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Microbial metabolisms in an abyssal ferromanganese crust from the Takuyo-Daigo Seamount as revealed by metagenomics

  • Shingo Kato ,

    Roles Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Visualization, Writing – original draft, Writing – review & editing

    Affiliations Submarine Resources Research Center, Japan Agency for Marine-Earth Science and Technology (JAMSTEC), Yokosuka, Kanagawa, Japan, Japan Collection of Microorganisms (JCM), RIKEN BioResource Research Center, Tsukuba, Ibaraki, Japan

  • Miho Hirai,

    Roles Data curation, Formal analysis, Methodology, Writing – review & editing

    Affiliation Research and Development Center for Marine Biosciences, JAMSTEC, Yokosuka, Kanagawa, Japan

  • Moriya Ohkuma,

    Roles Conceptualization, Methodology, Writing – review & editing

    Affiliation Japan Collection of Microorganisms (JCM), RIKEN BioResource Research Center, Tsukuba, Ibaraki, Japan

  • Katsuhiko Suzuki

    Roles Conceptualization, Funding acquisition, Investigation, Project administration, Writing – original draft, Writing – review & editing

    Affiliation Submarine Resources Research Center, Japan Agency for Marine-Earth Science and Technology (JAMSTEC), Yokosuka, Kanagawa, Japan


Rocky outcrops covered with thick Fe and Mn oxide coatings, which are known as ferromanganese (Fe-Mn) crusts, are commonly found on slopes of aged seamounts in bathyal and abyssal zones. Although the presence of diverse microorganisms on these Fe-Mn crusts has been reported, little is known about their metabolism. Here, we report the metabolic potential of the microbial community in an abyssal crust collected in the Takuyo-Daigo Seamount, in the north-western Pacific. We performed shotgun metagenomic sequencing of the Fe-Mn crust, and detected putative genes involved in dissolution and precipitation of Fe and Mn, nitrification, sulfur oxidation, carbon fixation, and decomposition of organics in the metagenome. In addition, four metagenome-assembled genomes (MAGs) of abundant members in the microbial community were recovered from the metagenome. The MAGs were affiliated with Thaumarchaeota, Alphaproteobacteria, and Gammaproteobacteria, and were distantly related to previously reported genomes/MAGs of cultured and uncultured species. Putative genes involved in the above reactions were also found in the crust MAGs. Our results suggest that crust microbial communities play a role in biogeochemical cycling of C, N, S, Fe, and Mn, and imply that they contribute to the growth of Fe-Mn crusts.


Ferromanganese (Fe-Mn) oxide coatings, such as Fe-Mn crusts and nodules, have been found in the pelagic deep ocean. Fe-Mn crusts generally cover rocky outcrops on slopes of aged and volcanically-inactive seamounts in bathyal and abyssal zones [13]. In some cases, the thickness of the crust is over 10 cm, which corresponds to a passage time of over ten million years (Myr) based on their extremely slow growth rate (1–10 mm/Myr) [14]. Fe-Mn oxides adsorb dissolved metallic ions from seawater [5, 6], and therefore, they are referred to as the “chemical scavengers of the sea” [7]. In fact, the deep-sea Fe-Mn coatings show ten times or higher concentrations of various elements such as cobalt (Co), molybdenum (Mo), tungsten (W), nickel (Ni), copper (Co), and zinc (Zn), in addition to Fe and Mn, than those in the seawater and even in Earth’s crustal rocks [8]. Many of these elements are essential for the growth of microbial life.

Despite the limitation of organic input from the ocean surface, the pelagic deep-sea Fe-Mn coatings harbor diverse and abundant microorganisms [913]. Indeed, the number of microbial cells on the surface is estimated to be 106–108 cells/g by microscopic direct counting or quantitative PCR [9, 11, 13, 14]. Considering that there are microorganisms contributing to the growth and dissolution of iron- and manganese-minerals [1517], the microbial activities thriving in the Fe-Mn coatings are potentially involved in elemental cycling between the coatings and seawater. Previous 16S rRNA gene analyses have indicated that the microbial community structures of the Fe-Mn coatings are distinguishable from those of the surrounding seawater and sediments [1014, 18], suggesting that a unique ecosystem develops in the Fe-Mn coatings. As-yet-uncultured lineages affiliated with Gammaproteobacteria, Alphaproteobacteria, and Thaumarchaeota are dominant in the microbial communities of the Fe-Mn coatings [914, 1820]. In particular, 16S rRNA genes related to Marine Group I (MGI) [21] of the Thaumarchaeota, which include ammonia-oxidizing autotrophs such as Nitrosopumilus spp. [22], have been detected as a major lineage in the Fe-Mn coatings. The amoA genes related to the MGI ammonia oxidizers have been also detected [11]. This gene encodes a subunit of ammonia monooxygenase, a key enzyme for ammonia oxidation. Thus, ammonia likely serves as one of the main energy sources to sustain the microbial ecosystem in the Fe-Mn coatings. However, the metabolic functions of the as-yet-uncultured microorganisms present in the deep-sea Fe-Mn coatings are still largely unknown due to a lack of cultured representatives and even whole-genome sequences. Therefore, it remains unclear whether and how these microorganisms contribute to biogeochemical cycling between the Fe-Mn coatings and seawater, and to the formation of Fe-Mn coatings.

Here we report the metabolic potential of microorganisms in an abyssal Fe-Mn crust, as revealed by metagenomics. The Fe-Mn crust was collected at a water depth of 5520 m in the Takuyo-Daigo Seamount [13], where the availability of organic matter derived from the ocean surface is limited. This seamount is in the north-western Pacific on one of the oldest oceanic plates (> 150 Myr old [23, 24]). Fe-Mn crusts have been found covering the slope of most of the seamount, from the top at a water depth of 800 m to the bottom at a water depth of up to 6000 m [2]. Previous 16S rRNA gene analyses have indicated that diverse and abundant microorganisms are present throughout the water depth [11, 13, 14]. In the present study, we found putative genes involved in biogeochemical cycling of carbon (C), nitrogen (N), Fe, and Mn in the metagenome. Furthermore, we reconstructed metagenome-assembled genomes (MAGs) of as-yet-uncultured lineages of Gammaproteobacteria, Alphaproteobacteria, and Thaumarchaeota, which were detected as dominant members in the metagenome of the Fe-Mn coating. Although metagenomics of deep seawater [2528], oligotrophic deep-sea surface sediments [29, 30], and seafloor basalts without Fe-Mn coatings [31] have been reported, so far there are no reports of metagenomics of deep-sea Fe-Mn coatings. Our results provide novel insights into the microbial contribution to the geochemical cycling and formation of the deep-sea Fe-Mn coatings.

Materials and methods

Field sampling

The sampling location and procedures have been previously described [13]. In brief, the Fe-Mn crust (the sample name, 680R2) was collected at a water depth of 5520 m at the Takuyo-Daigo Seamount during the KR16-E01 cruise (January 2016) with the research vessel (R/V) Kairei (JAMSTEC, Yokosuka, Kanagawa, Japan) and the remotely operated vehicle (ROV) Kaiko Mk-IV (JAMSTEC). Using the manipulators of the ROV on the seafloor, we transferred the crust sample into a sealable aluminum box to avoid contamination from surface seawater or sediments stirred up during the operation. On board, we subsampled the surface pieces of the Fe-Mn crust using sterile hammers and chisels. These pieces were stored at −80°C until DNA extraction.


