Pierre Curmi

Mohamed Hilal

Elsa Martin
email: elsa.martin@inra.fr

Virginie Piguet

Valley-bottom wetland selection for water-quality preservation: How to deal with the absence of quantification of water-quality benefits?

Keywords: Wetland conservation, Nutrient-retention function, Prioritizing criteria

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

1. Introduction

Wetlands provide several ecosystem services [START_REF] Mitsch | The value of wetlands: importance of scale and landscape setting[END_REF]. Despite this, degradation of wetlands is widespread and restoration is needed [START_REF] Bai | Wetland Degradation and Ecological Restoration[END_REF]. The main source of wetland degradation is linked to the divergence between private interests and public benefits. [START_REF] Ando | The roles of ownership, ecology, and economics in public wetlandconservation decisions[END_REF] show that there is a marked bias against conserving wetlands that are privately owned.

Applied to agricultural interests, [START_REF] Van Vuuren | Private and social returns from wetland preservation versus those from wetland conversion to agriculture[END_REF] estimate private and social benefits from generic wetland conservation versus conversion to agriculture to show the need for wetland conservation policies in Canada. [START_REF] Heimlich | Wetlands and Agriculture: Private Interests and Public Benefits[END_REF] develop the same kind of argument for the U.S.

De Laporte (2014) furthermore points out the effect of crop prices on wetland conversion in Canada whereas Van [START_REF] Van Kooten | Bioeconomic evaluation of government agricultural programs on wetlands conversion[END_REF] studies the effects of government agricultural support programs.

One of the well-studied services provided by wetlands is the improvement of water quality. For instance, [START_REF] Moshiri | Constructed Wetlands for Water Quality Improvement[END_REF] gives over an entire book to the impact of constructed wetlands on water quality. [START_REF] Verhoeven | Regional and global concerns over wetlands and water quqlity[END_REF] concentrate on the functional role of small wetlands in watersheds where the main source of pollution is agriculture. They explain that river catchments where the landscape is mainly agricultural often have lower-order stream (located upstream in the hydrologic network) subcatchments, i.e. headwater watersheds, that are strongly influenced by runoff from agricultural land use. [START_REF] Mérot | Innovative assessment tools to improve water quality and watershed management in farming areas[END_REF] furthermore explain that Valley-Bottom Wetlands (VBWs) in agricultural landscapes (wet meadows) are omitted from international (Ramsar), national, and regional wetland inventories because they are small and scattered across the rural landscape. However, they explain that VBWs considerably influence hydrology and water quality throughout the watershed area because they are located in the bottomlands of the headwater watershed. We will concentrate on these VBWs in agricultural landscapes that are mainly intermittent wet meadows. [START_REF] Turner | Ecological-economic analysis of wetlands: scientific integration for management and policy[END_REF] recommend conducting integrated ecological-economic analysis for the question of wetland management and policy improvement. We focus on an agricultural landscape and address this question at a headwater watershed scale within a framework of integrated research by economists and soil scientists alike.

The first step is to locate VBWs. Following [START_REF] Mérot | Testing a climate-topographic index for predicting wetlands distribution along an European climate gradient[END_REF], we assume that the primary control on VBWs is geomorphological: it determines the hydraulic gradient and the presence of high soil water content in valley bottoms. Intermittent stagnant water thus induced between storm events transforms soil into hydric soil and enables the growth of vegetation that may be specific either to classical wetlands (hydrophilic species) or to agricultural land use (wet meadows). The consequence is that the identification of the latter cannot be based on classical remote sensing data that only help in identifying hydrophilic species [START_REF] Lunetta | Application of Multi-Temporal Landsat 5 TM Imagery for Wetland Identification[END_REF][START_REF] Mulder | The use of remote sensing in soil and terrain mapping -A review[END_REF]. In other words, in works based on remote sensing data, the vegetation criterion is more important than the soil hydromorphy criterion, which is not the case for VBWs. More particularly, the first step in VBW identification is to locate what [START_REF] Mérot | Testing a climate-topographic index for predicting wetlands distribution along an European climate gradient[END_REF] call potential VBWs since they represent the maximal theoretical extension of VBWs. Potential VBWs are identified on a geomorphological basis (topography and parent material).

Here soil science methods are helpful. We locate VBWs at the headwater watershed scale based on seminal topographic wetness indices that were developed by [START_REF] Beven | A physically based variable contributing area model of basin hydrology[END_REF]. Such indices are used for predicting VBWs in Europe [START_REF] Mérot | Testing a climate-topographic index for predicting wetlands distribution along an European climate gradient[END_REF] and in France [START_REF] Berthier | Spatial prediction of potential wetlands at the French national scale based on hydroecoregions stratification and inference modelling[END_REF], taking into account climatic conditions. At the headwater watershed scale within an administrative region, climate variability is not sufficient, and as such, we ignore it. Contrary to [START_REF] Berthier | Spatial prediction of potential wetlands at the French national scale based on hydroecoregions stratification and inference modelling[END_REF], who determine national threshold values of topographic indices based on the stratification of hydroecoregions, we calibrate local threshold values based on field measurements. More generally, local threshold values are particularly adapted to headwater watersheds characterized by heterogeneous soil surface permeability where the climato-topographic index is proved to fail to predict wetland location [START_REF] Mérot | Testing a climate-topographic index for predicting wetlands distribution along an European climate gradient[END_REF][START_REF] Berthier | Spatial prediction of potential wetlands at the French national scale based on hydroecoregions stratification and inference modelling[END_REF]. This local calibration enables us to take permeability into account when computing indices, much as was done in the seminal proposition by [START_REF] Beven | A physically based variable contributing area model of basin hydrology[END_REF].

Once potential VBWs have been located, the second step is to evaluate their capacity to improve or secure a certain water quality. [START_REF] Yang | Cost-effective targeting of riparian buffers[END_REF] use a hydrologic model (the annualized agricultural nonpoint source pollution model) to examine land retirement targeting for establishing buffers connected to the river. The advantage of such a hydrological model is that it enables a precise measurement of water quality, taking into account several factors such as the size of the buffer, the inflow of pollutants, surface flows, etc. The disadvantage is that it needs a lot of precise data that are not always available (agricultural practices or water bodies for instance) and that it differs from reality since it remains a model. [START_REF] Yang | Cost-effective targeting of riparian buffers[END_REF] study was applied to a watershed in Canada. As stressed by [START_REF] Mérot | Innovative assessment tools to improve water quality and watershed management in farming areas[END_REF], in Europe, the interest in wetlands is new compared with North America. The consequence is that such hydrological models are not well-developed and that water agencies are far from being able to use them, at least in France. As a consequence, we argue that it is very much worth developing easily implementable methods to help them select wetlands in an effective way when there is no reliable method of quantifying water-quality benefits. Following [START_REF] Mérot | Testing a climate-topographic index for predicting wetlands distribution along an European climate gradient[END_REF], we will approximate the capacity of VBWs to improve or secure a certain water quality based on a qualitative classification that can be derived from the literature and that we will sum up in the method section.

According to [START_REF] Lavoux | Evaluation du Plan national d'action pour les zones humides 2010-2013 (PNZH)[END_REF], water agencies in France spent €58 million on purchasing 13,426 ha of wetlands from 2009 to 2012. i A further €2.5 million went into the purchase and management of land for the purpose of water-quality preservation between 2002 and 2011 within the framework of a sensitive natural spaces policy (METL, 2011). The small amount of financial capital involved raises questions regarding the prioritization of the wetlands to be selected first for conservation purposes.

Literature on biodiversity conservation shows that, in a world of limited budgets, consideration of the costs of preservation in the prioritizing procedure enables an increase in conserved biodiversity [START_REF] Naidoo | Integrating economic costs into conservation planning[END_REF][START_REF] Newburn | Economics and Land-Use Change in Prioritizing Private Land Conservation[END_REF]. We propose to test this idea in the case of wetland conservation for water-quality preservation. Once potential VBWs have been located and their capacity to improve or secure water quality evaluated, the third step is to estimate the cost of their conservation.

To the best of our knowledge, the literature on wetland prioritization focuses mainly on restoration, rather than on conservation (see, for instance, [START_REF] Darwiche-Criado | Comparing Two Multi-Criteria Methods for Prioritizing Wetland Restoration and Creation Sites Based on Ecological[END_REF]. One exception is the work by De [START_REF] De Laporte | Ecological goals and wetland preservation choice[END_REF] who propose a cost-effective prioritization procedure based on integrated economic and hydrologic modeling. However, contrary to our focus on VBWs, they concentrate on generic wetlands located without consideration of their soil characteristics (a small number of wetlands were investigated based on an inventory from a water agency). Furthermore, they compute returns to alternative land uses in order to estimate the cost of conservation; it is an opportunity cost.

For data availability reasons, we concentrate instead on the purchase costs of VBWs, i.e. market prices of agricultural land. To do so, we follow [START_REF] Newburn | Habitat and open space at risk of land-use conversion: targeting strategies for land conservation[END_REF] in implementing a hedonic price method.

To sum up, our main contribution to the literature is to provide an integrated framework of VBW conservation strategy, involving both economists and soil scientists, that could be easily implemented by a local agency in charge of water-quality management of a headwater watershed. On the one hand, our contribution with respect to the water resource economics literature is to provide an analysis regarding the trade-offs between decreased costs and increased effectiveness of different strategies of VBW prioritization when there is no reliable method to quantify water-quality benefits. On the other hand, our contribution to the soil science literature is to provide a method of VBW identification based on soil hydromorphy for headwater watersheds characterized by heterogeneous soil surface permeability where it is proved that the climato-topographic index fails to predict wetland location.

The next section describes the data and methods used in this study. Then, we present the results from the estimation of the cost of agricultural lands, followed by the results from the classification of VBWs with respect to their potential in terms of water-quality preservation. Afterwards, we analyze the i http://www.zones-humides.org/agir/plans-et-programmes/acquisition-de-20-000-ha trade-offs between decreased costs and increased effectiveness of different strategies of VBW prioritization. The final section sets out the conclusions.

Materials and methods

Headwater watershed selection and characterization

We perform the analysis on two French agricultural headwater watersheds: the Brenne and the Armançon which are located in the administrative division of Côte-d'Or (equivalent of NUTS ii 3 subdivision, 8,800 km² and 533,000 inhabitants), northeast France (see Figure 1). iii This area has a continental climate.

Both watersheds have natural and semi-natural land cover (urbanization cover is approximately 2.5%). This land cover is mainly agricultural and is composed of meadows and cereals (forest cover is 14% in the Armançon and 25% in the Brenne watersheds). iv More particularly, the Brenne watershed covers 781 km², 30.8% of which is meadowland and 22.2% cereal crops. There are 20,883 agricultural plots.

