Phylogenetic diversity in Guaymas Basin sediments

To examine the biodiversity of microbial communities inhabiting GB sediments, we sampled and sequenced eleven sediments covering different sampling locations, depths (0–24 cm), temperatures (3–60 °C) and geochemical regimes (Fig. 1, Supplementary Data 1, 2). Background sediments, represented by core 4567_28, are not influenced by hydrothermal activity (temperature ~3 °C) and occur interlaced with hydrothermal hot spots within the spreading center18. All other samples are characterized by steep thermal gradients, reflected by in-situ temperatures ranging from 4 °C to 60 °C. Dense mats of filamentous Gammaproteobacteria (family Beggiatoaceae) covered hydrothermal sediments from dive 4569, with an orange mat dominating core 4569_9 and a white mat at the adjacent core 4569_2. Core 4569_4 was collected from the periphery of this hydrothermal hotspot and did not contain visible mats (Fig. 1). Porewater methane, sulfate, dissolved inorganic carbon (DIC) and sulfide co-occurred throughout these cores (Supplementary Information), consistent with hydrothermal circulation and inmixing of seawater-derived electron acceptors. Cores 4571_4 and 4488_9 represent hot and oily sediments with yellow-white sulfur precipitates on the surface (Fig. 1). Among the hydrothermal cores, 4488_9 stands out by steep thermal gradients (~150 °C at 30 cm depth), high sample temperature (~60 °C), sulfate depletion at shallow depths, and accumulation of non-methane hydrocarbons (Supplementary Figure 1, Supplementary Data 1). After sequence assembly, we reconstructed 551 draft genomes via tetranucleotide and coverage binning. These metagenome-assembled genomes (MAGs), simplified as ‘genome’ throughout the manuscript, represent medium-quality MAGs and were > 50% complete and < 10% contaminated (301 genomes > 70% and 61 genomes > 90% complete; Supplementary Data 2, 3)28.

Fig. 1 Overview of sampling sites. In-situ photos of the three hydrothermal sampling sites (Vent1, Vent2, Vent3) and the non-hydrothermal background sediment, including Alvin dive and core number for the sediment cores that were used for DNA extraction and metagenomic analysis. White circle: spots where sediment cores were retrieved by push coring. For Vent1, three sediment cores were taken inside the yellow mat (4569_9), further outside in a white mat area (4569_2) and outside of the mat area (4569_4); next to each core a thermal logging probe was inserted into the sediment. At Vent2 and Vent3, one core each (4571_4 and 4488_9) was sampled. Metadata for all samples are summarized in Supplementary Data 1 Full size image

Each genome was classified by constructing a phylogenetic tree using 37 single-copy, protein-coding marker genes (Supplementary Data 4)29. Overall, the 551 genomes (247 archaea and 304 bacteria) represented 16 cultured and 40 uncultured, candidate phyla that comprise a substantial number of new microbial lineages, many of which branch basal to those previously described (Fig. 2, Supplementary Figure 2, Supplementary Data 5). GB genomes form 22 new lineages on the tree of life based on a phylogenetic distance analysis (collapsing branches at an average branch length distance < 0.6). Among those lineages, we discovered five new candidate phyla designated GB-AP1,2 and GB-BP1-3 for archaeal and bacterial phyla, respectively. The placement of these five phyla was confirmed by comparing the average amino acid identity (AAI) of genomes within a phylum to genomes of all other phyla (Supplementary Data 6). Within each new phylum, GB-AP1,2 shared an AAI of ~44 and ~96% and GB-BP1-3 of ~54, ~72 and ~60%, respectively, and were more similar to themselves then to other genomes (~43% AAI summarized across all genomes). While the genomes of GB-AP1 shared a low AAI, we did not detect any lineage with a closer similarity. Two 16S rRNA gene sequences recovered from GB-BP1 clustered with the uncultivated lineage MAT-CR-M4-B0730, which was previously detected in the Kazan mud volcano or Guerrero Negro hypersaline mats (Supplementary Figure 3). In total, we defined 24 archaeal and 37 bacterial groups (or ‘clusters’) for closer analysis (see Methods section, Supplementary Data 3 and Fig. 2). Archaeal genomes were represented by Bathyarchaeota (n = 41), Thermoproteales (n = 40) and Thermoplasmata (n = 36), and bacteria belonged to Deltaproteobacteria (n = 56), Gammaproteobacteria (n = 39) and Bacteroidetes (n = 27; Supplementary Data 3). Additionally, we detected several candidate lineages, including Asgard archaea (n = 9), Verstraetearchaeota (n = 7) and the bacterial CPR superphylum (n = 6). Overall, more genomes were recovered from hydrothermal (average of ~60 genomes per sample) than from background sediments (average ~9 genomes per sample; Supplementary Data 3). We detected only one archaeal (Bathyarchaeota) and 7 bacterial lineages (Chloroflexi, Deltaproteobacteria, Gammaproteobacteria) in the background compared to 22 archaeal and 31 bacterial clusters in the hydrothermal samples, suggesting a greater biodiversity in the more extreme environment.