DNA was extracted from the surface pieces (0.5 g; subsample ID, MnT55a) of the Fe-Mn crust using a FastDNA SPIN kit for soil (MP Biomedicals, Santa Ana, CA, USA) with a FastPrep instrument (MP Biomedicals) as previously described [13]. An aliquot of the extracted DNA has been previously used for 16S rRNA gene analysis [13]. Another aliquot was used for shotgun metagenomic sequencing in the present study. Library construction using a KAPA Hyper Prep Kit (KAPA Biosystems, Wilmington, MA, USA) and sequencing on an Illumina MiSeq platform (300 bp pair-end) were performed as previously described [32]. Sequence analysis was conducted as previously reported [33] with several modifications. For trimming and filtering of the reads, we used CLC Genomics Workbench version 9.5.3 (QIAGEN Aarhus A/S) with the default settings. The treated reads were assembled using SPAdes version 3.9.0 [34] with the following parameters: -k 55, 77, 99. Protein-coding DNA sequences (CDSs) in contigs (400 bp or longer) were predicted using Prodigal version 2.6.3 [35]. The treated reads were mapped to the contigs using BBmap version 36.49 ( to calculate read coverage. Functional characterization of the CDSs was performed using the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway tool [36] with GhostKOALA [37]. Homology searching of targeted CDSs against a non-redundant (nr) database in NCBI was performed using BLASTp version 2.5.0+ [38] with the default parameters. Using the search results of the top 100 hits, CDSs were taxonomically classified using MEGAN community edition version 6.6.7 [39] with default settings using the lowest common ancestor (LCA) algorithm [40]. We used phyloFlash version 3.0 [41] to determine the abundance of 16S rRNA genes in the metagenome and their taxonomy against the SILVA database release 128. The prediction of metabolic pathways was performed using the KEGG pathway tool with BlastKOALA [37]. CDSs for glycoside hydrolase (GH) families with the CAZy classification [42] were determined using dbCAN2 [43] and HMMER version 3.1 [44] with the thresholds of E-value <1e–15 and coverage >0.35.

The contigs and mapping data were used for binning using Metabat version 0.32.4 with the default parameters [45]. The binned contigs were visualized for GC content vs. coverage using gbtools version 2.4.5 [46] and manually curated. The reads mapped to contigs of each curated bin were then re-assembled using SPAdes with the following parameter (-k 99, 127) to improve assembly. The reassembled contigs were binned using Metabat and curated using gbtools, which resulted in four metagenome-assembled genomes (MAGs). The sequences of the MAGs were annotated using Prokka version 1.11 [47]. Enveomics version 1.0 was used to calculate amino acid identities (AAIs) using the default parameters [48]. Completeness and contamination levels for the MAGs were calculated by counting conserved single-copy marker genes using CheckM version 1.0.7 [49].

Phylogenetic analysis

Amino acid sequences were aligned using MUSCLE version 3.8.31 with the default parameters [50]. The alignment was trimmed using trimAl version 1.2rev59 with the option ‘-automated1’ [51]. Maximum likelihood trees were constructed using RAxML version 8.2.9 [52] with the GTRGAMMA model for nucleotide sequences and with the PROTGAMMALG model for amino acid sequences.

Accession numbers

The raw sequence data obtained in this study have been deposited into the DNA Data Bank of Japan (DDBJ) under the accession number DRA006451 for shotgun metagenomic sequences. The sequence and annotation data of the MAGs have been deposited under the accession numbers BFAR01000001–BFAR01000180, BFAS01000001–BFAS01000378, BFAT01000001–BFAT01000343, BFAU01000001–BFAU01000244, for MnTg01 to MnTg04, respectively. Nucleotide sequences of all contigs assembled from the metagenome, amino acid and nucleotide sequences of CDSs in the contigs, and the alignment dataset used for the phylogenetic tree construction are available in FigShare (


To address the metabolic potential of microorganisms in the Fe-Mn crust, we performed shotgun metagenomic sequencing. This produced 8.4 million high-quality trimmed reads (total 2.18 Gb) with an average of 260 bases. The sequence assembly contained 754,038 contigs comprising 400 bases or longer, 63,795 contigs comprising 1 kb or longer, and 668 contigs comprising 10 kb or longer. A total of 1,008,143 protein-coding DNA sequences (CDSs) was obtained from all contigs.

Membership of the crust community metagenome

To assess the relative abundance of each microorganism in the metagenome, read coverages for contigs containing a CDS of the ribosomal protein S3 gene (rpsC), a single-copy marker gene that was used for such analysis (e.g., [53]), were analyzed. A rank abundant plot of the top 20 contigs showing higher read coverages is shown in Fig 1A. The phylogeny of the RpsC (S1 Fig) from the top 20 taxonomic groups was generally consistent with the taxonomic affiliation determined by LCA analysis. The top 20 results indicated that members of the Thaumarchaeota, Gammaproteobacteria, and Alphaproteobacteria were abundant in the metagenome. Particularly, the RpsC CDSs of Thaumarchaeota were classified into the clade of ammonia-oxidizing archaea (AOA), including Nitrosomarinus spp., Nitrosopelagicus spp., and Nitrosopumilus spp. (S1 Fig). Members of Actinobacteria, Bacteroidetes, and the candidate phylum KSB1 were also present in the top 20. The top 20 read counts of 16S rRNA genes in the metagenome and those in the previous 16S rRNA gene amplicon analysis [13] contained members of the above taxonomic groups, in addition to members of Deltaproteobacteria, Nitrospirae, Nitrospinae, and Calditrichaeota (Fig 1B and 1C). Discrepancies in the order of members observed among the results (metagenomics vs. PCR amplicon analysis, and rpsC vs. 16S rRNA genes) (Fig 1) were probably due to differences in the copy number of each gene and/or the efficiency of the PCR amplification.

Fig 1. Rank abundant plot for phylogenetic marker genes.

(A) Read coverage of contigs containing CDSs for RpsC, (B) read counts of 16S rRNA gene operational taxonomic units (OTUs) in the metagenome, and (C) read counts of 16S rRNA gene OTUs in the PCR amplicon obtained in the previous study [13]. Taxonomic affiliations for the CDSs for RpsC and 16S rRNA genes are indicated on the bars. The IDs of metagenome-assembled genomes (MAGs) are shown for the contigs containing CDSs identical to those of the MAGs. Red and black bars indicate archaeal and bacterial CDSs, respectively.

Metabolic potential of the crust community

Nitrification is an important metabolic process for energy acquisition in oligotrophic deep-sea environments, including the surface of Fe-Mn crusts, as suggested previously based on 16S rRNA and amoA gene analysis [11, 13, 14]. To assess the nitrification potential of the crust community, we analyzed CDSs for ammonia monooxygenase (Amo) [Enzyme Commission (EC) numbers;], cyanase (Cyn) [EC], urease (Ure) [EC], and nitrite oxidoreductase (Nxr) [EC] (Fig 2A), which are involved in NH3 oxidation to NO2-, cyanate and urea degradation to NH3 and CO2, and NO2- oxidation to NO3-, respectively. Over ten thaumarchaeotic CDSs for UreB with the other subunits UreA and/or UreC were recovered from the metagenome, in addition to those affiliated with Gammaproteobacteria and Alphaproteobacteria. Only two alphaproteobacterial and gammaproteobacterial CDSs for Cyn were recovered. Seven thaumarchaeotic CDSs for AmoA with the other subunits AmoB and/or AmoC, and those affiliated with Nitrosomonadales, which include ammonia-oxidizing bacteria (AOB) such as Nitrosomonas spp. and Nitrosospira spp., were recovered. No CDSs for Amo related to Nitrospira were detected, which contain complete ammonia oxidizers (comammox), as recently reported [54, 55]. Because it was difficult to distinguish between Nxr and nitrate reductase (Nar) based only on homology searching, we constructed a phylogenetic tree for NarH/NxrB (S2 Fig), for which the subunit of Nar/Nxr has been used for functional and phylogenetic analysis [56]. Several Nar/Nxr CDSs in the metagenome were likely Nxr and were closely related to those encoded in the genomes of nitrite-oxidizing bacteria (NOB), such as Nitrospira spp. and Nitrospina spp. These AOA, AOB, and NOB are known to be autotrophs that fix inorganic carbon via the 3-hydroxypropionate/4-hydroxybutyrate (3HP/4HB) cycle, Calvin-Benson-Bassham (CBB) cycle, and reductive tricarboxylic acid cycle [57]. Indeed, CDSs for subunits of the key enzymes in these carbon fixation pathways, i.e., acetyl-CoA/propionyl-CoA carboxylase (Acc), ATP-citrate lyase (Acl), and ribulose-bisphosphate carboxylase (Rbc, or RubisCO), were recovered (Fig 2B). The bacterial CDSs for Acc were likely involved in fatty acid synthesis/degradation, rather than in carbon fixation.

Fig 2. Read-coverage-based rank abundant plot of contigs containing CDSs potentially involved in carbon and nitrogen cycling.

(A) CDSs for UreB, Cyn, AmoA, and NxrB/NarH involved in nitrification. (B) CDSs for AccC, AclA, and RbcL for key enzymes in carbon fixation pathways. (C) CDSs for cellulase and chitinase. (D) CDSs for extracellular peptidases. Peptidase family names for S, T, and M are indicated in parentheses. Taxonomic affiliations for the CDSs are indicated on the bars. The IDs of metagenome-assembled genomes (MAGs) are shown for the contigs containing CDSs identical to those of the MAGs.

