domain: sde spi

text:
Morgane Derrien
email: morgane.derrien@uoh.cl

Laurent Jeanneau

Emilie Jardé

Jin Hur

Sunghwan Kim

Exploration of changes in the chemical composition of sedimentary organic matter and the underlying processes during biodegradation through advanced analytical techniques

Keywords: Sedimentary organic matter, Biodegradation, Molecular characterization, LDI FT-ICR MS, Biomarkers

come

Introduction

Sediments operate as sources and sinks of nutrients and pollutants in aquatic systems.

They also represent a large reservoir of organic matter (OM) from diverse sources (e.g., terrestrial, aquatic, estuarine, marine, etc.) and in various proportions according to the environment, region, and hydrology. Indeed, sedimentary OM is derived from aquatic material such as algae, bacteria, plankton, macrophytes, and nekton formed in situ, but also receives terrestrial OM such as soil, vascular plants, leaves, root exudates and anthropogenic OM such as soil OM, which is easily transported from the upstream catchment into rivers through hydrological processes, finally ending up in sediments [START_REF] Briand | Major Sources of Organic Matter in a Complex Coral Reef Lagoon: Identification from Isotopic Signatures (δ(13)C and δ(15)N)[END_REF][START_REF] Jeanneau | Molecular fingerprinting of particulate organic matter as a new tool for its source apportionment: changes along a headwater drainage in coarse, medium and fine particles as a function of rainfalls[END_REF][START_REF] Van Der Meij | On the role of hydrologic processes in soil and landscape evolution modeling: concepts, complications and partial solutions[END_REF]. Sediments are also a reactive compartment where diagenetic processes occur, inducing physical, chemical, and/or biological changes to the sedimentary OM [START_REF] Henrichs | Early diagenesis of organic matter in marine sediments: progress and perplexity[END_REF][START_REF] Kuznetsova | What are the current analytical approaches for sediment analysis related to the study of diagenesis? Highlights from 2010 to 2018[END_REF][START_REF] Meyers | Lacustrine organic geochemistry-an overview of indicators of organic matter sources and diagenesis in lake sediments[END_REF]. Among the diagenetic processes, biodegradation plays a key role in OM biogeochemistry as it is one of the main processes causing changes in its amount, composition, and properties in aquatic systems [START_REF] Moran | Carbon loss and optical property changes during long-term photochemical and biological degradation of estuarine dissolved organic matter[END_REF][START_REF] Arndt | Quantifying the degradation of organic matter in marine sediments: A review and synthesis[END_REF][START_REF] Sankar | Effect of photobiodegradation and biodegradation on the biogeochemical cycling of dissolved organic matter across diverse surface water bodies[END_REF]Derrien et al., 2019a).

OM biodegradation is based on the common preconception that OM is represented as a mix of recalcitrant materials usually associated with terrestrial origin and labile materials associated with aquatic OM [START_REF] Hansell | Optical properties of dissolved organic matter (DOM): Effects of biological and photolytic degradation[END_REF]. OM biodegradation is often oversimplified and/or restricted to preferential degradation of labile and/or low molecular weight (LMW) organic compounds leading to the rapid loss of them rather than the recalcitrant material like lignin and high molecular weight (HMW) organic compounds [START_REF] Curtis-Jackson | Characterization of low molecular weight dissolved organic nitrogen by liquid chromatography-electrospray ionization-mass spectrometry[END_REF][START_REF] Hach | Rapid microbial diversification of dissolved organic matter in oceanic surface waters leads to carbon sequestration[END_REF][START_REF] Hansell | Optical properties of dissolved organic matter (DOM): Effects of biological and photolytic degradation[END_REF][START_REF] Moran | Role of photoreactions in the formation of biologically labile compounds from dissolved organic matter[END_REF][START_REF] Ward | Marine microbial community responses related to wetland carbon mobilization in the coastal zone[END_REF]. However, since the early 2000s, new paradigms on the stability of terrestrial OM and more specifically on soil OM have been proposed [START_REF] Wershaw | Evaluation of conceptual models of natural organic matter (humus) from a consideration of the chemical and biochemical processes of humification[END_REF]. They conceptualized soil OM stabilization as the result of a combination of physical factors controlling its accessibility [START_REF] Lützow | Stabilization of organic matter in temperate soils: mechanisms and their relevance under different soil conditions-a review[END_REF] as well as chemical factors such as its oxidizing degree controlling the energy available for microorganisms [START_REF] Larowe | Degradation of natural organic matter: a thermodynamic analysis[END_REF]. Even recalcitrance as an intrinsic property of molecules has been questioned arguing that under favorable environmental conditions, all organic molecules would be biodegradable [START_REF] Kleber | What is recalcitrant soil organic matter?[END_REF]). These paradigms are in line with what was observed in several studies where a preferential conversion of high molecular weight (HMW) compounds into reactive and bioavailable LMW compounds were observed [START_REF] Kellerman | Persistence of dissolved organic matter in lakes related to its molecular characteristics[END_REF][START_REF] Kothawala | Organic Matter Degradation across Ecosystem Boundaries: The Need for a Unified Conceptualization[END_REF][START_REF] Liu | Photodegradation of algae and macrophyte-derived dissolved organic matter: A multimethod assessment of DOM transformation[END_REF]). In the literature, biodegradation processes have also been associated with the production of HMW aromatic material through alteration and recombination of existing compounds (e.g., large organic biomolecules or humification processes) [START_REF] Hach | Rapid microbial diversification of dissolved organic matter in oceanic surface waters leads to carbon sequestration[END_REF][START_REF] Kleber | Humic Substances Extracted by Alkali Are Invalid Proxies for the Dynamics and Functions of Organic Matter in Terrestrial and Aquatic Ecosystems[END_REF][START_REF] Lee | Biodegradability of algal-derived organic matter in a large artificial lake by using stable isotope tracers[END_REF]). These various scenarios of biodegradation processes and our difficulties in finding a consensus on the biodegradation mechanisms and pathways are related not only to the characteristics of OM itself such as composition and sources but also to the characteristics and properties of the ecosystem (i.e., physiochemical conditions and biological communities) [START_REF] D'andrilli | Advancing Critical Applications of High Resolution Mass Spectrometry for DOM Assessments: Re-Engaging with Mass Spectral Principles, Limitations, and Data Analysis[END_REF][START_REF] Kothawala | Organic Matter Degradation across Ecosystem Boundaries: The Need for a Unified Conceptualization[END_REF][START_REF] Mccallister | Biogeochemical tools for characterizing organic carbon in inland aquatic ecosystems[END_REF]. Furthermore, priming effects represent a potentially important mechanism underlying the biodegradation of OM in aquatic systems complexifying our understanding [START_REF] Bianchi | The role of terrestrially derived organic carbon in the coastal ocean: a changing paradigm and the priming effect[END_REF][START_REF] Bianchi | Editorial: The Role of Priming in Terrestrial and Aquatic Ecosystems[END_REF][START_REF] Zhuang | Assessing the priming effect of dissolved organic matter from typical sources using fluorescence EEMs-PARAFAC[END_REF].

