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The ISME Journal
https://doi.org/10.1038/s41396-018-0263-1
ARTICLE
In situ development of a methanotrophic microbiome in deep-sea
sediments
S. E. Ruff1,4 ●J. Felden 1,2 ●H. R. Gruber-Vodicka1●Y. Marcon 2,3 ●K. Knittel1●A. Ramette1,5 ●A. Boetius1,2,3
Received: 13 February 2018 / Revised: 6 July 2018 / Accepted: 4 August 2018
© The Author(s) 2018. This article is published with open access
Abstract
Emission of the greenhouse gas methane from the seabed is globally controlled by marine aerobic and anaerobic
methanotrophs gaining energy via methane oxidation. However, the processes involved in the assembly and dynamics of
methanotrophic populations in complex natural microbial communities remain unclear. Here we investigated the
development of a methanotrophic microbiome following subsurface mud eruptions at Håkon Mosby mud volcano (1250 m
water depth). Freshly erupted muds hosted deep-subsurface communities that were dominated by Bathyarchaeota,
Atribacteria and Chloroflexi. Methanotrophy was initially limited to a thin surface layer of Methylococcales populations
consuming methane aerobically. With increasing distance to the eruptive center, anaerobic methanotrophic archaea, sulfate-
reducing Desulfobacterales and thiotrophic Beggiatoaceae developed, and their respective metabolic capabilities dominated
the biogeochemical functions of the community. Microbial richness, evenness, and cell numbers of the entire microbial
community increased up to tenfold within a few years downstream of the mud flow from the eruptive center. The increasing
diversity was accompanied by an up to fourfold increase in sequence abundance of relevant metabolic genes of the anaerobic
methanotrophic and thiotrophic guilds. The communities fundamentally changed in their structure and functions as reflected
in the metagenome turnover with distance from the eruptive center, and this was reflected in the biogeochemical zonation
across the mud volcano caldera. The observed functional succession provides a framework for the response time and
recovery of complex methanotrophic communities after disturbances of the deep-sea bed.
Introduction
The ocean seabed is the largest methane reservoir on Earth,
comprising this climate-relevant gas in the form of semi-
stable methane hydrates, as gas bubbles or dissolved in
porewater. Globally, most of the methane rising from dee-
per subsurface layers is oxidized by methanotrophic
microbial communities before it can reach the hydrosphere
[1]. The methanotrophic communities in the seabed are
diverse, but dominated by relatively few globally dis-
tributed types [2]. The thin oxic surface layer of methane-
rich sediments is often inhabited by aerobic methanotrophic
bacteria of the Methylococcales [2–5]. Anoxic subsurface
layers, where methane and sulfate overlap, are inhabited by
consortia of anaerobic methanotrophic archaea (ANME)
and their partner bacteria of the sulfate-reducing Desulfo-
bacterales [6–9]. These methanotrophic communities, also
referred to as the microbial methane filter, remove >90% of
the methane in undisturbed continental margin sediments
[1]. Methanotrophs also play an important role in methane
removal at shallow [10,11] and deep-sea gas-emitting seep
*S. E. Ruff
emil.ruff@ucalgary.ca
*A. Boetius
antje.boetius@awi.de
1Max Planck Institute for Marine Microbiology, Bremen, Germany
2MARUM Center for Marine Environmental Sciences, University
of Bremen, Bremen, Germany
3Alfred Wegener Institute, Helmholtz Center for Polar and Marine
Research, Bremerhaven, Germany
4Present address: Department of Geoscience, University of Calgary,
Calgary, AB, Canada
5Present address: Institute for Infectious Diseases, University of
Bern, Bern, Switzerland
Electronic supplementary material The online version of this article
(https://doi.org/10.1038/s41396-018-0263-1) contains supplementary
material, which is available to authorized users.
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habitats [12,13]. Hence, only a small fraction of the seabed
methane escapes from these sediments to the hydrosphere
and atmosphere. However, the microbial methane filter at
geologically highly dynamic seeps such as mud volcanoes
has a lower efficiency, removing only 10−30% of the rising
methane [14,15]. Understanding the causes for these dif-
ferent efficiencies, as well as the time scales needed for the
establishment of an efficient methane filter, is crucial in
order to assess the consequences of natural and man-made
seafloor disturbances, such as rapidly dissociating hydrates
[16,17], mud slides, eruptive mud volcanoes [14] or large
oil spills [18–20].
Here we study the development of a deep-sea micro-
biome disturbed by seafloor mixing due to gas eruptions
and mud slides at the actively gas-emitting Håkon Mosby
Mud Volcano (HMMV) on the Norwegian continental
slope. Marine mud volcanoes are seabed structures formed
by upward migration of subsurface gasses together with
fluids and sediments, from hundreds of meters to several
kilometers depth by buoyancy and gravitational forces [21].
They are an important source of the greenhouse gas
methane, globally emitting an estimated 27 Tg per year
[22]. It has been speculated that the reduced efficiency of
the microbial methane filter at mud volcanoes could be due
to the low availability of electron acceptors, since the
sediments are purged with anoxic subsurface fluids rising
with the gas [14,23]. Other factors may be fluctuating
temperatures, or frequent disturbances by mud mixing,
which affect the growth of methanotrophs [24]. To inves-
tigate this further we compared the biogeochemistry and
microbial community composition between recently dis-
turbed, partially recovered, and undisturbed seafloor, using
time-series observations and sampling of the Håkon Mosby in
the framework of the deep-sea observatory “LOOME—Long
term observations of mud volcano eruptions”(2003−2010).
The hypotheses tested were (1) that the subsurface microbial
signature of freshly erupted muds disappears with exposure to
deep oxygenated seawater, (2) that freshly erupted muds lack
complex methanotrophic communities and hence may have
a low capacity to remove methane, and (3) that it needs
years to develop complex cold-seep communities due to the
slow generation times and cold temperatures.