Another potential energy source for the crust community is particulate organic carbon (POC) sinking from the ocean surface. We detected CDSs for cellulase [EC] and chitinase [EC] in the metagenome (Fig 2C), which were affiliated with some taxa, such as Bacteroidetes, Gammaproteobacteria, and Alphaproteobacteria. In addition, many CDSs for GH families were detected (S3 Fig). Especially, GH3 including glucosidase [EC], GH15 including glucoamylase [EC], GH23 including lysozyme type G [EC], GH103 including peptidoglycan lytic transglycosylase [EC 3.2.1.-], and GH130 including mannosylglucose phosphorylase [EC] accounted for over 50 CDSs of each GH family. We also detected CDSs for putative extracellular serine peptidase (peptidase families S1, S8, S26, and S41), metallopeptidase (M23 and M28), and threonine peptidase (T3) in the metagenome (Fig 2D), which were affiliated with some taxa, such as Thaumarchaeota, Actinobacteria, Chloroflexi, and Bacteroidetes. The above enzymes might be used to decompose polysaccharides and protein debris of POC.

Simple organic carbon compounds such as pyruvate, acetaldehyde, and formaldehyde, which can be produced by abiotic decomposition of POC by Mn oxides [58], can be also used by crust microorganisms. Indeed, CDSs for formaldehyde dehydrogenase catalyzing formate production from formaldehyde [EC] were detected in several contigs, although the coverages were relatively low (1×) (S4 Fig), in addition to CDSs for the utilization of pyruvate (such as pyruvate formate-lyase [EC], 2-oxoacid oxidoreductase [EC]), acetaldehyde (such as aldehyde dehydrogenase (ALDH) [EC] and aldehyde reductase [EC]). The above CDSs might be involved in organic carbon decomposition to generate ATP and reduce electron carriers such as NADH and quinol, and not only in assimilation of organic carbon. Furthermore, we found CDSs for lactate dehydrogenase (LDH) [EC] affiliated with Planctomycetes and Thaumarchaeota (S4 Fig). These CDSs for LDH and ALDH could be involved in lactate- and acetate-producing fermentation (resulting in a pH decrease) and/or lactate and acetate degradation.

Reduced sulfur species (such as hydrogen sulfide and thiosulfate) are another potential energy source for chemolithotrophs in the Fe-Mn crust. The reduced sulfur species can be supplied by microbial decomposition of sinking organic particulates containing sulfur. In the metagenome, we found CDSs for dissimilatory sulfite reductase (Dsr) [EC:] and adenylyl-sulfate reductase (Apr) [EC:], which are involved in sulfur oxidation or sulfate reduction (Fig 3A and 3B). Phylogenetic analyses showed that the detected CDSs for DsrA and AprA were clustered with those from sulfur-oxidizing bacteria (SOB) (S5 Fig), suggesting that these CDSs originated from SOB. We also found CDSs for the SOX system (SoxABCXYZ) (Fig 3C), which is involved in thiosulfate oxidation. The detection of these CDSs suggested the presence of SOB in the Fe-Mn crust. Read coverages of some of the CDSs were relatively high (>10×), indicating that some SOB were not rare members in the microbial community in the Fe-Mn crust.

Fig 3. Read-coverage-based rank abundant plot of contigs containing CDSs potentially involved in sulfur oxidation.

CDSs of (A) DsrAB, (B) AprAB, and (C) SoxABCXYZ. Taxonomic affiliations for the CDSs are indicated on the bars. The IDs of metagenome-assembled genomes (MAGs) are shown for the contigs containing CDSs identical to those of the MAGs.

Some microorganisms can reduce solid Fe(III) and Mn(IV) oxides or oxidize dissolved Fe2+ and Mn2+ in the crusts. For Shewanella spp. in Gammaproteobacteria and Geobacter spp. in Deltaproteobacteria, multiheme c-type cytochromes (Cyc) located in their outer membrane, such as MtrC and OmcA, are involved in the reduction of Fe(III) and Mn(IV) oxides via extracellular electron transfer [5962]. The CDSs with one or multiple (up to ten) heme-binding motifs (CXXCH) showing high similarity to these outer membrane Cyc of Shewanella spp. and Geobacter spp. were found in the crust metagenome, although the read coverages were low (1× to 7×) (Fig 4A). OTUs belonging to Shewanella were detected in the above 16S rRNA gene amplicon analysis, although the abundance was also low (< 0.003% of the total reads from MnT55a) [13]. No OTUs related to Geobacter were detected in this sample. Outer membrane Cyc has been also suggested to be involved in Fe oxidation by Fe-oxidizing bacteria [6365]. However, such CDSs were not found in the metagenome, which was consistent with the result that no OTUs related to neutrophilic Fe-oxidizing bacteria, such as Mariprofundus [66] and Ferriphaselus [67], were detected in the sample.

Fig 4. Read-coverage-based rank abundant plot of contigs containing CDSs potentially involved in Mn and Fe cycling.

(A) CDSs for extracellular electron transfer (EET) related Cyc. The homologous gene name and the number of heme-binding motifs (CXXCH) are indicated in parentheses. CDSs for manganese oxidizing enzymes (B) MopA, and (C) CumA, MnxG, and MoxA. The threshold of BLAST e-values against the enzymes MopA of Aurantimonas manganoxydans SI85-9A1 (WP_009209951), CumA of Pseudomonas putida GB-1 (Accession no. AAD24211), MnxG of Bacillus sp. SG-1 (AAB06489), MoxA of Pedomicrobium sp. ACM 3067 (CAJ19378) are shown by the colors of the bars. The IDs of metagenome-assembled genomes (MAGs) are shown for the contigs containing CDSs identical to those of the MAGs.

Regarding Mn oxidation, we found CDSs homologous to some Mn oxidases, such as MopA (Fig 4B), classified in a heme peroxidase family, and CumA, MnxG, and MoxA (Fig 4C) in a multicopper oxidase family [68, 69]. These Mn oxidases have been reported in Aurantimonas spp., Pedomicrobium spp., Erythrobacter spp. in Alphaproteobacteria, Pseudomonas spp. in Gammaproteobacteria, and Bacillus spp. in Firmicutes. In 16S rRNA gene amplicon analysis, the OTUs belonging to Pseudomonas and Bacillus were detected in this sample (0.09% and 0.08% of the total reads from MnT55a, respectively) [13]. Some MopA CDSs were estimated to be in the extracellular region, which is consistent with a previous report [70]. The BLASTp e-values for some Mn oxidase CDSs were relatively low (< 1e-130, in some cases), suggesting that the CDSs included Mn oxidases. Furthermore, some MopA CDSs were homologous to animal heme peroxidases found in Roseobacter sp. AzwK-3b, which is involved in Mn oxidation via superoxide production and H2O2 degradation [71]. In the production of Mn oxides (MnO2) via superoxide production, H2O2 degradation is required, as intermediate Mn(III) in Mn(II) oxidation can be reduced back to Mn(II) by H2O2 [72]. In the crust environments, H2O2 could be removed by MnO2 abiotically and by microorganisms possessing the H2O2 degrading enzyme catalase [EC], of which CDSs were found in the metagenome (S6 Fig), in addition to the animal heme peroxidase.

Metabolic potential of metagenome-assembled genomes

We obtained four metagenome-assembled genomes (MAGs), defined as MnTg01–04, with over 70% genome completeness and below 5% contamination (Table 1). All the MAGs were classified as medium-quality based on the standard minimum information about a metagenome-assembled genome (MIMAG) [73]. A phylogenetic tree of a concatenated amino acid sequence of CDSs for 43 single-copy marker proteins (Fig 5) showed that these MAGs were affiliated with Thaumarchaeota for MnTg01, Alphaproteobacteria for MnTg02, and Gammaproteobacteria for MnTg03 and MnTg04. The average read coverages for the CDSs for RpsC of the MAGs (Fig 1A) indicated that the MnTg01 thaumarchaeon was the most abundant member of the crust community. The MAGs of MnTg02 and MnTg04 were also within the top 10 members. Although no CDS for RpsC was found in MnTg03, one of the relatively abundant contigs containing gammaproteobacterial RpsC CDS (Fig 1A) was likely derived from the MnTg03 bacterium based on the read coverage of the MAG (Table 1) and phylogeny (Figs 5 and S1). The reconstructed metabolic pathways for the four MAGs are shown in Fig 6A–6D, and the CDSs involved in the pathways are listed in S1 Table.