Priming effects refer to quantitative and qualitative changes in the microbial decomposition of recalcitrant OM upon the addition of labile OM [START_REF] Guenet | Fast mineralization of land-born C in inland waters: first experimental evidences of aquatic priming effect[END_REF](Guenet et al. , 2010a)). They are delineated as negative, neutral, or positive effects depending on the consequences in the ways that they may reduce or exert no effect on or stimulate OM biodegradation (B Guenet et al., 2010;[START_REF] Gontikaki | Negative priming effect on organic matter mineralisation in NE Atlantic slope sediments[END_REF][START_REF] Ward | The reactivity of plant-derived organic matter and the potential importance of priming effects along the lower Amazon River[END_REF][START_REF] Ward | Marine microbial community responses related to wetland carbon mobilization in the coastal zone[END_REF][START_REF] Bengtsson | Interactive effects on organic matter processing from soils to the ocean: are priming effects relevant in aquatic ecosystems?[END_REF]Derrien et al., 2019c). All these discrepancies in the observed biodegradation mechanisms coupled with the no consensus on the occurrence and role of priming effects result in a critical need for more studies focused on the biodegradation processes and mechanisms through approaches combining analyses providing quantitative and qualitative information [START_REF] D'andrilli | Advancing Critical Applications of High Resolution Mass Spectrometry for DOM Assessments: Re-Engaging with Mass Spectral Principles, Limitations, and Data Analysis[END_REF]).

Most of the biodegradation studies in the literature aim at quantifying the OM degradation and mineralization, and its kinetic through microbial biomass measurement, dissolved organic carbon or CO2 concentrations/fluxes [START_REF] Bowen | Biochemical properties and biodegradation of dissolved organic matter from soils[END_REF][START_REF] Kalbitz | Biodegradation of soil-derived dissolved organic matter as related to its properties[END_REF][START_REF] Moran | Carbon loss and optical property changes during long-term photochemical and biological degradation of estuarine dissolved organic matter[END_REF][START_REF] Sankar | Effect of photobiodegradation and biodegradation on the biogeochemical cycling of dissolved organic matter across diverse surface water bodies[END_REF][START_REF] Vähätalo | Biodegradability continuum and biodegradation kinetics of natural organic matter described by the beta distribution[END_REF]. Only a few studies target the qualitative aspect of the biodegradation processes (i.e., exploration of the molecular changes) while the structure and composition of OM play a key in these processes [START_REF] Arndt | Quantifying the degradation of organic matter in marine sediments: A review and synthesis[END_REF][START_REF] Herzsprung | High field FT-ICR mass spectrometry data sets enlighten qualitative DOM alteration in lake sediment porewater profiles[END_REF][START_REF] Kellerman | Persistence of dissolved organic matter in lakes related to its molecular characteristics[END_REF][START_REF] Kothawala | Organic Matter Degradation across Ecosystem Boundaries: The Need for a Unified Conceptualization[END_REF]). Yet, investigating these molecular changes in similar conditions will not only allow us to lighten our knowledge of biodegradation concepts but also provide a chemical fingerprint that helps the understanding of OM reactivity and metabolism. Additionally, the few studies exploring the molecular composition during biodegradation are limited to the dissolved fraction while two fractions exist (i.e., particulate and dissolved) and both are intimately linked to each other (Derrien et al. 2019a). Hence, we decided to tackle this knowledge gap by investigating the compositional changes of sedimentary OM during biodegradation in this study.

Due to the high heterogeneity and complexity of the OM composition related to its dynamics, involvement in a large number of biogeochemical processes, and the type of environment, we have decided to head toward a laboratory experiment for this study. Indeed, controlled laboratory experiments offer the benefits of providing in-depth insight into the effects of selected parameters have on OM composition, in contrast with field samples that only represent a snapshot in space and time. The controlled laboratory degradation experiment was conducted using organic-rich sediments artificially composed of two contrasting OM end-members (i.e., soil and algae) at known mixing ratios and under two oxygen conditions (oxic and anoxic). The molecular changes induced by biodegradation in sediments and the mechanisms behind them were investigated through two advanced analytical tools: laser desorption/ionization Fourier transform ion cyclotron resonance mass spectrometry (LDI FT-ICR MS) and thermally assisted hydrolysis and methylation gas chromatography-mass spectrometry (THM-GC-MS). Currently, high-resolution mass spectrometry techniques such as FT-ICR MS are likely considered as the most powerful tool used to characterize the OM molecular properties [START_REF] Kellerman | Persistence of dissolved organic matter in lakes related to its molecular characteristics[END_REF][START_REF] Valle | Extensive processing of sediment pore water dissolved organic matter during anoxic incubation as observed by high-field mass spectrometry (FTICR-MS)[END_REF]. The LDI FT-ICR MS technique was chosen as it represents a direct and highly sensitive analysis at the molecular level to explore the biodegradation-induced changes in chemical composition in sedimentary OM. The second technique was selected to explore the biomarker fingerprints to obtain clues to understand the underlying processes during biodegradation [START_REF] Meyers | Lacustrine organic geochemistry-an overview of indicators of organic matter sources and diagenesis in lake sediments[END_REF][START_REF] Wakeham | Diagenesis of organic matter in suspended particles and sediments in the Cariaco Trench[END_REF]. Both techniques were also selected as they present the advantage of being able to directly analyze artificial sediments without any pre-treatment step such as chemical extraction and thus limiting modifications of the sample [START_REF] Aubriet | Fourier transform ion cyclotron resonance mass spectrometry and laser: A versatile tool[END_REF].

The main goal of this study was to provide a detailed exploration of the molecular composition changes of sedimentary OM induced by biodegradation and evaluate the role of factors such as type of sources and oxygen on it. The study specifically aimed at answering the following questions: (i) what molecules or groups of molecules are the most affected by biodegradation processes, (ii) what is the potential effect of OM source or oxygen conditions (i.e., oxic versus anoxic) on biodegradation processes? and (iii) what are the underlying processes behind biodegradation?

Material and methods

Experimental design of the incubation experiment

Two contrasted end-members (i.e., soil and algae) were mixed at soil-to-algae ratios (S:A) of 100:0, 75:25, 50:50, 25:75, and 0:100, based on the organic carbon (OC) concentrations (Derrien et al. 2019b). In natural aquatic systems, ratios between both OM sources greatly vary according to the season and the hydrology. Therefore, we decided to perform the study at several ratios. The soil end-member (topsoil, 0-10cm) was collected at Bukhansan National Park, South Korea (37°43'37.0" N 127°00'50.9"), a fully forested area composed of broadleaved trees such as Quercus mongolica, Q. serrata, the coniferous tree, Pinus densiflora, and the Robinia pseudoacacia plantation [START_REF] Choi | Classification of tree species using high-resolution QuickBird-2 satellite images in the valley of Ui-dong in Bukhansan National Park[END_REF]. A commercial unicellular green alga (Chlorella vulgaris), which is commonly found in freshwaters and marine environments, was purchased from Aquanet Co., Ltd. in Gyeongsangnam-do, South Korea, and used as the algae end-member. Further details regarding the end-members and the experiment can be found in Derrien et al. 2019c. Briefly, incubation experiments in oxic and anoxic conditions were performed in pre-washed and pre-combusted (450 °C for 4 hours) 125 ml Wheaton® amber glass bottles with Teflon screwcaps. Samples for anoxic incubation were prepared and sampled using a sterile Aldrich® AtmosBag two-hand glove bag under nitrogen atmosphere. A mass (12 g) of end-member mixed samples were mixed with ultrapure water (Barnstead™ Easypure™ RoDi, Thermo Scientific) at a solid-tosolution ratio of 1:4 and equilibrated for 48 h in the dark at room temperature after shaking at 100 rpm for one hour. River water from the Jungnang River, a tributary of Seoul's Han River (37°40'16"N, 127°04' 47"E), was used as inoculum for microbial incubation. Before incubation, all artificial sediment samples were spiked with 3% (v/v) of the prepared inoculum, and a sufficient amount (1%, v/v) of nutrients (NH4NO3 and K2HPO4 at 10 mM) was added to each sample to avoid nutrient limitations during the incubation. The low inoculum-to-sample ratio had a negligible effect on the final OC concentrations of the end member mixtures (<1%) and on the molecular signature. Therefore, we concluded that the concentration and signature of the inoculum could be safely ignored. Finally, the samples in oxic and anoxic conditions were incubated in the dark at 25 °C for 60 days [START_REF] Guenet | Fast mineralization of land-born C in inland waters: first experimental evidences of aquatic priming effect[END_REF][START_REF] Navel | Sedimentary context controls the influence of ecosystem engineering by bioturbators on microbial processes in river sediments[END_REF]. Samples were collected for sampling on day 0 and day 60, with "day 0" corresponding to the day when the samples were inoculated. Degradation experiments were carried out in duplicate.

