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

Eric Capo
email: eric.capo@umu.se.

F a Bastiaan Daan M Van Vliet

Von Meijenfeldt

Stefan Bertilsson

Laura Villanueva

Irene Sánchez-Andrea

Erik Björn

Andrea G Bravo

Lars-Eric Heimburger Boavida

F A Bastiaan Von Meijenfeldt

Michael S Rappe

Bastiaan Von Meijenfeldt

Redox gradient shapes the abundance and diversity of mercury-methylating microorganisms along the water column of the Black Sea

Keywords: mercury methylation, diversity, hgcAB gene, metagenomics, redoxcline, niche partitioning, qPCR, MAGs

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

D ecades of anthropogenic emissions and widespread atmospheric dispersal make mercury (Hg) a contaminant of global concern [START_REF] Outridge | Updated global and oceanic mercury budgets for the United Nations global mercury assessment 2018[END_REF]. Hg can be transformed into the neurotoxin methylmercury (MeHg) and detected at high concentrations in certain marine ecosystems, where it bioaccumulates and biomagnifies, ultimately causing severe risks for humans [START_REF] Zhang | Global health effects of future atmospheric mercury emissions[END_REF]. The methylation of Hg II to MeHg is mainly mediated by microor ganisms and has primarily been described in anoxic environments such as wetlands, sediments, rice paddies, or animal gut [START_REF] Bravo | Biotic formation of methylmercury: a biophysico-chemical conundrum[END_REF]. Aside from the sine qua non presence and activity of microorganisms producing MeHg, Hg methylation is also controlled by Hg bioavailability, organic matter composition, and oxygen concentrations. Relatively high MeHg concentrations and Hg methylation potential have been reported in oxygen-deficient water columns [START_REF] Heimbürger | Methyl mercury distributions in relation to the presence of nanoand picophytoplankton in an oceanic water column (Ligurian Sea, North-Western Mediterranean)[END_REF][START_REF] Soerensen | Deciphering the role of water column redoxclines on methylmercury cycling using speciation modeling and observations from the Baltic Sea[END_REF]. However, there is still limited knowledge about the microbial key players involved in Hg methylation in marine ecosystems and the environmental conditions constraining their activity [START_REF] Yu | Microbial mercury transformations: molecules, functions and organisms[END_REF].

Microbial methylation of Hg has been shown to involve and rely on the enzyme coded by the gene pair hgcA and hgcB [START_REF] Parks | The genetic basis for bacterial mercury methylation[END_REF]. Microorganisms that harbor these genes (hgcAB gene-carrying [hgc + ] microorganisms), and the methylation capacity they provide, have been identified across diverse microbial lineages and different environ ments [START_REF] Capo | A consensus protocol for the recovery of mercury methylation genes from metagenomes[END_REF][START_REF] Mcdaniel | Expanded phylogenetic diversity and metabolic flexibility of mercury-methylating microorganisms[END_REF][START_REF] Podar | Global prevalence and distribution of genes and microorganisms involved in mercury methylation[END_REF]. Most cultivated lineages with experimentally validated Hg methylation capacity have been affiliated to sulfate-reducing, iron-reducing, and/or syntrophicfermenting bacteria from Desulfobacterota and Firmicutes, as well as to methano genic Archaea [START_REF] Bravo | Biotic formation of methylmercury: a biophysico-chemical conundrum[END_REF][START_REF] Gilmour | Mercury methylation by novel microorganisms from new environments[END_REF][START_REF] Gilmour | Robust mercury methylation across diverse methanogenic Archaea[END_REF]. Recent high-throughput sequencing analyses, including the reconstruction of metagenome-assembled genomes (MAGs) from environmental samples, have revealed a broader diversity of putative Hg methylators including previously unknown and largely uncultured hgc + microorganisms such as Planctomyce tota, Verrucomicrobiota, Chloroflexota, and Nitrospirota [START_REF] Capo | Oxygen-deficient water zones in the Baltic Sea promote uncharacterized Hg methylating microorganisms in underlying sediments[END_REF][START_REF] Jones | Molecular evidence for novel mercury methylating microorganisms in sulfate-impacted lakes[END_REF][START_REF] Peterson | Mercury methylation genes identified across diverse anaerobic microbial guilds in a eutrophic sulfate-enriched lake[END_REF][START_REF] Vigneron | Transcriptomic evidence for versatile metabolic activities of mercury cycling microorganisms in brackish microbial mats[END_REF], some of them being found abundantly in coastal and "dead zone" systems, such as the fully anoxic bot tom waters of a stratified fjord [START_REF] Podar | Global prevalence and distribution of genes and microorganisms involved in mercury methylation[END_REF], a seasonally anoxic fjord (Saanich Inlet) [START_REF] Lin | Mercury methylation by metabolically versatile and cosmopolitan marine bacteria[END_REF], and oxygen-deficient brackish water from the Baltic Sea [START_REF] Capo | Deltaproteobacteria and spirochaetes-like bacteria are abundant putative mercury methylators in oxygen-deficient water and marine particles in the Baltic sea[END_REF][START_REF] Capo | Expression levels of hgcAB genes and mercury availability jointly explain methylmercury formation in stratified brackish waters[END_REF]. These studies corrobo rate that the main methylators differ between ecosystems and along dominant redox gradients.

In the ocean, climate change and human activities lead to current-and further expected-seawater deoxygenation and expansion of oxygen-deficient zones [START_REF] Breitburg | Declining oxygen in the global ocean and coastal waters[END_REF]. The modification of redox gradients can dramatically affect microbial and biogeochemical cycles, including Hg transformations. Since the Black Sea is the largest and deepest permanently euxinic (anoxic and sulfidic conditions) stratified basin worldwide, with stable redox gradients extending over several tens of meters [START_REF] Wakeham | Organic biogeochemistry in the oxygen-deficient ocean: a review[END_REF][START_REF] Jürgens | Microbial ecology and biogeochemistry of oxygen-deficient water columns[END_REF], it is a promising target to study the partitioning of Hg-methylating microorganisms over contrasted redox niches. A stable permanent pycnocline prevents mixing and exchange between the upper oxygenated layers and anoxic deep waters, separated by a suboxic water layer extending from 75 to 120 m (down to 240 m at certain coastal stations) [START_REF] Glazer | Spatial and temporal variability of the Black Sea suboxic zone[END_REF]. In the Black Sea water column, high concentrations of MeHg concentrations have been reported in the suboxic and anoxic water layers [START_REF] Lamborg | Vertical distribution of mercury species at two sites in the Western Black Sea[END_REF][START_REF] Rosati | Mercury in the Black Sea: new insights from measurements and numerical modeling[END_REF]. The high horizontal (isopycnal) homogene ity of the Black Sea has been demonstrated, in terms of microbial community composi tion [START_REF] Zhang | Holistic pelagic biodiversity monitoring of the Black Sea via eDNA metabarcoding approach: from bacteria to marine mammals[END_REF], hydrography [START_REF] Zatsepin | Observations of Black Sea mesoscale eddies and associated horizontal mixing[END_REF], and geochemistry, including Hg chemistry [START_REF] Rosati | Mercury in the Black Sea: new insights from measurements and numerical modeling[END_REF]. However, the microorganisms involved in Hg methylation in the Black Sea water column have not been identified yet, neither the effect of the vertical stratification on their composition. As reported for other euxinic systems (e.g., Baltic Sea, Cariaco Basin, Saanich Inlet), it is plausible that the vertical gradient of oxygen and HS -concentrations in the Black Sea shapes the distribution of microbial communities, including those involved in MeHg formation, as well as their associated metabolic and biogeochemical functions [START_REF] Jürgens | Microbial ecology and biogeochemistry of oxygen-deficient water columns[END_REF][START_REF] Cabello-Yeves | The microbiome of the Black Sea water column analyzed by shotgun and genome centric metagenomics[END_REF][START_REF] Suominen | A diverse uncultivated microbial community is responsible for organic matter degradation in the Black Sea sulphidic zone[END_REF][START_REF] Van Vliet | The bacterial sulfur cycle in expanding dysoxic and euxinic marine waters[END_REF].

