Benjamin Lejeune
email: benjamin.lejeune@uliege.be

Anna Marcout

Dorothée Kopp

Fabien Morandeau

Sonia Mehault

Maud Aline Mouchet

Assessing discard consumption dynamic in shallow coastal environment using underwater video

Keywords: Behavioral interactions, Carrion, Facultative scavenger, Fisheries discards, Offal, Trophic Ecology

Food webs are typically studied with respect to predator-prey interactions while often neglecting to address the role or importance of scavenging (i.e. carrion consumption) on their structure and functioning. In some environmental contexts, scavenging can play a key role in supporting populations and communities as exemplified by seabirds feeding on fisheries

discards. Yet, a substantial part of fisheries discards sinks in the ocean where the range of consumers is most likely underestimated, owing to a lack of comprehensive understanding of the scavenging ability of marine fauna and local-scale empirical studies. Here, we deployed baited remote underwater video surveys (BRUVs) using discarded fish as baits to study the taxonomic richness of consumers, their interactions and consumption dynamic of discards in shallow coastal fishing grounds subject to discarding (Bay of Bourgneuf, North East Atlantic, France). We show that discards attract and are consumed by a wide taxonomic and trophic diversity of species. Interestingly, only one species observed is considered an obligate scavenger, while scavenging is little known or considered anecdotal in most other identified taxa. Analysis of consumption dynamic and interactions around discards revealed intra and interspecific competition among discard consumers as well as successions between consumers involved in predator-prey interactions. Data also suggests that decapods may facilitate discard consumption by non-piscivorous fish by generating scraps during consumption. We argue that underwater video surveys provide a valuable tool to better assess the occurrence and extent of facultative scavenging behaviors within marine communities and understand its role in food web dynamic.

Introduction

Food webs are typically studied with respect to predator-prey interactions while often neglecting to address the role or importance of scavenging (i.e. the consumption of carrion, or dead animals, that the consumer has not killed itself) on their structure or functioning [START_REF] Beasley | Ecological role of vertebrate scavengers[END_REF][START_REF] Depestele | The Impact of Fisheries Discards on Scavengers in the Sea[END_REF]. In some environmental contexts, scavenging can play a key role in supporting populations and communities, and be linked to human activities, as exemplified by seabirds feeding on fisheries discards (e.g. [START_REF] Garthe | Amounts of discards by commercial fisheries and their significance as food for seabirds in the North Sea[END_REF][START_REF] Votier | Changes in fisheries discard rates and seabird communities[END_REF][START_REF] Sherley | Scavenger communities and fisheries waste : North Sea discards support 3 million seabirds, 2 million fewer than in 1990[END_REF]. Fisheries discards correspond to unwanted catches (or bycatches) that are immediately returned to the sea, either dead or alive. Together with offal (discharge resulting from the processing of some target species onboard, e.g. guts, head, fins), they correspond to fisheries waste that may reintegrate marine food webs and support various marine fauna in sometimes neglected or underassessed ways [START_REF] Laptikhovsky | Fishery discard management and environmental impact in Falkland Islands Fisheries[END_REF]Lejeune et al., 2022b). Indeed, a substantial part of fisheries waste is not directly consumed by above surface scavengers, but sinks through the water column to become potential food sources for pelagic, demersal and finally benthic organisms [START_REF] Depestele | Favorites and leftovers on the menu of scavenging seabirds: modelling spatio-temporal variation in discard consumption[END_REF][START_REF] Oro | Ecological and evolutionary implications of food subsidies from humans[END_REF]). Yet, their consumption is considered to be underestimated in marine ecosystems, owing to a lack of comprehensive understanding of the scavenging ability of marine fauna and local scale empirical studies [START_REF] Depestele | The Impact of Fisheries Discards on Scavengers in the Sea[END_REF][START_REF] Guillen | A review of the European union landing obligation focusing on its implications for fisheries and the environment[END_REF]. In particular, little information is available about how species interactions may structure scavenger communities either via antagonistic behaviors (e.g. limiting the access to discards [START_REF] Davenport | Behavioural responses of shallow-water benthic marine scavengers to fish carrion: a preliminary study[END_REF] or positive interactions (e.g. gaining access to discards by relying on other better equipped species such as crabs for dismantling them first; [START_REF] Jenkins | Predator and scavenger aggregation to discarded by-catch from dredge fisheries : importance of damage level[END_REF].

Two types of scavengers can be distinguished: obligate scavengers (e.g. hagfish) that rely on carrion for survival or reproduction and facultative scavengers (e.g. crustaceans, echinoderms, fish) feeding on dead animals but which do not depend solely on carrion for their survival or reproduction [START_REF] Beasley | Ecological role of vertebrate scavengers[END_REF]. While the first category is restrictive and relatively well studied, studying facultative scavenging behaviors in marine fauna is a difficult task. Indeed, carrion, whether naturally occurring or linked to fishing (e.g. fisheries discards or marine fauna damaged by towed gear) are typically considered scarce, unpredictable and potentially quickly assimilated in marine environments [START_REF] Davenport | Behavioural responses of shallow-water benthic marine scavengers to fish carrion: a preliminary study[END_REF][START_REF] Depestele | The Impact of Fisheries Discards on Scavengers in the Sea[END_REF]. Moreover, diet assessment based on gut content analysis cannot ascertain whether ingested items were alive preys or carrion. Consequently, one may have to rely on other information such as consumers known diet, trophic traits (e.g. trophic level, trophic guild) and the importance of local discarding activity to evaluate whether specific prey ingestions likely resulted from predation on live prey or scavenging on discards (Lejeune et al., 2022b). In addition, it is not clear whether obligate scavengers or piscivorous species would necessarily be the first to detect and consume carrion or whether other species seemingly less adapted to consume this type of resource may more generally be able to benefit from it. One way to assess whether species are attracted and able to consume carrion (i.e. depicting scavenging behavior) is to rely on baited remote underwater videos (BRUV) using carrion as baits (e.g. [START_REF] Jenkins | Predator and scavenger aggregation to discarded by-catch from dredge fisheries : importance of damage level[END_REF][START_REF] Davenport | Behavioural responses of shallow-water benthic marine scavengers to fish carrion: a preliminary study[END_REF]. This is considered one of the only technique allowing direct observation of discard consumption, while also allowing to study its dynamic, including detection time, chronology of arrival of different groups and species interaction around discards to empirically determine the scavenging abilities of diverse marine fauna. Better understand the process of reintegration of discards within marine food webs is a timely issue since multiple countries around the world (e.g. the European Union, Norway, Chile, New Zealand) are currently aiming to reduce discarding practices [START_REF] Guillen | A review of the European union landing obligation focusing on its implications for fisheries and the environment[END_REF].

Here, we aimed to obtain direct evidence of species attracted and consuming discards, as well as describe discard consumption dynamic (consumers detection time, chronological order of arrival and associations) and characterize consumers behavioral interactions around discards that might play a role in consumption dynamic. To this end, we conducted BRUV surveys in a shallow coastal fishing ground subject to discarding activity (Bay of Bourgneuf, France, North East Atlantic). We hypothesized that (1) discards would not only attract obligate scavengers, but also a wide range of opportunistic species that are not typically considered as scavengers, (2) antagonistic interactions (competition or predation) may play a role in structuring discard consumption dynamic and (3) species which may be deemed unable to feed upon discarded fish according to their trophic morphology or known ecology may benefit from the presence of better equipped scavengers allowing them to exploit discards (e.g. presence of crabs dismantling and dispersing discards).

Material and methods

Study site

The study took place in the Bay of Bourgneuf (Bay of Biscay, France, Northeast Atlantic; 2.30•W 47.05•N). The bay is shallow (from 0 to 34 m depth) and covers a relatively small area (320 km 2 ), but is diverse in terms of substrate types (i.e composed of a variety of patchy rocky, sandy and muddy bottoms) and species occurrence [START_REF] Gauduchon | Captures et rejets des métiers de pêche français[END_REF]. It has long been exploited by fisheries and subject to discarding practices [START_REF] Cornou | Captures et rejets des métiers de pêche français[END_REF], which makes it an ideal area to study potential discard consumers and to describe intra and inter specific interactions around discards. The climate is temperate and oceanic with a mean daily air temperature ranging from 4 °C in January to 23 °C in August [START_REF] Morfin | Using acoustic telemetry to estimate post-release survival of undulate ray Raja undulata (Rajidae) in northeast Altantic[END_REF]. In July-August, averaged daily water temperature is 15 °C (min-max range = 13 -26 °C).

Video deployment and acquisition

We monitored the consumption of discards by local marine fauna during daylight using baited remote underwater video systems (BRUVs) set on the sea bed within a 2 km radius in the bay of Bourgneuf and at depth ranging between 5 and 12m, between July and August of 2019 and 2020. BRUVs consisted in a camera (GoPro Hero 7) fixed to a cage or a tripod, orientated towards the seafloor and pointing towards a bait (i.e. discarded fish carcass) (Figure A.1). One to three dead fish from a single species were fixed within the field of the camera with spikes or strings. Dead fish used were collected from local discarding activity and corresponded to some of the species most commonly discarded in the area: horse mackerel (Trachurus trachurus), black seabream (Spondyliosoma cantharus), gurnards (Eutrigla gurnardus or Chelidonichthys cuculus), mackerel (Scomber scombrus), whiting (Merlangius merlangus), hake (Merluccius merluccius), and pout (Trisopterus luscus).

Data collection

A total of 31 videos ranging from 17 min 34 s to 5 h 14 min 34 s were analyzed over the study period (Table 1). Each video sequence begins once the BRUV is settled on the bottom and ends when the discard is no longer visible (consumed or dragged outside of the camera's view) or the memory storage is full. For each video sequence, we noted the taxonomic identity of each individual consumer, the start of consumption time (i.e. when the individual touches and consumes the discard or parts of it that were previously scattered around the BRUV by other consumers), the end of consumption time (i.e. leaving) and occurrences of intra or interspecific behavioral interactions happening within the field of the camera. It is worth noting that contact with the discard could only be acknowledged when occurring above it, since any contact happening below would be out of the camera's field. All consumers were identified to the lowest taxonomic level possible based on morphological characteristics, following [START_REF] Martin | Les invertébrés marins du golfe de Gascogne à la Manche orientale[END_REF] for invertebrates and [START_REF] Froese | FishBase [WWW Document[END_REF] for fish.

