Benjamin Misson
email: misson@univ-tln.fr

Cédric Garnier

Béatrice Lauga

Huy Duc

Jean-François Dang

Jean-Ulrich Ghiglione

Robert Mullot

Olivier Duran

Pringault

Dang

Jean-François Ghiglione

Jean-Ulrich Mullot

Robert Duran

Olivier Pringault

Chemical multi-contamination drives benthic prokaryotic diversity in the anthropized Toulon Bay

Keywords: microbial ecotoxicology, multi-contamination, prokaryotic diversity, marine sediment

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

INTRODUCTION

Marine coastal areas represent ecotones between continental and marine environments.

Strong and natural coastal gradients (e.g. salinity, water inflows, bottom topography, sedimentation pattern, turbidity and nutrients) are known to shape the diversity of several organisms, ranging from fishes [START_REF] Winemiller | Fish Assemblages Across a Complex, Tropical Fresh-Water Marine Ecotone[END_REF] to bacteria [START_REF] Ortega-Retuerta | Spatial variability of particle-attached and free-living bacterial diversity in surface waters from the Mackenzie River to the Beaufort Sea (Canadian Arctic)[END_REF][START_REF] Troussellier | Bacterial activity and genetic richness along an estuarine gradient (Rhone River plume, France)[END_REF], including invertebrates [START_REF] Waterkeyn | Invertebrate community patterns in Mediterranean temporary wetlands along hydroperiod and salinity gradients[END_REF]. As a result, the functions of coastal ecosystems are largely driven by natural gradients [START_REF] Sklar | Coastal environmental impacts brought about by alterations to freshwater flow in the Gulf of Mexico[END_REF]. Since coastal areas are of great interest to humans, they also face increasing human-induced chemical contamination resulting from watershed drainage, domestic and industrial waste waters and other direct inputs, such as biocides released by anti-fouling paints or fuel residues from shipping (e.g. [START_REF] Colombo | Sources, vertical fluxes, and equivalent toxicity of aromatic hydrocarbons in coastal sediments of the Rio de la Plata Estuary, Argentina[END_REF][START_REF] Daskalakis | Distribution of Chemical Concentrations in Us Coastal and Estuarine Sediment[END_REF][START_REF] Levin | Effects of natural and human-induced hypoxia on coastal benthos[END_REF]Oursel et al., 2014Oursel et al., , 2013)). As a result, marine coastal areas are characterized by a complex set of chemical factors potentially affecting living organisms. Consequently, marine coastal ecosystems represent one of the most challenging environments for understanding the links between chemical composition and biological diversity.

Benthic archaea and bacteria are key microbial players in ecosystem functioning, because of their major roles in diverse biogeochemical cycles, particularly through carbon and nitrogen mineralization [START_REF] Francis | Ubiquity and diversity of ammonia-oxidizing archaea in water columns and sediments of the ocean[END_REF][START_REF] Jørgensen | Bacteria and Marine Biogeochemistry[END_REF] and toxic metals transformation, either directly (e.g. mercury methylation, [START_REF] Parks | The Genetic Basis for Bacterial Mercury Methylation[END_REF] or indirectly (e.g. formation of sulfide compounds after sulfide release by sulfate reduction, [START_REF] Jørgensen | Bacteria and Marine Biogeochemistry[END_REF]. However, little is known about the links between prokaryotes diversity and the global chemical composition of the sediment, including both the natural composition and anthropogenic chemical contaminants, in marine coastal areas. It was evidenced that early diagenesis, which is controlled by microbial activity, induced modifications to the characteristics of sedimentary organic matter (e.g. [START_REF] Burdige | Preservation of Organic Matte Mechanisms, and an Imbalance in Sediment Organic Carbon Budgets?[END_REF]Dang et al., 2014a) but also influenced the mobility of trace elements, such as trace metals/metalloids (e.g. Dang et al., 2015aDang et al., , 2014b;;[START_REF] Gendron | Early diagenesis of cadmium and cobalt in sediments of the Laurentian Trough[END_REF], with significant seasonal variations. Moreover, the influence of microbial activity on metal speciation has been demonstrated, particularly for mercury speciation [START_REF] Cossa | A Michaelis Menten type equation for describing methylmercury dependence on inorganic mercury in aquatic sediments[END_REF][START_REF] Duran | Mercury methylation by a microbial community from sediments of the Adour Estuary (Bay of Biscay, France)[END_REF] and organic tin degradation [START_REF] Filipkowska | Organotin compounds in surface sediments of the Southern Baltic coastal zone: a study on the main factors for their accumulation and degradation[END_REF][START_REF] Pougnet | Sources and historical record of tin and butyl-tin species in a Mediterranean bay (Toulon Bay, France)[END_REF] in coastal sediments. Our understanding of the influence of benthic microbial activity on the chemical composition of anthropized coastal sediment is thus progressing well. Nevertheless, the impact of the global chemical composition of sediment on benthic microbial communities is poorly documented. Some bacteria and microalgae were shown to resist or even benefit from high inorganic or organic contaminant concentrations (e.g. [START_REF] Edwards | Aerobic transformation of cadmium through metal sulfide biosynthesis in photosynthetic microorganisms[END_REF][START_REF] Gauthier | Marinobacter-Hydrocarbonoclasticus Gen-Nov, Sp-Nov, a New, Extremely Halotolerant, Hydrocarbon-Degrading Marine Bacterium[END_REF][START_REF] Louati | The roles of biological interactions and pollutant contamination in shaping microbial benthic community structure[END_REF][START_REF] Rensing | CopA: An Escherichia coli Cu(I)-translocating P-type ATPase[END_REF].

However, chemical pollution can affect the diversity and functions of prokaryotic communities [START_REF] Abell | Niche Differentiation of Ammonia-Oxidising Archaea (AOA) and Bacteria (AOB) in Response to Paper and Pulp Mill Effluent[END_REF][START_REF] Scott | The microbial nitrogen cycling potential is impacted by polyaromatic hydrocarbon pollution of marine sediments[END_REF], although the great adaptive skills of prokaryotes after long term exposure to chemical contaminants [START_REF] Gillan | The long-term adaptation of bacterial communities in metal-contaminated sediments: a metaproteogenomic study[END_REF] can lead us to observe no significant change in diversity [START_REF] Besaury | Abundance, activity, and diversity of archaeal and bacterial communities in both uncontaminated and highly copper-contaminated marine sediments[END_REF][START_REF] Gillan | Structure of Sediment-Associated Microbial Communities along a Heavy-Metal Contamination Gradient in the Marine Environment[END_REF], not even higher diversities [START_REF] Bengtsson | Microbial diversity and PAH catabolic genes tracking spatial heterogeneity of PAH concentrations[END_REF] in response to chemical pollution. Such influences result in spatial variability of microbial abundance and/or community composition in the environment, which can alter ecosystem functioning along the contamination gradients [START_REF] Abell | Niche Differentiation of Ammonia-Oxidising Archaea (AOA) and Bacteria (AOB) in Response to Paper and Pulp Mill Effluent[END_REF][START_REF] Scott | The microbial nitrogen cycling potential is impacted by polyaromatic hydrocarbon pollution of marine sediments[END_REF]. Thus, in marine coastal ecosystems, the relative contributions of natural abiotic gradients and anthropogenic and multiple contamination gradients to the spatial variability of microbial diversity need to be further explored in order to better apprehend the ecological consequences of human-induced environmental changes.

The present study was held at Toulon Bay, a semi-enclosed coastal ecosystem experiencing very strong and multiple contaminations by metals, metalloids, organometallic and organic pollutants [START_REF] Cossa | A Michaelis Menten type equation for describing methylmercury dependence on inorganic mercury in aquatic sediments[END_REF]Dang et al., 2015aDang et al., , 2014b;;[START_REF] Pougnet | Sources and historical record of tin and butyl-tin species in a Mediterranean bay (Toulon Bay, France)[END_REF][START_REF] Tessier | Study of the spatial and historical distribution of sediment inorganic contamination in the Toulon bay (France)[END_REF]. While this ecosystem experiences multiple contamination gradients of several orders of magnitude, its relatively small size greatly limits other abiotic variations such as climate related parameters, hydrology and mean sediment composition (excluding pollutants). An indepth geochemical characterization of surface sediments and the genetic fingerprinting of archaeal and bacterial benthic communities sampled at numerous stations in Toulon Bay allowed us (i) to address the impact of the global chemical environment and then (ii) to compare the respective influence of a wide range of both natural and anthropogenic gradients on both local microbial genetic richness and spatial variations in microbial community structure.