The sampling was performed as follows. First, samples were taken from the incubator, and the overlying water was carefully removed so as not to disturb the sediment. The artificial sediment samples were then centrifuged at 5000 rpm for 20 min to remove the porewater.

Finally, the porewater-free sediment samples were freeze-dried, ground, and homogenized for further analyses. All the analyses were performed on both replicates except for the LDI FT-ICR MS where both replicates were carefully mixed in order to obtain a representative sample for the different modalities. Total organic carbon (TOC) contents of sediments were measured using an elemental analyzer coupled with an isotope ratio mass spectrometer (EA-IRMS;

EuroEA-Isoprime IRMS, GV instruments, UK) for all samples in order to estimate the percentage of removal or production of OC after the 60 days of incubation (Supplementary Material, Table A.1).

Laser desorption ionization Fourier transform ion cyclotron resonance mass spectrometry (LDI FT-ICR MS)

Molecular analyses were performed with a (-) LDI solariX 2XR FT ICR mass spectrometer (Bruker Daltonic, Bremen, Germany) in Mass Spectrometry Based Convergence Research Center at Kyungpook National University. The instrument was equipped with a 7 T refrigerated actively shielded superconducted magnet and a dual-mode ESI/matrix-assisted laser desorption/ionization ion source with a frequency-tripled Nd:YAG (neodymium-doped yttrium aluminum garnet) laser emitting at 355 nm. Briefly, between 2 and 5 μg of freeze-dried artificial sediment samples were directly loaded onto preplaced double-sided tape on a MALDI (matrix-assisted laser desorption/ionization) plate. Before analysis, the plate was dried under vacuum for 2 hours. The broadband spectra were acquired between m/z 100 and 1000, with a 4MW free induction decays (2 Ω), and 300 spectra were averaged to improve the signal-tonoise ratio. For data processing, only peaks with an S/N ratio of ≥ 4 were considered. A detailed description of the analytical method is given in [START_REF] Solihat | Analyzing Solid-Phase Natural Organic Matter Using Laser Desorption Ionization Ultrahigh Resolution Mass Spectrometry[END_REF].

Molecular formulae were assigned to peaks in the mass range of m/z 200-600 with a mass error range of ± 1ppm. Molecular formulae were identified considering the following elemental combinations: 12 C0-∞ 1 H0-∞ 16 O0-∞ 14 N0-5 32 S0-2. Only the formulae presented the following elemental ratio criteria, 0.3 ≤ H/C ≤ 2.25, O/C < 1.2, N/C < 0.5, and S/C < 0.2, and the double bond equivalent rule (i.e., DBE = 1/2(2C-H+N) ≥ 0) was considered [START_REF] Koch | Fundamentals of Molecular Formula Assignment to Ultrahigh Resolution Mass Data of Natural Organic Matter[END_REF]). Several selected indices, including intensity-weighted average (wa) molecular masses, elemental ratios, DBE, AImod (modified aromatic index), and MLBL (molecular lability boundary for labile contributions) were also calculated [START_REF] D'andrilli | An ultrahigh-resolution mass spectrometry index to estimate natural organic matter lability[END_REF][START_REF] Koch | From mass to structure: an aromaticity index for highresolution mass data of natural organic matter[END_REF]. Finally, the assigned molecular formulae were examined using the van Krevelen diagram and were categorized into eight different compound classes (Supplementary Material, Table A.2) [START_REF] Derrien | Spectroscopic and molecular characterization of humic substances (HS) from soils and sediments in a watershed: comparative study of HS chemical fractions and the origins[END_REF][START_REF] Kim | Graphical Method for Analysis of Ultrahigh-Resolution Broadband Mass Spectra of Natural Organic Matter, the Van Krevelen Diagram[END_REF].

Thermally assisted hydrolysis and methylation (THM) gas chromatography-mass spectrometry (THM-GC-MS)

THM-GC-MS analyses were performed according to [START_REF] Jeanneau | Constraints on the sources and production mechanisms of dissolved organic matter in soils from molecular biomarkers[END_REF]. Briefly, we introduced between 0.3 mg (algae) and 5 mg (soil) of freeze-dried solid residue into an 80 µL aluminum reactor with an excess of solid tetramethylammonium hydroxide (ca. 10 mg).

The THM reaction was performed on-line using a vertical micro-furnace pyrolyzer PZ-2020D (Frontier Laboratories, Japan) operating at 400 °C. The products of this reaction were injected into a gas chromatograph GC-2010 (Shimadzu, Japan) equipped with a SLB 5MS capillary column in the split mode (60 m × 0.25 mm ID, 0.25 µm film thickness). The temperature of the transfer line was 321°C, and the temperature of the injection port was 310 °C. The oven was programmed to maintain an initial temperature of 50 °C for 2 minutes, then rise to 150 °C at 15 °C min -1 , and then rise to 310 °C at 3 °C min -1 where it stayed for 14 minutes. Helium was used as the carrier gas at a flow rate of 1.0 ml/min. Compounds were detected using a QP2010+ mass spectrometer (Shimadzu, Japan) operating in full scan mode. The temperature of the transfer line was set at 280 °C, the ionization source at 200 °C, and molecules were ionized by electron impact using an energy of 70 eV. The list of analyzed compounds and m/z ratios used for their integration are given in the Supplementary Material (Table A.2).

Compounds were identified based on their full-scan mass spectra by comparison with the NIST library and with published data [START_REF] Nierop | Rapid molecular assessment of the bioturbation extent in sandy soil horizons under pine using ester-bound lipids by on-line thermally assisted hydrolysis and methylation-gas chromatography/mass spectrometry[END_REF][START_REF] Klaas | Thermally Assisted Hydrolysis and Methylation of Purified Tannins from Plants[END_REF]).

