Ori Frid
email: fridori@gmail.com

Shahar Malamud

Antonio Di Franco

Paolo Guidetti

Ernesto Azzurro

Joachim Claudet

Fiorenza Micheli

Ruth Yahel

Enric Sala

Jonathan Belmaker

Marine protected areas' positive effect on fish biomass persists across the steep climatic gradient of the Mediterranean Sea

Keywords: MPAs, Fish, biomass, Mediterranean Sea, warm waters, effectiveness

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Introduction

Climate change has substantial implications for biodiversity, ecosystem functioning, and human wellbeing [START_REF] He | Climate Change, Human Impacts, and Coastal Ecosystems in the Anthropocene[END_REF][START_REF] Pinsky | Climate-Driven Shifts in Marine Species Ranges: Scaling from Organisms to Communities[END_REF]. Ocean warming is causing changes in fish size, species distributions, and community composition, as well as declines in fish biomass [START_REF] Lotze | Global ensemble projections reveal trophic amplification of ocean biomass declines with climate change[END_REF]Cheung et al. 2012;[START_REF] Van Rijn | Large but uneven reduction in fish size across species in relation to changing sea temperatures[END_REF][START_REF] Pinsky | Climate-Driven Shifts in Marine Species Ranges: Scaling from Organisms to Communities[END_REF].

Marine Protected Areas (MPAs) can help recover and sustain marine life [START_REF] Edgar | Global conservation outcomes depend on marine protected areas with five key features[END_REF]Reimer,et al 2021;[START_REF] Sala | No-take marine reserves are the most effective protected areas in the ocean[END_REF][START_REF] Grorud-Colvert | global goals for the ocean[END_REF] and continue to be advocated under climate change as they have been suggested to increase ecosystem resilience and resistance [START_REF] Rilov | A fast-moving target: achieving marine conservation goals under shifting climate and policies[END_REF]Roberts, et al., 2017;[START_REF] Wilson | Incorporating climate change adaptation into marine protected area planning[END_REF]. However, empirical evidence regarding MPAs ability to mitigate climate associated changes is limited [START_REF] Freedman | Marine protected areas do not prevent marine heatwave-induced fish community structure changes in a temperate transition zone[END_REF][START_REF] Bruno | Climate Change, Coral Loss, and the Curious Case of the Parrotfish Paradigm: Why Don't Marine Protected Areas Improve Reef Resilience[END_REF][START_REF] Bates | Climate resilience in marine protected areas and the 'Protection Paradox[END_REF][START_REF] Mellin | Marine protected areas increase resilience among coral reef communities[END_REF][START_REF] Bates | Resilience and signatures of tropicalization in protected reef fish communities[END_REF]. Thus, it remains unclear how climate interacts with MPAs to impact fish biomass, and whether MPAs can remain a valid conservation tool in the future.

There are a variety of hypotheses that might explain how MPA impact on fish biomass would change with increasing sea temperatures. Starting with a single species, we expect higher abundance and biomass under moderate temperatures, where thermal conditions are favorable, and decreases in abundance towards more extreme conditions towards the range edge [START_REF] Waldock | The shape of abundance distributions across temperature gradients in reef fishes[END_REF][START_REF] Yancovitch Shalom | A closer examination of the 'abundant centre' hypothesis for reef fishes[END_REF]. The mechanisms leading to this decrease in abundance towards the warm edge of species ranges may stem from thermal limitation on growth, survival, and fecundity, but also from altered biotic interactions such as higher predation rates or more severe competition (Paquette and Hargreaves 2021).

We outline three potential scenarios on how a gradient in thermal conditions may interact with protections from fishing:

(1) MPAs are less effective at warmer temperatures (Fig. 1A). While inside MPAs we may observe biomass decreases as water temperature increases, outside of MPAs fishing may consistently reduce fish biomass. This may lead to low biomass outside of MPAs regardless of temperature. Hence, the difference between fished and non-fished sites will decrease as water temperature increases (Fig. 1A). Note, that this scenario is dependent on high fishing pressure outside of the MPAs but is independent of the exact mechanisms leading to reduced biomass with higher temperature inside MPAs.

(2) MPAs are more effective at warmer temperatures. MPAs are hypothesized to may support both resistance and recovery from disturbances (Roberts et al., 2017;[START_REF] Wilson | Incorporating climate change adaptation into marine protected area planning[END_REF][START_REF] Duffy | Biodiversity enhances reef fish biomass and resistance to climate change[END_REF]. Warming waters is a major disturbance impacting marine systems, and its impact can be associated with acute heat waves (Bosch et al., 2021, Garrabou et al., 2022) but also with persistently warm water placing individuals under constant thermal stress.

Higher resilience within MPAs in face of waring could be due to many processes within MPAs including the presences of older, bigger and less sensitive individuals, more intact trophic food webs influencing the strength of trophic cascades or increased in ecosystem function via increased diversity [START_REF] Bates | Climate resilience in marine protected areas and the 'Protection Paradox[END_REF][START_REF] Bruno | Climate Change, Coral Loss, and the Curious Case of the Parrotfish Paradigm: Why Don't Marine Protected Areas Improve Reef Resilience[END_REF], Brandel et al., 2019, Lefcheck1 et al., 2019). All these mechanisms will cause higher relative increase in biomass within MPAs compared to fished areas in regions that are already subject to high water temperatures compared to more moderate conditions where fishing is the only stressor (Fig. 1B).

(3) Biomass decreases with warming water at similar rates both in MPAs and in fished areas (Fig. 1C). This would happen if the physiological or biotic constraints limiting biomass with warming do not interact with the effects of fishing. The relative support for these hypotheses has never, to the best of our knowledge, been tested. The scenarios outlined above are formulated at the species-level and extending these to the community-level, adds another level of complexity. Even across the same temperature gradient different species may have divergent thermal preferences and different range dynamics, leading to multiple community level patterns. Thus, total community level biomass may either decline or increase with temperature, depending on species identity and species turnover [START_REF] Free | Impacts of historical warming on marine fisheries production[END_REF][START_REF] Lotze | Global ensemble projections reveal trophic amplification of ocean biomass declines with climate change[END_REF][START_REF] Cheung | Signature of ocean warming in global fisheries catch[END_REF][START_REF] Tittensor | higher climate risks for marine ecosystems[END_REF][START_REF] Duffy | Biodiversity enhances reef fish biomass and resistance to climate change[END_REF]Moullec et al. 2019). Moreover, it is clear that different species display different sensitivity to fishing (Cheung et al. 2005). If, across species, the traits related to fishing sensitivity and those related to warm-water resilience are independent [START_REF] Bates | Climate resilience in marine protected areas and the 'Protection Paradox[END_REF] we may expect scenario C in which biomass changes with warming at similar rates both in MPAs and in fished areas. However, covariation between these traits may lead to alternative scenarios. Thus, when species most sensitive to warming are also most sensitive to fishing, we will observe scenario A (MPAs are less effective at warmer temperatures) and when species most sensitive to warming are least sensitive to fishing, we will observe scenario B (MPAs are more effective at warmer temperatures). Elucidating both the speciesand community-level patterns is critical for understanding how protection and temperature gradients interact.

In this study, we examined these three scenarios using extensive fish surveys carried out within and outside Mediterranean MPAs. The Mediterranean Sea is particularly relevant to study the effects of climate on marine species. Many Mediterranean fishes are of North Atlantic origin, and hence adapted to temperate climates which puts them under elevated risk from climate change [START_REF] Pita | Contrasted patterns in climate change risk for Mediterranean fisheries[END_REF]Marbà et al., 2015;[START_REF] Albouy | Projected climate change and the changing biogeography of coastal Mediterranean fishes[END_REF][START_REF] Coll | The Mediterranean Sea under siege: Spatial overlap between marine biodiversity, cumulative threats and marine reserves[END_REF][START_REF] Givan | Thermal affinity as the dominant factor changing Mediterranean fish abundances[END_REF][START_REF] Guidetti | Large-scale assessment of mediterranean marine protected areas effects on fish assemblages[END_REF]. In addition, the Mediterranean Sea has a large range of sea temperatures, with a high of 28C • (annual average) at its easternmost basin (Elgeziry, 2021) (Fig. 2). This unique blend of mostly cold-water species across a steep climatic gradient allows us to examine the variation in fish biomass gains associated with MPAs across multiple seawater temperatures. The results can help us understand whether MPAs can offset the impacts of climate on fish biomass and thus continue to be an important management tool in future oceans.

Methods

Study sites

We sampled fish assemblages in 52 rocky reef sites across the Mediterranean Sea (Fig. 2).

The data was aggregated across three main survey teams (Fig. A1) using similar methods (see expansion on survey methods in Supplementary material). Importantly, as sampling by each team was geographically dispersed (Fig. A1) we do not expect geographic biases related to sampling. Sampling sites were confined to rocky reef habitats and fished and MPA sites covered similar habitats and depths. MPAs ranged in size between 84 and 50,000 ha (mean description of the sampling sites see Supplementary material.

Sites were initially classified as either 'fully protected' MPAs (all fishing activities forbidden and enforced, n=9), 'intermediate protection' MPAs (most fishing activities regulated and enforced, n=10), 'non-enforced' MPAs (n=8), or 'fished' (n=25). However, we did not find a significant difference in biomass between 'intermediate protection' and 'fully protected' MPAs, so we combined and re-classified them as 'Protected' (Fig. A2). While we did not find significant differences between full and intermediate protection, fully protected MPAs do appear to have higher biomass as found in other studies [START_REF] Sala | No-take marine reserves are the most effective protected areas in the ocean[END_REF].

Therefore, this re-classification was only done to increase sample size and, thus, the power of the analyses. Using only fully protected MPAs did not change the main results (i.e., we still could not find an interaction between temperature and protection, see below). 'Non-enforced' MPAs (n=8) are regularly fished. Thus 'Non-enforced' MPAs and fished areas (n=25) were re-classified as 'Fished'.

Size and age of MPAs are known to significantly affect MPA in terms of safeguarding fish biomass [START_REF] Edgar | Global conservation outcomes depend on marine protected areas with five key features[END_REF][START_REF] Claudet | Marine reserves: Size and age do matter[END_REF] and were used as covariates in the analyses (see below). Importantly, neither MPA size nor age displayed clear gradients across the Mediterranean or with mean temperature (correlations between MPA size and age to temperature were r = 0.118 and r = -0.07, respectively). We note that our goal was not to explore these patterns in depth, but rather to assure that the results are not an artifact of hidden gradients in MPA size or age across the Mediterranean that may be mistakenly interpreted as associated with climatic gradients.