In this study, we aimed to determine the impact of the vertical redox gradient on the microorganisms potentially responsible for Hg methylation in the water column of the Black Sea. We combined geochemical and molecular data obtained from two sampling campaigns conducted in 2013 that had resulted in the previous characterization of (i) high-resolution Hg and MeHg concentrations throughout full water column transects [START_REF] Rosati | Mercury in the Black Sea: new insights from measurements and numerical modeling[END_REF] and (ii) specific (sulfur-and organic matter-linked) microbial metabolisms through genome-centric metagenomics [START_REF] Suominen | A diverse uncultivated microbial community is responsible for organic matter degradation in the Black Sea sulphidic zone[END_REF][START_REF] Van Vliet | The bacterial sulfur cycle in expanding dysoxic and euxinic marine waters[END_REF][START_REF] Villanueva | Bridging the membrane lipid divide: bacteria of the FCB group superphylum have the potential to synthesize archaeal ether lipids[END_REF]. We used several molecular analyses including 16S rRNA amplicon sequencing, metagenomics, and clade-specific quantitative PCR of the hgcA gene, at different depths, to determine whether the highest concentrations of MeHg observed in the anoxic water layers of the Black Sea were explained by the presence, abundance, and metabolic traits of hgc + microorganisms. The present study is novel in revealing the oxygen-dependent niche partitioning of diverse microorganisms potentially capable of Hg methylation in the Black Sea, consistently with measured MeHg concentrations.

MATERIALS AND METHODS

Sampling campaigns

Two complementary field cruises were conducted almost simultaneously in June-July 2013 in the Black Sea with the vessel R/V Pelagia to obtain (i) Hg chemistry data, hgcA quantitative PCR (qPCR), and 16S rRNA gene amplicon sequencing data (MEDBlack cruise) and (ii) planktonic metagenomes (Phoxy cruise). Following the definitions in Stewart et al. [START_REF] Stewart | Oxic, Suboxic, and Anoxic conditions in the black sea, p 1-22[END_REF] and the vertical discretization model of Rosati et al. [START_REF] Rosati | Mercury in the Black Sea: new insights from measurements and numerical modeling[END_REF], the water column was decomposed into three redox layers: the oxic layer (OL, from 0 to 75 m depth, characterized by O 2 concentrations between 30 and 300 µM and undetectable HS -concentrations), the suboxic layer (SOL, from 75 to 120 m depth, characterized by dissolved O 2 concentrations <20 µM and HS -concentrations <5 µM), and the anoxic layer (AOL, below 120 m depth, characterized by undetectable O 2 concentrations and HS -concentrations between 15 and 400 µM).

The MEDBlack cruise was conducted from 13 to 25 July 2013 and occupied 12 stations along a west-to-east transect. In the present work, we include five stations (1, 2, 5, 6, and 9, according to previous nomenclature [START_REF] Rosati | Mercury in the Black Sea: new insights from measurements and numerical modeling[END_REF]; Fig. 1). For microbiology, water samples were collected from three water depths: OL (30-50 m), SOL (90-110 m, except coastal station 6 sampled at 180 m depth), and AOL (140-150 m, except coastal station 6 sampled at 250 m depth) (exact sampling depths are provided in Data Sheet S1A). Samples were filtered with in situ Stand Alone Pump System (Challenger Oceanic, from NOC, Southampton) equipped with two 293 mm diameter filters: a Petex nylon mesh pre-filter (51 µm; 150 µm for station 1) and a polycarbonate filter (1 µm) further stored at -20°C.

The Phoxy cruise 64PE371 was conducted on 9 and 10 June 2013 in the western gyre of the Black Sea. Suspended particulate matter was collected from 15 depths across the oxygen gradient in the water column (from 50 to 2,000 m depth) at sampling station 2 (42.

Physicochemical measurements

For the Phoxy cruise, chemical parameters included the dissolved concentrations of O , respectively [START_REF] Sollai | A combined lipidomic and 16S rRNA gene amplicon sequencing approach reveals archaeal sources of intact polar lipids in the stratified Black Sea water column[END_REF]. A summary of available and new data for both campaigns is provided in Table 1. For the MEDBlack cruise, available measured physicochemical parameters (Data Sheet S1A) include pressure, temperature, conductivity, fluorescence, salinity, density, and the dissolved concentrations of O 2 , HS -, NH 4 + , NO 2 -, NO 3 -, PO 4 3-, Si, Fe, DOC, total Hg, and MeHg (sum of mono-and di-MeHg) according to previous protocols [START_REF] Rosati | Mercury in the Black Sea: new insights from measurements and numerical modeling[END_REF]. Specific analysis of Hg and MeHg is detailed in Supplementaal Information 1.1. The detection limit was 0.025 and 0.001 pM for HgD and MeHgD, respectively. Nutrients, HS -, and dissolved O 2 concentrations were measured similarly to the Phoxy cruise with the same detection limits. Despite coming from two different cruises, the variability between nutrients, HS -, and dissolved O 2 concentrations measured in both cruises at similar depths is low (4-14% variability on average).

DNA extractions

From the MEDBlack cruise, DNA was extracted from sections of the 15 filters (i.e., five stations, three depths) with the FastDNA kit and FastPrep homogenizer (MP Biomedi cals, Santa Ana, CA, USA) according to the manufacturer instructions. The filter fraction represented 2.5% of the whole filter area, corresponding to approximately 5-13 L of filtered seawater depending on the sampling points (8 L on average). From the Phoxy cruise, DNA was extracted from sections of 15 glass fiber filters (1/8 filter from 50 to 130 m depth and 1/4 from 170 to 2,000 m depth) with the RNA PowerSoil Total Isolation Kit plus the DNA elution accessory (Mo Bio Laboratories, Carlsbad, CA, USA) as previously described [START_REF] Villanueva | Bridging the membrane lipid divide: bacteria of the FCB group superphylum have the potential to synthesize archaeal ether lipids[END_REF].

Amplicon sequencing and qPCR estimates of 16S rRNA genes

For the MEDBlack cruise DNA samples, the hypervariable V4-V5 region of the 16S rRNA gene from Bacteria and Archaea was amplified with high-fidelity Phusion Hot Start II DNA polymerase (Thermo Scientific, Waltham, MA, USA) using universal primers 515F and 928R [START_REF] Wang | Conservative fragments in bacterial 16S rRNA genes and primer design for 16S ribosomal DNA amplicons in metagenomic studies[END_REF] and a two-step PCR protocol [START_REF] Schwob | Characterization of the gut microbiota of the antarctic heart urchin (spatangoida) Abatus agassizii[END_REF], as detailed in Supplemental Information 1.2. and Table S1. The correct amplicon size and the absence of non-specific bands were checked by agarose gel electrophoresis. Amplicons were sequenced using a 2 × 250 bp paired-end MiSeq system (Illumina, USA) at the Genotoul platform (Toulouse, France). The raw sequences have been deposited at NCBI GenBank, SRA database, under the BioProject accession number PRJNA895066.

Raw sequences were analyzed on the Galaxy bioinformatics platform through the FROGS pipeline, version 3.2.3, as detailed in the Supplemental Information. Especially, operational taxonomic units (OTUs) were defined by sequence clustering, using the high-resolution SWARM algorithm v3.2.3 [START_REF] Mahé | Swarm v3: towards tera-scale amplicon clustering[END_REF]. After filtering at 0.005% of abundance, OTUs were taxonomically annotated with the SILVA 16S database (version 138.1).

