Content uploaded by Marcus Elvert
Author content
All content in this area was uploaded by Marcus Elvert on May 02, 2022
Content may be subject to copyright.
Biogeosciences, 19, 2313–2331, 2022
https://doi.org/10.5194/bg-19-2313-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
Research article
Long-term incubations provide insight into the mechanisms of
anaerobic oxidation of methane in methanogenic lake sediments
Hanni Vigderovich1, Werner Eckert2, Michal Elul1, Maxim Rubin-Blum3, Marcus Elvert4, and Orit Sivan1
1Department of Earth and Environmental Sciences, Ben-Gurion University of the Negev, Be’er Sheva, Israel
2The Yigal Allon Kinneret Limnological Laboratory, Israel Oceanographic and Limnological Research, Migdal, Israel
3Israel Oceanographic and Limnological Research, Haifa, Israel
4Organic Geochemistry Group, MARUM – Center for Marine Environmental Sciences and Faculty of Geosciences,
University of Bremen, Bremen, Germany
Correspondence: Hanni Vigderovich (hannil@post.bgu.ac.il)
Received: 19 August 2021 – Discussion started: 24 August 2021
Revised: 15 March 2022 – Accepted: 17 March 2022 – Published: 2 May 2022
Abstract. Anaerobic oxidation of methane (AOM) is among
the main processes limiting the release of the greenhouse
gas methane from natural environments. Geochemical pro-
files and experiments with fresh sediments from Lake Kin-
neret (Israel) indicate that iron-coupled AOM (Fe-AOM)
sequesters 10 %–15 % of the methane produced in the
methanogenic zone (>20 cm sediment depth). The oxida-
tion of methane in this environment was shown to be me-
diated by a combination of mcr-gene-bearing archaea and
pmoA-gene-bearing aerobic bacterial methanotrophs. Here,
we used sediment slurry incubations under controlled con-
ditions to elucidate the electron acceptors and microorgan-
isms that are involved in the AOM process over the long
term (∼18 months). We monitored the process with the ad-
dition of 13C-labeled methane and two stages of incuba-
tions: (i) enrichment of the microbial population involved
in AOM and (ii) slurry dilution and manipulations, includ-
ing the addition of several electron acceptors (metal ox-
ides, nitrate, nitrite and humic substances) and inhibitors (2-
bromoethanesulfonate, acetylene and sodium molybdate) of
methanogenesis, methanotrophy and sulfate reduction and
sulfur disproportionation. Carbon isotope measurements in
the dissolved inorganic carbon pool suggest the persistence
of AOM, consuming 3%–8% of the methane produced at
a rate of 2.0 ±0.4 nmol per gram of dry sediment per day.
Lipid carbon isotopes and metagenomic analyses point to-
wards methanogens as the sole microbes performing the
AOM process by reverse methanogenesis. Humic substances
and iron oxides, although not sulfate, manganese, nitrate or
nitrite, are the likely electron acceptors used for this AOM.
Our observations support the contrast between methane oxi-
dation mechanisms in naturally anoxic lake sediments, with
potentially co-existing aerobes and anaerobes, and long-term
incubations, wherein anaerobes prevail.
1 Introduction
Methane (CH4) is an important greenhouse gas (Wuebbles
and Hayhoe, 2002), which has both anthropogenic and nat-
ural sources, the latter of which account for about 50 %
of the emission of this gas to the atmosphere (Saunois et
al., 2020). Naturally occurring methane is mainly produced
biogenically via the methanogenesis process, which is per-
formed by methanogenic archaea. Traditionally acknowl-
edged as the terminal process anchoring carbon remineraliza-
tion (Froelich et al., 1979), methanogenesis occurs primarily
via the reduction of carbon dioxide by hydrogen in marine
sediments and via acetate fermentation in freshwater systems
(Whiticar et al., 1986).
Methanotrophy, the aerobic oxidation of methane and the
anaerobic oxidation of methane (AOM) by microbes, nat-
urally controls the release of this gas to the atmosphere
(Conrad, 2009; Reeburgh, 2007; Knittel and Boetius, 2009).
In marine sediments, up to 90 % of the upward methane
flux is consumed anaerobically by sulfate, and in estab-
lished diffusive profiles, that methane consumption occurs
within a distinct sulfate–methane transition zone (Valen-
Published by Copernicus Publications on behalf of the European Geosciences Union.