Fig 5. Phylogenomic tree for the MAGs.

The maximum-likelihood tree of the MAGs was constructed using 43 conserved single-copy marker proteins. The IDs in bold and orange were reconstructed in the present study. Accession numbers for reference sequences are shown in S2 Table. The scale bar represents 0.3 amino acid substitutions per sequence position. Bootstrap values (> 50% of 1000 replicates) are indicated at nodes.

Fig 6. Key metabolic pathways of the four MAGs.

(A) MnTg01, (B) MnTg02, (C) MnTg03 and MnTg04. (A and B) The presence and absence of each gene is indicated by black and gray arrows, respectively. (C) Black arrows indicate genes present in MnTg03 and MnTg04. White arrows indicate genes absent in MnTg03 and MnTg04. Green or red arrows indicate genes present only in MnTg03 or MnTg04, respectively. The locus tags and full names of the genes in the pathways are shown in S1 Table.

The phylogenetic analysis (Figs 5 and S1) revealed that MnTg01 thaumarchaeon was located in the AOA clade which includes Nitrosopumilus spp. [74] and Nitrosopelagicus spp. [75]. Average amino acid identities (AAI) of MnTg01 to the cultivated AOA genomes were < 66.5%, suggesting that MnTg01 thaumarchaeon represented a novel genus based on a previously reported definition [76]. This was supported by the 93.7% sequence similarity of the 16S rRNA gene to the closest cultivated species, Candidatus Nitrosopelagicus brevis [75], which was lower than the 94.5% genus definition threshold [77]. The MnTg01 contained CDSs involved in ammonia oxidation (AmoABC and NirK), oxygen respiration (aa3-type Cox), and carbon fixation via the 3HP/4HB cycle (Fig 6A) as previously reported for thaumarchaeotic AOA [78, 79]. Many CDSs for the Embden–Meyerhof–Parnas (EMP) pathway and TCA cycle were found in MnTg01. CDSs involved in assimilatory sulfate reduction (Sat, CysH, and Sir) were also detected. No CDSs for GH families were detected. Notably, the MnTg01 contained CDSs for chemotaxis and archaeal flagellum (known as archaellum), as reported for some thaumarchaeotic AOA, such as Nitrososphaera spp. [79], Nitrosotalea spp. [80], and Nitrosoarchaeum spp. [81], suggesting that the MnTg01 thaumarchaeon had biofilm formation and surface adhesion capabilities [82].

The alphaproteobacterial MnTg02 was affiliated with the order Rhizobiales (Fig 5). This MAG was related to species in the genera Methyloligella, Hyphomicrobium, and Rhodomicrobium and to MAG RBG_16_64_48 recovered from terrestrial sediments [83] (AAI, < 56.3%), but clearly not to alphaproteobacterial MAGs (SPGG1 and SPGG7) recovered from pelagic deep-sea sediments [29]. Considering that an AAI threshold of 45–65% has been used for a family level definition [76], the alphaproteobacterial MnTg02 should be classified as a novel family. The MnTg02 contained CDSs for oxygen respiration (aa3-Cox, cbb3-Cox, and bd-type quinol oxidase), nitrate respiration (NapAB and NirS), fumarate respiration (Frd), thiosulfate/sulfite oxidation (SoxAXYZ, AprAB, and Sat), carbon fixation via the CBB cycle, sugar decomposition (GH families 3, 15, 23, 103 and 130), fatty acid decomposition (beta-oxidation pathway), and assimilatory sulfate reduction (CysNCDHI), in addition to the EMP pathway and TCA cycle (Fig 6B). As described above, CDSs for manganese oxidation (MopA and CumA) were also detected. The presence of CDSs for chemotaxis, pilus, and flagellum suggested biofilm formation and surface adhesion capabilities. In the biofilm, anoxic microenvironments could be created, where the MnTg02 alphaproteobacterium could grow by anaerobic respiration using nitrate and fumarate. In addition to the organic carbon in the sinking POC, reduced sulfur species, which could be produced by decomposition of sulfur-containing organic compounds (such as cysteine and methionine) contained in the POC, might be also used as an energy source for the MnTg02 alphaproteobacterium.

The two gammaproteobacterial members derived from the MAGs (MnTg03 and MnTg4) were affiliated with the order Chromatiales of the Gammaproteobacteria (Figs 5 and S1) and differed from each other at least at the family level (AAI, 45.4%). MnTg03 was distantly related to cultivated species of Chromatiales such as Granulosicoccus, Thioalkalivibrio, and Halothiobacillus with relatively low AAI values (< 47.2%). MnTg04 was affiliated with the clade JTB255/Woeseiaceae, whose members have been commonly detected in deep-sea sediments [84, 85]. MnTg04 was related to a chemoheterotrophic bacterium Woeseia oceani [86] and some MAGs/SAGs recovered from marine sediments [53, 85] (AAI, < 54.4%). Previous metagenomic studies and radio-isotope incubation experiments [85, 87] have suggested that the JTB255/Woeseiaceae contain autotrophs. The two gammaproteobacterial MAGs contained CDSs for the EMP pathway, TCA cycle, beta-oxidation pathway for lipid decomposition, GH families (3, 15, 23, 103 and 130) for sugar decomposition, and aerobic respiration, but none for chemolithoautotrophic metabolism or anaerobic respiration (Fig 6C and 6D). Therefore, they may be aerobic chemoheterotrophs and/or facultative anaerobic fermenting bacteria.


Our metagenomics data provided novel insights into the microbial ecology of the Fe-Mn crust surface, and to the microbial contribution to the formation of the Fe-Mn crust. Previous studies have shown the microbial community structures on the Fe-Mn crust surface using single-gene analysis (16S rRNA and amoA genes) [11, 13, 14]; however, their metabolic potentials were largely unknown. In the present study, we propose a model of the biogeochemical cycling of C, N, S, Fe and Mn on the crust surface (Fig 7) based on the metagenomic results, in addition to the previous microscopic results [13].

Fig 7. Proposed model of the microbial contribution to the biogeochemical cycling of C, N, S, Fe, and Mn and the formation of the Fe-Mn crust.

Illustration of a side-view of the crust at micrometer-scale is shown. Microorganisms with nano-sized fibers form biofilms in the crusts [13]. The biofilm can adsorb Fe and Mn oxide particles in seawater. Extracellular proteins produced by the microorganisms contribute to decomposition of particulate organic matter (POM) and manganese oxidation/reduction. Nitrifers play a role as primary producers in the crust ecosystem. Acidification by fermenters and ammonia oxidizers cause dissolution of Mn and Fe oxides. See main text for details.

Microbial ecosystem in the abyssal Fe-Mn crust

As an energy source, ammonia dissolved in seawater (generally several-tens nM or lower [88]) likely sustains the microbial ecosystem on the crust surface, as previously suggested [11, 13, 14]. It has been reported that ammonia is an important energy source in the deep ocean [89]. Based on the genes detected in the crust metagenome, nitrification (i.e., ammonia oxidation and nitrite oxidation) and carbon fixation are likely conducted by members of the MGI of Thaumarchaeota, Nitrosomonadales of Betaproteobacteria, Nitrospirae, and Nitrospinae. Furthermore, we obtained the MAG MnTg01 of an MGI member, which was the most abundant in the crust (Fig 1A). The genomic analysis of the MnTg01 confirmed the potential of ammonia oxidation by Amo and carbon fixation via the 3HP/4HB pathway (Fig 6A). Considering the high abundance of the MnTg01 in the microbial community and its chemolithoautotrophy potential, the MnTg01 thaumarchaeon likely plays a significant role as a primary producer in the microbial ecosystem of the Fe-Mn crust.

The gene survey in the metagenome suggests that urea is also used as an energy source by the Fe-Mn crust microorganisms. Previous isotope labeling studies have shown that urea is an important energy source for thaumarchaeotic AOA and betaproteobacterial AOB in pelagic oceans [9092]. Previous physiological characterization has confirmed that urea is used for some of the AOA and AOB cultivated isolates as an energy and carbon source [93, 94]. Based on the read coverage and taxonomic affiliation of CDSs for Ure and RpsC (Figs 1A and 2A), several abundant members of Thaumarchaeota on the crust surface may use urea as an energy and carbon source. However, the most abundant thaumarchaeotic member (i.e., the MnTg01 archaeon; read coverage, >45×) may not use urea, because the CDS for Ure was not found in its MAG. This is supported by the fact that no CDSs for Ure in the metagenome showed high read coverage. Thus, urea may support the microbial ecosystem as a secondary energy source.

