Céline Albert
email: celine.albert1@univ-lr.fr

Marina Renedo

Paco Bustamante

Jérôme Fort

Using blood and feathers to investigate large-scale Hg contamination in Arctic seabirds: A review

Keywords: Seabirds, Spatial ecotoxicology, Molting pattern, Mercury

, because of its deleterious effects on wildlife and its high concentrations in polar regions, has been widely studied in the Arctic. This provided important information regarding food web contamination, spatial and temporal trends of Hg in ecosystems or risk assessments for wildlife and Humans. Among the Arctic biota, seabirds have been among the most studied species due to their sensitivity to this toxicant, their role as bioindicators of the contamination status of their environment, and their consumption by Arctic communities. However, most studies that investigated Hg in Arctic seabirds focused on measurements in internal organs or in eggs, while few investigations have been performed on blood and feathers, despite the relevant and complementary information they provide. Here, we first provide a detailed overview of the specific information blood and feathers can bring when investigating Hg contamination of Arctic seabirds, including new knowledge on the poorly studied non-breeding period. Second, we perform a comprehensive review of the use of blood and feathers as non-lethal tissues to study Hg in Arctic seabirds. This review demonstrates important interspecific variations in Hg blood concentrations according to seabird trophic status, with seaducks generally presenting the lowest Hg concentrations while auks have the highest ones. However, all the observed Hg concentrations are below the admitted toxicity thresholds. Hg concentrations in feathers follow similar trends and gulls appear to be the most contaminated species, likely as a consequence of contrasting migratory and overwintering strategies. This review also confirms strong spatial variations with higher concentrations found in the Canadian Arctic and Pacific waters than in Greenland and the European Arctic. It also identifies some major understudied areas such as West Greenland, Aleutian Islands and Russia. Finally, we provide a thorough review of the current knowledge regarding molting patterns in Arctic seabirds, which is an essential information to interpret Hg concentrations measured in feathers. Overall, our results point out the importance of blood and feathers in seabird ecotoxicological assessments and highlight the need for large scale international collaborations and research programs.

Introduction

Mercury (Hg) is a metallic trace element naturally found in the environment, released by volcanic eruptions or weathering. However, human activities, such as coal burning or gold mining, have been responsible for a large increase in Hg emissions, especially since the 19 th century (UNEP, 2013). Because of its solubility, its ability to enter and biomagnify along the food chains (as methylmercury -MeHg [START_REF] Morel | The chemical cycle and bioaccumulation of mercury[END_REF]), and its toxicity for human and wildlife (e.g., [START_REF] Tan | The endocrine effects of mercury in humans and wildlife[END_REF][START_REF] Wolfe | Effects of mercury on wildlife: a comprehensive review[END_REF], this pollutant requires close monitoring.

More specifically, a major emphasis has been put towards the understanding of Hg levels in marine organisms, underlying modulators and resulting impacts on nervous systems, reproduction or development [START_REF] Eagles-Smith | Modulators of mercury risk to wildlife and humans in the context of rapid global change[END_REF]. Anthropogenic Hg is mainly emitted by midlatitude northern countries, with still increasing emissions in some regions such as Asia (UNEP, 2013). It is then transported over large distances to polar regions by atmospheric and oceanic currents and, in the case of the Arctic, by rivers [START_REF] Sonke | Eurasian river spring flood observations support net Arctic Ocean mercury export to the atmosphere and Atlantic Ocean[END_REF]UNEP, 2013). Therefore, polar top predators are among the most exposed organisms to Hg [START_REF] Cherel | Accumulate or eliminate? Seasonal mercury dynamics in albatrosses, the most contaminated family of birds[END_REF] and have thus been largely studied both in toxicity and conservation contexts, but also as efficient indicators to monitor Hg contamination in polar marine ecosystems (e.g., [START_REF] Carravieri | Penguins as bioindicators of mercury contamination in the Southern Ocean: birds from the Kerguelen Islands as a case study[END_REF][START_REF] Dietz | What are the toxicological effects of mercury in Arctic biota?[END_REF]Mallory et al., 2017;[START_REF] Sun | A 2000-year record of mercury and ancient civilizations in seal hairs from King George Island, West Antarctica[END_REF][START_REF] Verreault | The Svalbard glaucous gull as bioindicator species in the European arctic: insight from 35 Years of contaminants research[END_REF]. Among those polar top predators, Arctic seabirds, being long-lived species with a circumpolar distribution, have been widely used to study long-term and relatively large-scale Hg exposure (see [START_REF] Becker | Chapter 19 biomonitoring with birds[END_REF]. However, these studies mainly focused on the period during which seabirds are at their breeding site (hereafter the breeding season), even though this period represents a part of their annual cycle only. Conversely, investigations for the nonbreeding period are still scarce, mainly because most of seabirds are offshore during this period, making their sampling logistically difficult. Previous studies suggested that Arctic seabirds could be exposed to higher Hg levels during the non-breeding period with subsequent impacts on their reproduction (e.g. [START_REF] Fort | Spatial ecotoxicology: migratory arctic seabirds are exposed to mercury contamination while overwintering in the Northwest Atlantic[END_REF]. Hence, improving our knowledge of bird contamination during the non-breeding periodwhich mostly occurs outside the Arcticis crucial, first to determine its role on seabird exposure to Hg, but also to better understand the origin of this contamination, in space and time.

Several tissues were targeted within the various studies which investigated Hg in Arctic seabirds, providing information about seabird Hg contamination at different temporal scales. Indeed, once ingested through the diet (the main source of Hg intake), Hg enters the bloodstream where it stays a few weeks/months (e.g. half-life of 30 days in great skua (Stercorarius skua) [START_REF] Bearhop | Dynamics of mercury in blood and feathers of great skuas[END_REF] and of 40-65 days in Cory's shearwaters (Calonectric borealis) [START_REF] Monteiro | Kinetics, Dose-Response, and excretion of methylmercury in free-living adult Cory's shearwaters[END_REF]). Hg in blood thus informs about recent intakes (e.g. from late migration to chick-rearing when blood is sampled during the breeding season). Once Hg is assimilated, it is transported and distributed to the different organs, where it can be demethylated (i.e. protective mechanism against Hg toxicity) and/or stored [START_REF] Dietz | What are the toxicological effects of mercury in Arctic biota?[END_REF]. While internal organs such as liver, brain, kidney and muscle give access to longer term Hg contamination compared to blood [START_REF] Mallory | Mercury concentrations in blood, brain and muscle tissues of coastal and pelagic birds from northeastern Canada[END_REF], the liver also informs, depending on the species, about Hg demethylation abilities [START_REF] Dehn | Trace elements in tissues of phocid seals harvested in the Alaskan and Canadian Arctic: influence of age and feeding ecology[END_REF]Kim et al., 1996b;[START_REF] Thompson | The chemical form of mercury stored in South Atlantic seabirds[END_REF]. Finally, egg production and feather synthesis (molt) are two major excretion pathways for Hg. The study of eggs therefore informs about seabird Hg contamination during the laying time (and/or during the pre-breeding time in case of "capital" breeders (i.e. allocation of stored nutrients to egg formation) [START_REF] Becker | Chapter 19 biomonitoring with birds[END_REF][START_REF] Bond | Nutrient allocation for egg production in six Atlantic seabirds[END_REF]Mallory et al., 2017)). Cover feathers provide information about Hg contamination during a relatively longer period (over several weeks/months according to species and molting patterns [START_REF] Furness | Using bird feathers to measure mercury in the environment: relationships between mercury content and moult[END_REF], see below, Annex 1)). Because of toxicological risks for seabirds and consumers (seabirds and their eggs are consumed in several Arctic regions [START_REF] Bard | Global transport of anthropogenic contaminants and the consequences for the arctic marine ecosystem[END_REF][START_REF] Chan | A database for environmental contaminants in traditional foods in northern and arctic Canada: development and applications[END_REF][START_REF] Mallory | Tracking contaminants in seabirds of Arctic Canada: temporal and spatial insights[END_REF]), internal tissues and eggs have received most of the attention (Figs. 1 and2). Conversely, non-consumed tissues such as blood and feathers received much less attention, despite the relevant and complementary spatio-temporal information they could provide, and the fact that they can be non-lethally sampled. In the present study, we thus review and discuss the current knowledge of Hg contamination in Arctic seabirds, with a specific focus on the information provided by blood and feather tissues. We will also highlight how these tissues and their combination with new approaches could help us improving knowledge of seabird yearly (breeding and nonbreeding) Hg contamination.

Methods

Reviewing process

A review of the literature was done on Scopus searching for three keywords: "seabirds", "Arctic" and "mercury" on December 2018. The Arctic boundaries used were as defined by the Conservation of Arctic Flora and Fauna (CAFF) working group [START_REF] Caff | Proposed Protected Areas in the Circumpolar Arctic[END_REF], and only the species breeding within these boundaries and spending most of the year feeding in oceanic food webs were included in the analysis (Annex 1). Blood and feather Hg concentrations were extracted and, when necessary, blood values were converted to dry weight using a moisture of 79.13% [START_REF] Eagles-Smith | Mercury correlations among six tissues for four waterbird species breeding in San Francisco Bay, California, USA[END_REF] to allow comparison between published values. We considered feather concentrations provided in wet weight directly comparable to those in dry weight as moisture content is negligible in feathers (e.g. [START_REF] Stettenheim | Integument[END_REF]. A review of molting patterns for the retained species was also performed and is summarized in Annex 1.

Statistical analyses

The dataset does not provide sufficient information to test any temporal or spatial trend in Hg concentrations (underrepresentation of some families, species, countries or years). However, for both blood and feathers, we used ANOVA to compare Hg concentrations between families (see Figs. S1 andS2). More specifically, for blood, we used mean values provided by each study for each species and then compared Hg concentrations between families being adults anatids (n=29) and larids (n=19) and removed the alcids (n=4) and the procellariids (n=1) because of limited data (see Fig. S1). For feathers, we used mean values provided by each study for each species and then compared Hg concentrations between families being adults alcids (n=31), anatids (n=8) and larids (n=19) and removed Hg concentrations for hydrobatids (n=1) and stercorariids (n=2) because of limited data (see Fig. S2). Statistical significance was assumed at p < 0.05 and analyses were run with R studio (version 1.2.1335).

Results and discussion

Hg assessment in blood and feathers of Arctic seabirds

The present review shows that 101 published articles (see Annex 2) reported Hg concentrations in Arctic seabirds (i.e. species/populations breeding in the Arctic) since 1984.