Bacterial and archaeal abundances were quantified in the MEDBlack cruise DNA samples by quantitative PCR with Takyon No Rox SYBR 2X Master Mix (Eurogentec, Seraing, Belgium). Protocol details are provided in Table S1.

Clade-specific hgcA gene qPCR estimates and cloning sequencing of hgcA sequences

In the MEDBlack cruise DNA samples, the hgcA genes of each of the three dominant Hg-methylating clades (Desulfobacterota, Firmicutes, and Archaea) were quantified by qPCR, using clade-specific degenerated qPCR primers [START_REF] Christensen | Development and validation of broad-range qualitative and clade-specific quantitative molecular probes for assessing mercury methylation in the environment[END_REF] and Takyon No Rox SYBR 2X Master Mix (Eurogentec, Seraing, Belgium). The qPCR conditions have been optimized as detailed in the Supplemental Information. All qPCR details and primer sequences are provided in Supplemental Information 1.3. and Table S1.

For Archaea-hgcA, due to the low amplification efficiency and the ambiguity in the melting curves and agarose gel electrophoresis, the correct affiliation of the hgcA amplicons was verified by cloning and sequencing the amplified PCR product, as detailed in Supplemental Information 1.4. Obtained DNA sequences were translated into amino acid sequences and compared with hgcA sequences from the Hg-MATE database [START_REF] Gionfriddo | Hg-MATE-dB.V1.01142021. Hg-Cycling Microorg[END_REF] and from the 15 metagenomes obtained in the Phoxy cruise (see following section). The sequence analysis (Supplemental Information 1.4 and Fig. S2) showed that hgcA sequences obtained with this primer set clustered with Euryarchaeota and Chloroflexota sequences. Thus, from thereon, hgcA qPCR estimates from Archaea will be referred to hgcA qPCR estimates from Archaea-Chloroflexota.

Metagenomic estimates of hgcA genes

The 15 DNA extracts from the Phoxy cruise were used to prepare TruSeq nano libraries, sequenced with Illumina MiSeq (five samples multiplexed per lane) at Utrecht Sequenc ing Facility, generating 4.5 × 10 7 paired-end reads (2 × 250 bp), which were further processed as previously reported [START_REF] Villanueva | Bridging the membrane lipid divide: bacteria of the FCB group superphylum have the potential to synthesize archaeal ether lipids[END_REF] and summarized in Supplemental Information 1.5.

hgc homologs were identified and annotated in the amino acid FASTA file (generated from protein-coding genes detected in the metagenomes coassembly), using the HMM profiles of hgcA and hgcB genes derived from the Hg-MATE database v1.01142021 [START_REF] Gionfriddo | Hg-MATE-dB.V1.01142021. Hg-Cycling Microorg[END_REF] and the function hmmsearch from HMMER 3.2.1 [START_REF] Finn | HMMER web server: interactive sequence similarity searching[END_REF]. We considered genes with E-values <10 -3 as significant hits. To further confirm putative hgcA and hgcB genes (or hgc-like genes) within the HMM search hits, we used the high stringency cutoff defined by Capo et al. ( 8) by looking for unique conserved motifs from hgcA gene (NVWCA(A/G/ S)GK) and performed a manual inspection of the presence of hgcA genes. Coverage values of hgcA genes were calculated as the number of reads mapped to the gene divided by its length (base pairs, bp) and were further normalized by dividing them by the coverage values of the marker gene rpoB. The rpoB genes were detected using the function hmmsearch from HMMER 3.2.1 [START_REF] Finn | HMMER web server: interactive sequence similarity searching[END_REF] and HMM profile TIGR02013.hmm for bacterial rpoB genes and applying the trusted cutoff provided in HMM files.

The obtained hgcA homologs, translated in amino acid sequences, were taxonomi cally affiliated through a phylogenetic analysis, by placing them onto the HgcA reference tree using a pplacer approach [START_REF] Matsen | Pplacer: linear time maximum-likelihood and Bayesian phylogenetic placement of sequences onto a fixed reference tree[END_REF]. The construction of the reference tree was based on the reference package "hgcA" from Hg-MATE database v1, according to the protocol in the README.txt of the Hg-MATE database [START_REF] Gionfriddo | Hg-MATE-dB.V1.01142021. Hg-Cycling Microorg[END_REF] and in Capo et al. [START_REF] Capo | A consensus protocol for the recovery of mercury methylation genes from metagenomes[END_REF], as detailed in Supplemental Information 1.5. As a complement to this community-level analysis, metagenome-assembled genomes generated from the same previously published metagenomes [START_REF] Van Vliet | The bacterial sulfur cycle in expanding dysoxic and euxinic marine waters[END_REF][START_REF] Villanueva | Bridging the membrane lipid divide: bacteria of the FCB group superphylum have the potential to synthesize archaeal ether lipids[END_REF] were screened for hgc genes. The hgc genes found in MAGs were taxonomically identified using the MAG phylogeny and taxonomy (Data Sheet S1D).

Data analysis

The qPCR estimates were statistically analyzed by two-way analysis of variance (ANOVA) with the aov function (R software). The selected environmental parameters for corre lation analysis were the concentrations of dissolved O 2 , HS -, and MeHg. Spearman correlation plots were obtained using the functions rcorr and corrplot from the R packages Hmisc and corrplot, respectively. Shannon diversity indices were calculated with the estimate_richness function in the vegan R package. Principal coordinates analysis (PCoA) was performed applying the function wcmdscale to Bray-Curtis dissimilarity matrixes built with the function vegdist from the 16S rRNA gene-based OTU abundance table and the hgcA gene abundance (normalized coverage values) in the R package vegan. The discriminant hgcA genes explaining the most the clustering of hgc + commun ity according to depth zones were identified by linear discriminant analysis (run_lefse function, microbiomeMarker package) with cumulative sum scaling normalization and 100 bootstraps.

RESULTS

Mercury and microbial community stratification along water depth and oxygen gradient

Hg and MeHg profiles revealed a strong depth stratification, homogeneous across the whole basin (Fig. S1). In stations 1, 2, and 5, the MeHg concentration was always maximal at the same depth (130 m) reaching 0.83-1.13 pM, which represents 32%-48% of tHg at this depth. The MeHg concentration then decreased down to 250 m depth and remained relatively stable in deeper waters (0.50-0.65 pM on average below 250 m depth, representing 19%-26% of tHg).

Microbial community structure was homogeneous horizontally across the Black Sea basin, but vertically stratified across water depth and oxygen concentrations. Consider ing the MEDBlack samples, bacterial abundances based on qPCR of the bacterial 16S rRNA gene did not significantly differ along the west-to-east transect (two-way ANOVA, P = 0.4) but were significantly impacted by sampling depth (two-way ANOVA, P < 0.001) (Fig. 2A; Data Sheet S1A). The highest bacterial abundances (7.8 10 8 16S copies L -1 on average) were observed in the OL (30-50 m depth), being one order of magnitude higher than in the AOL (140-250 m depth). Archaeal abundances measured by qPCR also varied with depth (P = 0.001), but showed a reverse stratification pattern from bacteria (Fig. 2B) as detailed in Supplemental Information 2.1.

The taxonomic composition (Fig. S3) and the structure (Fig. 3A) of the prokaryotic community was similar across the west-east transect, as confirmed by the non-significant effect of sampling station on the community structure permutational multivariate analysis of variance (PERMANOVA P > 0.1) and Shannon diversity (ANOVA, P = 0.16). For all stations, OL communities were dominated by Cyanobacteria representing 70% of prokaryotes (Fig. 2D; Fig. S3; Data Sheet S1C and E). SOL and AOL were significantly more diverse (ANOVA, P < 0.001, Fig. 2C), dominated by Planctomycetota (29%-47% of the prokaryotes), Bacteroidota (13%-15%), and Desulfobacterota (7%-9%) (Supplemental Information 2.1). S3 (at the phylum level) and the detailed OTU composition is provided in Data Sheet S1C.