MATERIALS AND METHODS

Study site and sediment sampling

Sediments samples were collected at different locations of Toulon Bay, on the northwest Mediterranean coast. Its semi-close morphology associated with micro-tidal conditions and intermittent freshwater inputs [START_REF] Nicolau | Base flow and stormwater net fluxes of carbon and trace metals to the Mediterranean sea by an urbanized small river[END_REF], leads to relatively long water residence times [START_REF] Dufresne | Wind-forced circulation model and water exchanges through the channel in the Bay of Toulon[END_REF]. Consequently, numerous historic (e.g. World War II) and present (1 st French navy harbour, nautical traffic, tourism, urbanism, aquaculture, etc.) anthropogenic activities have resulted in a strong multi-contamination of the sedimentary compartment [START_REF] Cossa | A Michaelis Menten type equation for describing methylmercury dependence on inorganic mercury in aquatic sediments[END_REF]Dang et al., 2015aDang et al., , 2014b;;[START_REF] Pougnet | Sources and historical record of tin and butyl-tin species in a Mediterranean bay (Toulon Bay, France)[END_REF][START_REF] Tessier | Study of the spatial and historical distribution of sediment inorganic contamination in the Toulon bay (France)[END_REF] and also of the water column [START_REF] Jean | Protein expression from zooplankton communities in a metal contaminated[END_REF], Dang et al., 2015b). A map of Toulon Bay including the location of the main towns and anthropogenic activities, is presented in figure 1A. The bay is separated into two basins by a sea wall: Little Bay (LiB) on the northwestern side and Large Bay (LaB) on the southeastern part. Sediments were collected using an interface corer (equipped with 10-cm diameter and 1-m long Plexiglass tube, handled from a navy boat or divers) as previously described [START_REF] Tessier | Study of the spatial and historical distribution of sediment inorganic contamination in the Toulon bay (France)[END_REF] to collect sediments at 54 stations covering the whole bay (figure 1) .

Chemical characterization of the sediments

We compiled previously published data on the chemical characterization of the surface sediments, except for the organic pollutants (polycyclic aromatic hydrocarbons (PAHs), polychloro biphenylated (PCBs)). Briefly, the obtained surface sediments (0-5 cm) were analysed for (1) major constituents (major elements, particulate organic and inorganic carbon (POC, PIC), total phosphorus) and minor/trace elements (Dang et al., 2015a(Dang et al., , 2014a(Dang et al., , 2014b;;[START_REF] Tessier | Study of the spatial and historical distribution of sediment inorganic contamination in the Toulon bay (France)[END_REF]; (2) methyl mercury (MMHg) [START_REF] Cossa | A Michaelis Menten type equation for describing methylmercury dependence on inorganic mercury in aquatic sediments[END_REF]; and (3) tin and butyltin species [START_REF] Pougnet | Sources and historical record of tin and butyl-tin species in a Mediterranean bay (Toulon Bay, France)[END_REF]. Full description of samples treatment and chemical analysis can be found in the cited references. Briefly, sediments were deep-frozen, freezedried, 2-mm sieved and kept deep frozen (-18°C) until analysis. POC and PIC contents were determined using a TOC-V CSH analyzer (Shimadzu) coupled with a SSM-5000A module (Dang et al., 2014a;[START_REF] Tessier | Study of the spatial and historical distribution of sediment inorganic contamination in the Toulon bay (France)[END_REF]. Major elements and total phosphorus were measured by XRF (Philips PW 2400) equipped with a Rh-tube, on 50-µm crushed (on carbide tungsten rings mill, NAEF model M02) sediments [START_REF] Tessier | Study of the spatial and historical distribution of sediment inorganic contamination in the Toulon bay (France)[END_REF]. Minor/trace elements were determined by High Resolution Inductively Coupled Plasma Mass Spectrometer (HR ICP-MS, Element 2, Thermo Finnigan) after aqua regia and microwave (Anton Paar Multiwave 3000) digestion of sediments (Dang et al., 2014b(Dang et al., , 2015a;;[START_REF] Tessier | Study of the spatial and historical distribution of sediment inorganic contamination in the Toulon bay (France)[END_REF]. Hg contents were determined by an advanced mercury analyzer AMA 254 (Leco Corporation) [START_REF] Tessier | Study of the spatial and historical distribution of sediment inorganic contamination in the Toulon bay (France)[END_REF]. MeHg was analysed after propylation and isotopic dilution and detection by gas chromatography-ICP-MS (GC/ICP-MS, GC-Focus with X-series, Thermo Electron) [START_REF] Cossa | A Michaelis Menten type equation for describing methylmercury dependence on inorganic mercury in aquatic sediments[END_REF]. Butyl-tin species contents were determined by GC/ICP/MS (Thermo X7 Series II) after extraction of butyl-Sn species by acetic acid [START_REF] Pougnet | Sources and historical record of tin and butyl-tin species in a Mediterranean bay (Toulon Bay, France)[END_REF]. Moreover, 25 surface sediment samples from LiB (figure 1 and HEX (6-carboxy-1,4-dichloro--tetrachlorofluorescein) fluorochromes respectively for Bacteria and 344F [START_REF] Raskin | Group-specific 16S rRNA hybridization probes to describe natural communities of methanogens[END_REF])/915R (Stahl and Amann, 1991) labelled with FAM and HEX fluorochromes respectively for Archaea using AmpliTaq Gold® DNA Polymerase (Life technologies). For PCR amplification an initial denaturation step at 94 PCR amplicons were cleaned using the GFX PCR DNA Purification kit (GE Fisher) and digested with the restriction endonucleases HinfI for Bacteria and TaqI for Archaea (37°C, 3 h). T-RFLP profiles were obtained with a 3130xl Genetic Analyzer (Applied Biosystems)

following the manufacturer's recommendations and analysed with GeneMapper®Software (Applied Biosystems). Using T-Rex software [START_REF] Culman | T-REX: software for the processing and analysis of T-RFLP data[END_REF] raw data were normalized to account for differences in the amount of DNA loaded and terminal restriction fragments (T-RFs) assigned to produce the final matrix.

Data analysis and statistics

The high spatial resolution maps allowed the establishment of surface-weighted average (SWA) trace metal/metalloids contents for Toulon Bay, i.e. the most representative concentration values on the entire bay scale (Dang et al., 2015a;[START_REF] Larrose | Assessing the current state of the Gironde Estuary by mapping priority contaminant distribution and risk potential in surface sediment[END_REF][START_REF] Tessier | Study of the spatial and historical distribution of sediment inorganic contamination in the Toulon bay (France)[END_REF]. The kriging gridding method of Surfer software (9.9 version) with default parameters was used to generate contour map and Matlab software (7.8 version) was used for data processing. This clustering of chemical variables highlighted five groups corresponding to the sediment type ("marine", "terrigenous", POC, origin) and three groups of anthropogenic contaminants ("inorganic", "organometallic" and "organic" elements/compounds), resulting in 29 representative chemical variables. The content ranges, median content and SWA (only for the 23 variables measured on all the sediments samples) values of these chemical variables are summarized in table 1.

Enrichment factors (EF) [START_REF] Hilton | A mathematical model for analysis of sediment core data: Implications for enrichment factor calculations and trace-metal transport mechanisms[END_REF] were calculated for trace metals/metalloids contaminants in order to distinguish anthropogenic pollution from the natural content of the sediment as described in [START_REF] Tessier | Study of the spatial and historical distribution of sediment inorganic contamination in the Toulon bay (France)[END_REF]. Briefly, the measured trace elements contents were normalized to the Al contents of the samples, and then compared with the geochemical background of the studied area for the same normalized metal content, according to the following equation:

where Me is the content of the corresponding trace metal/metalloid. The geochemical background was here estimated as the average of the three lowest calculated Me/Al ratios from 146 samples originating from surface and deep sediments (including 210 Pb-dated core sediments corresponding to the lowest contamination records, from Dang et al., 2015a and[START_REF] Tessier | Study of the spatial and historical distribution of sediment inorganic contamination in the Toulon bay (France)[END_REF] of Toulon Bay. According to [START_REF] Sutherland | Bed sediment-associated trace metals in an urban stream, Oahu, Hawaii[END_REF], significant enrichment levels are reached if 5 < EF < 20, and very high enrichment levels if EF > 20.

