Archaea dominate subsoil oxic communities over time scales of millions of years | EXCLUSIVE OFFER !


Marine sediments are estimated to contain> 1029 microbial cells (1), which represent an omnipresent "deep biosphere" (2) extending at least up to 2500 meters under the seabed (mbsf) (3). The abyssal clay in the ultraoligotrophic regions of the ocean is generally oxic across the entire column of sediment up to the underlying oceanic crust; it is predicted that oxygen (O2) diffuses through the sediments to the igneous subsoil in 9 to 37% of the global seabed (4). These aerobic communities have extremely low metabolic activity (5) and live near the low energy life limit (4), surviving at ultra-low average respiration rates (6). The diversity, abundance, and metabolic potential of deep subsoil aerobic communities are still poorly understood. The genetic characterization of these aerobic communities is limited to the relatively low depth of 0.5 mbsf (7), compared to the anoxic sediment communities for which genetic records extend to 2500 mbsf (3).

Most of the deep biosphere studies of oxic abyssal clay have focused on Pacific sites, where cell abundance has declined6 cells / cm3 at the bottom (surface) at 103 cells / cm3 at ~ 10 mbsf (1, 4). Isotopic analyzes at oxic sites in the North Atlantic subsoil suggest the initiation of active nitrification, indicating that the oxidative nitrogen cycle may be an important feature of the microbial communities below. Abyssal seabed (8, 9). In accordance with these isotopic studies, the upper 50 cm of the South Pacific gypsum sediments contain ammonia-oxidative archaea (AOA) (7, ten), which is a key group contributing to the carbon cycle of the deep ocean in the water column (1113) and the benthos (1417).

The microbial community of the deep seabed is characterized by various assemblages of bacteria and archaea (18), with abundances ranging from 106 at 109 cells / cm3 sediments, tending to increase concentrations at higher latitudes (15). However, much less is known about the diversity and metabolism of microbial communities in oxic sediments located below the seabed of oligotrophic oceanic regions (19). The lack of knowledge of subsoil aerobic microbiomes is particularly notable compared to the relatively high number of surveys conducted on anoxic sites below the floor (20). We have therefore sought to characterize the diversity, abundance, functional potential and viability of aerobic microbiomes located in the abyssal abyssal red clay of the subsoil of an ultra-oligotropic zone of the North Atlantic.

We optimized a DNA extraction protocol for lean ultra-organic sediments, which increased DNA yields, allowing for 16-fold sequencing.S The rRNA and ammonia monooxygenase (amoA) genes, as well as the metagenomes, originate from two deep oxic sedimentary nuclei of the subsoil reaching about 15 million years ago. In addition, we demonstrate the viability of uncultivated microbial populations via 18O-labeling in long-term incubations (18 months) in the presence of H218O, a method of identifying actively growing microbes (21, 22). The results show that in these viability experiments, actively growing AOA populations dominate all other microbial populations in the samples taken throughout the core sediment column. The metagenomic analysis of the same samples shows that the potential coupling of chemolithoautotrophy and mixotrophy, fueled by the oxidation of ammonia, could help maintain a subsistence of AOA of several millions of years in this private habitat of energy.


We obtained sediment by multiple coring (0 to 0.22 mbsf), gravity coring (0.2 to 2.8 mbsf) and deep coring (1 to 28 mbsf) of oxygenated abyssal clay from two sites. of the North Atlantic (Table S1). These sites are located on ultra-oligotrophic high seas and are characterized by an average sedimentation rate of 1 m per million years (4). Thus, the deepest recovered sample was deposited approx. There are 28 million years. O draw2 with increasing depth at both sites (Figure S1) reflects the oxidation of organic matter by aerobic microorganisms. The corresponding accumulation of dissolved nitrate (NO3) (Fig. 1) reflects the ammonium oxidation released in the stoichiometry of C: N Redfield organic matter (Fig. S2), directly reflecting the activity of aerobic nitrifying microbial communities and consistent with isotopic analyzes of dissolved nitrogen from similar sites in the North Atlantic (8, 9). These biogeochemical data indicate that nitrification, an important feature of deep-sea planktonic ecosystems (11), is also a major mechanism for preserving these energy-limited aerobic communities located below the abyssal seabed for millions of years. To better understand the internal functioning of microbial survival on such (geologic) time scales, we performed quantitative gene sequencing, metagenomics, and stable isotope probing to characterize diversity, abundance, metabolism. and the activity of specific microbial groups.

Fig. 1 Microbial diversity, abundance and nitrification in the abyssal subsoil of the North Atlantic.

(A) Left: dissolved nitrate, quantitative polymerase chain reaction (qPCR) of 16S RRNA and AOA amoA genes and qPCR normalized abundance of bacteria and archaea 16S rRNA genes. Right: diversity of 16S rRNA genes. Note that two biological replicates were sequenced at site 11, 2.8 mbsf deep. The arrows indicate the depths of 18O-labeling of incubations. (B) Non-metric multidimensional scale analysis of 16S rRNA genes, the size of the points (samples) is normalized by the number of 16S The number of copies of rRNA genes per sample (qPCR), the numbers above each point indicate the depth in meters below the ocean floor, and the shaded areas indicate the relationship between the archaeal and bacterial sequences. ANOSIM analyzes were performed on groups of samples, as indicated by the dashed lines. Note that each meter in (A) represents approx. 1 million years of sediment deposition and the communities of the deepest sample at Site 11 have been around for about a year. 15 million years.