Clade-specific hgcA genes measured by qPCR are more abundant in the anoxic layer

Abundance of hgcA genes was quantified by qPCR for each of the well-known Hg-meth ylating clades Desulfobacterota, Firmicutes, and Archaea-Chloroflexota (37) (see Supple mental Information 1.4 for the clade definition). Analogous to 16S rRNA gene counts, absolute hgcA counts from Desulfobacterota, Firmicutes, and Archaea-Chloroflexota were similar along the west-to-east transect of the Black Sea (two-way ANOVA, P > 0.90), but strongly stratified over depth (two-way ANOVA, P < 0.0001). Tracking the MeHg concentration profiles (Fig. 4A; Fig. S1), the highest hgcA counts were found in the AOL for all three clades, reaching on average 9.0 ± 3.0 10 3 , 6.1 ± 1.4 10 6 , and 5.6 ± 1.5 10 6 copies L -1 of seawater for Firmicutes, Desulfobacterota, and Archaea-Chloroflexota, respectively (Fig. 4B; Data Sheet S1A). The hgcA counts were between 12 and 31 times lower in the OL. In the SOL and AOL, hgcA counts from Desulfobacterota and Archaea-Chloroflexota were similar, exceeding that of Firmicutes by one to three orders of magnitude. The higher abundance of hgcA genes in the AOL was not only observed for absolute hgcA counts, but also for relative hgcA counts (normalized by summed bacterial and archaeal 16S gene counts, Data Sheet S1A), which contrasts with the pattern observed for total bacteria and indicates a clear enrichment of potential Hg methylators in oxygen-deficient deeper waters. Relative hgcA counts from Desulfobacterota represented 4.8%-9.8% of the prokaryotes in the AOL, 0.5%-2.9% in the SOL, and <0.2% in the OL. hgcA counts from Archaea-Chloroflexota followed a similar depth pattern, representing 4.3%-6.9% of the prokaryotes in the AOL and 0.8%-2% in the SOL, while not detected in the OL. Finally, Firmicutes-hgcA genes accounted for <0.02% of the prokaryotes in all layers. The specificity of the Archaea-Chloroflexota hgcA primers is further evaluated and discussed in the Supplemental Information.

hgc genes in the water column are affiliated to diverse taxa with specific niches

A total of 91 hgcA genes were found in the Black Sea metagenome co-assembly, including 14 genes found next to hgcB genes on the same contig (Data Sheet S1D). Among them, 15 hgcA genes were found in MAGs affiliated to various orders of Desulfobacterota (Desulfobacterales, Desulfobulbales, unclassified), Chloroflexota (Anaerolineales), Bacteroidota (Bacteroidales), Planctomycetota (Phycisphaerales), Verrumicrobiota (Kiritimatiellales), and KSB1 candidate division (unclassified) (Fig. 5A). Among Desulfobacterota, the hgc + MAGs were identified as uncultured species of U Desulfacyla, U Desufatibia, U Desulfobia, and Desulfobacula. From the alignment to the Hg-MATE database, the remaining 76 unbinned hgcA genes were affiliated predomi nantly to Desulfobacterota [START_REF] Stewart | Oxic, Suboxic, and Anoxic conditions in the black sea, p 1-22[END_REF], Planctomycetota (14, among which 4 Phycisphaerae), Verrucomicrobiota (9 Kiritimatiellales), Chloroflexota (8 Anaerolineales), and various microbial lineages (Data Sheet S1D). The metagenome-estimated (MG-estimated) abundance and diversity of hgcA genes were both strongly stratified along the Black Sea water column (Fig. 5B; Data Sheet S1B). This was in line with the qPCR results for clade-specific hgcA genes, although samples for metagenomic analysis were collected with a higher vertical resolution (15 depths). hgcA genes were barely detected in the OL and at the top of the SOL (<0.1% of the reads above 70 m depth). The abundance of hgcA genes (i.e., normalized coverage values) gradually increased over depth, reaching the highest value at the SOL-AOL transition (130 m depth, 14.3% of the total hgcA abundance). In deeper water layers, hgcA abundance decreased to 8.4%-9.9% at 1,000-2,000 m depth. MG-derived hgcA genes from Desulfobacterota were predominant in both the SOL (28.3%-58.4% of all hgcA genes) and the AOL (33.0%-53.8%). The second most abundant MG-derived hgcA sequences belonged to Anaerolineales and Phycisphaerae and predominated in the AOL (representing, respectively, 15.1 ± 6.8% and 6.4 ± 3.1% of all hgcA in this layer), while hgcA genes from Kiritimatiellales and Bacteroidales predominated in the SOL (12.9 ± 10.1% and 5.9 ± 5.5%, respectively). At 1,000 and 2,000 m depths, where HS -concentra tions were the highest (>350 µM), the proportion of hgcA genes from Verrucomicrobiota and U Desulfacyla decreased, while those from other Desulfobacterota and Chloroflexota remained dominant (Fig. 5B; Data Sheet S1B). Also, hgcA genes from Firmicutes represen ted 1.4%-6.7% of all reads at the SOL-AOL transition (110-130 m), while they were undetected in all the other sampled depths (Data Sheet S1B and D).

Relationships between environmental gradients, Hg-related variables, and microbial stratification over depth

PCoA analyses showed that the structure of both the 16S rRNA gene-based prokaryotic community (Fig. 3A) and hgc + microbial groups (Fig. 3B) clustered similarly with depth (PERMANOVA, P < 0.05), according to the three redox zones (OL, SOL, and AOL). This microbial stratification over depth can be related to the observed geochemical gradients of oxygen, HS -, and MeHg concentrations, along with other stratified parameters (Table 1).

For the MEDBlack samples , the qPCR-estimated abundances of hgcA genes from Desulfobacterota, Firmicutes, and Archaea-Chloroflexota were significantly positively correlated with MeHg and HS -concentrations, and negatively correlated with oxy gen concentrations (Spearman rank correlations, P-value <0.01; Fig. 3C). Several other environmental parameters also appeared to be stratified and co-varied with oxygen along depth (Table 1).

For station 2 studied in the Phoxy cruise, the correlations between the MG-estimated abundance of hgcA genes and environmental conditions depended on the microbial groups (Fig. 3C). The abundances of hgcA genes from Bacteroidota and Verrucomicrobiota significantly increased with oxygen depletion but were not significantly correlated to HS - concentrations. In contrast, hgc + Chloroflexota, KSB1 Candidate Division, and Planctomy cetota were positively correlated to HS -concentrations and not significantly related to oxygen concentrations. Finally, hgcA genes from Desulfobacterota were negatively correlated to oxygen concentrations and positively correlated to HS -concentrations (Fig. 3C). The hgc + community clustering in the AOL was characterized by discriminant hgcA genes affiliated to Desulfobacterota ( U Desulfatibia), Chloroflexota (Anaerolineales), and Planctomycetota (mainly from Phycisphaerae), while the hgc + community in the SOL was discriminated by hgcA genes affiliated to Kiritimatiellales, U Desulfacyla, Bacteroidales, Desulfobacterales, and other PVC (Planctomycetota, Verrucomicrobiota, and Chlamy diota) superphylum members (lefse analysis , P < 0.05, Fig. S4), thus confirming the oxygen-dependent niche partitioning of potential methylators at a fine taxonomic resolution.