In total, 42 species (list provided in Annex 1) from all around the Arctic were assessed, yet with an emphasis on the Canadian Arctic (n=38 publications), Svalbard (n=23), Aleutian Islands (n=16), Alaska (n=14) and West Greenland (n=7). In addition, internal tissues and eggs were more investigated than blood and feathers (81, 30, 22 and 19 studies, respectively), also integrating a wider spatial scale (Figs. 1 and2). Among studied species, three families received most of the attention: gulls (hereafter larids) (n=56 publications), auks (hereafter alcids) (n=49) and seaducks (hereafter anatids) (n=44), covering all foraging strategies (benthic, pelagic, coastal, oceanic, divers, surface feeders, scavengers) and diets (insectivorous, molluscivorous, planktivorous, piscivorous, omnivorous).

Blood Hg concentrations were investigated in a total of 12 seabird species but anatids and larids were the most studied (see Table 1). For the Anatid family (n=12 studies), the common eider (Somateria mollissima), the king eider (Somateria spectabilis), the Steller's eider (Polysticta stelleri), the spectacled eider (Somateria fischeri) and the long-tailed duck (Clangula hyemalis) were studied, covering Alaska, Svalbard and the Canadian Arctic. For the Larid family, investigations focused on the black-legged kittiwake (Rissa tridactyla) (n=8 studies) covering both the Canadian Arctic and Svalbard, and the ivory gull (Pagophila eburnea) (n=1 study) in Svalbard. Finally, four studies investigated Hg contamination of alcids breeding in the Canadian Arctic (Brünnich's guillemots (Uria lomvia) and black guillemots (Cepphus grylle)), East Greenland (little auks (Alle alle)) and Svalbard (Mandt's black guillemot (Cepphus grylle mandtii)), and one study investigated Hg contamination in procellariids (northern fulmars (Fulmarus glacialis)) from the Canadian Arctic.

Most studies which measured Hg concentrations in feathers focused on body (n=18 publications) and flight (n=4) feathers. They covered more areas than blood investigations and were mainly performed in the Aleutian Islands (n=7 publications) and in Alaska (n=3), followed by East Greenland (n=3), Svalbard (n=2), Russia (n=2), the Canadian Arctic (n=2) and Norway (n=1). They encompassed alcids (n=10), larids (n=9), anatids (n=8), procellariids (n=2) and stercorariids (n=1) (see Tables 2 and3). There was a large heterogeneity between the different regions. In the Pacific Arctic, the Aleutian Islands are the only area where Hg contamination has been measured in feathers, targeting alcids (Kittlitz's murrelet (Brachyramphus brevorostris), pigeon guillemot (Cepphus columba), tufted puffin (Fratercula cirrhate)), anatids (common eider (Somateria mollissima)), hydrobatids (forktailed storm-petrel (Oceanodroma furcata)) and larids (blacklegged kittiwakes (Rissa tridactyla), glaucous-winged gull (Larus glaucescens)). In the Atlantic Arctic, each country was studied, providing information for alcids (Brünnich's guillemot, common guillemot (Uria aalge), little auk), anatids (king eider, common eider, long-tailed duck), larids (black-legged kittiwake, Arctic tern (Sterna paradisae), Sabine's gull (Xema sabini), ivory gull, glaucous gull (Larus hyperboreus), herring gull (Larus argentatus)), procellariids (northern fulmar) and stercorariids (parasitic jaeger (Stercorarius parasiticus), long-tailed jaeger (Stercorarius longicaudus)). The common eider and the black-legged kittiwake are the only two species studied in both the Atlantic and Pacific Arctic. In Russia, only one site (Chaun, Siberia) was studied with feather Hg measurements performed in anatids (long-tailed duck and king eider), larids (herring gull, Arctic tern, glaucous gull, Sabine's gull) and stercorariids (long-tailed and parasitic jaeger). Flight feathers were processed in three studies that only focused on alcids (Brünnich's guillemot, Kittlitz's murrelet), anatids (long-tailed-duck, common eider), larids (herring gull, Arctic tern, black-legged kittiwakes, ivory gull and glaucous gull) and procellariids (northern fulmar) (Table 3) [START_REF] Kenney | Mercury concentrations in multiple tissues of Kittlitz's murrelets (Brachyramphus brevirostris)[END_REF]Kim et al., 1996b;[START_REF] Mallory | Mercury concentrations in feathers of marine birds in Arctic Canada 29[END_REF]. Finally, three studies focused on the non-breeding period only, and all were performed on little auks breeding in East Greenland [START_REF] Fort | Spatial ecotoxicology: migratory arctic seabirds are exposed to mercury contamination while overwintering in the Northwest Atlantic[END_REF][START_REF] Fort | Does temporal variation of mercury levels in Arctic seabirds reflect changes in global environmental contamination, or a modification of Arctic marine food web functioning?[END_REF][START_REF] Amélineau | Arctic climate change and pollution impact little auk foraging and fitness across a decade[END_REF].

Blood as a tool to monitor Hg contamination during the breeding season

During the breeding season, seabirds aggregate in colonies where blood samples can be more easily collected. Sampling periods extend from the pre-laying to the late chick-rearing stages, allowing investigations on adult seabird short-term Hg contamination (i.e. from late migration to chick-rearing [START_REF] Bearhop | Dynamics of mercury in blood and feathers of great skuas[END_REF][START_REF] Evers | Adverse effects from environmental mercury loads on breeding common loons[END_REF][START_REF] Monteiro | Seabirds as Monitors of Mercury in the Marine Environment[END_REF]). Hg analyses are done on whole blood or on blood cells (concentrations in these two matrices being highly correlated (Sire et al. unpublished)). Blood is also a good proxy for Hg concentrations in other internal tissues. Indeed, Hg concentrations in blood have been found to be strongly correlated with Hg concentrations in brain and muscle (e.g., [START_REF] Fort | Mercury in wintering seabirds, an aggravating factor to winter wrecks?[END_REF][START_REF] Mallory | Mercury concentrations in blood, brain and muscle tissues of coastal and pelagic birds from northeastern Canada[END_REF]. In addition, as a non-lethally sampled tissue, blood has several advantages. First, individuals can be sampled every year for long-term Hg monitoring at the individual and population scales or several times along the breeding season. This provides specific information about Hg dynamics along the pre-laying, incubation and chick-rearing periods (see [START_REF] Lavoie | Contamination of mercury during the wintering period influences concentrations at breeding sites in two migratory piscivorous birds[END_REF]. Second, a large number of individuals and species can be sampled at a broad scale, allowing spatial comparisons of Hg concentrations and thus largescale monitoring. For instance, [START_REF] Ackerman | Maternal transfer of contaminants in birds: mercury and selenium concentrations in parents and their eggs[END_REF] reviewed bird Hg contamination across the Northwestern America to map the distribution of Hg concentrations and highlighted hotspots of Hg contamination.

Our results show that anatids had lower Hg concentrations in blood than larids (F1,46=14.36, p < 0.001). For anatids, Hg concentrations ranged from 0.57 ± 0.04 μg/g dw (long-tailed duck, [START_REF] Franson | Contaminants in molting long-tailed ducks and nesting common eiders in the Beaufort Sea[END_REF] to 2.25 ± 0.29 μg/g dw (common eider, [START_REF] Provencher | Anti-parasite treatment, but not mercury burdens, influence nesting propensity dependent on arrival time or body condition in a marine bird[END_REF] (Table 1, Figs. 3 and4) with an average value of 1.04 ± 0.33 μg/g dw. For larids, concentrations ranged from 0.81 ± 0.05 μg/g dw (ivory gull, [START_REF] Lucia | Trace element concentrations in relation to the trophic behaviour of endangered ivory gulls (Pagophila eburnea) during their stay at a breeding site in Svalbard[END_REF] to 3.04 ± 1.41 μg/g dw (black-legged kittiwake, [START_REF] Mallory | Mercury concentrations in blood, brain and muscle tissues of coastal and pelagic birds from northeastern Canada[END_REF] (Table 1, Figs. 3 and4) with an average value of 1.57 ± 0.48 μg/g dw.

Finally, Hg concentrations in alcid blood samples ranged from 0.32 ± 0.80 μg/g dw to 4.58 μg/g dw, both measured in black guillemots [START_REF] Eckbo | Individual variability in contaminants and physiological status in a resident Arctic seabird species[END_REF]Mallory et al., 2018, respectively), with an average value for this family of 2.16 ± 1.58 μg/g dw. Overall, these data show a high inter-species variability (see Table 1,Figs. 3 and 4). Even if alcids have the highest mean blood Hg concentration, too few values (n=4) were reported to confirm that they are significantly more contaminated than the two other families. In addition, such variations in blood Hg concentrations among taxa are in accordance with the feeding ecology of these species. Indeed, anatids feed at low trophic levels (i.e. mostly on molluscs and crustaceans) during the breeding season. Guillemots feed at intermediate levels (mostly on planktivorous fish species) (Gaston and Jones, 1998) while larids occupy the highest trophic levels (see [START_REF] Braune | Temporal trends of mercury in eggs of five sympatrically breeding seabird species in the Canadian Arctic[END_REF][START_REF] Burgess | Mercury trends in herring gull (Larus argentatus) eggs from Atlantic Canada, 1972-2008: temporal change or dietary shift?[END_REF][START_REF] Hobson | A Stable Isotope (δ 13 C, δ 15 N) Model for the North Water Food Web: Implications for Evaluating Trophodynamics and the Flow of Energy and Contaminants[END_REF][START_REF] Hobson | Using stable isotopes to determine seabird trophic relationships[END_REF] for a review) (Fig. 4). It should also be noted that all families reviewed in this study showed blood Hg concentrations below toxicity thresholds associated with substantial impairments to health and reproduction (2 μg/g ww, equivalent to approximately 9.6 μg/g dw; [START_REF] Ackerman | Maternal transfer of contaminants in birds: mercury and selenium concentrations in parents and their eggs[END_REF]. These results also highlight spatial variations through the Arctic, with higher levels found in the Canadian Arctic and Alaska than in East Greenland or Svalbard, and thus confirms previous investigations using eggs which found higher values in the Canadian Arctic (Arctic Monitoring and Assessment Programme (AMAP), 2018; [START_REF] Provencher | Mercury and marine birds in Arctic Canada: effects, current trends, and why we should be paying closer attention[END_REF]. They are also in agreement with previous investigations performed on internal tissues where higher Hg concentrations were found in the liver of Canadian Arctic seabirds (Northern Baffin Bay) compared to those from the European Arctic (Central Barents Sea) [START_REF] Borgå | Regional and species-specific bioaccumulation of major and trace elements in arctic seabirds[END_REF].

Although more analyses are needed to confirm this spatial trend by including various missing Arctic regions (e.g. Russia, Northwest Greenland, Aleutian Islands, Alaska), these observations provide additional elements towards the understanding of Hg spatial distribution in the Arctic.