Fig. 2 Maximum likelihood phylogenetic tree of GB genomes based on 37 concatenated protein-coding genes. Grey: Reference Genomes. Blue: Genomes assembled from cold background sediments. Red: Genomes recovered from hot, hydrothermal sediments. The full tree can be found in Supplementary Figure 2 and the tree file is available in Supplementary Data 5 Full size image

The effect of environmental parameters on community assembly

To better understand the factors that drive community assembly, we investigated the occurrence of major phylogenetic clusters across sites. First, we confirmed that the genomes accurately reflected the community as a whole based on the abundance of ribosomal protein S3 across sites (Supplementary Figure 4). Next, we used the genomes to estimate the occurrence of different phylogenetic groups across all samples (Supplementary Figure 5, Supplementary Data 7). Several bacterial lineages, such as Planctomycetes or Deltaproteobacteria, were more frequently detected in background sediments than in hydrothermal sediments. In contrast, archaea were increasingly detected within the deeper, hotter hydrothermal samples, but not in cool surface sediments on the periphery of hydrothermal hot spots. Dominant lineages in the hot samples were Thaumarchaeota and Archaeoglobales as well as Acetothermia, and Omnitrophica. Two genotypes dominated hot sediments: B48_G6 (Methanosarcinales, ANME-1) and B16_G6 (Thermodesulfobacteria, ~88% AAI to Ca. Desulfofervidus auxilii) (Supplementary Data 3, Supplementary Data 7). While the hydrothermal sediments had an overall similar distribution of taxa across depth profiles, the oily sediment from 4488_9 harbored only few abundant taxa, including Thermoplasmata, Aerophobetes and Thermotoga (Supplementary Figures 4, 5). Core 4488_9 differs from other hydrothermal samples in its high hydrocarbon content, quick downcore depletion of sulfate, and steep thermal gradients (Supplementary Data 1, Supplementary Methods). In combination these factors appear to reduce the microbial diversity, especially of the archaeal community. Altogether, the hydrothermal activity gives rise to a unique community that shows a marked enrichment in archaea that can represent up to 50% of recovered genomes (Supplementary Data 7). This enrichment appears to be largely driven by the rich substrate availability, by hydrothermal circulation and by inmixing of the electron acceptor sulfate (Supplementary Methods). However, a greater sampling size would be needed to disentangle the relative contribution of individual factors on community assembly such as temperature, methane or hydrocarbon availability.

Carbon cycling

Given that these genomes yielded such a large number of unique microbial lineages, we inferred their potential physiological capabilities by assigning metabolic functions to proteins in each individual genome. First, we investigated the ability of the community to degrade and metabolize complex carbohydrates and peptides deposited in sediments by searching genomes for the presence of carbohydrate-active enzymes (CAZYmes), peptidases and pathways for carbon metabolism. In total, we detected ~30,000 and ~11,000 potential CAZYmes and peptidases, respectively (Fig. 3, Supplementary Figure 6, Supplementary Data 8, 9). Generally, bacteria encoded for a broader repertoire of CAZYmes compared to archaea; for example GH13 (α-amylase), GH23 (lytic transglycosylase) or GH74 (xyloglucanase) were more common in bacteria (Fig. 3, Supplementary Data 8). Most CAZymes were assigned to Thermoproteales (n = 20) and Asgard archaea (n = 16) as well as Verrucomicrobia (n = 38) and Bacteroidetes (n = 30). Peptidases were more equally distributed across both domains and abundant in Asgard archaea (n = 34) and Thermococci (n = 24) as well as Aminicenantes (n = 54) and Acidobacteria (n = 51; Supplementary Figure 6, Supplementary Data 9). Approximately 2–3% of CAZYmes and peptidases are potentially secreted, suggesting that complex substrates are degraded outside of the cell and later taken up for degradation. Potentially secreted enzymes include CE8 (pectin methylesterase), and GH13 (α-amylase) as well as M28 (aminopeptidases) and S08 (subtilisin-like peptidases). A subset of CAZymes, such as GH23, may be involved in cell wall maintenance; however, the presence of sugar and peptide transporters as well as downstream metabolic pathways in most genomes suggest that other CAZymes might be involved in energy metabolism (see below).

