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Edited by Donald E. Canfield, University of Southern Denmark, Odense, Denmark, approved on April 29, 2021 (reviewed on April 10, 2020)

Methane is a strong greenhouse gas and plays a key role in the earth's climate. At the methane leak, a large amount of methane moves upward through the seabed, where the microbial community consumes most of the methane. Comprehensive statistics on methane sources and sinks have never been known to researchers-partly because key habitats, including carbonate hills, have been largely ignored. We sampled seven methane leaks representing four geological environments and found that all sites have rock microorganisms capable of consuming methane; in laboratory-based incubation, some people hatched at the highest rate reported to date. We show several factors that help determine the methane consumption potential of the sample, and propose that the carbonate rock at the methane leak may represent a significant methane sink.

Where methane leaks from the ocean, a large amount of methane moves through the shallow seabed and is mainly consumed by microbial communities. This process plays an important role in global methane dynamics, but we have not yet identified all methane sinks in the deep ocean. Here, we conducted a continental-scale survey on seven geologically different seabed seepages, and found that the carbonate rocks from all locations have methanotrophic methanotrophic communities of methanotrophic microorganisms. In a laboratory-based incubation in the Middle Universe, chimney carbonates exuded from the newly described Point Dume off the coast of Southern California showed the highest anaerobic methane oxidation rate measured so far. After thorough analysis of physicochemical, electrical and biological factors, we attribute this significant metabolic activity to higher cell density, mineral composition, kinetic parameters (including increased Vmax), and specific microorganisms The existence of the pedigree. Our data also suggests that other characteristics, such as electrical conductivity, rock particle size, and microbial community alpha diversity, may affect the methane oxidation potential of the sample, but these factors do not show a clear pattern of methane oxidation rate. Based on the obvious prevalence of the exuded carbonates of microbial communities capable of anaerobic oxidation of methane, and the frequent appearance of carbonates in the exudates, we believe that the methanotrophs of rock hosts may be an important contributor to ocean methane consumption.

Anaerobic oxidation of methane (AOM) strongly regulates the emission of potent greenhouse gases and represents the main production pathway for mobilizing carbon, sulfur and nitrogen on a global scale (1⇓ –3). It is estimated that 80% of underground methane is consumed by the AOM in the ocean methane leak (2). However, since the ways in which different substrate types (such as sediments or rocks) affect AOM have not been fully studied, the location and extent of methane oxidation in the seepage complex is strictly limited.

One neglected habitat at the methane leak is carbonate rock, which may account for a large part of the methane injection at the leak (4⇓ ⇓ ⇓ ⇓ –9). Biomarkers and geochemical features suggesting the methane oxidation lineage have been detected in the leakage-related carbonates (4, 10⇓ ⇓ –13), such as archaea lipids, 16S rRNA genes, and isotope light carbon components (4, 10⇓ ⇓ –13), but the potential role of these substrates in the contemporary methane cycle has been largely ignored. The change in the composition of the microbial community (14) indicates the activity of AOM carried by carbonate (in-stone), which is clearly demonstrated by the measurement of methane oxidation rate and the detection of stable isotopes at a single location [Hydrate Ridge (15)]. In view of the importance of methane in climate regulation, the presence of authigenic carbonates in the seepage, and the limited but encouraging signs of methane oxidation carried by rocks so far, the degree of methane oxidation activity in the methane seepage is worthwhile further research.

Here, we conducted a continental-scale survey of the microbial communities in sediments and rocks and their AOM potential in various ocean methane seepages. Sampling sites included seven locations in four geological environments: 1) the northern Gulf of Mexico, a sedimentary basin bordered by carbonate platforms (16); 2) two continental mid-continent slope submarine canyons on the passive edge of the Atlantic Ocean in the United States (17); 3 ) Two habitats in the Guaymas Basin of the Gulf of California, a hydrothermal site with heavy sedimentation and rich organic matter (18); and 4) Two leak points-including a newly discovered one located in Point Dume, California Nearby small carbonate "chimney" area-active squeeze edge along the coast of Southern California (19) (Figure 1, data set S1 and SI appendix, Figures S1-S5). We quantified the rate of methane oxidation under methane saturation conditions that represent many active leaks, compared our results with previously published data within the kinetic framework, and explored possible determinants of rate differences, including microbial abundance , Community composition and mineralogical background. Our research results reveal that the potential rate of AOM in specific carbonate structures is extremely high, verifies the limited sample set of earlier studies (15), and proves that the methanotrophic community in the inner stone may occur in some methane leakage areas. A lot of carbonate deposits are everywhere. We hypothesize that the exuded carbonate represents a habitat whose properties can support the increase in AOM rates, and that the AOM carried by the carbonate may play a role in the sequestration of greenhouse gases and the influx of methane-derived carbon into the biogeochemical cycle.

An overview of seven locations in four different geological environments sampled in this study. All scales are ∼25 cm; additional geographic and ground coverage environments are provided for each site in the SI appendix, Figure S1-S5.

Carbonate samples from all seven sites showed methane oxidation when incubated in the laboratory (Table 1). Two short-term (<7 d) AOM rate measurement methods are deployed. Radiolabeled 14CH4 is a commonly used high-sensitivity method (20⇓-22) to track the oxidation of methane carbon to inorganic carbon in seven repeated sample incubations, including at least one from each geological environment. CH3D is a recently developed method to measure the oxidation of methane by increasing the water-containing D/H ratio (23). Simultaneous side-by-side experiments have resulted in the conversion factor of a specific site linking the radioactive label data with the D/H value (data set S1 And SI appendix, table S1). This strategy allows us to deduce the apparent rate of AOM from non-destructive, higher-throughput CH3D experiments, which is confirmed by the absolute rate derived from the radiolabeled 14C experiment. The degree to which the conversion factor is applicable to other samples is uncertain, but the relatively low variance measured here (1.94 ± 0.16 SD) and hydrate ridge seepage sediments and carbonates (1.99 ± 0.09 SD) (23) provided The confidence of determining the apparent rate is reliable and robust through the CH3D experiment.