Although cyanate, a decomposition product of urea, is another potential energy source in oceans [92, 95], it may not be used as an energy source for the crust microorganisms. Several tens nM of cyanate have been detected in seawater [96]. Indeed, a thaumarchaeotic AOA isolate, Candidatus ‘Nitrososphaera gargensis’, of which the genome encodes Cyn and Amo, can grow with cyanate, which is converted into ammonia by Cyn, as the sole energy source [95]. However, we only found two CDSs for Cyn in the metagenome, and those CDSs were not affiliated with AOA or AOB. The gammaproteobacterial and alphaproteobacterial species possessing the CDSs for Cyn (Fig 2A) might use cyanate as a nitrogen source.

The Fe-Mn crust likely harbors heterotrophic microorganisms possessing GHs and peptidases, which likely use organic carbon derived from POC as their energy and carbon source. The MnTg03 and MnTg04 gammaproteobacteria likely contribute to the POC decomposition. Accordingly, the POC decomposition by heterotrophs can produce reduced sulfur compounds (such as sulfide and thiosulfate). The MnTg02 alphaproteobacterium and other bacteria, which possess the CDSs (such as Apr and Sox) involved in oxidation of reduced sulfur compounds, can chemolithotrophically use these sulfur compounds as energy sources. In addition, abiotic POC decomposition by Mn oxides into more labile carbon compounds such as pyruvate [58], which are easily used by heterotrophs, could occur in the Fe-Mn crust. Although there are several tens μM of dissolved organic carbon (DOC) in deep seawater, the majority of the DOC is refractory [97] and is not easily used by microorganisms [98]. However, if Mn oxides in the Fe-Mn crust also abiotically decompose such refractory DOC into labile organic compounds [58], the heterotrophic microorganisms can use them as energy and carbon sources.

Anaerobes may also be present in the Fe-Mn crust. Our previous microscopic observation indicated that microorganisms accumulated in valleys on the bumpy surface of the Fe-Mn crust [13]. Oxygen consumption by aerobes may create anoxic microenvironments in the valleys where POC are trapped. In such anoxic microenvironments, anaerobic respiration bacteria using nitrate, fumarate, Fe and Mn oxides as electron acceptors, and fermenting bacteria producing organic acids (such as lactic and acetic acids) can grow. This was supported by the detection of the CDSs involved in these anaerobic reactions in the metagenome.

Overall, the microbial community in the oligotrophic Fe-Mn crust is likely sustained by dissolved nitrogen compounds (i.e., ammonia and urea) and sinking particles containing organic carbon and sulfur as energy sources, which are suppled from the photosynthetic ecosystem at the ocean surface. Considering the wide distribution of the Fe-Mn crusts in oceans [2], the abundance and ubiquitousness of microorganisms in the crusts [11, 13], and their potential metabolic functions reported in this study, microbial communities in Fe-Mn crusts potentially play an important role in scavenging organic compounds for the whole ocean ecosystem.

Biological contribution to geochemical cycling of Fe and Mn

The microbial metabolisms described above potentially contribute to geochemical cycling of Fe and Mn. For instance, ammonia oxidation by AOA and AOB could decrease the pH by the following reaction: NH4+ + 1.5 O2 → NO2- + H2O + 2 H+. Organic acid production by fermenting bacteria could also decrease the pH. Because Mn2+ is more thermodynamically stable than Mn oxides (as MnO2) at lower pH (<7) even under aerobic conditions, a decreased pH could cause dissolution of Mn oxides in the Fe-Mn crusts. The putative Mn reducers possessing extracellular Cyc could also be involved in the Mn reduction and dissolution. These microbial Mn dissolution processes may explain the Mn depletion in the valleys on the Fe-Mn crust surface, which have been shown by a previous microscopic observation [13]. Fe oxides can be also reduced and dissolved by putative Fe reducers possessing extracellular Cyc, but the dissolved Fe2+ can be rapidly re-oxidized to Fe oxides abiotically under the aerobic and weak alkaline conditions of seawater.

The dissolved Mn2+ can be oxidized in the Fe-Mn crust by putative Mn oxidizers possessing Mn oxidases, such as the MnTg02 alphaproteobacterium. In addition, diverse microorganisms with H2O2-degrading capability could also be involved in Mn oxidation, as reported previously [71, 99]. Some microorganisms including members in the MGI of Thaumarchaeota and Rhizobiales of Alphaproteobacteria may form biofilms on the Fe-Mn crust. In fact, microbial cells with fibrous organic materials covering the crust surface have been observed by scanning electron microscopy [13]. Such biofilms can adsorb Mn and Fe oxide colloidal particles [100, 101].

The above microbial activities could contribute to both the acceleration and suppression of the growth of the Fe-Mn crust. The extremely slow growth rate of Fe-Mn crusts (1–10 mm/Myr) is potentially controlled by the balance of the acceleration and suppression of oxidation/reduction and dissolution/precipitation of Mn and Fe by microbial activities, although further experimental evaluation is needed.


The first metagenomic analysis of a deep-sea Fe-Mn crust indicated the potential of biogeochemical cycling of C, N, S, Fe, and Mn, driven by as-yet-uncultivated microorganisms. Our results led us to propose a model of the biogeochemical cycling in deep-sea Fe-Mn crusts, which implies that the growth rate of the Fe-Mn crusts is constrained by microbial activities. However, it remains unclear how active the metabolisms of these microorganisms are in situ environments, and how significant their activities are in oceanic biogeochemical cycling. Further studies, such as metatranscriptomics/metaproteomics and in situ tracer experiments, will be necessary to address the above questions.

Supporting information

S1 Fig. Phylogenetic tree of RpsC detected in the metagenome.

The IDs in orange and green were detected in the metagenome and the MAG MnTg01, respectively. Numbering (#1 to #20) of the top 20 of the higher read coverages are shown. The RpsC sequences from #10 and #12 in Alphaproteobacteria were removed from the tree construction because of their short sequences. The scale bar represents 0.1 amino acid substitutions per sequence position. Bootstrap values (> 50% of 1000 replicates) are indicated at nodes.


S2 Fig. Phylogenetic tree of NxrB/NarH.

The IDs in orange were detected in the metagenome. The clades of nitrite oxidizers are indicated. The scale bar represents 0.3 amino acid substitutions per sequence position. Bootstrap values (> 50% of 1000 replicates) are indicated at nodes.


S3 Fig. Rank abundant plot of CDSs for GH families detected in the metagenome.


S4 Fig. Read-coverage-based rank abundant plot of contigs containing CDSs for formaldehyde dehydrogenase (Fdh) and lactate dehydrogenase (Ldh).

Taxonomic affiliations for the genes are indicated on the bars.


S5 Fig. Phylogenetic tree of DsrA and AprA.

The IDs in orange were detected in the metagenome. The clades of sulfur oxidizers and sulfate reducers are indicated. The scale bar represents 0.1 amino acid substitutions per sequence position. Bootstrap values (> 50% of 1000 replicates) are indicated at nodes.


S6 Fig. Read-coverage-based rank abundant plot of contigs containing CDSs for catalases (KatE and KatG).

Taxonomic affiliations for the genes are indicated on the bars.



We are grateful to the crew of the R/V Kairei, operational team of the ROV Kaiko Mk-IV, and scientists who joined the KR16-E01 cruise for their cooperation in sample collection. We would like to thank Mr. Mitsuteru Kuno (Nippon Marine Enterprises) and Mr. Keisuke Matsumoto (Marine Work Japan) for their technical assistant on board. We would like to thank Editage for English language editing.