Finally, Braune et al. (2007) adjusted Hg concentrations by trophic status in seabird eggs (δ 15 N) to take into account any change in their trophic position and, hence, to study temporal changes in Hg contamination. This method was subsequently used on different species and sites [START_REF] Braune | Temporal trends of mercury in eggs of five sympatrically breeding seabird species in the Canadian Arctic[END_REF][START_REF] Burgess | Mercury trends in herring gull (Larus argentatus) eggs from Atlantic Canada, 1972-2008: temporal change or dietary shift?[END_REF]. Blood, as eggs, represents relatively local (in the vicinity of the colony) and short-term dietary exposure. Blood Hg concentrations strongly depend on seabird diet and trophic position (i.e. biomagnification process), which can vary between individuals, populations and species. Hence, and similarly to Braune and colleagues' method, we propose that the adjusted Hg concentrations in blood could be used to monitor Hg temporal and spatial trends not only in seabirds but also in the Arctic marine food chains.

Feathers as a tool to monitor Hg contamination at different seasons

Hg excretion to feathers, molting patterns and feathers to monitor Hg contamination through the Arctic

Approximately 70-90% of the Hg available in the bloodstream and internal tissues is excreted into the plumage during molt [START_REF] Agusa | Body distribution of trace elements in Blacktailed gulls from Rishiri Island, Japan: age-dependent accumulation and transfer to feathers and eggs[END_REF][START_REF] Braune | Comparison of total mercury levels in relation to diet and molt for nine species of marine birds[END_REF][START_REF] Honda | Seasonal changes in mercury accumulation in the black-eared kite, Milvus migrans lineatus[END_REF]. Hg bounds to disulphide bridges of feather keratins [START_REF] Crewther | The chemistry of keratins[END_REF] and becomes stable once the feather is grown [START_REF] Appelquist | Mercury monitoring: mercury stability in bird feathers[END_REF]. Hence, Hg concentrations in feathers represent the Hg accumulated between two molts and inform about the Hg body burden at the molting time [START_REF] Agusa | Body distribution of trace elements in Blacktailed gulls from Rishiri Island, Japan: age-dependent accumulation and transfer to feathers and eggs[END_REF][START_REF] Furness | Using bird feathers to measure mercury in the environment: relationships between mercury content and moult[END_REF]. As a consequence, Hg concentrations in feathers are not affected by the age of the individual [START_REF] Honda | Seasonal changes in mercury accumulation in the black-eared kite, Milvus migrans lineatus[END_REF][START_REF] Bustamante | High feather mercury concentrations in the wandering albatross are related to sex, breeding status and trophic ecology with no demographic consequences[END_REF]. As they can be non-lethally sampled, feathers have also been proposed as a good proxy to study seabird exposure to Hg [START_REF] Monteiro | Seabirds as Monitors of Mercury in the Marine Environment[END_REF]. The Hg excreted into feathers is mainly under its organic and toxic MeHg form (> 80%) [START_REF] Bond | Total and methyl mercury concentrations in seabird feathers and eggs[END_REF][START_REF] Renedo | Assessment of mercury speciation in feathers using species-specific isotope dilution analysis[END_REF][START_REF] Thompson | The chemical form of mercury stored in South Atlantic seabirds[END_REF]. This means that measuring total Hg concentrations in seabird feather samples provides a good information about their contamination and exposure to MeHg. Similar to blood, feathers can be collected every year on the same individuals [START_REF] Bearhop | Dynamics of mercury in blood and feathers of great skuas[END_REF], hence allowing long-term assessment of individual Hg exposure. In addition, depending on the species, molting patterns and the type of feather considered, feathers can inform about Hg exposure during different periods of the year [START_REF] Lavoie | Contamination of mercury during the wintering period influences concentrations at breeding sites in two migratory piscivorous birds[END_REF][START_REF] Fort | Spatial ecotoxicology: migratory arctic seabirds are exposed to mercury contamination while overwintering in the Northwest Atlantic[END_REF]. Some Arctic seabirds molt once a year only, i.e. post or pre-breeding molt, as is the case for female anatids or ivory gulls, respectively. Some other species (most of the alcids, larids, and male anatids) molt twice a year (see the complete review of molting patterns in Annex 1). As an example, alcids have a first partial molt occurring before the breeding period and leading to a nuptial plumage, when only head and neck feathers are replaced. A second complete molt occurs after the breeding period during which all feathers, including body, head and flight feathers, are renewed. Conversely, the northern gannet (Morus bassanus) is the only species breeding in the Arctic that presents a continuous molt of body feathers (see Annex 1), which leads to a more complex interpretation of the feather Hg concentrations [START_REF] Cherel | Accumulate or eliminate? Seasonal mercury dynamics in albatrosses, the most contaminated family of birds[END_REF].

Three different types of feather are commonly used in Hg assessments: flight (primary and secondary) feathers, body feathers and head feathers. Head feathers of most alcid and larid species (Annex 1) provide information about Hg contamination of individual seabirds specifically during the non-breeding period (Fort et al., 2014, Fig. 5). However, their use has been largely neglected to date. Primary and body feathers inform about seabird Hg contamination either over the breeding season for species molting twice a year or over a full year for those molting once a year (Fig. 5). Nevertheless, primary feathers show a much higher inter-feather variability of Hg concentrations compared to body feathers. Feathers are sequentially molted from primary 1 (P1) to primary 10 (P10), with higher Hg quantities excreted into P1 and then decreasing from P2 to P10 [START_REF] Furness | Using bird feathers to measure mercury in the environment: relationships between mercury content and moult[END_REF]) (Fig. 5).

Conversely, body feathers are molted at the same period and show lower variability (Brasso et al., 2013;[START_REF] Carravieri | Moulting patterns drive within-individual variations of stable isotopes and mercury in seabird body feathers: implications for monitoring of the marine environment[END_REF][START_REF] Furness | Using bird feathers to measure mercury in the environment: relationships between mercury content and moult[END_REF]. Therefore, if primary feathers are chosen to investigate seabird exposure to Hg, they must be carefully selected in order to make Hg measurements comparable between the different individuals. In addition, some species also have a sequential molt of their body and flight feathers over several months or an unknown molting pattern. The use of these species for feather Hg assessment is thus more complicated. This is the case of the Atlantic puffin (Fratercula arctica), the whiskered auklet (Aethia pygmaea), the Leach's storm-petrel (Oceanodroma leucorhoa) and the Fork-tailed storm-petrel (Oceanodroma furcata), the pelagic cormorant (Stercorarius longicaudus) and the red-faced cormorant (Stercorarius pomarinus) (Gaston and Jones, 1998;Harris, 1974;Pyle, 2016;Toochin and Fenneman, 2014;Van Tets, 1959). For instance, the Atlantic puffin, as most of the alcids, undergoes two molts per year but this species presents unsynchronized post-breeding molts between individuals (Gaston and Jones, 1998;Harris and Yule, 1977).

Hg contamination of Arctic seabirds during the breeding season or through the entire year

At the Arctic scale, Hg concentrations measured in body feathers significantly differed between bird families (ANOVA, F2,55=10.19, p < 0.001), with the lowest mean Hg concentrations measured in anatids (0.92 ± 0.19 μg/g dw), followed by alcids (2.20 ± 1.23 μg/g dw) and larids (3.53 ± 1.74 μg/g dw).

More specifically, while Hg concentrations measured in female anatids (for which body feathers represent yearly local exposure) did not exceed 2 μg/g dw and showed little intra-and interspecific variations, alcids (for which body feathers represent contamination during breeding period only), reached concentrations of 7 μg/g dw and showed higher interspecific variations (See Table 2, Figs. 6 and7). As observed for blood, these results are consistent with the knowledge of species' diet and trophic position. For instance, little auks (1.00 ± 0.22 to 2.11 ± 1.49 μg/g dw; [START_REF] Fort | Does temporal variation of mercury levels in Arctic seabirds reflect changes in global environmental contamination, or a modification of Arctic marine food web functioning?[END_REF][START_REF] Amélineau | Arctic climate change and pollution impact little auk foraging and fitness across a decade[END_REF] feed mostly on zooplankton, while tufted puffins (2.48 ± 0.25 to 2.59 ± 0.29 μg/g dw; Burger and Gochfeld, 2009) and Kittlitz's murrelets (from 1.66 ± 1.28 [START_REF] Kaler | Mercury concentrations in breast feathers of three upper trophic level marine predators from the western Aleutian Islands, Alaska[END_REF] to 5.15 ± 2.51 μg/g dw [START_REF] Kenney | Mercury concentrations in multiple tissues of Kittlitz's murrelets (Brachyramphus brevirostris)[END_REF]) feed on a mixed diet of fish and invertebrates (Gaston and Jones, 1998;[START_REF] Hobson | Using stable isotopes to determine seabird trophic relationships[END_REF]. However, these differences might also be explained by the spatial variations of Hg contamination of their prey. For instance, common (0.88 ± 0.19 μg/g dw; Wenzel and Gabrielsen, 1995), Brünnich's (0.78 ± 0.18 μg/g dw; Wenzel and Gabrielsen, 1995), and pigeon guillemots (7.72 ± 0.84 μg/g dw; Burger and Gochfeld, 2009) are all mostly piscivorous [START_REF] Gaston | Global patterns in biodiversity[END_REF][START_REF] Hobson | Using stable isotopes to determine seabird trophic relationships[END_REF] species during the breeding season. However, Hg concentrations measured in pigeon guillemots and Kittlitz's murrelets were about six and ten times higher than in common and Brünnich's guillemots, reflecting a hotspot of Hg contamination in the Aleutian Islands [START_REF] Ackerman | Maternal transfer of contaminants in birds: mercury and selenium concentrations in parents and their eggs[END_REF], where tufted puffins were also sampled. Those Hg concentrations in feathers are in accordance with previous works showing that pigeon guillemots breeding in the Pacific Ocean (Western North America) are facing potential toxicological risk linked to higher Hg concentrations in this region [START_REF] Ackerman | Maternal transfer of contaminants in birds: mercury and selenium concentrations in parents and their eggs[END_REF]; Arctic Monitoring and Assessment Programme (AMAP), 2018).