The rate and apparent rate of AOM are derived from short-term and long-term incubation under atmospheric pressure and short-term incubation under high pressure (7.58 MPa)

Most notably, the carbonate host community from the Point Dume (PD) chimney structure exhibits a very high AOM potential rate, oxidizing up to 5,528 (±466 SD, n = 3) nmol methane⋅ cm−3 ⋅ d− 1 (measured as a sample named PD R1). The rate of the three Point Dume carbonates exceeds 1,000 nmol ⋅ cm-3 ⋅ d-1, but even the more moderate values ​​measured with samples from the other three geological environments are large, ranging from ~200 to 850 nmol ⋅ cm-3 ⋅ d- 1. In order to directly compare our results with published rates (which have been evaluated under a range of methane concentrations), all previously measured values ​​are converted to their values ​​at 1.1 mM dissolved methane concentration Equivalent rate, assuming Michaelis-Menten kinetics and using 5.65 mM AOM KM (determined empirically below; please refer to the data set S2 and SI appendix for details on conversion). The Point Dume chimney sample showed the highest normalized methane oxidation rate, which is all previously published research included in the survey. The maximum apparent velocity of the Point Dume carbonate rock is 70 times higher than the previous study on the AOM carried by the carbonate rock in the Hydrate Ridge (15), 5 times higher than the rate of the most productive ocean seepage (21), and is higher than the previous study (15). The highest reported maximum rate of AOM [from the hypoxic Black Sea (24)]. Even several samples from the Gulf of Mexico (GoM), New England Percolation, Wigge Canyon, and northern Guaymas Basin (GBN) have the lowest intra-rock AOM rates that exceed the continental shelf samples and are consistent with the vast majority of percolations previously assessed Or higher than the sediment and mud volcano samples (Tables 1 and 2).

Previously announced AOM rates for methane seepage, mud volcanoes and continental shelf samples

In order to more realistically represent the in situ conditions of methane leakage from the seafloor, we conducted two additional rate measurement experiments: long-term incubation at atmospheric pressure to determine how the metabolic rate adjusts over time as metabolic byproducts accumulate, and In the short-term incubation at 7.58 MPa, the dependence of the AOM on the elevated pressure representing the water depth of 745 m (Point Dume penetration depth) was evaluated. In the course of 112 to 350 days under atmospheric pressure, the apparent rate increased by an average of 17% throughout the experiment, and there was no significant trend based on the matrix (sediments and rocks) or sample location (Table 1 and Figure 2)) . Under high pressure, rocks from all four geological environments showed significantly enhanced apparent velocity, which was an increase of 13.8 (GBN R3 sample) and 75.3 (GoM R1 sample) times compared to short-term experiments conducted under atmospheric pressure. Among the three sediment samples, although GoM PC1 0 to 5 cm does not have methane oxidation activity, two of the three sediment samples showed a relationship with carbonate (PD PC2: 26×, GBN PC1: 106.6× ) Pressure induced rate increases of similar magnitude. The apparent AOM rate of Point Dume chimney PD R4 is 2.8 × 104 nmol ⋅ cm−3 ⋅ d−1 (±0.1 × 104 SD, n = 3), which is the highest methane oxidation rate in the compilation study (Table 1 and Table 2) ) ).

The amount of methane oxidized in a laboratory-based extended incubation experiment. Please note that the 50,000 nmol/cm3 is interrupted by the scale and the y-axis scale marked by the dotted line is shifted by 10 times. Below this line, all data below 50,000 nmol/cm3 are displayed with axis increments of 10,000 nmol/cm3; above this line, all data above 50,000 nmol/cm3 are displayed with axis increments of 100,000 nmol/cm3 Incremental display. The error bars represent the propagation error from the D/H:14C scale factor, and if there is enough material available for three repeated experiments (data set S1), the SD is incubated. Subtract the value of the autoclaved control incubation from the specific location from each data point.

To better characterize the factors that may contribute to the very high AOM rates we measured in carbonates, we examined several key dynamics, mineralogy, and physical properties of the carbonate host environment. Reaction kinetics reflects the eco-physiological parameters that determine the rate, such as substrate affinity, continuous synthesis capacity, and the relative number of reaction centers. We measured co-located Point Dume sediments (PD PC2 0 to 5, AOM rate of 440.73 nmol ⋅ cm−3 ⋅ d-1; ±73.08 SD, n = 3) and carbonate (PD R3, 1,561.66 nmol ⋅ cm) Vmax and Km values ​​−3 ⋅ d−1; ±130.38 SD, n = 3) Fill the Michaelis-Menten curve by quantifying the apparent AOM rate using the CH3D method when the methane concentration is 1.1 to 129 mM. Based on the sediment rate reaching a Vmax of ∼9,500 nmol ⋅ cm-3 ⋅ d-1, the calculated Km is 5.65 mM (SI Appendix, Figure S6). Within the tested methane concentration range, the rock-based rate did not reach Vmax, indicating that Point Dume's carbonate-related methane oxidation process did not reach saturation under in-situ conditions. As the concentration of methane increases, the ratio of AOM carried by rocks to sediments increases, indicating that the relative contribution of AOM (per unit volume) within the rock may be in deeper waters (such as bays) under all other environmental factors being equal Methane-rich leaks increase Mexico, the Atlantic edge of the United States, the Guaymas Basin, and other similar and deeper discoveries.