Sampling

We performed underwater visual surveys to characterize fish assemblages using 25 x 5m belt transects and documenting fish identity, abundance, and size. Sampling was conducted in seasons where temperatures are suitable for diving, mostly summer. A total of 1,891 transects were sampled; the number of transects within each site varied between 9 and 138. We account for the unbalanced sampling design in the analyses (see below). Size was later converted to biomass using species-specific Mediterranean-based length-weight relationships (W = aL b ) gathered from FishBase (Froese and Pauly 2021). We included all species identified to species level (with the exception of Mugilidae and Atherinidae which are difficult to identify to species level underwater) and excluded cryptic species such as families Gobidae and Blennidae that are generally underestimated by visual censuses. Transects took place along rocky substrate at depths of 3-30m.

Although the Mediterranean Sea suffers from a high number of non-indigenous species, their abundance in our data was extremely low (8%). Moreover, these non-indigenous species are concentrated in the Levantine Basin which comprise only a small fraction of the area surveyed, and their community level impacts have been shown to be small [START_REF] Buba | Native-exotic diversity relationships for eastern mediterranean fishes reveal a weak pattern of interactions[END_REF][START_REF] Arndt | Shifts in eastern mediterranean fish communities: Abundance changes, trait overlap, and possible competition between native and non-native species[END_REF][START_REF] Givan | Thermal affinity as the dominant factor changing Mediterranean fish abundances[END_REF]Buba et al., 2017). Finally, all observed patterns were robust to inclusion or exclusion of these species.

Broad scale environmental data

For each site we extracted the following environmental variables: minimum annual temperature (C°, Tmin), mean annual temperature (C°, Tmean), maximum annual temperature (C°, Tmax), Primary Production (mgC•m-²•/day/cell), and Chlorophyll-a concentration (mg/m³). We downloaded environmental data from GMED (http://gmed.auckland.ac.nz/). This site provides sea surface temperature of the topmost m of the ocean water column, collected by remote sensing and at a resolution of 9.2 km.

To reduce potential small spatial-scale variability bias, we used average values within a radius of 15km from the site center. We used current values of these environmental variables and did not attempt to match values to the time of sampling as temporal changes over the time period examined are small relative to the large variability in these values across the Mediterranean (e.g., Tmean range was 6 °C, compared to maximal change of 0.32 C° over time within the range of periods examined (2003[START_REF] Ban | Fishing communities at risk[END_REF][START_REF] García-Monteiro | Surface Temperature trends in the Mediterranean Sea from MODIS data during years 2003-2019[END_REF].

We examined which environmental variables (Chlorophyll -a Primary Production, Tmin, Tmax, and Tmean) best explained transect-level biomass using Generalized Linear Models (GLMs) using fish biomass as a response, followed by calculating variable relative importance ("relaimpo" package in R). To identify the prime environmental variables for species-level occurrence we used 'MaxEnt' (Maximum Entropy) based species-distribution models, and then compared the relative importance of the environmental variables. With both methods, and across all species, temperature predictors (Tmin, Tmean and Tmax) contributed most to the explained variation. To avoid co-linearity, we used Tmean as our main temperature predictor in further analyses (Fig. A3).

Fishing pressure

Direct fishing pressure is hard to quantify, thus we estimated it using three different methods:

(1) First, we calculated the Gravity index, which was recently shown to be a reliable predictor of fishing pressure [START_REF] Cinner | Gravity of human impacts mediates coral reef conservation gains[END_REF]. To do so we downloaded human population density maps from NEO-NASA earth observation (https://neo.sci.gsfc.nasa.gov/about/; pixel resolution1 km 2 ). We divided the value of all pixels within a 150-km radius from each sampling point (a realistic travel distance for coastal fishers) by the squared distance to the point. Other radii gave similar results (50, 100, and 500 km). ( 2) Second, we calculated Catch per Km Coastline by extracting total fished tonnage of 'perch-likes' fish (most species in our data) by country along the Mediterranean coast. As this index is based on actual fish removed, albeit at coarse resolution, this is the only index directly related to catch and not to effort. Data were based on The Sea Around Us project (www.seaaroundus.org/data/#/topic/biodiversity), and are composed of catch reported to the UN Food and Agriculture Organization (FAO) operated by GFCM (General Fisheries Commission for the Mediterranean). GFCM has the biggest and most reliable fishing data repository available for the Mediterranean Sea that includes data from all countries included in our analysis. We then compiled data on Mediterranean coastlines from the (FAO) (www.fao.org), the CIA World Factbook (www.cia.gov/library/publications/the-worldfactbook), and Google Maps. We divided the tonnage fished in each country by their Mediterranean coastline to create an index of Catch per km Coastline [START_REF] Shapiro Goldberg | Original Article Decreases in length at maturation of Mediterranean fishes associated with higher sea temperatures[END_REF]. ( 3) Third, we used Distance from Port, downloaded from GMED and based on data from the National Geospatial intelligence Agency (https://msi.nga.mil/Publications/WPI). This data includes both large and small ports. Small ports were important to include in this indicator of fishing pressure as the sites surveyed in this study are mostly impacted by local coastal fishers, who often operate from very small ports.

Species-level traits

Climatic Affinity indicates the environmental conditions most suitable for each species. These values are based on the preferred temperature of the species which was estimated using species distribution models (including depth, salinity, temperature, and primary production).

We base our estimates on the Climatic Affinity values extracted from FishBase (Froese and Pauly 2021).

Sensitivity to fishing may explains species response to protection, with sensitive species displaying higher benefits. Intrinsic sensitivity to fishing was based on the vulnerability index (extracted from FishBase). This index is calculated using fuzzy logic, integrating life history and ecological characteristics of marine fishes including intrinsic rate of increase, longevity, age at first maturity, fecundity, and the von Bertalanffy growth parameter, K (Cheung et al. 2005).

Statistical analyses

Community level analyses

We first tested how assemblage-level biomass changes with protection (binary, yes/ no), depth, fishing pressure indices (Gravity, Catch per Km Coastline, Distance from Port), and across environmental gradients. To avoid over parametrized models, we considered each of the three fishing pressure indices separately. We did not include MPA age and size in these analyses as these values are not available outside MPAs. However, these were included in other analyses (see cross-species analysis below).

Our focus was on detecting to what extent temperature (Tmean) interacts with protection, to determine if protection influences fish assemblages differently at different locations along the temperature gradient (Fig. 1A andB). We used GLMMs (generalized linear mixed-effect models) using transect-level total biomass (log transformed) as a response. Site was included as a random effect to account for non-independence of transects within each site. Thus, the full model formula was as follows: log (Biomass) ~ protection x Tmean + depth +primary production + fishing pressure index +random (site)

While linear models are generally robust, highly uneven sampling designs may still bias results. In our case, we sampled many more transects along the Israeli coast than in other locations. Thus, we randomly sampled nine transects (the lowest number of transects in a site) in each site to create a new data set with a balanced sampling design. We then ran transect level analyses (see below) on 1,000 random iterations of the balanced data and presented the average values across these iterations.

We further tested spatial simultaneous autoregression (SAR) models at the site level to account for spatial proximity (function spautolm from the "spdep" R package). We examined a range of possible neighborhood sizes (400-2000 km) and chose the neighborhood size with the lowest AIC score (2000 km). However, adding the SAR component did not change the results (Table A1).

We also calculated weighted climatic affinity [START_REF] Cheung | Signature of ocean warming in global fisheries catch[END_REF], which represents the mean temperature preferences of the entire assemblage, by taking the Climatic Affinity weighted by the biomass of the species within the transect. Weighted climatic affinity is used to estimate changes in community composition associated with altered thermal preferences.

Model structure and statistical tests were similar to those used for biomass, and the focus was on estimating whether the effect of Tmean on weighted climatic affinity changes with protection.

Species level analyses

We repeated the community-level GLMM analyses at a species level, using transect-level biomass for each species. Tweedie models were used to deal with the zero inflated data (Shono 2008). We also estimated variable relative importance, quantified as the contribution of each variable to the R 2 of the model (calc.relimp function from the "relaimpo" R package). This analysis does not support random effects; thus, we could not include site in the relative importance models. The full model formula was as follows:

log (Species level biomass) ~ protection x Tmean + depth +primary production + fishing pressure index

Cross-species analysis

We were interested in understanding what explains both species-and site-level responses to protection. Thus, we separated the data into paired protected and fished sites, then calculated the log-ratio of biomass in protected vs. fished sites as a species-specific and site-specific effect size. This was done only for common species (>30 observations) (Table A2). We paired protected and fished sites by country, similar habitat, sampling procedures, and locations within 400 km of each other (88km ± 103, mean ± SD). Not all sites had such pairs, so we restricted our analyses to 17 paired sites (Fig. A1B). As the number of transects varied in both protected and fished sites, we calculated the pooled standard deviation of the log-ratio (Spooled) based on the sampling effort. The reciprocal of Spooled was used as a weighting factor.

We used GLMMs to investigate whether log-ratio values were affected by Tmean and species-level traits. Under the scenarios of higher biomass in MPAs in either moderate (Fig. 1A) or extreme conditions (Fig. 1B), we would expect an interaction between Tmean and species-level Climatic Affinity. As the effect of protection is expected to vary across species, we added Sensitivity to Fishing as an additional species-level predictor. Site level predictors included one of the three fishing pressure indices (Gravity, Catch per Km Coastline, Distance from Port), MPA area (log transformed), MPA age, and Primary Production. Species (as they appear multiple times at different sites) and site-pair (as multiple species are examined in each) were modeled as random effects. The full model formula was as follows:

Log-ratio ~ Tmean x climatic affinity + Sensitivity to Fishing+ Fishing pressure index + MPA area + MPA age + Primary Production+ random (species) + random (site)

Results

We surveyed a total of 1,891 transects over rocky habitats along 52 protected and fished sites.

Our first aim was to detect whether and to what extent seawater temperature (mean annual temperature; C°, Tmean) interacts with protection when explaining assemblage-level biomass (Fig. 1). We found that both Tmean and protection had a significant effect (p < 0.05) on overall community-level biomass. Biomass decreased with higher Tmean and was higher in protected compared to fished sites (Fig. 3A). Across the Mediterranean, the overall change in biomass associated with protection (37% higher biomass in protected relative to fished areas, on average) was similar to that of temperature (27% higher biomass at 16°C compared to 22°C, the lowest and highest Tmean across the gradient). However, the interaction between protection and Tmean was non-significant. These patterns remained even when fishing pressure (using the indices Catch per km Coastline, Distance from Port, and Gravity), productivity (Primary Production), and spatial autocorrelation were accounted for (Tables A1,A3). We did not find clear evidence of an interaction between protection and temperature suggesting that MPA effectiveness, in relation to increasing overall fish biomass, remains constant across the temperature gradient examined (scenario C; Fig. 1).