The toxic potential of the sediment was evaluated through comparison of the contents to effects range-low (ERL) and effects range-medium (ERM) guidelines, initially determined through toxicity evaluation on benthic invertebrates exposed to single contaminations [START_REF] Long | Incidence of adverse biological effects within ranges of chemical concentrations in marine and estuarine sediments[END_REF]. Then, in order to assess the global toxic potential of the multi-contaminated sediments of Toulon Bay, the mean ERM quotient (m-ERM-Q) was calculated as described in [START_REF] Long | Predicting toxicity in marine sediments with numerical sediment quality guidelines[END_REF], according to the following equation:

where C i is the sediment content of compound i, ERM i is the ERM for compound i and n is the number of compounds.

Local (alpha) diversity indexes (number of terminal restriction fragments (T-RF richness), using PRIMER 6 software (v6.1.13, [START_REF] Clarke | Non-parametric multivariate analyses of changes in community structure[END_REF].

-RF structure (beta-diversity) were analysed through quantitative distance analyses, conducted using PRIMER 6 software. Chemical Gower similarities were computed from median normalized substance contents in order to properly compare minor and major element content variation.

Biological Bray-Curtis similarities were computed from normalized T-RFLP data (Legendre and Legendre, 1998). Differences between samples originating from LiB or LaB were visualized through principal coordinate analysis (PCoA) and tested by one-way permutational multivariate analysis of variance (PERMANOVA) with Rstudio (RStudio Team,

2015, package vegan).

Correlations between biological and chemical similarities were assessed by using XLStat (version 2010.3.03, Addinsoft, Paris, France). Other correlations were tested using Rstudio (RStudio Team, 2015, packages stats and psych)

Variation partitioning through direct multivariate canonical correspondence analysis (CCA) was used to compare the respective contributions of anthropogenic contaminants and sediment type to the spatial variability of archaeal and bacterial community structure. In order to avoid using multicolinear variables and thus overestimating contributions to the biological variance, covariance analyses were performed and variables presenting variance inflation factors higher than 10 were excluded from the dataset. Covariance analysis and CCA were performed with Rstudio (RStudio Team, 2015, packages vegan, HH and usdm).

RESULTS

Abiotic characterization of the sediments

A set of chemical gradients was observed in surface sediments of Toulon Bay. Groups related to sediment origin and natural and mixed trace elements presented narrow to moderate content gradients (table 1), with Al (figure 2A) and Ca (figure SI-4A) presenting clear terrestrial-marine gradients resulting in an opposite relationship between these 2 elements (figure SI-5). Among inorganic contaminants (ex. Cd, figure 2B), the strongest spatial variations in concentrations was observed for Cu, Hg, Sn and Zn, with about 55-to 900-fold content ranges (table 1). Organo-metals also presented very wide content gradients, with a 13500-fold range for TBT and an approximately 80-fold range for MMHg (table 1).

Contamination levels and potential toxicity

In As detailed in table 1, the highest recorded concentrations of five inorganic contaminants (As, Cu, Hg, Pb and Zn) and of two organic contaminants (fluoranthene and PCB)

surpassed their ERM values. Moreover, approximately 50% of the surface of Toulon Bay presented Hg contents overpassing the corresponding ERM. Then, m-ERM-Q was calculated in order to compare the toxic potential of the different sediment samples. When considering only trace metals, 26.6% of the whole surface of Toulon bay presented m-ERM-q values above 0.5, representing a probability of being toxic of approximately 50% or higher.

Moreover, more than 80% of the surface presented m-ERM-Q values above 0.5. According to spatial variation in metals-based m-ERM-Q, the highest toxic potentials were observed in the northern part of LiB (figure 2E). Including organic pollutants also confirmed this trend (figure SI-4E).

Local microbial diversity variations

Bacterial T-RF richness ranged between 14 and 40 OTUs. It appeared to be higher in LiB, and decreased gradually through LaB where it reached its minimum before increasing

slightly towards the open sea (figure 3A). Archaeal T-RF richness appeared to be smaller with 4 to 13 T-RFs, and varied in a more chaotic way with important changes between very close sampling stations (figure 3B). Shannon indexes calculated from T-RFLP data provided very similar results ( ranging from 1.34 to 2.43 for archaea and from 2.60 to 3.52 for bacteria) and were very strongly correlated to richness (R² = 0.96 for archaea and 0.94 for bacteria). Evenness demonstrated very low spatial variations (ranging from 0.91 to 0.995 for both bacteria and archaea) and was not correlated with both archaea and bacteria), thus highlighting the importance of richness in bacterial and archaeal Shannon index variations among sediment samples. Hence, local microbial diversity will be represented by genetic richness in further analyses.

Bacterial T-RF richness was positively correlated with parameters related to terrigeneous elements (Al, Fe), one natural trace element (Ni), trace elements of mixed origin (As, Cr and S), some anthropogenically enriched toxic trace metals (Ag, Cu, Hg and Zn), organometallic contaminants (MMHg, TBT and BT ), some organic contaminants (CB-153, PCB) and metal-based m-ERM-Q, whereas it was correlated negatively with marine elements (Ca), Co and Ni (p < 0.05, table 2).

Archaeal genetic richness proved to be linked to fewer environmental parameters: it was also positively correlated with terrigeneous elements (Al, Fe), one trace element of mixed origin (Cr), some anthropogenically enriched toxic trace metals (Bi, Cu, Hg, Pb and Zn), organometallic contaminants (MMHg, TBT and BT ) and m-ERM-Q values (p < 0.05, table 2).

Hence, in Toulon Bay, both bacterial and archaeal T-RF richness appeared to be higher in sediments influenced by terrestrial inputs, enriched in many toxic substances, and thus presenting a high toxic potential. However, for most of the chemical substances presenting significant correlations with the T-RF richness of both microbial communities, the correlations were weaker and less significant for archaea. Particulate organic carbon, Mn and P contents in the sediments did not appear to be linked with either bacterial or archaeal T-RF richness (p > 0.05, table 2)

Spatial variations in microbial community structure

Beta-diversity analysis (PERMANOVA) of the bacterial community highlighted a clear segregation (p = 0.001) of the samples originating, on one hand, from LiB and, on the other hand, from LaB and towards the open sea (figure 4A). With reference to the less contaminated sites located outside of Toulon Bay, the bacterial similarity appeared very low (decreasing to approximately 20%) upon entry into LaB, then increased slightly but varyed strongly again between very close stations westward (figure 3C). Complementary analysis with reference to the most contaminated site (MIS station, in the northern part of LiB, figure SI-4F) demonstrated very strong differentiation towards the south of the bay, with low similarity (decreasing to 50%) between sites distant from barely more than 1km. In contrast, no evident clustering according to geographical origin (p = 0.052) could be observed for the archaeal community (figure 4B). The archaeal similarities were globally higher and less variable, with the strongest shifts being observed in LiB and near the mouth eastward (figure 3D).

Both archaeal and bacterial similarities were negatively correlated with the geographical distance between sites (n = 703, archaea: r = -0.286, p < 10 -4 , bacteria: r = -0.285, p < 10 -4 ), and positively correlated to (n = 703, archaea: r = 0.195, p < 10 -4 , bacteria: r = 0.209, p < 10 -4 ). However, the spatial variation in the global chemical signature only appeared very weakly correlated with the bacterial similarities (n = 703, r = 0.094, p = 0.014) and not significantly correlated with the archaeal similarities (n = 703, p > 0.05). did not demonstrate any significant correlation with biological similarities (n = 703, p > 0.05). The same trends were recorded with reduced datasets including BT species (n = 276) or organic contaminants (n = 171), while archaeal similarities only correlated significantly with the geographic distances between sites (data not shown).

When considering all of the sampling stations (n = 38), the combination of sediment type (represented by Ca, Co, As, Cr, Mn, S and POC) and anthropogenic contaminants (Ba, Cd, Hg, P, Sb, Sn and Ti) explained 46% of the bacterial structural variation, each of them accounting for 26% on its own. Similarly, this dataset explained 51% of the archaeal community structural variation, with anthropogenic contaminants explaining a little less than sediment type (26% and 26%, respectively). Including BT species did not significantly increase the contribution of the anthropogenic contaminants, since TBT and BT never explained more than 5% of the variability of the archaeal and bacterial communities structure, far less than the other contaminants, which contributed up to 9% in the same dataset (n = 24). However, the global statistical contribution of the chemical dataset to the biological variation rose to 60% for both bacteria and archaea. Similarly, CB-153 and PCB proved to be the least important statistical contributors to biological variation, with contributions ranging between 4% and 6%, whereas other single contaminants could explain up to 13%. On the contrary, fluoranthene and PAH contributed significantly (between 6% and 10%), and appeared to be among the four best statistical contributors of all the contaminants in the corresponding dataset (n = 19). Within this reduced dataset, the global statistical contribution to biological variation reached 85% and 78% for bacteria and archaea, respectively.