The mineral environment of a cell can significantly affect metabolism, from providing nutrients (25) to donating (26) and accepting (27) electrons in catabolic reactions. In this case, X-ray diffraction (XRD) analysis was performed on carbonates and sediments to assess the potential link between AOM rates and bulk mineralogy (SI Appendix, Table S2). Carbonate rocks from the Gulf of Mexico contain a major portion of magnesite calcite, which is consistent with the formation of sulphate-depleted fluid underground and subsequent exposure to the seafloor (28). There are obviously many forms of carbonate in a single Point Dume chimney, and its Chinese stone or magnesia calcite dominates in different samples. The overall mineralogy does not appear to be the primary determinant of the rate of methane oxidation; however, the presence of certain minerals may affect the metabolic relationship. Specifically, among the samples analyzed by XRD, the four samples (PD R1 to 4) exhibiting the highest methane oxidation rate all contained measurable levels of pyrite. The inner part of the sample PD R1 with the highest rate (> 2 mm below the outer shell) is composed of> 80% pyrite. Electron microscopy further revealed the abundance of rhombohedral pyrite and needle-like crystals suggestive of aragonite fan-shaped in the entire chimney. In some cases, it has also been observed that pyrite framboids have striking similarities with aggregates that are strikingly similar to the consortium of Anaerobic Methanotrophic (ANME) Archaea and Sulfate-Reducing Bacteria (SRB) (SI Appendix, Figure S7).

In view of the importance of extracellular electron transfer in AOM metabolism (29, 30), we want to know whether the presence of the iron-sulfur mineral phase can promote the "electronic market", which can transfer reducing equivalents between co-trophic partners, thereby supporting the improvement The AOM rate. The electrical and physical properties of multiple sediment and rock samples were tested to evaluate the effect of electrical conductivity and structural coherence on methane oxidation activity. The conductivity values ​​obtained from current-voltage measurements on sediment and rock samples range from 7.32 × 10−10 Ω−1 (GoM R1) to 3 × 10−9 Ω−1 (GoM PC1 0 to 5) (SI Appendix, Table S3). In addition, for a moderately applied voltage sweep from -100 to 100 mV, currents as high as hundreds of pA are detected. Although no consistent relationship between conductance and AOM has been observed, a comparison with the previously described electron transfer rate per cell interface (15 to 100 fA) (31) shows that in addition to direct cell-cell, electrons flow through sediments and Rock-substrate contact—may be an important link with a nutrient partner. This phenomenon has been observed in many iron-bearing minerals (32). Next, we tried to determine whether particle size affects the AOM rate, possibly through remote electron transfer. The sample PD R3 was divided into four size parts, ranging from ~400 μm to 2 cm, and the apparent velocity was measured over the course of 8 days. No significant relationship between granularity and AOM rate was observed (SI Appendix, Table S4), which means that the structural coherence on the spatial scale tested here is not an important rate determinant.

After investigating a series of abiotic factors, we next checked the abundance, composition and arrangement of the sample microbial community to determine the influence of these factors on the AOM rate. The cell counts of the unincubated samples and the samples after long-term incubation show that the methane oxidation rate is the same as 1) the pre-existing cell abundance (33% of the rate variance in the paired graph), and 2) the cell abundance after incubation (~60%) There is a positive correlation between the rate variance), and 3) the change in cell abundance (~61%; SI appendix, Table S5; all values ​​assume the same level of methane oxidation in each cell).

In order to examine the spatial relationship between microorganisms in the rock environment, we developed a direct fluorescence in situ hybridization (FISH) imaging technique for rock fragments. This “in situ” microscopic analysis of the sample PD R1 exposed dense cell combinations in various environments, including mixed archaea-SRB aggregates, shell-shaped aggregates, and more in the pore space covering the rock surface. Homogeneous community (Figure 3) and SI appendix, Figure S8). The high density of surface-related organisms — and the apparent diversity of cell-cell and cell-mineral spatial associations — is consistent with biological and non-biological feedback that can support increased metabolic activity. Such complex physical scaffolds spanning inner rock habitats of tens or hundreds of microns may retain local redox gradients and promote electron transfer reactions that are not present in the sediments. The solidified rock structure can also promote the flow of powerful fluids through established pipelines, providing methane for microbial components through upward advection, and sulfate through tidal mixing (33) or hydrological replenishment at the bottom of carbonate mounds (4, 34). (It is worth noting that we have observed advection fluid flow through the Point Dume chimney, and the ongoing geochemical analysis aims to further determine the composition of these fluids.) In contrast, sediments may have more distribution channel networks , Has greater tortuosity and lower fluid flow rate and may be easily damaged by biological disturbance (35, 36). In other words, the intralithic communities that accelerate the precipitation of carbonates and metal sulfides seem to be self-burying (37), and the long-term effects of such processes deserve further study.

Confocal microscope image of the complete interior of sample PD R1. (Top) The rock surface. (Bottom) Fluorescence signal from hybridized Arch 915 and DSS 658 FISH probes. A series of cell-cell and cell-rock arrangements were observed, including A) mixed archaea-SRB aggregates, B) "shell-type" aggregates, in which archaea members occupy the outer space, SRB members make up the interior, and C) domains -A specific community arranged in the pore space of the rock.