The target compounds (i.e., 136 biomarkers) were classified into eight chemical families: small organic acids (SOAc), phenolic compounds (PHE) including lignin and tannin markers, carbohydrates (Car), low molecular weight fatty acids (LMWFA), high molecular weight fatty acids (HMWFA), fatty alcohols (Falcohol), chlorophyll markers (Phytol) including phytol and neophytadiene, and N-containing compounds (Ncompound). The peak area of the selected m/z (mass/charge) for each compound was integrated and corrected by a mass spectra factor calculated as the reciprocal of the proportion of the fragment used for the integration and the entire fragmentogram provided by the NIST library (Supplementary Material, Table A.3) [START_REF] Denis | New molecular evidence for surface and sub-surface soil erosion controls on the composition of stream DOM during storm events[END_REF][START_REF] Jeanneau | Molecular fingerprinting of particulate organic matter as a new tool for its source apportionment: changes along a headwater drainage in coarse, medium and fine particles as a function of rainfalls[END_REF]. The proportion of each compound class was calculated by dividing the sum of the areas of the compounds in this class by the sum of the peak areas of all analyzed compounds expressed as a percentage.

Statistical analyses

All the statistical analyses were performed with R (version 3.4.3) using the packages Vegan (Vegan 2.4-1) and FactoMineR.

LDI FT-ICR MS data

The Bray-Curtis dissimilarity matrix was computed for the whole set of the LDI FT-ICR MS data (Supplementary Material, Table A.4 and A.5) to quantify the intra-and intervariability of the samples [START_REF] Bray | An Ordination of the Upland Forest Communities of Southern Wisconsin[END_REF]. Principal coordinates analysis (PCoA) was then performed based on this dissimilarity matrix.

THM-GC-MS data

A first principal component analysis (PCA) was performed using the relative proportions of the 136 biomarkers as variables, which allows the direct comparison of the different samples without the concentration effect (Supplementary Material, Table A.6 and A.7). This PCA allows identification of the correlated variables based on a modulus of the Pearson coefficient > 0.8. When the two variables were correlated, the least abundant was removed. Then a second PCA was performed. The variables with a correlation lower than 0.5 with the two first factors were removed, resulting in a new set of 67 variables. A third PCA and the associated hierarchical ascendant classification (HAC) were calculated. A last PCA and HAC were performed using specific microbial biomarkers (i.e., microbial FA: nC12:0, nC13:0, nC14:0, aC15:0, nC15:0, brC16:0, nC16:1, nC17:0, nC18:1 (2 isomers), and nC19:1) in order to explore the role of the microbial activity during biodegradation. nC16:0 and nC18:0 were not considered since these biomarkers are produced by the THM of algae and derive from higher plant inputs, respectively.

Results and discussion

All the detailed results of LDI FT-ICR MS and THM-GC-MS are presented in Supplementary Material (Tables A.4-7), 3.1. Identification of the biodegradation-induced changes in the pure end-member artificial sediments At day 0, no differences were observed based on the H/C and O/C ratios, but a clear distinction was observed for the distribution between the CHO, CHON, CHOS, and CHONS elemental formulae, common indices, and compound classes between both pure artificial sediments (S:A, 100:0 and S:A, 0:100) (Table A4-5). S:A, 100:0 mainly contained carbon-rich and heavily carboxylated compounds with a part of them rich in nitrogen (e.g., CHO of 55.2% and 39.3% and CHON of 33.6% and 38.4% in oxic and anoxic conditions respectively). By contrast, S:A, 0:100 exclusively consisted of CHO compounds (e.g., 98.9% and 96.5% in oxic and anoxic conditions respectively). Higher values of DBE and AImod and a much lower value for the MLBL for S:A, 0:100 than for S:A, 100:0 indicated the presence of highly aromatic and unsaturated compounds in the composition of the algae and the near absence of labile compounds. This was supported by the identification and distribution of the compounds classes as the S:A, 0:100 mainly consisted of unsaturated hydrocarbons (e.g., 36.3% and 37.5% for oxic and anoxic conditions, respectively), lignins/CRAM (e.g., 30.7% and 30.4% for oxic and anoxic conditions, respectively) and condensed aromatic structures (CAS, e.g., 30.1% and 27.2% for oxic and anoxic conditions, respectively) (Fig. 1). Algae material is commonly associated with labile material, however, it was also demonstrated that this kind of material can be characterized by a high amount of hydrocarbons [START_REF] Youngblood | Saturated and unsaturated hydrocarbons in marine benthic algae[END_REF]), lignins (Alzate-Gaviria et al. 2020;[START_REF] Martone | Discovery of Lignin in Seaweed Reveals Convergent Evolution of Cell-Wall Architecture[END_REF] and by biopolymers such as the algaenans, which represent the major constituent of the cell walls of green algae, for instance [START_REF] Derenne | Non-hydrolysable macromolecular constituents from outer walls of Chlorella fusca and Nanochlorum eucaryotum[END_REF][START_REF] Gelin | Novel, resistant microalgal polyethers: An important sink of organic carbon in the marine environment?[END_REF]. S:A, 100:0 also presented a distribution in compounds class rich in CAS (e.g., 51.2% and 37.2% for oxic and anoxic conditions, respectively) and lignins/CRAM (e.g., 31.1% and 38.2% for oxic and anoxic conditions, respectively). However, the rest of the distribution consisted of lipids (e.g., 7.1% and 7.3% for oxic and anoxic conditions, respectively), unsaturated hydrocarbons and/or tannins (e.g., ~5%), and a small amount of labile material such as proteins (e.g., ~3%) and carbohydrates and amino sugars (e.g, ~2%) (Fig. 1).

After 60 days of incubation, the main observed differences were related to the distribution in compound classes. A decrease of the highest molecular weight compounds (i.e., CAS and Lignins/CRAM) in S:A, 0:100 was observed in favor of an increase of the percentage of unsaturated hydrocarbons of 10.8 and 21.7 points with values reaching 47.1% and 592.2% for oxic and anoxic conditions, respectively (Fig. 1). A slight increase in labile compounds was also observed. Regarding the S:A, 100:0, the few changes were mainly observed in oxic conditions, with a decrease in the observed percentage of the CAS (e.g., from 51.2% to 38.9% at day 0 and day 60, respectively). In parallel, a slight increase in the percentage of the lignins/CRAM and labile compounds was also noted for both oxygen conditions. Classically, biodegradation is associated with a rapid loss of low molecular weight (LMW) compounds [START_REF] Hansell | Optical properties of dissolved organic matter (DOM): Effects of biological and photolytic degradation[END_REF][START_REF] Wetzel | Limnology: Lake and River Ecosystems, 3rd. Acadimic pres[END_REF]. However, in the present study, the results suggest preferential biodegradation of the high molecular weight (HMW) compounds associated with conversion into lower molecular weight compounds [START_REF] Curtis-Jackson | Characterization of low molecular weight dissolved organic nitrogen by liquid chromatography-electrospray ionization-mass spectrometry[END_REF][START_REF] Hach | Rapid microbial diversification of dissolved organic matter in oceanic surface waters leads to carbon sequestration[END_REF][START_REF] Liu | Photodegradation of algae and macrophyte-derived dissolved organic matter: A multimethod assessment of DOM transformation[END_REF][START_REF] Moran | Role of photoreactions in the formation of biologically labile compounds from dissolved organic matter[END_REF]. These observations agree with the paradigm in which all organic molecules could be biodegradable irrespective of their recalcitrance if favorable physical, chemical, and biological factors are present [START_REF] Kleber | What is recalcitrant soil organic matter?[END_REF]. This observation can be also the result of two-step processes. As it was previously observed in the literature, LMW compounds could have been consumed primarily generating a rapid loss of labile and LMW materials followed by the consumption of HMW compounds (e.g., CAS and lignins/CRAM) and their transformations in LMW compounds [START_REF] D'andrilli | Advancing Critical Applications of High Resolution Mass Spectrometry for DOM Assessments: Re-Engaging with Mass Spectral Principles, Limitations, and Data Analysis[END_REF][START_REF] Hansell | Optical properties of dissolved organic matter (DOM): Effects of biological and photolytic degradation[END_REF]. Unfortunately, the sampling design does not allow us to identify which processes (one or two steps processes) occurred.

