radius
also occurs at position –2’. The authors suggest these structures represent intermediate
states between open and desensitized conformations38. Moreover, the functional data
show that SsCl activation by IVM at pH 6.5 is modest and especially slow (Figure 2).
This can likely be attributed to the pore architecture in this state, characterized by a
constricted lower region alongside an unusually wide upper pore. Such a configuration
may hinder optimal chloride ion stabilization and coordination throughout permeation.
Additional comparisons between the IVM-bound structures reveal that the pore
expansion at position 9’ is more moderate at pH 9, where the radius only reaches 3.8 Å,
1.8 Å smaller than at pH 6.5 with IVM. Differences are also observed at position –2′. At
pH 9 with IVM, position –2′ exhibits a wider pore radius of 4.1 Å, sufficient for chloride
ion permeation. Interestingly, the narrowest constriction shifts upward, occurring at
position 2′ (T247) with a radius of 2.7 Å. This shift may contribute to stabilizing and
coordinating chloride ions to facilitate ion permeation (Figure 4a, d, e, h, i), which is
consistent with functional data showing that IVM more effectively activates the channel
at alkaline pH. Taking these observations together, we hypothesized that the mode of
IVM action is influenced by pH-dependent conformational changes in SsCl, which in
turn affect the architecture and dynamics of the pore. The structural variability aligns
with functional data, indicating that IVM, in combination with pH 9, results in more
efficient channel opening compared to pH 6.5 (Figure 2).
To better understand the structural basis for gating behaviour, the conformational
changes at position 9' were examined across all structures. Position 9' has long been
recognized as a critical determinant in pore gating. In an early 1995 study on the 7
nAChR, the leucines at 9’ were highlighted as key gate-forming residues and named the
leucine-ring. The author proposed that bending of the M2 helices toward the central axis
of the pore orients the leucines inward, forming a hydrophobic constriction that occludes
ion conduction44. Recent studies have further reinforced these findings43,45. A similar
mechanism is observed in SsCl: At pH 6.5 the L254 side chain faces the channel pore,
and upon channel opening with IVM, L254 rotates clockwise (extracellular view) to the
side away from the pore axis, relieving the hydrophobic barrier and permitting ion flow
(Figure 4 f, h, I, Supplementary Fig. 18). Interestingly, in the desensitized state, this
position resembles that of the closed state. L254 orients toward the pore, though slightly
less pronounced, restoring the hydrophobic gate (Figure 4g, Supplementary Fig. 18).
SsCl contains the proline-alanine-arginine motif, a highly conserved feature of
the Cys-loop receptor family that plays a key role in the anion selectivity filter46.
Typically, Pro and Ala residues located at the bottom of the TMD pore are crucial for
anion selectivity as described in the literature22,46. In SsCl, these residues correspond to
P243 (-2’) and A244 (-1’) (Figure 4b-e).
Inspection of the cryo-EM map of SsCl at pH 9 with IVM revealed a density
consistent with a chloride ion within the selectivity filter, near T251 (6′) and above T247
(2′). The distances between the fitted ion and surrounding residues suggest an
interaction with the hydroxyl oxygen of T251’s side chain (Supplementary Fig. 19). This,
together with the relatively constricted pore in this region, may be crucial in coordinating
the ion as it moves through the channel. In GluCl, a density corresponding to the
chloride ion was also found near the same position (6’) with similar distances as in
SsCl22.
To further investigate the selectivity of the SsCl channel for chloride ions, the
continuum electrostatic potential was analysed using the APBS. Importantly, due to
resolution limitations, ions were not built into the structures. Nonetheless, the ionic
environment was included in the calculations (see Method). These calculations were
performed for the SsCl structures at pH 9, at the pH at which the structure was
determined. Following prolonged exposure to alkaline conditions (pH 9), the pore
adopts a desensitized state with a constriction at position 9’. This is accompanied by a
shift in its electrostatic potential where the pore becomes almost entirely electronegative
(Supplementary Fig. 20a). This creates an unfavourable environment for chloride ion
permeation, further supporting the assignment of the pH 9 structure to a desensitized
state.
Unexpectedly, in the pH 9 IVM-bound structure, the entire ECD and the upper
regions of the TMD exhibit a strong electronegative potential, which would be expected
to repel anions and attract cations (Supplementary Fig. 20b,d). Nonetheless, chloride
conduction is facilitated by the local pore geometry, the presence of water molecules,
and screening by counterions, which together modulate the effective electrostatic
potential along the conduction pathway. From this perspective, the more expanded ECD
in this structure, combined with its negative electrostatic surface potential, may help
organize chloride ions at the vestibule and regulate their flow into the pore. Among the
pore-lining residues within the TMD, only one positively charged residue, K261 (16’),
is present (Figure 4b-e). Beyond K261, the electrostatic potential shifts to a more neutral
state and becomes increasingly electropositive from T258 (13’) downward. The
electropositive potential in the lower TMD arises from the dipole moment of the M2 -
helices that line the pore47,48, as the majority of pore-lining residues are polar but not
charged (Supplementary Fig. 20b).
Taken together, these analyses allow us to define four distinct conformational
states of the SsCl channel structures here determined: (1) a closed state at pH 6.5, (2)
a desensitized state at pH 9, (3) a partially open state at pH 6.5 in the presence of IVM,
and (4) an open state at pH 9 with IVM.
Structural basis for pH-sensing and channel activation
To investigate the pH-sensing mechanisms of SsCl and to identify possible
residues participating in channel gating, we combined an initial PROPKA49-based
screening of titratable residues with detailed structural analysis and direct comparisons
between the two pH states (see Method). A cluster of residues within and near the
binding-like region, which is a functionally important site in other Cys-loop receptors,
was identified for further experimental investigation.
The candidate residues cluster predominantly within the β7, β9, and β10 strands,
forming the binding-like region. This site is characterized by a central, linear
arrangement of three histidine residues H206 (β10), H208 (β10) and H187 (β9), flanked
by two glutamic acids E146 (β7) and E142 (β7) and surrounding polar residues which
may further support local proton exchange dynamics (Figure 5a, b, Supplementary Fig.
21, Supplementary Table 2). In this region, a conserved histidine analogous to H208 in
SsCl, has also been shown to coordinate zinc binding in glycine receptors which
produces positive modulation of the channel27,50.
In SsCl, H206 (β10) and E146 (β7) are predicted to be central and key residues
within the binding-like region. They form an ionic interaction that is sensitive to pH-
dependent protonation states. At acidic conditions (pH 6.5), H206 is protonated,
allowing it to form an ionic bond with the negatively charged E146. At alkaline pHs (pH
9), H206 becomes deprotonated and electrically neutral, disrupting this electrostatic
interaction. This transition likely weakens the structural coupling between β10 and β7,
increasing the flexibility of the β7 strand, which contains the conserved Cys-loop
disulfide bond. At alkaline pH, H206 and E146 may still interact via van der Waals forces
and contribute to the overall structure; however, these interactions are considerably
weaker than the original ionic bond (Figure 5b).
Beyond this central interaction, other residues within the binding-like region,
including H208 (β10), H187 (β9), and E142 (β7), are also affected by pH changes
through deprotonation and/or altered hydrogen bonding and may play a supportive role.
Hydroxyl-containing side chains, such as those of S185 (β9) and T144 (β7), may further
help to the local hydrogen-bonding network, also influencing the overall dynamics under
different pH conditions (Figure 5a, b).
Disruption or weakening of interactions within the binding-like region, particularly
those located at β10 and β7, induces a local clockwise twist at the end of β7 that
propagates to the ECD–TMD interface (coupling region) (Supplementary Movie 3).
This
displaces the Cys-loop, which impacts interactions between aromatic residues that
appear to be important for conformational rearrangements. For instance, a –
interaction between F140 on the Cys-loop and F213 on the M1 helix transitions from T-
shaped in the closed structure to a more parallel, off-centered stacking geometry,
observed in the opened structure51 (Figure 5c). This rearrangement increases the
overlap between their -electron clouds, potentially introducing repulsive forces, which
consequently drives a clockwise rotation (extracellular view) of the upper M1 helix.
This
motion is coupled to the adjacent M2 helix (gating region), which undergoes a gear-like
rotation. The upper segment containing position 9’ rotates clockwise while the lower
segment rotates counterclockwise (extracellular view) (Figure 5d, Supplementary Movie
4). In the structures determined with IVM, the entire TMD undergoes an additional rigid-
body clockwise rotation (extracellular view) (Supplementary Movie 5). We propose that
these coordinated helical and domain-level motions collectively drive pore expansion,
ultimately facilitating channel opening.
Interestingly, the β7 twist occurs not only in structures at pH 9, but also at pH 6.5
when IVM is bound (Supplementary Movie 6). This suggests that the β7 twist is
necessary for channel opening, even under acidic conditions where the H206–E146
ionic bond is present. IVM may physically enforce the β7 twist, overcoming the bonds'
stabilizing effect and contributing to the slower, less efficient channel activation.