In order to assess the extent to which the composition of the microbial community explains the observed difference in AOM rates, a 16S ribosomal RNA (rRNA) genetic survey was performed on 17 incubation samples at the end of the long-term metabolic rate experiment. Although the DNA extraction procedure used here does not distinguish between intracellular DNA from intact cells and extracellular DNA from dead cells (38), a comparative study of marine sediments reported that the persistence of extracellular DNA is important for community composition investigations. The impact is negligible. 39, 40), especially in the absence of biological disturbance (as in our hypoxic incubation) (41). Resolve precise sequence variations to observe single nucleotide differences and improve phylogenetic comparisons (42, 43). After evaluating the available computational tools, the Deblur protocol (44) produced amplicon variants with the most similar sequences to the database of the National Center for Biotechnology Information (NCBI) (SI appendix, Figure S9); this method has It has been proven to lead to a decrease in overall diversity, and based on simulated community control, a more realistic representation of community identity (44). There is no obvious correlation between methane oxidation rate and alpha diversity (SI appendix, Figure S10). The carbonate samples from Palos Verdes (PV R1) samples showed the highest degree of diversity among all indicators, while the Point Dume rock showed a higher AOM rate in our incubation, but the diversity was greatly reduced. Similar community diversity streamlines have been observed in carbonate rocks from Hydrate Ridge (14) and percolation sediments in the Gulf of Mexico, which were extracted onto artificial carbon cloth substrates, indicating an increase in volumetric rate (45). Non-metric multi-dimensional scaling analysis uses distance matrices to check the relationship between community composition, these distance matrices are adapted to sparse data sets (abundance weighted Jaccard) and relative abundance (Bray-Curtis), and consider the system between detected organisms Developmental distance (weighted UniFrac) (SI appendix, Figure S11)). Site location and mineralogy are both important factors in the classification of community relationships (P value for permutation multivariate analysis of variance: 0.001 to 0.036; SI appendix, Table S6). Multiple Beta diversity indicators reveal the importance of community structure and methane oxidation rate. Contact (SI appendix, tables S6 and S7).

We next focus on specific high relative abundance pedigrees. Figure 4 compiles the alpha diversity, methane oxidation rate and location data, as well as the relative abundance of 32 precise sequence variants that constitute at least 5% of the readings in at least one sample (see data set S3 for all relative abundances). Among ANME, ANME-2 has the highest content in Guaymas and California coast samples, including high-rate PD R1 and PD R2 samples, while ANME-1 is more common in low-rate samples, especially in the Gulf of Mexico site. Sequences in some lineages that are usually not related to methane or sulfur metabolism have also been detected with relatively high abundance. The 5 representatives of the Atribacteria candidate phylum belong to 32 high abundance taxa, and members of the Anaerolinaceae family (in the Chloroflexi phylum) are accounted for for community analysis (PD R1, PD R2 and GBN R3).

A heat map of the relative abundance of 32 16S rRNA gene exact sequence variants (ESVs) that account for at least 5% of the relative abundance in at least one sample. Each row represents a different ESV, and the columns correspond to 22 rock or sediment samples (all marked at the bottom of the figure). The classification and grouping of 32 ESVs and their closest results through the basic partial comparison search tool (or BLAST) are displayed on the left, and the ESV label is on the right, colored by the presumed metabolic category. The bars above the heat map represent Faith's phylogenetic diversity index (a measure of alpha diversity) and AOM rate (on the log10 scale).

Our testing of the ubiquitous in-rock AOM potential shows that methane consumption carried by carbonate rocks is an understudied component of the methane cycle. This phenomenon has been observed in all the locations we sampled-across four geological environments and seven geochemically different locations-and may be ubiquitous in the methane seepage in the ocean, which exhibits autogenous carbon. Salt deposits. The analysis of kinetic parameters, mineral composition, electrical properties, cell abundance, microbial diversity, and the existence of specific lineages pointed out a variety of factors. Together, these factors help explain the range of measurement rates and explain in laboratory-based Significant activity was observed during the incubation of Point Dume Carbonate. The cell count shows that the change in biomass and final cell abundance has a stronger positive correlation with the final long-term rate than the pre-existing biomass. These data indicate that environmental conditions such as in-situ methane concentration play a role in stimulating the AOM activity of the sample, but the inherent characteristics of the sample (such as mineralogy or microbial community structure) are more influential.

The significant link between pyrite and high interest rates is a particularly compelling avenue for further research. Framboidal pyrite formation can be accelerated by sulfate reduction in the presence of active iron minerals (46), and is also prominent in the Black Sea coral reef (47), which may be the closest known to the point dum (24) . In order to further study the prevalence of pyrite in carbonates exhibiting high AOM rates, we calculated all samples (data set S4). We hypothesize that more sulfate reducing agent and/or less sulfide oxidizer can cause sulfide to accumulate and eventually precipitate as pyrite, but no difference between the relative abundance of the target lineage and the abundance of pyrite is observed. Significant relationship. The currents in all samples—up to hundreds of picoamperes compared to previous cell interface measurements in the femtoampere range (31)—show that the electrical properties of the physical substrate may play a role in the methane oxidation activity. In fact, a similar phenomenon was observed in previous work when the seepage sediment community was transferred to the conductive carbon cloth and exhibited an increased AOM rate (45).

The existence of specific lineages directly or indirectly related to AOM may also play an important role in increasing the rate of methane oxidation. ANME-2 is more common in high-rate carbonates. It has a large amount of heme cytochromes and surface proteins, which can enable them to unload their reducing power through direct electron transfer between consortium partners (29). On the other hand, the relative abundance of ANME-1 is found to be higher in low-rate samples, and these specific genotypes may lack the physiological ability of high-throughput extracellular electron transfer (59, 60). In the Black Sea carbonate reef, the area dominated by ANME-2 shows a lower δ13C value than the area dominated by ANME-1, indicating that ANME-2 accelerates the rate of methane oxidation and assimilation (61). It is believed that Atribacteria and Anaerolinaceae do not participate in the core methane oxidation or sulfate reduction metabolism, but their popularity suggests that they may play an important supporting role. Atribacteria has been detected preferentially in marine methane leaks (62, 63), and may enter the seepage habitat from below through upwardly migrating fluids, such as the Gulf of Mexico leak (64) and the mud volcanoes in the Ryukyu Trench (63). As proved. Genomic analysis has shown that they undergo fermentation metabolism to produce acetate, CO2 and H2-potential substrates for methanogens and/or SRB (65, 66). Anaerobic bacteria are usually characterized by heterotrophic organisms; in a seepage environment, they are assumed to consume primary producer ANME biomass (67), but they may be more directly involved in hydrocarbon metabolism, such as alkane degradation and enrichment culture ( 68, 69) and percolation in the Gulf of Mexico (70).