The mean concentration of nitrate observed at the outlet is 19.7 mg/L; the mean flow is 9.2 m 3 /s; and the mean flux of nitrate is 20.8 kg/km²/day. v The Armançon watershed measures 333 km², 45.6% of which is given over to meadows and 17.6% to cereals. There are 11,892 agricultural plots. The mean concentration of nitrate observed at the outlet is 16.4 mg/L; the mean flow is 2.5 m 3 /s; and the mean flux of nitrate is 10.1 kg/km²/day. We specifically chose these headwater watersheds for data availability reasons and because they are characterized by different parent material permeability values which may mean that these VBWs differ in terms of their hydrological functioning. The parent material of the Brenne watershed is mainly (>50%) permeable limestone vi whereas for the Armançon it is mainly (>50%) composed of impermeable marls. In both watersheds, the most common texture of soils is clay and clay mixed with silt. vii ii The nomenclature of territorial units (NUTS) for statistics classification is a hierarchical system for dividing up the economic or administrative territory of the European Union.

iii Both headwater watersheds are hydrologically connected downstream (North of the map in Figure 1) despite what appears in Figure 1 because we delimited both watersheds with respect to water monitoring stations upstream from their confluence. iv Source: The French National Institute of Geographic and Forest Information -French topographic database, Agency for Services and Payment (France) and Integrated Administration and Control System (European Union) -Land Parcel Identification System (2006System ( -2009)). v Source: Seine-Normandy Water Agency -French surface water quality database (1994)(1995)(1996)(1997)(1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010) and Ministry for the Ecological and Inclusive Transition -French hydrometric database. vi Source: The French Geological Survey -French geological database. vii Source: The French Soils Scientific Interest Group -French soil database. Hydrologically, the Brenne is a rounded watershed that is characterized by 780 km of rivers, among which 87% have a Strahler order viii lower than 4 (i.e. they are located upstream in the watershed), and viii The Strahler order is a standard stream classification proposed by [START_REF] Strahler | Hypsometric (area-altitude) analysis of erosional topography[END_REF]. 13% are 4th order or higher, (i.e. are located downstream) (see Figure 2). ix The Armançon is a relatively elongate watershed that is characterized by 376 km of rivers, among which 90% have a Strahler order lower than 4 and 10% are higher than or equal to 4. The main river does not exceed 5th order in the area under study.

VBW location: soil science materials and methods

To prioritize VBWs for conservation purposes, the first step is to locate them. To do so, either of two main criteria can be used: vegetation or soil hydromorphy. For instance, the French water statute of ix Source: The French National Institute of Geographic and Forest Information -French topographic database.

1992 defines VBWs mainly with respect to vegetation, and it is a statutory decree of 2007 that adds soil hydromorphy to the definition. Here, we propose to concentrate on the soil hydromorphy criterion, which seems more challenging, especially with respect to French legislation and to VBWs.

French standard soil surveys provide an approximation of soil hydromorphy. However, an accurate description of the spatial distribution of soil hydromorphy requires supplementary mapping techniques because of the methodological and economic constraints of standard soil survey procedures [START_REF] Chaplot | Improving soil hydromorphy prediction according to DEM resolution and available pedological data[END_REF][START_REF] Chaplot | Testing quantitative soil-landscape models for predicting the soil hydromorphic index at a regional scale[END_REF]. The method used for identifying VBWs consists of two steps: the first step is to compute topographic indices, and the second to find local threshold values of these indices (i.e., values for which we can predict the presence of a VBW).

First, to compute topographic indices, we begin with the seminal proposal of [START_REF] Beven | A physically based variable contributing area model of basin hydrology[END_REF] by computing a topographic wetness index, denoted IBK, based on the concept of contributing area.

To do so, we use a data elevation model with 25 m resolution provided by the French National Institute of Geographic and Forest Information (IGN). Furthermore, we follow the methods of Mourier et al. Second, we determine threshold value of these indices. To establish these thresholds, we make field measurements based on transects. The transects are located where the BK index decreases as gradually as possible from the stream to the slope. Furthermore, transects are representative of the regional geology and the Strahler order. The permeability of the parent material is crucial in identifying VBWs. [START_REF] Beven | A physically based variable contributing area model of basin hydrology[END_REF] recommended considering transmissivity. The Brenne and Armançon watersheds correspond to two different geological settings, the former permeable and the latter impermeable. We locate transects based on low and high Strahler orders. Ultimately, we test 20 transects (with different combinations of parent material and Strahler order). In the field, soil hydromorphic features and the measurement of iron-manganese concretions [START_REF] D'amore | Saturation, Reduction, and the Formation of Iron-Manganese Concretions in the Jackson-Frazier Wetland, Oregon[END_REF] are identified on the boundary between well drained and poorly drained places to determine the value of the threshold from which a VBW can be predicted.

2.3. VBW qualitative classification for water-quality preservation: some useful results from the environmental science literature Once located, the second step in VBW prioritization is to select the VBWs that best preserve water quality. The nutrient-retention function of wetlands is now well known [START_REF] Mitsch | The value of wetlands: importance of scale and landscape setting[END_REF], and as such, we focus on this function. However, it remains difficult to precisely quantify nutrient retention for each potential VBW. To accommodate such difficulties, [START_REF] Mérot | A method for improving the management of controversial wetland[END_REF] proposed a theoretical qualitative analysis of potential, existing, and effective wetlands (PEEW) that is summed up in Figure 3. [START_REF] Heimlich | Wetlands and Agriculture: Private Interests and Public Benefits[END_REF], we focus on VBW conservation of agricultural lands. Drainage then helps to distinguish between potential and existing VBWs. This information is not easy to obtain at the plot scale. [START_REF] Mérot | A method for improving the management of controversial wetland[END_REF] approximate drainage by considering that cultivated lands are drained whereas meadows are not. We will make the same assumption. In the classification proposed by [START_REF] Mérot | A method for improving the management of controversial wetland[END_REF], potential VBWs minus existing VBWs designates degraded VBWs. When focusing on the effectiveness with respect to

Potential Existing

Effective a specific function, some VBWs have the potential to become effective again if restored. Here, we concentrate on existing VBWs because degraded VBWs require a valuation of their restoration costs in addition to their purchase cost.

Hydrogeomorphic criteria are helpful [START_REF] Mitsch | The value of wetlands: importance of scale and landscape setting[END_REF] in identifying different types of VBWs with respect to the effectiveness of their nutrient-retention function (see Figure 4). First, riparian VBWs (i.e. those connected to the river) are crucial for nutrient retention because of their roles as buffers [START_REF] Pinay | The role of riparian woods in regulating nitrogen fluxes between the alluvial aquifer and surface water: a conceptual model[END_REF][START_REF] Ockenden | Keeping agricultural soil out of rivers: Evidence of sediment and nutrient accumulation within field wetlands in the UK[END_REF]. As such, connected VBWs are more effective than unconnected VBWs. Second, parent material plays a crucial role: VBWs on permeable parent material are more effective than those on impermeable parent material because they induce more exchanges of water between the stream and the riparian zone [START_REF] Grimaldi | Nitrate depletion during within-stream transport: effects of exchange processes between streamwater, the hyporheic and riparian zones[END_REF]. Third, [START_REF] Montreuil | Nitrogen Removal in Valley Bottom Wetlands: Assessment in Headwater Catchments Distributed throughout a Large Basin[END_REF] and [START_REF] Montreuil | Estimation of nitrate removal by riparian wetlands and streams in agricultural catchments: Effect of discharge and stream order[END_REF][START_REF] Montreuil | Contrasting behaviour of two riparian wetlands in relation to their location in the hydrographic network[END_REF] show that VBWs located upstream (low Strahler orders) are crucial for nutrient retention. In the Brenne and Armançon watersheds, upstream VBWs are located next to agricultural runoffs whereas downstream (high Strahler orders), agricultural plots are fewer and mainly located at the bottom of the valley, because the slopes are steeper and more difficult to cultivate as soon as one moves away from the river. Furthermore, it is a well-established result that effectiveness is higher upstream than downstream for periods of low discharge [START_REF] Wollheim | Dynamics of N removal over annual time periods in a suburban river network[END_REF]. This can be explained by the increase in residence time [START_REF] Puckett | Transport and fate of nitrate at the ground-water ⁄surface-water inter-face[END_REF] which favors oxygen consumption and denitrification, as well by the fact that the hydrographic network is denser upstream than downstream which increases the area of contact between streams and wetlands [START_REF] Howarth | Regional nitrogen budgets and riverine N & P fluxes for the drainage to the North Atlantic Ocean: natural and human influences[END_REF].

Based on the previous elements, we propose to adopt the following hierarchy for the different types of VBWs with respect to their effectiveness in the Brenne and Armançon watersheds: First, we begin by estimating a hedonic price function of agricultural lands:

= + + + + +
where pi denotes the price of the plot i; li the location characteristics of the plot; ti its topographic characteristics; si its soil properties; ci denotes control variables; and εi is the error term. x To do so, we compute cluster-robust standard errors [START_REF] Cameron | Microeconometrics using Stata[END_REF]) using a cluster for each municipality (667 in our case).

Second, we use the estimated coefficient of the first steps to predict the price of the 42,189 undeveloped agricultural plots of the watersheds under study (see Table App-3 in Appendix 1 for the descriptive statistics of this sample). The presence of heteroscedasticity induces some specificity in the prediction procedure (for more details, see [START_REF] Hilal | Prediction of the Purchase Cost of Agricultural Land: The Example of Côte-d'Or, France[END_REF]. More specifically, we confirm that the [START_REF] Meulenberg | On the estimation of an exponential function[END_REF] proposal is the most appropriate predictor that was proposed in [START_REF] Hilal | Prediction of the Purchase Cost of Agricultural Land: The Example of Côte-d'Or, France[END_REF], according to the computation of a correlation coefficient with the real price and standard Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE) indicators. xi Finally, we introduce a corrective term such that the predicted price has the following form:

= exp" # + $ + # + $ + ̂ + 0.5)1 -, -. #²0

where , = 1 )2 3 2-45 1 3 with X the matrix of explanatory variables and xi the ith row of X; and σ² denotes the variance of the error term.

Purchasing cost of agricultural land in the Armançon and Brenne watersheds

x We run a White's test [START_REF] White | A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity[END_REF] leading us to reject the homoscedasticity assumption of the residuals and a Moran's I test [START_REF] Moran | Notes on continuous stochastic phenomena[END_REF] considering intra-municipal proximity to deduce the presence of spatial autocorrelation.

xi MAE is the average of the absolute differences between prediction and actual observation. RMSE is the square root of the average of squared differences between prediction and actual observation. MAE and RMSE are among the most common indices of predictive accuracy [START_REF] Fair | Specification and Analysis of Macroeconomic Models[END_REF].

The results of the hedonic price function estimation are reported in Appendix 2 ( The estimated coefficients associated with the presence of a river management scheme are of great interest. Indeed, some coefficients are positive and others negative. More specifically, the fact that an agricultural plot is located in the jurisdiction of the Armançon or Arroux management schemes lowers its price. In contrast, we find that the location of an agricultural plot in the jurisdiction of the Tille or Vouge management schemes increases its price. This result is linked to the fact that the Armançon and Arroux management schemes are restrictive for agricultural activities because their main goal is waterquality management. The Tille and Vouge management schemes are concerned with water quantity management because of urbanization. They can also be restrictive for agricultural activities in the short term, but in the long term, as noted by [START_REF] Cavailhès | Urban influences on periurban farmland prices[END_REF], expected urbanization fully determines agricultural land prices. In the long term, the expected increase in water-resource availability makes urbanization possible and, therefore, raises agricultural land prices because of conversion possibilities. The threshold values of topographic wetness indices obtained from field measurements described in more details in the second step of the soil science materials and method section are reported in Appendix 3 (Table App-6 When comparing the location of potential VBWs provided by topographic indices with the locations provided by hydromorphy from soil mapping units (Figures 6a and6b), it is apparent that topographic indices locate small VBWs in the Brenne watershed, whereas soil mapping units do not. Furthermore, topographic indices increase the precision of VBW locations whereas soil mapping units provide broad predictions only, especially in the Armançon watershed.