Second, we assessed how different seawater temperatures could impact the fish community composition, and whether this changed in response to protection. To test for a thermal signature at the community level, we calculated a weighted climatic affinity index based on the estimated thermal preference of each species ('Climatic Affinity') weighted by the species relative abundance. It is possible that protection leads to increased overall biomass but does not buffer against unfavorable climate change. In this case, we expected MPAs to have little impact on community composition in terms of weighted climatic affinity. On the other hand, if protection also acts as a climate refuge, MPAs may disproportionately support species with lower climatic affinity compared to fished sites. This could be observed as a significant interaction between protection and temperature. We found support for the former pattern; although temperature had a clear effect on weighted climatic affinity, and hence species composition, we found no interaction with protection (Fig 3B). Thus, protection does not appear to alter the relative thermal preferences of constituent species (Tables A4). Third, we analyzed the change in biomass of 39 species, and found that many species displayed strong responses to temperature (significant for 20 of the 39 species) and protection (significant for 15 species; Table A5). For most species, we observed a decline in biomass with increased Tmean, as observed for Coris julis and Dentex dentex, but some species, such as Epinephelus marginatus or Thalassoma pavo, actually benefit from higher Tmean (Fig. 4).

Interactions between temperature and protection (Tmean-protection interaction; Table A5) varied among species and did not consistently support any specific scenario. Ten species supported scenario A (biomass changes with increased temperature are steeper in protected sites), 5 scenario B (biomass changes with increased temperature are steeper in fished sites), and 24 species scenario C (protection and temperature effects are additive). Importantly, even when an interaction was present, most variation in biomass was explained by Tmean; the interaction between Tmean and protection explained only a small amount of the variation in the data (Fig. 5). Thus, also at the species level, protection did not have a consistently stronger effect in warm or cold waters. Finally, we were interested in understanding why some species responded to protection differently on different sides of the environmental gradient. For example, we expected that MPAs would enhance biomass more at cold temperatures for species with cold-water affinity, and at warm temperatures for species with warm-water affinity. We used the log-ratio of biomass between protected and fished sites as an effect size. This log ratio was not significantly affected by Tmean (Fig. 6A). This means that across all fish species, protection had a similar effect in the warmer and colder areas of the Mediterranean, consistent with the species and community level analyses reported above. Importantly, we did not detect an interaction between Tmean and species-level Climatic Affinity, and thus we find that MPAs benefit both warm and cold-water species similarly across temperatures. Sensitivity to Fishing was the only variable that had a positive significant effect on the log-ratio, indicating that species that are more sensitive to fishing tend to benefit more from protection (Fig. 6B, Table A6). Results were similar when we took Gravity, Catch per km Coastline, Distance from Port, Primary Production, and the size and age of MPAs into account (Table A6).

Discussion

We found that protection is associated with an increase in fish biomass, particularly for fishing-sensitive species. This result is intuitive and expected [START_REF] Edgar | Global conservation outcomes depend on marine protected areas with five key features[END_REF][START_REF] Micheli | Trajectories and correlates of community change in no-take marine reserves[END_REF]. In addition, higher temperatures had a strong negative effect on fish biomass, both at species and community levels. Importantly, we also found that when the community was considered as a whole, the rate of decrease in fish biomass with temperature was similar in protected and fished sites. This suggests that the effect of temperature and protection are additive (scenario C; Fig. 1), and thus that MPA effectiveness does not change with varying climate.

A decline in abundance along the temperature gradient is expected for a number of species [START_REF] Garrabou | Monitoring Climate-related responses in Mediterranean Marine Protected Areas and beyond: ELEVEN STANDARD PROTOCOLS[END_REF] and at the species level, we found a variable response of species to increased temperature and MPAs (Fig. 4). Nevertheless, here we observed that the most of species declined in biomass in warmer waters, and species sensitive to fishing were positively impacted by MPAs. At the same time, most species did not show a significant interaction between temperature and protection (Fig. 5), and we could not find species-level traits that explain why specific species follow each scenario. Hence, despite highly idiosyncratic species-level effects we find little support for the idea that MPAa can buffer against the impacts of warming.

Local decision makers and conservationists have limited management tools since climate change can only be effectively addressed on a global scale. One major management option is to increase the number and size of MPAs [START_REF] Sala | No-take marine reserves are the most effective protected areas in the ocean[END_REF]. However, uncertainty is high around the ability of MPAs to continue to perform as expected under changing climatic conditions [START_REF] Bates | Climate resilience in marine protected areas and the 'Protection Paradox[END_REF][START_REF] Wilson | Incorporating climate change adaptation into marine protected area planning[END_REF]. We show here that extreme temperatures do not undermine the capacity of MPAs to sustain larger fish biomass than fished sites (Fig. While these results are encouraging, we did not find broad evidence that MPAs can offset the relative decrease in fish biomass associated with warmer seawater. Consequently, increasing water temperatures will likely result in an overall decrease in fish biomass, even within MPAs. Further support for the inability of MPAs to mitigate warming is evident from the weighted climatic affinity analysis, as we found similar increases in weighted climatic affinity with increased temperature in fished and protected sites (Fig. 3B). Thus, higher water temperatures lead to species turnover and changes in species composition, the replacement of cold water species by warm water species, independent of protection levels. This implies that thermophilic species will become a more dominant part of fish communities under future seawater warming both within and outside MPAs, as recently illustrated for invasive fishes of tropical origin (D'Amen and Azzurro, 2020). At the same time, the lack of interaction at the community-level between the effect of MPA and temperature suggests that, across species, the traits related to fishing sensitivity and those related to warm-water preferences are independent [START_REF] Bates | Climate resilience in marine protected areas and the 'Protection Paradox[END_REF]. Consequently, although MPAs may maintain higher local biomass of exploited species, they will not be able to offset larger-scale biotic alterations associated with climate.

Marine ecological systems are predicted to suffer from warming water, especially in the Mediterranean Sea [START_REF] Albouy | Projected climate change and the changing biogeography of coastal Mediterranean fishes[END_REF]Giakoumi et al., 2017;[START_REF] Van Rijn | Large but uneven reduction in fish size across species in relation to changing sea temperatures[END_REF][START_REF] Pita | Contrasted patterns in climate change risk for Mediterranean fisheries[END_REF]. With business-as-usual emissions, sea-surface temperatures within MPAs are projected to increase 2.8 °C by 2100 [START_REF] Bruno | Climate change threatens the world's marine protected areas[END_REF] and Mediterranean MPAs are particularly vulnerable to warming [START_REF] Kyprioti | Is the current Mediterranean network of marine protected areas resilient to climate change?[END_REF], Garrabou et al., 2022). We show here that at the community level fish biomass strongly decreases with temperature.

Extrapolating this pattern through time, we may expect dramatic declines in fish biomass in the Mediterranean with additional warming. This is consistent with models predicting significant decreased catch in the Mediterranean under IPCC warming scenarios [START_REF] Cheung | Large-scale redistribution of maximum fisheries catch potential in the global ocean under climate change[END_REF][START_REF] Lotze | Global ensemble projections reveal trophic amplification of ocean biomass declines with climate change[END_REF]. We note that while some studies predict biomass declines with warming [START_REF] Free | Impacts of historical warming on marine fisheries production[END_REF][START_REF] Lotze | Global ensemble projections reveal trophic amplification of ocean biomass declines with climate change[END_REF][START_REF] Cheung | Signature of ocean warming in global fisheries catch[END_REF][START_REF] Tittensor | higher climate risks for marine ecosystems[END_REF] other studies have found fish biomass to be positively related to temperature [START_REF] Duffy | Biodiversity enhances reef fish biomass and resistance to climate change[END_REF]Moullec et al. 2019). This apparent contradiction with our results may stem from three main factors. First, the Mediterranean Sea, where we performed our study, contains mostly cold-water species, which may be particularly sensitive to warm waters [START_REF] Albouy | Projected climate change and the changing biogeography of coastal Mediterranean fishes[END_REF][START_REF] Giakoumi | Assessing the effects of marine protected areas on biological invasions: A global review[END_REF][START_REF] Givan | Thermal affinity as the dominant factor changing Mediterranean fish abundances[END_REF]. Second, the temperatures within the Mediterranean Sea, especially towards the Eastern Mediterranean, are amongst the warmest in the world [START_REF] Ozer | Interannual thermohaline (1979-2014) and nutrient (2002-2014) dynamics in the Levantine surface and intermediate water masses, SE Mediterranean Sea[END_REF] likely reaching the upper thermal threshold for many species [START_REF] Rilov | Multi-species collapses at the warm edge of a warming sea[END_REF]. These warm waters may lead to declines in fish biomass along the progressive loss of climatically suitable habitats, with species living in suboptimal conditions, reaching their physiological limits.

Finally, even within the Mediterranean Sea warming may produce different patterns for different regions and different species groups where large bodies species decline, and small bodies species increase in abundance (Moullec et al. 2019).

The steep spatial temperature gradient across the Mediterranean can be used as a 'space-fortime' substitution to infer climate-driven temporal changes in fish biomass. If the observed links between temperature and fish biomass are causal, then the results can be used to predict temporal changes associated with warming. Indeed, empirical assessments suggest that such an approach produces reliable results [START_REF] Algar | Predicting the future of species diversity: Macroecological theory, climate change, and direct tests of alternative forecasting methods[END_REF][START_REF] Blois | Space can substitute for time in predicting climate-change effects on biodiversity[END_REF][START_REF] White | Contrasting spatial and temporal global change impacts on butterfly species richness during the 20th century[END_REF]. One limitation of this approach is that the spatial patterns explored here focus on mean temperatures and long temporal scales, and do not quantify extreme climatic events at finer temporal scales. This prevented us to consider the effect of marine heat waves (MHW), that In the last 20 years, have globally doubled in frequency and have become more intense, longer-lasting and geographically extended (Frölicher et al 2018;[START_REF] Collins | Extremes, abrupt changes and managing risk[END_REF]Laufkötter et al., 2020). These extreme events are associated with increasing events of mass mortalities all over the world and in the Mediterranean Sea (Garrabou et al., 2022), with cascade effects, which are expected to affect a large number of marine organisms, including fish species. Another limitation is that adaptive responses by species to changing environmental conditions may differ across space and across time.

We also note that dispersal limitations and emergent species interactions may make temporal patterns differ from spatial patterns. However, the limited spatial extent of the Mediterranean, meaning that most species can be found throughout the entire study range, and the strong dispersal ability of marine fish larvae, make these less of a concern.