Results and discussion
We investigated the seabed microbial community in mud
flows of the HMMV (72°N, 14°44′E, 1250 m water depth)
during research campaigns in August 2009 and September
2010. In this period, the long-term geophysical recordings
of the LOOME observatory (Fig. 1, S1; [25]) measured
three major and 12 minor eruptions that occurred every
3−4 weeks. From this eruption pattern, detected by our
deployed instruments and visual observations, we were able
to infer an average mud flow velocity of 0.4 m day−1across
the HMMV center [25]. The mud velocity was used to
convert sample distance to the eruptive central conduit into
time. This space-for-time substitution approach used in
ecological analyses of disturbances [26] allowed us to infer
the spatiotemporal development of the methanotrophic
microbiome. After visual seafloor inspection by ROV Quest
and AUV Sentry, and biogeochemical sampling, we cate-
gorized the center muds into four zones (Figs. 1and 2, S1;
[27]). Zone 1 covered an area of about 50 × 90 m at the
HMMV center. It consisted of fresh subsurface muds that
were deposited during several gas eruptions recorded in
2009−2010 (Fig. 1c, Fig. S2; [25]). Zone 2 consisted of
older subsurface mud flows southeast of the active center.
The muds had a smooth, slightly rippled surface and were
exposed to seafloor conditions for 1−2 years according to
the morphology of the seabed and the measured flow
velocity of the muds. Zone 3 were muds > 200 m away from
the eruptive center, with thin thiotrophic mats, exposed to
cold bottom waters already for 2−5 years. As a fourth zone
we sampled the hummocky rim around the active center of
HMMV. These sediments are stabilized by layers of hydrate
at a few meters sediment depth [28]. They are not physically
mixed by the center eruptions, as evident by comparative
high-resolution mapping of the structure in 1996 [29,30],
and by the dense coverage of long-lived siboglinid tube-
worms (Fig. S2F), which were absent in zones 1–3.
Biogeochemistry and microbial methanotrophic
rates change with time and distance from the
eruptive center
The fresh warm subsurface muds exposed during eruptions
were saturated with methane as indicated by spontaneous
in situ degassing, and had high concentrations of dissolved
inorganic carbon (DIC), alkalinity and ammonium, indica-
tive of a deep-subsurface origin of the pore fluid (Table 2,
Fig. 2b, c). The fluids originate from a depth of up to 3 km
below the seafloor, where the central conduit of HMMV is
rooted [28,31]. The methane carbon isotopic signature of
the dissolved gas in the warm sediments is similar to that of
the surrounding gas hydrates with around δ13C=−60‰
(PDB), indicating a mixed thermogenic/biogenic origin in
the deep subsurface [32]. Due to holes and cracks from
degassing of the center muds (Fig. S2A), sulfate-containing
bottom water percolated 5−10 cm into the seafloor. In the
exposed surface muds 9 months after the main eruption, we
measured methane oxidation (MOx—total aerobic and
anaerobic methane oxidation) rates of up to 80 nmol ml−1
day−1. These are low rates for seep ecosystems [6], espe-
cially when considering the high availability of methane
and oxygen at the surface, or methane and sulfate in
S. E. Ruff et al.
HMMV subsurface sediments. Sulfate reduction (SR) was
not detectable, and the concave shape of the sulfate gradient
(Fig. 2b) is explained by the downward diffusion of sulfate
against an upward flux of subsurface fluids [33]. In zone 2,
which still showed ripples from the mud eruptions (Fig.
S2D), MOx rates were higher than in zone 1, peaking at
100 nmol ml−1day−1at the surface (Fig. 2c); SR rates
peaked in the top few centimeters, but still no free sulfide
Fig. 1 Bathymetry and seafloor imaging of Håkon Mosby mud vol-
cano (HMMV). Samples originated from four zones, which differed in
biogeochemistry and distance to the active center, i.e. time since the
last eruption (a). Samples 1−10 and 16 are from surface muds (top 0
−10 cm), samples 11−15 are from >2 m depth (b). Image of the
sediment surface close to the center of HMMV. Freshly erupted muds
flowing across consolidated muds that are covered with white mats of
sulfur-oxidizing bacteria (c)
In situ development of a methanotrophic microbiome in deep-sea sediments
was detected in the porewaters. Zone 3 is characterized by
mats of sulfide-oxidizing bacteria (Figs. S1B, C, S2D, E).
Here, the sulfate profile showed substantial consumption in
the upper centimeters, and sulfide concentration reached
almost 6 mmol l−1(Fig. 2d). Integrated SR rates of zone
3 sediments measured during six expeditions between 2001
and 2010 (Table 2) consistently showed the high rates that
are typical for a well-established community of anaerobic
methanotrophs (18 ± 4 mmol m−2d−1; mean ± S.E.; n=18;
Table 2;[34]). These rates are around 60-fold higher than
average sulfate reduction rates of nonseep impacted shelf
sediments [35]. Sulfide production peaked in surface sedi-
ments of zone 3 (1.19 ± 0.15 mmol l−l;n=110), whereas
sulfide concentrations were low in zones 1 and 2 (Table 2)
confirming that AOM was not established in fresh sedi-
ments. Porewater analyses as well as methane oxidation and
sulfate reduction rate measurements performed on these six
expeditions support the lateral zonation across the caldera.
This zonation is in accordance with the geophysical model,
in which centrally rising mud and gas are laterally trans-
ported and eventually sink in upon degassing [25]. Our
biogeochemical results strongly suggest that over the period
of at least one decade AOM continuously established in
muds of the same distance to the eruptive center—i.e. muds
of a similar age—despite a continuous mud flow.
Subsurface communities get transported to surface
sediments due to mud volcanism
We analyzed archived subsurface samples from the pre-
study phase in 2003 and additionally assessed the microbial
community composition of ten surface (S) and five
Fig. 2 Biogeochemistry of
surface sediments of HMMV
and of a reference site outside of
the mud volcano. In the
reference sediment (a) outside of
the HMMV caldera around 500
m upslope of the mud volcano,
dissolved inorganic carbon
(DIC), sulfate and alkalinity
showed typical background
concentrations, ammonium
(NH4) and sulfide (H2S) were
not detected, and there was no
measurable methane oxidation
(MOx) or sulfate reduction (SR).
Sediments at the center of
HMMV (b) show an upward
transport of sulfate-depleted
subsurface fluids enriched in
DIC and NH4and show low
MOx rates. SR is first detectable
in sediments of zone 2 (c) and
H2S production is first detectable
in aged sediments of zone 3 (d).