Table 1: Summary of videos data. ID = video ID. Discards = number of individual baits used. Fixation = camera's fixation system. Seafloor contact: 1 = direct contact between the discard and the seafloor, 0 = no contact. Algae: 1 = presence of algae, 0 = no algae. Visibility = visibility score (1 = correct, 2 = medium and 3 = low).

Description of discard consumers taxonomic richness

We characterized consumer taxa occurrence and taxonomic richness observed across BRUVs to obtain a view of the diversity of potential discard consumers in the Bay of Bourgneuf.

Taxonomic richness was assessed by counting the total number of different consumer taxa present in each video sequence. We used a multiple regression approach with model selection and averaging based on the AICc (delta < 2) in the R package MuMIn [START_REF] Bartoń | MuMIn: Multi-model inference[END_REF] in R version 3.1.0 (R Core Team, 2021) to explore the potential influence of experimental and environmental variables (categorical and continuous) on consumers taxonomic richness prior to further data analysis. Independent experimental and environmental variables tested were : video length, year, species used as discard, number of discards (unique or multiple), fixation system (cage or tripod), presence/absence of algae, visibility (score : "1" = correct visibility, "2" = presence of elements (e.g. algae) partly blocking the view of the camera from time to time, and "3" = turbid water or algae significantly blocking the view of the camera), condition of the discard at the beginning of the video (good or deteriorated [i.e. presence of sores on the body]), granulometry ("pebbles" for particles larger than 75 mm in diameter; "gravels" for particles size between 4.75 and 75 mm and "sands" for particle below 4.75 mm) and contact of the discard with the seafloor.

Discard consumption dynamic and patterns of consumer taxa associations

We described the speed of detection and chronological order of arrival of the different discard consumer taxa to evaluate whether some groups would arrive significantly faster than others (e.g. obligate scavengers, piscivorous consumers) and whether there was a pattern in the chronological order of arrival of the different consumer groups across BRUVs. Detection time and chronological order of arrival were determined based on the time of arrival of the first individual and departure of the last individual of each discard consumer taxon within each video sequence (i.e. together constituting the window of consumption time of each consumer taxon).

In these analyses, consumers were grouped in six groups characterized by different morphologies, locomotion mode and trophic ecology: Piscivorous teleost fish (European conger eel), non-piscivorous teleost fish, crabs (also including hermit and spider crabs), shrimps, gastropod (netted dog-whelk) and starfish. Teleost fish were split piscivorous and nonpiscivorous species [START_REF] Thompson | A feeding guild indicator to assess environmental change impacts on marine ecosystem structure and functioning[END_REF] following the hypothesis that piscivorous fish may behave differently than non-piscivorous fish in the face of discarded fish). Differences in detection time among groups of consumers were tested using a one-way PERMANOVA with Euclidean distances and 9999 permutations of residuals using a Monte Carlo resampling procedure (i.e. the equivalent of a non-parametric ANOVA), followed by post hoc pairwise tests between the different consumer groups using the same procedure. These tests were conducted in PRIMER version 7 software [START_REF] Clarke | PRIMER v6: User Manual/Tutorial[END_REF] and the PERMANOVA+ add-in [START_REF] Anderson | PERMANOVA+ for PRIMER: A guide to software and statistical methods[END_REF]. Chronological arrival data were analyzed by calculating the proportion of each taxon occupying each position (e.g. first, second, third) in the chronological order of arrival of the different consumers over the entire video set.

Finally, we tested for overall patterns of discard consumer taxa associations (positive, negative or random) across all videos following a probabilistic model approach [START_REF] Veech | A probabilistic model for analysing species co-occurrence[END_REF] using the cooccur R package [START_REF] Griffith | cooccur: Probabilistic species co-occurrence analysis in R[END_REF]. This approach uses presence-absence data from each video sequence to calculate an expected frequency of co-occurrence between taxa pairs following the hypothesis that they are distributed independently of one another across videos. Then, the model calculates the probability that the observed co-occurrence frequency is greater than the expected frequency (a positive co-occurrence association), less than the expected frequency (negative association), or random, using a α threshold of 0.05 to characterize significant differences (p-value < 0.05).

Behavioral interactions among discard consumers

To gain insight into the potential role of intra and inter specific interactions in discard consumption dynamic, we quantified the occurrence of four types of behavioral interactions as they occurred along videos: "succession events", "intraand interspecific repulsions" and "positive interactions". Characterization of these interactions are based on successions and overlaps between windows of consumption time of different consumers (i.e. from the moment an individual starts consuming the discard until the moment it leaves). In the case of fish consuming parts of the discard scattered around by other consumers, the end of consumption window was considered to be the moment when the fish got out of the camera's field. Cases where some individuals would leave for a short time but stay within the camera's field and come back to consume were considered as a single consumption event. If multiple individuals of the same species were indistinguishable, consumption windows were considered at the taxon level, from the first individual arrival until the moment they all left. "Succession events" were considered whenever the consumption window of two different taxa followed each other without any visible antagonistic interaction and within a 15 min timeframe. The occurrence of "intra-and interspecific repulsions" were characterized whenever a consumer left in response to the arrival of another consumer from the same or different taxon, respectively, while clearly displaying antagonistic behaviors such as hunting, pushing or escaping. Finally, "positive interactions" were considered whenever the prior presence of one consumer taxon seemed to favor consumption by another (e.g. promoting access to the discard). In addition, we specifically recorded Nassarius reticulatus abundance every 10 min along each video sequence to study its variation in relation to the presence of other potentially predatory species, since it was the only obligate scavenger and the most abundant species observed. Negative behavioral interactions among discard consumers were visualized using quantitative interaction networks by linking repulsed species to their aggressors and quantifying repulsion occurrences across all videos in the Bipartite R package [START_REF] Dormann | Introducing the bipartite package: Analysing ecological networks[END_REF]. Consumers belonged to six groups characterized by different morphologies, locomotion mode and trophic ecology: Piscivorous teleost fish, non-piscivorous teleost fish, crabs, shrimps, gastropods and starfish. There was only one gastropod species: the netted dog whelk (Nassarius reticulatus), which represented the most common taxon, occurring in more than 60% of the videos. Shrimps were present in 42% of the videos and ranked at the infra-order level (Caridea).

Results

3

Among crabs, four different taxa were identified at the species level: the velvet crab (Necora puber), the common spider crab (Maja brachydactyla), the edible crab (Cancer pagurus) and the European green crab (Carcinus maenas), which occurred in 35%, 26%, 3% and 3% of the videos respectively, and two at genus level: spider crabs belonging to (Macropodia sp.) and hermit crabs (Pagurus sp.), respectively in 6% and 3% of the videos. 20% of the videos also contained crabs that could only be ranked at the infra-order level (Brachyura). There was only one piscivorous teleost fish: the European Conger (Conger conger), which occurred in 16% of the videos. Among non-piscivorous teleost fish, two were identified at the species level: the common pout Trisopterus luscus and the black seabream Spondyliosoma cantharus, respectively in 13% and 6% of the videos; one at genus level: the dragonet Callionymus sp.

(26% of the videos); three at the family level: Gobiidae for gobies, Labridae for wrasses and Sparidae for porgies, respectively in 19%, 6% and 6% of the videos; and finally indeterminate teleost fish (6% of the videos). The common starfish (Asterias rubens) was present in one video sequence (3%).

Consumers detection time, chronology of arrival and co-occurrence patterns

All video sequences were analyzed together since they were conducted in a reduced area where environmental variation (e.g. sediment granulometry, vegetation) occurs in a patchy distribution at a very low spatial scale and there was no significant effect of any of those environmental variables on taxonomic richness of discard consumers. In addition, all observed taxa are mobile opportunistic feeders without strict microhabitat affiliation. Consumers depicted significantly different times of arrival to the discard according to their group (PERMANOVA: Pseudo-F5-93 = 4.11, p-value = 0.003; starfish were not included as there was only one observation) (Figure 2). N. reticulatus was the quickest to arrive on discards according to post hoc pairwise tests (t43 = 2.39, p = 0.021, t30 = 3.17, p = 0.004, t47 = 2.82, p = 0.007 and t22 = 6.45, p < 0.001 against non-piscivorous teleost fish, shrimps, crabs and piscivorous teleost fish, respectively) (Table A.2), with a median (minimum-maximum) time of arrival of the first individual of 6 min (0-78). Non-piscivorous teleost fish, shrimps and crabs were overlapping In terms of chronology of arrival to the discards across all video sequences, N.

reticulatus most frequently arrived first. It was present in 61% of the videos, arriving first in 48%, second in 10% and fourth in the remaining 3% (Figure 3). Crabs dominated the second position in the chronology, arriving second in 39% of the videos, including N. puber (10%), M. brachydactyla (13%), Macropodia sp. (3%), C. pagurus (3%) and indeterminate Brachyura (10%). Non-piscivorous teleost fish dominated the third position (i.e. 29% of the videos), and were more diversified in terms of taxonomic richness after the peak of decapods arrival in second position. Non-piscivorous teleost fish arriving in third position included T. luscus (3%), S. cantharus (7%), Sparidae (3%), Gobiidae (7%), Callionymus sp. (7%) and indeterminate teleost fish (3%). Crabs and teleost fish (including both non-piscivorous and piscivorous species) remained the dominant groups to arrive on the discards from the fourth to the seventh position in the chronology of arrival. There was a total of 36 possible taxa pairs from the presence-absence data matrices, out of which 2 were positive (6%) with taxa co-occurring more frequently than expected, 1 was negative (3%) with taxa co-occurring less frequently than expected, and 33 were random (92%)

(Figure 4a and4b). Significant positive co-occurrences were observed between N. reticulatus vs. Caridea (p-value < 0.001) and M. brachydactyla vs. C. conger (p-value = 0.043) (Figure 4a). Significant negative co-occurrence (α < 0.05) was observed between N. puber vs. N.

reticulatus (p-value = 0.042). Negative co-occurrence could be considered marginally significant between T. luscus and Caridea (p-value = 0.05) (Table A .3;Table A.4). C. conger was the species depicting the highest proportion of positive associations with other species (20% of pairings) while N. puber was the species depicting the highest proportion of negative associations with other species (12.5% of pairings) (Figure 4b).