DISCUSSION

Marine coastal areas are subject to various natural and anthropogenic gradients. The benthic compartment of Toulon Bay illustrates well this general observation with gradients of POC content, sediment origin and multiple contaminations. In the literature, previous attempts to understand the contributions of the various factors shaping prokaryotic communities in different ecosystems mainly focused on the relative contributions of bottom-up and top-down variables to better understand food-web functioning (e.g. [START_REF] Berdjeb | Bottom-up versus top-down control of hypoand epilimnion free-living bacterial community structures in two neighboring freshwater lakes[END_REF][START_REF] Salcher | Same same but different: ecological niche partitioning of planktonic freshwater prokaryotes[END_REF][START_REF] Van Wambeke | Bottom up effects on bacterioplankton growth and composition during summer-autumn transition in the open NW Mediterranean Sea[END_REF] or on the influence of chemical pollutants through ecotoxicological approaches (e.g. [START_REF] Besaury | Abundance, activity, and diversity of archaeal and bacterial communities in both uncontaminated and highly copper-contaminated marine sediments[END_REF][START_REF] Ben Said | Changes of benthic bacteria and meiofauna assemblages during bio-treatments of anthracene-contaminated sediments from Bizerta lagoon (Tunisia)[END_REF][START_REF] Kostka | Hydrocarbon-Degrading Bacteria and the Bacterial Community Response in Gulf of Mexico Beach Sands Impacted by the Deepwater Horizon Oil Spill[END_REF][START_REF] Paisse | Are alkane hydroxylase genes (alkB) relevant to assess petroleum bioremediation processes in chronically polluted coastal sediments?[END_REF][START_REF] Quillet | Abundance, diversity and activity of sulfate-reducing prokaryotes in heavy metal-contaminated sediment from a salt marsh in the Medway Estuary (UK)[END_REF][START_REF] Rasmussen | Effects of mercury contamination on the culturable heterotrophic, functional and genetic diversity of the bacterial community in soil[END_REF]. In this study, we chose to investigate the influence of the abiotic environment as a whole on microbial communities by considering together both potentially toxic contaminants and natural substances from various origins. The usefulness of such a global approach was demonstrated in this study by the major contribution of the chemical composition of the sediment in shaping benthic microbial communities of Toulon Bay. Indeed, from approximately 45% to more than 80% of the variability of bacterial and archaeal community structure could be statistically explained by a selection of chemical variables. Thus, a significant part of this variability remained statistically unexplained in our study, corresponding to some abrupt shifts that were observed in close and chemically similar sampling sites. This could be partly due to biotic factors, such as predation or viral lysis pressures, which are well known for their influence on prokaryotic community abundance and structure [START_REF] Ben Said | Changes of benthic bacteria and meiofauna assemblages during bio-treatments of anthracene-contaminated sediments from Bizerta lagoon (Tunisia)[END_REF][START_REF] Louati | The roles of biological interactions and pollutant contamination in shaping microbial benthic community structure[END_REF][START_REF] Ram | The relative importance of viral lysis and nanoflagellate grazing for prokaryote mortality in temperate lakes[END_REF][START_REF] Sauret | Influence of PAHs among other coastal environmental variables on total and PAH-degrading bacterial communities[END_REF] but

were not investigated in this work.

Investigating global chemical signatures also proved to be valuable through the significant links that were observed between biological and chemical distances. Interestingly, neither the global chemical distance between the different sampling sites, nor the distance related to anthropogenic contaminants appeared strongly linked to biological distances, whereas geographical distances demonstrated stronger links with biological ones. This observation tends to demonstrate that, in this contaminated sediment, local selective pressures are stronger than the dispersal rate of benthic microbial communities, in spite of the very limited geographic scale. The positive relationship between biological distances and the chemical distance related to sediment type (including its marine or terrestrial origin) suggests that benthic microbial dispersal would be limited to sediment transport processes, which could promote strong spatial differentiation. However, the high connectivity through the water column within this marine coastal area, with a mean annual water exchange time of 3.4 days, makes this hypothesis unlikely [START_REF] Dufresne | Wind-forced circulation model and water exchanges through the channel in the Bay of Toulon[END_REF]. Thereafter, high dispersal but low survival of benthic microorganisms, because of major chemical shifts between the origin and end point environments, appears to be a more reliable hypothesis. Future deep taxonomic investigations will help to test these two hypotheses.

Thus, when facing the complexity of chemical variable interactions, such as the antagonistic effects of nutrients and pollutants, an in-depth geochemical characterization of the environment appears useful for providing a holistic and detailed chemical signature of the samples. Then comparing this global chemical signature to other environmental constraints, such as biotic interactions, appears to be a promising approach to understanding the ecology of microorganisms and the influence of the human footprint on ecosystem functioning.

Another striking result of this study came from multivariate analyses and linear regression analyses to evaluate the relative contributions of different variable classes to the observed biological variation. Among the abiotic parameters measured, metallic contamination clearly appeared to be an influential factor in shaping benthic prokaryote community structure in Toulon Bay. Indeed, as demonstrated by partial CCA results, at least 26% of the spatial variation in bacterial and archaeal community structure could be explained by a selection of trace metal contaminants. The gradient of benthic contamination in Toulon Bay by such pollutants includes both very low concentrations (i.e., close to the geochemical background of the region) and dramatic enrichments (e.g., Hg contamination), when compared with other ecosystems (for a more detailed comparison, see [START_REF] Tessier | Study of the spatial and historical distribution of sediment inorganic contamination in the Toulon bay (France)[END_REF]. Then, considering the panel of potential toxic effects these pollutants are known to have on microorganisms (for review, see [START_REF] Gadd | Microbial interactions with tributyltin compounds: detoxification, accumulation, and environmental fate[END_REF][START_REF] Nies | Microbial heavy-metal resistance[END_REF], observing biological gradients in Toulon Bay appears logical. These results supported the intention to use bacterial communities as sensitive indicators of contaminant stress for use as an environmental monitoring tool [START_REF] Sun | Bacterial communities are sensitive indicators of contaminant stress[END_REF]. However, we did not observe any reduction in prokaryotic T-RF richness where trace metals and organometallic substances were the most enriched. On the contrary, we observed higher bacterial richness in the north-western bay, the most polluted area. This observation was confirmed by numerous positive, strong and significant correlations of T-RF richness with the concentrations of metallic and organometallic pollutants. In the same way, strong and positive correlations were also observed between T-RF richness and the toxic potential of the sediment estimated by the m-ERM-Q. However, caution is needed as this index is based on the sensitivity of macroorganisms rather than that of microorganisms [START_REF] Long | Predicting toxicity in marine sediments with numerical sediment quality guidelines[END_REF]. Therefore, m-ERM-Q is not well suited for predicting microbial community responses to chemical contaminations. Whereas metals and organometallic substances are well known for their toxic effects, their high concentrations were associated with a higher microbial richness. This striking relation tends to contradict the global erosion of marine biodiversity caused by anthropogenic inputs in the marine environment [START_REF] Johnston | Contaminants reduce the richness and evenness of marine communities: A review and meta-analysis[END_REF]. However, the responses of microbial diversity to contaminants are more complex than those of marine macrobiota and similar observations have been reported in other marine coastal sediments [START_REF] Ben Said | Changes of benthic bacteria and meiofauna assemblages during bio-treatments of anthracene-contaminated sediments from Bizerta lagoon (Tunisia)[END_REF][START_REF] Li | Impacts of mariculture on the diversity of bacterial communities within intertidal sediments in the Northeast of China[END_REF][START_REF] Paissé | Structure of bacterial communities along a hydrocarbon contamination gradient in a coastal sediment[END_REF].

One way to explain this contradiction relies on the intermediate disturbance hypothesis (IDH), which predicts the highest diversity for disturbances of intermediate frequency and intensity [START_REF] Connell | Diversity in tropical rain forests and coral reefs[END_REF]. Indeed, although concentrations of the pollutants observed in Toulon Bay can strongly disturb macroorganisms due to bioaccumulation and lower reproduction rates, they may induce a lower disturbance to the microbiota that grow faster and is able to resist and transform metal and organo-metallic substances [START_REF] Nies | Microbial heavy-metal resistance[END_REF].