Note: MUC827 is a parallel core
of Sample 9 (MUC823)
originating from the same dive
and same area. All profiles were
measured on the same
expedition in 2010. For details
as well as pore-water
concentrations and rates of other
samples in zones 1−4, see
Table 2and ref. [61]
S. E. Ruff et al.
subsurface (D) sediment samples across the same zones
sampled after the eruptions. The microbial communities in
the warm (10−20 °C) subsurface sediments (3.8−2.5 m
below seafloor) of the HMMV caldera were characterized
by a relatively low archaeal and bacterial alpha diversity,
and showed a low community turnover, i.e. replacement of
microbial taxa across zones (Figs. 3,4, Fig. S3). These
simple and homogeneous communities support the geo-
physical model of a uniform, warm subsurface mud layer
filling the central chimney of HMMV [25,28,36]. Inter-
estingly, the subsurface communities were most similar to
the surface communities of zone 1 (Fig. 3b, c; Table S2),
which is in accordance with the observed upward transport
and deposition of the subsurface sediments by gas eruptions
(Fig. S2A). Subsurface and also surface sediments of Zone
1 contained typical heterotrophic deep biosphere clades,
such as Bathyarchaeota (Miscellaneous Crenarchaeotic
Group), Chloroflexi and Atribacteria (candidate division
JS1) [37,38] as well as Peptococcaceae and methanogenic
Methanosaeta (Fig. 4, Fig. S4). The latter four clades were
suggested to form a syntrophic network, degrading proteins
and fatty acids under methanogenic conditions [39]. Bath-
yarchaeota, which comprise organisms that also degrade
detrital proteins [40], greatly dominated the archaeal com-
munity in the freshly deposited muds (Fig. 4,S4).We
detected many genes involved in fermentation and metha-
nogenesis (Fig. S4, S5A) in the subsurface metagenomes,
while genes for sulfate reduction, sulfur oxidation or
methane oxidation were absent or very rare. The subsurface
communities in the central mud conduct of HMMV may be
fueled by organic compounds transported with rising
porewater fluids from the deep subsurface. The subsurface
and surface community of zone 1 contained very few
ANME-3 sequences (<1% relative sequence abundance),
and few genes affiliated with Methylococcales, sulfate-
reducing bacteria (SRB) and sulfur-oxidizing bacteria
(SOB) (Fig. S4), in accordance with the biogeochemical
profiles of the freshly exposed muds (Fig. 2, Table 2).
By comparative sequence analysis, we tested if the
subsurface clades deposited at the surface, such as Atri-
bacteria [41], would persist in the surface muds with
increasing exposure and distance from the central mud
conduit. The subsurface-derived clades decreased in relative
sequence abundance with increasing distance to the center.
In zone 3, these clades were barely detectable in the sedi-
ments. The subsurface microbial signature was replaced by
that of typical seep communities within around 2 years.
Only 3−7% of the operational taxonomic units (OTUs; at
98% 16S rRNA gene V4-V6 sequence identity) were shared
between subsurface and surface muds (Fig. 3, Table S2) and
even less (1% shared OTUs) with the reference site that was
characterized by typical oligotrophic deep-sea sediment
organisms, such as Xanthomonadales and Thaumarchaeota
[42]. This diversity pattern was also confirmed based on the
turnover of gene families in the community metagenomes
(Fig. 5a). Only 18−35% of the gene families found in the
subsurface metagenome of zone 1 (sample 11) were found
in the surface metagenomes, while 66 and 77% gene
families were shared between sample 11 and the other two
subsurface metagenomes (Table S6). Similarly, the surface
metagenomes shared between 52 and 79% gene families
among each other (60 ± 9.8 %, mean ± SD, n=6), but only
18−48 % with the subsurface metagenomes (33 ± 9.4%,
mean ± SD, n=12). This suggests that subsurface-derived
genes, and hence subsurface community functions, were
rapidly depleted in the surface muds. Subsurface microbes
have longer generation times compared to surface bacteria
[43–45]. In addition, they were likely repressed by the
exposure to the seafloor conditions; i.e. cold temperatures of
−1 °C and high oxygen concentrations (>280 μM; [46]),
and were eventually overgrown by others.
Surface communities developing with distance from
the eruptive center
Using the mud flow velocities measured by LOOME
observatory and space-by-time substitution, we investigated
how the microbiome composition and metabolic capabilities
of the surface communities would shift across the different
zones with time, and if these changes were in accordance
with the changes in biogeochemical rates (Fig. 2; Table 2).
The analysis of 16S rRNA gene amplicons confirmed that
community structure was significantly different between the
zones, as tested by ANOSIM (RArch =0.7, pArch < 0.01;
RBac =0.5, pBac < 0.01, Fig. S3). Also, the communities
were more similar between adjacent zones than between
zones that were further apart, e.g. zone 1 shared more OTUs
with zone 2 than with zone 3 (Table S2). Total cell counts
increased with distance to the active center (Figs. 3,6a).
Relative cell abundances of key microbial clades involved
in methanotrophy and sulfate reduction also changed
between the zones (Fig. 6b), increasing twofold from zone 1
to 2. Further, we observed a strong increase in microbial
richness and evenness in zone 3 compared to surface sedi-
ments of zone 1 and 2 (Fig. 3). Microbial diversity con-
tinued to increase in the zone 4 sample and peaked in the
reference site. Around 85% of archaeal and bacterial OTUs
of the freshly erupted muds of zone 1 were replaced within
1−2 years of exposure to surface conditions (Fig. 3,
Table S2). Yet, the communities of zones 1 and 2 still
shared key organisms (e.g. Methylococcales and Desulfo-
bacterales), especially those samples taken at a similar
distance to the central conduit (e.g. Samples 3 and 5,
Fig. 3). Zone 3 sediments reached total cell numbers of 3 ×
109cells ml−1, similar to the community density in the
stable hummocky rim (zone 4). Zone 4 harbored the most
In situ development of a methanotrophic microbiome in deep-sea sediments
complex microbial communities at HMMV, with the
highest diversity and evenness (Fig. 3). The overall com-
munity development observed at the level of 16S ribosomal
RNA gene diversity and turnover was also confirmed by the
diversity and turnover of metabolic gene families (Fig. 5;
Figs. S4, S5). Rarefaction curves showed that the expected
number of gene families was highest in the consolidated
muds of zone 3 and the reference site (Fig. 5d) and gen-
erally lower in freshly exposed sediments and subsurface
muds. Similarly, the total number of observed gene families
was highest in the metagenome of surface sediment from
the reference site and low in the sediments of the active
center. At the same time the number of unique gene families
that exclusively occurred in one metagenome was high in
the active center and lowest in the reference site (Fig. 5a).