Another interesting comparison is between the locations of potential VBWs predicted at a local scale and the locations predicted at national scale, as discussed in [START_REF] Berthier | Spatial prediction of potential wetlands at the French national scale based on hydroecoregions stratification and inference modelling[END_REF] (Figures 6a and6c).

Local predictions provide more precise locations than national predictions. More specifically, local predictions can either reduce (Brenne) or increase (Armançon) the extension of VBWs obtained from national predictions. MEDDE, GIS Sol (2014) statistically tested the validity of the predictions proposed in [START_REF] Berthier | Spatial prediction of potential wetlands at the French national scale based on hydroecoregions stratification and inference modelling[END_REF]. They stress that the quality of their VBW predictions is very low for parent material such as those that characterize the Brenne and Armançon watersheds. This emphasizes the relevance of our method for predictions at a local scale. Table 1 and Figure 7 summarize the variation obtained within each watershed. The two watersheds have very different profiles with respect to their VBWs. The ratio of unconnected VBWs to connected VBWs is higher in the Armançon watershed than in the Brenne watershed. Among the connected xii The difference between potential VBWs resulting from the data elevation model and potential VBWs considered at the broader scale of the plot is linked to the change of scale of the analysis.

VBWs, the Armançon has more upstream VBWs than downstream VBWs, and the reverse is true in the Brenne watershed. Among upstream-connected VBWs, both watersheds have more VBWs with lowpermeability parent material. 5. Trade-offs between decreased cost and increased effectiveness of

VBW conservation

Figure 5 was generated from the predicted prices of all agricultural plots of the Armançon and Brenne watersheds. We now focus on the prices of existing VBWs that are used for agriculture. The amounts of money involved are so high that it is unavoidable to prioritize the VBWs that must be purchased first. Let us first consider an agency that uses an economic criterion alone for selection: this agency selects the least cost VBW first. Table 3 summarizes the type of VBW selected by such a procedure when the budget earmarked for conservation stands at €100,000. VBWs connected upstream with high permeability are not conserved whichever watershed the budget is allocated to:

the Armançon, the Brenne, or both. When the €100,000 are spent exclusively on the Brenne or on both watersheds, VBWs connected downstream are not conserved. Tables App-7 to App-10 yield the same results as Table 3 for different budgets. We see that all types of VBW are selected in both watersheds and in the Armançon only for a budget of €500,000 and that this is the case in the Brenne only for a budget of €5 million. *The areas are not equal to 0 ha: they are less than 1 ha but more than 0 ha.

Let us then consider an agency that operates in a cost-effective way, i.e. it selects VBWs based on the prioritization scale defined by the qualitative classification presented before, i.e. from the bottom of Table 2 to the top, by least cost. The results of such a selection are presented in Table 4. The main difference with respect to the previous prioritization process is that VBWs connected upstream with high permeability are the only type of VBWs to be selected when the budget of €100,000 is either spent on the Armançon watershed exclusively or on both watersheds. When such a budget is spent exclusively on the Brenne watershed, some VBWs connected upstream with low permeability are also selected. While the area is lower, the number of discrete wetland units preserved is higher than in Table 3, which may have additional water quality benefits since bigger wetlands are not always better in water quality [START_REF] De Laporte | Ecological goals and wetland preservation choice[END_REF].

Table App-11 to App-14 provides the same results as Table 4 for different budgets. We see that even for a budget of €10 million, not all types of VBWs are selected when spent on both watersheds since no unconnected VBWs are selected in this specific case. This means that the cost-effective prioritization process favors more effective but expensive VBWs than the least-cost prioritization process. To sum up, implementing a least-cost prioritization process reduces water-quality preservation even if the conservation area is greater (65 versus 35 hectares for a €100,000 budget) since the VBWs selected are less effective.

Based on a mean per-hectare cost, Table 2 confirms this result since unconnected VBWs are the cheapest whereas they are the least effective for water-quality preservation. xiii Furthermore, a costeffective prioritization process based on mean per-hectare costs would lead to VBWs connected upstream being selected ahead of VBWs connected downstream because €3,173/ha is less than €3,512/ha and VBWs connected upstream are more effective than those connected downstream in the qualitative classification presented before. However, a surprising a priori result is that the mean per-hectare costs are ranked in opposing ways for both the Armançon and Brenne watersheds when considered separately. To understand this counterintuitive result, Table 1 is helpful. On the one hand, Table 1 shows that the €3,512/ha mean is mainly driven by the VBWs connected downstream in the Brenne watershed, which are more widespread and expensive on a mean per-hectare basis than in the Armançon watershed. On the other hand, Table 1 shows that the €3,173/ha mean is mainly driven by the VBWs connected upstream in the Armançon watershed which are more widespread and less expensive on a mean per-hectare basis than in the Brenne watershed. A policy implication is that the mean per-hectare cost should be considered with caution because it can hide local disparities. This implication is particularly relevant for agencies operating over widespread jurisdictions. The need for caution surrounding the mean per-hectare cost criteria is also true within watersheds where the distribution of per-hectare costs can differ from the mean (see difference for VBWs connected upstream versus downstream and with high versus low permeability).

This result confirms that the prioritization procedure must be conducted as in Tables 3 and4: ranking VBWs from the cheapest to the most expensive, by effective types and beginning with the most effective type.

Conclusion and extensions

To the best of our knowledge, our work is the first to provide an integrated framework of valley-bottom wetland conservation for surface water-quality preservation in agricultural landscapes. This integrated framework consists of combining perspectives from both soil science and economics for the selection of VBWs to be conserved first for water-quality preservation purposes when there is no reliable method for quantifying water-quality benefits. Our analysis stresses the importance of the simultaneous consideration of hydrogeomorphic and cost criteria when prioritizing VBWs for conservation. Indeed, concentrating on either one or the other can reduce the impact on water-quality preservation within the framework of a constrained budget.

A good candidate for conservation is a VBW that has the best possible retention function from a hydrogeomorphic perspective as well as the lowest cost from an economic perspective. We identify situations in which these criteria are compatible (when the lowest-cost VBWs are the ones with the best retention function) and other situations in which they are competitive (when the lowest-cost

VBWs are the ones with the poorest retention function, for instance). The policy implications are direct. In a case in which the criteria are compatible, the qualitative method of VBW classification for water-quality preservation is adapted to prioritize VBWs, whereas in a case in which the criteria are competing, the prioritization must also consider the cost of conservation. An integrated cost-effective criterion must then be implemented.

Furthermore, our local prediction of VBWs allows us to consider upstream VBWs in the analysis.

National predictions are usually not accurate enough to precisely identify upstream VBWs, and tend to focus on downstream VBWs. Our analysis highlights that upstream VBWs can be of great importance for water-quality preservation. This contribution is particularly relevant in a context of climate change.

Indeed, since rainfall variability will increase in the future (see, for instance, GIECC, 2013), downstream

VBWs will flood more often, which will reduce their retention function.

This work could be extended in several ways. First, we adopt a lower-bound estimation of the costs, since we ignore any post-purchase costs, such as those linked to the maintenance of the land after it is put out of production. An extension could consist of collecting and integrating such costs. It would then be interesting to work on degraded VBWs (potential minus existing one from the PEEW approach). However, this is beyond the scope of the present paper.

The conservation method that we consider in this work can be viewed as an extreme method because it includes purchasing land for conservation purposes. A more flexible method could focus on restricting land use. Such restrictions could control the agricultural use of land, banning drainage, for instance. Such restrictions also have a cost, and can either decrease or increase the nutrient-retention function. Investigating the cost and the impact on the retention function of each restriction of land use could be a second extension of this work. It would then be useful to determine the best combination of purchases and agricultural land-use restrictions for conserving the nutrient-retention function of VBWs.

Yang et al. (2016) propose a hydrologic modeling approach to quantify the efficiency of riparian wetlands in terms of nutrient retention. A third extension of our work would be to apply our integrated analysis to hydrology in order to quantify the nutrient-retention capacity of VBWs. Once this retention capacity has been quantified, it would then be possible to perform a complete cost-efficiency analysis by computing the economic value of nutrient retention as [START_REF] Byström | The nitrogen abatement cost in wetlands[END_REF] or [START_REF] Grossman | Economic value of the nutrient retention function of restored floodplain wetlands in the Elbe River basin[END_REF] do for other types of wetlands. However, such an exercise, would need to be conducted with caution because of the imprecision of methods for estimating the existence value of natural goods such as water [START_REF] Kelman | Cost-benefit Analysis, an ethical critique[END_REF][START_REF] Spash | Re-establishing an ecological discourse in the policy debate over how to value ecosystems and biodiversity[END_REF].

Figure 1 :

 1 Figure 1: Study area -the Brenne and Armançon watersheds (bounding coordinates -Lambert93, RGF 93: N 6731000, W 796800, E 834400, S 6679000)

Figure 2 :

 2 Figure 2: Stream orders of the Armançon (south-west) and Brenne (north-east) river networks

  (2008) who recommend computing different topographic indices according to stream order. To do so, we compute different indices according to the Strahler order. For streams with Strahler orders lower than 4 (located upstream in the watershed), denoted with the subscript ls for low Strahler, we compute the index proposed by Mérot et al. (1995): = where A denotes the drainage area per unit contour length and tanα the local slope angle. For streams with Strahler orders greater than or equal to 4 (located downstream in the watershed), denoted with the subscript hs for high Strahler, we compute the index proposed by Crave and Gascuel-Odoux (1997): = where tanβ denotes the downslope gradient. This hydraulic gradient is equal to the ratio of the vertical over the horizontal distances between the sample point and the channel network.

Figure 3 :

 3 Figure3: The PEEW (potential, existing, effective wetlands) approach (source:[START_REF] Mérot | A method for improving the management of controversial wetland[END_REF]

Figure 4 :

 4 Figure 4: Classification of valley-bottom wetlands (VBW) with respect to effectiveness. (1) unconnected; (2) connected low permeability; (3) connected high permeability.

Connected_upstream_permeable

  Estimating the purchase cost of VBWs: economic materials and methodsThe method for estimating the purchase cost of potential VBWs follows[START_REF] Hilal | Prediction of the Purchase Cost of Agricultural Land: The Example of Côte-d'Or, France[END_REF] and consists of two steps. The first step is related to the estimation of a price function for agricultural land sold in the market, based on the observation of real-estate transactions. We define agricultural land as either a field or a meadow, excluding vineyards, orchards, and forests because we assume that additional information is needed in order to estimate the latter land uses. The second step involves predicting the price of agricultural land in 2008. For this purpose, we use a land-use layer for that year created in[START_REF] Hilal | Prediction of the Purchase Cost of Agricultural Land: The Example of Côte-d'Or, France[END_REF]. The land under consideration at this step is not necessarily sold in the market, which may be the case for potential VBWs. The predictions are based on the estimation results obtained in the first step. Because the land market is more widespread than a watershed, we concentrate only on the Côte-d'Or administrative division which is the scale at which companies for agricultural real-estate management operate.