Our results suggest that protection from fishing should remain an important management tool even at high water temperatures. In addition to increasing fish biomass within their boundaries, MPAs provide additional population-level advantages such as protecting individuals of high reproductive potential [START_REF] Marshall | Underestimating the benefits of marine protected areas for the replenishment of fished populations[END_REF][START_REF] Micheli | Evidence That Marine Reserves Enhance Resilience to Climatic Impacts[END_REF][START_REF] Venturelli | Evidence for harvest-induced maternal influences on the reproductive rates of fish populations[END_REF]) and increased ecosystem resilience [START_REF] Bates | Resilience and signatures of tropicalization in protected reef fish communities[END_REF][START_REF] Mellin | Marine protected areas increase resilience among coral reef communities[END_REF]. However, as protection does not offset the changes in biomass associated with warming, local conservation efforts and regular monitoring (Garrabou et al., 2022) should be accompanied by global efforts to limit climate change. Different MPAs protect different species [START_REF] Blowes | Mediterranean marine protected areas have higher biodiversity via increased evenness , not abundance[END_REF]. Hence a regionally planned network of MPAs, covering large climatic gradients [START_REF] Kyprioti | Is the current Mediterranean network of marine protected areas resilient to climate change?[END_REF][START_REF] Meehan | How far have we come? A review of MPA network performance indicators in reaching qualitative elements of Aichi Target 11[END_REF][START_REF] Claudet | Article Underprotected Marine Protected Areas in a Global Biodiversity Hotspot ll Underprotected Marine Protected Areas in a Global Biodiversity Hotspot[END_REF][START_REF] Rilov | A fast-moving target: achieving marine conservation goals under shifting climate and policies[END_REF], is vital to assure the regional conservation of fish and the ecosystem services they deliver to our societies.

Fig. 1 .

 1 Fig. 1. Schematic representation of three potential scenarios of Marine Protected Area (MPA) effectiveness, in terms of relative fish biomass gains, across a temperature gradient: (A) MPA effectiveness decreases when water temperature increases. (B) MPA effectiveness increases when water temperature increases. (C) No change in MPA effectiveness across a temperature gradient. In all scenarios we assume that total fish biomass decreases with increased temperatures. Arrows within plots illustrate the difference between MPA and fished areas, representing MPA effectiveness.

Fig. 2 .

 2 Fig.2. Sampling sites across the Mediterranean Sea. Colors represent mean annual temperatures (Tmean, °C) Circles represent fished sites and triangles protected sites (MPAs).

Fig. 3 .

 3 Fig. 3. Change in (A) biomass (kg) and (B) weighted climatic affinity (°C) for the entire fish community with mean temperature (Tmean, °C) and protection. (A) Temperature and protection had independent, significant effects on biomass, but no significant interaction was found between temperature and protection. (B) Weighted climatic affinity increased with temperature regardless of protection level. Shaded areas represent 95% confidence intervals.

Fig. 4 .

 4 Fig. 4. Select species' response to temperature and protection. Models represent the species' probability of occurrence. Temperature has a strong effect on species occurrence, but in different directions. Protection usually increased species occurrence probability, especiallyfor targeted species such as Epinephelus marginatus (A). However, across species, protection did not consistently increase probability of occurrence more at cold or warm temperatures.Shaded areas represent 95% confidence intervals.

Fig. 5 .

 5 Fig. 5. Mean relative importance across species (N=15) for which the interaction between temperature and protection was significant. Temperature has the highest effect on species biomass, while the interaction between protection and temperature has the lowest importance. Box plots display the 25% and 75% quartiles, and lines within boxes represents the median. Dots represent points 1.5 times outside the interquartile range.

Fig. 6 .

 6 Fig. 6. Change in log-ratio of mean biomass of protected to fished sites across (A) mean temperature (Tmean, °C) and (B) species sensitivity to fishing. Size of circles and transparency represent the magnitude of the log-ratio. (A) No change in log-ratio is found across the temperature gradient. (B) Species more sensitive to fishing benefit more from protection. Shaded areas around the line in both plots present 95% confidence intervals.

  Commenté [EA1]:Azzurro, E., Ballerini, T., Antoniadou, C., Aversa, G.D., Souissi, J.B., Blašković, A., Cappanera, V., Chiappi, M., Cinti, M.F., Colloca, F. and Cvitković, I., 2022. ClimateFish: A Collaborative Database to Track the Abundance of Selected Coastal Fish Species as Candidate Indicators of Climate Change in the Mediterranean Sea. Frontiers in Marine Science, 9, p.910887.Commenté [EA2]:Bipmass or abundance? 3A). Hence, even when faced with challenging extreme climates, managers can still rely on MPAs as a local management tool for reducing the damage caused by fishing.

  Commenté [EA3]: D'Amen, M. and Azzurro, E., 2020. Lessepsian fish invasion in Mediterranean marine protected areas: a risk assessment under climate change scenarios. ICES Journal of MarineScience, 77(1),

Acknowledgments

We acknowledge the support of the Pew Charitable Trust for data collection, through the Pew Marine Conservation Fellowships to EA and FM; the Israel Science Foundation (ISF, grant number 1356/15) to JB; the Manna Center Program for Food Safety and Security and the Smaller-Winnikow Fund for OF, and the Israeli Nature and Park Authority. We would like to thank all present and past Belmaker lab members who participated in data collection and D.

Shapiro-Goldberg for editing the manuscript. All data needed to evaluate the conclusions in the paper are present in the paper and/or the Supplementary Materials.

All of the data is available in the Belmaker lab Githb repository.


Gustavo Moraga-Cid

Ludovic Sauguet

Christèle Huon

Laurie Malherbe

Christine Girard-Blanc

Stéphane Petres

Samuel Murail

Antoine Taly

Marc Baaden

Marc Delarue
email: delarue@pasteur.fr

Christine Girard Blanc

Pierre-Jean Corringer

Allosteric and hyperekplexic mutant phenotypes investigated on an α1 glycine receptor transmembrane structure

de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

The Glycine receptor (GlyR) belongs to the superfamily of pentameric ligand-gated ion channels (pLGICs) which plays a key role in neuronal communication (1). In humans, this superfamily includes nicotinic acetylcholine (nACh), serotonin (5HT 3 ) and -aminobutryic acid (GABA A ) receptors. pLGICs are pentamers where each subunit is composed of an extracellular domain (ECD), a transmembrane domain (TMD) made of four helices M1-M4, and an intracellular domain (ICD).

Neurotransmitter binding within the ECD triggers receptor activation, resulting in channel opening in the TMD, followed by desensitization (1). These allosteric transitions are at the heart of pLGIC function under normal conditions.

In addition, point mutations altering the conductance of the channel, or more frequently the isomerization constants and/or kinetics between the allosteric states, cause congenital hyperekplexic, myasthenic and epileptic syndromes (2).

Hyperekplexia is a rare inherited neurological disorder characterized by noise-or touch-induced non-epileptic seizures and excessive muscle stiffness. It is mainly caused by mutations in the α 1 GlyR subunit, which forms functional homomeric receptors as well as heteromeric receptors in association with the βGlyR subunit (3).

While numerous hyperekplexic mutations have been extensively studied in recombinant systems, the molecular basis of their effects has remained elusive.

The last decade has seen decisive progress in the determination of X-ray structures of pLGICs (1). The acetylcholine binding proteins (AChBPs) homologous to the pLGIC-ECDs were first solved (4), followed by two bacterial homologs called ELIC (5) and GLIC (6). GLIC is activated by protons, and its crystallization under conditions favoring the resting (GLIC-pH7) (7) or the active (GLIC-pH4) (6,8,9) states revealed its gating mechanism. The ECDs of subunits that are loosely packed at pH7 come closer according to a "blooming" motion following acidification, in concert with channel opening that involves a major tilt of the M2 channel-lining helix.

Crystallization of several GLIC mutants revealed a locally-closed "GLIC-LC" state resembling the open form but where the M2 helices are arranged like in the GLIC-pH7 form (7,10,11). Recently, three structures of eukaryotic pLGICs have been solved: the GluCl receptor from C. elegans (12,13), the human β 3 GABA A R (14), and the rat 5HT 3 R (15), revealing a high conservation of the core structure of pLGICs from bacteria to animals. Interestingly, the GluCl receptor was solved in a closed (13) and open (12) conformation. Comparison of the two forms shows a reorganization of the ECD resembling that of GLIC, but at the TMD channel opening results from a global tilt of each subunit four helix bundle, that contrasts with the local tilt of M2 found in GLIC.

To develop a versatile method for collecting high-resolution structural data of human pLGICs, we used GLIC as scaffolding protein to host TMDs from other receptors and solve their structure. Indeed, GLIC crystal packings involve mainly interactions between the ECD and the short cytoplasmic M3-M4 loop, but only limited interaction with the TMD, largely shielded from the solvent by the detergent. In previous work, we designed a chimera composed of the ECD of GLIC fused to the TMD of the human α 1 GlyR, where the ICD of the α 1 GlyR was replaced by the short linker (SQP motif) found in GLIC (16). In this chimera, mutations Y119F and F121M were introduced (loop 7) and the C-terminal tail of the α 1 GlyR was substituted to that of GLIC to increase the structural complementarities between the ECD and the TMD. This construct, here called Lily (GLIC-GlyR, Figure 1A-D) functions as a proton-gated ion channel and displays a transmembrane pharmacology and ion channel properties closely resembling those of the α 1 GlyR.

Here, we solved the structure of Lily allowing us to reinvestigate the phenotype of several α 1 GlyR allosteric mutants, and to propose a gating mechanism based on the new X-ray structure.

Results

1-Over-Expression of Lily-His in a Functional State

In contrast to GLIC, we found that Lily does not overexpress in E. coli. We thus expressed Lily in Drosophilia Schneider 2 (S2) cells with a Gly-Gly-(His) 10 tag at its C-terminus (Figure 1, S1A). We checked that S2 cells expressing both Lily-His and GLIC-His yielded robust proton-elicited currents (Figure 1D), characterized by EC 50 s for proton activation of 4.1 ± 0.3 x 10 -6 M (pH 5.3) and 4.8 ± 0.6 x 10 -6 M (pH 5.3), respectively. At pH 5, application of the channel blocker picrotoxinin (100 μM) yielded a 91 ± 7% inhibition of the Lily-His currents showing the specificity of the response.

For the mutational studies showed below, we recorded Lily and GLIC in BHK cells with a C-terminal HA tag (16) which does not alter the electrophysiological response (17), yielding EC 50 s of 3.3 ± 0.1 × 10 -7 M (pH 6.5) and 4.8 ± 0.6 x 10 -6 M (pH 5.3), respectively.

2-X-ray Structure of Lily-His in the Locally-Closed Conformation

Lily-His was purified in dodecylmaltoside and subjected to extensive crystallization trials. The best crystals were obtained at pH 3 (similar crystals were obtained at pH 4, albeit diffracting to lower resolution). Lily-His was solved at 3.5 Å with I/σ of 1.2 in the highest resolution shell (Table S1) in a P2 1 2 1 2 1 type crystal packing (Figure S1 B,C).