DISCUSSION

Coupling methodological approaches to identify bioindicators of Hg methylation in the environment

Our 16S rRNA gene metabarcoding data support previous studies that reported the enrichment of Desulfobacterota, Planctomycetota, Acidobacteriota, and Firmicutes with increasing depth, and the restriction of Nitrospirota, Chloroflexota, and Verrucomicrobiota to the anoxic waters of the Black Sea [START_REF] Cabello-Yeves | The microbiome of the Black Sea water column analyzed by shotgun and genome centric metagenomics[END_REF][START_REF] Ozturk | Influence of the depth and season on microbial community dynamics of the black sea[END_REF]. Several of the dominant microbial lineages found in and below the redoxcline include hgc + microorganisms. However, studies based on 16S rRNA gene taxonomic classification are often not sufficient to predict the occurrence of Hg methylators, since Hg methylation is a species-(and possibly strain-) specific trait [START_REF] Bravo | Biotic formation of methylmercury: a biophysico-chemical conundrum[END_REF]. Alternative approaches targeting the hgc genes as a biomarker of microbial Hg methylation have been proposed [START_REF] Christensen | Development and validation of broad-range qualitative and clade-specific quantitative molecular probes for assessing mercury methylation in the environment[END_REF][START_REF] Christensen | Determining the reliability of measuring mercury cycling gene abundance with correlations with mercury and methylmercury concentrations[END_REF][START_REF] Gionfriddo | An improved hgcAB primer set and direct high-throughput sequencing expand Hg-methylator diversity in nature[END_REF]. To avoid the biases due to the large polyphyletic diversity of the hgcA gene [START_REF] Mcdaniel | Expanded phylogenetic diversity and metabolic flexibility of mercury-methylating microorganisms[END_REF], and the overrepresentation of hgcA sequences from Desulfobacterota in databases of known Hg methylators used for primer design [START_REF] Capo | A consensus protocol for the recovery of mercury methylation genes from metagenomes[END_REF][START_REF] Gionfriddo | An improved hgcAB primer set and direct high-throughput sequencing expand Hg-methylator diversity in nature[END_REF], clade-specific qPCR primers have been developed, targeting hgcA genes from each of the three dominant Hg-methylating clades, i.e., Desulfobacterota, Arch aea, and Firmicutes (37). This approach yielded results similar to metagenome-derived estimates for the identification of Hg methylation biomarkers [START_REF] Christensen | Determining the reliability of measuring mercury cycling gene abundance with correlations with mercury and methylmercury concentrations[END_REF], and is preferable to detect taxa-dependent correlations with environmental and/or functional outcomes. It is important to highlight that the outcomes of different methods should be interpre ted cautiously since some discrepancies have been previously reported between, e.g., metagenomics, functional gene sequencing, cloning, qPCR, and 16S metabarcoding [START_REF] Jones | Molecular evidence for novel mercury methylating microorganisms in sulfate-impacted lakes[END_REF][START_REF] Christensen | Determining the reliability of measuring mercury cycling gene abundance with correlations with mercury and methylmercury concentrations[END_REF][START_REF] Roth | Nutrient inputs stimulate mercury methylation by syntrophs in a subarctic peatland[END_REF]. Finally, DNA-based approaches should be complemented by gene expression and methylation rates measurements in order to confirm the involvement of potential Hg methylators.

Geochemical and microbial homogeneity along the Black Sea transect

Here, although qPCR and metagenomic estimates have been applied to samples from two different cruises, the results of the two cruises yield comparable results, including (i) similar stratification pattern of hgcA abundance across water depth and environmen tal conditions, and (ii) similar taxonomic identification and abundance distribution of putative Hg methylators. Even if metagenomic analysis has been carried out only at station 2 during the Phoxy cruise, our results are likely representative for the basin as a whole because of the high horizontal homogeneity of the Black Sea (excluding coastal areas), in terms of microbial community structure (as shown in the present and previous studies) [START_REF] Zhang | Holistic pelagic biodiversity monitoring of the Black Sea via eDNA metabarcoding approach: from bacteria to marine mammals[END_REF] hydrography [START_REF] Zatsepin | Observations of Black Sea mesoscale eddies and associated horizontal mixing[END_REF] and geochemistry [START_REF] Rosati | Mercury in the Black Sea: new insights from measurements and numerical modeling[END_REF]. Here, all the microbial indicators and metrics (i.e., total abundances, abundance of hgcA-carriers from different clades, alpha diversity, community structure, and composition) were similar across the east-west transect, as well as the full-depth high-resolution Hg and MeHg concentration profiles. Significant positive correlations were observed between hgcA qPCR estimates from the three targeted microbial groups (i.e., Desulfobacterota, Firmicutes, and Archaea-Chloroflexota) and MeHg concentrations. Such correlative links between hgcA (gene or transcript) abundance and MeHg concentration and/or formation activity have been previously reported [START_REF] Capo | Expression levels of hgcAB genes and mercury availability jointly explain methylmercury formation in stratified brackish waters[END_REF][START_REF] Vishnivetskaya | Microbial community structure with trends in methylation gene diversity and abundance in mercury-contaminated rice paddy soils in Guizhou, China[END_REF][START_REF] Peterson | Environmental formation of methylmercury is controlled by synergy of inorganic mercury bioavailability and microbial mercury-methylation capacity[END_REF], but are not always observed, depending on the ecosystems [START_REF] Bravo | Persistent Hg contamination and occurrence of Hg-methylating transcript (hgcA) downstream of a chloralkali plant in the Olt River (Romania)[END_REF][START_REF] Christensen | Carbon amendments alter microbial community structure and net mercury methylation potential in sediments[END_REF], as documented also for other metabolic processes [START_REF] Rocca | Relationships between proteinencoding gene abundance and corresponding process are commonly assumed yet rarely observed[END_REF].

A diverse community of hgc + microorganisms is distributed along the redox gradient in the Black Sea

We demonstrate that not only the overall community but also the abundance and diversity of hgc + microorganisms vary with the redox gradient in the water column of the Black Sea. The very low proportion of hgc genes detected in the oxic layer (and their taxonomic affiliation) is further discussed in Supplemental Information 3.1. Our findings showing a strong relation between oxygen depletion and hgc + microorganism abun dance are in line with previous studies in marine, brackish, and freshwater environments [START_REF] Peterson | Mercury methylation genes identified across diverse anaerobic microbial guilds in a eutrophic sulfate-enriched lake[END_REF][START_REF] Lin | Mercury methylation by metabolically versatile and cosmopolitan marine bacteria[END_REF][START_REF] Capo | Deltaproteobacteria and spirochaetes-like bacteria are abundant putative mercury methylators in oxygen-deficient water and marine particles in the Baltic sea[END_REF][START_REF] Capo | Expression levels of hgcAB genes and mercury availability jointly explain methylmercury formation in stratified brackish waters[END_REF]. We provide the first evidence for microbial potential to produce MeHg in the anoxic sulfidic waters of the Black Sea, as previously suggested by a modeling approach based on geochemical data [START_REF] Rosati | Mercury in the Black Sea: new insights from measurements and numerical modeling[END_REF]. This disagrees with earlier studies where persistently high sulfide concentrations were believed to inhibit Hg methylation in the AOL of the Black Sea [START_REF] Lamborg | Vertical distribution of mercury species at two sites in the Western Black Sea[END_REF] and other systems [START_REF] Benoit | Sulfide controls on mercury speciation and bioavailability to methylating bacteria in sediment pore waters[END_REF][START_REF] Hsu-Kim | Mechanisms regulating mercury bioavailability for methylating microorganisms in the aquatic environment: a critical review[END_REF]. Similar to our results, maximal methylation activity was also reported under sulfidic conditions in stratified brackish water [START_REF] Capo | Expression levels of hgcAB genes and mercury availability jointly explain methylmercury formation in stratified brackish waters[END_REF] and a meromictic lake [START_REF] Tisserand | Mercury, organic matter, iron, and sulfur co-cycling in a ferruginous meromictic lake[END_REF]. The dual role of sulfide in Hg methylation is complex and still uncertain [START_REF] Hsu-Kim | Mechanisms regulating mercury bioavailability for methylating microorganisms in the aquatic environment: a critical review[END_REF][START_REF] Regnell | Microbial mercury methylation in aquatic environments: a critical review of published field and laboratory studies[END_REF].