This
contrasts with channel activation at pH 9, where the H206–E146 bond is disrupted, and
channel activation is more efficient (Figure 2). We therefore hypothesize that pH-
sensing and the associated conformational changes in the presence of IVM exert a
modulatory effect on channel gating, tuning its efficiency rather than acting as a strict
binary (on/off) agonist-like mechanism. IVM acts as an allosteric agonist, with its
efficacy modulated by the pH-dependent conformational landscape of the channel.
Site-directed mutagenesis was performed to assess the functional contribution of
these residues to the channel gating. TEVC recordings reveal that H206 and E146
exhibit significantly elevated pH
50
values compared to WT when mutated to alanine.
Interestingly, mutation of H187 and H208, which are predicted to provide a supporting
role in the pH-sensor region, show reduced pH values; however, these did not reach
50
significance (Figure 6, Supplementary Fig. 22). To further explore the importance of the
histidine residues for pH-sensing, double-mutations at positions H206 and H187 were
examined. When mutated to alanine (H206A/H187A), the channel retains pH-sensitivity;
however, the concentration-response curve is greatly impacted due to a reduction in Hill
slope value. Interestingly, mutating both positions to cysteine abolishes pH-sensitivity
but retains significant currents in response to IVM, including the observed rebound
current (Figure 6d-f, Supplementary Fig. 22). This highlights the possible importance of
these residues for pH-sensing and suggests that the flexibility of the β-strands could
contribute to the mechanistic cascade.
Whether this series of protonation-dependent rearrangements represents the
primary mechanism for pH-sensing and channel activation remains an open and
intriguing question. Whilst the structural and functional data suggest H206 and E146
play a role in pH-sensing, these residues likely act in concert with other modulatory
elements to form a broader pH-sensing network, inviting further structural and functional
exploration of the binding-like region, and other sites throughout the structure. Notably,
these residues are not well conserved across pLGIC and related pH-sensitive channels
(Supplementary Fig. 1). Sequence alignment revealed that H206 in β10 of SsCl is
occupied by polar, uncharged residues in SecCl, GluCl, GLIC, and GABA receptors. By
contrast, in insect pHCl, human GlyR52, and the prokaryotic channel sTeLIC53,54, each
known to be pH-sensitive, this site is substituted by charged residues. The E146 in β7 of
SsCl is not conserved among these channels, but rather predominantly polar,
uncharged residues or proline, except for GLIC, which contains a histidine at this
position that is believed not to be implicated in pH sensing 55. In sTeLIC, the equivalent
position is occupied by a phenylalanine (Supplementary Fig.1).
Extending our observations on channel activation and functioning,
electrophysiological recordings showed that SsCl activity is modulated by extracellular
divalent cations. Both Zn²⁺ and Ca²⁺ inhibit currents evoked under alkaline conditions
(pH 9) in a concentration-dependent manner, with calcium producing the stronger
inhibition (Supplementary Fig. 23). Thus, while alkaline pH serves as the principal
gating stimulus, SsCl function is subject to additional regulation by divalent ions. This
interpretation is consistent with previous work reporting no agonistic effect of Zn²⁺ on
SsCl3. In addition, in GlyR, Zn²⁺ coordinates, among other residues, with a histidine and
a threonine at positions equivalent to H208 and T144 in SsCl. Notably, the histidine
equivalent to H208 in GlyR directly interacts with Zn²⁺, suggesting that this site may
represent a conserved spot for zinc binding52.
In addition to the binding-like region, other structural changes were observed,
particularly within the ECD. Comparison of all SsCl structures reveals a significant
conformational shift involving β10 (near loop C) of the primary subunit and β6 of the
complementary subunit. At the intersubunit interface, the residues E198 (β10) and R122
(β6) form an ionic interaction in the partially opened, opened, and desensitized states,
which is absent in the closed state. This interaction may be important for the movement
of loop C and ultimately channel opening. In addition, E155 in the β7–β8 loop bends
toward loop C in the partially open, open, and desensitized states (Figure 5e,
Supplementary Fig. 24, 25). Alanine substitution of R122 was shown to significantly
increase the pH , supporting its contribution to ECD movements and channel opening
50
(Figure 6). The complementary E155A mutation was conversely found to reduce the
pH .
50
Similar movements in loop C have been reported for multiple Cys-loop receptors
and linked to channel activation32,43. Loop C typically adopts an outward-facing
conformation in the closed state and moves inward to cap the canonical binding site
upon agonist binding, or in the case of SsCl, in response to pH changes
(Supplementary Fig. 26). In SsCl, the ECD also adopts an overall more compact
arrangement in the partially open, open, and desensitized states compared to the
closed state (Supplementary Movie 7).
Below loop C, an additional hydrophobic interaction is observed between M194
from loop C and M169 from loop F of the complementary subunit. This interaction
appears to stabilize the ECD at acidic pH, as it is present only in the structures at pH
6.5. At pH 9, these residues are positioned farther apart, suggesting that the pH-induced
conformational changes disrupt this interaction (Figure 5f, Supplementary Fig. 24).
Furthermore, Loop F exhibits pronounced movement in the partially open and open
states, but not in the desensitized state. Specifically, R171 within loop F moves inward,
towards the traditional orthosteric binding-pocket (Supplementary Movie 8). Loop F is a
critical component of the ligand-binding region, contributing to the complementary face
of the orthosteric site in Cys-loop receptors.
The structural observations and functional results outlined above provide initial
insight into the distinct pH-sensing and gating mechanisms of SsCl. Collectively, these
results highlight a cluster of histidine and glutamic acid residues within the binding-like
region of the ECD that influence pH sensing and are predicted to form an important
component involved in responding to pH changes. pH-induced activation is also
associated with conformational changes throughout the ECD, including loop C and loop
F, which are known to contribute to ligand binding and channel gating across pLGICs.
Moreover, the binding-like region is likely part of a broader pH-sensing network
distributed throughout the channel. To fully understand the complexity of pH sensing
and the mechanism of pH-dependent channel activation, additional studies exploring
other regions of the channel will be required.
In summary, SsCl is an atypical member of the pLGIC family. It is an anionic
chloride-channel activated by alkaline pH in a concentration-dependent manner. SsCl
only shares a low sequence conservation with its nearest relatives, such as insect
pHCls and the invertebrate GluCl. Despite this, it adopts an architectural fold that is
typical for the pLGIC family and shares some similar gating mechanisms, including a
pore constriction at the 9’ position in the closed state. An important feature of SsCl is the
predicted pH-sensing residues within the binding-like region, where non-conserved
histidine and glutamic acid residues contribute to pH-dependent channel activation. This
region is likely part of a broader pH-sensing network that requires further investigation.
IVM can also activate the channel by binding within the TM domains in a similar binding
mode to the one observed in GluCl, indicating a common mechanism of ligand
recognition. Structurally, IVM greatly widens the pore radius, thus facilitating the flow of
chloride ions through the channel. However, distinctive conformations are observed that
depend on the pH environment. At pH 6.5 in the presence of IVM, the pore constricts
around the selectivity filter, thus limiting ion flow. In contrast, at pH 9 with IVM, the pore
is wide open. A summarized view of the SsCl structural states is shown in Figure 7.
Another unusual feature in SsCl is the electrostatic surface potential. It is predominantly
electronegative in the ECD and upper part of TMD; however, it becomes neutral about
halfway down the pore and is positive near the selectivity filter. The helix dipole effect
likely contributes to lowering the energy barrier for ion permeation through the
constriction of the selectivity filter. Collectively, these findings highlight structural and
functional features of SsCl, and provide initial insights into the channel’s mechanisms,
which warrant further investigation. These findings could inform the development of
novel and more effective therapeutics targeting scabies.

Methods
Ethical Statement
Ovaries were harvested from Xenopus laevis female frogs following procedures
established with the Geneva Canton agreement. Frogs were obtained from the TEFOR
PARIS SARCLAY Institut des Neurosciences, bât. 151, 151 route de la Rotonde 91400
Sarclay, France. Experiments were conducted in Geneva with the authorization from the
animal care 34485 GE177.
SsCl cloning, expression, and purification
The plasmid encoding SsCl (GenBank ABV02573.1) in the vector pT7TS3 was a
gift from Joseph A. Dent, McGill University, Montreal, Canada. For expression
screening, we subcloned the SsCl sequence into a modified pFastBac vector containing
an N-terminal signal sequence from Lymnaea stagnalis AChBP56, an 8xHis-tag, GFP, a
thrombin cleavage site, a site for ligase-independent cloning (LIC)57 and a C-terminal
Strep-tag II site. The mature SsCl sequence N28-L489 was cloned into the LIC site and
used for initial construct design. To improve protein stability, we truncated the
intracellular M3-M4 loop (residues E331-E464) and replaced it with the linker sequence
SQPARAA from the prokaryotic homologue GLIC29. We termed this construct SsCl .
EM
The resulting GFP-fusion construct was employed to optimize expression in Sf9 insect
cells using the Bac-to-Bac expression system (Invitrogen). Detergent screening was
performed using FSEC30 and n-undecyl--D-maltoside was identified as a suitable
detergent for SsCl solubilization. For large-scale expression, we subcloned SsCl in
pFastBac as a fusion protein with maltose-binding protein (MBP). A thrombin cleavage
site was engineered between MBP and SsCl .
