Materials and methods

2.2.3.1 Study site and sampling

The Marennes-Oleron Bay is located in the middle of the Atlantic French coast (N 45°

54’, 53; W 01° 05’, 23). Sampling was performed in the ridges at low tide with similar tidal range (5.5 +/- 0.2 m). Two contrasted weather conditions were compared: high temperature and irradiance (July 5^th 2012) and low temperature and irradiance (February 11^th 2013). In this study we did not consider the two sampling dates as two seasons because we sampled one day that might not be reflective of the entire season. The texture of the sediment is muddy and grain size range from 8.68 to 14.37 µm. For each sampling date, triplicate 15-cm diameter cores were sliced in five layers from 0 to 10 cm below sediment surface (bsf) (D1 = 0 to 0.5 cm; D2 = 0.5 to 1 cm; D3 = 1 to 2 cm; D4 = 2 to 5 cm and D5 = 5 to 10 cm). Each sediment layer was homogenized directly in a sterile box on the field and brought back to the beach in the dark in a cool box (4°C). Samples were subdivided using 50 mL sterile syringes with cutoff tips for further analysis (storage conditions differ according to parameter). In parallel, triplicate 12-cm cores were recovered for the determination of pore water nutrient Massachusetts, USA) fixed on a homemade stick that was vertically pushed into the sediment to stabilize the sensors at the 5 depths (0.5 cm, 1 cm, 2 cm, 5 cm and 10 cm bsf). Pore water pH and salinity were measured on supernatant after sediment centrifugation (15 min, 3,000 g at 4°C) with a pH probe (Eutech Instruments PC150, USA) and a conductivity meter (Cond 3110, TetraCon 325, WTW, Germany) respectively. Pore water content was quantified by weighting 50 mL of fresh sediment before and after drying (48h at 60°C). Porosity was calculated as the ratio of the volume of water divided by the total volume of sediment. For particular organic matter analysis (POM; nitrogen: PON and carbon: POC), lyophilized and decarbonated samples were by the combustion method (Strickland and Parsons, 1972) using a CHN elemental analyzer (Thermo Fischer Flash EA 1112).

For nutrient concentration analyses, pore water was immediately sampled from the 12-cm diameter cores on the site for the 5 depths, using the Rhizons® (Rhizosphere Research Products, NL-6706, Wageningen) method (Seeberg-Elverfeldt et al., 2005) and interstitial water was stored at -20°C for further measurements. Nutrient concentrations (nitrites (NO2

-), expressed as µg µg^-1 dry weight (DW) according to Lorenzen (1966).

Prokaryotic abundance (PA) was evaluated by flow cytometry after a cell extraction procedure according to Lavergne et al. (2014). Briefly, the extraction was based on successive dilution in a detergent mix, a mechanical separation followed by counting the extracted cells stained with SYBRGreen I through flow cytometry.

2.2.3.3 Nucleic acid extraction

DNA was extracted from ~1g of thawed sediment (stored at -20°C) using the UltraClean Soil kit^® (MOBIO) according manufacturer recommendations to maximize yields. Samples were then stored at -20°C until quantitative PCR (qPCR) and pyrosequencing.

2.2.3.4 Nitrogen-related functional gene quantification by qPCR

Bacterial and archaeal 16S rRNA gene and six N-related genes (Table 17) were quantified based on fluorescent dye SYBRGreen I in each sediment DNA extract. The reaction mix (20 µL) contained 0.45 µM of each primer, 0.5-5 ng sample DNA, 10 µL of Master Mix (Maxima SYBRGreen/ROX, Fermentas) and qsp 20 µL nuclease-free water. All reactions were performed in triplicates using the thermocycler MxPro3000 equipped with MxPro software (Stratagene). For Archaea and Bacteria quantification, the thermal program used was: 50°C for 2 min, 95°C for 10 min, 45 cycles of denaturing (30 s at 94°C for Archaea, 1 min at 95°C for Bacteria), annealing (30 s at 64°C for archaea and 40 s at 57°C for Bacteria extension (40