Discussion

Diversity of discard consumers

Based on baited remote underwater video analysis, we identified 18 discard consumer taxa belonging to piscivorous and non-piscivorous teleost fish, crabs (including hermit crabs and spider crabs), shrimps, one gastropod and one starfish in shallow fishing grounds of the bay of Bourgneuf. The main discard consumers were netted dog whelks (gastropod), Caridea shrimps, velvet crabs, common spider crabs and dragonets (non-piscivorous teleost fish). Among all taxa observed to consume discards, only the netted dog whelk (N. reticulatus) is considered an obligate scavenger [START_REF] Ruxton | Energetic feasibility of an obligate marine scavenger[END_REF] and only the European conger (C. conger) belongs to the piscivore trophic guild [START_REF] Thompson | A feeding guild indicator to assess environmental change impacts on marine ecosystem structure and functioning[END_REF]. This suggests that in fishing grounds, facultative scavenging behaviors towards discarded fish may be relatively common among non-typically scavenging and non-piscivorous marine consumers. Most observed consumers are generalist and opportunistic taxa with a flexible feeding ecology, but whose piscivory or dietary dependence on carrion is considered to be low or never precisely assessed.

For example, the velvet crab N. puber is an omnivore that feeds mainly on benthic invertebrates or brown algae depending on its ontogenetic stage, and only occasionally on fish likely consumed as carrion [START_REF] Freire | Feeding ecology of the velvet swimming crab Necora puber in mussel raft areas of the Ría de Arousa (Galicia, NW Spain)[END_REF]MarLIN, 2006;[START_REF] Norman | Influence of depth, season and moult stage on the diet of the velvet swimming crab Necora puber (Brachyura , Portunidae)[END_REF]. Other decapods identified as discard consumers in this study show similar feeding plasticity, such as M. brachydactyla, C. maenas and C. pagurus [START_REF] Baeta | Feeding ecology of the green crab, Carcinus maenas (L., 1758) in a temperate estuary, Portugal[END_REF][START_REF] Bernárdez | Feeding of the spider crab Maja squinado in rocky subtidal areas of the Ría de Arousa (north-west Spain)[END_REF]MarLIN, 2006), and generally low trophic levels [START_REF] Palomares | SeaLifeBase [WWW Document[END_REF][START_REF] Pauly | Sea Around Us Concepts, Design and Data[END_REF]. Because spatial variability in the availability of prey has been identified as the primary cause of change in the trophic strategies of decapods [START_REF] Edgar | Predator-prey interactions in seagrass beds. II. Distribution and diet of the blue manna crab Portunus pelagicus Linnaeus at Cliff Head, Western Australia[END_REF][START_REF] Freire | Feeding ecology of the velvet swimming crab Necora puber in mussel raft areas of the Ría de Arousa (Galicia, NW Spain)[END_REF][START_REF] González-Gurriarán | Incidencia del cultivo de mejillón en la dieta de Liocarcinus depurator (L.) (Brachyura: Portunidae) en la Ría de Arousa (Galicia, NW España)[END_REF], they may rely more on discards where discarding practices are more common, as suggested in this study. Gut content metabarcoding analysis of marine fauna in fishing grounds of the Bay of Bourgneuf revealed that discard ingestion may be widespread across bentho-demersal consumers but more important in decapods (Lejeune et al., 2022b). Based on the analysis of muscle isotopic composition, a previous study in the same area also found that decapods depicted a high trophic level which may be explained by substantial reliance on fisheries discards (Lejeune et al., 2022a). But in the stable isotope study, evidence of discard consumption by fish was limited.

The authors interpreted this as resulting either from an absence of consumption of discards by most fish or the opportunistic consumption of other low trophic level prey displaced by trawling, which could counterbalance any visible effect of discard consumption on their isotopic composition. In this study, we can confirm that decapods but also a variety of teleost fish are effectively attracted by and able to consume discards. This echoes with research conducted in different environmental settings showing that demersal fish such as dragonets, gobies, pout (T. luscus) and other bentho-pelagic opportunistic predatory fish such as wrasses and porgies opportunistically scavenge upon discards or carrion generated by trawling (e.g. [START_REF] Groenewold | Effects on benthic scavengers of discards and damaged benthos produced by the beam-trawl fishery in the southern North Sea[END_REF][START_REF] Jenkins | Predator and scavenger aggregation to discarded by-catch from dredge fisheries : importance of damage level[END_REF][START_REF] Depestele | The Impact of Fisheries Discards on Scavengers in the Sea[END_REF]. Interestingly, the only piscivorous species (C. conger) arrived significantly later than all other consumer groups and acted like a discard "finisher", swallowing the discard whole.

Utility of underwater videos to elucidate consumption dynamic and species interactions around discards

Analyses of detection time and chronology of arrival of discard consumers revealed that the only obligate scavenger, the gastropod N. reticulatus, was the quickest to arrive on carcasses as well as the most occurring taxa (i.e. > 60% of the videos). Although we do not have information on species abundance in the area of study, this may be linked to a higher density of N.

reticulatus. Yet, N. reticulatus is also known to possess a well-developed olfactory system allowing it to rapidly detect and locate carrion in the environment [START_REF] Davenport | Behavioural responses of the netted dogwhelk Nassarius reticulatus to olfactory signals derived from conspecific and nonconspecific carrion[END_REF]. Being a potential prey for many other discard consumers, N. reticulatus was also the most subject to repulsion by others. As such, N. reticulatus individuals could generally be seen leaving the discard whenever other consumers would arrive (except shrimps and gobies). In several videos, N. reticulatus could even be seen massively leaving the discard < 10 min prior to the arrival of N. Puber and M. brachydactyla within the frame of the camera. These mass movements might correspond to the detection of potential predator arrivals, i.e. antipredator scavenger community was relying on crabs breaking open the scallop shells to consume them, with fish seen waiting and feeding at the chelae of crabs on many occasions. Likewise, extraoral digestion of fish skin by Asterias rubens can facilitate scavenger feeding on fish prey [START_REF] Ramsay | Consumption of fisheries discards by benthic scavengers: utilization of energy subsidies in different marine habitats[END_REF].

Direct observations of interactions between consumers also revealed many intraspecific repulsion events suggesting interference competition between conspecifics, especially in crabs.

Threat displays are well known in crabs which can 'elbow' with the carpus of the cheliped both for aggression and to space each other around carcasses [START_REF] Davenport | Behavioural responses of shallow-water benthic marine scavengers to fish carrion: a preliminary study[END_REF]. Moreover, we noted that threat displays between crabs generated a lot of sediment dispersion, which might dissuade other species from getting close. Positive associations between C. conger and M. brachydactyla or N. reticulatus and Caridea revealed by co-occurrence analysis could suggest that the species involved are attracted by the same type of discard or that they have similar microhabitat preferences. These results, together with observations from the literature (e.g. [START_REF] Kopp | Some expected impacts of the Common Fishery Policy on marine food webs[END_REF][START_REF] Sherley | Scavenger communities and fisheries waste : North Sea discards support 3 million seabirds, 2 million fewer than in 1990[END_REF]. A better understanding of facultative scavenging and its importance across marine fauna is key to forecast the impact of discarding practices on food web structure and functioning in fishing grounds, as well as anticipate potential food web changes linked to the implementation of discard bans in many areas around the globe [START_REF] Depestele | The Impact of Fisheries Discards on Scavengers in the Sea[END_REF]. This study constitutes a first step towards a better understanding of facultative scavenging abilities across benthic fauna in the shallow fishing grounds of the Bay of Bourgneuf. Together with previous indications of discard ingestion and assimilation in the same fishing ground obtained via stable isotopes (Lejeune et al., 2022a) and DNA metabarcoding of gut contents (Lejeune et al., 2022b), our study suggest that many low trophic level benthic taxa (e.g. decapods, small fish, mollusks) may be important nodes to consider for the reintegration of discards within the marine food web. Because these are potentially important prey at the base of the food web and some (e.g. decapods) are known to play structuring roles within benthic communities, reducing discards might propagate changes across the food web via these important species (Lejeune et al., 2022b).

Conclusions

The use of underwater videos offers unique insights in terms of characterization of consumption dynamic and species associations or interactions around discards which ultimately allow to understand and objectify the existence of trophic links between consumers and discards. Better knowledge on trophic links with discards constitutes one of the challenges of understanding fisheries discards reintegration into marine food webs [START_REF] Depestele | The Impact of Fisheries Discards on Scavengers in the Sea[END_REF][START_REF] Guillen | A review of the European union landing obligation focusing on its implications for fisheries and the environment[END_REF]. Ecosystem models aiming to depict marine food web and the influence of anthropogenic factors such as fishing or climate change on its dynamic (e.g. Atlantis or Ecopath with Ecosim;

Fulton 2010; [START_REF] Heymans | Best practice in Ecopath with Ecosim food-web models for ecosystem-based management[END_REF]) provide contrasting predictions regarding the importance of discards for marine fauna (e.g. [START_REF] Catchpole | Importance of discards from the English Nephrops norvegicus fishery in the North Sea to marine scavengers[END_REF][START_REF] Depestele | The Impact of Fisheries Discards on Scavengers in the Sea[END_REF], partly owing to the lack of empirical studies, especially at local scales. Altogether, we can conclude that in shallow coastal fishing grounds, discards could be consumed by a large diversity of species, both in terms of taxonomic and trophic groups, including low trophic level benthic fish and omnivorous invertebrate macrofauna such as decapods [START_REF] Froese | FishBase [WWW Document[END_REF][START_REF] Palomares | SeaLifeBase [WWW Document[END_REF][START_REF] Thompson | A feeding guild indicator to assess environmental change impacts on marine ecosystem structure and functioning[END_REF]. This supports previous research suggesting that the diversity of discard consumers may currently be underestimated [START_REF] Guillen | A review of the European union landing obligation focusing on its implications for fisheries and the environment[END_REF]Lejeune et al., 2022bLejeune et al., , 2022a)). Whether such behaviors correspond to stable trophic strategies over time remains to be established, notably through repeated measures and an integrated use of multiple diet assessment techniques (e.g. gut content, stables isotopes, fatty acids or other trophic tracers) [START_REF] Lejeune | Progenesis as an intrinsic factor of ecological opportunity in a polyphenic amphibian[END_REF].

Zeller, D., Cashion, T., Palomares, M.-L., Pauly, D., 2018. Global marine fisheries discards :

A synthesis of reconstructed data. Fish Fish. 19, 30-39. https://doi.org/10.1111/faf.12233

List of Appendices:

Appendix A. Supplementary tables and figures:

  .1 Discard consumers' taxonomic richness and influencing factors 18 different consumer taxa were observed in the 31 underwater videos (Figure 1; Figure A.2).