EM
Protein expression was induced in 600
mL cell culture volume with an Sf9 insect cell density of 2-3 x106/mL. 2 mL of P3
baculovirus was added to the culture and incubated for 4 days at 28°C in a rotary
shaker/incubator at 80 RPM.
3.6 L Sf9 insect cell culture expressing MBP-SsCl was harvested by
EM
centrifugation at 10,000 g for 10 min at 4°C. The resulting cell pellet was resuspended
in a volume two times the wet pellet weight (v/w) of cell lysis buffer containing 50 mM
Na-phosphate buffer and 150 mM NaCl, pH 8 supplemented with 1 mM PMSF, 0.1
mg/mL DNase, 0.5 mM MgCl , 1 g/mL pepstatin, 1 g/mL leupeptin and 1 g/mL
2
aprotinin. Cells were lysed by 2 passages through an Emulsiflex C-5 high-pressure
homogenizer (Avestin) at a maximum pressure of 1500 bar. Membranes were isolated
by ultracentrifugation at 125,000 g for 1 hour at 4°C. The membrane pellet was
resuspended in 40 mL buffer containing 50 mM Na-phosphate buffer and 150 mM NaCl,
pH 8. The membranes were solubilized by adding 2% n-undecyl-β-D-maltoside
(Anagrade, Anatrace) for 2 hours at 4°C. The solution was cleared by centrifugation at
30,000 g for 45 min at 4°C. The clear supernatant was loaded on a 3.6 mL pre-washed
amylose resin column (New England Biolabs). The column was washed with 10 column
volumes of wash buffer containing 50 mM Na-phosphate buffer, 150 mM NaCl, pH 8,
and 0.15% n-undecyl-β-D-maltoside. The protein was eluted with 5 column volumes of
elution buffer containing 50 mM Na-phosphate buffer, 150 mM NaCl, pH 8, 0.15% n-
undecyl-β-D-maltoside, and 50 mM maltose. The eluted fractions were analysed by
SDS-PAGE and pooled. 250 units of thrombin (Calbiochem) were added to cleave the
MBP-SsCl fusion protein and incubated overnight at 4°C. The resulting fraction was
EM
concentrated to 0.5 mL on an Amicon concentrator with a molecular weight cut-off of
100 kDa. This fraction was then loaded on a Superose 6 Increase 10/300 GL gel
filtration column (Cytiva) pre-equilibrated with a running buffer containing 10 mM bis-
trispropane at pH 9 or 6.5, 150 mM NaCl, and 0.15% n-undecyl-β-D-maltoside.
The
eluted fractions were analysed by SDS-PAGE and pooled. The resulting fraction was
concentrated on an Amicon concentrator with a molecular weight cut-off of 100 kDa.
This solution was then directly used to prepare EM grids. For the determination of the
IVM-bound structures, 10 g/mL IVM was added during all purification steps starting
from solubilization.
Cryo-EM sample preparation
Cryo-EM grids were prepared using QUANTIFOIL® R 1.2/1.3 holey carbon films
on 300 mesh copper supports. Before the sample application, grids were glow-
discharged for 60 s at 0.39 mBar and 15 mA, using a PELCO easiGlow™ Glow
Discharge System. Subsequently, 3 μL of purified protein sample ranging from 2 to 3
mg/mL was applied to each grid, which was then blotted for either 5.4 or 5.6 s at 4 °C
and 95% relative humidity using a Leica EM GP2 automatic plunge freezer. Grids were
immediately vitrified by plunge-freezing into liquid ethane and stored in liquid nitrogen.
Cryo-EM data acquisition
Cryo-EM datasets for the pH 9, pH 9 with IVM, and pH 6.5 with IVM conditions
were collected on a Titan Krios transmission electron microscope (Thermo Fisher
Scientific) operating at 300 kV with a Gatan BioQuantum energy filter (operated at 20
eV) and a Gatan K3 direct electron detector at the Electron Bio-Imaging Centre (eBIC),
Diamond Light Source, Harwell, UK. The dataset corresponding to the pH 6.5 (closed
state) condition was acquired on a JEOL CryoARM 300 transmission electron
microscope (JEOL Ltd.) operated at 300 kV with an Omega filter and K3 direct electron
detector, at the VIB-VUB Facility for Bio Electron Cryogenic Microscopy (BECM),
Brussels, Belgium. Specifications for data collection can be found in the Supplementary
Table 1.
Cryo-EM data processing
Datasets were processed according to the workflow outlined in Supplementary
Fig. 6. Initial processing was performed in RELION 5.0 (ref 58). Raw movies were
motion-corrected and dose-weighted using RELION’s implementation of MotionCor259,
and contrast transfer function (CTF) parameters were estimated with CTFFIND460.
Particle picking was conducted externally using crYOLO61, employing the general pre-
trained model with dataset-specific adjustments to picking threshold and particle size.
Picked coordinates were imported into RELION for particle extraction with initial
downsampling to accelerate processing. Extracted particles underwent multiple rounds
of 2D classification to remove poorly aligned classes and particles lacking clear
structural features of a pentameric channel. Selected particles were used to generate
an initial 3D model, followed by unsupervised 3D classification in C1. Particles from
well-resolved classes were then re-extracted at the original pixel size.
Further steps were carried out in cryoSPARC62. Another 2D classification step
was performed, followed by ab initio reconstruction, non-uniform63, and local refinement
in C1 symmetry. Symmetry analysis of the channel confirmed C5 symmetry, which was
applied in the final rounds of global and local refinement. Global and local CTF
refinement were performed to enhance overall map resolution and alignment fidelity.
Maps were visualized using UCSF ChimeraX64.
Model building, refinement, and validation
An initial reference model was generated using AlphaFold2 (or AlphaFold365) and
used as the starting point for model building. Construction began with a single subunit,
which was first rigid-body fitted into the cryo-EM map using the ‘fit’ tool in UCSF
ChimeraX. Interactive model building was then carried out in COOT66 to resolve
discrepancies and improve the overall fit. Refinement proceeded iteratively within the
Doppio suite (CCP-EM67), beginning with TEMPy-REFF68 to optimize model-to-map
agreement. This was followed by successive refinement cycles using
Refmac/Servalcat69, interspersed with detailed interactive model building in COOT. Final
optimization of local conformations was achieved using ISOLDE70 through interactive
molecular dynamics flexible fitting. Once the single-subunit model met refinement and
validation criteria, C5 symmetry was applied to reconstruct the full assembly.
Comprehensive validation was performed using Doppio’s integrated pipeline to assess
stereochemistry, fit-to-density, and sequence fidelity. Additional validation of sequence
registration was carried out using FindMySequence and CheckMySequence, enabling
correction and confirmation of residue-level assignments within the density. Figures
were prepared using PyMOL (The PyMOL Molecular Graphics System, Version 3.0,
Schrödinger, LLC.) and UCSF ChimeraX.
Pore analysis with HOLE
Pore dimensions were analyzed using the HOLE program71. The SsCl refined
atomic models were used as inputs, and the pore axis was defined manually by
selecting points along the central channel for each structure. HOLE was run using
default parameters to calculate the pore profile, and the resulting radius plot was used
to identify constriction sites and estimate the pore diameter along the channel axis. Pore
radius profiles were plotted using GraphPad Prism, and structural figures were
generated with PyMOL.
Electrostatics calculations
Electrostatics calculations were performed using the Adaptive Poisson–
Boltzmann Solver (APBS)72 at the experimental pH values of 6.5 and 9. Protonation
states were assigned using PROPKA through the PDB2PQR pipeline with Amber force-
field parameters. The linearized Poisson–Boltzmann equation was solved under single
Debye–Hückel boundary conditions. The protein dielectric constant was set to 2.0, and
the solvent dielectric constant to 78.0. Atomic charges were mapped to the grid using
cubic B-spline discretization. Calculations were performed at 310 K in the presence of
two mobile ion species (Na⁺ and Cl⁻), each at 0.15 M, with ion radii of 2.0 Å for Na⁺ and
1.8 Å for Cl⁻. The membrane environment was not included in these calculations. The
APBS results were visualized as Surface potentials and Electrostatic isocontours.
Residue selection for pH-sensing and gating analysis
The burial percentage and pKₐ values of all titratable residues were calculated
using PROPKA49 (via PDB2PQR, with Amber force-field parameters). Cysteine pairs
forming disulfide bonds were excluded from the analysis. In addition, residues within the
transmembrane domain were not considered since this study focused on the
extracellular region, known as important for binding and channel modulation in other
pLGICs.