  1. 1. Glasby G. Manganese: Predominant role of nodules and crusts. In: Schulz H, Zabel M, editors. Marine geochemistry: Springer Berlin Heidelberg; 2006. p. 371–427.
  2. 2. Usui A, Nishi K, Sato H, Nakasato Y, Thornton B, Kashiwabara T, et al. Continuous growth of hydrogenetic ferromanganese crusts since 17Myr ago on Takuyo-Daigo Seamount, NW Pacific, at water depths of 800–5500m. Ore Geol Rev. 2017;87:71–87.
  3. 3. Koschinsky A, Hein J. Marine ferromanganese encrustations: Archives of changing oceans. Elements. 2017;13(3):177–82.
  4. 4. Goto KT, Anbar AD, Gordon GW, Romaniello SJ, Shimoda G, Takaya Y, et al. Uranium isotope systematics of ferromanganese crusts in the pacific ocean: Implications for the marine 238U/235U isotope system. Geochim Cosmochim Acta. 2014;146:43–58.
  5. 5. Koschinsky A, Halbach P. Sequential leaching of marine ferromanganese precipitates: Genetic implications. Geochim Cosmochim Acta. 1995;59(24):5113–32.
  6. 6. Kashiwabara T, Oishi Y, Sakaguchi A, Sugiyama T, Usui A, Takahashi Y. Chemical processes for the extreme enrichment of tellurium into marine ferromanganese oxides. Geochim Cosmochim Acta. 2014;131(0):150–63.
  7. 7. Goldberg ED. Marine geochemistry 1. Chemical scavengers of the sea. J Geol. 1954;62(3):249–65.
  8. 8. Hein JR, Koschinsky A. Deep-ocean ferromanganese crusts and nodules. In: Turekian KK, editor. Treatise on geochemistry (second edition). 13. Oxford: Elsevier; 2014. p. 273–91.
  9. 9. Shiraishi F, Mitsunobu S, Suzuki K, Hoshino T, Morono Y, Inagaki F. Dense microbial community on a ferromanganese nodule from the ultra-oligotrophic South Pacific Gyre: Implications for biogeochemical cycles. Earth Planet Sci Lett. 2016;447:10–20.
  10. 10. Lindh MV, Maillot BM, Shulse CN, Gooday AJ, Amon DJ, Smith CR, et al. From the surface to the deep-sea: Bacterial distributions across polymetallic nodule fields in the Clarion-Clipperton Zone of the pacific ocean. Front Microbiol. 2017;8:1696. pmid:28943866
  11. 11. Nitahara S, Kato S, Usui A, Urabe T, Suzuki K, Yamagishi A. Archaeal and bacterial communities in deep-sea hydrogenetic ferromanganese crusts on old seamounts of the northwestern Pacific. PLOS ONE. 2017;12(2):e0173071. pmid:28235095
  12. 12. Shulse CN, Maillot B, Smith CR, Church MJ. Polymetallic nodules, sediments, and deep waters in the equatorial north pacific exhibit highly diverse and distinct bacterial, archaeal, and microeukaryotic communities. MicrobiologyOpen. 2017;6(2):e428. pmid:27868387
  13. 13. Kato S, Okumura T, Uematsu K, Hirai M, Iijima K, Usui A, et al. Heterogeneity of microbial communities on deep-sea ferromanganese crusts in the Takuyo-Daigo Seamount. Microbes Environ. 2018;33:366–377. pmid:30381615
  14. 14. Nitahara S, Kato S, Urabe T, Usui A, Yamagishi A. Molecular characterization of the microbial community in hydrogenetic ferromanganese crusts of the Takuyo-Daigo Seamount, northwest pacific. FEMS Microbiol Lett. 2011;321(2):121–9. pmid:21631576
  15. 15. Ehrlich HL. How microbes influence mineral growth and dissolution. Chemical Geology. 1996;132(1–4):5–9.
  16. 16. Melton ED, Swanner ED, Behrens S, Schmidt C, Kappler A. The interplay of microbially mediated and abiotic reactions in the biogeochemical fe cycle. Nat Rev Micro. 2014;12(12):797–808. pmid:25329406
  17. 17. Tebo BM, Bargar JR, Clement BG, Dick GJ, Murray KJ, Parker D, et al. Biogenic manganese oxides: Properties and mechanisms of formation. Annu Rev Earth Planet Sci. 2004;32(1):287–328.
  18. 18. Tully BJ, Heidelberg JF. Microbial communities associated with ferromanganese nodules and the surrounding sediments. Front Microbiol. 2013;4:161. pmid:23805131
  19. 19. Blothe M, Wegorzewski A, Muller C, Simon F, Kuhn T, Schippers A. Manganese-cycling microbial communities inside deep-sea manganese nodules. Environ Sci Technol. 2015;49(13):7692–700. pmid:26020127
  20. 20. Lee MD, Walworth NG, Sylvan JB, Edwards KJ, Orcutt BN. Microbial communities on seafloor basalts at Dorado Outcrop reflect level of alteration and highlight global lithic clades. Front Microbiol. 2015;6:1470. pmid:26779122
  21. 21. DeLong E. Archaea in coastal marine environments. Proc Natl Acad Sci USA. 1992;89:5685–9. pmid:1608980
  22. 22. Könneke M, Bernhard AE, de la Torre JR, Walker CB, Waterbury JB, Stahl DA. Isolation of an autotrophic ammonia-oxidizing marine archaeon. Nature. 2005;437(7058):543–6. pmid:16177789
  23. 23. Nakanishi M, Tamaki K, Kobayashi K. Mesozoic magnetic anomaly lineations and seafloor spreading history of the northwestern Pacific. J Geophys Res-Solid Earth. 1989;94(B11):15437–62.
  24. 24. Müller RD, Sdrolias M, Gaina C, Roest WR. Age, spreading rates, and spreading asymmetry of the world's ocean crust. Geochem Geophys Geosyst. 2008;9(4):Q04006,
  25. 25. DeLong EF, Preston CM, Mincer T, Rich V, Hallam SJ, Frigaard N-U, et al. Community genomics among stratified microbial assemblages in the ocean's interior. Science. 2006;311(5760):496–503. pmid:16439655
  26. 26. Eloe EA, Fadrosh DW, Novotny M, Zeigler Allen L, Kim M, Lombardo MJ, et al. Going deeper: Metagenome of a hadopelagic microbial community. PLoS One. 2011;6(5):e20388. pmid:21629664
  27. 27. Martin-Cuadrado AB, Lopez-Garcia P, Alba JC, Moreira D, Monticelli L, Strittmatter A, et al. Metagenomics of the deep mediterranean, a warm bathypelagic habitat. PLoS One. 2007;2(9):e914. pmid:17878949
  28. 28. Konstantinidis KT, Braff J, Karl DM, DeLong EF. Comparative metagenomic analysis of a microbial community residing at a depth of 4,000 meters at station aloha in the north pacific subtropical gyre. Applied and Environmental Microbiology. 2009;75(16):5345–55. pmid:19542347
  29. 29. Tully BJ, Heidelberg JF. Potential mechanisms for microbial energy acquisition in oxic deep-sea sediments. Applied and Environmental Microbiology. 2016;82(14):4232–43. pmid:27208118
  30. 30. Reese BK, Zinke LA, Sobol MS, LaRowe DE, Orcutt BN, Zhang X, et al. Nitrogen cycling of active bacteria within oligotrophic sediment of the Mid-Atlantic Ridge flank. Geomicrobiology Journal. 2018;35(6):468–83.
  31. 31. Singer E, Chong L, Heidelberg J, Edwards K. Similar microbial communities found on two distant seafloor basalts. Frontiers in Microbiology. 2015;6. pmid:26733957
  32. 32. Hirai M, Nishi S, Tsuda M, Sunamura M, Takaki Y, Nunoura T. Library construction from subnanogram DNA for pelagic sea water and deep-sea sediments. Microbes Environ. 2017;32(4):336–43. pmid:29187708
  33. 33. Kato S, Shibuya T, Takaki Y, Hirai M, Nunoura T, Suzuki K. Genome-enabled metabolic reconstruction of dominant chemosynthetic colonizers in deep-sea massive sulfide deposits. Environ Microbiol. 2018;20(2):862–77. pmid:29322618
  34. 34. Bankevich A, Nurk S, Antipov D, Gurevich AA, Dvorkin M, Kulikov AS, et al. SPAdes: A new genome assembly algorithm and its applications to single-cell sequencing. J Comput Biol. 2012;19(5):455–77. pmid:22506599