Regarding the biomarker distributions, two distinctive fingerprints were identified between the 2 pure end-member artificial sediments but closely the same irrespective of the oxygen condition (Fig. 2). In S:A, 100:0, the most abundant chemical family was HMWFA with aliphatic side chain containing 20 and more C atoms (60.6 ± 3.3% and 60.0 ± 7.4% for oxic and anoxic conditions, respectively). These HMWFA included linear n-alkanoic acids from n-C20:0 to n-C30:0 with an even-over-odd predominance characteristic of plant-derived inputs [START_REF] Eglinton | Leaf epicuticular waxes[END_REF], linear ω-hydroxyacids and α,ω-diacids from n-C16 to n-C26, 10,16-dihydroxyC16:0 and 9,10,18-trihydroxy C18:0 characteristic of plant-derived aliphatic biopolymers cutin and suberin [START_REF] Armas-Herrera | Management effects on composition and dynamics of cutin and suberin in topsoil under agricultural use[END_REF][START_REF] Kolattukudy | Polyesters in higher plants[END_REF]). The main molecules were 9,10,18-trihydroxyC18:0 (21.4 ± 0.9% and 14.5 ± 7.6% for oxic and anoxic conditions, respectively) and ωOH-C22 (7.9 ± 0.7% and 10.7 ± 0.7% for oxic and anoxic conditions, respectively), which indicated a higher proportion of suberin from roots than cutin from leaves [START_REF] Mueller | Differentiating temperate tree species and their organs using lipid biomarkers in leaves, roots and soil[END_REF]) (Table A6-7). The second most abundant chemical family was PHE produced by the THM of lignins and tannins (11.5 ± 0.0% and 11.7 ± 3.2% for oxic and anoxic conditions, respectively). This chemical family was dominated by 3,4dimethoxybenzoic acid methyl ester and 3,4,5-trimethoxybenzoic acid methyl ester, which are typical of the THM of woody plants [START_REF] Challinor | Characterisation of wood by pyrolysis derivatisation-gas chromatography/mass spectrometry[END_REF] and applied to investigate the transfer and reactivity of OM [START_REF] Denis | New molecular evidence for surface and sub-surface soil erosion controls on the composition of stream DOM during storm events[END_REF][START_REF] Williams | Contrasting temperature responses of dissolved organic carbon and phenols leached from soils[END_REF]). The third chemical family was LMWFA with 8.9 ± 0.4% and 11.4 ± 3.1% for oxic and anoxic conditions, respectively. This chemical family includes n-alkanoic acids from n-C8:0 to n-C19:1, iso and anteiso C15:0 and C17:0, iso C14:0 and C16:0 and n-alkenoic acids n-C16:1, n-C18:1 and n-C19:1. The LMWFA with less than 13 C atoms can be derived from microbial or plant-derived inputs, while the LMWFA with more than 13 C atoms are known as phospholipid fatty acids and are microbial biomarkers [START_REF] Frostegård | Phospholipid fatty acid composition, biomass, and activity of microbial communities from two soil types experimentally exposed to different heavy metals[END_REF]) except for n-C16:0 and n-C18:0, which can derive from plant-derived inputs. In S:A, 0:100, the most abundant chemical family was LMWFA with 67.8 ± 3.1% and 61.3 ± 3.8% for oxic and anoxic conditions, respectively. The distribution of the compounds was different from that analyzed in S:A, 100:0, with a large predominance of n-C16:0 (19.3 ± 0.2% and 22.3 ± 0.3% for oxic and anoxic conditions, respectively) and a large proportion of n-C16:2 (12.1 ± 2.3% and 9.5 ± 0.7% for oxic and anoxic conditions, respectively) and n-C18:2 (32.9 ± 2.3% and 25.7 ± 2.8% for oxic and anoxic conditions, respectively). The second most abundant chemical family was the chlorophyll biomarkers with two compounds: phytol and neophytadiene. They represented 18.3 ± 3.2% and 21.5 ± 7.8% of oxic and anoxic conditions, respectively. Finally, the third chemical family was composed of N-containing compounds, which represented 10.6 ± 0.1% and 13.6 ± 3.2% (i.e., for oxic and anoxic conditions, respectively). Among this family, 1,3-dimethyluracil was the dominant compound (4.3 ± 0.6% and 7.3 ± 1.1% for oxic and anoxic conditions, respectively).

After 60 days of incubation, the characteristic chemical fingerprints of each pure endmember artificial sediments remained the same, and no significant differences were observed (Fig. 2).

Identification of the biodegradation-induced changes in mixed samples

The mixed artificial sediments (e.g., S:A, 75:25; S:A, 50:50 and S:A, 25:75) did not show notable differences in their molecular profile at day 0 (Table A .4-5). A slight increase for the H/Cwa was observed compared to the end members with values of ~1.1 instead of 0.8 or 0.9, suggesting a lower unsaturation for these samples that was confirmed by the values of DBE, which are much lower than for both pure end-member artificial sediments (e.g., values ranged from 10.8 to 12.6 irrespective of the oxygen conditions). Likewise, the values of AImod> 0.5 and inferior to both pure end-member artificial sediments demonstrated the occurrence also of less aromatic compounds. The elemental formula distributions of CHO and CHON are also quite close to each other, whatever the proportions of algae; even so, a slightly higher proportion of CHON formula compounds is observed in anoxic conditions for the S:A, 25/75 mixed sediment which reaches 49.2% for instance. The percentages of formulae with sulfur (i.e., CHOS and CHONS) were higher than for either end members with values ranging from ~10% to ~17% for CHOS and ~7% to 14.3% for CHONS. Regarding the distribution in compound classes, similarities in values were also observed (Fig. 1). The two main groups of compound classes were lignins/CRAM and CAS with percentages ranging from 38.6% to 44.2% and 22.2% to 30.2% respectively, followed by lipids and unsaturated hydrocarbons with percentages ranged between 9% and 17.9%. Proteins and carbohydrates and aminosugars occurred at less than 5%, respectively. This distribution was also reflected in the MLBL index (percentage of labile material), which reaches values 1.5-to 7-fold those observed for the soil or pure algae artificial sediment, respectively (Table A.4 and A.5).