State-dependent changes were identified by detailed structural analysis and by
comparing the predicted pKₐ values and solvent exposure between the two pH
conditions. Residues exhibiting shifts in pKₐ together with changes in burial or solvent
accessibility were flagged as potential candidates, as such features indicate altered
interactions and/or structural rearrangements associated with pH-dependent
conformational transitions. Candidate residues were further investigated in the three-
dimensional structures to inspect local interactions, including hydrogen bonds,
electrostatic contacts, and clustering with neighbouring titratable groups. Known
functional roles of analogous regions in related pH-sensitive receptors were considered
to guide interpretation.
mRNA synthesis for electrophysiology
For expression in Xenopus oocytes, the full-length sequence of SsCl was
subcloned into pGEM-HE73 using EcoRI and HindIII restriction sites. SsCl was
engineered the same way as for the pFastBac expression construct. The plasmid was
linearized with PstI and transcribed with the mMESSAGE mMACHINE T7 ULTRA
Transcription kit. The typical yield of cRNA was around 1.5 g/L. Point mutants of SsCl
in pGEM-HE were engineered using the QuikChange site-directed mutagenesis kit
(Agilent). Mutations were confirmed by Sanger sequencing (LGC Genomics, Germany).
Oocyte preparation and injection
Ovaries were harvested from Xenopus laevis female frogs following procedures
established with the Geneva Canton agreement. Frogs were obtained from the TEFOR
PARIS SARCLAY Institut des Neurosciences, bât. 151, 151 route de la Rotonde 91400
Sarclay, France. Experiments were conducted in Geneva with the authorization from the
animal care 34485 GE177. Ovaries were isolated, placed in sterile medium, and kept in
clean conditions at 4°C. Ovaries were maintained in physiological OR2 medium (88 mM
NaCl, 2.5 mM KCl, 1.8 mM CaCl .2H O, 1 mM MgCl , 5 mM HEPES at pH 7.8, unless
2 2 2
indicated otherwise). Oocytes were isolated using mechanical and enzymatic
procedures with Type-I collagenase (Sigma). One or two days following isolation,
oocytes were injected with 15 nL of mRNA resuspended in distilled water at 0.1 μg/μL.
Injections were conducted using the automated Roboinject device (Multichannel
System, Germany). Functional expression of SsCl channels was assessed at least two
days after injection.
Electrophysiology
All recordings were conducted using the automated TEVC system, HiClamp
(Multichannel System, Germany). Electrodes were pulled from borosilicate glass
(1.2 mm O.D., 0.8 mm i.d.) using a proprietary puller and filled with 3 M KCl, yielding
electrodes displaying a typical resistance of about 500 kOhms. Voltage and currents
were digitized at 100 Hz and filtered at 20 Hz. Data acquisition and analysis were done
using proprietary software running under Matlab (Mathworks Inc.). Unless otherwise
indicated, cells were perfused with OR2 adjusted to a pH of 5.35 and maintained at -80
mV throughout the experiment. As desired in the experimental protocol, cells were
moved from the perfusion chamber to the incubation well of a 96-microtiter plate
(NUNC, Thermofisher). In the microwells, the solution was agitated by a small, specially
designed stirring magnet.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "This article reports the cryo-EM structure, in different states and at two different pHs, of a pH-gated pentameric ligand-gated ion channel (pLGIC), from scabies mites. This channel is an anionic one.\nThis work also reports cryo-EM structures in the presence of ivermectin, an allosteric effector of this ion channel and tries to\npinpoint the molecular origin of its pH sensititivity.\nThree out of the four structures reported are at atomic resolution (3.1.-3.6 Angstrom) while the fourth one is at medium\nresolution (4.24 Angstrom).\nMain remarks\n-Use APBS of for the calculation of electrostatic properties at the surface of the receptor:\nthe description of its use in Mat and Meth. section is unsufficient (line 600-601). In particular, what is the salt nature and\nconcentration in the buffer (NaCl? Concentration?) chosen for the calculation? How were the charges chosen for titrable\nresidues (PDB2PQR?). Radii of atoms? Dielectric constant in the protein (very important) and in the solvent? Temperature?\nWas the membrane taken into account?\nIn addition the authors should visualize the resulting two maps for the density of the cation (Na+) and anion (Cl-), and display\nit in a Figure around the top of the pore. Both maps are calculated on a grid, whose dimensions should be given (lengths\nand step sizes). The electrostatic potential projected onto the surface (Fig. S19b) is not enough to understand\nwhat is going on here.\nThis is important since the authors report but offer no explanation of the negative character of the upper part of the channel,\nwhich is in contradiction with what is expected for an anion-conducting channel (see line 334-5).\nIf, however, APBS predicts a strong counter-ion cloud in the vicinity of this region, that would effectively reverse the charge\nof this region, or at least neutralize it (if there is space for it), then a possible explanation for this contradiction might emerge.\n-Use of PropKa for the selection of possible important residues for pH sensitivity.\nWhy were residues only with a pKa below 7 selected (lines 348-354)?\nThis is completely baffling, since the pH_50 of the transition is around 8.5. Histidines are OK but why glutamates? Please\nexplain.\nWhy were residues like cysteines completely rejected from consideration: there are 9 of them and they have a pKa around\n8.5…\nAltogether, this section is unconvincing, especially as the two residues that are presented as responsible for the pH-driven\ntransition (E146 and H206) have only a modest effect on the pH_50 upon mutation into alanine – about 0.5 pH unit).\n-Function: do Zn++ ions have an effect on the transition? What about Ca++? These two types of divalent ions should be\ncharacterized as they are known to have an effect on pLGICs of the same family.\n-Comparisons with other structures and sequences\nSteLIC is a pH-gated pLGIC isolated from a symbiont of Tevnia jerichonana that also titrates around pH 8.5. It seems ideally\nsuited for interesting structural and functional comparisons, as much is known about its structure-function relationships (see\nbelow), even though it is a cationic channel, not an anionic one. However, it is absent from the multi-alignment (Figure S1)\nand from structural comparisons in the Discussion. It should be taken into account in the new version of the article. It might\nlead to new insights both for the authors and the readers.\nAlso, the description of the ivermectin binding site should be put in perspective with what is known on all allosteric sites of\npLGIC (see for instance Shasahvar et al., 2015 – see below).\nIn the introduction, the recent review of Cecchini et al, 2024 could be cited.\nIn summary, more efforts should be made to understand the molecular origin of the pH-gating of this channel, both with\ncalculations on the electrostatics at play and structural bioinformatics (APBS, superimposition with SteLIC), functional tests\n(effect of Zn++, Ca++), and mutants (effects of cysteine should be ruled out by experiments).\nMinor remarks\n-line 194: typo “it at pH 9”\n-line 415: typo at “Hill-slope”\n-Important references are missing and should be cited\n-Review on allosteric sites of pLGIC (seen by crystallography)\nSauguet, Shahsavar and Delarue. BBA 2015.\nhttps://pubmed.ncbi.nlm.nih.gov/24836522/\n-Recent Review on pLGICs: Cecchini, Corringer and Changeux.\nAnn. Rev. Biochem. 2024 https://pubmed.ncbi.nlm.nih.gov/38346274/\n-Articles on SteLIC\nHu H. et al., 2018 Proc Natl Acad Sci (USA)\nhttps://pubmed.ncbi.nlm.nih.gov/32482881/\nKarlsson et al., 2025 British J. Pharmacol.\nhttps://pubmed.ncbi.nlm.nih.gov/40065647/", "reviewer_2": "The manuscript by Kleiz-Ferreira et al. presents a high-quality structure-function analysis of the pH-sensitive pLGIC SsCl. The work is timely and of broad interest given the pathogen’s public health relevance and the urgent need for new therapeutic strategies. The authors provide significant advances in the field by elucidating mechanisms of pH-dependent gating, the interplay between IVM and pH, and identifying a potential pH sensor region.\nHowever, there are several points that should be addressed prior to publication, as outlined below:\nMajor Points:\n1. Resolution limits and structural interpretation\n* The resolution of the pH 6.5 closed-state structure is relatively low, precluding precise side chain placement in the pore-\nlining helices. As such, the pore radius for this state in Fig. 4 should either be omitted, or—at a minimum—rendered as a\ndotted or dashed line to indicate lower confidence relative to higher-resolution states.\n* While IVM can be confidently fit into the maps, details of the binding pocket at this resolution appear over-interpreted.\nBased on the maps, only two side chains (e.g. K264 and D277) can be defined unambiguously in the pocket. Figure 3, as\npresented, suggests considerably more certainty than is warranted. I recommend the authors indicate explicitly the\nlimitations of the data, and consider showing only mainchain positions and general pocket regions, omitting detailed side\nchains unless their orientation is clearly supported.\n2. Identification of M4\n* Can the authors clarify how they are assigning the M4 segment in the pH 9 conditions? In Supplemental Figure 10, there\ndoes not appear to be continuous density connecting M4 to the rest of the structure. A clear explanation, and if possible,\nsupporting visual evidence, would be helpful.\n3. Hourglass conformation\n* The “hourglass” channel profile is described as unexpected by the authors, but similar conformations have been observed\nin other pLGICs. The manuscript should clarify that this structural arrangement, while potentially unprecedented among\nanionic pLGICs, is not unique in the broader pLGIC family.