NCS symmetry averaging improved the quality of the electron density allowing the unambiguous reconstruction of the peptide backbone except for the first four Nterminal residues, the short M1-M2 loop (residues 218-222) and the C-terminal histidine tag (Figure 2A,B,D). The quality of the electron density at the bottom of the TMD and at the top of the M3 and M4 helices is lower. At these levels several side chains, representing a third of the TMD residues, could not be built unambiguously and were omitted in the model. (Figure S2 A,B).

Lily-His adopts the same locally-closed conformation as GLIC-His, with a C rmsd between the two structures of 0.68 Å (0.43 Å in the ECD and 0.85 Å in the TMD, Figure 2C) indicating a quasi-identical backbone conformation of the two proteins, notably of the four transmembrane helices and of the M2-M3 loop. Concerning GLIC-His, solved in the same crystal packing at a similar resolution (3.35 Å) (7), most of the side chains could be modeled from the electron density map. This indicates that, in this crystal, the TMD of the α 1 GlyR is more flexible than the TMD of GLIC, a feature supported by the high B factor of the TMD of Lily as compared to its ECD (200 ± 4 Å 2 vs 160 ± 12 Å 2 ). The lower thermostability of Lily-His in detergent solution (42°C) compared to GLIC-His (52°C) (Figure S2 C) is consistent with these observations.

2.1-Ion channel structure:

The ion channel is closed in the Lily structure (Figure 3A): the ring of L261(9') residues forms a tight hydrophobic constriction of 2.2 Å diameter constituting the gate of the channel (the main barrier to ion translocation).

Above, rings of T264(13') and S268(16') form a wider hydrophilic pore (6.1 and 7.1 Å diameter, respectively). A similar architecture is observed in the closed structure of the GluCl-Apo receptor, in contrast to bacterial cationic pLGICs that display a larger diameter at L261(9') but carry an extended hydrophobic gate at positions 13' or 16' (see Figure S3A for GluCl-Apo, GLIC-pH7 and ELIC structures). As no second hydrophobic barrier exists, the highly constricted barrier at the L261(9') level might be necessary to seal the channel and prevent any ion conduction. These data suggest a similar gate in the GlyR and GluCl receptors that are closely related in terms of sequence and ion channel properties. Finally, the upper turn of the M2 helix is partially broken in Lily, carrying the R271(19') residue that forms a polar/positively charged constriction of 2.8 Å diameter. Below the L261(9') position, the B-factor progressively increases when going down through T258(6'), G254(2') and P250(-2'), to reach the short disordered M1-M2 loop.

2.2-Inter-helices interactions:

The structure reveals a set of side-chain interactions that are specific to the α 1 GlyR (Figure 3B). At the tip of M2, the carboxylate of E243(GLIC) and the guanidinium moiety of R271(Lily) point toward the adjacent M2 helix and elicit quaternary hydrogen bonding with the main chain carbonyl of the 17' residue. The K248(GLIC)/K276(Lily) (24') side chain points toward E243(19') and is well resolved in GLIC, while it is resolved in only one out of five chains in Lily and points in the opposite direction. This suggests electrostatic attraction/repulsion between K248(GLIC)/K276(Lily)(24') and E243(GLIC)/R271(Lily) (19'). The tip of M1 interacts with the C-terminus of the M2-M3 loop in Lily through hydrophobic interactions between I225 and V280 while no such interaction occurs in GLIC.

2.3-ECD/TMD coupling interface:

The coupling region essentially consists in intrasubunit interactions between the lower part of the ECD (Loop 2, Loop 7 and pre-M1) and the upper part of the TMD (M2-M3 loop). 10 out of 15 interfacial residues are conserved between GLIC-LC and Lily (Figure S3B), resulting in the conservation of key interactions, notably hydrophobic stacking of P247(GLIC)/P275(Lily) with F116 and Y(GLIC)/F(Lily)119 (Figure 3B). In both structures, the side chain of L246(GLIC)/L274(Lily) points toward hydrophobic residues from the TMD. In the M2-M3 loop, the phenol moiety of Y251(GLIC)/Y279(Lily) is stacked with the guanidinium moiety of R117. This overlapping set of interactions at the ECD/TMD interface provides a structural explanation for the compatibility of the GLIC-ECD and the α 1 GlyR-TMD to form a functional channel.

Non-conserved GLIC/Lily residues are T253/K281, Y254/A282, Y119/F119, F121/M121 and Y194/M220 (Figure S3B). They do not impair the allosteric coupling, but certainly modulate the functional properties. For instance, we showed that performing the F119Y and M121F mutations on Lily results in an acceleration of the desensitization kinetics (16). Extensive mutagenesis work has shown that the entire interface is involved in fine tuning of the allosteric response to agonist (18,[START_REF] Smart | Synaptic neurotransmitter-gated receptors[END_REF].

3-Electrophysiological Analysis of Allosteric Mutants in Lily

We reinvestigated the effect of well-characterized α 1 GlyR mutations by patch-clamp electrophysiology on Lily-HA and α 1 GlyR in BHK cells. We selected 7 mutants, localized in various regions of the TMD: upper part of M1 behind the gate (Q226E), lower part of the channel (P250T and G254A), upper part of the channel (Q266E and R271Q) and M2-M3 loop (K276C and V280M) (Figure 4A). Except for Q266E and G254A, all mutations are associated with autosomal dominant hyperekplexia.

On Lily, R271Q produces a 10-fold increase in EC 50 for protons with a 1.5-fold decrease in maximal currents and a reduction in unitary conductance (from 86 ± 2 pS in WT to 56 ± 3 pS) (Figure 4B,S4E). On the α 1 GlyR, we observe a more marked 450-fold increase in EC 50 for glycine (Figure S4 A,B,C), in agreement with previous works, that also report a reduced single channel conductance [START_REF] Rajendra | Startle disease mutations reduce the agonist sensitivity of the human inhibitory glycine receptor[END_REF][START_REF] Rajendra | Mutation of an arginine residue in the human glycine receptor transforms betaalanine and taurine from agonists into competitive antagonists[END_REF]. The phenotype of R271Q is thus similar in Lily and α 1 GlyR, although a stronger effect on the agonist EC 50 is found for α 1 GlyR. Interestingly, the R271 residue in Lily appears close enough to elicit long-range electrostatic interaction with the K33 residue from the ECD, while a Thr is found at this position in the α 1 GlyR. The different side-chain environment may contribute to the difference in phenotypes between both receptor types.

Recently, Q226E was reported to produce spontaneously open channels [START_REF] Bode | Analysis of hyperekplexia mutations identifies transmembrane domain rearrangements that mediate glycine receptor activation[END_REF][START_REF] Bode | New hyperekplexia mutations provide insight into glycine receptor assembly, trafficking, and activation mechanisms[END_REF]. On Lily, this mutation equally produces constitutive opening: 1) Immediately after the whole-cell clamping at pH 8.0, cells expressing Q226E generate high leak currents,(~600 pA) that are blocked by 100μM of picrotoxin. Application of a more acidic solution further increases the currents, but the bad shape of the cells precluded repetitive stimulations and measurement of dose-response curves. 2) Single-channel recording at pH 8.0 shows repetitive spontaneous openings (Figure 4C), whereas no spontaneous activity is observed for Lily-WT.

On the α 1 GlyR, mutant cycle analysis suggests that Q226E stabilizes the active state through enhanced electrostatic attraction to R271 [START_REF] Bode | Analysis of hyperekplexia mutations identifies transmembrane domain rearrangements that mediate glycine receptor activation[END_REF]. We investigated this possibility on Lily. We observe that Q226E/R271Q no longer displays spontaneous currents, but a 570-fold increase in the EC 50 for protons as compared to WT (Figure 4B, S4F). It is not possible to measure the EC 50 of Q226E, but assuming a value around pH 8 as judged from single channel traces, mutant cycle analysis yields strong energetic coupling between Q226E and R271Q (15 KJ mol -1 ). This suggests that both positions interact through electrostatic forces to stabilize the open conformation. On the α 1 GlyR, R271Q and Q226E/R271Q both produce an increase in EC 50 , but the extents of their effects are significantly different from that found in Lily, pointing this time to a near-additive effect of R271Q and Q226E (Figure S4G and S5). We also introduced a glutamate at a different position nearby R271. On Lily, Q266E produces a 3.3-fold increase in sensitivity to protons (Figure 4D). Combining Q266E with R271Q results in a 230-fold decrease in proton sensitivity, again indicating energetic coupling between the two positions (10 KJ mol-1). However, performing the same set of mutations on the α 1 GlyR also points to an additive effect due to the different R271Q phenotype (Figure S5 D-F). The quantitative differences between the phenotypes of the R271Q and Q226E/R271Q in Lily and the α 1 GlyR may tentatively be accounted by the fact that, for Lily, proton activation may involve the titration of transmembrane residues interacting with the E226/R271 cluster. Indeed, recording of the α 1 GlyR R271Q and Q226E/R271Q mutants at pH 5 indicates a significant alteration of the dose-response curves (Figure S5 A-C). In conclusion, the analysis on Lily shows coupling energy between Q226E/R271Q and to a lesser extent Q266E/R271Q, but these features are not unraveled on the 1GlyR possibly due to a different mode of activation.

In the M2-M3 loop, we found that K276C on Lily produces a 120-fold increase in EC 50 and a large reduction of the maximal currents (Figure 4E,S4D,E). This phenotype is similar to what is found in the α 1 GlyR [START_REF] Lynch | Identification of intracellular and extracellular domains mediating signal transduction in the inhibitory glycine receptor chloride channel[END_REF][START_REF] Lape | The α1K276E startle disease mutation reveals multiple intermediate states in the gating of glycine receptors[END_REF]. Likewise, V280M [START_REF] Eiselé | Chimaeric nicotinic-serotonergic receptor combines distinct ligand binding and channel specificities[END_REF] was reported to produce a strong gain of function; we observed a phenotype similar to Q226E bearing spontaneous activity at pH8 (Figure 4F).