  Figure 5 illustrates this point. Indeed red areas, representing the highest prices, correspond to agricultural plots located within towns or hamlets; orange areas correspond to farmland near roads in the valleys; yellow areas indicate plots on the outskirts of the towns or hamlets, and blue areas are areas with very low population density.

Figure 5 :

 5 Figure 5: Spatial variation in the purchasing cost of agricultural land

  ). They differ by Strahler order and the type of parent material. They allow us to predict potential VBW locations. More specifically, we predict 33.37% of potential VBWs in the Armançon watershed (over the 333 km² area of the watershed) and 10.71% in the Brenne watershed (over 781 km²).

  Figure 6: A comparison of three different approaches for mapping VBWs

Figure 7 :

 7 Figure 7: Location of the four types of VBWs

  Figure App-2 to App-3 that confirm this xiii The criteria are in competition for the entire distribution of the per-hectare costs, and not only the mean. Indeed, Figure App-1 shows that the Lorenz curve for unconnected VBWs is invariably above the curve for connected VBWs. Consequently, focusing on a mean price is a good approximation for connected and unconnected VBWs in the Brenne and Armançon watersheds.

Figure App- 2 :

 2 Figure App-2: Distribution of the per-hectare costs in the Brenne and Armançon watersheds for upstream connected versus downstream connected VBWs

  Table App-1summarizes the variables included in the regression. Qualitative properties were put into quantitative form through dummy variables. Quantitative variables that exhibit non-linear relations with respect to the price were cut according to thresholds that were found by iteration, beginning with the aggregations that have the smallest impact on the adjusted R². This model is an adaptation of the one proposed by[START_REF] Hilal | Prediction of the Purchase Cost of Agricultural Land: The Example of Côte-d'Or, France[END_REF]: we use the same data but a different model that we consider to be more appropriate for our headwater watershed analysis.The seminal model is adapted in three ways. First, we simplify soil properties and location characteristics to reduce the number of explanatory variables. Second, we introduce the percentage of the plots under the jurisdiction of a river management scheme because it is linked to the wetland selection problem for water-quality preservation. Third, we introduce a new control (the percentage of the plot in either one or the other watershed) to test whether this model is appropriate for the watershed under study. Finally, location characteristics are measured by the Euclidian distance to the town hall, travel distance to the intermediate-level municipality that provides shops, facilities and public and private services, a dummy variable that indicates if the municipality is also the regional capital (Dijon), and percentage of the plot covered by a river management scheme. Topographic characteristics are measured by area, altitude, and slope. Soil properties are measured by determining textures (very fine, fine, medium, and coarse). Control variables include the percentage of the plot in either the Brenne or Armançon watershed, the year of the transaction, and whether the farmer is the purchaser or not. Land cover is classified as meadow or arable land.To estimate this function, we use data that were constructed and described in[START_REF] Hilal | Prediction of the Purchase Cost of Agricultural Land: The Example of Côte-d'Or, France[END_REF]. More specifically, we focus on 6,477 transactions between 1992 and 2008 in Côte-d'Or (see Table App-2 in Appendix 1 for the descriptive statistics of this sample). The estimation procedure is an Ordinary Least Squares (OLS) procedure, where we produce standard errors that are robust to heteroscedasticity and to intra-municipal spatial autocorrelation.

  Table App-4 provides the estimations with our model and Table App-5 the estimations from[START_REF] Hilal | Prediction of the Purchase Cost of Agricultural Land: The Example of Côte-d'Or, France[END_REF]). The adjusted R² increased with respect to the estimations of[START_REF] Hilal | Prediction of the Purchase Cost of Agricultural Land: The Example of Côte-d'Or, France[END_REF], from 71.15% to 71.87%. Hence, the model used for predicting the purchase cost of VBWs explains 71.87% of the variance in the log of the price. The absence of statistical significance in the estimated coefficients associated with the location of the plots in the Brenne or Armançon watersheds shows that our estimated model of the land market of Côte-d'Or is suitable for those watersheds.

Table 1 :

 1 Distribution of existing VBWs based on hydrogeomorphic criteria

	Types of VBW	Armançon		Brenne
		Number of	Area	Number of	Area
		plots	(ha)	plots	(ha)

Table 2

 2

summarizes the price, both in total and on a per-hectare basis, in each watershed. An agency willing to purchase agricultural VBWs in both the Armançon and Brenne watersheds would have to pay €24.5 million, which represents nearly one-third of the budget for VBW purchases by French water agencies between 2009 and 2012. Approximately 60% of this budget would be dedicated to the Armançon watershed. The global amount of €24.5 million corresponds to a mean unit cost of €3,109/ha -€2,881/ha for the Armançon watershed and €3,527/ha for the Brenne watershed. VBWs in the Armançon watershed are cheaper than those in the Brenne watershed, but there are more of them.

Table 2 :

 2 Prices of existing VBWs according to hydrogeomorphic criteria

Armançon Brenne Both watersheds Total (€) Mean (€/ha) Total (€) Mean (€/ha) Total (€) Mean (€/ha)

	Unconnected	8,173,692	2,847	3,250,157	3,112	11,423,849	2,917
	Connected	6,482,668	2,924	6,518,961	3,779	13,001,629	3,298
	Downstream	806,357	2,600	4,312,916	3,758	5,119,273	3,512
	Upstream	5,676,311	2,977	2,206,045	3,820	7,882,356	3,173
	Impermeable 5,576,189	2,976	2,161,484	3,813	7,737,673	3,170
	Permeable	100,123	3,039	44,561	4,192	144,683	3,320

Table 3 :

 3 VBWs selected in the least-cost prioritization process with a budget of €100,000

		Armançon			Brenne			Both
				Area			Area
		Cost (€) Number		Cost (€) Number		Cost (€) Number Area
				(ha)			(ha)
	Unconnected	97,096	19	59 96,783	12	61 98,696	14	64
	Connected downstream 2,217	1	1	-	-	-	-	-	-
	Upstream impermeable	687	1	0*	3,217	2	2	1,304	1	1
	Upstream permeable	-	-	-	-	-	-	-	-	-
	Total	100,000	21	61 100,000	14	63 100,000	15	65

Table 4 :

 4 VBWs selected in the cost-effective prioritization process with a budget of €100,000

		Armançon			Brenne			Both
				Area			Area
		Cost (€) Number		Cost (€) Number		Cost (€) Number Area
				(ha)			(ha)
	Unconnected	-	-	-	-	-	-	-	-	-
	Connected downstream	-	-	-	-	-	-	-	-	-
	Upstream impermeable	-	-	-	55,439	20	28	-	-	-
	Upstream permeable	100,000	45	33 44,561	41	11 100,000	35	35
	Total	100,000	45	33 100,000	61	39 100,000	35	35

Table App -

 App Table App-3: Descriptive statistics of variables used for predictions (N=42,189) Significant at 10% level, **Significant at 5% level, ***Significant at 1% level Appendix 4: Sensitivity analysis of the least-cost prioritization process to the available budget Table App-7: VBW selected in the least-cost prioritization process with a budget of €500,000 Table App-8: VBW selected in the least-cost prioritization process with a budget of €1,000,000 9: VBW selected in the least-cost prioritization process with a budget of €5,000,000 Armançon

		Year_1995 Table App-2: Descriptive statistics of variables used for estimations (N=6,477) Transaction in 1995 1: yes -0: no Year_2007 +0.148** 0.066
		Year_1996 Continuous variables Mean Standard Deviation Minimum Maximum Transaction in 1996 1: yes -0: no Continuous variables Mean Standard Deviation Minimum Maximum Year_2008 +0.139** 0.063
		Year_1997 Surface area Surface area Field	Transaction in 1997 39 38 +0.134*** 21 20 0.029 0.02 0.02		1: yes -0: no 841 716
		Year_1998 Altitude Altitude FarmerPurch	Transaction in 1998 111 82 -0.273*** 309 380 0.025 176 199		1: yes -0: no 689 596
	Year_1999 Year_2000 Slope Slope Intercept Year_2001 Year_2002 DistMun TDistRetPlace DistMun TDistRetPlace Number of observations 6,477 3 4 +8.263*** Transaction in 1999 Transaction in 2000 3 3 0.142 0.0003 0.0003 Armançon Brenne Transaction in 2001 Transaction in 2002 1.36 0.89 0.03 11 6 1.41 0.86 0.01 15 8 R² Cost (€) Number Area (ha) Cost (€) Number Area (ha) Cost (€) Number Area 1: yes -0: no 25 25 Both 1: yes -0: no 1: yes -0: no 5.84 36 5.30 36 0.7115 1: yes -0: no Year_2003 Transaction in 2003 Armançon_manag 0.163 0.369 1 Armançon_manag 0.766 0.421 1 Unconnected 408,355 66 226 405,711 82 214 418,077 72 244 1: yes -0: no Year_2004 Transaction in 2004 1: yes -0: no Year_2005 Transaction in 2005 Arroux_manag 0.106 0.308 1 Ouche_manag 0.097 0.294 1 Arroux_manag 0.001 0.023 0.981 Ouche_manag 0.002 0.043 Connected downstream 40,281 6 21 36,229 13 18 21,977 5 12 1 1: yes -0: no Year_2006 Transaction in 2006 Tille_manag 0.094 0.292 1 Tille_manag 0.009 0.096 1 Upstream impermeable 50,190 7 27 58,060 21 29 58,773 15 32 1: yes -0: no Year_2007 Transaction in 2007 Vouge_manag 0.067 0.249 1 Vouge_manag 0 0 0 Upstream permeable 1,173 1 1 ---1,173 1 1 1: yes -0: no Year_2008 Transaction in 2008 1: yes -0: no FarmerPurch Farmer Purchaser 1: yes -0: no Brenne 0.094 0.292 1 Armançon 0.043 0.202 1 Brenne 0.495 0.500 1 Armançon 0.282 0.450 1 Total 500,000 80 275 500,000 116 261 500,000 93 289
		Field Dummy variables Dummy variables	Field			1: cultivated land 0: meadow
		Texture_vf Texture_vf	0.260 0.185		0.439 0.388			1 1
		Texture_f Texture_f	0.501 0.807 Armançon		0.500 0.395	Brenne		1 1		Both
		Texture_m Texture_c Texture_m Texture_c	0.194 0.045 0.008 0 Cost (€) Number Area (ha) Cost (€) Number Area (ha) Cost (€) Number Area 0.395 1 0.207 1 0.091 1 0 1
	Year_1992 Year_1992 Unconnected	0.063 0 664,284	116	0.244 0 352	612,311	124	1 0	302	716,996	127	397
	Year_1993 Year_1994 Year_1993 Year_1994 Connected downstream 144,336 0.069 0.052 0 0	20	0.253 0.222 0 0 73	284,925	40	1 1 0 0	122	126,357	18	65
	Year_1995 Year_1995 Upstream impermeable 190,206 0.050 0	26	0.217 0 96	102,765	30	1 0	49	155,474	25	81
	Year_1996 Year_1996 Upstream permeable	0.051 0 1,173	1	0.219 0 1	-	-	1 0	-	1,173	1	1
	Total	Year_1997 Year_1998 Year_1997 Year_1998	0.041 0.057 0 0 1,000,000	163	0.197 0.232 0 0 522	1,000,000	194	1 1 0 0	472	1,000,000	171	543
		Year_1999 Year_1999	0.049 0		0.215 0			1 0
		Year_2000 Year_2000	0.052 0		0.222 0			1 0
		Year_2001 Year_2001	0.054 0		0.227 0			1 0
		Year_2002 Year_2002	0.050 0		0.218 0			1 0
		Year_2003 Year_2003	0.055 0		0.227 0			1 0
		Year_2004 Year_2004	0.062 0		0.242 0			1 0
		Year_2005 Year_2005	0.064 1		0.245 0			1 1
		Year_2006 Year_2006	0.067 0		0.249 0			1 0
		Year_2007 Year_2007	0.078 0		0.269 0			1 0
		Year_2008 Year_2008	0.086 0		0.281 0			1 0
		Field Field	0.709 0.509		0.454 0.500			1 1
		FarmerPurch FarmerPurch	0.274 0		0.446 0			1 0
		RetPlace_dijon RetPlace_dijon	0.080 0.006		0.272 0.078			1 1