Other lineage-specific attributes that can speed up the rate and explain the higher Vmax observed in Point Dume Carbonate include a) increased reactant uptake and product release rate by any of the same trophic partners, and b) differences in enzymes that perform rate-limiting reactions Protein type (methyl-Coenzyme M reductase, dissimilatory sulfite reductase), c) a higher number of rate-limiting enzymes per cell, and/or d) different lineage-specific partnerships. Clarifying the role of these factors will require more detailed biochemical, genomic and proteomic studies, which may contribute to the increasing understanding of the diversity of methyl-Coenzyme M reductase (71⇓ -73).

Existing estimates of the degree of methane oxidation in the global marine environment (1, 2, 74) do not distinguish between the methanotrophs of sediments and carbonate hosts, although the abundance and often dominance of carbonate rocks in methane exudates Status (4⇓ ⇓ –7, 75, 76). When assessing the impact of Neishi AOM on the global methane cycle, several important factors need to be considered, including the local concentration of metabolic reactants and products found in and around carbonates, and the total amount of carbonates in the leak. Some of the key parameters are currently not well constrained. In addition, our experimental incubation was conducted under high methane and sulfate-rich conditions. These conditions do not represent all leakage environments. For this reason, the absolute rate obtained by our incubation reflects the methane oxidation potential of the sample, which may exceed its in-situ methane oxidation contribution. Nonetheless, by maintaining standardized experimental parameters for carbonates and sediments during our incubation, and converting previously published results to equivalent conditions, our comparison of potential AOM rates based on substrate and cross-over studies showed that, Carbonate-borne AOM may be an important type of methane sinking in the marine environment.

Carbonate rocks account for a large part of the seafloor, and at many leaks (4⇓ –6, 8, 9, 77), they account for most of the methane injection volume. Although diffusion limitations may regulate the maximum reaction rate in some carbonate buildings, many authigenic carbonates at the leak show high porosity (4, 28, 78) and are associated with nearby sediments (15, 33). ) The same permeability value. Therefore, the reactant transport in these two environmental systems may be relatively similar, and may even be less restricted in some carbonates. Not all leaks exhibit such a common carbonate structure, because cation availability may limit carbonate precipitation, and it is expected that only a portion of the rock volume will experience the sulfate concentration in seawater. However, nitrogen and metal reduction (79, 80) and low sulfate AOM (81), as well as tidal forcing (33) or hydrological replenishment (4, 34) caused by carbonate mound sulfate infiltration may expand the AOM habitat in the rock Go deep into underground rock habitats.

When assessing the potential range of the AOM within the stone, the last consideration is the increase in the average velocity in the rock compared to the sediment. The scale factor of rock load to sediment load comes from the short-term rate compiled in this study (Table 1). At the locations where the in-rock and sediment-based AOM is observed, the specific rate value of the substrate is averaged and the ratio of the AOM carried by the rock to the AOM carried by the sediment is determined. These ratios for the Gulf of Mexico sample were 0.88, the ratio for the northern Guaymas Basin sample was 8.85, and the Point Dume sample ratio was 3.47, indicating a large difference, but on average, under the same experimental conditions, each unit of volume and carbon The ratios related to acid salts are higher than those related to sediments.

The data provided here shows that carbonate samples from all leak points inspected so far span a range of geological environments and have a large amount of anaerobic methane oxidation potential. In addition, some of the inner stone communities evaluated in laboratory-based incubation showed the highest AOM rates ever, indicating that the physicochemical aspects of the carbonate host habitat contributed to the increase in methane consumption. Although the full extent to which intra-rock AOM affects the global methane cycle remains to be determined, our results indicate that the intra-rock environment may be an important contributor to the biogeochemical assessment of methane. Considering the methanotrophic community in the carbonate host environment has an impact on mitigating potential methane hydrate decomposition (82) and ocean acidification (83, 84). A more detailed understanding of the structural and mineralogical properties that increase the rate of AOM carried by carbonates can also help rationally design methane scrubbing systems for greenhouse gas remediation or distributed biofuel production (85).

It is generally believed that the ANME microbial community plays an important role in the consumption of methane in the marine environment, but laboratory analysis and global estimates lack the contribution of rock habitats to a large extent. After conducting a continental-scale assessment of a series of geological environments, we showed that AOM within the rock is a common phenomenon, and that the methane consumption rate of the microbial community in the rock usually exceeds the methane consumption rate associated with sediments. At the newly characterized Point Dume percolation site on the coast of Southern California, we report chimney-like carbonate structures that oxidize methane at the highest rate ever measured in laboratory-based incubations. We identified several factors, including cell abundance, mineral composition, kinetic parameters, and the presence of specific microbial lineages, which may play a key role in supporting the elevated AOM rate of endoliths. We expect that future research will better describe how these and other aspects of the system contribute to the observed rate, and will clarify the contribution of carbonate-borne AOM to the ocean methane budget. Given its frequent occurrence and increased methane oxidation potential, the carbonate rocks at the methane leak may constitute a major ocean methane sink.