This indicates that with distance from the active center the
surface sediments are becoming increasingly diverse, but
also increasingly similar on the level of community
functions.
Development of aerobic methanotrophic
populations
In zones 1 and 2, OTUs affiliated with aerobic methano-
trophic Methylococcales were abundant in the top cm of
surface sediments exposed to the oxygen-rich cold bottom
waters, as shown by relative sequence and cell abundances
(Figs. 4,6) and a high number of 16S rRNA and pmoA gene
sequences in the metagenome (Fig. S4, S5B). The Methy-
lococcales reached 5 × 108cells ml−1sediment (3.1 ± 1.9 ×
Fig. 3 Alpha and beta diversity, and total cell abundance across
HMMV sediments. aArchaeal and bacterial diversity was determined
using OTUs (Operational taxonomic units at 98% 16S rRNA V4-V6
gene sequence identity, corresponding to the recommended taxonomic
threshold for microbial species [74]). OTU data were used to assess
observed richness, Inverse Simpson diversity, and Chao1 estimated
richness. Note: The axes for archaeal and bacterial values differ by one
order of magnitude. Total cell numbers were determined by Acridine
Orange Direct Counts and were integrated over the top 10 cm sediment
depth. Dashes denote missing data points. bShift of microbial com-
munity structure in HMMV sediments as visualized by nonmetric
multidimensional scaling (NMDS) using relative sequence abundance
of archaeal and bacterial OTUs. Color indicates the sample origin
(Subsurface =gray polygon; Zone 1 =red; Zone 2 =purple; Zone 3
=light blue; Zone 4 =dark blue; Reference site =brown). The per-
centages of microbial OTUs that are shared between zones (numbers
next to arrows) are based on presence−absence data, i.e. showing that
only 1% of OTUs that are present in the subsurface are also found in
the surface sediment of the reference site. The microbial communities
of the subsurface and of zones 1−3 were all significantly different
from each other (ANOSIM based on presence/absence data: R=0.7,
p=0.001). Zone 4 and the reference site could not be included in the
ANOSIM as there was only one sample retrieved. cDendrogram
showing hierarchical clustering of the samples based on archaeal and
bacterial OTUs.
S. E. Ruff et al.
Fig. 4 Succession of microbial clades in sediments of HMMV based
on relative abundance of OTUs. Together the bars of one sample add
up to 100% archaeal and 100% bacterial relative sequence abun-
dance focusing on functionally relevant clades involved in the methane
and sulfur cycle. Each bar in these panels shows the top 2−3 most
sequence abundant OTUs and all remaining OTUs (Other) that belong
to this subset. A complete table with archaeal and bacterial OTUs, as
well as a summary table of relative abundances of key populations
(e.g. ANME-3) is available at PANGAEA, see ref. [61]
In situ development of a methanotrophic microbiome in deep-sea sediments
108cells ml−1sediment, mean ± SD, n=6; Table 2) already
after a few months of exposure of the subsurface muds (Fig.
S6). This peak in cell abundance of aerobic methylotrophs
in fresh muds was observed in previous expeditions [14,15,
47], suggesting that these organisms rapidly colonize fresh
HMMV muds in general. In the thin sediment surface layer
where oxygen is available, Methylococcales can respond
faster to the high supply of methane, as their higher energy
yield supports faster growth rates compared to those of
anaerobic methanotrophs [48–51]. Also, aerobic methylo-
trophs could relatively rapidly colonize freshly exposed
gassy muds, as they can disperse with bottom waters [2,
52]. Assuming that representatives of this group would
settle on the freshly deposited muds by sediment resus-
pension across the mud volcano, and applying a mud
transport rate of 0.4 m per day between sediments of zones
1 and 2 as observed in this time period [25], the aerobic
methylotrophs could have achieved a net growth rate of
0.01 day−1corresponding to a doubling time of 60 days.
This rate is similar to that calculated for Methylococcales in
arctic, boreal swamps (0.02 day−1;[53]). In comparison,
cold-water anaerobic methanotrophs commonly show
growth rates of around (0.003 day−1)[48]. This finding
supports previous hypotheses, that aerobic methanotrophs
dominate surface sediments of emerging methane leaks and
young seep systems [24,54,55]. However, spatially, they
can only occupy a small niche due to limited oxygen
penetration into the seafloor [12,15,54].
Development of anaerobic methanotrophic
communities and sulfur-oxidizing bacteria
Cell counts and sequences showed that anaerobic methane-
oxidizing archaea (ANME) and their sulfate-reducing part-
ner bacteria were rare in the freshly exposed center sedi-
ments of zone 1 (Figs. 4,6; Fig. S7). Free-living sulfate-
Fig. 5 Richness and turnover of gene families (gf) across HMMV
sediments. aThe “UpSet”diagram is analogous to a Venn diagram
and is based on a presence/absence matrix. The vertical bars represent
the number of gene families that were exclusively found in a respective
combination of metagenomes. The total number of gene families found
in a metagenome is shown as horizontal bar, percentages of gene
families shared between metagenomes are indicated. Note: For clarity
the subsurface samples 14 and 15 were omitted in the UpSet diagram,
without changing the overall trends. Gene family richness and percent
shared gene families of all seven metagenomes are shown in Tables S5
and S6, respectively. Turnover of gene families between metagenomes
is visualized by dendrogram (b) and nonmetric multidimensional
scaling ordination (c). dRarefaction indicates that most gene families,
and possibly metabolisms, that are present at HMMV were detected
S. E. Ruff et al.
reducing bacteria (SRB) increased tenfold in relative
abundance from zone 1 to zone 2, the latter harboring 2.4 ±
1.5 × 108SRB cells ml−1sediment (Table 2). Zone 3 had
similar SRB counts as zone 2, but in addition harbored large
numbers of ANME/SRB consortia (Fig. 6, Table 2). The
sulfide that was produced by these AOM consortia (Fig. 2d,
Table 2) supported the growth and establishment of sulfur-
oxidizing bacteria (SOB), forming white mats covering
zone 3 (Fig. S1, S2D, E). In comparison, the thiotrophs
were rare in sequence abundance in sediments of zone 1.