\n4. Micrograph quality and data processing\n* There are concerning artifacts visible in several representative micrographs (e.g., a vertical black streak in the pH 6.5\nclosed, other artifacts in pH 6.5 IVM, and a white vertical line in pH 9). Were the images properly gain-corrected? Please\nclarify the source of these artifacts and their implications.\n* The workflow states three rounds of 2D classification, yet only four 2D classes remain. Why so few? All 2D classes should\nbe presented with selected classes clearly marked.\n* The approach to 3D classification appears limited; what was the rationale for the number of classes, and could more\nexhaustive searching improve map quality or state separation?\n* The total particle numbers for each 3D class should be provided for transparency and reproducibility.\n* Scale bars should be added to all micrographs.\n* 3DFSC plots should be included for each map so that map anisotropy can be assessed.\n5. Electrophysiology data reporting\n* For most electrophysiological experiments, “n ≥ 3” is listed as the number of replicates. For clarity and full transparency, the\nexplicit number of repeats for each condition should be stated in all figure legends and results.\nMinor Points:\n* In Figure 5, please include all color definitions and legend details within the figure itself to facilitate interpretation."}, "author_response": "Point-by-point response to the reviewers’ comments\nReviewer #1 (Remarks to the Author):\nThis article reports the cryo-EM structure, in di6erent states and at two di6erent pHs,\nof a pH-gated pentameric ligand-gated ion channel (pLGIC), from scabies mites. This\nchannel is an anionic one. This work also reports cryo-EM structures in the presence of\nivermectin, an allosteric e6ector of this ion channel and tries to pinpoint the molecular origin\nof its pH sensitivity. Three out of the four structures reported are at atomic resolution (3.1.-\n3.6 Angstrom) while the fourth one is at medium resolution (4.24 Angstrom).\nMain remarks\n-Use APBS of for the calculation of electrostatic properties at the surface of the receptor: the\ndescription of its use in Mat and Meth. section is unsu6icient (line 600-601). In particular,\nwhat is the salt nature and concentration in the bu6er (NaCl? Concentration?) chosen for\nthe calculation? How were the charges chosen for titrable residues (PDB2PQR?). Radii of\natoms? Dielectric constant in the protein (very important) and in the solvent? Temperature?\nWas the membrane taken into account?\nResponse: The referee raises an important point, which we have carefully considered. To\nclarify, the protonation states of titratable residues were assigned using PROPKA at the\nexperimental pH values of 6.5 and 9 through the PDB2PQR pipeline, with parameterization\nbased on the Amber force field. Electrostatic calculations were performed using the\nAdaptive Poisson-Boltzmann Solver (APBS). The ionic environment was modelled with two\nmobile ion species representing physiological Na⁺ and Cl⁻, each at 0.15 M concentration.\nIon radii were set to 2.0 Å for Na⁺ and 1.8 Å for Cl⁻. The dielectric constant of the solvent was\nset to 78, and the biomolecular dielectric constant set to 2. Atomic charges were mapped\nonto the grid using cubic B-spline discretization. All calculations were conducted at 310 K\ntemperature. The membrane environment was not included in these calculations. A Method\nsection (“Electrostatics calculations”) was included in the manuscript.\nMethod section (Lines 623-633)\nElectrostatics calculations: Electrostatics calculations were performed using the Adaptive\nPoisson–Boltzmann Solver (APBS)71 at the experimental pH values of 6.5 and 9. Protonation\nstates were assigned using PROPKA through the PDB2PQR pipeline with Amber force-field\nparameters. The linearized Poisson–Boltzmann equation was solved under single Debye–\nHückel boundary conditions. The protein dielectric constant was set to 2.0 and the solvent\ndielectric constant to 78.0. Atomic charges were mapped to the grid using cubic B-spline\ndiscretization. Calculations were performed at 310 K in the presence of two mobile ion\nspecies (Na⁺ and Cl⁻) each at 0.15 M, with ion radii of 2.0 Å for Na⁺ and 1.8 Å for Cl⁻. The\nmembrane environment was not included in these calculations.\n-In addition the authors should visualize the resulting two maps for the density of the cation\n(Na+) and anion (Cl-), and display it in a Figure around the top of the pore. Both maps are\ncalculated on a grid, whose dimensions should be given (lengths and step sizes). The\nelectrostatic potential projected onto the surface (Fig. S19b) is not enough to understand\nwhat is going on here.\nThis is important since the authors report but o6er no explanation of the negative character\nof the upper part of the channel, which is in contradiction with what is expected for an anion-\nconducting channel (see line 334-5).\nIf, however, APBS predicts a strong counter-ion cloud in the vicinity of this region, that would\ne6ectively reverse the charge of this region, or at least neutralize it (if there is space for it),\nthen a possible explanation for this contradiction might emerge.\nResponse: We thank the referee for this insightful comment. We agree that visualization of\ncation and anion densities, with their placement in the maps, can substantially inform and\npotentially influence the electrostatic potential calculations. However, unambiguous\nplacement of ions or water molecules in cryo-EM maps at resolutions lower than 3 Å remains\nchallenging 1. The electrostatic surface potential shown in Sup. Fig. 19 (now 20) was\ncalculated for structures determined at 3.1 Å and 3.6 Å resolution, where the identification\nof discrete ion densities is not reliably supported by the map. Given these limitations, we\nopted not to place individual Na⁺ or Cl⁻ ions, or water molecules, into the structural models.\nNevertheless, the ionic environment was explicitly incorporated into the APBS calculation.\nTwo mobile ion species representing Na⁺ and Cl⁻ were included at 0.15 M concentration,\nwith radii of 2.0 Å and 1.8 Å, respectively. The solvent dielectric constant was set to 78, and\na biomolecular dielectric of 2 was used. These parameters allow for proper treatment of\nionic screening. Thus, while the model does not feature ions, the calculated electrostatic\npotential reflects their contribution. We acknowledge that the absence of resolved charges\nin the structure may limit fine and precise detail, but this approach avoids introducing poorly\nsupported features while retaining the influence of the physiological ionic environment. We\nhave now included a sentence in the manuscript (lines 327-329) to clarify that ions were not\nmodelled into the cryo-EM maps due to resolution limitations, though the ionic environment\nwas included in the calculations.\nIn addition, the step size is 1 (full resolution) for all maps, and the specific voxel size\nfor each map are reported in the corresponding PDB EM validation report. For clarity, the step\nsize, the grid dimension and length have now been included in the supplementary cryo-EM\ninfo table 1.\n-Use of PropKa for the selection of possible important residues for pH sensitivity.\nWhy were residues only with a pKa below 7 selected (lines 348-354)?\nThis is completely ba6ling, since the pH_50 of the transition is around 8.5. Histidines are OK\nbut why glutamates? Please explain.\nResponse: Our selection strategy did not aim to match predicted pKₐ values to the\nexperimental pH₅₀ of activation (8.5), nor did we set a pKₐ threshold (e.g., <7) as a formal\nselection criterion. Rather, we sought to identify residues whose protonation state could\nchange within the specific structural environment of each experimental condition. To this\nend, we used PROPKA with the pH set to that of the structural dataset (6.5 or 9), thereby\nmimicking the electrostatic environment present in each conformation.\nIn addition to the predicted pKₐ, we considered the solvent-exposed surface area of\neach titratable residue, as a likely pH sensor should not be deeply buried. Candidates were\nthen visually inspected in the 3D structure to assess their local chemical environment.\nAlthough the residues we ultimately identified happened to have predicted pKₐ values below\n7, this was an outcome of the calculation rather than a predefined filter.\nThis process led us to focus on glutamates and histidines, which are also known to\nparticipate in pH sensing in other receptors (e.g. GLIC2 and PAC3,4). Thus, the experimental\npH₅₀ was used to characterize whole-protein functional transitions, but not as a direct filter\nfor residue selection. A new Method section has been included for clarify and the sentence\n“Residues with lower pKa values (≤ 7) and strategically positioned on the structure (e.g.\naccessible to solvent) were selected” was removed.\nMethod section: (Lines 635-643)\npKₐ prediction and residue analysis: pKₐ values for titratable residues were calculated with\nPROPKA48 (via PDB2PQR, Amber 6 parameters) using the experimental pH of each structure\n(6.5 or 9) to reflect its specific electrostatic environment. Predicted pKₐ values were\nconsidered together with solvent-exposed surface area, as likely pH sensors are not deeply\nburied. Candidate residues were then inspected in the three-dimensional structure to\nassess local interactions. No pKₐ threshold was imposed. Known roles for analogous\nresidues in other pH-sensing receptors informed the interpretation.\n-Why were residues like cysteines completely rejected from consideration: there are 9 of\nthem and they have a pKa around 8.5…\nAltogether, this section is unconvincing, especially as the two residues that are presented as\nresponsible for the pH-driven transition (E146 and H206) have only a modest e6ect on the\npH_50 upon mutation into alanine – about 0.5 pH unit).\nResponse: We thank the referee for this observation. Although cysteine residues have\nintrinsic pKₐ values near 8.5, their protonation behaviour is strongly influenced by their local\nenvironment. Importantly, our analyses were based on predicted pKₐ values calculated at\nthe experimental pH of the structures and did not use the pH₅₀ as a selection criterion; this\nhas been clarified in the newly added Methods section (“pKₐ prediction and residue\nanalysis”).