*

Brenne Both Cost (€) Number Area (ha) Cost (€) Number Area (ha) Cost (€) Number Area

  Table App-10: VBW selected in the least-cost prioritization process with a budget of €10,000,000

	Unconnected	296,2822	491	1,306	205,0362	411	780	308,7881	529	1422
	Connected downstream 394,817	51	181	1,974,457	271	658	657,771	93	295
	Upstream impermeable 1,627,586	213	684	958,738	180	314	1,238,638	180	545
	Upstream permeable	14,775	5	6	16,443	9	5	15,711	6	7
	Total	5,000,000	760	2,177 5,000,000	871	1,757 5,000,000	808	2,268
		Armançon			Brenne			Both
		Cost (€) Number Area (ha) Cost (€) Number Area (ha) Cost (€) Number Area
	Unconnected	5,672,092	936	2,221 3,250,157	836	1,044	5,788,978 1,002 2,400
	Connected downstream	661,028	83	270	4,312,916	767	1,148	1,204,301	182	494
	Upstream impermeable 3,591,867	483	1,351 2,161,484	534	567	2,958,925	428	1,174
	Upstream permeable	75,013	21	27	44,561	41	11	47,796	17	18

This work was funded by the French Environmental Ministry as part of the GESSOL 3 national research program. We also acknowledge Jean-Sauveur Ay, Daniel Gilbert and two

Appendices

Appendix 1: Variables used in the econometric models Appendix 5: Sensitivity analysis of the cost-effective prioritization process to the amount of budget available The Lorenz curve is a cumulative frequency curve that compares the distribution of a variable with the uniform distribution. The diagonal orientation of the graph depicts the uniform distribution. The more the Lorenz curve lies below the diagonal, the more unevenly the price is shared between various VBWs.


Florian Bahut

Youzhong Liu

Remy Romanet

Christian Coelho

Nathalie Sieczkowski

Hervé Alexandre

Philippe Schmitt-Kopplin

Maria Nikolantonaki

Régis D Gougeon
email: regis.gougeon@u-bourgogne.fr

Rémy Romanet

Metabolic diversity conveyed by the process leading to glutathione accumulation in inactivated dry yeast: A synthetic media study

Keywords: Mass spectrometry, Wine, Oenology, Untargeted analysis

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

Introduction

There has been a growing interest for yeast derivatives in winemaking over the last few decades, as these products can improve fermentation processes and organoleptic properties of wine (recently reviewed by Pozo-Bayòn and collaborators (2009)). They divided enological preparations of yeast derivatives into five classes depending on the industrial process of production : the yeast hulls, yeast mannoproteins, the yeast autolysate, the yeast protein extracts and the inactivated dry yeasts (IDY). The latter are mainly Saccharomyces cerevisiae strains grown under aerobic condition in a non-limiting medium before being inactivated and dried and can then be used from the vineyards through to the fermentation and barrel aging steps of the winemaking process.

Although IDY have already been largely used in wineries, scientific explanations for their impact on winemaking have only recently been elucidated. IDY can release amino acids and peptides expressed in yeast assimilable nitrogen (of the order of a few mg N/L) which contribute to enrich the must in nutrients [START_REF] Pozo-Bayón | Characterization of commercial inactive dry yeast preparations for enological use based on their ability to release soluble compounds and their behavior toward aroma compounds in model wines[END_REF]. Since the amount of nitrogen released by inactivated yeast is low (compared to yeast autolysates), these products are more generally advised for micronutrient and survival factors (notably vitamins and fatty acids). However, the extent of the fraction of assimilable nitrogen related to the presence of small peptides and proteins released by both active and IDY is still unexplored (Liu et al., 2017). Polysaccharides are also significantly released by IDY [START_REF] Pozo-Bayón | Characterization of commercial inactive dry yeast preparations for enological use based on their ability to release soluble compounds and their behavior toward aroma compounds in model wines[END_REF]. The main component of the yeast cell wall is mannan (chains of mannose) and β-glucan (chains of glucose) which could be linked to proteins. Cell wall polysaccharides mainly have color stabilization properties [START_REF] Escot | Release of polysaccharides by yeasts and the influence of released polysaccharides on colour stability and wine astringency[END_REF][START_REF] Guadalupe | Effect of commercial mannoprotein addition on polysaccharide, polyphenolic, and color composition in red wines[END_REF], notably through polyphenolic interactions [START_REF] Andújar-Ortiz | Effect of using glutathione-enriched inactive dry yeast preparations on the phenolic composition of rosé grenache wines during winemaking[END_REF]. It is however acknowledged that cell walls can exhibit a potential antioxidant activity not only due to the linked proteins but also due to the polysaccharides structures themselves [START_REF] Jaehrig | Antioxidative activity of (1→3), (1→6)-β-d-glucan from Saccharomyces cerevisiae grown on different media[END_REF][START_REF] Jaehrig | In Vitro Potential Antioxidant Activity of (1→3), (1→6)-β-dglucan and Protein Fractions from Saccharomyces cerevisiae Cell Walls[END_REF].

Recently there has been an interest in the use IDYs during winemaking, notably with a focus on their antioxidant properties. The concept of IDY rich in glutathione (GSH), as natural antioxidant for a use in winemaking originated in 2005 with the first patent for naturally rich inactive yeast (PCT/FR2005/000115). Glutathione is a cysteine-containing peptide and is considered to be the most abundant low molecular thiol in yeast cells [START_REF] Elskens | Glutathione as an endogenous sulphur source in the yeast Saccharomyces cerevisiae[END_REF]. In winemaking, GSH has been proposed to reduce the oxidation phenomena that leads to browning, and thus improves wine preservation and varietal aroma stability during aging [START_REF] Antoce | Effects of Glutathione and Ascorbic Acid Addition on the CIELab Chromatic Characteristics of Muscat Ottonel Wines[END_REF][START_REF] Kritzinger | Role of glutathione in winemaking: A review[END_REF][START_REF] Nikolantonaki | Impact of Glutathione on Wines Oxidative Stability: A Combined Sensory and Metabolomic Study[END_REF][START_REF] Webber | Utilization of amino acids to enhance glutathione production in Saccharomyces cerevisiae[END_REF].

IDY can have a higher GSH content by activating the GSH yeast intracellular production during processing [START_REF] Li | Glutathione: A review on biotechnological production[END_REF][START_REF] Webber | Utilization of amino acids to enhance glutathione production in Saccharomyces cerevisiae[END_REF]. The increase in GSH content of IDYs during processing can be achieved after modulation of the sulfur metabolic pathway when cysteine is present in the culture medium [START_REF] Nisamedtinov | Metabolic changes underlying the higher accumulation of glutathione in Saccharomyces cerevisiae mutants[END_REF]. However, it is well known that sulfur-containing compounds can exert an antioxidant activity and these reactive compounds are more abundant in GSH-enriched IDY than in IDY [START_REF] Elias | Antioxidant Activity of Proteins and Peptides[END_REF][START_REF] Rodriguez-Bencomo | Impact of glutathione-enriched inactive dry yeast preparations on the stability of terpenes during model wine aging[END_REF]. Even though there is quite a lot of literature on the general metabolites which could impact the wine quality and safety, there is a lack of knowledge on the global diversity and functionality of IDY compounds released during winemaking and their impact on wines composition [START_REF] Liu | New molecular evidence of wine yeast-bacteria interaction unraveled by nontargeted exometabolomic profiling[END_REF]Liu et al., 2017).

In this study, we combined various non-targeted analyses in order to characterize the diversity of compounds, which can be potentially extracted from GSH-enriched inactivated dry yeasts when added to wines. Three IDYs with increasing GSH enrichments were characterized for their potential molecular and macromolecular release, and the diversity of the annotated/identified compounds provides new insights on IDY functionalities under winemaking conditions, and underlines crucial IDY compositional differences in a GSHaccumulation process-dependent manner.

Material and methods

Sample preparation

Three non-commercial inactivated dry yeasts were obtained from Lallemand SAS (Blagnac, France). These products were produced at a laboratory scale process allowing optimizing chemical, physical and nutritional features of the bio-process in order to maximize the intracellular concentration of metabolites, notably glutathione. Two products were specifically produced from different yeast strains to increase the bioavailability of glutathione (G-IDY and Gplus-IDY which release 18 mg and 25 mg of glutathione per gram of IDY, respectively). The third product (N-IDY) was produced with the same strain as for G-IDY without following the specific process of GSH accumulation and releases 12 mg of glutathione per gram of IDY. At the first opening of the sealed prepared products, the three IDY products were aliquoted in pre-weighed 2 mL vials under nitrogen and stored at -18°C in dark. Three different extractions were made to obtain: the acidified Water-Soluble Fraction (WSF) from ultrapure water (18.2 MΩ, Millipore, Germany) with 0.01% (v/v) formic acid at pH 3.2, the Model Wine Soluble Fraction (MWSF), from 12% (v/v) ethanol in ultrapure water with 0.01% (v/v) formic acid at pH 3.2, and the Methanol Soluble Fraction (MSF), from methanol with 0.1% (v/v) formic acid. IDYs were resuspended at 4 g/L and soluble fractions were obtained after 1h stirring at room temperature in dark. Samples were then centrifuged (12000 g, 5 min, 4°C) and the supernatants were aliquoted and stored under nitrogen at 4°C until analysis. All samples were prepared in triplicate.