Fig. 3 Number of carbohydrate-active enzymes (CAZymes) encoded in GB genomes. Percentage of carbohydrate esterases (CE), glycoside hydrolases (GH) and polysaccharide lyases (PL) encoded in GB genomes summarized for each phylogenetic cluster. Brackets: Total number of genomes encoded in each phylogenetic cluster. Asterisk: CAZyme with potential secretion signal (see also Supplementary Data 8) Full size image

Common pathways for the degradation of substrates produced by the activity of CAZymes and peptidases include glycolysis (glucokinase (glk), phosphofructokinase (pfk), pyruvate kinase (pyk)), gluconeogenesis (fructose-1,6-bisphosphatase (fbp), phosphoenolpyruvate carboxykinase (pckA)) and fermentation (Fig. 4 and Supplementary Data 10). In several cases, archaeal genomes encoded for more key genes of gluconeogenesis compared to glycolysis, which could imply that some archaea prefer peptides as an energy source; this finding is consistent with the occurrence of a high number of peptidases in their genomes (Supplementary Figure 6). Compared to archaea, bacteria contained a greater metabolic repertoire and might use both glycolysis and gluconeogenesis. Most genomes encoded for the potential to metabolize pyruvate produced during glycolysis to acetyl-CoA and further into fermentation pathways, producing formate, ethanol or acetate (Fig. 4). GB archaea were mainly capable of acetate formation using the ADP-forming acetyl-CoA synthetase (acdA), while bacteria encoded for phosphate acetyltransferase (pta) and acetate kinase (ackA) for acetate production; formate C-acetyltransferase (pflD) and formate dehydrogenase (fdoG) for formate production; and aldehyde dehydrogenase (aldh) and alcohol dehydrogenase (adh) for ethanol production.

Fig. 4 Core metabolic genes detected across phylogenetic clusters inhabiting GB sediments. Presence of core metabolic genes involved in carbon metabolism, hydrocarbon (HC) degradation and respiration. Shaded colors: Gene present in 30–50% of genomes/phylogenetic cluster. Solid colors: Gene present in 50–100% of genomes/cluster. C1 C1- compound metabolism, H2 hydrogen metabolism, N nitrogen metabolism, S sulfur metabolism, O 2 oxygen metabolism, ArsRed arsenate reductase, SeRed selenate reductase, Gly glycolysis, Glu gluconeogenesis, Prop propane. Number in brackets: number of genomes belonging to individual phylogenetic clusters. Grey circle: Bootstrap support > 70%. Asterisk: Deltaproteobacteria includes genomes from both Deltaproteobacteria and Thermodesulfobacteria. 1pflD and assA are often difficult to discriminate from other glycyl radical enzymes, therefore, an additional phylogenetic analysis can be found in Supplementary Figure 8. 2Phylogenetical analyses of substrate specificity of acd genes can be found in Supplementary Figure 7. A complete list of metabolic genes can be found in Supplementary Data 10 Full size image