\nSpecifically, of the nine cysteines present, four form disulfide bonds, one is located\nin the pore region, and the remainder reside within the transmembrane domain, where most\nare buried. Given these structural contexts, cysteines were excluded from consideration as\nprimary pH sensors. This does not imply that they have no influence, but as explained in the\nmanuscript “Whether this series of protonation-dependent rearrangements represent the\nunique mechanism for pH-sensing and channel activation remains an open and intriguing\nquestion. While the structural cascade centers around H206 and E146, these residues may\nact in concert with other modulatory elements or alternative sensing pathways, inviting\nfurther structural and functional exploration.”; lines 418-422.\nConcerning the modest (~0.5 pH unit) shifts in pH₅₀ observed upon mutation of E146\nand H206 to alanine, this reflects the multifactorial nature of pH sensing in the receptor,\nwhich likely involves multiple residues and cooperative e6ects, as discussed in the\nmanuscript. Our analysis identifies E146 and H206 as key contributors within this network\nrather than sole determinants.\n-Function: do Zn++ ions have an e6ect on the transition? What about Ca++? These two types\nof divalent ions should be characterized as they are known to have an e6ect on pLGICs of\nthe same family.\nResponse: We thank the referee for this important point. While Zn²⁺ ions are known\nmodulators of some pentameric ligand-gated ion channels, a previous publication on SsCl\nreported no agonist response to zinc ions at concentrations up to 1 mM at pH 7.5 in oocytes\n5 . However, we have explored the modulatory e6ect of Zn²⁺ and Ca²⁺ ions on SsCl via\nadditional electrophysiology experiments and found them to have an inhibitory e6ect on the\npH-induced current. These additional experiments have been included in the manuscript as\nsupplementary material (Sup.Fig. 23) and discussed in lines 431-441.\n-Comparisons with other structures and sequences\nSteLIC is a pH-gated pLGIC isolated from a symbiont of Tevnia jerichonana that also titrates\naround pH 8.5. It seems ideally suited for interesting structural and functional comparisons,\nas much is known about its structure-function relationships (see below), even though it is a\ncationic channel, not an anionic one. However, it is absent from the multi-alignment (Figure\nS1) and from structural comparisons in the Discussion. It should be taken into account in\nthe new version of the article. It might lead to new insights both for the authors and the\nreaders.\nResponse: sTeLIC has been added to the pLGIC alignment in Sup. Fig. 1 and a comparison\nof relevant residues have also been included within the discussion (lines 423-430).\n-Also, the description of the ivermectin binding site should be put in perspective with what\nis known on all allosteric sites of pLGIC (see for instance Shasahvar et al., 2015 – see below).\nIn the introduction, the recent review of Cecchini et al, 2024 could be cited.\nResponse: Throughout the section ‘Allosteric activation by IVM and its dependency on pH’\n(line 185), the functional activity of ivermectin, its binding site identified within the cryo-EM\nstructure and key residues within SsCl that interact with IVM have all been thoroughly\ncompared to other pLGICs including the related GluCl channel, glycine receptors and α7\nnAChR. The reference to the review from Cecchini et al. has been included in line 307.\n-In summary, more e6orts should be made to understand the molecular origin of the pH-\ngating of this channel, both with calculations on the electrostatics at play and structural\nbioinformatics (APBS, superimposition with SteLIC), functional tests (e6ect of Zn++, Ca++),\nand mutants (e6ects of cysteine should be ruled out by experiments).\nMinor remarks\n-line 194: typo “it at pH 9”\n-line 415: typo at “Hill-slope”\n-Important references are missing and should be cited\n-Review on allosteric sites of pLGIC (seen by crystallography)\nSauguet, Shahsavar and Delarue. BBA 2015.\nhttps://pubmed.ncbi.nlm.nih.gov/24836522/\n-Recent Review on pLGICs: Cecchini, Corringer and Changeux.\nAnn. Rev. Biochem. 2024 https://pubmed.ncbi.nlm.nih.gov/38346274/\n-Articles on SteLIC\nHu H. et al., 2018 Proc Natl Acad Sci (USA)\nhttps://pubmed.ncbi.nlm.nih.gov/32482881/\nKarlsson et al., 2025 British J. Pharmacol.\nhttps://pubmed.ncbi.nlm.nih.gov/40065647/\nResponse: We thank the referee for the thorough revision. All minor remarks have been\ncarefully addressed.\nReviewer #2 (Remarks to the Author):\nThe manuscript by Kleiz-Ferreira et al. presents a high-quality structure-function\nanalysis of the pH-sensitive pLGIC SsCl. The work is timely and of broad interest given the\npathogen’s public health relevance and the urgent need for new therapeutic strategies. The\nauthors provide significant advances in the field by elucidating mechanisms of pH-\ndependent gating, the interplay between IVM and pH, and identifying a potential pH sensor\nregion.\nHowever, there are several points that should be addressed prior to publication, as outlined\nbelow:\nMajor Points:\n1. Resolution limits and structural interpretation\n-The resolution of the pH 6.5 closed-state structure is relatively low, precluding precise side\nchain placement in the pore-lining helices. As such, the pore radius for this state in Fig. 4\nshould either be omitted, or—at a minimum—rendered as a dotted or dashed line to indicate\nlower confidence relative to higher-resolution states.\nResponse: Thank you for your observation. We agree that the low resolution a6ects the\nprecision of side chain placement. Although limited, the pore-lining residues were carefully\nexamined through inspection of raw and sharpened maps to ensure the most accurate\ninterpretation possible within the limitation. While some uncertainty could remain due to\nresolution, the consistency across multiple map treatments supports confidence in the\noverall assignment. To reflect this, we have clarified in the manuscript (lines 243-245) that\nthe pore radius for this state was carefully interpreted due to low resolution.\n-While IVM can be confidently fit into the maps, details of the binding pocket at this\nresolution appear over-interpreted. Based on the maps, only two side chains (e.g. K264 and\nD277) can be defined unambiguously in the pocket. Figure 3, as presented, suggests\nconsiderably more certainty than is warranted. I recommend the authors indicate explicitly\nthe limitations of the data, and consider showing only mainchain positions and general\npocket regions, omitting detailed side chains unless their orientation is clearly supported.\nResponse: The densities in the IVM pocket region were carefully examined before\nconfidently reporting the residues involved in IVM binding pocket. We believe some\nconfusion may arise from the Sup. Fig. 14 (now renumbered to 15), which shows only the\nside chains of K264 and D277 as part of a focused discussion on these residues. To avoid\nany misunderstanding and better represent the data, we have now included a new\nsupplementary figure (new Sup. Fig. 14, line 217) displaying the cryo-EM densities for all\nresidues within the IVM pocket for both structures at pH 6.5 and pH 9 with IVM. This aims to\nclarify the discussed data that is supported by the density. In the new updated\nsupplementary material, the figures from old 14 on were renumbered accordingly.\n2. Identification of M4\n-Can the authors clarify how they are assigning the M4 segment in the pH 9 conditions? In\nSupplemental Figure 10, there does not appear to be continuous density connecting M4 to\nthe rest of the structure. A clear explanation, and if possible, supporting visual evidence,\nwould be helpful.\nResponse: The identification of the M4 segment in the cryo-EM maps at pH 9 was based on\nthe highly conserved overall position of this segment among Cys-loop receptors. In\nSupplementary Figure 10, we present the M4 segment in a side view alongside a bottom view\nwith a slice through the structure. Due to this slicing, the connections between the\ntransmembrane helices are not visible if the connecting loop is positioned at the bottom of\nthe structure. For clarity, we have included a dotted line in the side view indicating the plane\nat which the bottom view is sliced.\n3. Hourglass conformation\n-The “hourglass” channel profile is described as unexpected by the authors, but similar\nconformations have been observed in other pLGICs. The manuscript should clarify that this\nstructural arrangement, while potentially unprecedented among anionic pLGICs, is not\nunique in the broader pLGIC family.\nResponse: The discussion of this unique conformation for an anionic channel and\ncomparison to cationic channels is included within the text, constituting its own paragraph\nwithin the ‘ion-conducting pathway and selectivity’ section (lines 260-269).\nAs this is an interesting find we wish to draw the reader’s attention to, it is also\nincluded within the abstract (lines 31-33) “The desensitized structure adopts an unexpected\n“hourglass” conformation, suggesting the gating mechanisms may be more related to\ncation-selective channels”.\nWe believe these references are su6icient to communicate to the reader that this\nconformation is unexpected and indeed unique for anionic channels, however that the\nconformation has been noted before for cationic channels such as the nicotinic\nacetylcholine receptor.\n4. Micrograph quality and data processing\n- There are concerning artifacts visible in several representative micrographs (e.g., a vertical\nblack streak in the pH 6.5 closed, other artifacts in pH 6.5 IVM, and a white vertical line in pH\n9). Were the images properly gain-corrected? Please clarify the source of these artifacts and\ntheir implications.