Our optimized DNA extraction protocol allowed us to reach a detection limit of 102 gene copies per gram of extracted sediment (see Materials and Methods) and allowed us to characterize these basement communities up to 15 mbsf (Fig. 1A). Because the sedimentation rate is 1 m per million years (4), the microbial communities in the deepest samples (Fig. 1A) persisted in the subfloor for approx. 15 million years. To our knowledge, these metagenomic data are the deepest and oldest geologically, from abyssal abyssal clay to sub-floor to date.

At both sites, the number of 16S The copies of the rRNA and amoA gene of AOA are up to an order of magnitude greater than the number of bacteria.S copies of the rRNA gene on the surface of the sediment, while 16S Chloroflexi-related copies of rRNA genes gradually increase in number with depth below the ocean floor (Fig. 1A). The most abundant Chloroflexi operational taxonomic unit (OTU) at both sites was affiliated with SAR202 clade, a typical deep-water and sediment inhabitant (23). It codes for monooxygenases catalyzing the insertion of oxygen into relatively unreactive aromatic hydrocarbons, indicating an ability to metabolize older, less reactive and highly persistent organic materials (23). This character of SAR202 can be selected in underwater abyssal clays, where the organic matter is relatively unreactive and extremely scarce (4), but necessary to ensure long-term survival (24). In the oxic sediment of the South Pacific Gyre subfloor, O2 the consumption rates are higher than can be explained by the oxidation of heterotrophic particulate organic carbon (POC) alone (4, 25). O2 The consumption of chemolitho-autotrophic AOA is responsible for underwater breathing that can not be explained by the aerobic degradation of POC via microbial heterotrophy.

The increase of NO3 The depth concentrations associated with the high abundance of AOA indicate active nitrification and in situ ammonia oxidation. Superior O2 Higher withdrawal rates and nitrification rates are observed at site 11 relative to site 12, which correlates with higher microbial abundances at site 11 (Fig. 1A and Fig. S1). Similar to O2 profiles (Fig. S1), 16S The copies of the rRNA and amoA gene per gram of sediment decrease exponentially with depth at both sites (Fig. 1A). This profile is consistent between the samples acquired through multi-core drilling, gravity coring, and long cores (Fig. 1A and Table S1).

Our results show that the DNA extracted from the sample comes mainly from living cells in sediment, as opposed to extracellular DNA (eDNA), for several reasons. First, the cDNA binds to the charged mineral surfaces, making it resistant to DNA extraction (26). Our experimental data demonstrates this point because an artificial cDNA extract containing> 109 16S The rRNA genes per gram added to the "killed" controls (autoclaved) were detected only <103 16S RRNA genes per gram after re-extraction of DNA from the autoclaved sediment (Fig. 2). This weak recovery of cDNA with our protocol is probably due to the majority of the cDNAs being chemically bound to clay minerals (26). In contrast, the DNA extracted from "living" (immaculate frozen) sediments contained 106.5 at 102 16S rRNA genes per gram of sediment (Figure 1A). In addition, the same cDNA extract was used as a nutrient source by the growth of microbes in "live" suspensions (not autoclaved) during a 210-day incubation (Fig. 2). Although microbial activity in sediment increases in sludge compared to intact carrots (27), the experiment shows that viable cells of the sediment have the potential to use a bioavailable DNA. It also suggests that some microbes can use mineral-related cDNA as a growth substrate. All of these data sources indicate that the extractable DNA from our samples comes mainly from viable cells living in sediments.

Fig. 2 Use of cDNA by live microbes and lack of detectable cDNA added to autoclaved sediments.

The samples derived from 2.8 mbsf, the depth used for the 18Site O-SIP experiment 11. The lack of detection of DNA in autoclaved sediments, where the addition of e-DNA after autoclaving (open circles) indicates that the l-39 DNA is tightly bound to sediment particles such as clay minerals and the DNA extracted with our protocol should target intact living cells, and it is unlikely to be biased by dead microbes cDNA. The error bars represent the range of three technical replicates.

To further identify viable microbial populations, we used H218O in long-term incubations, such as 18Incorporation of labeled water can be used to identify actively growing populations within complex microbial communities from environmental samples (22). After 7 and 18 months of incubation with H2180, there was measurable respiration and density gradient centrifugation followed by a quantitative polymerase chain reaction (qPCR) revealed that 16S rRNA genes have been enriched in 18O (Fig. S3). High throughput sequencing of 16S rRNA genes in individual density fractions in 18Control treatments labeled O ("Tag-SIP") have identified more than 50 actively growing treatments (18OTU) (Table S2), corresponding to 4 to 9% of the total number of OTUs detected in situ (not = 480).