The larid family showed the highest Hg concentrations in body feathers as well as the highest intra-and interspecific variations, with values ranging from 0.89 ± 0.15 μg/g dw (Arctic tern, Kim et al., 1996aKim et al., , 1996b) ) to 11.66 ± 6.52 μg/g dw (ivory gull, [START_REF] Mallory | Mercury concentrations in feathers of marine birds in Arctic Canada[END_REF] (See Table 2, Figs. 6 and7). Interestingly, the lowest values were measured in Arctic terns breeding in Russia, while this species is reaching toxicological concerns in the Canadian Arctic, where it faces both high Hg concentrations (in both eggs and liver) and decreasing population trends [START_REF] Provencher | Mercury and marine birds in Arctic Canada: effects, current trends, and why we should be paying closer attention[END_REF], Akearok et al., 2010). In addition, the highest Hg concentrations were measured in ivory gulls breeding in the Canadian Arctic, while the lowest values for this species were measured in birds from Svalbard. Again, these results are consistent with Hg spatial trends highlighted from the study of other seabird tissues [START_REF] Provencher | Mercury and marine birds in Arctic Canada: effects, current trends, and why we should be paying closer attention[END_REF] or other species (Arctic Monitoring and Assessment Programme (AMAP), 2018), showing that the Canadian Arctic marine biota presents higher Hg contamination compared to other Arctic regions. High Hg concentrations measured in blacklegged kittiwakes, ivory gulls, glaucous, glaucous-winged and herring gulls are in accordance with their mostly piscivorous diet (opportunistic diet, from young to older fish, see [START_REF] Braune | Temporal trends of mercury in eggs of five sympatrically breeding seabird species in the Canadian Arctic 15[END_REF][START_REF] Burgess | Mercury trends in herring gull (Larus argentatus) eggs from Atlantic Canada, 1972-2008: temporal change or dietary shift?[END_REF][START_REF] Hobson | A Stable Isotope (δ 13 C, δ 15 N) Model for the North Water Food Web: Implications for Evaluating Trophodynamics and the Flow of Energy and Contaminants[END_REF][START_REF] Hobson | Using stable isotopes to determine seabird trophic relationships[END_REF] for a review) and with previous studies focused on bird eggs and liver [START_REF] Provencher | Mercury and marine birds in Arctic Canada: effects, current trends, and why we should be paying closer attention[END_REF].

For the other seabird families, data are much more limited. Hg concentrations in body feathers were investigated only once in hydrobatids, including the study of fork-tailed storm-petrels breeding in the Aleutian Islands, for which the molting pattern is unclear (see Annex 1, but see Harris, 1974) and exhibited the highest Hg concentrations (6.70 ± 1.63 μg/g dw; [START_REF] Kaler | Mercury concentrations in breast feathers of three upper trophic level marine predators from the western Aleutian Islands[END_REF], close to concentrations observed in some larids. This species mostly feeds on relatively low trophic level prey (amphipods, small fish or cephalopods - [START_REF] Hobson | Using stable isotopes to determine seabird trophic relationships[END_REF]), and like pigeon guillemots and Kittlitz's murrelet, might be exposed to higher Hg concentrations in the Aleutian Islands. Similarly, stercorariids were barely investigated, with feather Hg measurements in long-tailed and parasitic jaegers breeding in Russia only. As these species have two molts per year, we suggest that body feathers represent Hg exposure during the breeding period, as for most of alcid and larid species. Long-tailed and parasitic jaegers showed Hg concentrations of 1.95 ± 0.54 and 1.84 μg/g dw, respectively (Kim et al., 1996a(Kim et al., , 1996b)). The former species preferentially feeds on lemmings during the breeding season (see [START_REF] Gilg | Trans-equatorial migration routes, staging sites and wintering areas of a high-arctic avian predator: the long-tailed skua (Stercorarius longicaudus)[END_REF] for a review) while the latter mostly consumes robbed fishes caught by other seabirds [START_REF] Davis | Food availability affects adult survival as well as breeding success of parasitic jaegers[END_REF]. Their Hg concentrations, close to the ones of Sabine's gulls (also having two molts per yearsee Annex 1) from the same region and also feeding on small fish, suggests that these jaeger populations also feed on intermediate trophic levels (see Figs. 6 and7). [START_REF] Eisler | Mercury hazards to fish, wildlife and invertebrates: a synoptic review[END_REF] (see also [START_REF] Burger | Risk, mercury levels, and birds: relating adverse laboratory effects to field biomonitoring[END_REF] proposed a toxicity threshold in feathers of 5 μg/g dw. Here, all of the anatids were below this limit. In the case of alcids and larids however, bird vulnerability depended on their breeding regions. Brünnich's and common guillemots from Norway, little auks from East Greenland and tufted puffin from Aleutian Islands were below the toxicity threshold. In Kittlitz's murrelets, most of the measured Hg concentrations were below the threshold, except for the population breeding in the Adak Island. For the pigeon guillemot, the Alaska population was below the threshold, while all the colonies from the Aleutian Islands were above. For larids, Hg concentrations of black-legged kittiwakes, Arctic tern, glaucous-winged and Sabine's gull were not of concern, while Hg concentrations of herring and glaucous gulls from Russia, and ivory gull from the Canadian Arctic, were exceeding the threshold. Finally, the fork-tailed storm-petrel from the Aleutian Islands showed Hg concentrations above this toxicity threshold. Overall, this suggests that some species and/or areas need to be carefully monitored to follow any trend in Hg contaminations and therefore permanent toxicity risks for these populations.

Flight feathers provide complementary information to other feathers, but have only been used in three studies within the Arctic [START_REF] Kenney | Mercury concentrations in multiple tissues of Kittlitz's murrelets (Brachyramphus brevirostris)[END_REF]Kim et al., 1996b;[START_REF] Mallory | Mercury concentrations in feathers of marine birds in Arctic Canada[END_REF].

While one of these studies sampled primary 1 or primary 3 only [START_REF] Mallory | Mercury concentrations in feathers of marine birds in Arctic Canada[END_REF], another focused on primary 5 (Kim et al., 1996b), and secondary feathers [START_REF] Kenney | Mercury concentrations in multiple tissues of Kittlitz's murrelets (Brachyramphus brevirostris)[END_REF]. This makes comparisons difficult as those feathers do not molt at the same time.

Nevertheless, a similar trophic/spatial pattern than in body feathers can be observed in primary feathers. The lowest Hg concentrations were found in anatids (0.59 ± 0.21 μg/g dw and 0.70 ± 0.20 μg/g dw respectively for common eiders of the Canadian Arctic; [START_REF] Mallory | Mercury concentrations in feathers of marine birds in Arctic Canada 29[END_REF]; and for long-tailed ducks in Russia; Kim et al., 1996aKim et al., , 1996b) and the highest concentrations were observed in larids, with ivory gulls being the most contaminated species (15.79 ± 14.13 μg/g dw; [START_REF] Mallory | Mercury concentrations in feathers of marine birds in Arctic Canada[END_REF]. Brünnich's guillemots and northern fulmars had intermediate Hg concentrations (1.94 ± 0.63 and 2.71 ± 0.72 μg/g dw, respectively; [START_REF] Mallory | Mercury concentrations in feathers of marine birds in Arctic Canada[END_REF]. Secondary feathers have only been used for the Kittlitz's murrelet breeding on the Aleutian Islands, with the highest Hg concentration being 37.18 μg/g dw [START_REF] Kenney | Mercury concentrations in multiple tissues of Kittlitz's murrelets (Brachyramphus brevirostris)[END_REF]. This unique value is in agreement with the Hg concentrations measured in Kittlitz's murrelet body feathers from the Aleutian Islands. However, as this type of feather has not been used in any other study, the comparison of its Hg concentration with other feathers remains uncertain.

Hg contamination of Arctic seabirds during the non-breeding period

As illustrated above through blood and body feather measurements, the breeding time is the most studied period in Arctic seabird Hg monitoring. However, investigations covering their entire annual cycle, and thus both the breeding and non-breeding periods, are important in order to have a complete understanding of seabird exposure to Hg and of the associated risks, both in the Arctic and outside of the Arctic. Indeed, most seabirds breeding in the Arctic migrate southwards to spend the non-breeding time outside the Arctic [START_REF] Egevang | Tracking of Arctic terns Sterna paradisaea reveals longest animal migration[END_REF][START_REF] Gilg | Trans-equatorial migration routes, staging sites and wintering areas of a high-arctic avian predator: the long-tailed skua (Stercorarius longicaudus)[END_REF]. Previous studies used bird carcasses legally shot or beached along the coasts [START_REF] Bond | Trace element concentrations in harvested auks from Newfoundland: toxicological risk of a traditional hunt[END_REF][START_REF] Fort | Mercury in wintering seabirds, an aggravating factor to winter wrecks?[END_REF] to get information for this specific period.

However, for obvious ethical reasons or because stranded dead birds could show a bias in their Hg concentrations (e.g. starvation might affect Hg concentrations of internal tissues, [START_REF] Fort | Mercury in wintering seabirds, an aggravating factor to winter wrecks?[END_REF], an alternative solution is required. Seabird bycatch could provide opportunities to collect unbiased bird carcasses but would restrict samples to diving and piscivorous species and has never been used or validated until now. In that context, analysis of feathers appears as a useful and non-lethal approach to obtain information about bird non-breeding contamination, by the use of 1) head feathers for species molting twice a year, or 2) body feather for species molting once a year only. In this latter case, body feathers integrate information about Hg accumulated over the year and extraction of the non-breeding information should be performed. As proposed for the clapper rails (Rallus longirostris obsoletus) by [START_REF] Ackerman | Does mercury contamination reduce body condition of endangered California clapper rails?[END_REF], it could be relevant to use published equations to predict Hg concentrations in different seabird tissues (i.e. head and body feathers, blood) and thus obtain information for specific seasons.

Head feathers have been used in only three studies focused on little auks from East Greenland to assess Hg contamination during the nonbreeding period (Table 4), with values ranging from 2.27 ± 0.41 to 3.99 ± 1.96 μg/g dw [START_REF] Amélineau | Arctic climate change and pollution impact little auk foraging and fitness across a decade[END_REF][START_REF] Fort | Does temporal variation of mercury levels in Arctic seabirds reflect changes in global environmental contamination, or a modification of Arctic marine food web functioning?[END_REF][START_REF] Fort | Spatial ecotoxicology: migratory arctic seabirds are exposed to mercury contamination while overwintering in the Northwest Atlantic[END_REF].

These studies showed that non-breeding (head feathers) concentrations were significantly higher than breeding (body feathers) ones and suggested a higher exposure to Hg during the non-breeding period [START_REF] Fort | Spatial ecotoxicology: migratory arctic seabirds are exposed to mercury contamination while overwintering in the Northwest Atlantic[END_REF]. These values are below the 5 μg/g toxicity threshold proposed by [START_REF] Eisler | Mercury hazards to fish, wildlife and invertebrates: a synoptic review[END_REF]. A long-term study of the same population did not find a link between Hg concentrations and adult survival [START_REF] Amélineau | Arctic climate change and pollution impact little auk foraging and fitness across a decade[END_REF]. Even though this method has been scarcely used in the Arctic, other studies combining carbon and nitrogen stable isotope analyses together with Hg measurements (both in feathers and/or in blood), demonstrated important seasonal variations in Hg contamination in Double-crested Cormorants (Phalacrocorax auratus) [START_REF] Lavoie | Contamination of mercury during the wintering period influences concentrations at breeding sites in two migratory piscivorous birds[END_REF][START_REF] Ofukany | Connecting breeding and wintering habitats of migratory piscivorous birds: implications for tracking contaminants (Hg) using multiple stable isotopes[END_REF], Caspian terns (Hydroprogne caspia) [START_REF] Lavoie | Contamination of mercury during the wintering period influences concentrations at breeding sites in two migratory piscivorous birds[END_REF] and common terns (Sterna hirundo) [START_REF] Nisbet | Use of stable isotopes to investigate individual differences in diets and mercury exposures among common terns Sterna hirundo in breeding and wintering grounds[END_REF]. This highlights the importance to further study such seasonal variations in Hg exposure, which could be performed by the analysis of feathers.