Desulfobacterota members exhibit the highest diversity and abundances of hgcA genes in the Black Sea water column. The presence of Desulfobacterota in the anoxic water layer of the Black Sea can be explained by their metabolisms as sulfate reducers, iron reducers, and/or fermentative syntrophic in oxygen-deficient environments [START_REF] Waite | Proposal to reclassify the proteobacterial classes Deltaproteobacte ria and Oligoflexia, and the phylum Thermodesulfobacteria into four phyla reflecting major functional capabilities[END_REF]. Sulfate reduction has been previously reported in the Black Sea anoxic water [START_REF] Van Vliet | The bacterial sulfur cycle in expanding dysoxic and euxinic marine waters[END_REF][START_REF] Neretin | A sulfur budget for the black sea anoxic zone. Deep-Sea Res I[END_REF] and is also supported by our high HS -concentrations in the AOL. For decades, Desulfobacter ota members have been confirmed to be capable of Hg methylation and/or carrying hgc genes [START_REF] Bravo | Biotic formation of methylmercury: a biophysico-chemical conundrum[END_REF][START_REF] Gilmour | Mercury methylation by novel microorganisms from new environments[END_REF]. Desulfobacterota have also previously been identified as prevalent hgc + microorganisms in many anoxic marine waters [START_REF] Lin | Mercury methylation by metabolically versatile and cosmopolitan marine bacteria[END_REF][START_REF] Capo | Deltaproteobacteria and spirochaetes-like bacteria are abundant putative mercury methylators in oxygen-deficient water and marine particles in the Baltic sea[END_REF][START_REF] Capo | Expression levels of hgcAB genes and mercury availability jointly explain methylmercury formation in stratified brackish waters[END_REF] and sediments [START_REF] Capo | Oxygen-deficient water zones in the Baltic Sea promote uncharacterized Hg methylating microorganisms in underlying sediments[END_REF][START_REF] Azaroff | Marine mercury-methylating microbial communities from coastal to Capbreton Canyon sediments (North Atlantic ocean)[END_REF]. In our work, certain hgcA genes belong to MAGs previously reconstructed from the Phoxy metagenomes [START_REF] Van Vliet | The bacterial sulfur cycle in expanding dysoxic and euxinic marine waters[END_REF]. Among them, the hgc + MAGs U Desulfatibia profunda NIOZ-UU30 and U Desulfacyla NIOZ-UU19, enriched in the anoxic waters, were described as probably having a strict sulfate-reducing lifestyle. By contrast, the hgc + sulfate reducers U Desulfacyla euxinica NIOZ-UU27, U Desulfatibia vada NIOZ-UU17, and U Desulfobacula maris NIOZ-UU16, which were abundant in the suboxic waters and dominant at the top of the anoxic waters, feature a more flexible potential metabolism, with the ability to gain energy from the reduction of diverse electron acceptors (S 0 , thiosulfate, tetrathionate, nitrate, nitrite), possibly including oxygen respiration [START_REF] Van Vliet | The bacterial sulfur cycle in expanding dysoxic and euxinic marine waters[END_REF]. The MAG of the SRB U Desulfo bia pelagia NIOZ-UU47, for which hgcA genes were found between 105 and 250 m, seems to have the ability to fix nitrogen. Altogether, these results show that Desulfobacterotamediated MeHg formation in the Black Sea may be coupled to sulfate reduction but also to other metabolic pathways depending on the redox niche.

Certain Anaerolineales (Chloroflexota) are also part of the dominant hgcA-carriers in the suboxic and anoxic waters of the Black Sea including the MAGs NIOZ-UU11 and NIOZ-UU52. Anaerolineales are fermenters, in possible syntrophic association with methanogens [START_REF] Sekiguchi | Anaerolinea thermophila gen. nov., sp. nov. and Caldilinea aerophila gen. nov., sp. nov., novel filamentous thermophiles that represent a previously uncultured lineage of the domain Bacteria at the subphylum level[END_REF]. Anaerolineales MAGs were previously identified as highly abundant in the Black Sea, where some of them carried sulfate reduction genes [START_REF] Cabello-Yeves | The microbiome of the Black Sea water column analyzed by shotgun and genome centric metagenomics[END_REF]. Although there is still limited genomic information about members of this group, a hgc + MAG Anaerolineales representative (BSW_bin111) was detected in the anoxic brackish water of the Baltic Sea [START_REF] Capo | Expression levels of hgcAB genes and mercury availability jointly explain methylmercury formation in stratified brackish waters[END_REF]. In addition, Phycisphaerae (Planctomycetota), Kiritimatiellales (Verrucomicrobiota), and Bacteroidales (Bacteroidota) were identified as major potential Hg methylators in the oxygen-deficient waters of the Black Sea. Among these new, underappreciated, fermentative hgcA carriers, the Bacteroidota MAG NIOZ-UU65 was equipped with polysulfide reductase genes [START_REF] Van Vliet | The bacterial sulfur cycle in expanding dysoxic and euxinic marine waters[END_REF]. Phycisphaerales have been identified in the euxinic waters of the Cariaco basin as attached to particles [START_REF] Suter | Free-living chemoautotrophic and particle-attached heterotrophic prokaryotes dominate microbial assemblages along a pelagic redox gradient[END_REF] and in the Black Sea (59) as potential degraders of newly formed OM not linked to the redox gradient [START_REF] Suominen | Interplay between microbial community composition and chemodiversity of dissolved organic matter throughout the black sea water column redox gradient[END_REF], and some type strains seemed capable of nitrate reduction [START_REF] Fukunaga | Phycisphaera mikurensis gen. nov., sp. nov., isolated from a marine alga, and proposal of Phycisphaeraceae fam. nov., Phycisphaerales ord. nov. and Phycisphaerae classis nov. in the phylum Planctomycetes[END_REF]. Phycisphaerales have been reported as minor putative Hg methylator in marine sediments [START_REF] Capo | Oxygen-deficient water zones in the Baltic Sea promote uncharacterized Hg methylating microorganisms in underlying sediments[END_REF], salt marsh, and freshwater sediment [START_REF] Gionfriddo | An improved hgcAB primer set and direct high-throughput sequencing expand Hg-methylator diversity in nature[END_REF]. Culture and single-cell genomics of Kiritimatiellales representa tives indicated a fermentative lifestyle, with the capacity for degradation of complex and recalcitrant polysaccharides and glycoproteins, as well as hydrolysis of sulfate esters, with wide oxygen and salinity tolerance, and a preference for biofilm habitats [START_REF] Sackett | Four draft single-cell genome sequences of novel, nearly identical Kiritimatiellaeota strains isolated from the continental deep subsurface[END_REF][START_REF] Spring | Characterization of the first cultured representative of Verrucomi crobia subdivision 5 indicates the proposal of a novel phylum[END_REF][START_REF] Van Vliet | Pontiella desulfatans gen. nov., sp. nov., and pontiella sulfatireligans sp. nov., two marine anaerobes of the pontiellaceae fam. nov. producing sulfated glycosaminoglycan-like exopolymers[END_REF][START_REF] Van Vliet | Anaerobic degradation of sulfated polysaccharides by two novel Kiritimatiellales strains isolated from black sea sediment[END_REF]. Kiritimatiellales were previously identified by metagenomic approaches among the most prominent putative Hg methylators in sediment and anoxic water of eutrophic sulfaterich freshwater lakes [START_REF] Jones | Molecular evidence for novel mercury methylating microorganisms in sulfate-impacted lakes[END_REF][START_REF] Peterson | Mercury methylation genes identified across diverse anaerobic microbial guilds in a eutrophic sulfate-enriched lake[END_REF] and in the anoxic brackish water of the Baltic Sea [START_REF] Capo | Expression levels of hgcAB genes and mercury availability jointly explain methylmercury formation in stratified brackish waters[END_REF]. Overall, fermenters from Anaerolineales, Phycisphaerae, Kiritimatiellales, and Bacteroidales have been rarely reported as putative Hg methylators, usually at low abundance in ecosystems different from the present one. To our knowledge, this is the first report of their substantial joint contribution to Hg methylation, conforming a unique assemblage in a permanently stratified marine ecosystem. Among these diverse Hg methylators candidates found in the Black Sea suboxic/anoxic waters, some lineages (Anaerolineales and Kiritimatiellales) are common to other euxinic basins [START_REF] Lin | Mercury methylation by metabolically versatile and cosmopolitan marine bacteria[END_REF][START_REF] Capo | Expression levels of hgcAB genes and mercury availability jointly explain methylmercury formation in stratified brackish waters[END_REF], suggesting that they may be part of the important mediators of Hg methylation in permanently or not permanently anoxic water from marine and/or brackish environments with high sulfide concentrations. However, it is unclear if this diversity is a common trait of (not euxinic) OMZ, where Hg methylators have been rarely detected [START_REF] Podar | Global prevalence and distribution of genes and microorganisms involved in mercury methylation[END_REF]. Further studies should compare the hgc + MAGs identified here and in similar oxygen-depleted marine systems, to explore the metabolic versatility of Hg-methylating microorganisms and their environmental drivers.