Of the 10 most in situ OTUs, three were affiliated with AOA (Thaumarchaeota) and were all 18O-labeled, demonstrating their viability and activity (Fig. 3). Most arched OTUs that were 18The net presence of growth at least marked on the label O (Figure S4). Although the term "net growth" may have different meanings depending on the experimental configuration, we use this term in our experiment to refer to the increase in the standardized abundance of 16 qPCR.S rRNA genes by OTU compared to the T0 value (there axis in fig. S4, B and C). This minimal net growth of AOA suggests that some 18O tagging of these archaea can occur via growth-independent cell maintenance activities, such as DNA repair. In bacteria, incorporation of 18O Marked water occurs exclusively during the replication and growth of DNA (22), but we do not know if this model also applies to archaea. The most abundant OTU in situ at both sites is a viable solution (18The O-labeled AOA population persists as the dominant population in all two sediment sequences sampled, dominating the microbial community at several depths of more than an order of magnitude (Figure 3). This viable AOA population has thus dominated the two underwater ecosystems sampled for millions of years, which, to our knowledge, is the longest period of time when aerobic archeology has been reported to dominate an underground habitat.

Fig. 3 In situ distributions of the most abundant populations and 18O-labeling.

The most abundant in situ populations are indicated, indicating those that were viable (18O-marked) in H218O incubations. Asterisks indicate the depths of 18O-labeling of incubations. Note that only one viable population of AOA (Thaumarchaeota), OTU3, dominated the microbial communities at both sites and that each meter represents approx. 1 million years of sediment deposition (the deepest sample is about 15 million years old).

On both sites, the 16S The rRNA and amoA genes of AOA are distinct from planktonic AOA (28) and most closely related to benthic AOA, including those detected in the abyssal sediments of South Pacific gyres (Fig. 4B and Fig. S5) (7, 29). Below 1 mbsf, the microbial communities between sites 11 and 12 are significantly different (similarity analysis (ANOSIM), P <0.01) (Fig. 1B) and exhibit diverse protein-encoding genes, with site 11 communities having higher metabolic diversity (Fig. 5A), which coincides with higher nitrification rates (Fig. 1A). The different levels of nitrification are furthermore consistent with different clades of submarine amoA genes at sites 11 and 12 (FIG. 4B). However, only one 16S The OTU rRNA gene of Thaumarchaeota is dominant at both sites (Fig. 4A). This indicates that two different oxidant ammonia variants within this dominant AOA population are selected at sites 11 and 12, and that the selected AOA variant at site 11 is likely to be present at sites 11 and 12. origin of higher nitrification rates compared to site 12.

Fig. 4 Diversity of 16S RRNA and amoA genes from AOA.

(A) Histograms showing the relative abundance of AOA OTUs based on 16S rRNA gene data. Asterisks mark the OTUs that were 18O-labeled in long-term incubations. (BPhylogenetic analysis (PhyML) of genes coding for amoA of AOA at sites 11 and 12. It should be noted that the amoA genes of sites 11 and 12 form two separate clades supported by the bootstrap and consisting mainly of deeper sequences (6.6 and 12 mbsf), which probably derive from the very abundant OTU3 in these deeper intervals (in (A)). Tree is based on an alignment of 655 nucleotides under a model of general reversible evolution over time (GTR) with four categories of rate. Bootstraps were calculated from 100 replications.

Fig. 5 Taxonomic representation and metabolic potential in metagenomes.

(A) The number of ORFs as a function of depth at sites 11 and 12. (BRelative abundance of taxonomic groups represented in the metagenomes. (CRelative abundance of metabolic functions in metagenomes. The amoA and HP / HB genes were encoded only by Thaumarchaeota (AOA). In both cases (B) and (C), "percentage of mapped reads" refers to the percentage of raw reads mapped to ORF coding contigs.

The in situ dominance of Thaumarchaeota in this energy-free environment over such long periods of time is consistent with the adaptation of marine AOA to oligotrophic environments with low nutrient fluxes (11, 30) such as ammonia (31), which is generally lower than the detection in oxic clay of the subsoil (9). Benthic AOAs generally represent distinct lineages of planktonic groups (Fig. 4B) (16), which may correspond to different physiologies, allowing benthic AOA to exploit submarine sedimentary environments (32). Thus, we carried out a functional metagenomics to better understand the potential metabolism of the success of these AOA dominating aerobic microbial communities of the subsoil for millions of years.

The metagenomes of each sample were sequenced to an average depth of 15 million readings, and the de novo assembly gave a total of 177,498 contigs on all sequenced samples (Table S3). A total of 66 to 95% of the raw readings could be related to the contigs, indicating that the de novo assembled contigs accounted for most of the data obtained (Table S3). There is a tendency for exponential decrease in functional gene diversity with depth at both sites (r = 0.95), the number of genes encoding proteins decreasing more rapidly over time at site 12 relative to site 11 (Figure 5A). Consistency with the dominance of AOA in the 16S As the rRNA and amoA gene datasets (Figure 1), the metagenomes of both sites are dominated by genes encoding proteins with the greatest similarity to Thaumarchaeota (Figure 5B). All the amoA genes detected in the metagenomes had the greatest similarity with Thaumarchaeota. After Thaumarchaeota, the protein coding genes at depths sampled at both sites were dominated by chloroflexi, Deltaproteobacteria, and Phyla candidate radiation (Figure 5B). The nitrite oxidizing groups Nitrospirae and Nitrospinae are also represented in the metagenomes, as are the ANME-2d and NC10 groups in relatively lower abundance (Figure 5B).