During the R/V (research ship) Atlantis voyage 26-12-scientifically verified cruise from the Gulf of Mexico, the Atlantic edge of the United States during the Atlantis voyage 36, and during the Atlantis voyage 37-06 During the Guaymas Basin and California coast, samples were collected during E/V (exploration vessel) Nautilus cruises 073 and 084 and R/V Falkor segment 163 019. More information about the geological environment and detailed information on sample collection can be found in the SI appendix. After being recovered from the seabed, the push core and carbonate submerged in the bottom water are immediately transferred to a 4°C cold storage room and processed within a few hours. The push core is cut into predetermined layers and stored in a sterile Whirl-Pak bag at 4°C, and placed in an oxygen-deficient, argon flushed, airtight polyester film bag (IMPAK Corporation) until use. The carbonate rocks are washed to remove any attached sediments, to remove the fauna, and broken into smaller pieces when needed with a hammer and chisel cleaned with ethanol. Place the rock block in a polyester film bag and immerse it in the co-located bottom water; then purge the bag with Ar gas (5 minutes per 100 mL water volume), seal and store it at 4°C.

In the laboratory, the sediment and carbonate samples were transferred to new sterile bottles and polyester film bags, respectively, and immersed in the bottom water from the collection point. The bottom water had passed through a 0.22-μm Durapore filter (EMD Millipore) , Pass N2 gas, and stay in anoxic chamber overnight. The samples are stored at 4 °C and protected from light. Two weeks before the rate experiment was set up, the sample was bubbled with CH4 (5 minutes per 100 mL water volume); this “pre-incubation” was performed to minimize the start-up effect and lag time in the metabolic rate measurement experiment. These and all subsequent sample processing steps are performed in a vinyl anoxic chamber (Coy Laboratory Products).

Perform short-term incubation with 14CH4 radioactive tracer, as described in detail in the reference. 21. Set up headspace-free culture in a sterile SVG-50 glass vial (Nichiden-Rika Glass Co. Ltd) containing 10 mL of sediment or carbonate and 50 mL of 0.22 μm filtered hypoxic seawater and pre-blown with CH4 . The gas chromatograph verification using the CH4:N2 dilution series and the concentration based on Henry's law (combined with temperature and salinity correction) showed that the initial methane concentration was 1.35 mM. Inject radiolabeled methane into each vial (14CH4 dissolved in seawater, specific activity of 1.89 GBq/mmol, activity per incubation of 12 kBq), and the vials were kept in the dark at 4 °C during the incubation. The material is then quickly transferred to a sterile 250 ml stoppered bottle, which is pre-filled with 7.5 ml of 30% (weight/weight) NaOH to prevent microbial activity. The headspace of the flask was purged through a 850 °C quartz tube filled with copper oxide at a rate of 30 mL/min for 30 minutes to burn unreacted 14CH4 into 14CO2. The burning gas passes through two consecutively scintillating vials, which are pre-filled with 1 mL of phenethylamine and 7 mL of 2-methoxyethanol, to which 10 mL of scintillation mixture (Ultima Gold, PerkinElmer) is added. In order to measure the 14C-labeled inorganic carbon made during the incubation period, a pre-filled scintillation vial (1 mL 2.5% NaOH and 1 mL phenethylamine) was hung on the stopper in the bottle, and a drop of antifoaming agent and 5 mL 6 M HCl was added to a sealed container, and the bottle was placed on a shaker at room temperature for 16 hours. Then a total of 5 mL of scintillation mixture was added. This method has been shown to recover an average of 98% of 14CO2 (21). After waiting for 24 hours, use a Beckman Coulter LS 6500 scintillation counter to measure the scintillation vials for 10 minutes per vial. The methane oxidation rate is determined by the following formula: methane oxidation = CO214•CH4(CH414 CO214)•v•t.

14CH4 represents the unreacted radiolabeled methane after combustion, 14CO2 represents the amount of acidified oxidation products, CH4 is the initial amount of methane in the experiment, v is the volume of sediment or carbonate rock, and t is the incubation time. The scintillation vial measurement and calculation are performed in a double-blind manner.

This method of methane oxidation rate measurement has key scientific and procedural advantages: 1) it is non-destructive, allowing true replication and time series measurement of heterogeneous samples such as seepage sediments and carbonates, and 2) it is more Safety and less logistical burden Compared with radioisotope work, each measurement requires much less hands-on and total time. The settings of the short-term CH3D rate experiment and the carbonate fragment size test are as above, but there are two differences: methane injection is done with 75% CH4 and 25% CH3D, and 14CH4 tracer is not added. For fragment size incubation, use an autoclaved mortar and pestle to homogenize the rock, and use a digital caliper to determine 20 fragments of sample A (2.0 to 2.5 cm) and B (0.5 to 0.7 cm) along the longest axis Size) and measure the samples C (~2,000 μm) and D (~400 μm) under an optical microscope. A negative control for autoclaved 2.0 to 2.5 cm fragments is also included. At the end of all short-term CH3D incubations, unless otherwise specified below, the water is sampled and analyzed as detailed in (23) above. In short, use a sterile syringe to collect 1 mL of incubation solution in the hypoxic chamber through a stopper, and push through a 0.22-μm filter into a 250-μL glass insert in a 1-mL gas chromatography vial. Use the T-LWIA-45-EP liquid water isotope analyzer (Los Gatos Research) to measure the water-containing D/H ratio of each sample. The analyzer uses an off-axis integrating cavity output spectrometer to measure high-precision D/H and 18O /16O ratios (86). Each sample is subjected to four rounds of 10 injections, but only the data of the last five injections are used in the analysis to avoid memory effects. Including 5 working standards with known isotope ratios: 2C (-123.7‰), 3C (-97.3‰), 4C (-51.6‰), ER2 (191.4‰) and ER3 (383.3‰); every 40 to 60 times Re-measure the standard sample to minimize the influence of instrument drift. If the instrument temperature or pressure sign appears (2.1% of all measured values, corresponding to a temperature change in the measuring cell exceeding 0.3 °C per hour or a pressure increase during analysis), exclude the data and determine the D/H ratio from the remaining measurements middle. Standardize the D/H ratio to the Vienna standard average ocean water scale using water standards and linear interpolation/extrapolation. Using this standardized ratio, the number of activated methane molecules is determined (the first step of methane oxidation allows DH to be exchanged with water, but not necessarily completely oxidized to CO2). Using the 14C-based rate from the parallel experiment, the scale factor connecting the two methods is calculated and applied to the remaining CH3D value, which is called the "apparent" AOM rate (SI Appendix, Table S1). Due to sample limitations, it is not possible to calculate sample-specific scale factors. Errors related to D/H: 14C scale factor (SI appendix, Table S1) and CH3D rate values ​​are calculated by adding orthogonal uncertainty and applying the resulting error ("Table S1"). View "rate error" below) to AOM calculation "apparent rate": ApparentrateerrorApparentrate=(CH3DrateerrorCH3Drate)2 (ScalingfactorerrorScalingfactor)2