After 60 days of incubation, each mixed artificial sediment displayed a unique molecular profile compared to the initial according to its ratio of end-members and/or its oxygen condition. S:A, 50:50, irrespective of the oxygen conditions, strictly showed the same distribution in compounds class, suggesting a homogeneous effect of the biodegradation on the whole pool of OM an. A similar observation was made for S:A, 75:25 in oxic conditions. By contrast, molecular changes were observed in S:A, 25:75 for both oxygen conditions and specifically for S:A, 75:25 in anoxic conditions (Fig. 1). In S:A, 75:25, a decrease of the CAS and lignin/CRAM was noted in favor of the unsaturated hydrocarbons becoming, thus, the main compound class (i.e., 33.7%). For S:A, 25:75, similar changes were also observed, however, the lignin/CRAM compound class remained the main one (i.e., values of 39% and 33% for oxic and anoxic conditions, respectively). Similar changes to the changes observed for the endmember in higher proportion would have been expected, however, results displayed different trends as 3 different scenarios of biodegradation according to the mixing ratios were observed (e.g., no changes or homogeneous changes for all types of compounds, consumption of LMW compounds associated to production of LMW compounds and preferential degradation of one type of HMW compounds). These differences and similarities in the compound distribution for the mixed samples suggest the occurrence of underlying mechanisms.

At day 0, the biomarker distribution of biomarkers into chemical families illustrated a gradual modification of the biomarker distribution induced by the mixing of end-members (Fig. 2). This gradual modification was characterized by the progressive increase in the proportion of LMWFA from 24.0 ± 5.2% (S:A,75:25; 26.3 ± 6.0% and 21.6 ± 4.7% in oxic and anoxic conditions, respectively) to 55.4 ± 3.8% (S:A, 25:75; 57.8 ± 4.6% and 53.0 ± 0.2% in oxic and anoxic conditions, respectively). An increase in the proportion of chlorophyll biomarkers was also observed with the increase of algae proportions with values from 3.0 ± 1.3% (S:A, 75:25, 3.8 ± 1.4% and 2.2 ± 0.9% in oxic and anoxic conditions, respectively) to 11.0 ± 3.5% (S:A, 25:75, 11.0 ± 1.4% and 11.0 ± 5.8% in oxic and anoxic conditions, respectively). At the same time, the proportion of HMWFA decreased from 45.0 ± 6.4% (S:A, 75:25; 41.6 ± 7.5% and 48.3 ± 4.6% in oxic and anoxic conditions, respectively) to 19.6 ± 3.9% (S:A, 25:75; 18.5 ± 4.1% and 20.6 ± 4.8% in oxic and anoxic conditions, respectively). The PHE proportion also decreased regularly from 9.5 ± 1.1% (S:A, 75:25; 8.8 ± 0.2% and 10.2 ± 1.0% in oxic and anoxic conditions, respectively) to 2.3 ± 0.4% (S:A, 75:25; 2.0 ± 0.2% and 2.6 ± 0.3% in oxic and anoxic conditions, respectively).

At day 60, various changes were observed in the distribution of biomarkers. The most significant changes were observed for S:A, 75,25, and S:A, 50:50, and specifically in anoxic conditions, where a significant (p-value < 0.05) diminution was observed for almost all the types of chemical families. By contrast, an increase in the proportion of LMWFA was observed for all mixing ratios and oxygen conditions, but this increase was significant only for S:A, 75;25 and S:A, 50:50 in anoxic conditions. Regarding S:A, 25:75 only the diminution of SOAc and Ncompound were significant.

Factors controlling the biodegradation

Source mixing factor

In order to understand the role and the weight of the factor "source", a PCoA was performed based on the Bray-Curtis dissimilarity matrix computed all the FT-ICR MS parameters (Fig. 3). Unfortunately, the ordination did not show any clear distinction either according to the sources or mixing of sources and/or the incubation time. Although FT-ICR MS analysis has emerged as a reliable tool for the in-depth molecular characterization of complex mixtures as OM with the capacity of identifying thousands of molecules per sample and assigning associated elemental formulae with a high level of confidence [START_REF] Repeta | Chapter 2 -Chemical Characterization and Cycling of Dissolved Organic Matter A2 -Hansell, Dennis A[END_REF][START_REF] Stubbins | Dissolved Organic Matter in Aquatic Systems[END_REF], this technique can also present some inherent limitations. The main limitations of the FT-ICR MS tool relate to the inconsistent ionization efficiency for different sample matrices, potentially leading to a bias of detection toward certain groups of compounds or even to un-characterization of material [START_REF] Blackburn | Laser desorption/ionization coupled to FTICR mass spectrometry for studies of natural organic matter[END_REF][START_REF] D'andrilli | Advancing Critical Applications of High Resolution Mass Spectrometry for DOM Assessments: Re-Engaging with Mass Spectral Principles, Limitations, and Data Analysis[END_REF][START_REF] Dittmar | A simple and efficient method for the solid-phase extraction of dissolved organic matter (SPE-DOM) from seawater[END_REF][START_REF] Hawkes | Complexity of dissolved organic matter in the molecular size dimension: insights from coupled size exclusion chromatography electrospray ionisation mass spectrometry[END_REF][START_REF] Mopper | Advanced Instrumental Approaches for Characterization of Marine Dissolved Organic Matter: Extraction Techniques, Mass Spectrometry, and Nuclear Magnetic Resonance Spectroscopy[END_REF][START_REF] Patriarca | Investigating the ionization of dissolved organic matter by electrospray ionization[END_REF]). In the present study, it is noticed the number of assigned formulae decreased gradually with the increase of the algae end-member, which could be assimilated to lower efficiency of the ionization for this kind of matrix (Table A.4 and A.5) [START_REF] Blackburn | Laser desorption/ionization coupled to FTICR mass spectrometry for studies of natural organic matter[END_REF][START_REF] Kew | Response to comment on "laser desorption/ionization coupled to FTICR mass spectrometry for studies of natural organic matter[END_REF].

A lower ionization efficiency and preferential ionization for some group of compounds might constrain the data interpretation and make it harder for disentangling the complexity of the OM molecular composition (Derrien et al. 2019a;[START_REF] Hawkes | Extreme isomeric complexity of dissolved organic matter found across aquatic environments[END_REF]. This could be one of the reasons for the failure of the ordination to identify sub-groups according to the sources, oxygen conditions, and/or time of incubations. Another reason could be related to the nondiscriminatory character of the data. FT-ICR MS is a technique able to identify with high accuracy hundreds to several thousands of ions with an m/z range typically from 200 to 1000 Da. However, this level of sensitivity is not that discriminant for observing an ordination between our set of samples.

By contrast, we clearly identified an effect of the factor "source" through the use of the biomarkers. The PCA based on the distribution of the 67 variables displayed a clear separation on axis PC1 according to the proportion of algae (Fig. 4). The HAC performed on the results of this latter PCA identified 4 groups. The 2 pure artificial sediments at day 0 and day 60 were grouped with their respective endmember sample in two different groups (Groups 1 and 3).

The biomarker fingerprint modifications induced by the mixing of end-members were fairly well illustrated by the projection of the samples at day 0 on PC1, representing 62.7% of the variance of the dataset. They corresponded almost exactly to the theoretical points calculated via the end-member mixing approach (Fig. 4). The HAC grouped S:A, 75:25 at day 0 samples with the S:A, 100:0 (Group 3) and the rest of the mixed samples (S:A, 50:50 and 25:75) from day 0 as a distinct group (Group 2). The last group identified by the HAC consisted of all three S:A mixed samples from day 60 (Group 4). This group was characterized by proportions of n-C14:0, n-C15:0, n-C16:0, aC15:0, and n-C18:0 FA higher than the mean of the samples and by proportions of N-containing compounds, succinic and fumaric acids, n-C18:1, n-C18:2, n-C16:2 FA, and a,w-diacid n-C9:0 lower than the mean of the samples. 60 days' incubation resulted in a specific decrease in the proportion of compounds that were specific to algae namely Ncontaining compounds and di-unsaturated FA. However, this decrease was not associated with an increase in soil-specific markers such as HMWFA or PHE whose proportions tend to decrease or to remain stable during the incubation (Fig. 2). This decrease was significant (Wilcoxon test) only for PHE for S:A, 75:25, and 50:50. In the same time, the proportion of microbial FA increased, which could be interpreted as stimulation of microbial biomass and therefore the occurrence of positive priming effects [START_REF] Guenet | Fast mineralization of land-born C in inland waters: first experimental evidences of aquatic priming effect[END_REF].