The relative abundances of metabolic pathways and functional gene categories observed in metagenomes are generally consistent for the two sampled sites (Fig. 5C). For example, the hydroxypropionate / hydroxybutyrate (HP / HB) pathway and the Thaumarchaeota amoA genes were dominant at each site. Open reading frames (ORFs) encoding proteins very similar to those involved in the reducing tricarboxylic acid (rTCA) cycle were detected only at site 11 in relatively low abundance (Figure 5C), indicating that organisms encoding this pathway are present lower abundance than those coding for the HP / HB carbon binding pathway. Nitrite-oxidizing bacteria in the deep oceanic waters bind carbon through the rTCA cycle, which is a major component of deep-sea bacterioplankton (33). Our results indicate that carbon fixation by NOBs via rTCA could also continue in deep oxic sediments of the subsoil.

ORFs encoding proteins with similarity to Archean viruses and bacteriophages at both sites show potential for regeneration of microbial necromass. It was concluded that the viruses were active in submarine sediments (34), and viral-like particles are abundant in the abyssal oxic clay of the South Pacific Gyre (35). Viruses can play a key role in the regeneration of microbial necromass in marine sediments (36), possibly allowing a subsistence over long periods (19). The increased growth in the presence of eDNA extract compared to a control (Fig. 2) indicates that microbes in oxic submarine oxic sediments could use necromass (eg, the eDNA) released by viral lysis. The viral lysis of AOA could also explain the minimal net growth of active growth (18OA labeled AOA in long-term incubations (Figs S4, B and C), keeping permanent stocks of AOA down. Genes encoding proteins with high similarity to Thaumarchaiens viruses (37) were relatively abundant in metagenomes compared to bacteriophages (Fig. 5C).

H2 Radiolysis of water has been proposed as a major energy source in abyssal oxic clay (5). The recovered metagenomes corroborate this hypothesis in the form of ORFs homologous to Hup / Hox / Hyp hydrogenases involved in H2 oxidation (38) are relatively abundant and detected at both sites (Fig. 5C). The majority shows the greatest similarity to a NiFe-hydrogenase from a "new Proteobacteria taxon" found in surface sediments of the South Pacific Gyre (Table S4) (39). Hydrogenases were also similar to those detected in underground terrestrial metagenomes (Table S4) in a suboxic / anoxic aquifer (40), indicating that several groups of H2Oxidative micro-organisms remain in the oxic sediments of the subsoil. The results indicate that the aerobic and energetically favorable H2 oxidation (41) is a potentially important form of energy metabolism at the bottom of the deep seabed. Some representatives of ONB and Woesearchaea, groups present in the 16S data (Fig. 1A), are also capable of aerobic H2 oxidation (38) (42). However, hydrogenases from these groups were not detected in metagenomes, probably because of their lower abundance (Figures 1 and 5B).

The carbon fixation pathways in metagenomes are dominated by the HP / HB cycle (Figure 5C) exclusively encoded by Thaumarchaeota (AOA). The dominance of Thaumarchaeota (Figures 1A and 5B) in this context of lack of energy can be explained in part by their use of a modified HP / HB cycle, which is the most energy-efficient aerobic carbon binding pathway (43). Energy-efficient metabolism can be expected to improve physical fitness in oxic sediments, where surviving cells face a constant energy limitation (4). In addition, the ability of some AOAs to practice mixotrophy (17, 28, 44, 45) can enable them to supplement their carbon demand with organic carbon. Not all amoAcarrying Thaumarchaeota are mandatory chemiolithoautotrophs (46).

The metagenomes demonstrate a mixotropic capacity of AOA, as genes encoding thaumarche transmembrane transporters for organic matter including peptides, amino acids and sugars (Figure 6A). The metabolic transport potential of peptides and amino acids is several orders of magnitude higher than that of sugars and urea in these metagenomes, indicating that peptides and amino acids are important sources of carbon for the mixotrophy of AOA (Figure 5A). This is compatible with other deep-sea planktonic AOAs with mixotrophic metabolism, including the use of nitrogenous organic compounds (45). Transporters for ammonia lyases, deaminases and proteases originate mainly from AOA in almost every sample from both sites (Figure 6A). Ammonia lyases and deaminases are major classes of enzymes responsible for the production of ammonia during the degradation of nitrogenous organic compounds (amino acids, nucleotides and proteins), thus indicating that AOA dominated bacteria in terms of potential regeneration of ammonia. These metabolic characteristics of the AOA subfloor are consistent with the experiments that have shown that the planktonic marine AOA uses organic nitrogen for mixotrophic growth (47, 48).

Fig. 6 The metabolic potential of mixotrophic deamination is dominated by Thaumarchaeota.

(AThe top indicates the relative abundance of ORFs at site 11 (white bars) or at site 12 (black bars), corresponding to the transporters of organic matter, desiring enzymes (ammonia lyases and deaminases) and proteolytics (proteases). . The bottom shows the taxonomic affiliation of the same ORFs. (B) Conceptual model of how proteolysis and deamination of AOA could provide carbon sources for mixotrophic growth and supplemental energy (ATP) for chemolitho-autotrophic growth. The outer lines represent the archaeal cell membrane, which is less permeable and can help reduce the loss of intracellular regenerated ammonia. The H+"Represents protons derived from the oxidation of ammonia that can be used to produce additional energy (ATP) required for carbon fixation via the HP / HB cycle. pmf, motive force of the proton; CPR, candidate Phyla Radiation.