Chicks as relevant stage for assessing Hg local contamination

Chicks, through measurements in blood, down and fully-grown feathers, can provide valuable information about pre-breeding and local Hg contamination (see [START_REF] Bond | Nutrient allocation for egg production in six Atlantic seabirds[END_REF] for the eggs). In the case of capital breeders (i.e. allocation of stored nutrients to egg formation) [START_REF] Akearok | Inter-and intra-clutch variation in egg mercury levels in marine bird species from the Canadian Arctic[END_REF], Hg accumulated by females during the late migration and egg formation is transferred to the eggs (Burger et al., 2008b). In the case of income breeders (i.e. allocation of local nutrient to egg formation), eggs represent female dietary Hg intakes during the egg formation only [START_REF] Bond | Nutrient allocation for egg production in six Atlantic seabirds[END_REF]. Several species (e.g. Atlantic puffin or razorbill) have an intermediate strategy [START_REF] Bond | Nutrient allocation for egg production in six Atlantic seabirds[END_REF]. As the down is grown into the egg before its hatch, Hg concentrations in eggs and chick down are correlated [START_REF] Furness | Seabirds as monitors of the marine environment[END_REF][START_REF] Stewart | Influence of species, age and diet on mercury concentrations in Shetland seabirds[END_REF]. Hence, down was proposed as an alternative to egg collection [START_REF] Monteiro | Seabirds as Monitors of Mercury in the Marine Environment[END_REF], as it can be less destructive to assess Hg contamination in declining species (such as the ivory gull). For conservation purpose, eggshells could also be a useful non-lethal tissue to monitor Hg concentrations [START_REF] Peterson | A critical evaluation of the utility of eggshells for estimating mercury concentrations in avian eggs: mercury in eggshells[END_REF].

During chick growth, the down is replaced by feathers, which thus integrate Hg from the chick diet. Therefore, chick feathers are useful indicators of the local Hg contamination during the chick rearing period [START_REF] Blévin | Wide range of mercury contamination in chicks of Southern Ocean seabirds[END_REF][START_REF] Furness | Seabirds as monitors of the marine environment[END_REF]. Indeed, most adults feed their chicks with relatively local food (except in a few species such as for instance northern fulmars which can travel several hundreds of kilometers to find their prey [START_REF] Weimerskirch | Nest attendance and foraging movements of northern fulmars rearing chicks at Bjornoya Barents Sea[END_REF]). Unlike eggs, chick feathers and blood have been scarcely studied in the Arctic [START_REF] Kaler | Mercury concentrations in breast feathers of three upper trophic level marine predators from the western Aleutian Islands, Alaska[END_REF][START_REF] Tartu | Mercury exposure, stress and prolactin secretion in an Arctic seabird: an experimental study[END_REF]Wenzel and Gabrielsen, 1995). Chick feathers constitute a good alternative to adult feathers to assess Hg local contamination [START_REF] Blévin | Wide range of mercury contamination in chicks of Southern Ocean seabirds[END_REF][START_REF] Monteiro | Seabirds as Monitors of Mercury in the Marine Environment[END_REF], with the advantage to integrate, in most cases, the local Hg contamination only (see above) while adult body feathers can integrate Hg exposure over much larger geographical scales, especially in species molting once a year. Finally, chick blood informs about recent intakes and local contamination only and presents the same advantages than fully-grown feathers. However, collecting blood in growing chicks could be more challenging and stressful for the bird than collecting feathers or down.

Future direction: spatial ecotoxicology to link seabird

Blood and feathers thus appear as important tissues for the monitoring of seabird Hg contamination and its temporal variations along their whole biological cycle. However, to further comprehend the vulnerability of these species to Hg marine contamination, it is essential to understand where individuals, populations or species get contaminated. Indeed, seabirds can use contrasting feeding areas, both at small spatial scale over a season and large scale when migrating thousands of kilometers between their breeding, molting and wintering grounds. Therefore, they potentially experience various levels of Hg environmental contamination (e.g. [START_REF] Leat | Influence of wintering area on persistent organic pollutants in a breeding migratory seabird[END_REF]. Different tools exist to track movements in Arctic seabirds. For instance, miniaturized electronic devices (e.g. GLS, GPS, Argos) are used to track large scale movements of birds over days, months or years and can be combined to Hg measurements in blood and feathers to highlight the role played by specific regions on their contamination [START_REF] Fort | Spatial ecotoxicology: migratory arctic seabirds are exposed to mercury contamination while overwintering in the Northwest Atlantic[END_REF]. Furthermore, Hg isotopes have been widely used in the last decades as a new and powerful perspective to explore the cycle of this element [START_REF] Blum | Mercury isotopes in earth and environmental sciences[END_REF] and could thus be used to track the trophic and spatial origins of Hg in polar seabirds [START_REF] Renedo | Identification of sources and bioaccumulation pathways of MeHg in subantarctic penguins: a stable isotopic investigation[END_REF]. Hg has seven naturally occurring stable isotopes that undergo both mass-dependent fractionation (MDF) and mass-independent fractionation (MIF), both related to distinct Hg isotopic ratios.

Hg MDF (normally reported as ẟ 202 Hg) is induced during physicochemical reactions including environmental processes such as volatilization, redox transformations, methylation and demethylation, photochemical reactions and biological processes [START_REF] Kritee | Mass dependent stable isotope fractionation of mercury during mer mediated microbial degradation of monomethylmercury[END_REF][START_REF] Kritee | Mercury stable isotope fractionation during reduction of Hg(II) to Hg(0) by mercury resistant microorganisms[END_REF][START_REF] Perrot | Identical Hg isotope mass dependent fractionation signature during methylation by sulfatereducing bacteria in sulfate and sulfate-free environment[END_REF][START_REF] Rodríguez-González | Species-specific stable isotope fractionation of mercury during Hg(II) methylation by an anaerobic bacteria (Desulfobulbus propionicus) under dark conditions[END_REF][START_REF] Zheng | Mercury isotope fractionation during volatilization of Hg(0) from solution into the gas phase[END_REF]. Conversely, Hg MIF is essentially attributed to the photochemical reduction of inorganic Hg and photodemethylation of MeHg in aquatic systems before its incorporation into the food web [START_REF] Bergquist | Mass-dependent and -independent fractionation of Hg isotopes by photoreduction in aquatic systems[END_REF][START_REF] Zheng | Isotope fractionation of mercury during its photochemical reduction by low-molecular-weight organic compounds[END_REF]. These two processes cause a significant "anomaly" in the fractionation of odd Hg isotopes (reported as Δ 199 Hg and Δ 201 Hg) which represents the deviation from the theoretical MDF. Further, as Hg MIF is not produced during biological processes [START_REF] Kritee | Mass dependent stable isotope fractionation of mercury during mer mediated microbial degradation of monomethylmercury[END_REF][START_REF] Kritee | Mercury stable isotope fractionation during reduction of Hg(II) to Hg(0) by mercury resistant microorganisms[END_REF], its signature is conserved along the food webs. Therefore, the measurement of Hg MIF magnitudes and ratios in the tissues of top predators permits to trace Hg photochemical conditions in their foraging habitats [START_REF] Masbou | Hg stable isotope variations in marine top predators of the western Arctic Ocean[END_REF][START_REF] Perrot | Natural Hg isotopic composition of different Hg compounds in mammal tissues as a proxy for in vivo breakdown of toxic methylmercury[END_REF][START_REF] Renedo | Identification of sources and bioaccumulation pathways of MeHg in subantarctic penguins: a stable isotopic investigation[END_REF]. Since seabirds forage in diverse locations at sea, both in the horizontal and vertical scales, their use for Hg isotopic investigations present important advantages for the investigation of Hg sources and its associated geochemical processes in the ocean [START_REF] Renedo | Identification of sources and bioaccumulation pathways of MeHg in subantarctic penguins: a stable isotopic investigation[END_REF]. In the Arctic, [START_REF] Point | Methylmercury photodegradation influenced by sea-ice cover in Arctic marine ecosystems[END_REF] were pioneers on the use of avian samples (eggs) as bioindicators for Hg isotopic analyses.

These authors revealed the influence of ice cover on Hg marine photochemistry by the differences of Hg odd-MIF signatures between ice-covered and non-ice-covered oceanic areas of the Alaskan Arctic Ocean, using Brünnich's and common guillemot as bioindicators.

Likewise, another study on seabird eggs from these species identified variations of Hg isotopic signatures between coastal and open ocean environments attributed to both different sources and processes (photochemistry) between these two reservoirs in the Alaskan region [START_REF] Day | Mercury stable isotopes in seabird eggs reflect a gradient from terrestrial geogenic to oceanic mercury reservoirs[END_REF]. In the Southern Ocean, Hg isotopic signatures in blood samples of subantarctic adult penguins also permitted to illustrate different MeHg biogeochemical characteristics across inshore-offshore marine compartments depending on specific foraging behaviour variability within a same ecosystem [START_REF] Renedo | Identification of sources and bioaccumulation pathways of MeHg in subantarctic penguins: a stable isotopic investigation[END_REF]. Significant latitudinal variations of Hg isotopic signatures have also been observed in seabird tissues across distant colonies of the Southern Ocean (Renedo et al., submitted). These observations indicate that both specific foraging habitats and latitudinal movements of seabirds highly determine their exposure to distinct environmental MeHg sources in variable marine ecosystems.

Hg isotopic composition in seabirds has demonstrated to be a potent tool for the definition of MeHg sources and to highlight the variability of processes among the different marine compartments. Therefore, the use of Hg isotopic approaches in migratory seabirds, feather Hg isotopic signatures will reflect the integration of Hg from diverse sources during an entire year for species molting once a year. This integrative effect of adult feathers could be interesting for tracking whole annual Hg contamination, i.e. including the wintering areas.

Furthermore, analyses of different type of feather of species moulting twice a year such as the case of alcids, appears as a suitable approach to obtain information about both the breeding and non-breeding Hg contamination. Measurements of Hg isotopic composition in feathers of flying migratory seabirds could then open a new horizon for exploring Hg exposure pathways at their breeding sites in summer but also in large zones of the marine environment during their non-breeding period outside the Arctic. Finally, stable isotopes of carbon and nitrogen (respectively indicators of foraging habitat and trophic level), together with the use of Hg isotopes (proxies of Hg biogeochemical characteristics in each marine compartment), would enable to help elucidating the Hg exposure pathways of migratory seabirds during their whole annual cycle, both during their breeding and non-breeding periods.