Not only is the GB microbiome able to process the deposited organic carbon pool by fermentation, but we also detected pathways for carbon fixation. The most common route of carbon fixation was the Wood-Ljungdahl pathway in both archaea and bacteria, while the Calvin-Benson-Bassham (CBB) and rTCA cycles were restricted mostly to Proteobacteria (Fig. 4, Supplementary Data 10). Although the Group III Ribulose-1,5-bisphosphate carboxylase-oxygenase (Rubisco, key marker gene of the CBB cycle) was detected in most archaea, this subgroup is implied in a nucleotide salvage pathway and not necessarily used for carbon fixation (Supplementary Data 10)31. A Group I/II Rubisco, feeding CO 2 into the CBB cycle, was only detected in some Gammaproteobacteria (orders Chromatiales and Thiotrichales). Additionally, marker genes for the rTCA cycle, including ATP-citrate-lyase (aclAB), pyruvate ferredoxin oxidoreductase (porABCD) and 2-oxoacid ferredoxin oxidoreductase (oorABCD), were mainly detected in Epsilonproteobacteria (order Campylobacterales; Supplementary Data 10). While several genes of the 3-hydroxypropionate or related cycles were present in a subset of genomes, a full pathway appeared to be absent (Supplementary Data 10). Conversely, the Wood-Ljungdahl pathway was present in several clusters, including Archaeoglobales and Methanosarcinales as well as Chloroflexi and Deltaproteobacteria (Fig. 4, Supplementary Data 10). Interestingly, we also detected genes from this pathway in candidate phyla, including Hydrothermarchaeota and Latescibacteria, which might either oxidize acetate or perform acetogenesis.

Alkyl-coenzyme M reductase linked hydrocarbon cycling

We detected the methyl-Coenzyme M reductase (mcrA), a key enzyme for methanogenesis and AOM, in Syntrophoarchaea, Methanomicrobia, and a deep-branching Thermoproteales lineage (designated DeepCrenGroup1; Fig. 4, Supplementary Data 3). To our knowledge this is the first report of mcrABG genes in the Crenarchaeota. The only bacteria able to utilize methane encoded for the particulate methane monooxygenase (pmoA), which was restricted to Gammaproteobacteria (orders Cellvibrionales and Methylococcales; Supplementary Data 10). A closer phylogenetic analysis of McrA might even suggest a broader substrate usage potentially not restricted to methane (Fig. 5, Supplementary Data 11). McrA from most ANME-1, ANME-2c and DeepCrenGroup1 clustered with known methane oxidizers, while the McrA from one Syntrophoarchaeum (B49_G1) clustered with butane-oxidizers (Fig. 5). McrA from GoM-Arc1 branched between those two clusters, which is consistent with earlier work that suggested that GoM-Arc1 might utilize a different alkane, perhaps ethane, which can reach relatively high concentrations of 40-100 µM in GB11,20. However, further experimental evidence, preferably from enrichment cultures, is needed to confirm the substrate usage of these McrA proteins.

Fig. 5 Maximum likelihood phylogenetic tree of the methyl-Coenzyme M reductase (McrA) protein detected in GB genomes. Bold labels: McrA detected in GB genomes (see also Supplementary Data 10). Black circle: Bootstrap support ≥ 70 (number of bootstraps determined using the extended majority-rule consensus tree criterion). RaxML was run as raxmlHPC-PTHREADS-AVX -f a -m PROTGAMMAAUTO -N autoMRE. The tree file is available in Supplementary Data 11 Full size image

Surprisingly, ANME-1 bin B39_G2 contains two McrA proteins (on two different contigs, both mate-paired to other contigs from that bin) that are phylogenetically related to those from Ca. Syntrophoarchaeum spp. (Fig. 5). Similarly to Ca. Syntrophoarchaeum spp. B39_G2 contains genes with homology to those that encode for the butyryl-CoA oxidation pathway, such as acyl-CoA dehydrogenase and enoyl-CoA dehydratase (Supplementary Data 10, Supplementary Figure 7). This pathway appears to be involved in butane oxidation in Ca. Syntrophoarchaeum butanivorans16, making this the first example of an ANME-1 archaeon potentially able to use short-chain alkanes. The detection of these unique methyl coenzyme-M reductase genes and pathways suggests that ANME-1 archaea are not limited to methane utilization and potentially able to oxidize alkanes anaerobically.