Their relative sequence abundance increased between zones
2 and 3, where an increasing amount of oxidative dsrAB
genes were detected in the metagenomes (Figs. S4, S8). The
archaeal community of zone 3 was dominated by a single
ANME-3 OTU. This OTU had a relative sequence abun-
dance of below 0.1% in freshly exposed subsurface muds of
zone 1, 2−30% in zone 2 and comprised 63−88% of all
archaeal sequences in zone 3, indicating a significant
increase of the population with time and distance from the
mud and gas conduit, but also suggesting a slow doubling
time of 100−200 days. This estimated doubling time of
ANME-3 in situ corresponds to a growth rate of 0.003
−0.006 day−1which is in good agreement to the rates
estimated by in vitro experiments with psychrophilic
ANME-2 (0.003 day−1;[48]). All populations of ANME,
SRB and SOB (Figs. 4,6) and their metagenomic sig-
natures, especially the relative abundances of mcrA and
dsrAB genes (Figs. S4, S5A, S8) showed the same pattern.
They were rare in subsurface and freshly exposed muds,
and became abundant in surface sediments with increasing
distance from the center and thus exposure time of the
muds. This demonstrates that slow-growing, and initially
rare hydrocarbon-consuming microorganisms are able to
out-compete others at cold seeps when the conditions are
favorable and the time-scale permits [56,57]. In the
undisturbed zone 4, ANME-2a and ANME-3 archaea had
similar relative sequence abundances (Fig. 4), indicating
that these consolidated sediments harbor niches for more
Fig. 6 Total and relative cell abundance of microbial clades in top
sediment layers of HMMV. Total microbial cell numbers (a) were
assessed with DAPI (white bars) and compared to bacterial cell
abundance (probe: EUB338-I-III, gray bars). Replicate samples were
available for zones 1−3 (zone 1: n=3, zone 2/3: n=2), shown as
multiple bar pairs. bRelative cell abundances based on single-cell
counts using CARD-FISH with specific probes for Bacteria (probe
EUB338 I-III), Methylococcales (probe MTMC-701 and competitor
probes), Desulfosarcina/Desulfococcus (probe DSS658), Archaea
(probe Arch915), and ANME-3 (probe ANME3-1249 and helper
probes). Bacteria that did not overlap with Methylococcales or DSS
are denoted “other Bacteria”. Archaea that did not overlap with
ANME-3 are referred to as “other Archaea”.“Cells without probe
signal”were only stained by the nucleic acid stain DAPI and not by
general archaeal or bacterial probes. Relative abundances were aver-
aged over the top ten centimeters; all three layers are shown in Fig-
ure S7. Note: The relative cell abundances for ANME-3,
Desulfosarcina/Desulfococcus and Methylococcales are under-
estimated as these clades formed cell aggregates that were not included
in the single-cell counts. Probe details are given in Table S3; detailed
values and cell counts are archived [61]
In situ development of a methanotrophic microbiome in deep-sea sediments
ANME clades, as compared to the disturbed sediments of
the caldera, which were highly dominated by ANME-3. In
zone 4, very little methane reaches the surface sediment due
to active methanotrophic communities at the roots of the
tubeworms in ~60 cm depth [47], resulting in very low
methane oxidation rates at the surface (Table 2). The low
temperature and stability of the sediments as well as the
presence of hydrates below 0.5−1 m sediment depth may
explain why the investigated surface sediment are of low
activity and share 12% OTUs with surface sediment of the
nonmethane reference site (Fig. 3, Fig. S3). Together, the
observation of community succession on mud flows at
HMMV match previous experiments with wood and whale
falls showing that deep-sea methanogenic, methanotrophic
and thiotrophic clades need years to develop functional
communities on allochthonous surfaces and energy supplies
[58–60].
Conclusion
Here we studied the development of a deep-sea methano-
trophic microbiome on mud flows of a methane-emitting
mud volcano in situ. We were able to sample the commu-
nities of freshly exposed subsurface muds, and compare
them to their source community, as well as to increasingly
developed seep and nonseep communities outside the cal-
dera. Changes in biogeochemical rates with increasing
distance to the eruptive center of the mud volcano were
mirrored by changes in the corresponding metabolic genes
and cell counts of the respective clades. At the level of the
whole microbial metagenome, both 16S rRNA sequence
turnover as well as the diversity of metabolic gene families
showed a pattern of increasing complexity with increasing
development of the methanotrophic assemblages, support-
ing a rich and diverse bacterial and archaeal community.
We were able to confirm our initial hypothesis based on
biogeochemical measurements that subsurface communities
of bacteria and archaea are replaced by pioneering aerobic
methanotrophs and later complex anaerobic methanotrophic
and thiotrophic communities. Even when electron donors
and acceptors are not limiting, the succession of benthic
deep-sea bacterial and archaeal populations may need years,
before the typically high diversity and evenness of deep-sea
sediment communities is reached. Our findings indicate that
loss of seafloor integrity—in this case by gas eruptions and
mud mixing—and thereby the local decline of active and
complex methanotrophic communities can explain the low
efficiency of methane consumption that is globally observed
at active mud volcanoes. Over several years, a seep
microbiome can develop from initially rare populations to a
complex community, in this case study evidenced by
increasing cell and sequence numbers, and increasing
diversity, of aerobic and anaerobic methanotrophs and
thiotrophs. The observed functional succession provides
insights into the response time and recovery of complex
microbial communities to natural and anthropogenic dis-
turbances in the deep sea.
Materials and methods
Sampling sites
Surface sediment samples (0−10 cm) at HMMV are
exposed to the cold Arctic bottom water, and generally have
an ambient temperature of −1 °C. They were recovered
either by TV-guided Multicorer or by push cores using the
remotely operated vehicle Quest (Marum, University Bre-
men) (Table 1). Subsurface sediments of all zones (>2 m
below sea floor) were obtained by gravity corer. Their
temperature at 4 m below the seafloor ranged from around
15 °C in the center to around 3 °C at the hummocky rim
[36]. After recovery, sediments were immediately sub-
sampled in a refrigerated container (0 °C) and further pro-
cessed for biogeochemical analyses or preserved at −20 °C
for later DNA analyses. Further details to the geographic
locations, dates of sampling, and all contextual data are
provided in the supporting information Table 1and in the
public archive for Earth and environmental data PAN-
GAEA; see ref. [61].