In deep seabed sediments, it has been proposed that AOAs benefit mainly from the ammonia produced by desiccant heterotrophic bacteria (39). However, our deep underground oxic metagenomes illustrate that the metabolic potential of using organic nitrogen and deamination is dominated by the mixotropic AOA that can oxidize regenerated ammonia via the # 39; amoA at the source of its creation: in the AOA cells (Figure 6B). The oxidation of ammonia produced by intracellular deamination represents an advantage in terms of shape in this energy-free setting, clearly limiting the diffusion loss of ammonia releasing energy from the cell. Such a potential mechanism of ammonia concentration would provide an advantage of AOA in oxic sediments, where ammonia concentrations are extremely low (9). Unique concentration mechanisms have been proposed as adaptation of deep-sea planktonic AOA ecotypes to low concentrations of ammonia (28). Such a mechanism is consistent with the "survival of the fewest" model for aerobic life in basements (49), with energy efficiency providing a selective advantage to long-term microbial sustenance in the oceanic seabeds underlying the oligotrophic ocean regions.

Aerobic oxidation of ammonia produced intracellularly by AOA deamination has the potential to provide additional energy (in the form of adenosine 5'-triphosphate (ATP)) to feed the fixation cycle HP / HB (Figure 6B), which depends on ATP (43). The metabolic potential of coupling in this way between chemo-litho-autotrophic metabolism and mixotrophic metabolism is correlated with an improvement in the ability, since the genes encoding the essential components of this metabolic coupling are dominated by AOA (Figure 6A), which is the most abundant group in the sampled sediment sequence. at both sites (Figures 1, 3 and 4). Compulsory mixotrophic growth of marine AOA occurs by using α-ketoglutaric acid as a carbon source (44). Since α-ketoglutaric acid is the keto acid produced by glutamate deamination, it is plausible that deaved AOA amino acids, such as glutamate, oxidize ammonia to extra energy, then assimilate the resulting organic carbon de-aminated (for example, the resulting α-ketoglutaric). acide) pour la construction de biomasse et / ou de processus de maintenance cellulaire (Fig. 6B).

Les archées anaérobies sont omniprésentes et dominent souvent les sédiments marins dépourvus d’énergie anoxique (5053), qui a été attribuée à plusieurs adaptations de l&#39;archaea anaérobie à des environnements anoxiques soumis à des contraintes énergétiques (54). Une adaptation majeure du potentiel énergétique des archées est souvent supposée être la perméabilité inférieure de leur membrane cellulaire par rapport aux bactéries, ce qui leur permet de réduire les pertes d’énergie (54). Notre étude montre que cette adaptation générale des archées peut également aider les populations d’archives aérobies (AOA) à dominer au sein des écosystèmes oxiques du sous-sol en limitant éventuellement la perte par diffusion de l’ammoniac régénéré de manière intracellulaire. L’oxydation de l’ammoniac régénéré intracellulaire produit par désamination de l’azote organique permettrait à ces AOA mixotrophes de produire l’ATP supplémentaire nécessaire à la fixation du carbone dans le cycle HP / HB (43). Comme le besoin en ATP pour le cycle de fixation du carbone hautement efficace en énergie de Thaumarchaeota est déjà relativement faible (43), le mécanisme unique de réduction de la perte d’énergie présenté ici expliquerait comment ces arches aérobies peuvent subsister en plus grande abondance par rapport à d’autres taxons pendant des millions d’années sous un stress énergétique constant dans les sédiments oxiques du sous-plancher.



Tous les échantillons ont été prélevés par Cruise KN223 du R / V Knorr, dans l&#39;Atlantique Nord, du 26 octobre 2014 au 3 décembre 2014 (Woods Hole, MA à Woods Hole, MA). Sur le site 11 (22 ° 47,0 ′ nord, 56 ° 31,0 ′ ouest, profondeur de l’eau ~ 5600 m) et sur le site 12 (29 ° 40,6 ′ nord, 58 ° 19,7 ′ ouest, profondeur de l’eau ~ 5400 m), des noyaux de sous-plancher progressivement plus profonds ont été prises avec un multicodeur (jusqu&#39;à environ 0,4 mbsf), un carottier gravitationnel (jusqu&#39;à environ 3 mbsf) et le dispositif de carottage à piston «long carottier» de 45 m de la Woods Hole Institution (WHI) ( / longcore /) (jusqu&#39;à ~ 28 mbsf) (table S1). Des détails supplémentaires sur l’échantillonnage aux sites 11 et 12 sont décrits par D’Hondt. et al. (4). Des sous-échantillons des sections de base pour l&#39;extraction de l&#39;ADN ont été prélevés à bord du navire immédiatement après leur récupération avec des seringues stériles de 60 ml, l&#39;extrémité du cône Luer coupée et congelée immédiatement à -80 ° C avant l&#39;extraction de l&#39;ADN. Sous-échantillons pour le 18Les expériences portant sur l’o-marquage ont été échantillonnées dans les sections principales de la même manière, mais ont été conservées à + 4 ° C avant la mise en incubation.