\nResponse: We thank the referee for highlighting these details. All micrographs were properly\ngain-corrected prior to further processing using the gain reference file obtained before the\nparticular data collection. The vertical streaks and lines observed in some micrographs are\nknown artifacts that can arise from beam-induced motion, detector defects, or residual\nissues in image acquisition. These artifacts are localized and do not a6ect the overall dataset\nquality or the final reconstructions, as they are mitigated during the subsequent steps in the\ndata processing. We have reviewed the micrographs carefully and confirm that the a6ected\nimages constitute a small fraction of the dataset and do not bias the results. We have\nupdated the example micrographs in Sup.Fig. 6 changing to images that better represent the\ndatasets, and now we are showing motion corrected images.\n- The workflow states three rounds of 2D classification, yet only four 2D classes remain. Why\nso few? All 2D classes should be presented with selected classes clearly marked.\nResponse: Three rounds of 2D classification were performed in Relion with a large number\nof initial classes (typically 50–100). We chose to present only the selected classes\nrepresenting the predominant particle views in our datasets. Displaying a subset of well-\ndefined classes is common practice in cryo-EM studies to focus on relevant particle\npopulations without redundancy. Additionally, several 2D classes discarded during the initial\nclassifications corresponded to dust or empty micelles, common contaminants that are\nirrelevant for further processing, and were therefore excluded from the presentation in Sup.\nFig. 6. We have updated the Sup. Fig. 6 legend accordingly for clarity.\n-The approach to 3D classification appears limited; what was the rationale for the number of\nclasses, and could more exhaustive searching improve map quality or state separation?\n-The total particle numbers for each 3D class should be provided for transparency and\nreproducibility.\nResponse: Initially, we tested di6erent numbers of 3D classes to explore dataset\nheterogeneity, but higher number of classes did not improve the final reconstructions, likely\ndue to insu6icient number of particles in each class. Therefore, for some datasets, two\nclasses were adequate, while four classes were used for datasets with, for example, more\ncontamination such as empty micelles. This strategy balances computational e6iciency\nwith meaningful state separation. We acknowledge that cryo-EM processing is non-linear\nand highly dependent on dataset characteristics, and thus flexible approaches are often\nnecessary. In addition, we have now included total particle numbers for each 3D class in\nSup. Fig. 6, for transparency.\n-Scale bars should be added to all micrographs.\nResponse: Scale bars have been added to the micrographs present in Sup. Figure 6.\n-3DFSC plots should be included for each map so that map anisotropy can be assessed.\nResponse: 3DFSC plots have been included for each map in Sup. Figure 6.\n5. Electrophysiology data reporting\n-For most electrophysiological experiments, “n ≥ 3” is listed as the number of replicates.\nFor clarity and full transparency, the explicit number of repeats for each condition should be\nstated in all figure legends and results.\nResponse: For all electrophysiology data we have reported the minimum number of repeats\nin the figure legends, as is common for publications using this technique. We have\nadditionally displayed the explicit number of repeats for each condition within the figures,\ndependent on the type of data being depicted.\nFor all electrophysiology data, we have included a figure in the supplementary\nmaterial that includes a table displaying all numerical information for each condition,\nincluding the explicit number of repeats (example: Sup. Figure 22).\nAdditionally, for all electrophysiology data represented as bar graphs we have\ndisplayed the individual data points on the graphs. This provides greater transparency as it\nvisually presents the number of replicates, as well as the spread of the data (examples:\nFigure 6 panels C and F).\nAs all figures with functional electrophysiology data contain multiple single and triple\nmutants, listing all mutations and their exact number of replicates would be too extensive.\nWe believe the current display method to be su6icient, with all numerical information\nprovided clearly in supplementary figure 22.\nMinor Points:\n-In Figure 5, please include all color definitions and legend details within the figure itself to\nfacilitate interpretation.\nResponse: The legend for Figure 5 provides a comprehensive explanation of all the colors\npresent in the figure, along with their respective meanings.\nReferences\n1. Bick, T., Dominiak, P. M. & Wendler, P. Exploiting the full potential of cryo-EM maps.\nBBA Adv. 5, 100113 (2024).\n2. Nemecz, Á. et al. Full mutational mapping of titratable residues helps to identify\nproton-sensors involved in the control of channel gating in the Gloeobacter violaceus\npentameric ligand-gated ion channel. PLoS Biol. 15, e2004470 (2017).\n3. Ruan, Z., Osei-Owusu, J., Du, J., Qiu, Z. & Lü, W. Structures and pH-sensing\nmechanism of the proton-activated chloride channel. Nature 588, 350–354 (2020).\n4. Osei-Owusu, J. et al. Molecular determinants of pH sensing in the proton-activated\nchloride channel. Proc. Natl. Acad. Sci. 119, e2200727119 (2022).\n5. Mounsey, K. E. et al. Molecular characterisation of a pH-gated chloride channel from\nSarcoptes scabiei. Invertebrate neuroscience : IN 7, 149–156 (2007)."}, {"round": 2, "reviewer_comments": {"reviewer_1": "Overall, the manuscript has improved.\nHowever, among the corrections that were asked for, some have been correctly addressed and some were not satisfactorily\naddressed or simply misunderstood.\nHere is a point by point answer to the rebuttal.\n1. Experimental details on how the APBS calculation was done.\nAnswers are mostly OK and the Mat and Methods section has been indeed updated.\n2. Providing the ionic density maps from APBS\nThe authors have misunderstood the question.\nThe map that was asked for is NOT the experimental cryo-EM map, but the calculated APBS map for the electric potential\n\\phi(r)\nFrom this map, the ionic density can be inferred since \\rho+(r)=e \\phi(r)\nand \\rho-(r)= -e \\phi(r). Contouring the map with positive and negative threshold will reveal the\nions density. Moreover, the sign of \\phi(r) on the pore axis will become observable.\nIts value on the surface of the protein is not what matters most.\nThe detailed instructions on how to get this map can be found in the APBS on-line manual:\nhttps://apbs.readthedocs.io/en/latest/using/examples/visualization-pymol.html#visualize-the-results\nThe authors should provide the \\phi(r) map, as contoured by Pymol, with both positive and negative contours. This will allow\nto see how the surface of the entrance of the channel is screened by counter ions and, hopefully, allow to understand why it\nlets anions go through on the pore axis.\n-Selecting residues for an active role in the pH-driven transition\nThe authors have not correctly addressed the question.\nUsing propKa and its predicted pKa values of ionizable residues for selecting potential residues implicated in the gating\nmechanism is simply not correct. PropKa is mostly a geometrical method to determine the pKa, and can be grossly\ninaccurate.\nOther methods based on the calculation of the electric potential by solving the Poisson-Boltzmann equation, such as the\nFDDH method by J. Warwicker and colleagues, are more physically sound, accurate and freely available. They represent\nthe state-of-the-art.\nA recent application of this methods to two anionic pLGICs (GABA-R and GlyR) is described in this article:\nhttps://pubmed.ncbi.nlm.nih.gov/37570721/\nMost of the statements of the rebuttal in this section are in contradiction with the conclusions of the above-cited article.\nFor instance\n-Buried histidines are also sensitive to pH\n-Asp can be as important as Glu (Fig. 5)\n-Arg (whose intrinsic pKa is way above the pH_50) can be important too (Fig 6), so probably Lys too\n-Tyr can be important too\nRestricting the list to His and Glu residues is simply not understandable.\nAltogether, the rules followed by the authors to select residues to mutate in order to probe their role in the transition seems\nrather arbitrary, and does not take into account state-of-the-art available methods (such as FDDH).\nMy advice would be to state plainly that this is a preliminary study on the mechanism of the pH-driven transition and that a\nmore complete study will be needed to understand this mechanism, and eliminate from the text the claims that this\nmechanism has been \"revealed\".\n-Role of cysteines\nOK, if the cysteines are either in the trans-membrane region or involved in disulfide bridges\nthey are probably not involved in the transition\nPossible advice: The authors should look at hydrogen bonds and ion pairs (salt bridges) that can be broken at higher pH,\nin the open form. Salt-bridges that exchange partners in the two forms are generally very informative in the pLGIC family.\n-Zn++ or Ca++ roles\nOK\n-Comparison with SteLIC\nOK\n-References\nI did not see the Shahsavar et al. reference included in the corrected manuscript?\nConclusion:\nAs it stands, while the structural results are solid and interesting, this study represents only a very preliminary attempt to\nidentify the residues involved in the pH-driven transition.\nI do not agree that the mutants presented \"reveal the mechanism of the pH-sensitivity\"\nnor on the sentence of the Abstract below:\n\"Structure-based analysis and mutagenesis highlighted extracellular histidine and glutamate residues\nwhich act as pH-sensors, revealing the protonation-dependent gating mechanism.\"\nwhich kind of implies that the authors have identified all the pH-sensors.\nThe results presented identify some of the possible pH-sensors -there are probably others-\nand they do no \"reveal\" the protonation-dependent gating mechanism.\nA much more in-depth study would be necessary to claim this.\nThe Abstract and the Discussion should be rewritten accordingly.", "reviewer_2": "Thank you to the authors for their work on the revision. The manuscript has substantially improved.\nHowever, there is no basis for the side chain modeling and placement in the pH 6.5 closed map; this is confirmed by the\nsupplementary figure 8a. The authors need to make this limitation much more clear in the text, or alternatively improve their\nimage processing or collect additional data."