Moreover, the most enriched pollutants in the sediments of Toulon Bay are historical contaminants that have been present in excess for several decades [START_REF] Pougnet | Sources and historical record of tin and butyl-tin species in a Mediterranean bay (Toulon Bay, France)[END_REF][START_REF] Tessier | Study of the spatial and historical distribution of sediment inorganic contamination in the Toulon bay (France)[END_REF]. This stability of the contamination level at the scale of microbial lifetime could therefore no longer represent a disturbance with respect to the IDH. Indeed, the bacterial community might have evolved and could now be particularly adapted to such an environmental stress, as observed in similar ecosystems impacted by metallic pollutions (e.g. [START_REF] Besaury | Abundance, activity, and diversity of archaeal and bacterial communities in both uncontaminated and highly copper-contaminated marine sediments[END_REF]. In chronically polluted systems, diversity indexes may be a nonadapted indicator of ecosystem stress as it can recover due to the divergence and proliferation of tolerant species [START_REF] Gillan | Structure of Sediment-Associated Microbial Communities along a Heavy-Metal Contamination Gradient in the Marine Environment[END_REF].

Organic contaminants appeared to be a less influential environmental stress on benthic prokaryote communities than metallic and organo-metallic contaminations in Toulon Bay sediments by statistic disentangling. Indeed, only a few links between organic contamination and prokaryote T-RF richness were observed in the sediment of Toulon Bay. Moreover, the contribution of organic contaminants to beta diversity patterns appeared limited. This observation is quite surprising when considering the relatively high concentrations measured in comparison to other sites and with reference to sediment quality guidelines (e.g. [START_REF] Gao | Evolution of trace metal and organic pollutant concentrations in the Scheldt River Basin and the Belgian Coastal Zone over the last three decades[END_REF][START_REF] Long | Predicting toxicity in marine sediments with numerical sediment quality guidelines[END_REF]Wolska et al., 2014). Moreover, several studies reported decreases, or at least very significant shifts, in microbial diversity in response to PAHs or PCBs contamination (e.g. [START_REF] Correa | The effects of individual PCB congeners on the soil bacterial community structure and the abundance of biphenyl dioxygenase genes[END_REF][START_REF] Guazzaroni | Metaproteogenomic insights beyond bacterial response to naphthalene exposure and bio-stimulation[END_REF]. This could be explained by the difference of more than one order of magnitude observed between the respective extents of contamination gradients of metallic and organic pollutants. The influence of organic contamination could thus be hidden by that of toxic trace metals.

Nevertheless, as for trace metals, organic contaminations appeared to be positively related to prokaryote T-RF richness in Toulon Bay. Similar observation were previously reported in other ecosystems [START_REF] Bengtsson | Microbial diversity and PAH catabolic genes tracking spatial heterogeneity of PAH concentrations[END_REF], which could indicate a characteristic feature of contaminated sites with multiple contaminant types. Indeed, microorganisms are also known for their ability to grow on organic substrates, and especially PAH. Organic and more or less biodegradable contamination could thus increase the diversity of carbon resources for heterotrophic prokaryotes, creating new ecological niches. Thus, in agreement with IDH, organic contamination could partly explain the higher microbial richness found in the northwestern part of the bay as previously demonstrated [START_REF] Bengtsson | Microbial diversity and PAH catabolic genes tracking spatial heterogeneity of PAH concentrations[END_REF]. Organic contamination could actually counterbalance the degradation of microbial diversity that could occur because of toxic metal enrichment, and finally reduce the extent of disturbance of these microorganisms. T-RF richness and the chemical substances measured is counterbalanced by the explanation of 26% to nearly 50% of the spatial variation of archaeal community structure by anthropogenic contaminants, as observed for the bacterial community. This observation could indicate that, whether or not the richness of the community was only poorly affected, its composition was likely more affected. From an ecological point of view, metal resistance in archaea and bacteria involves similar enzymatic responses [START_REF] Bini | Archaeal transformation of metals in the environment[END_REF], but archaea are known to predominate in extreme environments, especially where they are exposed to particularly high metal stress as in extremely acidic ecosystems [START_REF] Baker | Microbial communities in acid mine drainage[END_REF][START_REF] Bini | Archaeal transformation of metals in the environment[END_REF][START_REF] Edwards | An Archaeal Iron-Oxidizing Extreme Acidophile Important in Acid Mine Drainage[END_REF]. The question arises as to whether archaeal communities could present different and more widespread adaptive strategies than bacterial communities when facing multi-contaminations, especially the combination of organic, organometallic and inorganic contaminants. Further inventories of structural and functional diversity of bacteria and, above all, archaea are now required to explain the different trends we observed in this study between these communities.

Whether inorganic, organometallic or organic, the influence of a pollutant or chemical cocktail depends on its bioavailability. Although not studied in this work, Dang et al. (2014bDang et al. ( , 2015a) ) have previously demonstrated that trace metals and metalloids could be highly mobilized from particles to pore water in surface sediments (0-10 cm), and that this mobilization could vary throughout the year. This suggests a potentially high bioavailability of inorganic contaminants in the sediment of Toulon Bay, and tends to support the hypothesis of welladapted communities. Thus the observed link between the mobility of inorganic contaminants and diagenesis activity throughout the seasons (Dang et al., 2014b(Dang et al., , 2015a) also suggests that, in addition to being well adapted, microbial communities could drive the fate of these contaminants in the sediments of Toulon Bay. Now, investigating microbial community composition and focusing on functional communities with higher resolution methods under controlled conditions could help to shed the light on these different interactions between chemical contamination and microbial communities, as well as on potential cross-interactions between contaminant types.

CONCLUSION

Through this study, we have demonstrated the strong influence of the sediments' chemical signature on marine coastal benthic prokaryotic community diversity. In the sediments of Toulon Bay, the influence of such a chemical signature appeared to be mainly related to contamination gradients of trace metal and organo-metallic compounds, which proved to be strongly related to spatial variation in alpha and beta diversity of bacteria, and to a lesser extent, of archaea. Although bacterial and archaeal diversity appeared to be linked to this chemical signature, the major contamination gradients in Toulon Bay surface sediments did not appear to have resulted in diversity loss. On the contrary, bacterial richness seemed to be higher in the most polluted areas. The underlying ecological adaptive processes and the cross interactions between the multiple pollutant classes now require further clarification.

The current socio-economical context leads more and more scientists to focus on the consequences of human-related inputs for the environment, and especially on the threat they represent to living organisms and natural communities. For instance, it was recently demonstrated that the high Pb levels observed both in farmed and wild mussels from Toulon Bay, mostly originate from Pb sediment contamination, evidencing a clear link between the contaminated abiotic compartment and biotic species (Dang et al., 2015b). However, microorganisms are also well known for their role in the transformation of chemical contaminants, and especially in the geochemistry of toxic trace metals. Our work, in which no apparent toxic effect was observed in spite of very high contamination levels, reminds us how difficult it can be to evaluate which component, i.e., the chemical or the microbiological environment, influences the other to the greatest extent, even in multi-contaminated sites.

The microbial contribution to the geochemical cycles of trace metals is still of major interest, and this study illustrates the need for better understanding to fully elucidate the consequences of toxic trace metal inputs to biodiversity. Further in-depth analyses of structural and functional diversities within microbial communities will help in identifying key species and adaptive mechanisms.