Finally, our results suggest that the qPCR estimates of hgcA genes identified by primers primarily designed to target Archaea are overestimated. This is supported by cloning-sequencing of PCR products obtained using Archaea-specific hgcA qPCR primers, showing that some amplicon sequences group with Chloroflexota rather than Archaea (Supplemental Information 1.4, Fig. S2). Additionally, our metagenome analyses consistently show that hgc + Chloroflexota are major putative Hg methylation contribu tors, especially in the AOL, while Archaea-assigned hgcA are rare and not abundant (Data Sheet S1B and D). Recently, an analysis of publicly available MAGs revealed high similarities of hgc genes from Euryarchaeota and Chloroflexota, potentially due to horizontal gene transfers [START_REF] Mcdaniel | Expanded phylogenetic diversity and metabolic flexibility of mercury-methylating microorganisms[END_REF]. Altogether, these results suggest that the Archaea-hgcA primers from Christensen et al. [START_REF] Christensen | Development and validation of broad-range qualitative and clade-specific quantitative molecular probes for assessing mercury methylation in the environment[END_REF] are less specific than initially thought and likely include hgcA genes from other clades such as Chloroflexota.

Conclusion

Oxygen-limited and anoxic areas are spreading in the coastal and offshore ocean, implying modifications of biogeochemical cycles. The Black Sea offers a unique opportunity to study the effect of oxygen gradients on biogeochemical cycles such as Hg transformations. Our findings highlight that a unique combination of diverse dominant hgc + microbes can coexist and jointly contribute to MeHg production in marine environments, with niche partitioning according to the redox gradient. We identified members of Desulfobacterota, Chloroflexota, Verrucomicrobiota, Planctomyce tota, and Bacteroidota as the main actors of Hg methylation in the Black Sea water column. The microbial communities, including putative Hg methylators, were horizon tally homogeneous across the Black Sea, but vertically stratified. The abundance of hgcA genes increased with depth, being positively correlated with MeHg concentration and negatively with oxygen concentration. Our DNA-based results support that Hg methylation potentially occurs predominantly in the anoxic waters of the Black Sea, which should be further confirmed by measuring gene expression and/or methylation rates. Microorganisms harboring hgc + were dominated by Desulfobacterota, followed by a high diversity of previously less recognized Hg methylators belonging to Phyci sphaerae, Kiritimatiellales, and Anaerolineales. The strong environmental gradients across the Black Sea water column affect the microbial community composition, resulting in a partitioning of Hg-methylating microorganisms, and their associated metabolic pathways, differing across redox niches. Our results, robustly validated by two different methodological approaches (qPCR and metagenomics), were consistent with measured environmental parameters, including MeHg concentration. By identifying marine anoxic niches as a primary MeHg source, this study is of major relevance in the context of global warming and anthropogenic activity which currently result in enhanced seawater deoxygenation and global expansion of anoxic zones.

  89 N, 30.67 E, 2,107 m depth [Fig. 1], at 72 km from the MEDBlack station 2 and visited 35 days earlier) with McLane WTS-LV in situ pumps (McLane Laboratories Inc., Falmouth, MA, USA) on pre-combusted glass fiber filters with 142 mm diameter and 0.7 µm nominal pore size, further stored at -80°C. One sample from the Phoxy cruise belonged to the OL (50 m depth), eight samples to the SOL (70-110 m depth), and six samples to the AOL (130-2000,m depth).

FIG 1

 1 FIG 1 Locations of stations sampled in the Black Sea during the MEDBlack cruise and analyzed in this study (black dots). The star indicates station 2 which was also sampled during the Phoxy cruise for metagenomics analysis. The exact coordinates are provided in Data Sheet S1A.

FIG 2

 2 FIG 2 Stratification of microbial profiles in the Black Sea water column. Data from the five sampling stations have been averaged for oxic (OL, 25-50 m), suboxic (SOL, 85-110 m, except station 6 at 175 m), and anoxic (AOL, 145-250 m) layers. (A) qPCR quantification of bacterial 16S rRNA gene, per filtered volume of seawater. (B) qPCR quantification of archaeal 16S rRNA gene, per filtered volume of seawater. (C) Diversity of total microbial community based on Shannon index, computed from 16S rRNA gene amplicon sequences. (D) Taxonomic composition of microbial communities at the phylum level, representing the 11 most abundant phyla. In panels A to C, the bold line of each boxplot shows the median, while upper and lower limits of the boxes represent the first and third quartiles, respectively. The whiskers are maximum and minimum values and the dots show the outliers. For panel D, for each phylum, the averages and standard deviations calculated per water layer are provided in Data Sheet S1E. The taxonomic composition of the five individual sampling stations across the Black Sea basin is shown in Fig. S3 (at the phylum level) and the detailed OTU composition is provided in Data Sheet S1C.

FIG 3

 3 FIG 3 Depth stratification of prokaryotic and hgc + communities in relation with environmental gradients and Hg-related variables. (A and B) PCoA plots based on Bray-Curtis dissimilarity showing the structure of the overall prokaryotic community (A; MEDBlack cruise samples) and of the hgc + microbial groups (B; Phoxy cruise samples). The dot color denotes the HS -concentrations measured in the same samples. The color of the sample name label corresponds to the three water-depth zones: the oxic (OL, gray), suboxic (SOL, light blue), and anoxic (AOL, dark blue) water layers. (C) Correlation plots based on Spearman correlation coefficients between environmental parameters (O 2 , HS -, and MeHg concentrations) and qPCR and metagenomic (MG) estimates of hgcA genes from different microbial groups. Only significant relationships (P < 0.05) are displayed. No MeHg measurements were done during the Phoxy cruise (metagenome samples).

FIG 4

 4 FIG 4 Vertical stratification of MeHg concentrations and hgcA gene abundances in the Black Sea water column. Data from the five sampling stations have been averaged for oxic (OL, 25-50 m), suboxic (SOL, 85-110 m, except station 6 at 175 m), and anoxic (AOL, 145-250 m) layers. (A) Dissolved concentration of MeHg. (B) qPCR quantification of hgcA gene, indicator of Hg methylation ability, for Firmicutes, Desulfobacterota, and Archaea-Chloroflexota, in copies per seawater filtered volume. The bold line of each boxplot shows the median, while upper and lower limits of the boxes represent the first and third quartiles, respectively. The whiskers are maximum and minimum values and the dots show the outliers. The values for the five individual sampling stations are provided in Data Sheet S1A, as well as the relative hgcA counts (normalized by total prokaryotic abundance).