The long-term rate experiment was prepared in a 0.35-L wide-filled bottle with stopper (VWR International). In the anoxic chamber, add 10 mL of sediment or rock, and then fill the bottle with co-located 0.22-μm filtered anoxic bottom water. Residual methane is removed by a N2 jet, and gas headspace (160 mL CH3D and 80 mL N2) is added, and an equal volume of liquid is discharged through a second needle to create a headspace with a known partial pressure. The dissolved methane concentration at the beginning of these experiments was calculated according to Henry's law and confirmed to be 1.1 mM by gas chromatography measurement (SI appendix). The container was then placed upside down in the dark at 4 °C until the sample was taken for water isotope analysis as described above.

A customized 4-L titanium pressure vessel is used to 1) determine the apparent rate of methane oxidation for several samples under methane saturation conditions and 2) determine Point Dume sediments (PD PC20 to 5) and carbonates (PD PC20) To 5) rate and concentration curve PD R3) sample to evaluate the reaction kinetics. In the hypoxic chamber, put 10 mL of sediment or rock and 100 mL of co-located and filtered bottom seawater into a polyester film bag and seal it. Outdoors, open a small hole in the bag, and nitrogen gas flows through the hole at a rate of 50 mL/min for 5 minutes. Then remove all headspace by squeezing the bag until a drop of water appears; then use a pre-filled syringe to inject 100 mL (at 1 atmosphere) of the appropriate gas mixture (SI Appendix, Table S8), quickly seal the bag and place it in Temperature controlled environmental chamber (5° C). The 7.58 MPa target pressure (simulated 745 m water depth) was obtained using a high-performance liquid chromatography pump (P-1536, Chrom Tech, Inc.) and adjusted with a stainless steel back pressure valve (StraVal Valve). Experiment under pressure for 8 hours. At the designated end point, the polyester film bag was taken out and moved to the hypoxic chamber; the water was collected through the bag with a sterile syringe for D/H analysis and measured as described above.

For all 14CH4 and CH3D rate measurements, the equipment and related supplies are sterilized by an autoclave before use, and the value of the corresponding autoclave sterilization control sample is subtracted. Unless otherwise stated (data set S1), all rate-based experiments were performed in triplicate.

At the end of the long-term incubation experiment, a second sampling of the XRD material is taken from the rate measurement incubation. The inner part of the rock (defined as at least 3 mm from the outer and inner surfaces) is recovered with a sterile razor blade. The sample was air-dried, homogenized with a sterile mortar and pestle, and run as a packaged powder. All samples were run on Panalytical X'Pert3 powder XRD, using a Cu Kα source, voltages of 40 kV and 45 mA, and scanning from 5 to 70° 2θ. The final scan is an average of 3 scans-each with 0, -1, and 1° swing to confirm that there is no preferential sample orientation. HighScore Plus is used to fit and identify peaks (using Rietveld refinement method), and International Diffraction Data Center 2014 is used for sample identification. The relative quantification of the phases is given in weight percent. The mineralogy determined by XRD is limited using elemental results obtained from Scanning Electron Microscopy (SEM)/Energy Dispersive X-ray Spectroscopy using Tescan VP-SEM in high vacuum mode with backscatter detector at 20 kV conduct.

The pre-cultured sub-samples of rock PD R1 were continuously dehydrated with 50, 80 and 100% ethanol solutions (balanced deionized [DI] H2O). The internal debris was obtained with a sterile chisel and mounted on an aluminum short tube using double-sided carbon tape. The samples were then sputter-coated with 10 nm Pt:Pd (80:20) (Q300T D sputtering system, Quorum Technologies) and imaged using the Zeiss Supra 55VP field emission electron microscope operating at the Harvard Nanosystems Center. The Everhart-Thornley secondary electron detector was used to obtain the secondary electron image at a voltage of 15 kV. A silicon drift detector (EDAX) was used for elemental analysis at 15 kV, and the data was processed with Genesis software.

The Agilent 4156C precision semiconductor parameter analyzer was used to perform dual-probe current-voltage (IV) measurement on the Signatone 1160 probe station for fine positioning. For each IV measurement, the probes are about 40 μm apart on the sample. During placement and all measurements, the SMZ-168 stereo microscope was used to monitor the probe position. For IV measurements, the current response is measured in 20 mV steps during the -100 to 100 mV (and reverse) sweep. Before measuring the current, each voltage step is maintained for 65 seconds to eliminate the influence of the capacitive current. The following Agilent 4156C settings were selected to improve current sensitivity: 1 nA consistency, autoranging, and long integration time (16 power line cycles). Ohm's law can be used to take the conductance of each sample as the slope of a linear regression line through the IV data points of the sample, where conductance is the reciprocal of resistance.