Figure 1 .

 1 Figure 1. Percentage of occurrence of consumer taxa across videos (n=31). Colors represent

  in their arrival time (non-significant post hoc pairwise tests), being 18 min (1-313),23 (1-114) and 37 min (0-314), respectively. The only starfish Asterias rubens arrived after 28 min on the discard, falling within the same window of first arrival time as crabs, shrimps and nonpiscivorous teleost fish. The only piscivorous teleost fish Conger conger arrived significantly later than all other groups (t16 = 3.37, p = 0.004, t33 = 2.35, p = 0.023 and t29 = 2.70, p = 0.013 against shrimp, crabs and non-piscivorous teleost fish, respectively), with a median time of arrival of 132 min (45-242).

Figure 2 .

 2 Figure 2. Time of arrival of the first individual of each taxon (in minutes) on the discard

Figure 3 .

 3 Figure 3. Chronology of arrival of the consumers on discards across videos (n = 31). The

Figure 4 .

 4 Figure 4. Consumers' co-occurrence analysis. (a) Heatmap of pairwise associations between

3. 3

 3 Analysis of consumer successions and behavioral interactions 19 of the 31 videos contained behavioral interactions. There were 5 succession events, 15 interspecific repulsions, 25 intraspecific repulsions and 1 positive interaction. All 5 succession events (i.e. without displaying antagonistic behaviors) concerned non-piscivorous teleost fish (T. luscus, S. cantharus, Gobiidae and indeterminate teleost fish) coming to consume discards right after the departure of crabs (M. brachydactyla, N. puber and Pagurus sp.) (Figure A.5). The 15 interspecific repulsions involved 7 different taxa: C. pagurus, C. conger, A. rubens, M. brachydactyla, N. puber, N. reticulatus and Caridea (Figure 5; Figure A.6). N. reticulatus wasthe most repelled taxon (11 out of 15 interspecific repulsions events). They were observed to be repelled by: M. brachydactyla (36.4% of repulsion events directed towards N. reticulatus), N. puber and C. conger (both 27.3% of repulsion events) and A. rubens (9.1% of repulsion events). Whenever possible, analysis of the variation of N. reticulatus abundance in relation to the presence of repulsive species revealed an important decrease prior to the arrival of the decapods M. brachydactyla and N. puber and subsequent increase following their departure from the discards(Figure A.7). N. reticulatus abundance also decreased following the arrival of the starfish A. rubens. Caridea were repelled by N. puber in 100% of cases. M. brachydactyla was repelled in 50% of cases by C. conger and 50% by C. pagurus. Repulsion events (hunting, escaping or pushing each other) were observed between individuals of the same species in: N. reticulatus (n = 2); T. luscus (n = 13); Callionymus sp. (n = 1); N. puber (n = 1) and Brachyura (n = 8). One potential positive interaction was observed between T. luscus and N. puber, the first being observed to consume pieces of the discard scattered around the BRUVs by feeding N. puber.

Figure 5 .

 5 Figure 5. Bipartite network of the observed interspecific antagonistic behaviors (i.e.

Figure A. 1 :

 1 Figure A.1: (A) Tripod and (B) cage systems used for baited remote underwater videos.

Figure A. 2 :

 2 Figure A.2: Camera footages of some of the different discard consumers.

Figure A. 3 :

 3 Figure A.3: Influence of environmental and experimental parameters on the taxonomic

Figure A. 4 :

 4 Figure A.4: Relation between video length (in minutes) and taxonomic richness of consumers.

Figure A. 5 :

 5 Figure A.5: Co-occurrence of consumer taxa across time revealing five succession events in

Figure A. 6 :

 6 Figure A.6: Co-occurrence of consumer taxa across time revealing interspecific repulsions in

Figure A. 7 :

 7 Figure A.7: Variations of N. reticulatus abundance in the presence of repulsive taxa in video

Understanding the impact of fisheries discards and their reduction on marine food webs

  [START_REF] Jenkins | Predator and scavenger aggregation to discarded by-catch from dredge fisheries : importance of damage level[END_REF], illustrate how video analysis can provide valuable information to verify or understand the ability of a species to consume discards and better understand the dynamic of discard consumption by marine fauna. The fact that taxonomic richness increased with video length suggests that longer videos could further increase the richness of observed taxa and the occurrence of behavioral interactions, as well as identify other species which could potentially only consume discards in a state of advanced degradation. However, this also increases the probability of large piscivores, such as C. conger to find the discard and consume it whole, as observed in this study. Finally, one may expect that different discarded species would attract different scavengers or affect detection time due to differences in nutritional composition (e.g. mackerel being a fatty fish is likely very different from the other discarded species used in this study). Low sample size did not allow us to test such an effect here, but future studies aiming to characterize attraction towards different types of discards depending on their nutritional composition may allow to predict which species would likely be attracted based on the composition of discarded fish community in a given area or season.Fisheries discard rates (i.e. animals caught, but returned to the sea, dead or alive, as a result of low commercial value, under quota restriction, below the minimum allowable size or damaged) are estimated to represent ~10 % of global annual catches(Zeller et al., 2018), but may vary considerably at lower spatial scale. Discarding practices have recently been recognized as a source of concern for the perennation of marine resources, prompting global efforts towards

	4.3

their reduction

(Zeller et al., 2018)

. However, effects of such measures on populations, communities and ecosystem functioning, whether beneficial or detrimental, direct or indirect, are still unclear (e.g.

Table A . 1 :

 A1 Summary statistics of the multiple linear model testing for the effects of environmental and experimental variables on taxonomic richness of discard consumers.Table A.2: post hoc pairwise PERMANOVA tests of detection time among discard consumers.

Table A.3: Discard consumers' co-occurrence analysis. Table A.4: Consumer taxa occurrences in each of the 31 video sequences.

Acknowledgements:

We are thankful to the fishing crew which helped set the BRUVs on the seabed. We thank the Associate Editor and the 2 anonymous reviewers for their constructive comments. This study was supported by the European Maritime and Fisheries Fund (EMFF), grant PFEA390018FA1000001 and France Filière Pêche, grant PH/2018/08.

behaviors. Indeed, previous experimental work revealed that thanks to their well-developed olfactory system, starved N. reticulatus remain hidden whenever they detect damaged conspecifics likely as an antipredator response [START_REF] Davenport | Behavioural responses of the netted dogwhelk Nassarius reticulatus to olfactory signals derived from conspecific and nonconspecific carrion[END_REF]. Yet in our case, this remains speculative and further studies are needed to clearly test the ability of N. reticulatus to detect predators to some distance and initiate an escape. The observed behavioral interactions might also explain the negative association between N. reticulatus and N. puber, or the marginally significant one between N. reticulatus and T. luscus in co-occurrence analysis, as they are known predators of gastropods [START_REF] Froese | FishBase [WWW Document[END_REF][START_REF] Palomares | SeaLifeBase [WWW Document[END_REF][START_REF] Thompson | A feeding guild indicator to assess environmental change impacts on marine ecosystem structure and functioning[END_REF].

Crabs and non-piscivorous teleost fish were most occurrent in the second and third position of the chronology of arrival, respectively. Direct observations of interactions between consumers revealed that the departure of decapods such as N. puber and M. brachydactyla was followed by a quick arrival of fish in several videos, which is consistent with the fact that fish tend to avoid approaching carrion whenever crabs are already at it [START_REF] Davenport | Behavioural responses of shallow-water benthic marine scavengers to fish carrion: a preliminary study[END_REF]). Yet interestingly, T. luscus could also be seen taking advantage of the wasteful feeding of crabs by consuming pieces of discards being scattered around by N. puber, allowing them to consume discards at the same time as crabs while avoiding potential aggressive behaviors by staying at a distance. This suggests that crabs might more generally facilitate the consumption of discards by non-typically scavenger or non-piscivorous fish, despite the fact that they are potential competitors. All teleost fish attracted by discards in this study are non-piscivorous species [START_REF] Thompson | A feeding guild indicator to assess environmental change impacts on marine ecosystem structure and functioning[END_REF] and may be considered ill-equipped to consume discarded fish (i.e. small gape size or low bite force), except C. conger. They may therefore benefit from the presence of other species to dismantle it first. [START_REF] Davenport | Behavioural responses of shallow-water benthic marine scavengers to fish carrion: a preliminary study[END_REF] also showed that crabs are generating scraps for indirect feeders when scavenging on carrion, resulting in the attraction of more scavengers. In a study using scallop baits, [START_REF] Jenkins | Predator and scavenger aggregation to discarded by-catch from dredge fisheries : importance of damage level[END_REF] also noted that the


Pedro G Vásquez-Ocmín

Guillaume Marti

Alice Gadea

Guillaume Cabanac

Juan Vásquez-Briones

Sandro Casavilca-Zambrano

Nadia Ponts

Patricia Jargeat

Mohamed Haddad

Stéphane Bertani
email: stephane.bertani@ird.fr

Juan A Vásquez- Briones

Metabotyping of Andean pseudocereals and characterization of emerging mycotoxins

Keywords: Andean pseudecereals, metabotyping, mycotoxins, fungal communities

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

Introduction

Pseudocereals are best known for three crops derived from the Andes: quinoa (Chenopodium quinoa), canihua (C. pallidicaule), and kiwicha (Amaranthus caudatus). The use of these pseudocereals as "superfood" for healthier diets has been growing exponentially over the past decade because of their high content of essential amino acids, antioxidants, fibers, and vitamins while being gluten-free [START_REF] Pereira | Chemical and nutritional characterization of Chenopodium quinoa Willd (quinoa) grains: A good alternative to nutritious food[END_REF]. Due to its high nutritional value, the Food and Agriculture Organization (FAO) has deemed quinoa a "golden seed" because of its potential to ensure food safety and nutrition for the world's population amid climate change. Thus, pseudocereals, are not only recognized for their nutritional benefits but also for their ability to adapt to a variety of agro-environmental conditions. Indeed, Peru, Bolivia, and Ecuador are the main producers of quinoa, canihua, and kiwicha, where these pseudocereals are especially well adapted to the abiotic stresses found in Andean highlands [START_REF] Bonifacio | Mejoramiento de la quinua (Chenopodium quinoa Wild.) y qañawa (Chenopdium pallidicaule Aellen) en un contexto de cambio climático en los Andes altos[END_REF].