Biogeochemistry
Porewater and turnover rates were measured in surface
sediment cores obtained in 2010 using methods described
previously [62]. We show four profiles in detail (Fig. 2,
MUC-809, MUC-827, MUC-838, MUC-847), all other
measurements from 2010 are included in Fig. S8 and the
summary Table 2and can be accessed from the data pub-
lisher PANGAEA; see ref. [61]. Biogeochemical parameters
of sediments from 2003 and 2009 have been reported pre-
viously [14,15]. The pore water was extracted with Rhizons
in 1 cm resolution and immediately fixed in 5% zinc acetate
(ZnAc) solution for sulfate, and sulfide analyses. The total
sulfide concentrations (H2S+HS−+S2−) were determined
using the diamine complexation method [63]. DIC and
alkalinity were measured using the flow injection method
(detector VWR scientific model 1054) [64]. Nutrients were
determined with a Skalar Continuous-Flow Analyzer [65].
Sulfate reduction (SR) and anaerobic oxidation of methane
(AOM) were measured ex situ by the whole core injection
method [66] as previously described [67,68]. Refer to SI
for details on biogeochemical analyses. All cores except the
reference site were degassing methane after retrieval; hence
we could not measure true in situ methane concentration in
S. E. Ruff et al.
Table 1 Sample overview
Sample ID Sample
zone
Sediment depth
(mbsf)
VAMPS project labelaPANGAEA event label—
relative cell abundancesb
PANGAEA event label—porewater
chemistry and biogeochemistryb
Date (MM/
DD/YYYY)
Latitude Longitude
1 Zone 1 0-0.1 RAM_Av6v4_PS74_2_169_1_PUC3 PS74/169-1_PUC-1 PS74/169-1_PUC-15 7/23/2009 72.00500 14.72640
2 Zone 1 0-0.1 RAM_Av6v4_PS74_2_168_1_MUC PS74/168-1 PS74/168-1 7/23/2009 72.00470 14.72420
3 Zone 1 0-0.1 RAM_Av6v4_MSM16_2_838_1_MUC MSM16/2_838-1 MSM16/2_838-1 10/1/2010 72.00480 14.72615
4 Zone 2 0-0.1 RAM_Av6v4_PS64_312_1_MUC PS64/312-1 PS64/312-1 6/28/2003 72.00420 14.72490
5 Zone 2 0-0.1 RAM_Av6v4_MSM16_2_847_1_MUC MSM16/2_847-1 MSM16/2_847-1 10/2/2010 72.00417 14.72702
6 Zone 2 0-0.1 RAM_Av6v4_MSM16_2_855_1_MUC MSM16/2_855-1 MSM16/2_855-1 10/4/2010 72.00403 14.72980
7 Zone 3 0-0.1 RAM_Av6v4_PS64_317_PUC_17 PS64/317_PUC-17 PS64/317_PUC-17 6/30/2003 72.00260 14.73145
8 Zone 3 0-0.1 RAM_Av6v4_PS74_2_172_1_PUC131 PS74/172-1_PUC-131 PS74/172-1_PUC-136 7/25/2009 72.00520 14.72623
9 Zone 3 0-0.1 RAM_Av6v4_MSM16_2_823_1_MUC MSM16/2_823-1 MSM16/2_826-1 9/29/2010 72.00311 14.73134
10 Zone 4 0-0.1 RAM_Av6v4_PS64_326_PUC_12 PS64/326_PUC-12 PS64/326_PUC-12 7/2/2003 72.00098 14.70217
11 Zone 1 3.8 RAM_Av6v4_PS64_332_1_GC PS64/332-1 PS64/332-1 7/2/2003 72.00470 14.72620
12 Zone 2 2.5 RAM_Av6v4_PS64_372_1_GC PS64/372-1 PS64/372-1 7/11/2003 72.00440 14.72660
13 Zone 3 4.6 RAM_Av6v4_PS64_371_1_GC PS64/371-1 PS64/371-1 7/11/2003 72.00330 14.73130
14 Zone 3 2.8 RAM_Av6v4_PS64_373_1_GC PS64/373-1 PS64/373-1 7/11/2003 72.00340 14.72770
15 Zone 4 3.8 RAM_Av6v4_PS64_336_1_GC PS64/336-1 PS64/336-1 7/5/2003 72.00030 14.73550
16 REF 0-0.1 RAM_Av6v4_MSM16_2_809_1_MUC MSM16/2_809-1 MSM16/2_809-1 9/26/2010 72.00666 14.74766
mbsf meters below seafloor
aThis label denotes archaeal datasets. Corresponding bacterial datasets can be accessed under (e.g. RAM_Bv6v4_*).
Sequencing raw data and metadata can be accessed under: https://vamps.mbl.edu/
bContextual data can be accessed under doi: 10.1594/PANGAEA.861266 (https://doi.pangaea.de/10.1594/PANGAEA.861266)
In situ development of a methanotrophic microbiome in deep-sea sediments
Table 2 Porewater chemistry, cell counts, methane oxidation, and sulfate reduction ratesa
SO42−
(mM)
H2S
(mM)
DIC
(mM)
Alkalinity
(mM)
SiO44−
(µM)
PO43−
(µM)
NH4
+
(µM)
NO3
−+
NO2
−
(µM)
NO2
−
(µM)
Mox Rate
[mmol m2d-
1]
SR Rate
[mmol m2d-
1]
Cell counts
probe DSS-
658b
Cell counts
probe MTMC-
701b
Cell counts
probe ANME-
1249b
Zone 1
Mean 10.4 0.03 5.9 26.3 278 3.4 2379 n.d.n.d. 3.3 0.7 0.3 0.2 0
Standard
Error
1.6 <0.01 1.5 3.4 25.7 0.5 166 n.d.n.d. 1.0 0.5 0.2 0.1 0
No. Samples 28 28 28 28 28 28 28 n.d.n.d.8 8 9 9 9
Zone 2
Mean 13.1 0.001 10.1 15.5 237 2.1 1471 1.6 0.3 n.d.n.d. 2.4 3.1 0
Standard
Error
1.3 < 0.001 1.7 1.6 25.2 0.3 176 0.5 0.2 n.d.n.d. 1.5 1.9 0
No. Samples 33 24 25 16 16 16 16 16 16 n.d.n.d.6 6 6
Zone 3
Mean 11.0 1.19 3.8 18.8 225 31.4 963 n.d. 0.4 7.9 18.1 2.4 2.4 1.7
Standard
Error
0.7 0.15 0.9 1.5 18.7 3.6 101 n.d. 0.1 1.4 4.1 0.9 1.7 0.6
No. Samples 121 110 88 26 25 25 25 n.d.1615 18 6 6 6
Zone 4
Mean 30.2 0.47 5.6 0.5 23 3.9 140 6.1 0.6 0.9 n.d. 0.9 0.03 0.01
Standard
Error
1.4 0.21 0.8 0.1 1.2 0.3 26 1.5 0.1 0.8 n.d. 0.3 0.02 0.01
No. Samples 23 10 11 11 11 11 11 7 11 4 n.d.6 6 6
REF
Mean 31.0 0 2.6 2.6 47 3.0 3 10.0 0.2 n.d.n.d. 0.1 0.01 0
Standard
Error
0.1 0 0.1 0.1 14.0 0.6 0.6 3.9 0.0 n.d.n.d.n.c.n.c.n.c.