The cell count was performed as previously described (87), with slight modifications. Representative rock and sediment samples were fixed in 2% paraformaldehyde at room temperature for 1 hour, then rinsed with ddH2O and dried, and then homogenized with a sterile mortar and pestle. Sonication, Percoll density gradient separation, filtration, and DAPI staining were previously described (87). The cumulative volume of cell aggregates per unit volume of the sample is determined by counting 30 continuous fields of view using a 60-fold objective lens (Zeiss) under an LSM 880 upright confocal microscope. This volume is divided by the volume of a typical cell (1 micron in diameter) and multiplied by the largest possible spherical packing density [0.7405 (88)]. (Therefore, the cell abundance in the aggregates is the largest potential value; no significant difference in the packing density of the aggregates is observed, and the consistent analysis and calculation workflow ensures that the relative relationship is reliable.) Finally, on the filter The observed abundance of individual cells is additive.

In order to prepare for in situ microscopic imaging of the intact microbial community, FISH was performed directly on a small piece of rock inside PD R1 using the previously described buffer formula (3). Probe Arch-915 [5'-GTG CTC CCC CGC CAA TTC CT-3' (89), 5'conjugated cyanine 3 dye] and DSS-658 [5'-TCC ACT TCC CTC TCC CAT-3' ( 90), the final concentration of 5'conjugated 6-FAM dye] is 5 ng/μL (Biomers). Use a 35% formamide concentration in both the hybridization and wash buffers. The hybridization incubation is 12 hours at 46°C, and the washing incubation is incubated in pre-warmed wash buffer at 48°C for 15 minutes. Then rinse the sample with deionized water and allow it to air dry. Microscopy analysis was performed with a water immersion microscope and LSM 880 upright confocal microscope using a 20x objective lens (Zeiss). Using lasers with wavelengths of 488 and 561 nm, the reflection channel recorded 80% of the 488 nm laser reflection to show the characteristics of the rock surface. The control experiment allowed PD R1 rock fragments to accept the complete FISH protocol, but with the meaningless 338 probe (91) or no probe; in both cases, the observed signal was negligible (SI appendix, figure) S8).

High-throughput sequencing was performed on the V4 and V5 regions of the 16S rRNA gene to compare the diversity and composition of archaeal and bacterial communities from 17 sediment and rock samples (listed in data set S1). Use PowerSoil DNA Separation Kit (MoBio) to extract DNA from 0.5 g (wet weight) sample material, and use oligonucleotide primers 515yF (5'-GTGYCAGCMGCCGCGGTAA-3') and 806bR (5'-GGACTACNVGGGTWTCTAAT-3') Amplification target area), which contains the Illumina flow cell adapter sequence (92) and necessary barcodes. Use USEARCH v7.0.1090 (93) to check the chimera of the combined quality trimming readings, and to be 97% identical to UCLUST [v1.2.22q (93)] in the Quantitative Insights Into Microbial Ecology platform QIIMEp v1.9.1 (94) Sexual clustering)]. Select the most abundant sequence in each cluster as the representative sequence, and then use assign_taxonomy.py and the chimeric screening database named SILVA v128 SSURef to assign taxonomy in QIIME. The SI appendix provides detailed information on single nucleotide analysis methods, diversity analysis, and phylogenetic allocation. The sample metadata and SSU rRNA sequence files used in this study have been submitted to the NCBI BioSample and Sequence Read Archive databases and can be accessed through the BioProject identifier PRJNA648152.

The DNA sequence data has been deposited in NCBI (PRJNA648152). All other research data is included in the article and/or supporting information.

We thank Jenny Delaney, Dr. Aude Picard, Stephanie Connon, Stephanie Hillsgrove, Dr. Douglas Richardson, and Dr. Nicole Raineault for their experimental and logistical assistance in collecting the samples and data provided here. We would also like to thank the captain and captain, crew and scientific party members on the R/V Atlantis on the voyage AT 26-12-SVC (using the deep submersible vehicle Alvin), AT 36 (using the deep submersible vehicle Alvin and autonomous underwater vehicle sentinel ) And AT 37-06 (with DSV Alvin) and E/V Nautilus on the flight segments NA-073 and NA-084 (with the remote control vehicle Hercules). We thank the Schmidt Institute of Oceanography for supporting the expedition FK181005, the crew of R/V Falkor and the pilot of ROV SUBastian. We are grateful to the Ocean Exploration Trust Fund for their support of the preliminary investigation of the Point Dume research site. Some of the analyses presented here were performed at the Harvard Nanosystems Center, which is a member of the National Nanotechnology Coordination Infrastructure Network, which is supported by the NSF under the NSF Electrical, Communication, and Network Systems Award 1541959. We thank the Harvard Bioimaging Center for infrastructure and support. This work was supported by NSF under grants PRG NSF-1542506 and NSF OCE-1635365. Any opinions, findings, conclusions, or recommendations expressed in this material are those of non-U.S. Geological Survey (USGS) authors. Suggestions, and do not necessarily reflect the views of NSF. This journal article has been peer reviewed and approved for publication, in line with USGS basic science practice (https://pubs.usgs.gov/circ/1367/). Any use of trade, company or product names is for descriptive purposes only and does not imply endorsement by the U.S. government. This work has also been supported by NASA, through the simulation research program through the planetary science and technology project to grant NNX17AB31G funding to PRG.

↵2 Current address: Department of Biology, Boston University, Boston, Massachusetts, 02215.

↵3 Current address: Department of Earth Sciences, Boise State University, Boise, ID 83706.

Author contributions: JJM and PRG design research; JJM and DH conducted research; DH, SPJ, LMR, AG, MSC, MYE-N. and NT contributed new reagents/analysis tools; JJM, SPJ, LMR, AG, MSC , MYE-N., VJO and PRG analyzed the data; JJM and PRG wrote this paper, and received revisions and feedback from all authors.

The author declares no competing interests.

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