There is a higher level of polyphenism among the pseudocereals cultivated in the Andean countries. For instance, three types of quinoa have been categorized according to the color of the seeds: red quinoa, white quinoa, and black quinoa. However, the chemical foundation that would rely upon such polyphenism has not been thoroughly investigated. Meanwhile, the chemical food safety of pseudocereals remains poorly documented as well. Despite their appeal to an organic diet, pseudocereals may still have the potential for adverse effects from secondary metabolites produced by infesting microorganisms, such as mycotoxin-producing fungi. Mycotoxins are naturally occurring secondary metabolites with adverse effects on human and animal health upon ingestion. They are mainly produced by strains of the three fungal genera Aspergillus, Fusarium, and Penicillium [START_REF] Bräse | Chemistry and Biology of Mycotoxins and Related Fungal Metabolites[END_REF]. More than 25% of the crop production worldwide bears contamination with mycotoxins, making them ubiquitous in cereals and cereal-derived foods [START_REF] Eskola | Worldwide contamination of food-crops with mycotoxins: Validity of the widely cited 'FAO estimate' of 25%[END_REF][START_REF] Lee | Worldwide Occurrence of Mycotoxins in Cereals and Cereal-Derived Food Products: Public Health Perspectives of Their Co-occurrence[END_REF].

Therefore, it is essential to better understand local diversity and mycotoxigenic risk for pseudocereals . CC-BY 4.0 International license made available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is

The copyright holder for this preprint this version posted June 23, 2022. ; https://doi.org/10.1101/2022.06.23.497323 doi: bioRxiv preprint 3 in the context of a global demand that encourages market diversification and sustainable and equitable development.

Metabolomics based on technology like hyphenated liquid chromatography-mass spectrometry (LC-MS) assisted by bioinformatics and statistical analysis is a powerful approach for both the detection and the annotation of key compounds, as well as for deciphering their biological functions. Our team has previously implemented a workflow based on untargeted LC-MS-based metabolomics able to achieve the metabotyping of plants by identifying their main biomarkers [START_REF] Vásquez-Ocmín | Cannabinoids vs. whole metabolome: Relevance of cannabinomics in analyzing Cannabis varieties[END_REF].

In the present study, we applied this approach to both achieve a comprehensive chemical mapping of pseudocereal samples collected in the Andes, and to classify them according to their chemotype.

Additionally, targeted LC-MS metabolomics was applied on the same samples to quantify their contents in mycotoxins Aflatoxin B 1 , Beauvericin, Fumonisin B 1 , Ochratoxin A, and Patulin. Finally, an inventory of the fungal community infesting pseudocereal samples from the Andes was documented, thereby correlating the presence of toxicogenic fungi and their associated secondary metabolites.

Material and methods

All solvents used for chromatography were LC-MS grade (HiPerSolv Chromanorm, VWR, Fontenay-Sous-Bois, France). Milli-Q RG system (Millipore, France) was used to produce high purity water of 18.2 MΩ.cm resistivity. Formic acid was >98% for LC-MS (Fluka, Buchs, Switzerland). Mycotoxins standards [i.e., Aflatoxin B 1 (AflaB 1 ), Beauvericin (BEA), Fumonisin B 1 (FumB 1 ), Ochratoxin A (OTA), and Patulin (PAT)] were purchased from Sigma-Aldrich (St. Louis, MO, USA) and immediately stored at -30 °C.

Plant material

Twenty-seven grain samples were collected between September 2019 and December 2020 in seven regions of Peru (elevation range: 1,410-3,855 meters height above mean sea level) and one grain sample was bought in a local market in Toulouse, France. For quinoa samples from Peru, eight grains were collected directly (unwashed) and the 13 others having been washed (see the list and description of varieties in supp info 1). After the collection, all grain samples were immediately stored in airtight

Metabolome analyses

Untargeted metabolomics

For each grain sample (100 mg), a biphasic microextraction was performed in triplicate following: i) first, 1.5 mL of Methyl-tert butyl ether (MtBE)/MeOH (75:25, v/v), then vortex and

4

sonication for 3 min, ii) second, 1.5 mL of water/MeOH (75:25, v/v), then vortex and sonication for 3 min. The suspension was centrifuged at 14,000 rpm for 3 min at 5°C, then, 500 µL of medium polar extract was taken and dried at 30°C using a vacuum concentrator. The residue was then resuspended using methanol and then stored at -30 °C prior analysis. A quality control (QC) sample was made by pooling aliquots from each extract. Final concentration for untargeted metabolomic analyses was performed at 50-fold dilutions.

On washed samples, an ultra-high-performance liquid chromatography high-resolution mass spectrometry (UHPLC-HRMS) analyses were performed on a Q Exactive™ Plus Hybrid Quadrupole-Orbitrap™ Mass Spectrometer equipped with a Heated Electrospray Ionization (HESI-II) Probe coupled to a UltiMate™ 3000 Rapid Separation LC (RSLC) system (Thermo Fisher Scientific, Villebon-Sur-Yvette, France). Separation was performed on a Luna Omega Polar C18 UHPLC column (150 mm × 2.1 mm i.d.,

1.6 μm) with a guard column (Phenomenex, Sartrouville, France). The mobile phase gradient used water containing 0.05 % formic acid (A) and acetonitrile containing 0.05% of formic acid (B). A gradient method at a constant flow rate of 0.3 mL/min was applied under the following conditions: 0 % B for 1 min to 100 % B in 20 min, held at 100 % B over 4 min, then equilibration with 100 % over 4 min. The column oven temperature was set to 40°C, the autosampler temperature was set to 5°C, and the injection volume was fixed to 1 μL. Mass detection was performed in positive ionization (PI) and negative ionization (NI) modes at resolution 30,000 [fullwidth at half-maximum (fwhm) at 400m/z] for MS1 and resolution 17,500 with automatic gain control (AGC) target of 1×10 6 for full scan MS1 and 1×10 5 for MS2. Ionization spray voltage was set to 3.5 kV (for PI) and 2.5 kV (for NI), and the capillary temperature was set to 256 °C for both modes. The mass scanning range was m/z 100-1500. Each full MS scan was followed by a data-dependent acquisition of MS/MS spectra for the six most intense ions using stepped normalized collision energy of 20, 40, and 60 eV.

Targeted metabolomics

For each grain sample (5 g), extraction was performed in triplicate using 20 mL of ethyl acetate and sonication for 1 h. The suspension was centrifuged at 14,000 rpm for 10 min, and the supernatant dried at 30°C using a vacuum concentrator. The residue was then resuspended using methanol and then stored at -30 °C prior analysis. Final concentration for targeted metabolomic analyses was performed at 12-fold dilutions.

On all set samples in supp info 1, a Triple Quad 5500+ LC-MS/MS System -QTRAP Ready (AB Sciex, Villebon sur Yvette, France) equipped with a Turbo Spray source. Separation was performed on an ACQUITY UPLC® BEH C18 column (100 mm × 2.1 mm i.d., 1.7 μm, Waters, MA, USA) equipped with a guard column. The mobile phase gradient used water containing 0.1 % formic acid (A) and acetonitrile containing 0.1% of formic acid (B). A flow rate of 0.3 mL/min was applied following: isocratic conditions, 10% of B and 90% of A for 3 min, then, a gradient of B until 70% in 7 min, and went up to 90% in 1.1 min (curve 6). After 1.9 min, it went back to the initial condition in 0.1 min, and then a reequilibration for 2.9 min. The column oven temperature was set to 40°C, the autosampler temperature was set to 5°C, and the injection volume was fixed to 5 μL. Mass detection was performed in PI and NI modes at nominal resolution. Ionization spray voltage was set to 4.5 kV (for PI) and 4.5 kV (for NI), and the capillary temperature was set to 500 °C , curtain gas set at 20, ion source gas at 1 at 60 and ion source gas 2 at 70 for both modes. Two main transitions for each standard were performed in PI and NI (details in supp info 2). A curve of calibration was carried out for targeted metabolomics from a mix of standards to final concentrations of: 100 ng/mL, 10 ng/mL, 1 ng/mL, 0.1 ng/mL, 0.01 ng/mL, and 0.001 ng/mL in acetonitrile.

Data mining process

Untargeted metabolomics

LC-MS data were processed according to the MSCleanR workflow [START_REF] Fraisier-Vannier | MS-CleanR: A Feature-Filtering Workflow for Untargeted LC-MS Based Metabolomics[END_REF][START_REF] Vásquez-Ocmín | Cannabinoids vs. whole metabolome: Relevance of cannabinomics in analyzing Cannabis varieties[END_REF]. Briefly, batches in PI and NI were processed separately with MS-DIAL version 4.80 [START_REF] Tsugawa | MS-DIAL: Data-independent MS/MS deconvolution for comprehensive metabolome analysis[END_REF]. MS1 and MS2 tolerances were set to 0.01 and 0.05 Da, respectively, in centroid mode for each dataset. Peaks were aligned on QC reference with an RT tolerance of 0.2 min, a mass tolerance of 0.015 Da, and a minimum peak height detection at 1 × 10 6 for both ionization modes. MS-DIAL data (both PI and NI) were deconvoluted together with MS-CleanR by selecting all filters with a minimum blank ratio set to 0.8 and a maximum relative standard deviation (RSD) set to 40. The maximum mass difference for feature relationships detection was set to 0.005 Da, and the maximum RT difference was set to 0.025 min. The Pearson correlation links were applied for a correlation ≥ 0.8 and a p-value significance threshold = 0.05. Two peaks were kept in each cluster for further database requests and the kept features were annotated with MS-FINDER version 3.52 [START_REF] Tsugawa | Hydrogen Rearrangement Rules: Computational MS/MS Fragmentation and Structure Elucidation Using MS-FINDER Software[END_REF]. The MS1 and MS2 tolerances were set to 5 and 15 ppm, respectively. The formula finder was exclusively processed with C, H, O, and N atoms. Two pathways from several sets of data were carried out for the compound's annotation. For metabolite annotation at level 1: experimental LC-MS/MS data for 500 compounds (including five mycotoxins standards), analyzed on the same instrument and with the same method, were used as references using MS-DIAL based on accurate and exact mass, fragmentation, and retention time. For metabolite annotation level 2: the MS-DIAL, MONA (MassBank of North America), and GNPS (Global Natural Product Social Molecular Networking) mass spectral records were used for spectral match using a dot product score cut-off of 800. The in silico match (annotation level 3) were prioritized according to: 1) compounds identified in the literature for both Chenopodium and Amaranthus genera, and both Amaranthaceae and Chenopodiaceae botanic family (Dictionary of Natural Products version 28.2, CRC press) mined by MS Finder based on exact mass and in silico fragmentation; 2) generic databases included in MS-FINDER (i.e., FooDB, PlantCyc, ChEBI, T3DB, Natural Products Atlas, NANPDB, COCONUT, and KNApSAcK);

3)fungal compounds (including mycotoxins) were performed using four "in-house" databases from literature to compile: i) only mycotoxins (n=300) and ii) compounds produced from major mycotoxigenic fungi Fusarium, Aspergillus, and Penicillium.