Chemical parameters

  Using a principal component analysis (PCA) on 2 chemical characteristics (PIC, POC) and 31 major/minor/trace elements (Ag, Al, As, Ba, Be, Bi, Ca, Cd, Co, Cr, Cs, Cu, Fe, Hg, K, Li, Mn, Mo, Ni, P, Pb, Rb, S, Sb, Sn, Sr, Ti, Tl, U, V and Zn) from 130 surface and deep sediments from Toulon Bay,Dang et al. (2015a) have evidenced 6 groups of elements: (1) the "marine" originated elements (Ca, PIC and Sr), (2) the "terrigenous" elements, mainly representing clays (Al, Be, Cs, Fe, K, Li and mainly of anthropogenic origins (Ag, Ba, Bi, Cd, Cu, Hg, P, Pb, Sb, Sn, Ti and Zn), (4) inorganic trace elements having mainly "natural" origin, from terrigenous inputs (Co, Mo, Ni, Tl, U and V), (5) elements showing "mixed" anthropogenic and terrigenous origins (As, Cr, Mn and S), and (6) the POC. To illustrate these co-variations, the observed relationship between PIC and Ca, Rb vs. Al, Bi vs. Pb, Co vs. Ni and As vs. Cr in the surface sediments dataset considered in the present study are shown in Fig.SI-1. In order to reduce the number of chemical variables for further statistical analysis, the elements of "marine" origin were then only represented by Ca, the "terrigenous" elements by Al and Fe, and the trace elements of "natural" origin by Co and Ni, when POC, "inorganic contaminants" and trace elements of "mixed" origin were all taken into consideration. Then, a 7 th group of "organometallic contaminants" was defined using: monomethylmercury (MMHg), tributyltin (TBT) and the sum of butyltin-species ( BT). Significant relationships observed between TBT and BT, and MMHg and Hg (Fig.SI-2) were evidenced by[START_REF] Pougnet | Sources and historical record of tin and butyl-tin species in a Mediterranean bay (Toulon Bay, France)[END_REF][START_REF] Cossa | A Michaelis Menten type equation for describing methylmercury dependence on inorganic mercury in aquatic sediments[END_REF] and suggested the strong influence of microbial communities on the sedimentary dynamics of these species. Finally, an 8 th group included the "organic contaminants" (PAHs and PCBs). Considering the significant correlations (R² ranging from 0.86 to 0.98 and from 0.95 to 0.99 for PAHs and PCBs respectively, data not shown) observed between each of the 17 measured PAHs and their sum ( PAH), and between each of the 8 measured PCBs and their sum ( PCB), the present study only considered the following chemical variables: PAH, PCB, Fluoranthene and CB-153 (being the most abundant PAH and PCB, accounting on average for 16% and 29% (N=26) of the PAH and PCB, respectively; figure SI-3).

  Organic contaminations followed moderate to strong gradients with approximately 15 to 89fold content ranges for PAH (figure SI-4B), fluoranthene, POC, CB-153 (figure 2C) and PCB, respectively (table 1). Most of the natural or mixed trace elements and inorganic, organometallic or organic contaminants presented similar distribution, their content values being the highest in the northern part of LiB and gradually decreasing toward the south-east and the open sea (for representative examples, see figures 2B, 2C and SI-4A). Tin, POC fluoranthene and PAH did not follow this trend, presenting more random variations (figure SI-4B). Considering most of these representative physical-chemical parameters together (except for TBT, BT, fluoranthene, PAH, CB-153 and PCB, which were not measured in all of the sampling sites), spatial variations in the global chemical signature of the sediment (i.e.considering all 8 of the clusters identified above) were assessed by calculating Gower similarities. This distance analysis demonstrated important variations of sediment chemical composition with reference to the less contaminated sites (two stations located south-east and south-west of Toulon bay, respectively, away from most of the human activities centers), with an offshore-to-coast gradient following the distribution of the main contaminants (figure2D). Very important shifts of chemical signature were especially recorded in LiB, the most anthropized area, resulting in a very low degree of similarity (decreasing to 28%) compared with the mouth of the bay. Similar gradients were globally observed when computing Gower distances for the chemical signatures of the sediment type and the anthropogenic contaminants, with significant local shifts observed mainly in the northern LiB and near the coasts of St.(figure SI-4C and D). Specific distance assessments with fewer sampling points to include organic contaminants (24 sampling sites) or TBT and BT (29 sampling sites) confirmed this trend (data not shown).

  The chemical gradients observed in the sediment of Toulon Bay did not present the same relations with the archaeal and bacterial benthic communities. This observation suggests differential responses of bacteria and archaea to this kind of chemical contamination. The spatial variations of archaeal T-RF richness were weaker than for bacteria, without a significant increase in the most polluted area, and demonstrated fewer and weaker links to the abiotic variables recorded, especially those corresponding to the sediment origin or to biologically relevant substances (POC, S and Mn). Although the low number of archaeal T-RFs detected could raise some methodological concerns, such as partial recovery of the archaeal community, the validation of the method in various previous studies (e.g.[START_REF] Stevenson | Temporal and seasonal change in microbial community structure of an undisturbed, disturbed, and carbon-amended pasture soil[END_REF] tends to invalidate this argument. Moreover, the weak relation between archaeal

FIGURE CAPTIONS Figure 1 .

 CAPTIONS1 FIGURE CAPTIONS

Figure 2 .

 2 Figure 2. Examples of benthic abiotic spatial gradients in the Toulon bay. A, B, C: contents

Figure 3 .

 3 Figure 3. Spatial variations of prokaryotic richness and community structure in surface

Figure 4 .

 4 Figure 4. PCoA of bacterial (A) and archaeal (B) communities using Bray-Curtis distances,

  Figure captions Click here to download Figure: figure captions_151030.docx

. DNA extraction and prokaryotic fingerprinting

	of these protocols was validated using certified material (MRC 1941b and MRC 1944 for
	PAHs and CBs, respectively).
	2.3DNA was extracted from aliquots of lyophilized sediments (kept frozen at -20°C) from 38
	samples from among the 54 described above (figure 1), covering the whole range of main
	sediment characteristics and chemical contaminants levels. Extractions were performed
	using the Power Soil DNA Extraction Kit (Mobio Laboratories, Carlsbad, CA) following the
	manufacturer's recommendations. Terminal Restriction Fragment Length Polymorphism (T-
	RFLP) profiling was conducted on each sample after 16S rRNA gene amplification using
	primers 8F (Lane, 1991)/519R (Frank et al., 2013) labeled with FAM (5-carboxyfluorescein)
				) were
	analysed for 17 PAHs (Acenaphthene, Anthracene, Benz[a]anthracene, Benzo[a]pyrene,
	Benzo[b]fluoranthene,	Benzo[ghi]perylene,	Benzo[k]fluoranthene,	Chrysene,
	Dibenz[a,h]anthracene, Fluoranthene, Fluorene, Indeno[1,2,3-cd]pyrene, Naphthalene,
	Phenanthrene, Pyrene, 2-methylfluoranthene, 2-methylnaphthalene) and 8 PCBs (CB-28,
	CB-31, CB-52, CB-101, CB-118, CB-138, CB-153, CB-180), accordingly to the French
	standard AFNOR XP X33-012. Briefly, PAHs were extracted from 4 g of sediment using a
	mixture of hexane/acetone (50:50) assisted by ASE (ASE 200, Dionex), the obtained extract
	was then purified by solid-phase extraction (SPE, ASPEC XL, Gilson), concentrated (50°C
	under N 2 flux), adjusted to 5 mL with acetonitrile/water (50/50) and PAHs concentrations
	were analysed by HPLC (Shimadzu, Prominence UFLC) with UV and fluorescence detection.
	Concerning PCBs, they were extracted from 7 g of sediments by using a mixture of
	hexane/acetone (50:50) assisted by ASE (ASE 200, Dionex) in the presence of 1g of Cu
	powder. The obtained extract was then purified on SPE (ASPEC XL, Gilson), concentrated
	(50°C under N 2 flux), and adjusted to 1 mL with hexane. CBs concentrations were analysed
	by GC/MS (Thermoelectron, Polaris Q) in negative chemical ionization mode. The accuracy

here to download Table: table 2.docx

	Table2
	Click Sn	ns	ns
		Ti	ns	ns
		Zn	0.44**	0.48**
		MMHg	0.38*	0.59***
	Organometallic
	contaminants	TBT	Archaea 0.06*	Bacteria 0.73***
	Marine	Ca BT	ns 0.47*	-0.38* 0.73***
		Al Fluoranthene	0.35* ns	0.54*** ns
	Terrigeneous Organic	Fe	0.36* ns	0.48** ns
	contaminants	Co CB-153	ns ns	ns 0.47*
	Natural	Ni	ns ns	0.35* 0.47*
	Organic matter	As POC	ns ns	0.38* ns
	Sediment	Cr Metal based m-ERM-Q	0.33* 0.42**	0.54*** 0.55***
	Mixed potential toxicity	Mn m-ERM-Q with PAHs	ns 0.50*	ns ns
		S	ns	0.57***
		Ag	0.41*	0.70***
		Ba	ns	ns
		Bi	0.50**	ns
	Inorganic	Cd	ns	ns
	contaminants	Cu	0.39*	0.55***
	(EF)	Hg	0.41*	0.51**
		P	ns	ns
		Pb	0.45**	ns
		Sb	ns	ns

ACKNOWLEDGEMENTS

This study was performed in the framework of MerMex-WP3-C3A research program (part of the international IMBER project), CARTOCHIM and CARTOC research programs (funded by "Toulon-Provence--Méditerranée et Corse"). The authors wish to thank the French Navy for diving and sampling assistance as well as the LASEM-Cherbourg laboratory (Aline Olivier, Laurent Lacombe) for

PAHs and CBs analysis on sediments. We acknowledge the technical assistance of Claire Gassie (EEM) and the Regional Platform for Environmental Microbiology PREMICE supported by the Aquitaine Regional Government Council (France), the urban community of Pau-Pyrénées (France) and the CNRS. The English grammar and syntax of the manuscript have been revised by Proof-Reading-Service.com


Léa Cabrol
email: lea.cabrol@mio.osupytheas.fr

Marianne Quéméneur

Benjamin Misson

Inhibitory effects of sodium azide on microbial growth in experimental resuspension of marine sediment

Keywords:

Sodium azide (NaN 3 ) was evaluated as inhibitor of microbial growth and activity in marine sediment resuspensions by monitoring the abundance of free-living and sessile bacteria using both flow cytometry and qPCR methods. Results show that 50 mM of NaN 3 strongly inhibits bacterial growth under natural and enriched resource conditions.