Oxygen factor

Oxygen is one of the most important reactants in biogeochemical cycles as it impacts the redox potential of the environment as well as the energetic situation of the microorganisms [START_REF] Brune | Life at the oxic-anoxic interface: microbial activities and adaptations[END_REF]. Therefore, its occurrence or absence may affect the biodegradation processes and pathways. In the molecular profiles obtained by LDI FT-ICR MS, the main differences were observed in S:A, 25:75, S:A, 75:25, and S:A, 0:100. The absence of oxygen led to a higher production of unsaturated hydrocarbons of 1.5 to ~3 times higher at day 60 than at day 0 with values from 12.0% to 33.7% and from 17.9% to 28.3% for the S:A, 25:75 and S:A, 75:25 samples, respectively (Fig. 1 andTable A.5). In parallel, for the same samples, a higher distribution was noticed in labile compounds after biodegradation than in oxic conditions. These observations suggest a preferential biodegradation through the conversion of HMW molecules into smaller compounds. By contrast, no differences were observed for the distribution in biomarkers (Fig. 2). This was also confirmed with the PCA as the oxic and anoxic samples are gathered together with no exceptions (Fig. 4). From our results, it seems difficult to state on the effect of the oxygen condition on the observed biodegradation pathways.

Behind the chemical mechanisms of biodegradation

In order to further investigate the potential stimulation of the microbial biomass and determine if there was a modification of the composition of the microbial community, the distribution of microbial FA (e.g., FA with a low molecular weight (< C19:0) except for C16:0 and C18:0) was investigated using a PCA and a HAC, resulting in four groups depicted by grey areas in Fig. 5. At day 0, the distribution of microbial FA in soil was modified by the addition of algae. The evolution of this distribution was almost regular along the segment formed by the end members. For algae, samples from days 0 and 60 remained in the same group (Group 1), which highlighted that the distribution of FA remained almost stable during the incubation. On the contrary for the soil, samples from day 60 were plotted in a distinct group (Group 3). This indicates a modification of the distribution of microbial FA during the experiment, which could be interpreted as a modification of the composition of the microbial community [START_REF] Frostegård | Phospholipid fatty acid composition, biomass, and activity of microbial communities from two soil types experimentally exposed to different heavy metals[END_REF]). The S:A mixed samples at day 60 were also classified as a specific group (Group 4).

The direction of the modifications of the distribution of microbial FA was almost orthogonal (i) to the segment formed by the end members and (ii) to the direction of the modifications in the soil during the experiment. Consequently, these changes in the distribution of FA were not only the result of the mixture but were also due to the adaptation of the composition of microbial communities to the mixture of soil and algae.

A second point is that the Euclidean distance between day 0 and 60 for the different S:A ratios seems to increase with the proportion of algae from 2.9 ± 0.9 (S:A, 75:25) to 3.9 ± 0.3 (S:A, 50:50) and 4.7 ± 0.3 (S:A, 25:75). The number of experimental replicates was not sufficient to test the significance of this increase. However, it could suggest that the magnitude of the modification of the composition of microbial communities increased with the proportion of algae added to the soil. Moreover, S:A mixed samples at day 60 were grouped without clear differentiations of mixture ratios, which could indicate that the modification of the microbial communities was independent of the S:A ratio. Finally, this group of S:A mixed samples from day 60 were characterized by proportions of n-C12:0 and n-C14:0 higher than the average and proportion of n-C18:1 (isomer 1), n-C17:0 and n-C19:1 lower than the average. Moreover, n-C18:1 (isomer 1) correlated with iC17:0. The differences between the average proportion in group 4 and the average proportion in the entire dataset were significant for iC17:0 (p-value < 0.001).

This group may then be associated with a decrease in the proportion of terminally branched FA (iC17:0) that has been proposed as a marker of Gram-positive bacteria [START_REF] Willers | Phospholipid fatty acid profiling of microbial communities-a review of interpretations and recent applications[END_REF].

These results could signify that this microbial group was disadvantaged by the mixing of soil with algae.

Conclusion

This study aimed at gaining insights into the biodegradation pathways and molecular modifications of sedimentary organic matter, as well as to fathom the underlying mechanisms via a laboratory experiment. The FT-ICR MS analysis allowed us to identify the group of compounds preferentially degraded during early microbial diagenesis. In both pure endmembers, CAS and lignins/CRAM were identified as the molecules the most affected by biodegradation. For the mixed artificial sediments (i.e., S:A, 75:25, S:A, 50:50, and S:A, 25:75), distinct biodegradation alterations emerged for each ratio, underscoring the potent influence of the "source" factor. The divergent shifts in compositional changes for different mixing ratios post-incubation also hint at the potential involvement of underlying mechanisms, such as priming effects. Notably, with the present study design, no discernible correlation was established between the proportions of labile material and the intensity of priming effects.

Furthermore, the combination of the biomarker and molecular analyses allowed us to suggest the capability of the microbial communities to adapt or shift in response to the varying types and proportions of organic matter sources, facilitating the biodegradation of diverse materials.

However, additional studies and complementary qualitative analyses are imperative to test this hypothesis conclusively. Nevertheless, this latter observation underscores the compelling need to delve into and elucidate the intricate interplay between microbial communities and organic matter. Addressing this challenge necessitates a holistic analytical approach, one that combines organic geochemistry and meta-omic methods. This holistic approach, as underlined by [START_REF] Bianchi | Editorial: The Role of Priming in Terrestrial and Aquatic Ecosystems[END_REF], would enable the identification of both the composition and function of microbial communities. While this study indeed stems from a controlled laboratory experiment, resulting in the formulation of questions and hypotheses for future testing, it fundamentally demonstrates the intrinsic significance of chemical, biological, and environmental factors in shaping the reactivity of OM.

Anoxic Oxic

Fig. 2 Relative proportions of the chemical families identified by the THM-GC-MS analysis of the end members at t = 0 day and t = 60 days in all the artificial sediments for both oxygen conditions (i.e., oxic and anoxic). Uncertainties are the standard deviation of two experimental replicates.

Asterisks was added on data where a significant difference (p-value < 0.05) is observed between day 0 and day 60.

Fig. 1

 1 Fig. 1 Distribution in compounds classes and elemental formulas of all the artificial sediments

Fig. 2

 2 Fig. 2 Relative proportions of the chemical families identified by the THM-GC-MS analysis

Fig. 3

 3 Fig. 3 Principal coordinate analysis ordination of the Bray-Curtis dissimilarity matrix

Fig. 4

 4 Fig. 4 Principal component analysis performed with the distribution of biomarker (67). Purple

Fig. 5

 5 Fig. 5 Principal component analysis performed with the distribution of microbial fatty acids

Fig. 1

 1 Fig. 1 Distribution in compounds classes of all the artificial sediments for both oxygen conditions (i.e., oxic and anoxic). Characteristics of compound classes are presented in Table A.2.