Mass spectra similarity networking was carried out from PI mode using MetGem [START_REF] Olivon | MetGem Software for the generation of molecular networks based on the t-SNE algorithm[END_REF] on the final annotated .msp file and metadata files compiled for both batches obtained with MSCleanR. Values used were MS2 m/z tolerance = 0.02 Da, minimum matched peaks = 4 and minimal cosine score value = 0.7. Visualization of the molecular network (MN) was performed on Cytoscape version 3.9.1 [START_REF] Shannon | Cytoscape: A Software Environment for Integrated Models of Biomolecular Interaction Networks[END_REF]. Original LCMS raw data were uploaded in zenodo (DOI:xxxx)

Targeted metabolomics and mycotoxins quantification

Dataset acquired in format .wiff was converted in .abf format using Analysis Base File Converter (Reifycs, Tokyo, Japan). Analyses were performed with MRMPROBS program version 2.60 [START_REF] Tsugawa | MRMPROBS: A Data Assessment and Metabolite Identification Tool for Large-Scale Multiple Reaction Monitoring Based Widely Targeted Metabolomics[END_REF][START_REF] Tsugawa | MRM-DIFF: Data processing strategy for differential analysis in large scale MRM-based lipidomics studies[END_REF], using as parameters of peak detection: five scans for minimum peak width; 2,000 as minimum peak height; 0.2 min as retention time tolerance for peak identification; 15% as amplitude tolerance; and 70% as minimum posterior. A list of transitions in .txt format was used as a compound library file. A final list containing the information about the Area above zero for each transition selected in the samples was exported in .txt format. From the final list of information about the mycotoxin standards, a calibration curve was created for each concentration mentioned above. Validation parameters were determined following the International Conference on Harmonization (ICH) Guidelines [START_REF] Ich | Validation of Analytical Procedures: Text and Methodology[END_REF], and the following characteristics were evaluated: 1) linearity, 2) limit of detection (LOD), and 3) limit of quantification (LOQ). Wheat contaminated with enniatins, and beauvericin was used as positive control. Original LC-MS raw data were uploaded in zenodo (DOI:10.5281/zenodo.6700223).

Statistical analyses

The final annotated metabolome dataset generated by the MS-CleanR workflow was uploaded on the MetaboAnalyst 5.0 online platform [START_REF] Chong | Using MetaboAnalyst 4.0 for Comprehensive and Integrative Metabolomics Data Analysis[END_REF]. The data were normalized by sum and scaled by Pareto before statistical analysis. First, principal component analysis (PCA) was applied as an exploratory data analysis to provide an overview of LC-MS fingerprints. Then, a hierarchical cluster analysis (HCA) was performed to obtain a dendrogram of varieties using the untargeted metabolome dataset. For each variable the average value across replicates was calculated; then distance matrices were obtained using either 1-r (Pearson correlation coefficient), followed by HCA on each matrix using Ward's minimum variance criterion using Orange 3.32.0 [START_REF] Demšar | Orange: Data Mining Toolbox in Python[END_REF]. On the clusters obtained, a partial least squares discriminant analysis (PLS-DA) was conducted using clusters as Yvalue, and the top 50 features were plotted on a heatmap using ANOVA. GraphPad Prism 5.0 was used to perform the bar-plot for data quantification.

Fungi isolation and molecular identification

For each sample (supp info 1), dried seeds were deposited on Malt Extract Agar (MEA) plates (diameter 15 cm) containing chloramphenicol (100 μg/mL) under the laminar airflow (LAF). Plates were incubated at 27°C daylight. After at least 48h of incubation, growing fungi were replicated on MEA plates without chloramphenicol and incubated at 27°C, with daylight. All the isolated mycelia are stored in UMR 152 laboratory collection (cryopreservation at -80°C in 20% of glycerol).

Total DNA was extracted from mycelium directly picked from the plate, using the Wizard® Genomic DNA Purification kit (Promega, Charbonnières-Les-Bains, France). The final pellet was resuspended in 40 μL of sterile ultra-high quality (UHQ) water and diluted 10 times in UHQ water. The ITS rDNA region was amplified by polymerase chain reaction (PCR) using the primer set ITS5/ITS4 [START_REF] White | Amplification and direct sequencing of fungal ribosomal RNA genes for phylogenetics[END_REF]. Reactions were carried out in a final volume of 25 μL, containing 2 μL of diluted DNA, 5 µL GoTaq polymerase buffer 5x (Promega), 0.5 μL of each primer, 0.5 µL of dNTP, 0.5 units of GoTaq® Hot Start polymerase (Promega), and 16.5 µL of UHQ sterile water. PCR cycling conditions of the Mastercycler® Nexus Thermal Cycler (Eppendorf AG, Hamburg, Germany) were as follows: initial denaturation at 95°C for 3 min; 35 cycles at 95°C for 45 s, 55°C for 45 s, 72°C for 1 min; and a final extension at 72°C for 10 min. For identification at the species level of the Aspergillus and Penicillium isolates, beta-tubuline and calmoduline regions were PCR-amplified using the primers Bt2a/Bt2b [START_REF] Glass | Development of primer sets designed for use with the PCR to amplify conserved genes from filamentous ascomycetes[END_REF] and CMD5/CMD6 [START_REF] Hong | Polyphasic taxonomy of Aspergillus fumigatus and related species[END_REF], in the same conditions as above, except for annealing temperature (58°C instead of 55°C). PCR amplicons were sequenced by Eurofins Genomics (Ebersberg, Germany) according to a Sanger method using ITS5, Bt2a, and CMD5 respectively. Sequences were submitted to the BLASTn program (http://blast.ncbi.nlm.nih.gov/Blast.cgi) to determine the close matches in the GenBank database. All ITS sequences were aligned with MAFFT v6.814b (Katoh at al 2002) using Geneious®6.1.8.

The PhyML method [START_REF] Guindon | A Simple, Fast, and Accurate Algorithm to Estimate Large Phylogenies by Maximum Likelihood[END_REF] was used via the Geneious® platform to generate a maximum-likelihood phylogenetic tree with the following setting: GTR substitution model, 100 bootstraps, estimated transition/transversion ratio, the estimated proportion of invariable sites, estimated gamma distribution, branch length, and optimized substitution rate. Phylogenetic trees were visualized and edited with MEGAX [START_REF] Kumar | MEGA X: Molecular Evolutionary Genetics Analysis across Computing Platforms[END_REF].

Results and discussion

Untargeted metabolomics for the metabotyping of Andean pseudocereals

Nowadays, chemotype discrimination between plants of the same botanical genus or family represents a challenge in the functional food sector. Chemotypes are characterized by the presence of certain metabolites, as major or minor compounds, in a plant. Despite their potential to enhance the food basket, the chemodiversity of pseudocereals has received little attention so far. To explore this chemodiversity, we used an untargeted metabolomics approach referred to as "metabotyping" as we did in a previous work investigating Cannabis cultivars [START_REF] Vásquez-Ocmín | Cannabinoids vs. whole metabolome: Relevance of cannabinomics in analyzing Cannabis varieties[END_REF]. We thus analyzed the whole metabolomes of several pseudocereal grains collected in the Andes of Peru, as well as one quinoa sample from France (Fig. 1-A). To ensure a comprehensive analysis of medium polar extract, positive ionization mode was investigated using the MS-CleanR workflow, which resulted in a list of 219 features (m/z x RT). Depending on the level of annotation mentioned above, 19 compounds were yielded for the genus (8.7%), 43 compounds for the family (19.6%), 128 compounds for the generic level (58.4 %), and 29 unknowns (13.2 %). The fitness of compound annotation generally depends on the databases (DB) used. Despite the few studies on pseudocereals, we confirmed an intern DB from family and genera gathered from the literature, responsible for 28.3 % of annotations (annotation level 3-1). This was complemented with our experimental DB (annotation level 1) and the spectral match with other DB in line (annotation level 2). Using NPClassifire and ClassyFire [START_REF] Djoumbou Feunang | ClassyFire: Automated chemical classification with a comprehensive, computable taxonomy[END_REF][START_REF] Kim | NPClassifier: A Deep Neural Network-Based Structural Classification Tool for Natural Products[END_REF] the major classes and subclasses of compounds following their biosynthetic pathway were identified (supp info 3).