Chimie de l&#39;eau des pores

Des échantillons d’eau interstitielle sédimentaire pour les analyses de nitrates ont été obtenus à l’aide d’échantillonneurs d’humidité du sol Rhizon standard (55) (Rhizosphere Research Products, Wageningen, Pays-Bas). L&#39;échantillonnage de Rhizon a extrait l&#39;eau interstitielle du noyau sédimentaire en filtrant par aspiration à travers de minces tubes de polymère poreux hydrophile d&#39;un diamètre moyen des pores de 0,1 µm. Des rhizons (longueur de filtre de 5 cm) ont été insérés dans l&#39;une des extrémités d&#39;une section de noyau arrondie et un volume total allant jusqu&#39;à 10 ml d&#39;eau interstitielle a été extrait. Avant le déploiement, les échantillonneurs Rhizon ont été trempés dans 18 mégohms d’eau désionisée pendant plusieurs heures, puis rincés avec 30 ml d’eau désionisée filtrée par aspiration à travers chaque Rhizon. Après le lavage, les Rhizons ont été laissés à sécher sur du papier filtre. Les concentrations de nitrate ont été mesurées à bord d&#39;un navire à l&#39;aide d&#39;un CI compact Metrohm 844 UV / VIS avec une colonne Metrosep A Supp 8 150 de 150 mm sur 4,0 mm. Environ 0,8 ml d’eau interstitielle a été injecté manuellement dans une boucle d’échantillon de 250 µl; l&#39;échantillon a ensuite été élue de la colonne avec une solution à 10% de NaCl. L’absorbance à 215 nm a été utilisée pour la quantification. Un étalon de nitrate de sodium à 50 µM a été utilisé tous les cinq ou six échantillons pour corriger la dérive des instruments. Les concentrations en oxygène dissous dans les sections de noyau équilibrées ont été mesurées avec une solution optique en forme d&#39;aiguille.2 capteurs (optodes) (PreSens, Regensburg, Allemagne) décrits précédemment (56). L&#39;O dissous2 Les données de l&#39;expédition KN223 ont été signalées pour la première fois par D’Hondt et al. (4). Ils sont archivés et disponibles en ligne dans la base de données IEDA (Integrated Earth Data Applications) (

Extraction d&#39;ADN

Les sous-échantillons échantillonnés de manière aseptique avec des seringues stériles ont été sous-échantillonnés de manière aseptique dans une hotte à flux laminaire à ADN / ARN stérilisé aux ultraviolets (UV) / UV filtrée par HEPA. Pour réduire la contamination, la paraffine a été retirée et les 3 cm extérieurs de sédiment ont été poussés hors de la seringue, qui a ensuite été découpée à l&#39;aide d&#39;une spatule stérile chauffée au rouge. Une seconde spatule stérile et non utilisée a été utilisée pour échantillonner avec soin le centre non contaminé du noyau restant dans la seringue. L&#39;extraction de l&#39;ADN a été extraite de 10 g de sédiment en utilisant la méthode d&#39;Orsi et al. (57), modifié avec deux étapes de congélation / décongélation après homogénéisation. En bref, 10 g de sédiment ont été transférés dans 50 ml de tubes Lysing Matrix E (MP Biomedicals) contenant des billes de verre de silice et homogénéisés pendant 40 secondes à 6 m / s en utilisant un homogénéisateur FastPrep-5 5G (MP Biomedicals) en présence de 15 ml de tampon d’extraction filtré de manière stérile et préchauffé (65 ° C) (76% en volume de NaPO 1 M4 (pH 8), 15% en volume, 200% d’éthanol, 8% en volume de solution de tampon de lyse MoBio C1 et 1% en volume de SDS). Les échantillons ont été incubés à 99 ° C pendant 2 min et congelés pendant une nuit à -20 ° C, décongelés et recongelés à -20 ° C pendant une nuit, puis incubés à nouveau à 99 ° C pendant 2 min et une seconde homogénéisation à l&#39;aide des réglages décrit ci-dessus. Les étapes supplémentaires de congélation / décongélation, en particulier la congélation toute la nuit, augmentaient le rendement en ADN de 2 à 10 fois. Après la seconde homogénéisation, les échantillons ont été centrifugés pendant 15 min et les surnageants ont été concentrés à un volume de 100 ul à l&#39;aide de filtres centrifuges Amicon de 50 kDa (Millipore). Les acides humiques coextractés inhibant la PCR et d&#39;autres composés ont été retirés de l&#39;extrait concentré en utilisant le kit de purification PowerClean Pro DNA (MoBio). Des blancs d&#39;extraction ont été réalisés à côté des échantillons pour évaluer la contamination en laboratoire au cours du processus d&#39;extraction.