At the bottom of the channel, P250T confers reduced glycine sensitivity and increases the rate of desensitization on the α 1 GlyR (Table S2) [START_REF] Saul | Novel GLRA1 missense mutation (P250T) in dominant hyperekplexia defines an intracellular determinant of glycine receptor channel gating[END_REF]. On Lily, P250T produces a very similar phenotype characterized by: 1) a marked increase in desensitization kinetics, with current traces displaying a 20% vs. an 80% decay upon 1s application of proton at pH 4 for WT and P250T, respectively (Figure 5A,C); 2) a 46-fold increase in EC 50 for protons (Figure 5B), and 3) a 5-fold reduction of the maximal currents. Second, the α 2 GlyR displays slow kinetics of activation and a large conductance in the 100-120 pS range [START_REF] Bormann | Residues within transmembrane segment M2 determine chloride conductance of glycine receptor homo-and hetero-oligomers[END_REF]. The M2 helix of α 1 and α 2 GlyRs are identical except at position 254 (Lily numbering) (α 1 Gly and α 2 Ala). We thus performed the G254A mutation on Lily (Figure 5D-F), showing a marked reduction of the rate of activation evaluated by following the onset of the whole-cell current traces (at pH 5.0 τ act = 950 ± 62 ms vs. 64 ± 6.6 ms for G254A and WT, respectively).

Moreover, the G254A mutant shows an increase in single channel conductance (125 vs. 86 pS).

Overall, except for mutants R271Q and Q226E/R271Q, this data points to a similar phenotype when equivalent mutations are performed on Lily and on α 1 GlyR.

Discussion

1-A modular architecture for pLGICs

The early observation that the α 7 nAChR(ECD)-5HT 3 R(TMD+ICD) chimera was functional was the first evidence that the ECD and TMD may constitute independent tertiary modules [START_REF] Eiselé | Chimaeric nicotinic-serotonergic receptor combines distinct ligand binding and channel specificities[END_REF]. The α 7 nAChR(ECD)-α 1 GlyR(TMD+ICD) (18), the AChBP-5HT 3 (TMD+ICD) [START_REF] Bouzat | Coupling of agonist binding to channel gating in an ACh-binding protein linked to an ion channel[END_REF], and recently the ELIC(ECD)-α 7 nAChR(TMD) chimera [START_REF] Tillman | ELIC-α7nAChR Chimeras Reveal a Prominent Role of the Extracellular-Transmembrane Domain Interface in Allosteric Modulation[END_REF] were subsequently reported to be functional, the ECD retaining "native-like" pharmacology for agonists and the TMD "native-like" channel selectivity. It is noteworthy that extensive mutations at the ECD-TMD interface were required to produce properly folded and/or functional AChBP-5HT 3 (TMD+ICD) and ELIC(ECD)α 7 nAChR(TMD) chimeras.

A conserved modular architecture of pLGICs from bacteria to humans is now established by all available X-ray structures. Interestingly, the two domains of Lily, when expressed alone, were previously found to self-assemble. First, we showed that the isolated ECD of GLIC folds as a soluble monomer and its X-ray structure confirmed it retains the usual -sandwich fold (331). Second, an ensemble of 15 models of the α 1 GlyR TMD expressed alone and refolded in lipidic micelles has been solved by a combination of electron microscopy (EM) and nuclear magnetic resonance (NMR) [START_REF] Mowrey | Open-channel structures of the human glycine receptor α1 full-length transmembrane domain[END_REF]. The former shows in majority a pentameric assembly and the latter a bundle of 4 helices for each chain. However, these models show marked difference with the Lily TMD structure, a feature possibly due to lack of structural constraints applied by the ECD (for discussion, see Figure S6 A-B and legends).

These data suggest a maturation pathway of Lily that would explain the striking compatibility between ECDs and TMDs from different pLGICs, even when separated by billions of years of evolution. The ECD and TMD of Lily would fold autonomously, followed by the assembly of the TMD into a pentamer, triggering subsequent pentamerization of the ECD. This scheme may be extended to other pLGIC subtypes since other domains were found to self-assemble, including the ECD of the α 1 nAChR [START_REF] Dellisanti | Crystal structure of the extracellular domain of nAChR alpha1 bound to alpha-bungarotoxin at 1.94 A resolution[END_REF], and the isolated TMDs of the α 4 β 2 and α 7 (34) nAChRs.

2-A plausible gating mechanism of the TMD of the α 1 GlyR

Our electrophysiological analysis showed that the TMD of Lily displays an ion channel indistinguishable from that of the α 1 GlyR in terms of conductance and selectivity, and a pharmacology for general anesthetics, alcohols, and ivermectin similar to that of the α 1 GlyR (16). We show here that the phenotypes for key allosteric mutations, scattered at different locations within the TMD are similar on the α 1 GlyR and Lily. In addition, those phenotypes involve all aspects of the activation transition, including 1) increase or decrease of the isomerization constant between resting and active state (causing decreased agonist sensitivity (R271Q and K276C) and constitutive opening (Q226E and V280M), respectively), 2) alteration of activation kinetics (in G254A) and 3) single channel conductance (R271Q and G254A). This indicates that those residues experience similar changes in microenvironment during activation in both Lily and the α 1 GlyR. Concerning desensitization, our data also suggest a preserved mechanism thanks to the conservation of the phenotype of P250T. These data suggest a similar gating reorganization of the TMD in Lily and in the α 1 GlyR.

Here, Lily is expressed as a functional channel and crystallized in the LC conformation. For GLIC, the LC form corresponds globally to the open form, but a concerted bending of the upper part of the all M2 helices obstructs the pore by forming a tightly packed bundle, along with a revolving motion of the M2-M3 loop that is similar to what is observed in the pH7 conformation. Therefore, the conformation of the TMD in the LC form is similar to the pH7 resting form, with the exception of the M1 helix showing a 10° hinge motion in its upper half. We built a "completed X-ray structure" model of the TMD of Lily by adding the missing side chains and the backbone atoms of the five missing residues to the X-ray structure. We verified that a homology model of Lily based on GLIC-pH7 shows a TMD conformation (Figure S6B) similar to that of the completed X-ray structure (figure 6 A,B,C).

Concerning the open state, the available structural data of pLGICs show a similar TMD structure of GLIC and of the GluCl receptor. GLIC and the GluCl receptor are phylogenetically close to the α 1 GlyR (sharing respectively 34% and 26% amino acid identity at the TMD), supporting the idea that they are good models for the open form of the α 1 GlyR at the TMD. We therefore built a homology model of the open conformation of Lily based on GLIC-pH4. We chose GLIC-pH4 because its open channel structure was not constrained by ivermectin.

Assuming a common gating pathway between GLIC and the α 1 GlyR, we can use the completed X-ray structure and the homology open model as templates to investigate the activation transition of the α 1 GlyR TMD (Figure 6). According to this "Lily" gating model, channel opening is caused by a tilt of the upper-half of each M2 helix. In the process, M2 comes closer to M3 from the same subunit and to M1 from the adjacent subunit. This mechanism is consistent with a wealth of biochemical and mutational data collected on various pLGICs (7). In particular, it accounts for the phenotype of cross-linked double cysteine mutants, which show that M2 comes closer to M3 during activation in both GLIC and the α 1 GlyR (10,[START_REF] Lobo | Cross-linking of glycine receptor transmembrane segments two and three alters coupling of ligand binding with channel opening[END_REF].

3-Structural interpretation of allosteric mutant phenotypes

For Lily, electrophysiological data points to an electrostatic interaction between R271 and E226 to stabilize the open state. In the open model of Lily, both residues are close enough to interact through a salt bridge, while they are far away in the closed form, suggesting that E226 stabilizes the open channel though "pulling" R271, at the tip of M2, away from the 5-fold symmetry axis to interact with M1. On the  1 GlyR, the Q226E and R271Q mutations do not reveal coupling energy between the 2 positions, but a series of other mutations support the above conclusion [START_REF] Bode | Analysis of hyperekplexia mutations identifies transmembrane domain rearrangements that mediate glycine receptor activation[END_REF]. Data were previously interpreted on the basis of a speculative gating model between ELIC (closed) and GLIC (open) [START_REF] Bode | Analysis of hyperekplexia mutations identifies transmembrane domain rearrangements that mediate glycine receptor activation[END_REF][START_REF] Bode | New hyperekplexia mutations provide insight into glycine receptor assembly, trafficking, and activation mechanisms[END_REF], where M2 and M3 tilt altogether as a rigid block.

Here we provide a different gating model supported by a combination of electrophysiological, X-ray and modeling data that mainly involves motion of M2 alone (Figure 6C,F; S7).

In addition, the V280 residue is an interesting reporter as it is located in the M2-M3 loop that undergoes a key revolving motion during gating. V280 interacts with I225 from the upper part M1, a helix portion directly linked to the ECD and involved in signal transduction. In the α 1 GlyR, the spontaneous currents of V280M were correlated with an increased volume of the side chain [START_REF] Bode | Analysis of hyperekplexia mutations identifies transmembrane domain rearrangements that mediate glycine receptor activation[END_REF]. In the gating model, the upper part of M1 moves away from M3 in the course of channel opening, resulting in an increased distance between V280 and I225 (a Cβ-Cβ distance increase from 5.7 to 6.6 Å). Bulkier residues at position 280 are thus expected to stabilize the open form, providing a structural explanation for the observed phenotypes (Figure 6B,E).

We further show a loss-of-function phenotype for the K276C mutation on Lily, whereas the homologous K248C mutation on GLIC has an opposite effect yielding a 20-fold increase in proton sensitivity (10). This conserved Lys side chain points in different orientations in both structures (Figure 3B). In GLIC, it projects toward the upper part of M2, possibly making a salt bridge with E243, whereas in Lily, it projects between helices M1 and M2 from the adjacent subunit, possibly because of electrostatic repulsion with R271. The markedly different orientations of this otherwise conserved residue provide a rationale for the opposite phenotypes observed by electrophysiology.

Conclusion

The receptor engineering approach based on functional chimeras presented here allowed us to solve the structure of the TMD of the α 1 GlyR, and should be easily extended to other pLGICs. The Lily structure may help the drug design of allosteric effectors acting at the α 1 GlyR TMD. For instance, comparison of the open and closed models of Lily shows a reorganization of the intersubunit pocket that is lined by the S268 and A288 residues and mediates allosteric potentiation of the α 1 GlyR by general anesthetics and ethanol [START_REF] Mihic | Sites of alcohol and volatile anaesthetic action on GABA(A) and glycine receptors[END_REF]. The pocket markedly narrows down in the open-channel form, providing a plausible mechanism whereby it contracts around the effector to facilitate activation (Figure 6D,G). We also demonstrate that Lily is a pertinent model for studying the molecular mechanisms underlying allosteric mutations that may be ultimately beneficial for patients suffering hyperekplexia.

Materials and Methods

Lily was expressed and purified as in ref. (7). Crystals were obtained using vapor diffusion. The (6-8 mg/ml) protein was mixed in a 1:1 ratio with reservoir solution containing 16-20% PEG 2000MME, 50 mM NiCl2, 4% DMSO, 11% ethylene glycol and 0.1 M NaAcetate pH 3.0. Coordinates and structure factors were deposited with PDBid 4X5T. Whole cell and single channel patch-clamp electrophysiology was performed as previously described (16). Details are provided in supplementary information.