Lipid and hydrocarbon utilization

Pathways for lipid degradation were widespread in bacteria and less common in archaea, where they were mainly detected in Archaeoglobales, Bathyarchaeota and Geothermarchaeota (Fig. 4, Supplementary Data 10). The acyl-CoA dehydrogenase (acd) represents a key gene catalyzing the first step in beta-oxidation and accommodates a broad substrate range32,33. GB ACDs fell alongside described glutaryl-CoA dehydrogenases, small/medium- and long-chain acyl-CoA dehydrogenases, potential butyryl-CoA dehydrogenases and isovaleryl-CoA dehydrogenases (Supplementary Figure 7, Supplementary Data 12). Only ~50% of archaeal lineages encoded for acd, which was found scattered across taxa, for example only ~30% of Verstraetearchaeota encoded for acd. This gene was common in Archaeoglobales, Asgard archaea and Geothermarchaeota, all of which encoded for other beta-oxidation genes, such as enoyl-CoA hydratase (EC 4.2.1.17) or 3-hydroxyacyl-CoA dehydrogenase (EC 1.1.1.35; Fig. 4, Supplementary Data 10). In contrast, 33 out of 37 bacterial lineages encoded for acd. However, only a subset of those lineages - including Aquificae, Chloroflexi or Deltaproteobacteria - encoded for further beta-oxidation genes. In these cases, enzymes, such as the glutaryl-CoA dehydrogenase, might be involved in amino acid catabolism or in benzoyl-CoA degradation32,34.

Hydrocarbons are another abundant source for energy and biomass generation in GB. While we did not detect genes for aerobic hydrocarbon degradation, we found indications that GB genomes might anaerobically degrade hydrocarbons using glycyl radical enzymes (GREs, Supplementary Figure 8, Supplementary Data 13). GREs use a radical-based chemistry to carry out challenging metabolic reactions under anaerobic conditions and are involved in a multitude of pathways, such as fermentation, DNA synthesis or hydrocarbon degradation35,36. Compared to ACDs, GREs had a sparser distribution and were found in only 6 out of 24 archaeal and 21 out of 37 bacterial lineages. GREs were common in Deltaproteobacteria (n = 32), Bacteroidetes (n = 23) or Asgard archaea (n = 15). Several GREs encoded for enzymes involved in anaerobic hydrocarbon degradation, such as benzylsuccinate synthase (bssA) in Deltaproteobacteria (B38_G6, B7_G9), alkylsuccinate synthase (assA) in Deltaproteobacteria (B2_G1, B111_G9) or hydroxyphenylacetate decarboxylase in Bathyarchaeota (B26_G17) and Chloroflexi (B43_G15). Some GREs grouped neither with the previously mentioned enzymes nor with the pyruvate formate lyase or other characterized GREs35, suggesting that those might utilize different substrates, such as carbohydrates or peptides.

Respiratory processes

Next, we investigated the GB microbial communities for their involvement in respiratory processes. Overall, more bacterial and archaeal genomes contained genes that encode anaerobic rather than aerobic respiratory pathways, consistent with rapidly depleted oxygen levels within the first few millimeters of the sediment (Fig. 4, Supplementary Data 10)18. Cytochrome c oxidases occurred in ~10% of genomes, but were mainly limited to Bacteroidetes, Epsilon-/and Gammaproteobacteria, and Verrucomicrobia. Conversely, genes for hydrogen, nitrogen, sulfur and potentially arsenate and selenate cycling were more widespread. We detected [FeFe]-hydrogenases in ~10% of genomes and these mostly belonged to Group A, which can be involved in fermentative hydrogen evolution37. Approximately 70% of genomes encoded for [NiFe]-hydrogenases belonging to Group 1 (a–e and h; membrane-bound hydrogen-uptake hydrogenases involved in hydrogenotrophic respiration), Group 3 (a–d; cytosolic bidirectional hydrogenases) and Group 4 (b,d,e and g; membrane-bound, hydrogen-evolving hydrogenases; Supplementary Data 10)37. The most common [NiFe]-hydrogenase was found in ~25% of genomes, and belongs to Group 3b that is involved in NADPH oxidation coupled to hydrogen evolution.