Microbial communities play key roles in biogeochemical cycles of contaminants, affecting their fate by degradation, (de)sorption, redox transformations, albeit often in a still poorly understood way. In order to identify clearly the role of microbial communities in contaminant dynamics (e.g. trace metal cycling and mobility) and to distinguish biological and physicochemical contributions, it is crucial to develop experimental incubations under controlled conditions, to enable comparison of biotic microcosms with abiotic controls (i.e. where microbial growth and activity have been inhibited). However, in the complex matrices of contaminated ecosystems, the sterilization method must be chosen cautiously in order not to interfere with abiotic drivers of contaminant dynamics.

Several chemical and physical methods exist to sterilize various kinds of materials, based on heat, chemicals, antibiotics, filtration or radiations. Among physical methods, steam sterilization through autoclaving is the most widespread technique but it has several drawbacks when focusing on contaminant fate, such as: disruption of the physical structure of soils and sediments [START_REF] Ramsay | Effect of sterilization and storage on respiration, nitrogen status and direct counts of soil bacteria using acridine orange[END_REF][START_REF] Trevors | Sterilization and inhibition of microbial activity in soil[END_REF]; release of dissolved metals and nutrients [START_REF] Quéméneur | Bacterial community structure and functional arrA gene diversity associated with arsenic release and reduction in an industrially contaminated soil[END_REF][START_REF] Senko | Characterization of Fe(II) oxidizing bacterial activities and communities at two acidic Appalachian coalmine drainage-impacted sites[END_REF]; desorption of organic compounds acting as possible metal ligands and modification of metal speciation [START_REF] Egli | Influence of steam sterilisation on soil chemical characteristics, trace metals and clay mineralogy[END_REF]. γ-irradiation is considered as an alternative technique, but it is generally less easily available, requires long stabilization times [START_REF] Ramsay | Effect of sterilization and storage on respiration, nitrogen status and direct counts of soil bacteria using acridine orange[END_REF], and creates reactive redox agents that may induce abiotic reactions with metals [START_REF] Trevors | Sterilization and inhibition of microbial activity in soil[END_REF][START_REF] Bank | Effects of gamma-sterilization on the physico-chemical properties of natural sediments[END_REF]. Both γ-irradiation and autoclaving altered soil organic matter chemistry (functional group identity and abundance), thus affecting pollutant sorption, affinity and bioavailability [START_REF] Brickett | Comparison of methods used to inhibit bacterial activity in sulfide ore bioleaching studies[END_REF][START_REF] Kelsey | Sterilization affects soil organic matter chemistry and bioaccumulation of spiked p,p′-DDE and anthracene by earthworms[END_REF]. Among chemical agents, methyl bromide, formaldehyde or mercuric chloride are efficient microbial inhibitors [START_REF] Trevors | Sterilization and inhibition of microbial activity in soil[END_REF], but they contaminate the matrix with toxic residues, including metals, complexing agents, and oxidizing/reducing compounds, making them unsuitable for the investigation of contaminant dynamics, especially trace metals [START_REF] Brickett | Comparison of methods used to inhibit bacterial activity in sulfide ore bioleaching studies[END_REF].

Among chemical poisons, sodium azide (NaN 3 ) is a strong metabolic inhibitor of the respiratory chain [START_REF] Lichstein | Studies of the effect of sodium azide on microbic growth and respiration. I. The action of sodium azide on microbic growth[END_REF], used in various matrices to prepare abiotic controls avoiding physicochemical alterations, especially when studying metal-polluted matrices. NaN 3 is known to inhibit microbial growth and distinct microbial activities, such as MTBE degradation [START_REF] Hanson | Biodegradation of methyl tert-butyl ether by a bacterial pure culture[END_REF], manganese-, iron-, and sulfur-oxidation in pure cultures and metal-contaminated river-sediments [START_REF] Burton | Iron-monosulfide oxidation in natural sediments: resolving microbially mediated S transformations using XANES, electron microscopy, and selective extractions[END_REF][START_REF] Wang | Removal of multi-heavy metals using biogenic manganese oxides generated by a deep-sea sedimentary bacterium -Brachybacterium sp. strain Mn32[END_REF]; PAH-degradation activity in wetland sediments [START_REF] Beckles | Effect of mixtures of polycyclic aromatic hydrocarbons and sediments on fluoranthene biodegradation patterns[END_REF] and sulfate-reducing bacterial enrichment cultures [START_REF] Tsai | Anaerobic biotransformation of fluorene and phenanthrene by sulfate-reducing bacteria and identification of biotransformation pathway[END_REF]; mercury methylation and demethylation in lake sediments [START_REF] Zhang | Biotic and abiotic mercury methylation and demethylation in sediments[END_REF]. In these studies, NaN 3 concentration usually ranged between 1 and 150 mM. However, the efficiency of NaN 3 depends on its concentration and the environmental matrix properties, and few studies have quantified its inhibitory effect on microbial growth in marine matrices, especially in the presence of sediments.

The objective of this study is to evaluate the efficiency and the dose effect of NaN 3 in inhibiting microbial growth and activity during resuspension of marine sediment in seawater. The susceptibility of microbial communities was compared under natural-and enriched-resource supply conditions, representative of normal and nutrient rich environments. Moreover, both free-living and sessile microbes were targeted since both life forms are known to occur naturally in marine environments.

Surface seawater and surface (0-5 cm) marine sediments were collected in the northern part of the multicontaminated Toulon Bay (France). The sampling procedure and sampling site characteristics (MIS station) are detailed elsewhere [START_REF] Dang | Evidencing the impact of coastal contaminated sediments on mussels through pb stable isotopes composition[END_REF]. Chemical and biological characteristics of water and sediment samples from the same sites at a similar period of the year were previously described (Misson et al., 2016, Coclet et al., submitted).

Sediments and sea water were aerobically mixed at a solid/liquid ratio of 30 g L -1 (wet weight). Thirty milliliters of the sediment suspension were incubated in sterile 50 mL tubes at ambient temperature, in the dark, under continuous overhead shaking (15 rpm, Heidolph Reax 20) during 11 days. Tubes were frequently opened under sterile conditions to ensure sufficient oxygenation along the experiment. Two series of experiments were conducted. First, the inhibitory effect of a common NaN 3 concentration (50 mM) was evaluated under natural resource conditions, by comparison with unpoisoned control. Secondly, the inhibitory effect of low (5 mM) and high (50 mM) NaN 3 concentrations was evaluated under growth-promoting conditions (addition of 0.1× of Luria-Bertani (LB) broth and 1 g L -1 glucose), by comparison with unpoisoned control under the same nutrient-rich conditions. Each condition was done in triplicate. pH was measured in the suspension at the beginning (T 0 ), after 2 h, 4 days, and at the end (T f ) of the incubations using a Cyberscan 510 (Eutech) probe.

In the suspended phase, free-living prokaryote abundance and activity (esterase assay) were estimated at T 0 , after 2 h, 4 days and at T f by flow cytometry. One mL sediment suspension aliquots were centrifuged (2′, 800 g) to remove the largest particles. The supernatant was analyzed with an Accuri C6 flow cytometer (BD), total heterotrophic prokaryotes being enumerated after SYBR green staining (0.5 × final concentration) and active prokaryotes being enumerated after CFDA staining (10 μM final concentration) according to previous work [START_REF] Grégori | Resolution of viable and membrane-compromised bacteria in freshwater and marine waters based on analytical flow cytometry and nucleic acid double staining[END_REF].