No. Samples 7777 7767 7n.d.n.d.3 3 3
n.d. not determined, n.c. not calculated, due to low number of samples
aConcentrations and cell counts have been averaged over the top 10 cm of sediment, and rates have been integrated over the top 10 cm of sediment using samples of respective zones from six
expeditions: L’Atalante (2001), PS64 (2003), VKGD276 (2006), PS70 (2007), PS74 (2009), MSM16 (2010)
bCell counts are given as cells ×108ml−1sediment
S. E. Ruff et al.
pore waters. It was previously estimated that the in situ
concentrations of methane in the gassy HMMV center could
reach 100 mM [23].
16S rRNA gene V4-V6 amplicon pyrosequencing
DNA extraction was done in duplicates using 1 g sediment
each and a commercially available extraction kit (Ultra-
Clean Soil DNA Isolation Kit, MoBio, Carlsbad, CA). The
DNA was pooled and the V4-V6 hypervariable regions of
archaeal and bacterial SSU rRNA genes were amplified
using degenerate primers. The bacterial primers 1064R and
518F, or archaeal primers 517F and 1048R (for details see
SI) were fused to Roche GSFLX amplicon sequencing
adapters including 5 nt multiplexing barcodes. We gener-
ated PCR amplicons in triplicate 33 µl reaction volumes
containing 1.0 U Platinum Taq Hi-Fidelity Polymerase
(Invitrogen, Carlsbad, CA), 1× Hi-Fidelity buffer, 200 µM
dNTP PurePeak DNA polymerase mix (Pierce Nucleic Acid
Technologies, Milwaukee, WI), 1.5 mM MgSO4and
0.2 µM of each primer. We added approximately 10−25 ng
template DNA to each PCR and ran a no-template control
for each primer pair. Amplification conditions were: initial
denaturation 94 °C for 3 min; 30 cycles of 94 °C for 30 s,
60 °C for 60 s, and 72 °C for 90 s; final extension at 72 °C
for 10 min. We assessed the quality, size and concentration
of PCR products on a Perkin Elmer Caliper GX. Reads were
demultiplexed and barcodes removed for submission.
Sequence reads were submitted to a rigorous quality control
procedure using mothur v30 [69] and a routine [2,70] that
included denoising of the flow grams [71], single-linkage
preclustering [72] and the removal of chimeras [73].
Sequences were clustered at 98% ribosomal RNA gene V4-
V6 sequence identity—corresponding to the recommended
taxonomic threshold for microbial species [74]—and were
taxonomically assigned using the SILVA taxonomy
(SSURef v119, 07-2014 [75]). Further information about
sequencing datasets and contextual data are available at
PANGAEA [61].
Analyses of V4-V6 amplicon data
Relative abundance of archaeal and bacterial OTUs
(operational taxonomic units clustered at 98% sequence
identity) is based on the original mothur output (Table S1).
To calculate Inverse Simpson diversity indices and Chao1
Richness [76] the OTU abundance tables were rarefied to
account for unequal sampling effort using 300 (Archaea)
and 1000 (Bacteria) randomly chosen sequences without
replacement using mothur. Bray−Curtis dissimilarities [77]
between all samples were calculated and used for two-
dimensional nonmetric multidimensional scaling (NMDS)
ordinations with 20 random starts [78]. All analyses were
carried out with the R statistical environment and the
packages vegan [79], labdsv [80], as well as with custom R
scripts (for details see SI).
Shotgun metagenomics
DNA extraction using 3 g sediment (pooled from 0 to 10 cm
sediment depth) was performed manually as previously
described [81]. DNA was sheared using a Covaris
and libraries were constructed with the Nugen Ovation
Ultralow Library protocol and were amplified for 10−11
cycles. The amplified product was visualized on an Agilent
DNA1000 chip or Caliper HiSens Bioanalyzer assay.
Libraries were pooled at equimolar concentrations based on
these results and size selected using a Sage PippinPrep 2%
cassette. The final library pool had an average insert size
of 170 bp with ~25−30 bp partial overlap between pairs
of reads. It was quantified using a Kapa Biosystems
qPCR library quantification kit, then sequenced on the
Illumina HiSeq1000 in a 2 × 101 paired-end sequencing run
using dedicated read indexing. The samples were
demultiplexed with CASAVA 1.8.2. Details on the library
output are given in Table S4. Further information about
sequencing datasets and contextual data are available at
PANGAEA [61,82].
Ribosomal and metabolic gene reconstruction from
metagenomic data
16S rRNA and metabolic gene abundances as well as gene
reconstructions were generated using a novel, modified
version of the phyloFlash pipeline (https://github.com/
HRGV/phyloFlash) called funcFlash for metabolic genes.
In brief, the generated reads were mapped with BBMap at
minimal global nucleotide identity of 70% against curated
nucleotide databases: The SILVA SSURef v119 database
[75], a published dsrAB gene database (http://www.
microbial-ecology.net/db_download/dsr_v3.zip,[83]) and
two newly generated pmoA and mcrA gene databases that
are publicly available at PANGAEA; see ref. [61]. The
mapped read pairs were counted when at least one read had
a positive mapping. Full-length (>70% of the target length)
genes were assembled with SPAdes [84] or reconstructed
with EMIRGE [85]. The mapping of reconstructed meta-
bolic genes to curated databases using funcFlash can be
used to distinguish, whether a gene of interest is affiliated
with organisms performing the reductive or oxidative
pathway. In our case this new analysis allowed us to dis-
tinguish between dsrAB genes from sulfate reducers and
from sulfur oxidizers, as well as between mcrA genes from
methanogens and from methanotrophs.