Gel Permeation Chromatography (GPC)

GPC was performed with a high-performance liquid chromatography (HPLC) (Elite LaChromElite, VWR, Radnor, Pennsylvanie) coupled to a Diode Array Detector (DAD)/Fluorescence detector. 50 µL of sample were injected through a column Yarra 3µ SEC-2000 300 x 7.8 mm (Phenomenex, Sartrouville, France) connected to a stationary phase guard column with SecurityGuard (Phenomenex, Sartrouville, France). Elution was performed with hydro-alcoholic solution (12% (v/v) ethanol, 6 g/L of tartaric acid at pH 3.5) in an isocratic gradient (500 µL/min which corresponds to a pressure of 75 bars) for 45 min.

The temperature of the sampler and the column were kept constant at 4°C and 25°C respectively during analysis. Fluorescence detector was set at 280 nm for the excitation wavelength and 350 nm for the emission wavelength, and the DAD enabled absorption spectra acquisition from 200 to 400 nm. Data were acquired with the EZChrom Elite (Agilent Technologies, Santa Clara, California) software, exported as .dat converted into .asc and processed with CHROMuLAN v0.79 (PiKRON Ltd.). Data were calibrated against a low molecular weight standards mix (LMW Gel Filtration calibration kits, GE Healthcare, Buckinghamshire) with the following standards: Conalbumin (75 kDa), Ovalbumin (43 kDa), Ribonuclease A (13.7 kDa), Aprotinin (6.5 kDa) and Angiotensine (1.1 kDa). Elution times were converted into molecular weight masses according to the calibration curve (Supplementary information 1).

Metabolomics analyses by Fourier Transform Ion Cyclotron Resonance Mass Spectrometry

Ultra-high-resolution mass spectra were acquired in negative mode on a Bruker SolariX Ion Cyclotron Resonance Fourier Transform Mass Spectrometer ((-)FT-ICR-MS) (BrukerDaltonics GmbH, Bremen, Germany) equipped with a 12 Tesla superconducting magnet (Magnex Scientific Inc., Yarnton, GB) and a APOLO II ESI source (BrukerDaltonics GmbH, Bremen, Germany), and operating in negative and positive ionization modes. 20 µL sample was diluted in 1mL of pure methanol and then injected at a flow rate of 120 µL/h into the microelectrospray. Spectra were acquired with a time-domain of 4 mega words over a mass range of m/z 147 to 2000. A total of 300 scans were accumulated for each sample. All samples were injected randomly in the same batch to avoid batch variability. External calibration was done with clusters of arginine (10 mg/L in methanol). Internal calibration was performed for each sample by using yeast ubiquitous compounds for negative mode [START_REF] Gougeon | The chemodiversity of wines can reveal a metabologeography expression of cooperage oak wood[END_REF] (Supplementary information 2). External and internal calibration led to a day-to-day mass accuracy lower than 0.1 ppm.

Identification of metabolites by liquid chromatography coupled to time-of-flight mass spectrometry

Metabolite separation was performed with an ultra-high-performance liquid chromatography (Dionex Ultimate 3000, ThermoFischer) coupled to a MaXis plus MQ ESI-Q-ToF mass spectrometer (Bruker, Bremen, Germany). The non-polar and low polar metabolites were separated in reversed phase liquid chromatography (RP-LC) by injecting 5 µL in an Acquity UPLC BEH C 18 1.7 µm column 100 x 2.1 mm (Waters, Guyancourt, France). Elution was performed at 40°C by (A) acidified water with 0.1% (v/v) of formic acid and (B) acetonitrile with 0.1% (v/v) of formic acid with the following gradient: 0-1.10 min 5% (v/v) of B and 95% (v/v) of B at 6.40 min. The flow rate was set at 400 µL/min and maintained for 5min at initial conditions before each injection. Solvent and analytes were ionized with an electrospray (Nebulizer pressure = 2 bars and nitrogen dry gas flow = 10 L/min). Ions transfer was done with an end plate offset at 500 V and transfer capillary voltage at 4500 V. A divert valve was used to inject four times diluted ESI-L Low Concentration Tuning Mix (Agilent, Les Ulis, France) at the beginning of each run, allowing a recalibration of each spectrum. The mass spectrometer was calibrated with undiluted Tuning Mix before batch analysis in enhanced quadratic mode, with less than 0.5 ppm errors after calibration. Spectra were acquired on the 100 to 1500 m/z mass range, both in negative and positive ionization modes. UHPLC-Q-ToF-MS quality control (mix of standard peptides and polyphenols) and experimental quality control (mix of samples) were used to guarantee the UHPLC-Q-ToF-MS system performance. All samples were injected randomly in the same batch to avoid batch-to-batch variability. Features (couple of m/z-values and retention times) fragmentation was performed using the AutoMS/MS function on the most intense features with a frequency of 2 Hz. The fragmentation was done at three different collision energies: 15, 25 and 35 eV.

Data analysis

Results were expressed as the average of three replicates with the associated standard deviations.

(-)FT-ICR-MS data were handled with DataAnalysis (v. 4.3,Bruker Daltonik GmbH).

Calibrated data were filtered to keep only m/z peaks with a signal to noise (S/N) ratio above 10 and an absolute intensity higher than 2.0x10 6 . Peaks alignment was made by Matrix Generator software (v. 0.4, Helmholtz-Zentrum Muenchen) with a mass accuracy window of 1 ppm [START_REF] Lucio | Datamining metabolomics: the convergence point of non-target approach and statistical investigation[END_REF]. Peaks with intensity equal to 0 in more than 80% of samples were removed from the analysis. Finally, the in-house software NetCalc 2015 (v. 1.1a, Helmholtz-Zentrum Muenchen) was used to annotate peaks [START_REF] Tziotis | Letter: Kendrick-analogous network visualisation of ion cyclotron resonance Fourier transform mass spectra: improved options for the assignment of elemental compositions and the classification of organic molecular complexity[END_REF]. 46% of the initially aligned peaks were annotated by NetCalc and used for this study. Van Krevelen diagrams, which plot the H/C against the O/C ratio of annotated metabolites were generated by an Excel file, providing instantaneous chemical pictures of the metabolites diversity [START_REF] Brockman | Van Krevelen diagram visualization of high resolution-mass spectrometry metabolomics data with OpenVanKrevelen[END_REF][START_REF] Kim | Graphical Method for Analysis of Ultrahigh-Resolution Broadband Mass Spectra of Natural Organic Matter, the Van Krevelen Diagram[END_REF]. The OligoNet webserver was also used to annotate potential peptides with a max error of 1 ppm (Liu et al., 2017).

The UHPLC-Q-ToF-MS data were calibrated internally by 1/4 diluted tuning mix with DataAnalysis (v. 4.3,Bruker Daltonik GmbH). Calibrated features were filtered to retain those with signal/noise ratio (S/N) higher than 30 and an absolute intensity of at least 1000.

Before features extraction, the spectral background noise was removed. The extracted features were aligned with a R script with a m/z tolerance of 2 ppm and retention time tolerance of 0.2 seconds.

Parent ions and fragments were submitted to different databases with the MassTRIX interface (http://masstrix.org) [START_REF] Suhre | MassTRIX: mass translator into pathways[END_REF], Metlin (https://metlin.scripps.edu) and YMDB 2.0 (http://www.ymdb.ca) [START_REF] Ramirez-Gaona | YMDB 2.0: a significantly expanded version of the yeast metabolome database[END_REF]. According to the precision of UHPLC-Q-ToF-MS and (-)FT-ICR-MS, an error of 3 ppm and 1 ppm was chosen respectively for the annotation of the metabolites [START_REF] Roullier-Gall | High precision mass measurements for wine metabolomics[END_REF][START_REF] Roullier-Gall | Integrating analytical resolutions in non-targeted wine metabolomics[END_REF]. The combination of these databases enabled covering the widest range of metabolites found in biological systems, and notably in yeast.

Results and discussion

IDY macromolecular profile

Besides the obvious discrimination between soluble and non-soluble fractions in a specific medium, the gel permeation chromatography is dedicated to determine the global size repartition of compounds within complex samples. This first experiment was a good always low, whatever the solvent used (Supplementary information 3). However, methanol extracts showed limited high molecular weight compounds response, probably because of organic solvent precipitation [START_REF] Chertov | Organic solvent extraction of proteins and peptides from serum as an effective sample preparation for detection and identification of biomarkers by mass spectrometry[END_REF].

FIGURE 1

The second time-frame window (II) in the chromatogram, between 17. In addition, in order to get a more representative characterization of IDY soluble fractions, UV detection at 210 nm was also considered. UV detection is less sensitive and less specific compared to fluorescence, but allows the peptide bond, carbon to carbon and carbon to oxygen double bond detection [START_REF] Stoscheck | Quantitation of protein[END_REF]. Supplementary information 2 shows chromatograms of G-IDY, Gplus-IDY and N-IDY for the three extraction media, recorded at 210 nm. UV responses were far less important than those monitored with fluorescence, and concerned specifically the third time-domain corresponding to the low molecular weight compounds (below 5 kDa).

On the basis of these results, and whatever the detection method or the extraction medium used, GPC could not discriminate IDY soluble fractions. The medium and high molecular weight compounds showed a similar fluorescent profile among samples which indicated that the bio-process enrichment would only impact the low molecular weight fraction of IDYs. In that respect, to further the characterization of IDY soluble fractions, ultrahigh-resolution mass spectrometry was used to assess the diversity of the abundant low molecular weight compounds.

IDY low molecular weight chemical diversity

The ultra-high accuracy of (-)FT-ICR-MS enables the exact mass of ionizable compounds present in complex matrices to be determined, including wine, thus allowing to have a more comprehensive picture of the chemical diversity present in the sample [START_REF] Roullier-Gall | Sulfites and the wine metabolome[END_REF], 2014). Based on this result, G-IDY, Gplus-IDY and N-IDY MWSFs were compared in order to characterise the diversty of IDY extractible compounds. For all conditions, yeast derivatives were inactivated by short term heating before being dried and sealed hermetically for storage.

In that respect, compounds potentially released by IDY are a combination of bio-accumulated metabolites and bio-transformed compounds related to the production process. Since the inactivation and drying process were identical for the three IDYs, it can be assumed that the major contribution to the diversity could be mainly attributed to the bio-process.

As shown in Figure 2B, 37.1% of the overall 1674 extractable ions were common to each IDY and only 1.8%, 3.9% and 11.7% of the ions were unique to G-IDY, N-IDY and Gplus-IDY, respectively. We also observed that N-IDY and G-IDY, obtained from the same yeast strain, shared more common ions (62.1%) than with Gplus-IDY (46.1% and 48.6% respectively). These results show that both the intracellular accumulation of glutathione and the yeast strain are key factors modifing the metabolic signatures of IDY soluble fractions, in agreement with existing literature [START_REF] Allen | High-throughput classification of yeast mutants for functional genomics using metabolic footprinting[END_REF][START_REF] Brauer | Conservation of the metabolomic response to starvation across two divergent microbes[END_REF][START_REF] Dikicioglu | Short-and longterm dynamic responses of the metabolic network and gene expression in yeast to a transient change in the nutrient environment[END_REF].