For sedimentary microbial abundance quantification, 20 mL-samples of the sediment suspension were collected at initial and final days from all incubations, centrifuged at 10.000 rpm for 15 min, and the pellets were stored at -20 °C until DNA extraction. Total genomic DNA was extracted from the pellets (app. 325 mg) with PowerSoil DNA Isolation Kit (MoBio Laboratories, Carlsbad, CA, US). Bacterial abundances were quantified by real-time PCR (CFX96, Bio-Rad Laboratories) of 16S rRNA gene fragments, with GoTaq qPCR Master Mix (Promega), using GML5F and Univ516 primers, as described previously [START_REF] Duran | Effect of physical sediments reworking on hydrocarbon degradation and bacterial community structure in marine coastal sediments[END_REF].

Under natural resource conditions, and without addition of NaN 3 , the abundance of free-living prokaryotes in the suspended phase showed an 8-fold increase compared to T 0 during the first four days, prior to returning to the initial level by T f (Fig. 1A), probably as a result of resource depletion or predator-prey succession [START_REF] Sauret | Top-down control of diesel-degrading prokaryotic communities[END_REF]. The number of CFDA-degrading (active) free-living prokaryotes followed a similar pattern, although their transient increase was limited to 4fold (Supplementary information SI.1A). In the sedimentary phase, the number of bacterial 16S rRNA gene copies increased by a factor of 9 between T 0 and T f (Fig. 2), confirming global bacterial growth and indicating different dynamics between free-living and sessile prokaryotes.

When NaN 3 was added at 50 mM, the growth of free-living prokaryotes was inhibited throughout the experiment (Fig. 1A) and free-living active cells were less numerous (4-fold decrease compared to T 0 ) as soon as 2 h after poisoning, maintaining this low level until the end of incubation (Fig. SI.1A). Moreover, sessile bacterial 16S rRNA gene copy number demonstrated a 4-fold decrease between T 0 and T f (Fig. 2). Therefore, under natural resource conditions, NaN 3 at 50 mM was found to efficiently inhibit microbial growth and activity in both suspended and sediment phases.

However, NaN 3 efficiency required further evaluation under rich substrate conditions favoring microbial growth. Depending on the matrix properties, high NaN 3 concentration may induce physicochemical interactions with contaminant dynamics, through -for example-abiotic CO 2 and volatile acid evolution as well as pH rise, as evidenced in soil when NaN 3 concentration exceeded 77 mM [START_REF] Rozycki | Problems associated with the use of azide as an inhibitor of microbial activity in soil[END_REF]. It is thus important to assess if lower NaN 3 concentrations have sufficient inhibitory effect, even under rapid growth-promoting conditions.

Under simulated nutrient rich conditions (LB and glucose addition), microbial growth was strongly enhanced in both suspended and sediment compartments, in absence of NaN 3 poisoning. A continuous increase was observed for both total (Fig. 1B) and active (Fig. SI•1B) free-living cell abundance, exceeding 1000-fold enrichments between T 0 and T f . Sessile bacteria 16S rRNA gene copy number also increased by a factor larger than 1000 between T 0 and T f (Fig. 2).

Under high resource availability, the use of 5 mM NaN 3 (i.e. in the low range of reported concentrations in the literature) reduced the planktonic and sessile biomass growth (by a factor 100 compared to the unpoisoned condition) but was not sufficient to completely inhibit microbial growth and activity in either suspended or sediment phases. Indeed, growth was only slowed down and delayed by the addition of NaN 3 at 5 mM, which still allowed a 22-fold increase of free-living prokaryote abundance (Fig. 1B), a 50-fold increase in active free-living cell number (Fig. SI•1B), and a 12-fold increase of bacterial 16S rRNA gene copy number, between T 0 and T f (Fig. 2). The efficiency of NaN 3 is reported to be dose-dependent: it was for example less efficient (at 20 mM) than other chemicals (acetonitrile) to inhibit dehydrogenase activity in river sediments [START_REF] Mosher | A simplified dehydrogenase enzyme assay in contaminated sediment using 2-(p-iodophenyl)-3(p-nitrophenyl)-5-phenyl tetrazolium chloride[END_REF], while it had only a partial inhibition effect (at 1 mM) on manganese reduction in pure bacterial cultures, lower than other metabolic poisons (formaldehyde, antimycin, CCCP) under anaerobic conditions [START_REF] Myers | Bacterial manganese reduction and growth withmanganese oxide as the sole electron acceptor[END_REF].

By contrast, the addition of 50 mM NaN 3 resulted in a 1000-fold reduction of planktonic and sessile bacterial growth compared to the unpoisoned condition. Despite growth-favoring conditions, the addition of 50 mM NaN 3 led to a stable number of free-living active cells during the whole incubation (Fig. SI•1B) and a slight (3-fold) decrease of sessile bacterial 16S rRNA gene copy number between T 0 and T f (Fig. 2). However, a minor (2-fold) increase of free-living prokaryote abundance was still observed during the incubation (Fig. 1B). The fact that the abundance of sessile bacteria not only remained constant (indicating impediment of growth), but in some cases decreased during the incubation (in presence of NaN 3 at 50 mM, independently of the substrate conditions) suggests that NaN 3 not only suppressed microbial growth but may also have lysed a fraction of the initial indigenous cells. When considering the active fraction of free-living prokaryotes, NaN 3 (at both tested concentrations) seemed to have a stronger transient inhibitory effect at short term, i.e. resulting in a loss of active cells (by a factor 4 to 14) during the first two hours, before further increase (Supplementary Fig. S1).

In absence of NaN 3 , pH dropped from 8.3, at T 0 , to 7.3 ± 0.2 and 7.6 ± 0.2, at T f (respectively with and without nutrient enrichment), as a result of microbial activity. Under growth favoring conditions, the addition of 5 mM NaN 3 did not modify the amplitude of pH drop (decreasing to 7.2 ± 0.1 at T f ), while the addition of 50 mM NaN 3 resulted in a less marked pH decrease compared to the unpoisoned control (down to 7.7 ± 0.0 at T f ), thus confirming the partial efficiency of 5 mM NaN3 and the better reduction of microbial activity in presence of 50 mM NaN 3 . The difference of pH between T 0 and 50 mM NaN 3 condition may be due to (i) residual microbial activity or (ii) abiotic effect of NaN 3 . Thus, in nutrient rich environments, 50 mM NaN 3 appears efficient for complete inhibition of growth of sessile bacteria over 11 days (contrary to 5 mM NaN 3 ), but failed to totally inhibit free-living prokaryote growth, as a small fraction of free-living cells remained active and able to grow. Therefore, the use of NaN 3 to perform abiotic controls in microcosm experiments appears feasible when employed at sufficiently high concentration (≥50 mM) for short term incubations, depending on resources availability. NaN 3 poisoning is considered as relatively benign in terms of metal interactions and abiotic oxidation processes (precipitation, leaching…) even in metal-contaminated matrices [START_REF] Neubauer | Life at the energetic edge: kinetics of circumneutral iron oxidation by lithotrophic iron-oxidizing bacteria isolated from the wetland-plant rhizosphere[END_REF][START_REF] Rentz | Control of ferrous iron oxidation within circumneutral microbial iron mats by cellular activity and autocatalysis[END_REF]. Although the present study demonstrates the inhibition efficiency of NaN 3 on microbial growth and activity, its potential physicochemical effects on the geochemistry of the samples should be further evaluated according to the targeted contaminant, the poison concentration, and the matrix properties. For example, NaN 3 reacts chemically with some organic compounds, such as atrazine, and thus should not be used to prepare abiotic controls in atrazine degradation studies [START_REF] Chefetz | Interactions of sodium azide with triazine herbicides: effect on sorption to soils[END_REF].

Supplementary data to this article can be found online at http://dx. doi.org/10.1016/j.mimet.2016.12.021.

Fig. 1 .

 1 Fig. 1. Abundance of free-living prokaryotes in the suspended phase, quantified by flow-cytometry along incubation time, under (A) natural resource conditions and (B) nutrient-rich conditions (supplemented LB and glucose medium), in absence of NaN 3 , and in presence of NaN 3 at 5 mM and 50 mM. Each point represents the average of triplicate incubations and error bars represent standard deviations.

L. Cabrol et al. / Journal of Microbiological Methods 133 (2017) 62-65

Acknowledgements

This study was financially supported by the French Research Institute for Development (IRD) (ACTION SUD-MIO) and the MerMex-WP3-C3A/MISTRALS research program (part of the international IMBER, LOICZ and SOLAS projects). The authors wish to thank Dr. C. Garnier, the French Navy and the LASEM for diving and sediment sampling assistance, as well as Sophie Guasco for technical support and Sean C. Smith for helpful correction of English wording.