Phylogenetic taxonomy has grouped the previously separated subfamily Chenopodiaceae within the family Amaranthaceae s.l., which include now the five phylotranscriptomic clades Amaranthaceae s.s., Betoideae, "Chenopods I", "Chenopods II", and Polycnemoideae [START_REF] Morales-Briones | Disentangling Sources of Gene Tree Discordance in Phylogenomic Data Sets: Testing Ancient Hybridizations in Amaranthaceae s[END_REF]. In our study, we have profiled by LC-MS 20 pseudocereal grain samples that belonged to:

Chenopods I [Chenopodium quinoa (14 samples) and C. pallidicaule (3 samples)] and Amaranthaceae s.s. [Amaranthus caudatus (syn: A. cruentus) (3 samples)]. To obtain an unsupervised overview of chemical fingerprint distribution, we firstly performed a principal component analysis (PCA). The PCA score plot from the two first principal components accounted for 63.8% of the total variance (Fig. 1-B). As expected, repeated injections of QC were grouped near the center of the PCA score plot demonstrating a good reproducibility and stability of the analytical workflow. Then, a hierarchical clustering analysis (HCA) was performed with 20 samples (three analytical repeats for each sample), obtaining three very well differenced clusters (Fig. 1-C). So, our metabolomic signature showed that Chenopodium species are grouped in two distinct clusters: cluster 1 (14 samples of quinoa) and cluster 2 (3 samples of canihua). Cluster 3 brought together the three Amaranthus grains (kiwicha). On the other hand, the provenance (in all clusters) and color of grains (in the cluster quinoa) did not play a significant role in the metabolomic classification intraspecies. However, inside the cluster quinoa, two other subgroups for red and white quinoa can be observed. An exception is white quinoa samples from Ayacucho and Cuzco that were compiled with red quinoa samples, which could infer a putative hybridization intraspecies. Additionally, to validate the HCA model and highlight characteristic biomarkers of each cluster, we performed a supervised Partial Least Squares-Discriminant Analysis (PLS-DA) based on the variable importance in projection (VIP) and a heat map was generated from the top 50 metabolites selected by Anova (supp info 4, 6-8). After our workflow analysis, unanticipated metabolites produced by filamentous fungi were identified in the final metadata. These metabolites were placed in a molecular network (Fig. 2-A). The molecular network of the whole dataset analyzed in PI mode was constructed to identify possible similarities between molecules based on spectral mass similarity (MS-MS fragmentation patterns) (Fig. 2). By grouping the major classes of compounds in clusters according to their biosynthetic pathway, there were a number of characteristic groups, such as amino acids and peptides, carbohydrates, alkaloids, fatty acids, polyketides, shikimates and phenylpropanoids, terpenoids, and others. Here, we can also observe the macrolide derivatives pandangolide 1a isolated from Cladosporium sp. [START_REF] Gesner | Pandangolide 1a, a Metabolite of the Sponge-Associated Fungus Cladosporium sp., and the Absolute Stereochemistry of Pandangolide 1 and iso-Cladospolide B[END_REF], and chaxlactin A from Streptomyces strain [START_REF] Rateb | Diverse Metabolic Profiles of a Streptomyces Strain Isolated from a Hyper-arid Environment[END_REF], the indole diketopiperazine alkaloid derivative asperfumifatin previously isolated from the endophytic Aspergillus fumigatus [START_REF] Xie | Secondary Metabolites from Aspergillus fumigatus, an Endophytic Fungus from the Liverwort Heteroscyphus tener (Steph.) Schiffn[END_REF], and the polyketide derivative altersolanol O from Alternaria sp. [START_REF] Chen | The Anthraquinone Derivatives from the Fungus Alternaria sp. XZSBG-1 from the Saline Lake in Bange, Tibet, China[END_REF] (Fig. 2-A). Another compound identified was a zearalenone derivative (3-(14,16-dihydroxy-3-methyl-1,7dioxo-3,4,5,6,7,8,9,10-octahydro-1H-2-benzoxacyclotetradecin-15-yl) (3,4,5-trimethoxyphenyl) propenamide). This compound was also identified as a marker for the cluster kiwicha (supp info 4-C). Zearalenone (ZEA) type of compounds are produced by several mycotoxigenic Fusarium (F. graminearum, F. cerealis, F. culmorum, F. equiseti, etc.), and are considered as mycotoxins. ZEA is distributed worldwide and naturally occurs in agricultural crops, particularly in maize. This mycotoxin could contaminate products made of barley, wheat, oats, rice, sorghum, and others (G.-L. Zhang et al., 2018). The structure is a macrolide type, and the name "zearalenone" is derived from the combination of the terms maize (Zea mays)-"zea", resorcylic acid lactone-"ral", -"en" for the presence of a double-bond, and "one" for the ketone group (Ropejko & Twarużek, 2021).

-N-[2-(1H-imidazol-1-yl)ethyl]-3-
The flexibility of the molecule is enough to adopt a conformation able to bind to the mammalian estrogen receptor, although with an affinity lower than the natural estrogen 17-β-estradiol resulting in severe effects on the reproductive system in several animal species, particularly pigs (Galaverna & Dall'Asta, 2012;G.-L. Zhang et al., 2018). Even if the molecule identified has the same macrolide structure of ZEA, this latter also presents a tyrosine alkaloid moiety. So far, to our knowledge, no bibliography about their toxicity was found. In this sense, close attention was taken to the compounds having structural similarities. In addition, another macrolide derivative (retrorsine) previously reported from Senecio gilliesiano or S. gilliesianus (Asteraceae) [START_REF] Guidugli | 1-Hydroxyplatyphyllide, a norsesquiterpene lactone from Senecio gilliesiano[END_REF] was annotated. All these metabolites described above are placed as self-loop in the molecular network. This suggests that there are no other molecule derivatives in the whole metabolome of the grains.

Moreover, we displayed the information correlated between the major class of compounds and the cluster producing (Fig. 2-B). As described in the literature, here we can observe that terpenoids (41%) and molecules belonging at shikimates and phenylpropanoids (24%) (e.g. flavonols, anthocyanidins, cinnamic acid derivatives, etc) are the most representative for the cluster quinoa [START_REF] Lin | Quinoa Secondary Metabolites and Their Biological Activities or Functions[END_REF][START_REF] Tabatabaei | The diversity of quinoa morphological traits and seed metabolic composition[END_REF]. Among the terpenoids, saponins were not identified, it is due to the postharvest process, where the grains are washed on various days with plenty of water to remove saponins localized in the pericarp [START_REF] Jarvis | The genome of Chenopodium quinoa[END_REF]. Triterpene saponins are known for their ecological defense role in the plant but are also known by the local people for providing a bitterness "amargor" or bitter-tasting "sabor amargo" to the unwashed grains [START_REF] Mccartney | Effects of saponin-rich quinoa (Chenopodium quinoa Willd.) bran and bran extract in diets of adapted and non-adapted quinoa pests in laboratory bioassays[END_REF]. For the cluster canihua, terpenoids (37%) and carbohydrates (29%) are the most representative class of molecules. At the opposite of the Chenopodium grains of the clusters quinoa and canihua, the majoritarian compounds identified for the cluster kiwicha were the amino acids (76%), mainly small peptides (Fig. 2-B). Due to the nutritional richness, in the last years the pseudocereals studied here are appreciated worldwide [START_REF] Fletcher | Pseudocereals: Overview[END_REF][START_REF] Perez-Rea | Chapter 12-The Functionality of Pseudocereal Starches[END_REF].

Targeted metabolomics revels the presence of an emerging mycotoxin in Andean pseudocereals

We complemented our approach with a targeted metabolomic analysis using LC-MS Qtrap Multiple Reaction Monitoring (Qtrap-MRM). Specifically, we focused on Aflatoxin B1 (AflaB1), Beauvericin (BEA), Fumonisin B1 (FumB1), Ochratoxin (OTA), and Patulin (Pat), which are mycotoxins produced by several species of Fusarium, Aspergillus, and Penicillium. Before implementing QqQ-MRM, we designed the main transitions (fragments) in both PI and NI modes of mycotoxins standards, as described previously (sup. info 2) [START_REF] Stead | The Development of a Sensitive Multi-Residue LC-MS/MS Method for the Quantitative Determination of Mycotoxins in Animal Feedstuffs and Silage Using Xevo TQ-S. Waters[END_REF]. We then assessed whether post-harvest washing could eliminate mycotoxins by comparing targeted metabolomes of washed and unwashed quinoa grains. On the five mycotoxins targeted, only FumB 1 and BEA were detected in PI mode (supp info 9). Among all samples, only seven of the quinoa samples trace amounts of FumB 1 (not quantifiable, <LOQ) (supp info 10). This result supports the interest in the consumption of quinoa as safe food, taking into account that our team has previously reported that other Andean grains may be contaminated with high levels of FumB 1 (notably maizes), exceeding the maximum food safety level of 1,000 ng/g [START_REF] Ducos | Natural Occurrence of Mycotoxin-Producing Fusaria in Market-Bought Peruvian Cereals: A Food Safety Threat for Andean Populations[END_REF]. Fumonisins, which have a long carbon chain aminoalcohol structure as their basic skeleton, are structurally similar to sphingosines (sphingoids). These mycotoxins are primarily produced by F. verticillioides and F. proliferatum [START_REF] Smith | Chapter 71-Fumonisins[END_REF]. It has been suggested that FumB 1 may increase the risk of cancer, notably in kidney and liver. Thus, FumB 1 was classified by the International Agency for Research on Cancer (IARC) as a potential human carcinogen (Group 2B) [START_REF] Claeys | Mycotoxin exposure and human cancer risk: A systematic review of epidemiological studies[END_REF][START_REF] Ostry | Mycotoxins as human carcinogens-The IARC Monographs classification[END_REF]. Concerning BEA, it was detected in 17 pseudocereal grain samples from Peru and in the only sample from France, with levels equal to or greater than the limit reported by the European Food Safety Authority (EFSA) for dietary acute exposure (i.e., 0.05 ng/mL or 0.14 ng/g of dried seeds) (Fig. 3-A) (EFSA, 2014). BEA and enniatins are emerging mycotoxins since they are not routinely determined nor regulated like other Fusarium mycotoxins, but evidence of their occurrence is rapidly increasing as an important natural contaminant in cereals and cereal-derived foods [START_REF] Malachova | Deoxynivalenol, Deoxynivalenol-3-glucoside, and Enniatins: The Major Mycotoxins Found in Cereal-Based Products on the Czech Market[END_REF][START_REF] Vaclavikova | Emerging' mycotoxins in cereals processing chains: Changes of enniatins during beer and bread making[END_REF]. BEA is a cyclic hexadepsipeptide synthesized by mycotoxigenic fungi, such as Beauveria bassiana and Fusarium spp. [START_REF] Wu | A Review on the Synthesis and Bioactivity Aspects of Beauvericin, a Fusarium Mycotoxin[END_REF]. This mycotoxin is harmful to human cells, displaying toxicity at lower concentrations than AflaB 1 [START_REF] Svingen | Enniatin B and beauvericin are common in Danish cereals and show high hepatotoxicity on a high-content imaging platform[END_REF]. Disturbingly, our findings indicate very elevated levels of BEA (7.9 ± 0.85 ng/g) in washed quinoa samples from Cajabamba (region of Cajamarca), 150-fold higher than the limit set by EFSA.