qPCR efficiencies were 86-101% and correlation coefficients (R²) were always higher than 0.91 (Table S3). Gene copies number was expressed per gram sediment dry weight (DW) taking into account the copies of each gene per genome: 1 copy per cell of archaeal amoA (Blainey et al., 2011), nirS, nirK, nosZ (Philippot, 2002), 2.5 copies of bacterial amoA (Arp et al., 2007) and 4.3 copies of 16S rRNA gene for Planctomycetes Bacteria (mean based on the available genomes). Log10 ratio AOB:AOA was calculated according to Santoro et al.

(2008).

2.2.3.5 454 Pyrosequencing and bioinformatic analysis

Amplification of the V3-V5 region of the 16S rRNA gene was performed with primers: 563F (AYT GGG YDT AAA GNG) and 907R (CCG TCAA TTC MTT TGA GTT T) for Bacteria and 519F (CAG CCG CCG CGG TAA) and 915R (GTG CTC CCC CGC CAA TTC CT) for Archaea. Pyrosequencing was achieved by the GATC plateform (Konstanz, Germany) by using a Roche 454 GS-FLX system with titanium chemistry. Raw sequences for Archaea and Bacteria were cleaned according to procedures consisting in the elimination of sequences presenting ambiguous bases “N”, a quality score <30 for Archaea and <27 for Bacteria, length shorter than 200pb and with a mismatch in the forward primer. The remaining reads were clustered at 97% similarity threshold (Kim et al., 2011) and representative sequence for each OTU were inserted in phylogenetic trees for taxonomic annotation. The process was February) at 5 sediment layers (see “Study site and sampling” section). Sampling triplicates were pooled after PCR assays before purification of PCR products. For bacterial analysis, six samples were retained for the analysis because, 1) we do not managed to sequence samples from 2 to 10 cm bsf in July (J-D4 and J-D5) and from 5 to 10 cm in February (F-D5); and 2) F-D4 was excluded because of a large chloroplast amplification bias in the sample. For Bacteria, in our dataset, 44% of total operational taxonomic units (OTUs) number were

singletons, after removing these singletons, 6 645 OTUs were retained. In the same way, 46%

of archaeal OTUs were singletons and 1025 OTUs were retained for the analysis.

2.2.3.6 Statistical analysis

In the results section, all values are presented as mean ±SE. In order to determine if two variables belong to the same population, student tests (t test) or wilcoxon tests were performed, according to the normality of the data. Spearman was used to measure and test the correlation between functional genes and environmental variables. Non-metric Multidimensional Scaling (NMDS) was performed based on the Bray-Curtis dissimilarity matrix of relative abundance of total archaeal Operational Taxonomic Units (OTUs) and coupled with fitting environmental variables in order to evaluate the drivers of the composition of the community. Then, the number of significant clusters was estimated by the Mantel optimal number of groups followed by a hierarchical ascendant classification (HAC) and significant groups were plotted on the NMDS ordination. The relationship between the functional genes (² transformed) and 8 environmental parameters was assessed by canonical correlation analysis (CCA). These analyses were performed with the VEGAN package (http://cran.r-project.org/web/packages/vegan/index.html) in R.

2.2.4 Results

2.2.4.1 Environmental parameters of sediments of Marennes-Oleron Bay

The temperature weakly fluctuated among vertical depth, but strongly varied between sampling dates as maximum values were recorded in July (21.6 ±0.15°C) and minima in February (8.9 ±0.13°C). Salinity rose to 45.37 ±2.32 in surficial sediment in July and was lower deeper throughout the whole sediment (< 37.5 in July and < 29.5 in February). In February, salinity never compassed 30 and was stable throughout the studied sediment depth.