FIGURE 2

Network annotation of the m/z ions present in MWSF by NetCalc software allows access to the molecular formulas of 53% of the 1674 ions detected. The extensive chemical differences between G-IDY, Gplus-IDY and N-IDY MWSFs were clearly visible from the histograms depicting the distribution of elemental compositions (CHO, CHON, CHOS, and CHONS), along with Van Krevelen diagrams of the (-)FT-ICR-MS derived molecular formulas (Figure 3). Figure 3A presents the 379 annotated m/z ions (42.7%) common to the three IDYs soluble fractions in model wine (MWSF). These ions could be considered as representative of extractable metabolites from IDYs whatever the strain or the production process. Common ions were found in different chemical spaces such as lipid-like, peptide-like and saccharide-like domains, which agrees with a glutathione accumulation bioprocess that preserves the yeast basic metabolism during the production.

FIGURE 3

Figure 3B, 3C and 3D show annotated masses unique to each MWSFs, colored according to their chemical compositions and sized according to their mass peak relative intensity. An overview of the Van Krevelen diagrams reveals significant differences between the samples in terms of number of unique formulas (already visible in Figure 2) and chemical families. N-IDY (Figure 3D) appeared much richer in unique CHO containing formulas (16) than G-IDY

(3) and Gplus-IDY (0). These formulas are mainly in peptide-like and lipid-like domains, which could correspond to small chain fatty acids for example. In contrast, Gplus-IDY (Figure 3B) was characterized by a significantly higher number of unique CHONS containing formulas compared to G-IDY and N-IDY (36 against 3 and 1, respectively). These formulas, mainly located in the peptide-like domain could correspond to peptides with sulfur-containing amino acid residues, such as methionine and cysteine. The high diversity of sulfhydryl containing compounds (-SH group) could explain the relative activity of these products against oxidation, as it is known than peptides and thiols could have antioxidant property in wine [START_REF] Elias | Antioxidant Activity of Proteins and Peptides[END_REF][START_REF] Nikolantonaki | Reactivity of volatile thiols with polyphenols in a wine-model medium: Impact of oxygen, iron, and sulfur dioxide[END_REF][START_REF] Nikolantonaki | Measuring protection of aromatic wine thiols from oxidation by competitive reactions vs wine preservatives with ortho-quinones[END_REF]. It is remarkable to note how the glutathione enrichment process, which is designed to accumulate intracellular glutathione, is actually accompanied by an overall increase of the CHONS/CHO ratio when going from N-IDY to Gplus-IDY (Figure 3E), with G-IDY potentially releasing 3 times more CHONS compounds than N-IDY, and Gplus-IDY releasing more than 10 times more compounds than N-IDY. With a moderate hypothesis of 3 isomers per (-)FT-ICR-MS ion, these results show altogether that Gplus-IDYs would be discriminated by more than 100 different N,Scontaining compounds, compared to G-IDY and N-IDY, thus providing an unprecedented molecular representation of the actual metabolic response of glutathione enrichment. The relatively low number of unique compounds released from G-IDY is not surprising since it is obtained from the same strain as N-IDY, and it follows the same bio-process as Gplus-IDY, thus most of the released compounds are likely shared with at least one other IDY. Although it was not the aim of this study, it is further interesting to note the strain-dependency of the glutathione enrichment process, with Gplus-IDY releasing nearly 4 times more CHONS compounds than G-IDY while the released glutathione is increased by 2.

Impact of GSH enrichment process on IDYs peptides diversity

The presence of cysteine in the growth medium during IDY GSH accumulation processing at industrial scale [START_REF] Li | Glutathione: A review on biotechnological production[END_REF], modifies the global metabolism of sulfur amino acids and leads to over representation of sulfur-containing metabolites [START_REF] Thomas | Metabolism of sulfur amino acids in Saccharomyces cerevisiae[END_REF]. As the Van Krevelen diagrams highlight the increasing diversity of CHON and CHONS containing compounds along with the enrichment process, this diversity could be putatively attributed to peptides containing cysteine or methionine residues. Amongst the 1674 m/z submitted to the OligoNet webserver, 193 were annotated as potential peptides (from 2 to 5 residues) with an error below 1ppm (Supplementary information 4). Within the 193 annotated ions, 132 have a Multiple Amino Acids Combination (MAAC) and 61 a Unique Amino Acids Combination (UAAC) (Figure 4A). Most of the peptides (144 m/z) are common to at least two out of three IDYs, whereas Gplus-IDY presents the greatest diversity with 40 peptides against 7 and 2 for G-IDY and N-IDY, respectively. (Figure 4B). Amongst the UAAC, 26 out of 65 contain a cysteinyl residue. These unambiguous annotations of peptides allowed all possible connections between these peptides to be determined (Supplementary information 5). The Gplus-IDY clearly released more unique peptides and more peptides with a cysteinyl residue. Nevertheless, most of the UAAC are shared between the IDYs (regardless of their relative concentrations). The global similarity between our samples analyzed by (-)FT-ICR-MS allowed us to compare the absolute intensity between samples providing an indication of the abundance of each compound released. Figure 4C reveals that within the 61 UAAC released by the IDY, Gplus-IDY released 28 peptides significantly more intense than G-and N-IDY (3 peptides and 1 peptides respectively). These results are in accordance with the Van Krevelen diagram (Figure 3B) showing a higher diversity of compounds in the peptide-like domain for Gplus-IDY.

FIGURE 4

In addition to the peptides enrichment, other metabolites could be impacted by the bioprocess. (-)FT-ICR-MS enables to have access to the elemental formulas of detected ions and thus to acquire instantaneous metabolic fingerprints of what can be released by IDYs. Since a single CHONS elemental formula can be associated with numerous compounds, (especially for high m/z ions) the combination with separative UHPLC-Q-ToF-MS and UHPLC-Q-ToF-MS S/MS methods was used to access structural and quantitative information about these molecular markers [START_REF] Roullier-Gall | High precision mass measurements for wine metabolomics[END_REF]. The highest resolution of the (-)FT-ICR-MS (600,000 against 20,000 for UHPLC-Q-ToF-MS at m/z 306) was used to annotate UHPLC-Q-ToF-MS peaks which could be aligned with (-)FT-ICR-MS peaks, using an in-house designed alignment script. Up to 128 m/z peaks of the UHPLC-Q-ToF-MS spectra where found to match (-)FT-ICR-MS peaks (with an absolute error lower than 2 ppm) (Supplementary information 6) . Alignment was done on the basis of the similarity of m/z without consideration of the retention time, only for the negative mode of the UHPLC-Q-ToF-MS . The aim was to have both an unambiguous annotation of UHPLC-Q-ToF-MS ions with the ultrahigh resolution of (-)FT-ICR-MS, and quantitative information from UHPLC-Q-ToF-MS. Ions present UHPLC-Q-ToF-MS data but not found in (-)FT-ICR-MS data (Figure 4B) were likely molecules easily suppressed in direct infusion with ESI, showing the added value of using chromatographic separation before MS analysis [START_REF] Roullier-Gall | High precision mass measurements for wine metabolomics[END_REF].

Keeping in mind the formula annotation of m/z ions with the (-)FT-ICR-MS data, the fragmentation of 16 important ions (issued from positive and negative ionization mode) enabled to have access to molecular structural information. Fragments were submitted to metabolomic databases, and annotation of the parent's ions are summarized in Table 1.

Following the new prescriptions of Sumner and collaborators, the identification point (which gives the identification confidence level) of each metabolite is 5.5 (High resolution retention time, accurate mass of parent ion, molecular formula based upon accurate m/z and isotope pattern and accurate tandem mass spectrum) [START_REF] Sumner | Proposed quantitative and alphanumeric metabolite identification metrics[END_REF]. Most of these compounds were already described in yeast metabolic pathways, but never so far as compounds which could be potentially extracted from IDY in winemaking conditions. Most interestingly, glutathione and its precursor (glutamyl-cysteine) were found in the three extracts, but consistently with the enrichment process, i.e. with a relative abundance following the Gplus > G > N trend. In contrast, lysine-leucine and arginine-leucine dipeptides appeared as GPlus-IDY markers, whereas homocitric acid appeared as N-IDY marker. Amino acids (glutamate, tyrosine, phenylalanine), which have been extensively studied in IDY [START_REF] Pozo-Bayón | Characterization of commercial inactive dry yeast preparations for enological use based on their ability to release soluble compounds and their behavior toward aroma compounds in model wines[END_REF] were examples of contrasted trends with relative concentrations that did not appear to be directly correlated to the GSH accumulation process. Similarly, methyl-thioadenosine, a precursors of adenosylmethionine which is a sulfur and nitrogen stock molecule in poor medium [START_REF] Shapiro | Conversion of 5'-methylthioadenosine into Sadenosylmethionine by yeast cells[END_REF], and thus a potential fermentation enhancer already putatively annotated in IDYs [START_REF] Rodriguez-Bencomo | Impact of glutathione-enriched inactive dry yeast preparations on the stability of terpenes during model wine aging[END_REF] were identify in the three samples. Weak organic acids like citric acid have been described for their sensory impact (fresh notes), whereas homocitric acid and pipecolic are related to the lysine metabolism in yeast [START_REF] He | Pipecolic acid in microbes: Biosynthetic routes and enzymes[END_REF][START_REF] Tucci | Homocitrate synthase from yeast[END_REF], but not yet described in IDYs. Finally, the pantothenic acid, which exhibits a promoting effect on yeast growth [START_REF] Richards | The stimulation of yeast proliferation by pantothenic acid[END_REF] is much more present in N-IDY than in G-IDY and Gplus-IDY. Adenosine and arginine-leucine were recently shown to possibly promote bacteria growth [START_REF] Liu | New molecular evidence of wine yeast-bacteria interaction unraveled by nontargeted exometabolomic profiling[END_REF]Liu et al., 2017) and thus facilitate the malolactic fermentation. Whereas Adenosine are abundant in the three IDYs, the dipeptide Arg-Leu is specific to Gplus-IDY and almost absent in the other IDYs.

Such structural identifications provide a good overview of the richness and the diversity of compounds released by IDYs, and it also highlights the yet unknown potential contribution of IDYs during fermentation.

TABLE 1

Most of the ions detected by (-)FT-ICR-MS and UHPLC-Q-ToF-MS are difficult to isolate and fragment, which implies that most of the compounds present in the MWSFs are still largely unknown. Supplementary Information 7 gives the list of NetCalc annotated (-)FT-ICR-MS peaks found in the database, with the relative intensity of each ion and these possible database ID with an error lower than 2ppm. In this way we can have a quick overview of specific and common compounds from each IDY and appreciate how the medium is modified by using specific IDY.

Conclusion

In this work, the soluble fraction that can be extracted from three inactive dry yeasts by model wine, were characterized by a combination of Gel Permeation chromatography (GPC), (-)FT-ICR-MS and UHPLC-Q-ToF-MS in order to provide a comprehensive picture of the diversity of potentially active compounds associated with the glutathione accumulation process. To that purpose, the extract of non-enriched IDYs (N-IDY) was compared to extracts of an GSH-rich IDY from the same strain (G-IDY) and an even more GSH-rich IDY, but from a different strain (Gplus-IDY). Consistently with the expected GSH accumulation process, Gplus-IDY exhibited higher amounts of extractable glutathione (and its glutamylcysteine precursor) than G-IDY, which in turn appeared richer than N-IDY. Moreover, the increase in peptides containing cysteinyl residues in Gplus-IDY shows than the glutathione accumulation bio-process also impacts the peptidome of the yeast. Modulation of the GSH pathway leads to a global modification of cysteine incorporation and thus could have important implications in wine making.