  35. 35. Hyatt D, Chen GL, Locascio PF, Land ML, Larimer FW, Hauser LJ. Prodigal: Prokaryotic gene recognition and translation initiation site identification. BMC Bioinformatics. 2010;11(1):119. pmid:20211023
  36. 36. Ogata H, Goto S, Sato K, Fujibuchi W, Bono H, Kanehisa M. KEGG: Kyoto encyclopedia of genes and genomes. Nucleic Acids Res. 1999;27(1):29–34. pmid:9847135
  37. 37. Kanehisa M, Sato Y, Morishima K. BlastKOALA and GhostKOALA: KEGG tools for functional characterization of genome and metagenome sequences. J MolBiol. 2016;428(4):726–31. pmid:26585406
  38. 38. Altschul SF, Madden TL, Schaffer AA, Zhang J, Zhang Z, Miller W, et al. Gapped BLAST and PSI-BLAST: A new generation of protein database search programs. Nucleic Acids Res. 1997;25(17):3389–402. pmid:9254694
  39. 39. Huson DH, Beier S, Flade I, Górska A, El-Hadidi M, Mitra S, et al. MEGAN community edition—interactive exploration and analysis of large-scale microbiome sequencing data. PLoS Comput Biol. 2016;12(6):e1004957. pmid:27327495
  40. 40. Huson DH, Auch AF, Qi J, Schuster SC. MEGAN analysis of metagenomic data. Genome Res. 2007;17(3):377–86. pmid:17255551
  41. 41. Gruber-Vodicka HR, Seah BKB, Pruesse E. phyloFlash—rapid SSU rRNA profiling and targeted assembly from metagenomes. bioRxiv. 2019:521922.
  42. 42. Lombard V, Golaconda Ramulu H, Drula E, Coutinho PM, Henrissat B. The carbohydrate-active enzymes database (cazy) in 2013. Nucleic Acids Research. 2014;42(D1):D490–D5. pmid:24270786
  43. 43. Zhang H, Yohe T, Huang L, Entwistle S, Wu P, Yang Z, et al. Dbcan2: A meta server for automated carbohydrate-active enzyme annotation. Nucleic Acids Research. 2018;46(W1):W95–W101. pmid:29771380
  44. 44. Eddy SR. Accelerated profile hmm searches. PLOS Computational Biology. 2011;7(10):e1002195. pmid:22039361
  45. 45. Kang DD, Froula J, Egan R, Wang Z. MetaBAT, an efficient tool for accurately reconstructing single genomes from complex microbial communities. PeerJ. 2015;3:e1165. pmid:26336640
  46. 46. Seah BKB, Gruber-Vodicka HR. gbtools: Interactive visualization of metagenome bins in R. Front Microbiol. 2015;6: pmid:26732662
  47. 47. Seemann T. Prokka: Rapid prokaryotic genome annotation. Bioinformatics. 2014;30(14):2068–9. pmid:24642063
  48. 48. Rodriguez R LM, Konstantinidis KT. The enveomics collection: A toolbox for specialized analyses of microbial genomes and metagenomes. PeerJ Preprints. 2016;4:e1900v1.
  49. 49. Parks DH, Imelfort M, Skennerton CT, Hugenholtz P, Tyson GW. CheckM: Assessing the quality of microbial genomes recovered from isolates, single cells, and metagenomes. Genome Res. 2015;25(7):1043–55. pmid:25977477
  50. 50. Edgar RC. MUSCLE: Multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res. 2004;32(5):1792–7. pmid:15034147
  51. 51. Capella-Gutierrez S, Silla-Martinez JM, Gabaldon T. trimAl: A tool for automated alignment trimming in large-scale phylogenetic analyses. Bioinformatics. 2009;25(15):1972–3. pmid:19505945
  52. 52. Stamatakis A. RAxML version 8: A tool for phylogenetic analysis and post-analysis of large phylogenies. Bioinformatics. 2014;30(9):1312–3. pmid:24451623
  53. 53. Baker BJ, Lazar CS, Teske AP, Dick GJ. Genomic resolution of linkages in carbon, nitrogen, and sulfur cycling among widespread estuary sediment bacteria. Microbiome. 2015;3(1):14. pmid:25922666
  54. 54. Daims H, Lebedeva EV, Pjevac P, Han P, Herbold C, Albertsen M, et al. Complete nitrification by Nitrospira bacteria. Nature. 2015;528(7583):504–9. pmid:26610024
  55. 55. van Kessel MA, Speth DR, Albertsen M, Nielsen PH, Op den Camp HJ, Kartal B, et al. Complete nitrification by a single microorganism. Nature. 2015;528(7583):555–9. pmid:26610025
  56. 56. Pester M, Maixner F, Berry D, Rattei T, Koch H, Lucker S, et al. NxrB encoding the beta subunit of nitrite oxidoreductase as functional and phylogenetic marker for nitrite-oxidizing Nitrospira. Environ Microbiol. 2014;16(10):3055–71. pmid:24118804
  57. 57. Hügler M, Sievert SM. Beyond the calvin cycle: Autotrophic carbon fixation in the ocean. Annual Review of Marine Science. 2010;3(1):261–89. pmid:21329206
  58. 58. Sunda WG, Kieber DJ. Oxidation of humic substances by manganese oxides yields low-molecular-weight organic substrates. Nature. 1994;367(6458):62–4.
  59. 59. Myers JM, Myers CR. Role for outer membrane cytochromes omca and omcb of shewanella putrefaciens mr-1 in reduction of manganese dioxide. Applied and Environmental Microbiology. 2001;67(1):260–9. pmid:11133454
  60. 60. Mehta T, Coppi MV, Childers SE, Lovley DR. Outer membrane c-type cytochromes required for Fe(III) and Mn(IV) oxide reduction in Geobacter sulfurreducens. Appl Environ Microbiol. 2005;71(12):8634–41. pmid:16332857
  61. 61. Leang C, Coppi MV, Lovley DR. Omcb, a c-type polyheme cytochrome, involved in Fe(III) reduction in Geobacter sulfurreducens. J Bacteriol. 2003;185.
  62. 62. Butler JE, Young ND, Lovley DR. Evolution of electron transfer out of the cell: Comparative genomics of six Geobacter genomes. BMC Genomics. 2010;11(1):40. pmid:20078895
  63. 63. Kato S, Ohkuma M, Powell DH, Krepski ST, Oshima K, Hattori M, et al. Comparative genomic insights into ecophysiology of neutrophilic, microaerophilic iron oxidizing bacteria. Front Microbiol. 2015;6: pmid:26617599
  64. 64. Barco RA, Emerson D, Sylvan JB, Orcutt BN, Jacobson Meyers ME, Ramirez GA, et al. New insight into microbial iron oxidation as revealed by the proteomic profile of an obligate iron-oxidizing chemolithoautotroph. Appl Environ Microbiol. 2015;81(17):5927–37. pmid:26092463
  65. 65. Castelle C, Guiral M, Malarte G, Ledgham F, Leroy G, Brugna M, et al. A new iron-oxidizing/O2-reducing supercomplex spanning both inner and outer membranes, isolated from the extreme acidophile Acidithiobacillus ferrooxidans. J Biol Chem. 2008;283(38):25803–11. pmid:18632666
  66. 66. Emerson D, Rentz JA, Lilburn TG, Davis RE, Aldrich H, Chan C, et al. A novel lineage of proteobacteria involved in formation of marine fe-oxidizing microbial mat communities. PLOS ONE. 2007;2(8):e667. pmid:17668050
  67. 67. Kato S, Krepski S, Chan C, Itoh T, Ohkuma M. Ferriphaselus amnicola gen. nov., sp. nov., a neutrophilic, stalk-forming, iron-oxidizing bacterium isolated from an iron-rich groundwater seep. Int J Syst Evol Microbiol. 2014;64(Pt 3):921–5. pmid:24425821
  68. 68. Geszvain K, Butterfield C, Davis Richard E, Madison Andrew S, Lee S-W, Parker Dorothy L, et al. The molecular biogeochemistry of manganese(II) oxidation. Biochemical Society Transactions. 2012;40(6):1244–8. pmid:23176462
  69. 69. Tebo BM, Johnson HA, McCarthy JK, Templeton AS. Geomicrobiology of manganese(II) oxidation. Trends Microbiol. 2005;13(9):421–8. pmid:16054815
  70. 70. Anderson CR, Johnson HA, Caputo N, Davis RE, Torpey JW, Tebo BM. Mn(II) oxidation is catalyzed by heme peroxidases in “aurantimonas manganoxydans” strain si85-9a1 and erythrobacter sp. Strain sd-21. Applied and Environmental Microbiology. 2009;75(12):4130–8. pmid:19411418