Cajabamba is located on the eastern slopes of the Andes (2,648 meters height above mean sea level, toward the highland jungle); hence, its ecoregion might have favorable conditions for the formation of mycotoxins by fungi (temperature, pH, moisture, etc.). The contamination of quinoa grains with BEA originating from Cajamarca represents a point of concern regarding food safety, as local authorities have recently promoted the cultivation of quinoa in this region (Gobierno Regional de Cajamarca, 2020). Significant amounts of BEA were also detected in canihua samples from Puno (C-Pun), with quinoa samples from France (WQw-Lauz) and red quinoa samples from Arequipa (RQw-Aqp). We also compared the relative mean peak area of detected mycotoxin in the untargeted metabolomics approach. In this sense, asperfumigatin, and altersolanol O are more present in samples for the quinoa and zearalenone derivative for all kiwicha samples (Fig 3-B). In cluster quinoa, the samples with more presence of asperfumigatin were red quinoa from Huaraz, Arequipa and Cajamarca, and white quinoa from Cajamarca (RQw-Huar, RQw-Aqp, RQw-Cax, WQw-Cax); and for altersolanol O, mainly white quinoa from Arequipa and Ayacucho, and red quinoa from Puno (WQw-Aqp, and WQw-Aya, RQw-Pun) (data not showed).

Fungal inventory infesting the Andean pseudocereals

The fungal inventory was realized with the aims to better know the filamentous fungi presents in the Andean pseudocereal samples and try to correlate this information with the presence of molecules produced themselves, especially the mycotoxins. Infestation by at least one fungal endobiont was spotted in 22 up 28 grain samples (78%). Sequence analysis was able to identify 74 fungal isolates (out of 85 total) at the genus level. Overall, we pinpointed 15 fungal families, composed by 20 genera and 14 species (supp info 11). Ascomycetes were the most common phylum of fungi (84%) (Fig. 4 A-B), represented by five orders: i) Eurotioales (Aspergillus sp., Penicillium sp., and Talaromycetes sp.), represents nearly two-third of the strains isolated (58%); ii) Pleosporales (19%), comprising: Alternaria sp., Bipolaris sp., Didymella sp., and Epicoccum sp.; iii) Cladosporales (11%) (only Cladosporium sp.); iv) Hypocreales (6%), and v) Xylariales (6%). In the same way, five Basidiomycetes and two Mucoromycetes species were spotted. Based on the ITS phylogeny and beta-tubulin and calmoduline genes analysis, a large diversity of Aspergillus sp. and Penicillium species could be observed. However, the precise identification of some others species was not achieved using ITS5 primers and the utilization of genus specifics primers (i.e. gpd 1 for Alternaria) would allow to go further in identifications [START_REF] Berbee | Cochliobolus Phylogenetics and the Origin of Known, Highly Virulent Pathogens, Inferred from ITS and Glyceraldehyde-3-Phosphate Dehydrogenase Gene Sequences[END_REF].

Mycotoxigenic fungi have been traditionally classified into two main groups: i) field fungi that contaminate crops before and during harvest (e.g., Fusarium, Alternaria, and Cladosporium spp.) and, ii) storage fungi (e.g., Penicillium and Aspergillus spp.) that tend to contaminate crops in a post-harvest manner. Overall, the mycotoxigenic fungi we found attached to Andean pseudocereals belonged to several genera, including Aspergillus, Penicillium, and Alternaria. For instance, Alternaria sp. is an ubiquitous plant pathogen that can infest a broad spectrum of plants, causing damage to crops and representing a hazard to human health [START_REF] Troncoso-Rojas | Chapter 5-Alternaria alternata (Black Rot, Black Spot)[END_REF]. Moreover, some genera have also the ability to protect their host against phytopathogens, such as the heterogeneous genus Cladosporium able to synthesize metabolites such as cladosporine with antifungal activity on the spore germination of Penicillium and Aspergillus species [START_REF] Bensch | Common but different: The expanding realm of Cladosporium[END_REF][START_REF] Scott | Cladosporin, a new antifungal metabolite from Cladosporium ciadosporioides[END_REF].

In our study even if BEA was detected in several samples, our fungal inventory about pseudocereals did not show the presence of Fusaria or Beauveria. It could be explained by fact that mycotoxin may persist while the fungus has disappeared. In addition, the natural production of these fungal groups is very sensitive to many environmental factors, i.e., altitude, drought, etc. Experimental limits, mainly the use of a limited number of seeds for each sample leading to non-exhaustive fungal isolation could also explain the absence of a Fusarium community in our inventory. Indeed, in our experimental condition, others species, better adapted to our experimental design might inhibit the growth of other strains. Likewise, the presence of the fungus does not prove the presence of mycotoxins. Some species are kwon to inhibit the mycotoxins production of other species such as the post-harvest pathogen Rhizopus oryzae, able to degrade mycotoxins like aflatoxins, OTA, or patulin, by the presence of a specific enzyme [START_REF] Varga | Degradation of ochratoxin A and other mycotoxins by Rhizopus isolates[END_REF]. The strain Rhizopus sp. was present concomitantly in our samples (RQw-Aqp and RQun-Cax) infested by A. flavus and A. cf. ochraceus, producers of aflatoxins like AflaB 1 or OTA. Our chemical analysis did not detect AflaB 1 and OTA in these samples, so we hypothesized that Rhizopus sp. could have detoxified the sample of the mycotoxins.

On the other hand, our inventory highlighted the presence of Alternaria, Aspergillus, and Cladosporium which could validate the metabolites production of alternolanol O (Alternaria sp.), asperfumigatin (Aspergillus fumigatus), and Pandangolide 1a (Cladosporium sp.), respectively.

A comparison between fungal species encountered on washed and unwashed quinoa was also

Conclusion

Global interest in pseudocereals as "superfood" has increased over the last decade. However, their chemodiversity has not been well studied to date. In the present work, metabotyping was able to add new insights into the chemotaxonomy of pseudocereals, confirming the previously established phylotranscriptomic clades. Metabolomics identified three clusters among Chenopodium (clusters 1 and 2) and Amaranthus grain samples (cluster 3). In addition, we highlighted their main markers and major class of compounds by cluster. Moreover, we report for the first time the presence of mycotoxins in the pseudocereals. Sixteen samples of Peru (out of 27) and one sample from France (out of one) were contaminated with Beauvericin, an emerging mycotoxin. One sample of white quinoa from Cajabamba (Cajamarca) showed an alarming high level of Beauvericin. To link the occurrence of mycotoxins with the presence of toxin-producing fungi in pseudocereals, an inventory of filamentous fungi was taken. Several mycotoxigenic fungi were detected, including Aspergillus sp., Penicillium sp., and Alternaria sp., but not Fusaria. The present study underscores the need to better understand the chemistry of pseudocereals, as well as further research into the risk associated with emerging mycotoxins.

  bags at -20°C. Authorization to access genetic resources was granted by the competent authority (INIA) under Biodiversity Collection Permit Number 021-2018-MINAGRI-INIA-DGIA/SDRIA.

Figure 1 .

 1 Figure 1. (A) Geographic origins of the grain samples. The names of the 24 administrative departments of Peru are indicated in black. The departments of collection are stamped with a red star marked with the number of samples collected therein. Green = Peruvian Amazon (including highland and lowland jungles); brown = Andean highlands; orange = arid and semi-arid Pacific coastal lands. (B) Set of samples used for the metabolomics analyses. (C) Global PCA of 20 pseudocereal grains from Peru (except for WQ-Lauz, France). (D) Hierarchical clustering analysis (HCA) following the whole metabolome to group all grain samples. Pseudocereal varieties: WQw-Cuz = white quinoa washed from Cuzco, WQw-Aya = white quinoa washed from Ayacucho, RQw-Aya = red quinoa washed from

Figure 2 .

 2 Figure 2. Molecular network (PI mode) from compounds identified in pseudocereals, based on MetGem and visualized by Cytoscape. Colors in A and B are correlated with the major classes of compounds annotated. Structures and names of some metabolites annotated from fungal biosources are represented in A. In B, the clusters are correlated with Fig 1-C. In these clusters, we represented the percentage of the major classes of compounds obtained by cluster.

Figure 3 .

 3 Figure 3. Quantification of BEA mycotoxin and others metabolites by LCMS. (A) Bar-plot of BEA amount (mean + sd, n=3) in Andean pseudocereal samples expressed in ng/g of dried grains. The dotted line represents the theoretical level of beauvericin among the legislation (0.14 ng/g in dried seeds, EFSA). (B) Bar-plot displaying the relative quantification by the cluster of three molecules produced by fungus microorganisms in AP. The lowercase letters indicate significant differences between pseudocereal samples (one-way ANOVA).

  performed. Nineteen species were isolated on unwashed seeds and 11 on washed samples (Fig4-C).Among them, only three species grew in both conditions: Aspergillus amstelodami/montevidensis, Cladosporium cf. cladosporoides, and Rhizopus sp. These washing steps have double consequences: on the one hand, it can cause the elimination of the fungal strains present on seeds at the time of the harvest, and, on the other hand, this phenomenon involving water can allow the emergence of other strains being able to develop under favorable conditions.

Figure 4 .

 4 Figure 4. Maximum-likelihood phylogenetic tree based on samples ITS sequences and closest ITS reference sequences from GenBank. The tree was obtained by applying the PhyML method in the Geneious® plateform. Bootstrap values > 50% are indicated above branches. (A) Codes of samples are described in supp info 1 and letters were assigned for each strain isolated. (B) Main genus of fungal community identified from Andean pseudocereals, genera are expressed in number of strains and percentage. (C) Diagram of Venn for washed and unwashed conditions from quinoa relied to their fungal community. * : not possible to choose between the 2 species

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Acknowledges

The authors wish to acknowledge a postdoctoral fellowship of PGV-O from the French National Research Institute for Sustainable Development (IRD) under contract number 04077858. The authors are grateful to Pascal Pineau (Institut Pasteur de Paris), Olivier Puel, Sophie Lorber-Pascal (Toxalim, INRAE) for the provision of mycotoxin standards. The authors are also grateful with Lina Abdelwahed (Université Paul Sabatier -Toulouse 3), Sylvie Fournier, Amélie Pérez, Justine Chervin, Virginie Puech-Pagès (MetaToul-Agromix), Juan Pablo Cerapio Arroyo (Centre de Recherches en Cancérologie de Toulouse), David Condori Cruz (Universidad Peruana Cayetano Heredia) for their technical supports; and Alexandre Maciuk (Université Paris-Saclay) for his critical discussion.

Authors contribution

Conceptualization: SB, PGV-O, and GM; methodology: PGV-O, GM, and SB; chemical data acquisition/curation: PGVO and GM; biological data curation: AG, PJ, and SB; investigation: PGV-O, GM, AG, SB, GC, JAV-B, SC-Z, PJ, NP, and MH. PGV-O wrote the original draft and all the authors contributed and validated the final manuscript.

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.