Our metabolomic approach provided a comprehensive molecular picture of the detailed impact of the glutathione accumulation process. It further revealed how the yeast strain can modulate the extent of the accumulation process, with the annotation of more than hundred N,S-containing potential active compounds for Gplus-IDYs, most of them being unknown yet. Altogether, our results shed important light on the potential activity of IDYs on musts and wines, in terms of organoleptic and/or stability properties. For each IDY, the total number of annotated masses corresponding to CHO and CHONS were used to calculate this ratio.

Figure and Table Captions

  introduction to understand the relatively unknown diversity of compounds released by IDY in different extraction media. Acidified water and model wine media were chosen to identify what can be released by IDY in must and wine, respectively. Methanol was used to have an overview of the mildly hydrophobic soluble fraction present in our samples, independent of the oenological conditions in winemaking process. In this experiment, it was possible to separate macromolecules from 300 kDa to 5 kDa between 9.5 min and 22.5 min depending on the column specification. Separation was performed with model wine and without any denaturant to keep macromolecules in their native forms. The fluorescent detector was set up to track the presence of potent proteinaceous fluorophores among the chromophore extracted from yeast extracts[START_REF] Coelho | Asymmetrical flow field-flow fractionation of white wine chromophoric colloidal matter[END_REF]. Figure1shows GPC chromatograms of MWSF for G-IDY, Gplus-IDY and N-IDY and supplementary information 3 shows those for WSF and MSF. These chromatograms clearly revealed three different time frame windows common to all MWSF extracts. The first time-frame (I) between 9.5 and 17.3 min (outside of the calibrated region) represents about 1 % of the total fluorescent response and had a mass range from 300 to 75 kDa. G-IDY, Gplus-IDY and N-IDY showed no significant differences in abundance of high molecular weight molecules in this region. This result is in agreement withPozo-Bayon and collaborators (2009), who reported that high molecular weight compounds are in lower concentration than peptides and amino acids in the model wine soluble fraction of different IDY[START_REF] Pozo-Bayón | Characterization of commercial inactive dry yeast preparations for enological use based on their ability to release soluble compounds and their behavior toward aroma compounds in model wines[END_REF]. Under our experimental conditions, the percentage of high molecular weight compounds released from G-IDY, Gplus-IDY and N-IDY was

  3 and 22.5 min, represents medium molecular weight compounds in a mass range from 75 to 5 kDa, the latter corresponding to the exclusion limit of the column. G-IDY, Gplus-IDY and N-IDY relative concentrations in medium molecular weight compounds varied from 7 to 14% of the total fluorescence of the sample, in an extraction medium dependent manner. In detail, WSF and MWSF exhibited concentrations in medium molecular weight compounds, which were 1.5 times higher for Gplus-IDY compared to those for G-IDY and N-IDY. However, MSF presented relatively low concentrations of medium molecular weight compounds, of about 3% of the total fluorescence responses (Supplementary information 3). Finally, the most abundant fluorescent responses (whatever the extraction media) were observed for the third time-frame (III) from 22.5 to 45 min, where fluorescent compounds accounted for 92%, 91% and 86% of the total fluorescence response of G-IDY, N-IDY, and Gplus-IDY respectively in model wine extraction medium. This chromatographic region is out of the molecular size exclusion limit of 5 kDa of the column and suggests the importance of low molecular weight compounds on the IDY soluble fraction independently of the extraction medium.

  Figure 2A gives an overview of the number of ions detected in one specific IDY (G-IDY) in the three different extraction media. Within the 1280 ions detected for G-IDY, 701 (54.8%) were common to the three extraction media and only a total of 40 ions (3.2%) were found to be medium specific. MWSF showed the best extraction yield with 97.4% of the total extractable m/z ions (N-IDY and Gplus-IDY MWSF had similar extraction yields with 85.4% and 89% respectively, data not shown). The polarity of the model wine appears to lead to a better solubilization of IDY compounds than water and methanol alone.

Figure 1 :

 1 Figure 1: Gel permeation chromatograms of model wine soluble fractions (MWSF) of G-IDY (red), Gplus-IDY (green) and N-IDY (black) with fluorescence detection (EX/EM = 280/350 nm). Dotted lines indicate the calibration areas based on standard compounds.

Figure 2 :

 2 Figure 2: Venn diagrams presenting the total counts of detected ions by (-)FT-ICR-MS, with percentages in brackets. (A) Extraction yield for the specific G-IDY in the three extraction media, and (B) unique and common ions to the model wine soluble fractions of N-IDY, G-IDY and Gplus-IDY.

Figure 3 :

 3 Figure 3: Van Krevelen representation of annotated masses from (-)FT-ICR-MS analyses of the MWSFs (Model Wine Soluble Fraction) of Gplus-IDY, G-IDY and N-IDY. (A) masses shared by Gplus-IDY, G-IDY and N-IDY MWSFs. (B) Specific m/z ions to Gplus-IDY , (C) specific m/z ions to G-IDY, and (D) specific m/z ions to N-IDY. In B, C and D common m/z ions were depicted in grey. Van Krevelen plots were coloured according to molecular classes i.e CHO (blue), CHOS (green), CHON (orange), CHONS (red). Bubble sizes correspond to the triplicate averaged relative intensities of mass peaks. Bar histograms indicate the number (and corresponding percentage at the bar-top) of molecular formulae presented in the Van Krevelen diagrams. (E) Relative abundance of CHONS against CHO for the three MWSFs.

Figure 4 :

 4 Figure 4: 193 potential peptides annotation, out of the 1674 m/z from (-)FT-ICR-MS submitted to the OligoNet webserver. (A) Annotations correspond to 142 Multiple Amino Acid Combination (MAAC, with 89 and 43 with and without cysteinyl residue respectively) and 61 Unique Amino Acid Combination (UAAC, with 26 and 35 with and without cysteinyl residue respectively). (B) Within the 193 potential peptides N-IDY (red), G-IDY (blue) and Gplus-IDY (green) released 2, 7 and 40 unique m/z attributed to peptides, respectively. The 144 remaining potential peptides are shared (grey) by at least 2 IDYs. (C) Amongst the 61 UAAC, 28 are significantly more released by Gplus-IDY, in contrast only 3 and 1 are more abundant using G-or N-IDY respectively (p-value < 0.05).

Table 1 :

 1 Metabolites fragmented by UHPLC-Q-ToF-MS/MS in the MWSF for the three IDYs, and their corresponding chemical family. Main fragments used to identify features from databases are listed in the discriminant fragments column allowing a high confidence level. Relative abundance of metabolites between IDYs is expressed as percentage of the biggest area. The identification is the combination of composition elucidation by (-)FT-ICR-MS (when available) and structural elucidation by UHPLC-Q-ToF-MS /MS.

								Area (%)
	m/z Adduct	Ret. time (min)	Collision energy (eV)	Discriminant Fragments	Annotation [M]	Error (ppm)	N-IDY G-IDY	Gplus-IDY	Identified metabolite	Database ID
	130.0863 [M+H]+	0.7		84.0808	C 6 H 11 NO 2	0.35	100	43	41	Pipecolic acid	C00408 (KEGG)
	148.0601 [M+H]+	0.6		84.0447;130.0497	C 5 H 9 NO 4	-2.03	100	78	53	Glutamic acid	C00025 (KEGG)
	165.0548 [M+H]+	0.7		147.0442;119.0492 ;91.0544	C 9 H 8 O 3	1.08	47	30	100	Coumaric acid	C12621/ C00811 (KEGG)
	166.0861 [M+H]+	1.0		166.0862;120.0806 ;131.0490	C 9 H 11 NO 2	-1.20	44	36	100	Phenylalanine	C00079 (KEGG)
	179.0485 [M+H]+	0.7		162.0222;144.0116 ;116.0164	C 5 H 10 N 2 O 3 S	0.06	36	91	100	Cysteinyl-glycine	C01419 (KEGG)
	182.0811 [M+H]+	0.7		136.0757;123.0438 ;147.0442	C 9 H 11 NO 3	-0.55	71	43	100	Tyrosine	C00082 (KEGG)
	191.0199 [M-H]-	0.7		173.0095;129.0197 ;111.0094	C 6 H 8 O 7	1.05	100	37	17	Citric acid	C00158 (KEGG)
	205.0355 [M-H]-	0.8		143.0352;125.0248	C 7 H 10 O 7	0.49	100	<1	<1	Homocitric acid	C05662 (KEGG)
	218.1037 [M-H]-	1.1		146.082	C 9 H 17 NO 5	1.38	100	63	73	Pantothenic acid	C00864 (KEGG)
	251.0693 [M+H]+	0.7		122.0269;130.0497 ;188.0373	C 8 H 14 N 2 O 5 S	-1.19	19	71	100	Glutamyl-cysteine	C00669 (KEGG)
	258.11 [M+H]+	0.6		184.0735;104.1070 C 8 H 20 NO 6 P	-0.39	18	23	100 Glycerophosphocholine C00670 (KEGG)
	260.1969 [M+H]+	0.8		147.1132;129.1025 ;84.0810	C 12 H 25 N 3 O 3	0.12	<1	<1	100	Leucyl-lysine	HMDB28912 (HMDB)
	268.1037 [M+H]+	0.7		119.0353;136.0617 C 10 H 13 N 5 O 4	-1.12	92	100	94	Adenosine	C00212 (KEGG)
	288.2030 [M+H]+	0.8		271.1763;175.1187 C 12 H 25 N 5 O 3	-0.06	<1	<1	100	Leucyl-arginine	HMDB28923 (HMDB)
	298.0970 [M+H]+	1.3		136.0616;145.0320 C 11 H 15 N 5 O 3 S	0.67	74	100	85	Methyl-thioadenosine C00170 (KEGG)
	306.0763 [M-H]-	0.7		272.0890;143.0464 ;210.0882	C 10 H 17 N 3 O 6 S -0.65	33	89	100	Glutathione	C00051 (KEGG)

ACKNOWLEDGEMENTS

The authors acknowledge the Regional Council of Bourgogne -Franche-Comté, the "Fonds Européen de DEveloppement Régional (FEDER)" and Lallemand SAS (31, Blagnac), for financial support. They also would like to thank Dr. Eveline Bartowsky for a careful reading of the manuscript by a native English speaker.

The authors wish to confirm that there are no conflicts of interest associated with this publication.

14299197); Adenosine (PubChem CID: 60961); Glutamyl-cysteine (PubChem CID: 123938); Pantothenic acid (PubChem CID: 6613); Cysteinyl-glycine (PubChem CID: 439498); Pipecolic acid (PubChem CID: 439227); Homocitric acid (PubChem CID: 5460287); Methyl-thioadenosine (PubChem CID: 439176)

Conflicts of interest