Genes involved in the nitrogen and sulfur cycle were mostly restricted to bacteria, whereas archaeal nitrogen cycling genes were limited to nifH in Methanomicrobia (Fig. 4, Supplementary Data 10). Genes for dissimilatory nitrate reduction to ammonium (DNRA) (narGH/napAB and nirBD/nrfAH) were present in few Bacteroidetes (i.e. B27_G6, B58_G6), Epsilonproteobacteria (B6_G4, B37_G6) and several Gammaproteobacteria (Methylococcaceae, Thiotrichales). More commonly, we detected DNRA genes distributed separately over several genomes. A complete denitrification pathway (napA/narGH, nirK/nirS, norBC, nosZ) was present in a few genomes, including one Bacteroidetes (B2_G4), some Epsilonproteobacteria (i.e. B135_G9) and several Gammaproteobacteria genomes (Halieaceae, Thiotrichales); individual denitrification genes were found scattered across different taxonomic lineages. Genes involved in anaerobic ammonium oxidation (anammox) were not found, consistent with low nitrate and nitrite concentrations in GB sediments38. Genes for the dissimilatory reduction of sulfate to sulfide (sat, aprAB and dsrAB) were found in few archaea (i.e. Archaeoglobales) and several bacteria including Deltaproteobacteria, Gammaproteobacteria and Zixibacteria. The sulfur-oxidation (SOX) system (soxAX, soxYZ, soxB, soxCD) showed a restricted phylogenetic distribution and was only located in Epsilonproteobacteria and Gammaproteobacteria. While on average ~10% of all genomes contained genes for sulfur and nitrogen cycling, complete pathways for these processes were present in only few genomes.

Redundancy and interconnectivity among GB microbes

To assess whether hydrothermal sediments not only host a greater phylogenetic but also metabolic diversity than background samples (Fig. 2), we next investigated the spatial distribution of core metabolic genes across all sites and taxa. Regardless of their origin, most genomes encoded genes for general carbon cycling (CAZymes, peptidases, gluconeogenesis, glycolysis), fermentation and lipid oxidation (Fig. 6 and Supplementary Data 10). Respiratory genes were restricted to cooler, shallower samples but present in both background and hydrothermal sediment cores. For example, denitrification genes, SOX genes or the cytochrome c oxidase were found only in the shallower, colder sediments (temperature ~5 °C) and were present in ~20-30% of genomes. In contrast, these genes were represented in only ~0-4% of genomes in deeper, hotter samples (temperature range of 10 °C-60 °C). Exceptions were genes for sulfate/sulfite reduction, such as dsrAB, that were still found in ~8% of genomes in deeper, hotter sediments. Compared to background samples, genes involved in C1-metabolism and hydrogenases were more frequently found in hydrothermal sediments. In background sediments only one Bathyarchaeotal genome contained carbon fixation-related genes (cdhAB), while genes for methane cycling (mcrA) were undetectable. Hydrogenases belonging to Group 4 g, which represent membrane-bound hydrogenases that generate a proton-motive force for energy generation, were absent from the background but present in ~25-30% of genomes across all hydrothermal samples (Fig. 6 and Supplementary Data 10). These findings suggest that methane and hydrogen might be important drivers of metabolic processes in GB hydrothermal sediments.

Fig. 6 Metabolic profile across different GB sediment sites, depth profiles and temperature regimes. Shown is the number of core metabolic genes relative to the total number of genomes (in %) per site, depth and temperature regime. Temperatures are averages for the 2 or 3 cm thick sediment layers from which DNA was isolated. Background samples: Cold GB samples without hydrothermal activity. Vent1–3: Hydrothermal sediment sampling locations, see also Fig. 1. ID at the bottom: number codes designating every Alvin dive and sediment core (see also Supplementary Data 1 for further explanation). A complete list of metabolic genes can be found in Supplementary Data 10. Number in circles: Number of phylogenetic clusters that encode for individual core metabolic genes at each site Full size image

With few exceptions most metabolic genes were encoded in several taxonomically distinct lineages. For example, C1-related genes (with the exception of mcrA) and genes related to beta-oxidation, hydrogen, nitrogen, sulfur and oxygen cycling were found in ~10 different phylogenetic lineages; fermentation genes were present in most phylogenetic clusters of both the archaeal and bacterial community. While the studied genomic dataset from the cold and hydrothermal samples were not represented by an equal number of genomes (average of ~9 and ~60 genomes per habitat type, respectively), we still find that those genomes represent the community well in terms of phylogenetic diversity (Supplementary Figure 4). Additionally, when searching for a subset of these core metabolic genes in binned and unbinned contigs from the complete assembly (only considering contigs > 2,000 bp), we observed a similar trend (Supplementary Data 14). For example, fermentation genes were abundant across all sites, denitrification genes were more common in cold and shallow samples and mcrA was completely absent from the background samples. Overall, these findings suggest that the GB genomes are representative of the community as a whole, and that they reflect key metabolic differences between the microbial communities present in hydrothermal and background samples.