}, "author_response": "REVIEWER COMMENTS\nReviewer #1 (Remarks to the Author):\nOverall, the manuscript has improved.\nHowever, among the corrections that were asked for, some have been correctly addressed\nand some were not satisfactorily addressed or simply misunderstood.\nHere is a point by point answer to the rebuttal.\n1. Experimental details on how the APBS calculation was done.\nAnswers are mostly OK and the Mat and Methods section has been indeed updated.\n2. Providing the ionic density maps from APBS\nThe authors have misunderstood the question.\nThe map that was asked for is NOT the experimental cryo-EM map, but the calculated APBS\nmap for the electric potential \\phi(r)\nFrom this map, the ionic density can be inferred since \\rho+(r)=e \\phi(r)\nand \\rho-(r)= -e \\phi(r). Contouring the map with positive and negative threshold will reveal\nthe\nions density. Moreover, the sign of \\phi(r) on the pore axis will become observable.\nIts value on the surface of the protein is not what matters most.\nThe detailed instructions on how to get this map can be found in the APBS on-line manual:\nhttps://apbs.readthedocs.io/en/latest/using/examples/visualization-pymol.html#visualize-\nthe-results\nThe authors should provide the \\phi(r) map, as contoured by Pymol, with both positive and\nnegative contours. This will allow to see how the surface of the entrance of the channel is\nscreened by counter ions and, hopefully, allow to understand why it lets anions go through\non the pore axis.\nResponse: We thank the reviewer for the clarification. Following the reviewer’s guidance, we\ngenerated the Electrostatic isocontour visualization from the APBS-calculated potential map. This\nrepresentation now reveals the spatial distribution of the electrostatic potential φ(r) and is clearly\nobservable along the pore axis, as requested. At the entrance of the ECD pore, the surface potential\nvisualization shows a strong negative electrostatic potential (φ < 0), which would, from a physics\nstandpoint, repel anions and attract cations. In the electrostatic isocontour visualization, we\nobserved similar results. Nonetheless, chloride conduction is possible due to the local pore\ngeometry, the presence of water molecules, and screening by counterions, which modulate the\npotential along the conduction path. The new visualization, Electrostatic isocontour, has been\nincluded in the supplementary figure 20, together with the Surface potential visualization. In\naddition, a brief explanation was added to the manuscript (lines 345-352).\n-Selecting residues for an active role in the pH-driven transition\nThe authors have not correctly addressed the question.\nUsing propKa and its predicted pKa values of ionizable residues for selecting potential\nresidues implicated in the gating mechanism is simply not correct. PropKa is mostly a\ngeometrical method to determine the pKa, and can be grossly\ninaccurate.\nOther methods based on the calculation of the electric potential by solving the Poisson-\nBoltzmann equation, such as the FDDH method by J. Warwicker and colleagues, are more\nphysically sound, accurate and freely available. They represent the state-of-the-art.\nA recent application of this methods to two anionic pLGICs (GABA-R and GlyR) is described\nin this article: https://pubmed.ncbi.nlm.nih.gov/37570721/\nMost of the statements of the rebuttal in this section are in contradiction with the\nconclusions of the above-cited article.\nFor instance\n-Buried histidines are also sensitive to pH\n-Asp can be as important as Glu (Fig. 5)\n-Arg (whose intrinsic pKa is way above the pH_50) can be important too (Fig 6), so\nprobably Lys too\n-Tyr can be important too\nRestricting the list to His and Glu residues is simply not understandable.\nAltogether, the rules followed by the authors to select residues to mutate in order to probe\ntheir role in the transition seems rather arbitrary, and does not take into account state-of-\nthe-art available methods (such as FDDH).\nResponse: We fully acknowledge and agree with the reviewer that the FDDH approach (within\nProtein-Sol pKa module), combining Poisson-Boltzmann calculations with Debye–Hückel theory,\noffers a physics-based, rigorous framework. It identifies pH-dependent stabilizing vs. destabilizing\nresidues and predicts pKₐ shifts based on physics rather than empirical rules. As so, it can\npotentially reveal a buried “pH-sensor residue” whose protonation state modulates channel\nfunction with a more pronounced mechanism.\nAt the same time, PROPKA remains an empirical but widely used tool for simply\npredicting residue pKₐ values in protein structures. Nonetheless, it is highly cited and well-\nestablished in the literature (e.g., ref. PROPKA3: consistent treatment of internal and surface\nresidues in empirical pKa predictions, >3,500 citations). PROPKA is also commonly used\nalongside APBS calculations (via PDB2PQR) and has been successfully applied to identify\nionizable residues in other pH-sensitive channels, as for example the proton-activated chloride\nchannel (Nature, 2020), supporting its use as an initial, rapid screening tool.\nImportantly, in our study, PROPKA predictions were interpreted as part of a broader,\nthorough structural analysis, rather than as a standalone determinant. Candidate residues likely\ninvolved in pH-sensing and gating in SsCl were identified through an integrated approach that\nincluded: (i) PROPKA-predicted pKₐ values and solvent exposure; (ii) comparative structural\nanalysis between pH 6.5 and pH 9; and (iii) insights from related pH-sensitive channels. In\nparticular, we focused on residues showing state-dependent shifts in predicted pKₐ between pH 6.5\nand 9, accompanied by changes in solvent exposure or burial, which suggest potential side-chain\nrearrangements and/or new interactions. This analysis highlighted a cluster of residues within the\nbinding-like region described in the manuscript. This region is known to be functionally relevant\nin other pLGICs. Altogether, we therefore decided to focus on this site, and mutagenesis was\nprioritized mainly for the residues within this region to investigate both the pH-sensing mechanism\nand its role in gating.\nWe agree that residues beyond histidines and glutamates, including buried or partially\nburied residues, can also contribute to pH-dependent transitions. In fact, changes in pH impact\nproteins in general. Specifically for pH-activated channels, pH changes likely propagate through\na network of interactions that influence the global conformational transition to gating, as described\nin the manuscript. Our approach was therefore designed to prioritize residues supported by our\nintegrated analysis, rather than to predict all functionally relevant sites definitively. Moreover, we\nare describing what may be just the initial cascade of pH-dependent conformational changes that\nwill further impact a more critical residue, a buried ionizable one, for example. For clarity, we\nadded an paragraph to the manuscript (lines 365-370) and updated the method to provide more\ndetails of our analysis.\nMethod section (lines 668-684).\nMy advice would be to state plainly that this is a preliminary study on the mechanism of the\npH-driven transition and that a more complete study will be needed to understand this\nmechanism, and eliminate from the text the claims that this mechanism has been\n\"revealed\".\nResponse: We agree with the reviewer's advice, and the manuscript was adjusted accordingly.\n-Role of cysteines\nOK, if the cysteines are either in the trans-membrane region or involved in disulfide bridges\nthey are probably not involved in the transition\nPossible advice: The authors should look at hydrogen bonds and ion pairs (salt bridges) that\ncan be broken at higher pH, in the open form. Salt-bridges that exchange partners in the\ntwo forms are generally very informative in the pLGIC family.\nResponse: We had conducted a detailed investigation during structural analysis, and this is\nalready described in the section “Structural basis for pH-sensing and channel activation”.\n-Zn++ or Ca++ roles\nOK\n-Comparison with SteLIC\nOK\n-References\nI did not see the Shahsavar et al. reference included in the corrected manuscript?\nResponse: The reference was added to the manuscript (line 109).\nConclusion:\nAs it stands, while the structural results are solid and interesting, this study represents only\na very preliminary attempt to identify the residues involved in the pH-driven transition.\nI do not agree that the mutants presented \"reveal the mechanism of the pH-sensitivity\"\nnor on the sentence of the Abstract below:\n\"Structure-based analysis and mutagenesis highlighted extracellular histidine and glutamate\nresidues\nwhich act as pH-sensors, revealing the protonation-dependent gating mechanism.\"\nwhich kind of implies that the authors have identified all the pH-sensors.\nThe results presented identify some of the possible pH-sensors -there are probably others-\nand they do no \"reveal\" the protonation-dependent gating mechanism.\nA much more in-depth study would be necessary to claim this.\nThe Abstract and the Discussion should be rewritten accordingly.\nResponse: We agreed with the reviewer, and the manuscript was updated accordingly.\nReviewer #2 (Remarks to the Author):\nThank you to the authors for their work on the revision. The manuscript has substantially\nimproved.\nHowever, there is no basis for the side chain modeling and placement in the pH 6.5 closed\nmap; this is confirmed by the supplementary figure 8a. The authors need to make this\nlimitation much more clear in the text, or alternatively improve their image processing or\ncollect additional data.\nResponse: We agree with the reviewer. The manuscript was updated to make it clearer the\nlimitation of this dataset due to low resolution (lines 140-145; lines 249-254)."}, {"round": 3, "reviewer_comments": {"reviewer_1": "I am satisfied with the answers from the authors.\nThe paper is OK now.", "reviewer_2": "The authors have addressed my concerns."}, "author_response": ""}]

Decision letter