Réaction en chaîne de la polymérase quantitative

L&#39;ADN a été quantifié par fluorométrie à l&#39;aide d&#39;un Qubit avec un kit haute sensibilité pour ADN double brin (Life Technologies). qPCR was performed using the custom primer dual indexed approach that targets the V4 hypervariable region of the 16S rRNA gene (58) using updated 16S rRNA gene primers 515F/806R (515F, 5′-GTGYCAGCMGCCGCGGTAA-3′; 806R, GGACTACNVGGGTWTCTAAT) that increase coverage of ammonia oxidizing archaea and other marine strains (59). To measure the abundance of amoA genes from archaea, the primers Arch amoA-1F (STAATGGTCTGGCTTAGACG) and Arch amoA-2R (GCGGCCATCCATCTGTATGT) were used (16). qPCR reactions were prepared using an automated liquid handler (pipetting robot). The epMotion 5070 (Eppendorf) was used to set up all qPCR reactions and standard curves as described previously (60). The efficiency values of the qPCR was <90%, and R2 values were >0.95%. qPCR was performed using white 96-well plates as this was found to increase the signal-to-noise ratio in the SYBR green assay twofold compared to clear plates. The technical variability of 16S rRNA gene qPCR measurements was determined to be consistently <5% using the epMotion 5070.

16S rRNA and amoA gene sequencing

Barcoded V4 hypervariable regions of amplified 16S rRNA genes were sequenced on an Illumina MiniSeq following an established protocol (58). This yielded a total of >20,000,000 raw sequencing reads that were then subjected to quality control. To quality control the OTU picking algorithm for the data, we also sequenced a “mock community” alongside our environmental samples. The mock communities contained a defined number of species (not = 18) all containing 16S rRNA genes >3% difference (58). USEARCH version 10.0.240 was used for quality control and OTU picking (61), and OTUs were clustered at 97% sequence identity. The taxonomic relationship of OTU representative sequences was identified by BLASTn searches against SILVA database ( version 128. To identify contaminants, 16S rRNA genes from extraction blanks and dust samples from the lab were also sequenced. These 16S rRNA gene sequences from contaminants were used to identify any contaminating bacteria in our oxic abyssal clay samples. All OTUs containing sequences from these “contaminant” samples were removed before downstream analysis.

qPCR values of 16S rRNA genes in DNA extraction blanks were consistently <102 copies per extraction, and thus, we used 102 copies to define our detection limit for the abyssal clay samples. Consistent with this, high-throughput sequencing of amplicons with qPCR values <102 copies per gram of sediment had up to 50% sequence representation from contaminant taxa, whereas samples with values >102 copies per gram of sediment had <5% representation from contaminant taxa. This further supported our definition of <102 as a realistic detection limit. Using samples that had 16S rRNA gene copies >102 copies per gram of sediment, we were able to analyze microbial communities down to ca. 15 mbsf at site 11 and ca. 8 mbsf at site 12 (Fig. 1).

Thaumarchaeal amoA genes amplified via qPCR using the method described above were cloned using the TOPO TA Cloning Kit and Sanger-sequenced at the LMU Munich Sequencing Service at the Faculty of Biology ( Before phylogenetic analysis, the reads were quality trimmed in CLC Genomics using the default settings for quality control.

Experimental setups

DNA-SIP experiments with H218O were set up at two North Atlantic coring sites: sites 11 and 12 from depths of 2.8 and 3.5 mbsf, respectively. Before setting up the incubations, the subcores were sampled with sterile syringes using the sample aseptic technique used for the DNA extraction. For each sample depth, 7 g of abyssal clay was placed into sterile 20-ml glass flasks and incubated with 4 ml of sterile artificial seawater composed of either H218O (97% atomic enrichment) or unlabeled artificial seawater. Vials were crimp-sealed, with an oxygenated headspace of approximately 10 ml, and incubated at 8°C. The water content of the clay was measured to be approximately 40% (±5%) of the total weight. This initial water content diluted the final concentration of added H218O to be ca. 60% of the total water content of the sample. The artificial seawater was different from the pore water at depth because there was no added nitrate, but there was also no added ammonia, which should be similar to the in situ conditions where ammonia is generally below detection (9). Oxygen was measured continuously throughout the incubations using noninvasive fiber-optic measurements as described previously (62). Small fluctuations in the oxygen measurements in the killed control, and experimental incubations (fig. S3), were likely due to temperature fluctuations of the incubator itself (±1°C), since the noninvasive fiber-optic oxygen sensor spots are temperature sensitive (62).

To assess the preservation potential of eDNA, and its ability to bias our study that is based on DNA from living organisms, we monitored microbial growth in the presence and absence of added eDNA over a 210-day incubation experiment. eDNA extracted from a culture of Rhodococcus erythropolis was added to sediment slurries from 2.8 mbsf at site 11 at a concentration of 5 ng/g. Microbial growth was measured over time with 16S rRNA gene qPCR and also in a control that did not receive the eDNA. As a second control, we added eDNA to autoclaved (dead) sediment. DNA was extracted from each time point and measured with qPCR using the methods described above.

Density gradient fractionation and qPCR

We used Tag-SIP (63, 64) to measure the atom % 18O enrichment of actively growing microbial taxa following the equations described previously for 18O-SIP data (21). Briefly, after 7 and 18 months of incubation, DNA was extracted and subjected to cesium chloride (CsCl) density gradient centrifugation as described previously (60). The same 16S 515F/806R primers (described above) were used in qPCR (described above) to determine density shifts in the peak DNA of buoyant density for each incubation. 16S rRNA gene amplicons from each fraction resulting from the density gradient fractionation were Illumina sequenced as described above. To identify contaminants that may have entered during the fractionation process, we also included in the sequencing run extraction blanks from the SIP fractionation. OTUs containing sequences from extraction blanks were removed.