The algal biomass on the surface (D1) was 69.5 ±2.35 µg Chl a g^-1 sed DW in July and 59.4

±1.72 µg Chl a g^-1 sed DW in February (Figure 52A & D). This algal biomass showed an exponential decrease with values never exceeding 17.4 µg Chl a g^-1 sed DW under 0.5 cm below sediment surface (bsf). The porosity of the sediment was almost lower in deeper layer with values ranging from 0.68 to 0.79 regardless of the sampling date. Concerning pore water nutrients, NO2

+ NO3

(NOx) concentrations tended to be higher in July between 1 and 2 cm bsf (8.3 ±0.37 µM, Figure 52B). In contrast, NOx concentrations in February were highly variables and tend to be higher in surface between 0 and 0.5 cm bsf (Figure 52E).

NH4+

concentrations were two times lower in July than in February (Figure 52B & E) and were always higher in deeper layers (5-225 µM).

The abundance of prokaryotes followed a decreasing gradient regardless the sampling date (Figure 52C & F) except in surficial sediment in February where their abundance exhibited low values. Prokaryotic abundance ranged from 1.08 ±0.75×10¹⁰ to 3.45 ±1.05×10¹⁰ cells g^-1 sed DW. The percentage of Archaea (quantified by qPCR) ranged from 4.7% to 39.6 % of total prokaryotic 16S rRNA genes from surface to deeper layers (Figure 52C & F). This proportion of Archaea was significantly correlated with ammonia concentration (Spearman correlation: ρ = 0.46, P = 0.011, n=30) and negatively correlated with chlorophyll a and porosity (Spearman correlation: ρ = -0.88 and -0.66 respectively, P<0.01, n=30).

2.2.4.2 Bacterial diversity, the predominance of Proteobacteria

The structure of the bacterial community was assessed by 454 pyrosequencing on the bacterial 16S rRNA genes. The Shannon index, used as a proxy of the bacterial community diversity (at the OTUs level), was higher in July (7.06) than in February (6.63) (Table 18). The total number of OTUs in each sediment sample ranged from 2376 to 3273 OTUs with coverage always higher than 86% (Table 18) and rarefaction curves reaching a plateau (Figure 59).

Considering the 1000 most abundant OTUs, no variation in bacterial OTUs number within phyla was recorded among sampling dates and depths (Figure 53). Our samples were highly diverse as 40 phyla were represented and retrieved in almost all the samples resulting to a high similarity value (mean = 86.7%) between samples (always higher to 79%, Table 19).

The lowest similarity was observed between D1 in February and D3 in July notably due to the difference in abundance of Planctomycetes (333 and 1095 sequences respectively) and Proteobacteria (6129 and 4653 sequences respectively). The dominant phylum was the Proteobacteria, representing 48%-62% of the total bacterial sequences. Within Proteobacteria, δ-proteobacteria accounted for 41-57%, γ-proteobacteria contributed to 29-44%, α-proteobacteria contributed to 8-11% and β-proteobacteria were the less prevalent contributing to 0.9-1.5% (Figure 54). The δ-proteobacteria were represented by 210 different OTUs and mostly by the Desulfobacterales which are sulfate-reducing bacteria (SRB). All others taxa contributed to a lesser extent (less than 5% of total bacterial sequences) except for the Planctomycetes with a prevalence of 6-17% across samples. Planctomycetes also exhibited a high diversity of OTUs compared to other taxa and were represented by 72 OTUs (Figure 52). Nitrospirae, Chloroflexi and Planctomycetes 16S rRNA gene sequences relative abundance followed an increasing gradient with depth from 0 to 2 cm bsf (D1-D3) (Figure 53). Acidobacteria and Bacteroidetes never encompass 5% and both always accounted for 8%

of the bacterial community. The Chlamydiae was the less dominant taxa and was only present in D1 in July and in D2 in February.

Figure 54. 16S rRNA gene relative abundance and affiliation of the 1 000 most abundant bacterial operational taxonomic units (OTUs) on the phylum level among sampling dates (July = July 5^th, 2012, February = February 11^th, 2013) and vertical depth gradient below sediment surface (bsf). Pie charts are relative abundance of the Proteobacteria in each sample.