Limitations

Although highly valuable to inform about seabird Hg contamination through the Arctic, the use of blood and feathers also shows some limitations. Even if seabirds have been used in ecotoxicology since decades, detailed information about their trophic and behavioral ecology is essential to properly interpret their exposure to the environmental contamination. Such information is nonetheless often missing or ignored. For instance, information about seabird diet and molting patterns, mostly during the non-breeding period, are still scarce in many species. The present paper reviewed this existing knowledge of Arctic seabird molting patterns (pre-and/or post-breeding) (Annex 1) and should help future investigations using feathers to track seabird Hg contamination. Furthermore, Hg measurements are not always performed under the same protocols (e.g. different sample preparations leading to contrasting units (dry vs wet weights)). Although correction factors exist, they add uncertainties in the data and complicate comparisons. Such potential bias could be easily avoided by the use of homogenized methods, ensuring comparability of Hg measurements between areas and species. Finally, spatial ecotoxicology approaches combining biologging with Hg analyses should be developed to track the spatial origin of Hg contamination. However, large scale movements such as migration could also be associated to changes in diet, possibly affecting Hg intakes. Although nitrogen stable isotopes can be used to investigate seabird trophic status, isotopic values cannot be directly compared to Hg measurements in feathers as they do not provide information for the same periods [START_REF] Bond | Relationships between stable isotopes and metal contaminants in feathers are spurious and biologically uninformative[END_REF]. Therefore, feathers cannot be corrected to take into account potential diet effects as we can do for blood samples.

Conclusion

Although largely neglected in comparison to internal tissues or eggs, feathers and blood are two complementary and important tissues allowing large spatio-temporal investigations of Hg contamination in Arctic seabirds during both the breeding and non-breeding periods. They also provide information about risks encountered by seabirds depending on their Arctic breeding site, their migratory movements and their wintering grounds, within or outside the Arctic. Further studies monitoring long-term and large scale Hg contamination and potential subsequent risks for Arctic seabirds are now necessary, and require large international collaborations and monitoring programmes such as those implemented in Canada (Braune et al., 2001, Northern Contaminants Program (Chételat and[START_REF] Braune | Toxicity of methylmercury injected into eggs of thick-billed murres and arctic terns[END_REF] Table 1. Total Hg concentrations measured in blood samples (whole blood μg/g dw mean ± SD or SE; red blood cell μg/g dw mean ± SD; sample size is given into bracket) for seabirds breeding in the Arctic. If sexes were differentiated, F for female or M for male is added. * wet weight converted to dry weight following a moisture content of 79.13% [START_REF] Eagles-Smith | Mercury correlations among six tissues for four waterbird species breeding in San Francisco Bay, California, USA[END_REF], a nmol/g to μg/g, b overall sample size=105.

Table 2. Total Hg concentrations measured in body feathers (BF) (mean ± SD or SE μg/g dw; sample size is given into bracket) for seabirds breeding in the Arctic. If sexes were differentiated, F for female or M for male is added. a: ppb to μg/g; b: fw. Table 3. Total Hg concentrations (mean ± SD μg/g dw; sample size is given into bracket) measured in flight feathers (a: primary or b: secondary) for seabirds breeding in the Arctic. Table 4. Total Hg concentrations measured in head feathers (HF) (mean ± SD μg/g dw, sample size is given in brackets) for seabirds breeding in the Arctic.

Annex 1: List of the 42 species referenced in the 101 articles who studied Hg contamination in seabirds breeding in the Arctic. For each species, pre or post breeding have been assessed.

Family

  ), Norway (SEAPOP (Anker-Nilssen et al., 2017)) or at the pan-Arctic scale (newly established ARCTOX program). Such initiatives are indeed essential in order to determine temporal and spatial trends, to define baseline and hotspots of Hg contamination, and to allow international actions (see the Minamata Convention, the Arctic Monitoring Assessment Program or the Global Mercury Assessment).

Fig. 1 .

 1 Fig. 1. Occurrence of tissues analysed for Hg in Arctic seabirds in the 101 reviewed articles. Some publications studied several tissues. Internal tissues comprise liver (n=38), kidneys (n=10), muscle (n=25), heart (n=1), bones (n=1), brain (n=4), gonads (n=1) and lungs (n=1).

  Feathers comprise body feathers (n=14), head feathers (n=3) and flight feathers (n=4).

Fig. 2 .

 2 Fig. 2. Occurrence of tissues analysed for Hg in Arctic seabirds in the 101 reviewed articles, by Arctic region. Some publications studied several tissues. Internal tissues comprise liver (n=38), kidneys (n=10), muscle (n=25), heart (n=1), bones (n=1), brain (n=4), gonads (n=1) and lungs (n=1). Others (excrements, n=2). Feathers comprise body feathers (n=14), head feathers (n=3) and flight feathers (n=4).

Fig. 3 .

 3 Fig. 3. Spatial distribution of Hg concentrations measured in blood.

Fig. 4 .

 4 Fig. 4. Mean Hg concentrations (mean ± SD μg/g dw) measured in blood by species, in relation to bird diet during the breeding season.

Fig. 5 .

 5 Fig. 5. Schematic representation of Hg excretion from internal tissues and organs to body,

Fig. 6 .

 6 Fig. 6. Spatial distribution of Hg concentrations in body feathers.

Fig. 7 .

 7 Fig. 7. Mean Hg concentrations (mean ± SD μg/g dw) measured in body feathers, by species, in relation to bird diet during the breeding season.

Acknowledgments

This study is part of several research programs supported by the French Polar Institute (IPEV -Pgr. 388 ADACLIM), the French Agency for National Research (ILETOP project ANR-16-CE34-0005, MAMBA project ANR-16-TERC-0004), the French Arctic Initiative -CNRS (PARCS project), and the Mission pour l'Interdisciplinarité -CNRS (Changements en Sibérie project). CA is supported by a PhD fellowship from the French Ministry of higher education and research. The IUF (Institut Universitaire de France) is also acknowledged for its support to PB as a Senior Member.

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(1) (17) [START_REF] Amélineau | Arctic climate change and pollution impact little auk fraging and fitness across a decade 2[END_REF] (***)


Sílvia Mas

A Torro

L Fernández

N Bec

C Gongora

C Larroque

P Martineau

A De Juan

S Marco

MALDI imaging mass spectrometry and chemometric tools to discriminate highly similar colorectal cancer tissues

Keywords: MALDI imaging, tumor heterogeneity, chemometrics, multivariate analysis, colorectal cancer

Intratumour heterogeneity due to cancer cell clonal evolution and microenvironment composition and tumor differences due to genetic variations between patients suffering of the same cancer pathology play a crucial role in patient response to therapies. This study is oriented to show that matrix-assisted laser-desorption ionization-Mass spectrometry imaging (MALDI-MSI), combined with an advanced multivariate data processing pipeline can be used to discriminate subtle variations between highly similar colorectal tumors.

To this aim, experimental tumors reproducing the emergence of drug-resistant clones were generated in athymic mice using subcutaneous injection of different mixes of two isogenic cell lines, the irinotecan-resistant HCT116-SN50 (R) and its sibling human colon adenocarcinoma sensitive cell line HCT116 (S). Because irinotecan-resistant and irinotecan-sensitive are derived from the same original parental HCT116 cell line, their genetic characteristics and molecular compositions are closely related.

The multivariate data processing pipeline proposed relies on three steps: (a) multiset multivariate curve resolution (MCR) to separate biological contributions from background;

(b) multiset K-means segmentation using MCR scores of the biological contributions to separate between tumor and necrotic parts of the tissues; and (c) partial-least squares discriminant analysis (PLS-DA) applied to tumor pixel spectra to discriminate between R and S tumor populations. High levels of correct classification rates (0.85), sensitivity (0.92) and specificity (0.77) for the PLS-DA classification model were obtained. If previously labeled tissue is available, the multistep modeling strategy proposed constitutes a good approach for the identification and characterization of highly similar phenotypic tumor subpopulations that could be potentially applicable to any kind of cancer tissue that exhibits substantial heterogeneity.

Introduction

Colorectal cancer (CRC) is the third cause of cancer mortality worldwide, affecting men and women almost equally. Despite significant improvements in early cancer detection and treatment, about half of the patient will develop distant metastases (mCRC) associated with a 5-year survival rate for patients of less than 10 % [1]. The standard of care for mCRC includes surgery of the primary tumor, if still present, combined with chemotherapy based on Oxaliplatin, Irinotecan and 5-Fluorouracile administered in various combinations and an antibody-based chemotherapy. These treatments may induce regression of metastases and, in favorable cases, a secondary surgery of liver metastases.

Tumor heterogeneity is now recognized as a key driver in patient response to therapy and thus in clinical outcome. Whereas intertumor heterogeneity among patients has been identified for many years as an important factor explaining differences in patient response to therapeutic regimens, intratumor heterogeneity and its implication in resistance mechanisms has been only more recently recognized and addressed [START_REF] Dagogo-Jack | Tumour heterogeneity and resistance to cancer therapies[END_REF][START_REF] Mcgranahan | Clonal Heterogeneity and Tumor Evolution: Past, Present, and the Future[END_REF][START_REF] Jamal-Hanjani | Tracking the Evolution of Non-Small-Cell Lung Cancer[END_REF][START_REF] Nowell | The clonal evolution of tumor cell populations[END_REF][START_REF] Piotrowska | Heterogeneity Underlies the Emergence of EGFRT790 Wild-Type Clones Following Treatment of T790M-Positive Cancers with a Third-Generation EGFR Inhibitor[END_REF][START_REF] Diaz | The molecular evolution of acquired resistance to targeted EGFR blockade in colorectal cancers[END_REF]. Understanding and characterizing tumor heterogeneity is therefore a key factor to improve patient management and treatment.

To characterize these heterogeneities, a technique that maintains the spatial organization of cells but allows in depth analysis of their molecular content in eventually unknown molecules is needed. Matrix-assisted laser-desorption ionization-mass spectrometry imaging (MALDI-MSI) fulfills these constraints and several studies have indeed shown that this approach may characterize relevant tumor populations within cancer tissues [START_REF] Willems | Imaging mass spectrometry of myxoid sarcomas identifies proteins and lipids specific to tumour type and grade , and reveals biochemical intratumour heterogeneity §[END_REF][START_REF] Emrys | Multiple Statistical Analysis Techniques Corroborate Intratumor Heterogeneity in Imaging Mass Spectrometry Datasets of Myxofibrosarcoma[END_REF][START_REF] Balluff | De novo discovery of phenotypic intratumour heterogeneity using imaging mass spectrometry[END_REF]. In particular, because it relies on multivariate analysis of large-scale molecular signatures, MALDI-MSI has the potential to identify differences between histologically indistinguishable regions of a tissue, which are the basis of cancer phenotypes that drives tumor progression and ultimately determines which variant of cancer a patient will experience. In addition, coupled with other MS analytical techniques, the approach cannot only define signatures but also identify characteristic biomolecular ions to get information on the underlining mechanisms of cancer cell resistance in vivo and eventually derive new targeted-treatments. Moreover, no requirement for specific staining/labelling agents is needed as compared with histological analysis, thus permitting multiplex analysis of several molecules in the same tissue section. Finally, it allows the correlation of molecular information with traditional histology by maintaining the spatial localization information of the analytes during mass spectrometric measurement.