In situ development of a methanotrophic microbiome in deep-sea sediments
Multivariate analyses of metabolic gene families
from metagenomic data
We used metagenomic data from seven sites to investigate
richness, abundance, and turnover of gene families across
the different zones of HMMV. Each metagenome was fil-
tered to remove low-quality and/or short reads. Raw reads
were merged into paired reads with BBMerge [86]. To
enable the comparison of gene diversity across sites, each
metagenome was subsampled to 106paired reads using the
BBMap “reformat”tool. Subsampled reads were analyzed
with humann2 [87]. Here, the reads were subjected to a
translated nucleotide search against species-level clusters of
nonredundant gene families of the UniRef50 database [88]
using DIAMOND [89]. Gene abundances were normalized
according to gene length, and then conjoined to obtain a
gene ×metagenome table, analogous to an OTU ×sample
table, with gene families as rows and metagenomes as
columns. This matrix allowed us to investigate diversity
using metabolic gene families (functions) rather than the
commonly used ribosomal genes (taxonomy). The gene ×
metagenome table was subjected to multivariate analyses
(data reduction, hypothesis testing, visualization) based on
the R packages vegan,labdsv,UpSetR [90] and customized
R scripts. Prior to the analyses we removed gene families
with less than ten read hits cumulated across all metagen-
omes, to focus on abundant gene families and to minimize
the influence of spurious hits. NMDS ordinations, calcu-
lated percentages of shared gene families and the UpsetR
diagram are based on a presence/absence matrix. Diversity
indices and rarefaction curves were calculated with a
subsampling-based iterative approach using abundance
information. Refer to SI for details.
Nucleotide sequence accession and contextual data
availability
16S rRNA amplicon and shotgun metagenomic data are
publicly available under SRA Bioproject PRJNA248084
(https://www.ncbi.nlm.nih.gov/bioproject/PRJNA248084/).
Gene sequences were archived under accession numbers
KX581156-KX581194 (16S rRNA), KX581122-
KX581155 (mcrA) and KX581195-KX581216 (pmoA).
Comprehensive contextual data [61] are publicly available
from the publisher for Earth and environmental data
PANGAEA under (https://doi.pangaea.de/10.1594/
PANGAEA.861266).
Cell counts and catalyzed reporter deposition
fluorescence in situ hybridization (CARD-FISH)
Total numbers of single cells were determined using acri-
dine orange direct counts according to the protocol
published elsewhere [91]. CARD-FISH was performed as
previously described [54] with the following modifications.
4−6 µl of 25-fold diluted sediment were used for filtration.
Archaeal cell walls were permeabilized with 0.1 M HCl for
2 min to detect ANME-3 cells, or Proteinase K solution
(15 µg ml−1(Merck, Darmstadt, Germany) in 0.05 M EDTA
(pH 8), 0.1 M Tris-HCl (pH 8), 0.5 M NaCl) for 2−4 min at
room temperature for all other archaea. Bacterial cell walls
were permeabilized with lysozyme solution (1000 kU/ml)
for 60 min at 37 °C. Cells were stained with DAPI (1 µg/
ml), embedded in mounting medium and counted in 40−60
independent microscopic fields using an Axiophot II epi-
fluorescence microscope (Carl Zeiss, Jena, Germany). Cell
numbers of dense aggregates were estimated semi-
quantitatively as previously described [47]. A complete
list of oligonucleotide probes, helpers, and competitors used
in this study is provided (Table S3). A summary of the
results from all 260 CARD-FISH experiments is publicly
available at PANGAEA; see ref. [61].
Acknowledgements We thank the chief scientists, captains and crews
of the R/V Polarstern expedition ARKXIX3b, ARKXXIV-2 and R/V
Maria S. Merian expedition MSM16/2 for their support with work at
sea. We also acknowledge the excellent work of the ROV teams
QUEST (MARUM University Bremen), VICTOR6000 (IFREMER),
and GENESIS (Ghent University), as well as of the AUV team Sentry
(WHOI), and FIELAX data services. We are very grateful to R. Stiens
for assistance with FISH. We thank P.L. Buttigieg, X. Dong, D.V.
Meier, and B. Angelov for support with analyses and D. De Beer, B.
Cheng, E. Hamann, M. Kleiner, M. Strous, G. Wegener, and M.
Winkel for discussions. This study has been supported by the LOOME
demonstration project of the EU 6th FP program ESONET (EC No.
036851) and the EU 7th FP program HERMIONE (EC No. 226354).
S.E.R. was supported by a Deep Life Community Pilot Project Grant
and an AITF/Eyes High Postdoctoral Fellowship. Sequencing was
enabled by the Deep Carbon Observatory’s Census of Deep Life
supported by the Alfred P. Sloan Foundation and performed at Marine
Biological Laboratory (Woods Hole, USA). We thank M. Sogin, S.
Huse, J. Vineis, A. Voorhis, S. Grim, and H. Morrison at MBL.
Additional funds were made available by the Helmholtz Association,
the Max Planck Society, and the DFG METEOR/MERIAN program,
as well as the Leibniz program awarded to A.B.
Author contributions S.E.R. designed the study, performed experi-
ments, analyzed data and wrote the manuscript. J.F. performed
experiments and wrote the manuscript. H.R.G.-V. analyzed data and
wrote the manuscript. Y.M. analyzed data and wrote the manuscript.
K.K. performed experiments and wrote the manuscript. A.R. analyzed
data and wrote the manuscript. A.B. carried out the expeditions and
dives, designed the study, and wrote the manuscript.
Compliance with ethical standards
Conflict of interest The authors declare that they have no conflict of
interest.
Open Access This article is licensed under a Creative Commons
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long as you give appropriate credit to the original author(s) and the
S. E. Ruff et al.
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changes were made. The images or other third party material in this
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use, you will need to obtain permission directly from the copyright
holder. To view a copy of this license, visit http://creativecommons.
org/licenses/by/4.0/.
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