Calculating 18O enrichment

Excess atom % 18O enrichment was calculated for each taxon according to the equations for quantifying per OTU atomic enrichment from Tag-SIP data provided by Coskun et al. (60). The atom fraction excess of 18O for each OTU (UNEOXYGENi) accounts for the background fractional abundance of 18O (0.002000429) using the following formula


or MLABI is the molecular weight of the 16S gene for taxon I in the labeled treatment, MLUMIÈREI is the molecular weight of the 16S gene for taxon I in the unlabeled treatment, and MHEAVYMAXI is the theoretical maximum molecular weight of a fully labeled 16S gene with 18O. The lowest detection limit in the density shifts were proposed as 0.0034 to 0.0042 g/ml (65), and we selected a conservative lowest limit of 0.005 g/ml for a significant shift. Therefore, throughout this study, we referred to OTUs meeting this criterion as those having incorporated the given substrate.

Metagenome library preparation, sequencing, and bioinformatics analysis

Before library preparation, whole-genome amplifications were performed on DNA extracts through a multiple displacement amplification step of 6 to 7 hours using the REPLI-g Midi Kit (QIAGEN) and following the manufacturer’s instructions. We monitored amplification using SYBR green I (Invitrogen) on a CFX Connect qPCR machine, stopping amplifications once the exponential phase was reached. Metagenomic libraries were prepared using the Nextera XT DNA Library Prep Kit (Illumina). Quality control and quantification of the libraries were obtained on an Agilent 2100 Bioanalyzer System using the High Sensitivity DNA reagents and DNA chips (Agilent Genomics). Metagenomic libraries were diluted to 1 nM using the Select-a-Size DNA Clean and Concentrator MagBead Kit (Zymo Research) and pooled for further sequencing on the Illumina MiniSeq platform. Contigs were assembled on CLC Genomics Workbench v. 9.5.4 (QIAGEN) using a word size of 20, a bubble size of 50, and a minimum contig length of 300 nucleotides. Reads were then mapped to the contigs using the following parameters (mismatch penalty = 3, insertion penalty = 3, deletion penalty = 3, minimum alignment length = 50% of read length, and minimum percent identity = 95%). We then performed even further stringency controls by removing any contig that had less than 5× coverage, e.g., reads per kilobase mapped (RPKM). The final resulting dataset of contigs was then used for ORF searches and BLAST analysis. Protein-encoding genes and ORFs were extracted using FragGeneScan v. 1.30 and functionally annotated against a large microbial genome database using a bioinformatics pipeline as described previously (66). Cutoff values for assigning hits to specific taxa were performed at a minimum bit score of 50, a minimum amino acid similarity of 60, and an alignment length of 50 residues.

For phylogenetic analyses, OTUs of AOAs were aligned with SINA online v.1.2.11 (67) and plotted in ARB (68) against the SILVA 16S rRNA SSU NR99 reference database release 132 (69). Closest environmental sequences with nearly full-length sequences (>1400 base pair) were selected as taxonomic references and used to calculate trees using the maximum likelihood algorithm RAxML implemented with the archaeal filter and advanced bootstrap refinement selecting the best tree among 100 replicates (70). Partial OTU sequences were added to the tree using the maximum parsimony algorithm without allowing changes of tree topology. Statistical analyses of beta-diversity were performed using R.Studio Version 3.3.0 (71) with the vegan package (72).

Acknowledgments: We thank N. Fierer and two anonymous reviewers for useful suggestions. Funding: This work was supported primarily by the Deutsche Forschungsgemeinschaft (DFG) project OR 417/1-1 granted to W.D.O. Preliminary work was supported by the Center for Dark Energy Biosphere Investigations project OCE-0939564 also granted to W.D.O. Publication of the manuscript was supported by the LMU Mentoring Program. The expedition was funded by the US National Science Foundation through grant NSF-OCE-1433150 to A.J.S, S.D., and R.P. R.W.M. led the expedition. This is a contribution of the Deep Carbon Observatory (DCO). S.D.W. acknowledges partial support from NASA Exobiology (NNX15AM04G). This is Center for Dark Energy Biosphere Investigations (C-DEBI) publication number 463. Portions of this material are based on work supported while R.W.M. was serving at the National Science Foundation. A portion of this work was performed as part of the LMU Masters Program “Geobiology and Paleobiology” (MGAP). Author contributions: W.D.O., S.D.W., A.J.S., R.W.M., D.C.S., and S.D. conceived the work and experimental approach. A.V., W.D.O., O.K.C., T.M., S.V., and E.R.E. contributed to the laboratory/bioinformatics analyses and experimental work. R.W.M., D.C.S., E.R.E., and R.P. obtained the samples during the KN223 R/V Knorr oceanographic expedition. W.D.O., S.D.W., R.W.M., D.C.S., E.R.E., A.V., S.V., and S.D. discussed and wrote the manuscript and commented on the paper. Competing interests: The authors declare that they have no competing interests. Data and materials availability: Data are publicly available through NCBI BioProject PRJNA473406. Metagenomes from sites 11 and 12 have Short Read Archive (SRA) BioSample accession numbers SAMN10924458 and SAMN10924459, respectively. The 16S data are available in SRA BioSample accessions SAMN10929403 to SAMN10929517. Additional data related to this paper may be requested from the authors.

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