Traditional analysis of MALDI-MSI images has made only limited use of the big amount of information achieved with this kind of data. To attain the distribution of molecular phenotypes while demonstrating the significant spatial heterogeneity present in the molecular phenotype distribution, the use of an efficient multivariate data processing pipeline is vital. The data analysis workflow proposed in this work is applied to fifteen tissues of experimental colorectal cancer images with different degree of heterogeneity using a mixture of isogenic cells all derived from HCT116 human colon adenocarcinoma cells. Using mixtures of Irinotecan-sensitive (S) and resistant (R) cell lines presenting highly similar molecular phenotypes will accurately represent the clinical question of clonal evolution and emergence of resistant cancer cells during treatment [START_REF] Greaves | Clonal evolution in cancer[END_REF]. The strategy follows the three steps below: a) Multiset multivariate curve resolution (MCR) on the 15 images. Basic MS spectral signatures and related distribution maps of all components in MSI are recovered. This method allows segmenting components related to background signal contributions from biological components. However, biological components related to different tissue types (necrotic and tumoral parts) may overlap, and hence no hard separation between them could be achieved. Moreover, in this case, R and S cell lines cannot be easily separated by MCR due to highly similar MS signatures and/or unclear spatial pattern. b) Multiset K-means image segmentation analysis on the MCR scores (concentration profiles) of only biological contributions. In this step, a hard clustering method separates classes of tumor and necrotic tissues. However, this unsupervised clustering is not sufficient/powerful enough to distinguish between R and S tumors, and hence, a supervised discrimination method is needed. c) Partial-least squares discriminant analysis (PLS-DA) model on pixel spectra from tumoral clusters. Supervised classifier such PLS-DA using previous pixel labeling (classes R or S) will help to discriminate between irinotecan-resistant and irinotecan-sensitive cell lines even if only subtle differences among R and S are present.

The proposed approach is a method to find the spatial tumor heterogeneity based on MALDI-MSI measurements even in scenarios of highly similar cancer subpopulations.

Experimental

A model of tumor heterogeneity, using two human colon adenocarcinoma cell lines; one sensitive (HCT116) and another resistant (HCT116-SN50) to Irinotecan, was designed to examine the feasibility of the proposed strategy. The complete methodology and materials used are detailed in our recent paper [START_REF] Mas | Use of physiological information based on grayscale images to improve mass spectrometry imaging data analysis from biological tissues[END_REF]. Briefly, experimental tumors were generated in athymic mice by a subcutaneous injection of a mix of a resistant (R) and a sensitive (S) HCT116 cell lines at five ratios (100%S; 90%S; 50%S; 90%R; 100%R). Tumors were then collected, sliced, scanned with an Epson Perfection 4990 Photo Scanner and subsequently analyzed by a 4800 Plus MALDI TOF/TOF TM Analyzer. A total of 15 images corresponding to different tumor samples (corresponding to different mice) and replicates of slices of the same tumor were analyzed. Table 1 summarizes the description and image labelling.

TABLE 1

Data analysis

The data analysis workflow proposed follow the four steps below: These steps are described in detail in the following subsections.

Image preprocessing

To extract reliable conclusions and to retain maximum biological information from MSI data, it is necessary to choose appropriate preprocessing steps. We chose MALDIquant R package [START_REF] Gibb | Maldiquant: A versatile R package for the analysis of mass spectrometry data[END_REF] to perform almost all preprocessing data, which includes baseline correction, spectra smoothing, peak detection and spectra alignment. A matrix D (n,m) of dimension n equal to (x × y) pixels by m m/z values was generated per each image. Finally, a multiset structure containing all 15 images was built, concatenating the 15 individual matrices one on top of each other. For a more detailed information about the preprocessing steps and parameters, please refer to our recent publication about the same dataset [START_REF] Mas | Use of physiological information based on grayscale images to improve mass spectrometry imaging data analysis from biological tissues[END_REF].

MCR-ALS resolution of MSI multiset

The goal of the image resolution step by Multivariate Curve Resolution Alternating Least Squares (MCR-ALS) algorithm is the decomposition of the data set into the distribution maps (relative amounts or concentration) and pure spectra of the signal contributions present in the imaged sample [START_REF] Jaumot | Potential use of multivariate curve resolution for the analysis of mass spectrometry images[END_REF][START_REF] Bedia | Analysis of multiple mass spectrometry images from different Phaseolus vulgaris samples by multivariate curve resolution[END_REF][START_REF] Piqueras | Combining multiset resolution and segmentation for hyperspectral image analysis of biological tissues[END_REF]. In this study, all 15 images were analyzed simultaneously in a single multiset structure. This multiset was obtained by appending the where the matrix C aug , is a column-wise matrix formed by as many submatrices C i (matrix of the relative amounts or concentration of n components) as images in the multiset and S T is a single matrix of pure spectra of n components, valid for all the images in the multiset.

MCR-ALS estimates iteratively the matrices C aug and S T under the control of constraints [START_REF] Mas | Use of physiological information based on grayscale images to improve mass spectrometry imaging data analysis from biological tissues[END_REF].

. In this study, the most common constraints in image resolution, such as non-negativity and normalization, were used. As a particularity, physiological information based on scanned images were coded as local rank constraints and were oriented to extract much more reliable MS signatures and distribution maps of the different tissue types present in the samples. Further information on the application of this local rank constraint can be found in [START_REF] Mas | Use of physiological information based on grayscale images to improve mass spectrometry imaging data analysis from biological tissues[END_REF]. Indeed, more details about the MCR-ALS method are given in [START_REF] De Juan | Two-Way Data Analysis: Multivariate Curve Resolution -Iterative Resolution Methods[END_REF][START_REF] Jaumot | MCR-ALS GUI 2.0: New features and applications[END_REF][START_REF] Tauler | Multivariate curve resolution applied to second order data[END_REF] and a GUI to use the algorithm is freely available at http://mcrals.info. MCR-ALS results, i.e., distribution maps (C matrix) and pure spectra (S T matrix) may be further used to obtain additional information. In this work, distribution maps were used as starting information in K-means that allows a component selection of the profiles to be included in the segmentation process, i.e. resolved components linked clearly to background signal contributions are discarded and only those linked to biological contributions are retained for segmentation.

K-means multiset segmentation

The main goal of image segmentation is to partition the images into pixel groups built according to their pixel similarity in an unsupervised way [START_REF] De Juan | Two-Way Data Analysis: Multivariate Curve Resolution -Iterative Resolution Methods[END_REF]. In this work, K-means was used as a segmentation approach that tries to partition the dataset into K pre-defined clusters where each pixel belongs to only one group.

K-means analysis has been applied to the multiset structure containing all 15 images. MCR scores (concentration profiles) of biological contributions were used as starting information because MCR scores are compressed and noise-filtered and keep only biological relevant information on pixel composition, which makes them more suitable than raw spectra for segmentation purposes. It has been proved that dimensionality reduction prior to K-means clustering can be beneficial for the quality of the clustering [START_REF] Liu | Reducing microarray data via nonnegative matrix factorization for visualization and clustering analysis[END_REF].

Based on the comparison between segmentation map and grayscale images, we can determine which pixels are localized in each region and classify the corresponding spectra into categories (tumoral or necrotic tissues). Tumoral spectra will be used for further supervised classifications purposes.

Supervised Classification

Supervised learning methods are widely used in tissue MSI based-research when prior examples regarding píxel labeling in tissue samples is available [START_REF] Zhang | Machine learning techniques for mass spectrometry imaging data analysis and applications[END_REF]. In this work, Partial

Least Squares Discriminant Analysis (PLS-DA) was used as supervised classification method to predict the class (R or S tumor type) of unknown samples according to their mass spectrum (MS pixels) [START_REF] Liu | Reducing microarray data via nonnegative matrix factorization for visualization and clustering analysis[END_REF]. The use of a supervised methodology responds to the fact that individual MS signatures of R and S cell subpopulations are not sufficiently different to be properly separated by the sole use of unsupervised methods [START_REF] Willems | Imaging mass spectrometry of myxoid sarcomas identifies proteins and lipids specific to tumour type and grade , and reveals biochemical intratumour heterogeneity §[END_REF]. . PLS-DA is a discriminant technique based on PLS regression that builds a model using an appropriate set of latent variables to maximize the covariance between X, the MS pixels, and Y, a vector containing the categorical classes R and S, numerically coded. Since PLS-DA is very prone to provide overoptimistic results even in cross-validation [START_REF] Rodríguez-Pérez | Overoptimism in cross-validation when using partial least squares-discriminant analysis for omics data: a systematic study[END_REF], the use of permutation tests is also applied to investigate the statistical significance of the classifier accuracy [START_REF] Ojala | Permutation Tests for Studying Classi er Performance[END_REF].

In our case, labelling can only be done on images with 100% of either R or S cell types.

Mixed images cannot be labelled since visually type R tumor cannot be differentiated from tumor type S. Therefore, from all 15 images only 8 images were labelled, please refer to The classification rate is taken as a criterion of goodness for the developed model. The number of LV was selected as the one that provides a maximum CR in cross-validation.

However, we applied the Parsimony principle: the inclusion of one more LV should represent a gain of more than 1 % in the CR value to be considered.

To asses the quality of the model, classification rate (accuracy), sensitivity (Se), defined as proportion of samples correctly classified within a particular class, selectivity (Sp), defined as proportion of samples correctly classified outside a particular class, and area under Receiver Operator Characteristic (AUROC), which is equal to 1 for perfect classification accross all possible values of the threshold. [START_REF] Abdi | Signal Detection Theory ( SDT )[END_REF].

A permutation test has been used to assess whether the specific classification of the MS pixels in the two designed groups (R or S) is significantly better than random classification in two arbitrary groups. In this stduy, 6000 permutations have been done to define the In order to understand the molecular ions that contribute to the discrimination between both classes (R and S tumor classes), the Variable Importance in Projection (VIP) has been used [START_REF] Wold | PLS: Partial Least Squares Projections to Latent Structures[END_REF].

All data treatment (resolution, segmentation and classification methods) has been performed in Matlab (The MathWorks Inc.). The PLS-DA method has been applied using in-house routines, partly based on the PLS Toolbox (Eigenvector Research Inc.).

Results and discussion

Selection of tumoral pixels for further discrimination purposes.

Results from the proposed combination of MCR-ALS resolution with K-means segmentation in order to select the tumor spectra pixels of the tissues, that will be used for further discrimination tasks, could be found in our recent publication about the same dataset [START_REF] Mas | Use of physiological information based on grayscale images to improve mass spectrometry imaging data analysis from biological tissues[END_REF].