! E19'! I16'! A13'! I9'! S6'! T2'! E-2'! R19'! S16'! T13'! L9'! T6'! G2'! P-2'! Z (Å)! Pore radius (Å)! loop7! R117! Y251! P250! F195! M1! (n+1)! M2 (n+1)! M2! F121! P120! N245! E243! P247! K248! Y119! I225! R117! Y279! V280! K276! P275! M121! P120! R271! F119! F116! Q226! M1! M2! M2! M3! pore! (n+1)! GLIC-LC! LILY-LC! A! B! A! C! B! D! F! E! M2! M3! M4! P250T! G254A! R271Q! K276C! V280M! Q266E! pore! Q226E! M1! Normalized Currents! 0! 0.2! 0.4! 0.6! 0.8! 1.0! 1.2! 1E-8!1E-7! 1E-6!1E-5!1E-4! 1E-3! [H + ]! 5 pA! 300 m s! WT! R271Q! WT! R271Q! Q226E/R271Q! ! Normalized Currents! 0! 0.2! 0.4! 0.6! 0.8! 1.0! 1.2! WT! R271Q! Q266E! Q226E/
.0! 1.2! 1E-3! A! B! C! E! F! D! G! H! Q226! I225! V280! M2 (n+1)! M2! R271! Q226! M1 (n+1)! R271! Q226! S267! S268! Q266! Q266! M3! I225! V280! Q266! I225! V280! M2! R271! Q226! Q266! M3! R271! Q226! I225! V280! Q266! S267! S268! P230! Q266! Closed! Open (model)!
Supporting Information.

Materials and Methods

Protein Production

The cDNA coding for Lily-His consists, from the N-to the C-terminus, in a Drosophilia signal peptide (MKLCILLAVVAFVGLSLG), the mature sequence of Lily followed to a C-terminal his-tag inserted into a pMT/BiP/V5-HisA vector (Invitrogen). This plasmid and the pPURO selection-plasmid (19 μg and 1 μg, respectively) were co-transfected into S2-type insect cells in the presence of cellfectin (Invitrogen). Co-transfected celllines were grown in Insect-XPRESS medium (Lonza) supplemented with 0.6 µg/ml puromycine at 28°C without CO 2 . Cell-lines are considered stable after 3-4 weeks.

Protein expression is induced upon addition of Cadmium (5 µM) when the culture reaches a cell-density population of 10 7 cells/ml. Cells were collected by centrifugation (1500 g for 10 minutes). Lily-His was extracted and purified following the same procedure as described previously (1). In brief, cells were broken by sonication at 4°C in Buffer A (Tris 20 mM, NaCl 300 mM). Membranes were recovered by centrifugation (1h at 40000 rpm) and solubilized using DDM 2% in Buffer A with agitation overnight at 4°C. The supernatant was collected by centrifugation at 20000 rpm (1h). Lily was finally recovered from the supernatant by affinity chromatography using Cobalt resin, eluted using imidazole (250 mM) and purified by size exclusion chromatography.

Crystallography

Crystal Preparation

All crystals were obtained using vapor diffusion in hanging drops at 20°C. The

Data Collection

Datasets were collected on beamline ID23-1 of the European Synchrotron Radiation Facility (Grenoble, France). Crystals were collected using the helicoïdal data collection facility. Reflections were integrated using XDS(2) and further processed using the CCP4 programs (2). Crystals of Lily-His belong to the P2 1 2 1 2 1 space group (a,b,c=118.9, 132.3, 190.5Å and α=β=γ=90°) with one pentamer in the asymmetric unit. Details on the data collection statistics are provided in Table S1.

Phasing and Refinement

The molecular replacement solution was found in Phaser (3) by using the structure of GLIC (PDB 4HFI) at 2.4 Å as a starting model. This initial model was refined in Refmac 5 (4) by using rigid-body refinement and subsequently, by using restrained refinement (4). The resulting model was improved by manual building in COOT (5).

The model was finally refined in Buster (6). Automatically-generated noncrystallographic symmetry restraints were thus used throughout refinement (7). Right S1.

Homology Modelling

We constructed three homology models of Lily. The first model completes the missing parts of the crystal structure of Lily-His in the LC state. The others propose a model of Lily in the open state (based on GLIC-pH4) and the resting state (based on GLIC-pH7). We manually created the sequence alignment between GLIC and Lily, as it is straightforward since only one gap could be found in the M1-M2 loop.

For the LC structural model of Lily, we used as a template the presented crystal structure of Lily as well as parts of the crystal structure of GLIC in the same crystal packing (see below). The homology models were constructed while keeping all completely attributed residues, in the used Lily structure, as rigid body constraints, and thus not modified. To model the missing part of the M1-M2 loop we used the structure of four residues of GLIC in the M1-M2 loop (residues 218 to 221 [STST],

ST-SY, see Figure 1) as a structural template. For the last of the five Lily chains, the last helix turn of M1 was missing, we used the same strategy as described previously, by adding the residues 213 to 216 (TAFW) from GLIC as structural template. For the open model of Lily, we used as a template the high-resolution structure of GLIC in the open state (PDB: 4HFI) (9). The whole ECD (residues 5 to 191) of GLIC was used as a rigid body constraint with the exception of the two loops in contact with the TMD, loop loop2 (residues 31 to 33) and loop7 (residues 112 to 122).

The Modeller software (10) was used to generate 100 homology models of each state. The best scoring model was chosen for the last step of side-chain refinement.

All residue side chains which were not part of the rigid body restraints were rebuilt using the backbone-dependent rotamer library SCRWL4 (11). Radii were calculated using the program Hole ( 12)

Electrophysiology cDNA Constructs.
The cDNA construct encoding the Lily receptors with a C-terminal HA-tag subcloned into the pMT3 vector for expression in BHK cells has been described previously (13).

Mutations were inserted by using the QuikChange site-directed mutagenesis method.

All constructions were confirmed by full sequencing.

Cell Culture and Transfection.

BHK cells tk-ts13 variant, display weak endogenous proton-gated currents and are therefore favorable to record Lily and its mutants. Cells were grown at 37 °C under a 5% CO 2 atmosphere in DMEM with Glutamax (Invitrogen), supplemented with 5% fetal bovine serum (FBS), penicillin (0.1 g/L), and streptomycin (100 U/mL). Cells were seeded at 104 cells/cm2 in 35-mm Petri dishes 24 h before transfection. Cells were transfected with 4μg of cDNA of interest and 1μg of GFP-cDNA cloned into the pMT3 vector using the calcium phosphate precipitation method, GFP-positive cells were used for electrophysiology 16-24h after transfection. For recordings performed in S2 cells, stable cell lines were grown in Insect-XPRESS medium supplemented with 0.6 µg/ml puromycine at 28°C without CO 2 . 5 days before patch experiments, Lily expression was induced upon addition of Cadmium (5 µM). The day before, cells were plated in 35mm dishes coated with poly-L-lysine (Sigma-Aldrich).

Patch-Clamp Recordings.

Whole-cell recordings in BHK and S2 cells were performed using a holding potential of -60 mV. Patch electrodes were filled with (in mM): 140 CsCl, 2 MgCl2, 2 Ca2Cl, 10 BAPTA, 10 HEPES (pH 7.4). The external solution contained (in mM): 150 NaCl, 10 KCl, 2.0 CaCl2, 1.0 MgCl2, 10 HEPES (pH 7.4), and 10 glucose. The amplitude of currents was assayed using a brief (1-2 s) pulse with external solution at desired pHs every 60 seconds. Proton dose-response curves were calculated normalizing the maximal current at each proton concentration to the maximal current obtained at saturating concentrations of the protons (100%). EC 50 , nH and τ act values and plots were constructed using the Origin 6.0 (MicroCal) software. To calculate the coupling energy between pair of residues, mutant cycle analysis was performed as described previously ( 14) using the equation,

∆𝐺 = 𝑅𝑇 𝑙𝑛 [ 𝐸𝐶50, 𝑤𝑤 * 𝐸𝐶50, 𝑚𝑚 𝐸𝐶50, 𝑤𝑚 * 𝐸𝐶50, 𝑚𝑤 ]
where ΔG is the coupling energy, R is the universal gas constant, T is temperature (K), EC 50,ww is the wild type EC 50 value, EC 50,mm is the double mutant EC 50 value, and EC5 0,mw and EC 50,wm are the two single mutant EC 50 values

The methodology for single-channel recordings in the outside-out configuration has been previously published (13). Briefly, patch pipettes had tip resistances of 7-15 megaohms following fire polishing. Patchs were voltage clamped at -60 mV and the data were filtered (5 kHz low-pass 8-pole Bessel) and acquired at 50 kHz using pClamp software (Molecular Devices, Sunnyvale, CA). The solutions at different pHs were applied to the patch using a gravity-driven solution exchanger perfusion system. were incubated over a range of temperatures for 10 min using a thermal cycler, followed by centrifugation to remove precipitated material. The supernatant was then loaded onto a superose 6 column equilibrated with SEC buffer (20mM Tris pH 7,5, 300mM NaCl, 0,02% DDM) and run at the flow rate of 0,5mL/min. The eluent was detected by UV absorption at 280nm.

Lily thus displays marked flexibility at the level of M4 and at the cytoplasmic side of the TMD, a feature observed in the crystal and possibly related to the lower thermal stability of Lily versus GLIC observed in detergent solution. Such flexibility may have several origins: 1) it may be due to the lack of the intracellular domain, an ~88 amino acid segment between the M3 and M4 that is present in α 1 GlyR but has been removed in Lily. However, it is noteworthy that in the GluCl structures, the bottom segment of the TMD is well ordered while the cytoplasmic domain was removed in a similar manner as in Lily; 2) specific lipids may be needed to constrain the TMD of the α 1 GlyR, a feature well documented for nAChRs and 3) an interesting possibility would be that the α 1 GlyR carries a TMD intrinsically flexible in its closed-channel conformation. This may be related to its TMD structure that carries a single ring of hydrophobic residues at position 261 that hold together the M2 helices in the closed channel, together with the presence of two rings of glycine residues at positions 254 and 256 that may confer backbone flexibility. Thus, the observed flexibility might be an intrinsic property of the closed-channel conformation, a feature that might have functional implication for channel activation. Upon activation, a conformational change might stabilize the intracellular side of the TMD as well as the intracellular end of the pore that hosts the selectivity filter. in the isolated TMD (REFGGGGFI sequence) than in Lily (SQP sequence). However the rest of the TMD is identical in sequence between both structures, and we observed marked differences in the relative orientations of the helices. In addition, the M2-M3 linker is partly folded in helix and highly dynamic in the NMR models while it is folded in an extended conformation in Lily. The secondary structure of the TMD is highly conserved in all X-ray structures solved so far. It is highly unlikely that the TMD of the α 1 GlyR would fold in different manner. The difference of the isolated TMD structure may be due to: 1) a lack of structural constraints applied by the ECD, 2) a mobilizing effect of the micellar environment (17), and 3) the NMR data may be compatible with other structural models since, in particular, the set of Overhauser effect (NOE) connectivity and paramagnetic relaxation enhancement (PRE) restraints cannot be unambiguously assigned to inter-or intra subunit distances, and the initial model used to build the TMD was based on residual dipolar coupling (RDC) constraints on a peptide comprising only the M2 and M3 segments (18).