  71. 71. Andeer PF, Learman DR, McIlvin M, Dunn JA, Hansel CM. Extracellular haem peroxidases mediate Mn(II) oxidation in a marine roseobacter bacterium via superoxide production. Environmental Microbiology. 2015;17(10):3925–36. pmid:25923595
  72. 72. Learman DR, Voelker BM, Madden AS, Hansel CM. Constraints on superoxide mediated formation of manganese oxides. Front Microbiol. 2013;4:262. pmid:24027565
  73. 73. Bowers RM, Kyrpides NC, Stepanauskas R, Harmon-Smith M, Doud D, Reddy TBK, et al. Minimum information about a single amplified genome (MISAG) and a metagenome-assembled genome (MIMAG) of bacteria and archaea. Nat Biotechnol. 2017;35(8):725–31. pmid:28787424
  74. 74. Qin W, Heal KR, Ramdasi R, Kobelt JN, Martens-Habbena W, Bertagnolli AD, et al. Nitrosopumilus maritimus gen. nov., sp. nov., nitrosopumilus cobalaminigenes sp. nov., nitrosopumilus oxyclinae sp. nov., and nitrosopumilus ureiphilus sp. nov., four marine ammonia-oxidizing archaea of the phylum Thaumarchaeota. Int J Syst Evol Microbiol. 2017;67:5067–79. pmid:29034851
  75. 75. Santoro AE, Dupont CL, Richter RA, Craig MT, Carini P, McIlvin MR, et al. Genomic and proteomic characterization of “Candidatus nitrosopelagicus brevis”: An ammonia-oxidizing archaeon from the open ocean. Proceedings of the National Academy of Sciences. 2015;112(4):1173–8. pmid:25587132
  76. 76. Konstantinidis KT, Rossello-Mora R, Amann R. Uncultivated microbes in need of their own taxonomy. ISME J. 2017;11(11):2399–406. pmid:28731467
  77. 77. Yarza P, Yilmaz P, Pruesse E, Glockner FO, Ludwig W, Schleifer K-H, et al. Uniting the classification of cultured and uncultured bacteria and archaea using 16S rRNA gene sequences. Nat Rev Micro. 2014;12(9):635–45. - supplementary-information. pmid:25118885
  78. 78. Walker CB, de la Torre JR, Klotz MG, Urakawa H, Pinel N, Arp DJ, et al. Nitrosopumilus maritimus genome reveals unique mechanisms for nitrification and autotrophy in globally distributed marine crenarchaea. Proc Natl Acad Sci USA. 2010;107(19):8818–23. pmid:20421470
  79. 79. Kerou M, Offre P, Valledor L, Abby SS, Melcher M, Nagler M, et al. Proteomics and comparative genomics of nitrososphaera viennensis reveal the core genome and adaptations of archaeal ammonia oxidizers. Proc Natl Acad Sci USA. 2016;113(49):E7937–E46. pmid:27864514
  80. 80. Lehtovirta-Morley LE, Sayavedra-Soto LA, Gallois N, Schouten S, Stein LY, Prosser JI, et al. Identifying potential mechanisms enabling acidophily in the ammonia-oxidizing archaeon “Candidatus nitrosotalea devanaterra”. Applied and Environmental Microbiology. 2016;82(9):2608–19. pmid:26896134
  81. 81. Mosier AC, Lund MB, Francis CA. Ecophysiology of an ammonia-oxidizing archaeon adapted to low-salinity habitats. Microbial Ecology. 2012;64(4):955–63. pmid:22644483
  82. 82. Lassak K, Ghosh A, Albers S-V. Diversity, assembly and regulation of archaeal type IV pili-like and non-type-IV pili-like surface structures. Research in Microbiology. 2012;163(9):630–44.
  83. 83. Anantharaman K, Brown CT, Hug LA, Sharon I, Castelle CJ, Probst AJ, et al. Thousands of microbial genomes shed light on interconnected biogeochemical processes in an aquifer system. Nat Commun. 2016;7:13219.
  84. 84. Bienhold C, Zinger L, Boetius A, Ramette A. Diversity and biogeography of bathyal and abyssal seafloor bacteria. PLOS ONE. 2016;11(1):e0148016. pmid:26814838
  85. 85. Mußmann M, Pjevac P, Krüger K, Dyksma S. Genomic repertoire of the woeseiaceae/jtb255, cosmopolitan and abundant core members of microbial communities in marine sediments. ISME J. 2017;11(5):1276–81. pmid:28060363
  86. 86. Du Z-J, Wang Z-J, Zhao J-X, Chen G-J. Woeseia oceani gen. nov., sp. nov., a chemoheterotrophic member of the order chromatiales, and proposal of woeseiaceae fam. Nov. International Journal of Systematic and Evolutionary Microbiology. 2016;66(1):107–12. pmid:26474827
  87. 87. Dyksma S, Bischof K, Fuchs BM, Hoffmann K, Meier D, Meyerdierks A, et al. Ubiquitous gammaproteobacteria dominate dark carbon fixation in coastal sediments. ISME J. 2016;10(8):1939–53. pmid:26872043
  88. 88. Rees AP, Woodward EMS, Joint I. Concentrations and uptake of nitrate and ammonium in the atlantic ocean between 60on and 50os. Deep Sea Research Part II: Topical Studies in Oceanography. 2006;53(14–16):1649–65.
  89. 89. Wuchter C, Abbas B, Coolen MJ, Herfort L, van Bleijswijk J, Timmers P, et al. Archaeal nitrification in the ocean. Proc Natl Acad Sci U S A. 2006;103(33):12317–22. pmid:16894176
  90. 90. Tolar BB, Wallsgrove NJ, Popp BN, Hollibaugh JT. Oxidation of urea-derived nitrogen by thaumarchaeota-dominated marine nitrifying communities. Environmental Microbiology. 2017;19(12):4838–50. pmid:27422798
  91. 91. Alonso-Sáez L, Waller AS, Mende DR, Bakker K, Farnelid H, Yager PL, et al. Role for urea in nitrification by polar marine archaea. Proc Natl Acad Sci U S A. 2012;109(44):17989–94. pmid:23027926
  92. 92. Kitzinger K, Padilla CC, Marchant HK, Hach PF, Herbold CW, Kidane AT, et al. Cyanate and urea are substrates for nitrification by Thaumarchaeota in the marine environment. Nature Microbiology. 2019;4(2):234–43. pmid:30531977
  93. 93. Qin W, Amin SA, Martens-Habbena W, Walker CB, Urakawa H, Devol AH, et al. Marine ammonia-oxidizing archaeal isolates display obligate mixotrophy and wide ecotypic variation. Proc Natl Acad Sci U S A. 2014;111(34):12504–9. pmid:25114236
  94. 94. Bayer B, Vojvoda J, Offre P, Alves RJ, Elisabeth NH, Garcia JA, et al. Physiological and genomic characterization of two novel marine thaumarchaeal strains indicates niche differentiation. ISME J. 2016;10(5):1051–63. pmid:26528837
  95. 95. Palatinszky M, Herbold C, Jehmlich N, Pogoda M, Han P, von Bergen M, et al. Cyanate as an energy source for nitrifiers. Nature. 2015;524:105. - supplementary-information. pmid:26222031
  96. 96. Widner B, Mulholland MR, Mopper K. Chromatographic determination of nanomolar cyanate concentrations in estuarine and sea waters by precolumn fluorescence derivatization. Anal Chem. 2013;85(14):6661–6. pmid:23738747
  97. 97. Hansell DA. Recalcitrant dissolved organic carbon fractions. Annu Rev Mar Sci. 2013;5(1):421–45. pmid:22881353
  98. 98. Barber RT. Dissolved organic carbon from deep waters resists microbial oxidation. Nature. 1968;220(5164):274–5. pmid:5684857
  99. 99. Learman DR, Voelker BM, Vazquez-Rodriguez AI, Hansel CM. Formation of manganese oxides by bacterially generated superoxide. Nat Geosci. 2011;4(2):95–8.
  100. 100. Moreau JW, Weber PK, Martin MC, Gilbert B, Hutcheon ID, Banfield JF. Extracellular proteins limit the dispersal of biogenic nanoparticles. Science. 2007;316(5831):1600–3. pmid:17569859
  101. 101. Kleber M, Eusterhues K, Keiluweit M, Mikutta C, Mikutta R, Nico PS. Mineral–organic associations: Formation, properties, and relevance in soil environments. In: Sparks DL, editor. Advances in agronomy. 130: Academic Press; 2015. p. 1–140.