Fig. 3

 3 Fig. 3 Principal coordinate analysis ordination of the Bray-Curtis dissimilarity matrix computed for the LDI FT-ICR MS data.

Fig. 4

 4 Fig.4Principal component analysis performed with the distribution of biomarker (67). Purple pentagons are the theoretical points of the S:A mixed samples calculated using an end-member mixing approach. Grey shapes highlight the groups identified by the hierarchical analysis classification.

Fig. 5

 5 Fig. 5 Principal component analysis performed with the distribution of microbial fatty acids biomarker (11). Grey shapes highlight the groups identified by the hierarchical analysis classification.

, 100:0 51.2% 31.1% 2.8% 1.7% 7.1% 4.8% 1.3% 38.9% 37.7% 2.7% 2.3% 8.6% 6.8% 3.1% S:A, 75:25

  Table A.2.

	S:A, 25:75 S:A, 0:100	0.2%	10.9%	30.2% 13.8% 30.1% 36.3%	1.3%	5.1%	38.6% 30.7%	2.0%	1.0%	2.0%	18.2% 14.2% 23.1%	14.2% 47.1%		39.0% 25.3%	8.7% 3.7%	1.6% 2.8%	Tannins Lipids Unsaturated hydrocarbons	S:A, 25:75 S:A, 0:100	0.3%	17.9%	22.2% 27.2%	15.5% 37.5%		39.2% 30.4%	4.9% 2.9% 0.3% 1.7%	1.0% 6.1%	19.2%	28.3% 26.1%	59.2%	33.0% 12.9%	3.7%	3.0% 2.7% 4.9%
	S:A, 50:50	2.4%	12.2%	28.0% 10.3%	2.0%	5.4%	39.6%			1.1%	12.0%	28.8% 11.9%	1.8%	5.4%	39.0%		Carbohydrates & aminosugars	S:A, 50:50	1.0%	12.5%		27.0% 10.8%	0.8%	3.7%	44.2%	0.8%	13.6%	24.8% 12.0%	1.3%	4.6% 42.8%
	t = 0 day S:A28.9% 12.0% 9.0% 2.8%	2.6%	4.9%	39.7%		8.7% 3.7%		27.1% 10.6%	1.5%	t = 60 days 4.7%		43.6%		Lignins/CRAM Condensed aromatic structures Proteins	S:A, 100:0 S:A, 75:25	4.9% 5.2% 2.3%	7.3% 12.0%	t = 0 day 37.2% 3.6% 3.5% 27.7% 11.4%	1.4%	38.2% 3.3%	42.0%	4.6% 4.2%	2.1% 19.8% 8.2%	37.9% 2.0% 33.7%	t = 60 days 41.6% 30.8%	4.5%	1.1%	10.2%

Acknowledgments

This work was supported by a National Research Foundation of Korea (NRF) grant [No. 2017R1D1A1B033546, 2017 funded by the Korean government (MSIP). The authors thank Dr. Yunju Cho for handling the LDI FT-ICR MS analyses. THM-GCMS analyses were performed through the support of the Condate Eau -OSUR analytical platform of Rennes University.

Data Availability Statement

The data that support this study are available in the article and accompanying online supplementary material.

Conflict of Interest statement

The authors declare no conflicts of interest.

Declaration of Funding

The funding of this work was the National Research Foundation of Korea (NRF) grant [No. 2017R1D1A1B033546, 2017 from the Korean government (MSIP).

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As part of a multidisciplinary research and a PhD project to strengthen the attachment for retired couples living at home, we imagined and designed Yōkobo. It is a robot at the crossroads of a sensitive approach and a robotic trend that bridges the gap between humans (Human-Robot-Human Interactions field).

Yōkobo is a trinket bowl placed in the entrance of homes. It expresses home hospitality and celebrates small moments of everyday life by its discreet presence that welcomes visitors and inhabitants of the house. The name comes from the contraction of "yōkoso" (welcome in Japanese) and "robot" (with French pronunciation). As a theoretical contribution, Yokobo is at the crossing of different concepts: behavioural objects, robjects, weak robotics, and slow technology. Yōkobo is resolutely innovative and disruptive. It uses the different discrepancies existing concerning the generally shared vision of robots:

• it is an object intended to be unobtrusive, stemming from ambient computing while having an on-going subtle presence. It does not make sounds, unlike the voice assistants and voice modality trend. It expresses itself and its surroundings only through motion and light.

• to move away from home's companion robots and the biases they can generate by the presence of a face representation, Yōkobo is neither anthropomorphic nor can talk.

• Yōkobo is made of natural materials such as ceramic, wood, or wool to break with the idea of plastic, disposable, and toy robots and to improve its integration in everyday home life.

• as a slow technology product, understanding and integrating Yōkobo into one's life takes time and requires accepting not having a clear, repetitive, and instantaneous response to an action. It is the sum of different experiences with the product over time that creates the meaning and value of the object. Getting to know Yōkobo's expressive motions is continuous and progressive. The experience with Yokobo is a sensible one and it poetically interacts with people in their homes.it. Its contribution is not measured in terms of efficiency and utility.

Yōkobo is a concept that puts people at the centre. It is an object that steps in order to cherish the relationship between people.

  It does not impose itself to propose an exclusive Human-Object relationship. It reveals the presence of the other by expressing the last impermanent trace of the other's passage. It is an object of sensitive presence. a selection of keywords related to the subject of the publication: layout (scroll.able, pan.able, zoom.able, story.able, video.able, more information in the layout formats specifications PDF): Pan.able bibliography and references* This journal uses the Chicago Manual of Style, 17th edition. Visit an .able article example for more information full credits to feature on the website (authors, designer, editorial mediator, financial support, acknowledgement…) Niveau 1 Dessins originaux de Dora Garcin. Numérisation et ajustement du style de Dominique Deuff Niveau 2 (images de gauche à droite) Images 1 à 8 -génération d'images 3D de Dino Beschi Image 9photo et montage Photoshop de Dominique Deuff Images 10 et 11 -génération d'images 3D de Clément Laurenziani et montage Photoshop de Dominique Deuff 12 et 13dessins de Dominique Deuff Image 14 et 15 -génération d'images 3D de Corentin Aznar Image 16 et 17dessins de Corentin Aznar Niveau 3 Dessins réalisés par Dominique Deuff media one or a few pictures with captions and credits : .able needs 4 images : • 1 image in 1920x1080, 72 dpi • 1 image in 700x460, 72 dpi • 1 image in 2200*700, 72 dpi • 1 portrait image in A4 format, 300 dpi for print-on-demand use Image 1: Photo et montage Photoshop de Dominique Deuff Image 2: Photo et montage Photoshop de Dominique Deuff Image 3: Photo et montage Photoshop de Dominique Deuff Image 4: Photo et montage Photoshop de Dominique Deuff

Scassellati, Brian, Laura Boccanfuso, Chien-Ming Huang, Marilena Mademtzi, Meiying Qin, Nicole Salomons, Pamela Ventola, and Frederick Shic. 2018. "Improving social skills in children with ASD using a long-term, in-home social robot." Science Robotics 3 ( 21