Figure 1 :

 1 Figure 1: Overall view of the Lily X-ray structure. (A) Side view of Lily. One chain is represented in cartoon with the ECD colored in blue, M1 in cyan, M2 and loop M2-M3 in orange, M3 and M4 in gray. (B) Scheme of the Lily construct with local modifications indicated. The sequence shows the M1 and M2 region, with the mutated residues in red. (C) Upper view of Lily with the same color code. (D) Typical pH-elicited current traces of Lily-His and GLIC-His expressed in S2 cells, and Lily-HA expressed in BHK cells. In this and all subsequent figures, horizontal bars indicate the duration of the proton applications with concentrations given as pH units.

Figure 2 :

 2 Figure 2: Structure of the TMD of a Lily subunit

Figure 3 :

 3 Figure 3: Ion channel architecture and interaction networks in Lily and GLIC-LC.

Figure 4 :

 4 Figure 4: Phenotypes of the Q226E, Q266E, R271Q, K276C and V280M mutants on Lily

Figure 5 :

 5 Figure 5: Phenotypes of the P250T and G254A mutants on Lily

Figure 6 :

 6 Figure 6: Proposed gating mechanism of the TMD of the α 1 GlyR

EF i g u r e 1 B -f a c t o r p e r r e s i d u e 4 F i g u r e 1 -

 141 C F 1 4 ' A A p o G L I C F 1 4 ' A + e t h a n o l C W i l d -T y p e G L I C F 1 4 ! A ( a p o ) G L I C F 1 4 ! A + E t h a n o l

concentrated ( 6 -

 6 8 mg/ml) protein was mixed in a 1:1 ratio with reservoir solution typically containing 16-20% PEG 2000MME, 50 mM NiCl 2 , 4% DMSO, 11% ethylene glycol and 0.1 M NaAcetate pH 3.0. Crystallization was induced by the micro-seeding technique from a solution of crushed crystals 1 hour after setting-up the crystallization experiment. Crystals appeared overnight and grew for one week before reaching their final dimensions (typically 100 μm x 100 μm x 100 μm). All crystals were cryoprotected using a three-step protocol. 1) The crystal-containing drops were transferred to the cold room (4°C), sealed onto a novel crystal plate that contained no reservoir solution and left at 4°C for 10 minutes. 2) 3-5 l of a dehydrating solution composed of the reservoir solution supplemented with 30% of ethylene glycol was added to the crystallization drop. 3) The drop was left to air-dry for 5-20 minutes prior to flash-freezing in liquid nitrogen.

  after molecular replacement, B-factors were reset to an arbitrary value of 120 corresponding to the Wilson-plot estimated B-factors and set constant until the final steps of refinement. B-factors were then refined using 2 TLS parameter by chain (one for the ECD (residue 5 to 191), one for the TMD (residue 218 to 413)). NCS symmetry averaging improves the quality of the electron density thus allowing the unambiguous reconstruction of the main chain except for the first four N-terminal residues, the M1-M2 loop (residue 218-222) as well as the C-terminal 10-histidine expression tag. Model geometry validation: 94.8% of the residues were in the most favored regions of the Ramachandran plot. MolProbity scores (8) for the refined model ranged within the 100 th percentiles of structures refined at comparable resolutions. Details of the refinement statistics are provided in Table

FiguresFigure s1 :

 s1 Figures

Figure s2 :

 s2 Figure s2: Missing atoms in the Lily refined crystal structure. (A) Sequencealignment of the five chains constituting the TMD of Lily. Residues are respectively colored in blue and red when the whole residue or its side chain has been omitted from the final model. (B) Cartoon representation of a TMD of Lily. Residues are colored in red when their side chains are missing in all five monomers and in pink when modeled at least one in monomer. (C) Thermostability of GLIC-His and Lily purified in detergent solution. The purified protein samples (500µL at 0.2 mg/mL)

Figure s3 :

 s3 Figure s3: (A) Ion permeation pathway. Cartoon representations of the ion channel of Lily, ELIC (PDBid: 2VL0), GLIC Active (PDBid: 4HFI), GLIC Resting (PDBid: 4NPQ) and GluCl Apo (PDBid: 4TNV), with the 2 front helices removed. The green grids show the volume accessible to the solvent. Side chains of pore lining residues are shown as sticks. (B) ECD-TMD interface in Lily and GLIC-LC. Cartoon representation of the domain interface of a monomer of GLIC-LC and Lily with the ECD colored blue, the TMD colored white. Residues contributing to the interface are shown in sticks and colored according to their location and conservation between GLIC and Lily. At the ECD, conserved (vs non-conserved) residues are colored blue (vs magenta). At the TMD conserved (vs non-conserved) residues are colored orange (vs red).

Figure s4 :

 s4 Figure s4: Electrophysiological characterization of Lily and  1 GlyR mutants. (A) Typical current traces of whole cell recordings for Lily WT and R271Q and K276C mutants. (B) Typical current traces of whole cell recordings for the α 1 GlyR (without tag) WT, and R271Q and K276C mutants. (C) Normalized dose-response curves for α 1 GlyR WT and the indicated mutants. (D) Single-channel events recording at -60 mV and pH 6.0 of outside-out patches containing Lily WT or K276C mutant (E) The I/V relationship plots summarized the mean channel amplitude obtained at different voltages of Lily WT and R271Q and K276C mutant. (F) Typical current traces of whole cell recordings for Lily WT, and Q226E/R271Q double mutant. (G) Sample trace for α 1 GlyR Q226E mutant showing the leak current observed without glycine, the maximal glycine-elicited current (1mM) and the inhibition of the leak current by 100 μM picrotoxin (PTX, quantified in the bar graph where error bars represent +/-SD).

Figure s5 :

 s5 Figure s5: Electrophysiological characterization of Lily and 1GlyR mutants. (A) Typical current traces of whole cell recordings for α 1 GlyR WT, R271Q and Q226E/R271Q mutants performed at pH 7.3 (B) Typical current traces of whole cell recordings for α 1 GlyR WT, R271Q and Q226E/R271Q mutants performed at pH 5.

Figure s7 :

 s7 Figure s7: Closed channel conformation of Lily (modeled by homology using GLIC-pH7; PDBid: 4NPQ) and comparison with the GluCl-apo closed (4TNV) structure. The upper view of Lily (A, B) and GluCl (E,H) are represented in the same manner as in figure 6B,E. M2 of a single subunit is colored orange and the neighboring M1 and M2 from the adjacent subunit are colored cyan and pale orange, respectively. Side views of Lily (C) and GluCl (F). Side chains of Q226, Q266, R271 and D284 residues in Lily (E) and the homologous Q219, N259, N264 and D277 in GluCl are shown in sticks.

Table 1 . Data collection and refinement statistics

 1 100 th percentile is the best among structures of comparable resolution; 0 th is the worst

	Lily

*Values in parentheses are for highest-resolution shell. #

Table S2 : Properties of Lily and GlyRs wild type and mutants receptors.

 S2

						-Lily-								-GlyR-
	Receptor	EC 50 (M) [H	+ ]	EC 50 Mut/ EC 50 WT	I max (nA)	nH	Conduct (pS)	n	EC 50 (M) [Glycine]		EC 50 WT EC 50 Mut/	Imax (nA)	nH	(pS) Conduct	n
	WT Q226E	2.6 ± 0.5 x10 ND	-7	1 -	1.6 ± 0.31 1.2 ± 0.25	1.2 ± 0.2 -	86 ± 2 85 ± 2	14 6	44 ± 2 x10 4.7 ± 0.2 x10 -6 -6	1 0.1	2.26 ± 0.31 1.66 ± 0.3	1.7 ± 0.2 1.3 ± 0.2	90 ± 3 -	10 6
	P250T G254A Q266E	1.2 ± 0.2 x10 2.6 ± 0.2 x10 8.7 ± 0.3 x10 -8 -5 -7	46 1 0.3	0.3 ± 0.12 1.3 ± 0.31 1.1 ± 0.28	1.3 ± 0.2 1.2 ± 0.4 1.2 ± 0.2	-126 ± 3 -	6 7 6	570± 80 x10 -6 -6 42± 3 x10 14± 2 x10 -6	13 1 0.3	0.8 ± 0.12 2.1 ±0.31 6.66 ± 0.8	1.3 ±0.2 1.1 ± 0.4 1.4 ± 0.2	---	6 5 5
	R271Q	2.8 ± 0.5 x10	-6	10	1.1 ± 0.31	1.3 ± 0.4	56 ± 3	7	20 ± 2.5 x10 -3 *	454	0.98 ± 0.27	1.2 ± 0.4	-	5
	K276C	3.1 ± 0.2 x10	-5 *	119	0.2 ± 0.11	1.1 ± 0.4	87 ± 3	7	3.8 ± 0.9 x10	-3 *	86	1.7 ± 0.11	1.3 ± 0.4	-	6
	V280M	ND				-	-	-	86 ± 3	5	NP		-	-	-	-	-
	Q226E/R271Q Q266E/R271Q	1.5 ± 0.2 x10 6.07 ± 0.3 10 -4 * -5	576 233	0.6 ± 0.35 0.7 ± 0.29	1.2 ± 0.2 1.1 ± 0.3	--	4 5	-3 * 3.1 ± 0.4 x10 4.9 ± 0.6 x10 -3 *	70 112	2.1 ± 0.3 1.96 ± 0.3	2.2± 0.3 1.6 ± 0.2	--	5 5

*: For these mutants, the plateau response of the D-R curves could not be accurately achieved; ND: Not Determined; NP: Not Performed; all error values are given as +/-standard deviation

Acknowledgments: we acknowledge financial support by the fondation de la recherche médicale (GMC), the DARRI (Institut Pasteur), and the Agence Nationale de la Recherche ("Nicochimera"). The "Initiative d'Excellence" (Grant "DYNAMO", ANR-11-LABX-0011 to SM, AT and MB). Fondation Pierre-Gilles de Gennes pour la Recherche (SM).

D! C! F! E!