As an example, Figure 1a shows a schematic illustration of the proposed strategy for the image 100R1b. Firstly, basic description of pure contributions of the tissue is achieved by MCR-ALS. Background and biological (tumoral and necrotic) contributions could be clearly differentiated. Background signals present noise spectral signatures while biological components present chemically meaningful signatures. However, it was seen that distribution maps present overlaps among necrotic and tumoral contributions; i.e. no hard separation of these contributions is obtained and, due to heterogeneity, more than one contribution is needed to describe these two kinds of tissues [START_REF] Willems | Imaging mass spectrometry of myxoid sarcomas identifies proteins and lipids specific to tumour type and grade , and reveals biochemical intratumour heterogeneity §[END_REF]. Moreover, MCR results, i.e distribution maps (concentration profiles) and pure MS spectra (figure not shown), were not conclusive enough to separate R and S cell populations. Secondly, MCR concentration profiles of biological contributions were used as input information for K-means segmentation. In this case, hard separation of necrotic and tumoral pixels is achieved. Two Clusters (green and orange) correspond to the tumor parts, they have the same spatial distribution of the dark grey regions in the scanned image. Similarly, two clusters (blue and brown) were associated with the necrotic parts. It is worth to mention that the information coming from segmentation maps is richer than that provided by the grayscale images because it reveals heterogeneity within necrotic and tumor tissues and is based on chemical information (from MS measurement) rather than simple color intensity. All the pixels could be assigned to any of the tissue types (tumoral or necrotic), as opposed to grayscale images, where the assignment of a pixel is just based on the grayscale level and hence some pixels cannot be straightforwardly assigned to any tissue type. Now, we can determine which pixels are localized to each region and classify the corresponding spectra into categories (tumoral or necrotic tissues). However, this plain unsupervised clustering is not enough to distinguish between R and S tumors, and hence a dedicated method for discrimination is required. Therefore, tumoral spectra selected from the clusters associated with tumoral parts by K-means (see figure 1b) will be used as starting information in order to discriminate between R and S cell populations.

PLS-DA classification method. Discrimination between R and S populations

In supplementary material, Figure S1a shows the plots of the mean of CR and their confidence interval calculated from the binomial distribution in cross validation as a function of the increasing number of latent variables. The model seems to show a plateau from 5 to 10 components and thus appears to be rather stable. Therefore, the number of LVs chose was 5 since inclusion of one more dimension did not represent a gain of more than 1% in the CR value.

Once the optimal number of LV has been selected, calculation the PLS-DA model on the calibration samples has been carried out. This calculation was performed selecting 5 LV and the same cross validation groups for internal validation. In Table S1 Once the model is built and validated, it has been used to predict the distribution of R and S class pixels in the images coming from xenografts where both R and S cell lines in different proportions were inoculated. Figure 3 shows the pixel class assignment in the analyzed samples. As can be seen, pixels of the two cell lines are detected in tumors where both were inoculated. From the analyzed samples, no morphological distribution patterns can be associated with the growth of the two cell lines, i.e., both cell lines grow similarly and in a mixed way in the tissue analyzed. Qualitatively, it seems that both cell lines R and S present ratios in the tumor sections analyzed similar to the ratio inoculated, except for sample 90S8.

FIGURE 3

Indeed, this observation could be confirmed when quantitative ratios of R and S tumors were calculated by using the percentage of pixels predicted for each class in every sample over the total number of pixels considered to be tumor. An estimation of the percentage of R tumor populations is presented in Table 2.

TABLE 2

From Table 2, a satisfactory estimate of the percentage of R tumor populations can be observed except for the image 90S8. Without considering this image, a correlation of 0.93 between real % of R and estimated % of R was observed. This indicates that the % of the different cell lines found by PLS-DA in the analyzed images is closely correlated with the one in the inoculated samples. When grafted independently, the growth rate of the R and Scell lines are similar with a doubling time of 8.6 +/-0.6 and 9.0 +/-0.4 days respectively.

The similarity in the predicted proportion of R cells between injection and resection suggests that there is no competition for growth between the two cell lines in vivo. The deviations in the % of cell lines predicted can be explained by biological variability between mice, but also because we analyzed a single tumor slice that cannot represent the composition of the full tumor. This is particularly evident in sample 90S8, where the results linked to the tissue section analyzed are far from the cell line R/S ratio expected.

As a final summary, the combination of MSI and a powerful protocol combining consecutive modeling steps of image resolutionsegmentationdiscrimination has proven to be efficient to distinguish the highly similar Rand irinotecan-sensitive tumor cell lines.

Conclusions

Combination of image resolution, segmentation and classification multivariate analysis method results in the capacity to much better discriminate highly similar tumors subpopulations (irinotecan-resistant (R) and irinotecan-sensitive (S)) in heterogenous cancer tissues investigated by MALDI-MSI.

In the present model of irinotecan-resistant human adenocarcinoma cells, discriminating differences in the intensities of the peaks of masses around 750-800 and 520-525 have been detected. These masses could be assigned to glycosyldiradylglycerols, glycerophosphocholines or glycerophosphoglycerols, and to oxidized glycerophospholipids or fatty acyl glycosides, respectively. Furthermore, the results obtained support the idea that the different tumor cell lines (R and S) present the same proliferation behavior in vivo, as shown by the preservation of ratios of R and S cells during tumor growth.

The conclusions reached in this work promote further biological research in order to evaluate the discriminant potential of this approach in case of bigger data sets showing a large variability among individuals. In particular, studies of patient samples are now required to more precisely characterize the type of heterogeneity that can be identified using this approach and the interest in patient monitoring during treatment [START_REF] Dagogo-Jack | Tumour heterogeneity and resistance to cancer therapies[END_REF][START_REF] Mcgranahan | Clonal Heterogeneity and Tumor Evolution: Past, Present, and the Future[END_REF]. In addition, a A systematic comparison with conventionally stained sections would be of interest to evaluate the potential of the proposed strategy as a complement to this routine approach.

Nevertheless, MALDI-MSI combined with the proposed data analysis protocol has been shown to be a valuable tool to investigate tumor heterogeneity even in scenarios of highly similar cancer subpopulations.

code 100% R a 1 100R1a 100% R b 1 100R1b 100% R c 1 100R1c 100% R - 2 100R2 100% S a 1 100S3a 100% S b 1 100S3b 100% S c 1 100S3c 100% S - 2 100S4 90% R (10% S) - 1 90R5 90% R (10% S) - 2 90R6 90% S (10% R) - 1 90S7 90% S (10% R) - 2 90S8 90% S (10% R) - 3 90S9 50% S (50% R) - 1 50R10 50% S (50% R) - 2 50R11

  a) Image preprocessing b) Multiset MCR resolution on all images to recover basic spectral signatures and distribution maps of pure compounds contributions, allowing separation of tumor and necrotic contributions from background. c) Multiset K-means image segmentation analysis on the MCR scores (concentration profiles) of only biological contributions, to identify tumor or necrotic parts, permitting selection of tumor pixels for discrimination purposes. d) Use of supervised classification method to discriminate between irinotecanresistant and irinotecan-sensitive populations of tumor tissue.

  pixel MS matrix of the different MALDI images one on top of each other to form a column-wise augmented matrix, D aug = [D100R1a; D100R1b; D100R1c; D100R2… D50R11]. This column-wise augmented data matrix D aug can be decomposed using the bilinear model equation: D aug =C aug S T +E aug Equation 1

  classification paràmetresassociated with the arbitrary class models. Statistical significance of the PLS-DA model is then assessed by relating the value of the classification parameters obtained by the original data set to the distribution of them calculated with the permuted data sets. In this way, permutation test allows to estimate a p-value for the classification rate obtained with the real labels. The significance threshold is usually set to 0.05 as in most biologic applications. p-values smaller than 0.05 indicate that differences between the two classes are statistically significant.

2

 2 figure that the class threshold for the best classification of R class is ranged from 0.591 to

  Figure 1. (a) Graphical representation of the strategy used for PLS-DA-oriented pixel

Figure 2 .Figure 3 .

 23 Figure 2. Mean spectrum of pixels from images of R class (black), mean spectrum of the

table 1

 1 , which include mixtures of R and S tumors, in order to determine the spatial distribution of the tumors over the images.Within the calibration test, cross-validation performed by leaving one image of each class out was used to choose the optimal number of latent variables as well as to test the predictive performance of the model, according to the cross-validation table shown below (see TableS1in supplement material).

	to see which images correspond to 100% of one type of tumor. The calibration set
	comprises 3 images of 100% irinotecan-resistant (100R1a, 100Rab, 100R1c) from the
	same tumor and 3 images of 100% irinotecan-sensitive from the same tumor (100S3a,
	100S3b, 100S3c). External validation set includes the images of 100% R and 100% S

obtained from another grafted mouse but without replicates (100R2 and 100S4, respectively). Additionally, we have also applied the resultant predictive model to the remaining images

Table 1 .

 1 Percentage of both R and S cell lines in xenografts, replicate number of either the same or different tumors (mice) and code of the image sections analyzed.

	Percentage	Replicate of	Replicate	Image
	of cell	the same	number of
	lines	tumor	different tumors

Table 2 .

 2 Real vs. estimated % of R cell line in heterogenous tumor samples as predicted in the analyzed MS images by PLS-DA.

	Image	Real % of R	Estimated % of R
	90R5	90	79
	90R6	90	91
	90S7	10	14
	90S8	10	74
	90S9	10	8
	50R10	50	39
	50R11	50	76

Acknowledgements

This work is part of the BEST Postdoctoral Program, funded by the European Commission under Horizon 2020 Marie Skłodowska-Curie Actions COFUND scheme (Grant Agreement no. 712754) and by the Severo Ochoa program of the Spanish Ministry of Science and Competitiveness (Grant SEV-2014-0425 (2015-2019)). A.J. acknowledges financial support from the Catalan government through project 2017 SGR 753 and the Spanish government through project CTQ2015-66254-C2-2-P. We would like to acknowledge the Departament d'Universitats, Recerca i Societat de la Informació de la Generalitat de Catalunya (expedient 2017 SGR 1721); the Comissionat per a Universitats i Recerca del DIUE de la Generalitat de Catalunya; and the European Social Fund (ESF).

Additional financial support has been provided by the Institut de Bioenginyeria de Catalunya (IBEC). IBEC is a member of the CERCA Programme/Generalitat de Catalunya. This publication has been also funded with support from the French National Research Agency under the program "Investissements d'avenir" Grant Agreement LabEx MAbImprove: ANR-10-LABX-53. A. T. and P. M. acknowledge the support of the Fondation pour la Recherche Médicale. We thank the Experimental Histology Network of Montpellier for histology/immunohistology experiments (RHEM,http://www.rhem.cnrs.fr).

Conflict of interest

The authors report there are not conflicts of interest

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