FIG 5 A

 5 FIG 5 A diverse microbial community potentially able to methylate Hg in the Black Sea water column. (A) Unrooted hgcA phylogenetic tree showing the diversity of hgc + microorganisms from the Black Sea water column compared to the reference sequences from the Hg-MATE database. The 15 binned hgcA genes found in MAGS are denoted in the figure by their ID number in red (see "gene_id" in Data Sheet S1D). The other 77 unbinned hgcA genes are listed in Data Sheet S1D; after examination of their placement on the phylogenetic tree, they were assigned to a taxonomic cluster denoted from "a" to "h" (indicated in the column "Corresponding cluster in hcgA tree" of Data Sheet S1D). For clarity purpose, only the cluster letter is shown on the tree (blue circles at the basis of each group) instead of the 77 sequences. The reference phylogenetic tree was provided by the Hg-MATE database using hgcA sequences from (i) pure culture/environmental microbial isolates (204 sequences), (ii) single-cell genome sequences (29 sequences), and (iii) metagenome-assembled genomes (787 sequences), as detailed in Materials and Methods and Supplemental Information 1.5. (B) Vertical distribution of MG-estimated coverage values of hgcA genes normalized by rpoB coverage values along the water column depth in the Black Sea. The corresponding compartmentation into oxic (OL), suboxic (SOL), and anoxic (AOL) layers is shown on the left axis. Color code corresponds to taxonomic affiliation.

(

  L. Cabrol), the Severo Ochoa Excellence Program postdoctoral fellowship awar ded in 2021 to Eric Capo (CEX2019-000928-S), and the Ramón y Cajal program (RYC2019-028400-I, AEI Spain) awarded to Andrea G. Bravo. We acknowledge the Dutch funding agency (project number: 822.01.015) of the national science foundation NWO for funding this work as part of GEOTRACES. L.-E.H.-B.'s work was supported by research grant ERC-2010-StG_20091028 from the European Research Council.

TABLE 1

 1 Description of samples included in this study and summary of the main measured geochemical parameters, available from Rosati et al. (25) (for MEDBlack samples) and from Sollai et al. (33) (for Phoxy cruise) a

Sample name Cruise campaign Sampling depth (m) Concentrations of dissolved elements Method O 2 (µM) HS -(µM) NH 4 + (µM) PO 4 3-(µM) tHg (pM) MeHg (pM)

	F1-OL	MEDBlack	55.5	142.4	<LoD	<LoD	0.7	1.4	0.2	MB, qPCR
	F1-SOL	MEDBlack	85.7	3.4	<LoD	0.1	0.9	1.4	0.1	MB, qPCR
	F1-AOL	MEDBlack	145.3	<LoD	19.3	13.5	5.0	3.1	0.8	MB, qPCR
	F2-OL	MEDBlack	24.2	423.0	<LoD	0.2	<LoD	3.3	0.1	MB, qPCR
	F2-SOL	MEDBlack	99.5	1.8	<LoD	3.9	6.2	1.6	0.2	MB, qPCR
	F2-AOL	MEDBlack	144.8	<LoD	22.6	15.2	5.0	5.3	0.8	MB, qPCR
	F9-OL	MEDBlack	45.8	213.1	<LoD	0.1	0.8	2.2	0.1	MB, qPCR
	F9-SOL	MEDBlack	100.4	1.8	<LoD	2.0	6.6	2.2	0.2	MB, qPCR
	F9-AOL	MEDBlack	149.6	<LoD	17.7	15.8	4.8	3.6	1.1	MB, qPCR
	F5-OL	MEDBlack	40.5	373.8	<LoD	0.1	<LoD	2.8	0.1	MB, qPCR
	F5-SOL	MEDBlack	110.4	1.8	<LoD	3.6	7.0	3.2	0.4	MB, qPCR
	F5-AOL	MEDBlack	149.4	<LoD	15.3	13.8	4.8	3.3	0.8	MB, qPCR
	F6-OL	MEDBlack	40.3	377.0	<LoD	<LoD	<LoD	3.0	0.1	MB, qPCR
	F6-SOL	MEDBlack	175.0	10.7	<LoD	0.2	3.1	2.9	0.4	MB, qPCR
	F6-AOL	MEDBlack	250.3	<LoD	36.5	19.2	4.9	3.3	0.8	MB, qPCR
	F2-50	Phoxy	50	121.2	<LoD	0.1	0.7	Nd	Nd	MG
	F2-70	Phoxy	70	2.2	<LoD	0.1	1.1	Nd	Nd	MG
	F2-80	Phoxy	80	<LoD	<LoD	0.1	1.1	Nd	Nd	MG
	F2-85	Phoxy	85	<LoD	<LoD	0.1	0.8	Nd	Nd	MG
	F2-90	Phoxy	90	<LoD	<LoD	0.4	2.1	Nd	Nd	MG
	F2-95	Phoxy	95	<LoD	<LoD	1.1	4.7	Nd	Nd	MG
	F2-100	Phoxy	100	<LoD	<LoD	5.7	7.2	Nd	Nd	MG
	F2-105	Phoxy	105	<LoD	0.9	7.2	7.9	Nd	Nd	MG
	F2-110	Phoxy	110	<LoD	4.6	8.8	6.7	Nd	Nd	MG
	F2-130	Phoxy	130	<LoD	14.7	13.9	5.5	Nd	Nd	MG
	F2-170	Phoxy	170	<LoD	31.6	20.1	4.9	Nd	Nd	MG
	F2-250	Phoxy	250	<LoD	84.7	32.6	5.2	Nd	Nd	MG
	F2-500	Phoxy	500	<LoD	206.3	59.8	6.8	Nd	Nd	MG
	F2-1000	Phoxy	1,000	<LoD	353.8	90.8	7.9	Nd	Nd	MG
	F2-2000	Phoxy	2,000	<LoD	397	100.2	8.4	Nd	Nd	MG

a Detailed data sets including additional measured parameters are provided in Data Sheet S1A and B. Nd, non-determined; LoD, limit of detection. The "method" column stands for the molecular methods applied in the current study: MB for metabarcoding, qPCR for quantitative PCR, MG for metagenomics.

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Aix Marseille University, Univ. Toulon, CNRS, IRD, Mediterranean Institute of Oceanogra phy (MIO) UM 110, Marseille, France

Institute of Ecology and Biodiversity (IEB), University of Chile, Santiago, Chile

Department of Marine Biology and Oceanography, Institute of Marine Sciences, CSIC, Barcelona, Spain

Department of Aquatic Sciences and Assessment, Swedish University of Agricultural Sciences, Uppsala, Sweden

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The authors declare no conflict of interest.

See the funding table on p. 15.

ACKNOWLEDGMENTS

This study was financially supported by the French National Research Institute for Sustainable Development (IRD) through the M.I.O. internal grant "ACTION SUD-Commet" We thank the chief scientists of the MEDBlack cruise, M. J. A. Rijkenberg, L. J. A. Gerringa, and the shipboard party for their support. A special thanks goes to Matthew Patey for handling the in situ pumps. We thank Sophie Guasco at the M.I.O. for technical support with cloning sequencing of hgcA genes. The computations were performed on resources provided by the Swedish Research Council (grants to S.B.) and SNIC through Uppsala Multidisciplinary Center for Advanced Computational Science (UPPMAX) using the compute project SNIC 2021/5-53.

The authors have no competing interests to declare.

FUNDING Funder

Grant(s) Author(s)

DATA AVAILABILITY

Raw sequences have been deposited at NCBI GenBank, SRA database, under the BioProject accession number PRJNA895066.

ADDITIONAL FILES

The following material is available online.

Supplemental Material

Supplemental Information (mSystems.00537-23-s0001.docx). Table S1, supplemental text, and Figure S1 to S4. Data Sheet (mSystems.00537-23-s0002.xlsx). Environmental and molecular data from both cruises, OTU abundance table and taxonomy, hgcA and hgcB genes found in Phoxy cruise metagenomes, and community composition.