2314 H. Vigderovich et al.: Long-term incubations provide insight into the mechanisms of anaerobic oxidation
tine, 2002). While sulfate-dependent AOM, catalyzed by
the archaeal anaerobic methanotrophs (ANMEs) 1–3, is
widespread chiefly in marine sediments (Hoehler et al., 1994;
Boetius et al., 2000; Orphan et al., 2001; Treude et al., 2005,
2014), methane oxidation in other environments can be cou-
pled to other electron acceptors (e.g., Raghoebarsing et al.,
2006; Ettwig et al., 2010; Sivan et al., 2011; Crowe et al.,
2011; Norði and Thamdrup, 2014; Valenzuela et al., 2017).
In freshwater sediments, sulfate is often depleted, and
methanogenesis may be responsible for most of the organic
carbon remineralization, resulting in high concentrations of
methane in shallow sediments (Sinke et al., 1992). Indeed,
lakes and wetlands are responsible for 33 %–55 % of natu-
rally emitted methane (Rosentreter et al., 2021). A large por-
tion of this produced methane is oxidized by aerobic (type I,
type II and type X) methanotrophic bacteria via oxygen. Aer-
obic methanotrophy is generally observed at the sediment–
water interface (Damgaard et al., 1998) and/or in the water
column thermocline (Bastviken, 2009). AOM, however, can
also consume over 50% of the produced methane (Segarra et
al., 2015).
Sulfate can be an electron acceptor of AOM in freshwa-
ter sediments, as was shown for example in Lake Cadagno
(Schubert et al., 2011; Su et al., 2020). Alternative electron
acceptors for AOM in natural freshwater environments and
cultures include humic substances, nitrate, nitrite and metals
(such as iron, manganese and chromium). Natural humic sub-
stances and their synthetic analogs were shown to function
as terminal electron acceptors for AOM in soils, wetlands
and cultures (Valenzuela et al., 2017, 2019; Bai et al., 2019;
Zhang et al., 2019; Fan et al., 2020). Nitrate-dependent AOM
has been demonstrated in a consortium of archaea and den-
itrifying bacteria from a canal (Raghoebarsing et al., 2006),
in freshwater lake sediments (Norði and Thamdrup, 2014)
and in a sewage enrichment culture of ANME-2d (Haroon et
al., 2013; Arshad et al., 2015). Nitrite is exploited to oxidize
methane by the aerobic bacteria Methylomirabilis (NC10),
which split the nitrite into N2and O2and then use the pro-
duced oxygen to oxidize the methane (Ettwig et al., 2010).
ANME-2d archaea were also suggested to be involved in
Cr(VI)-coupled AOM, either alone or with a bacterial part-
ner (Lu et al., 2016). Iron- and/or manganese-coupled AOM
has also been suggested in lakes (Sivan et al., 2011; Crowe
et al., 2011; Norði et al., 2013), sometimes by supporting
sulfate-coupled AOM (Schubert et al., 2011; Su et al., 2020;
Mostovaya et al., 2021). Iron-coupled AOM was also shown
to occur in enriched, denitrifying cultures from sewage where
it was performed by ANME-2 (Ettwig et al., 2016) and in a
bioreactor with natural sediments (Cai et al., 2018).
The mechanism and role of iron-coupled AOM in lake
sediments have been studied with a variety of tools in the
sediments of Lake Kinneret. In situ porewater profiles and
top-core experiments (Sivan et al., 2011), diagenetic mod-
els (Adler et al., 2011), and batch incubation experiments
with fresh sediment slurries (Bar-Or et al., 2017) suggest
that iron-coupled AOM (Fe-AOM) removes 10 %–15 % of
the produced methane in the deeper part of the methanogenic
zone (>20 cm below the water–sediment interface). Anal-
ysis of the microbial community structure suggested that
both methanogenic archaea and methanotrophic bacteria are
potentially involved in methane oxidation (Bar-Or et al.,
2015). Analyses of stable isotopes in fatty acids, 16S rRNA
gene amplicons and metagenomics showed that both re-
verse methanogenesis by archaea and bacterial type-I aero-
bic methanotrophy by Methylococcales play important roles
in methane cycling (Bar-Or et al., 2017; Elul et al., 2021).
Aerobic methanotrophy, which has also been observed in
the hypolimnion and sediments of several other lakes that
are considered anoxic (Beck et al., 2013; Oswald et al.,
2016; Martinez-Cruz et al., 2017; Cabrol et al., 2020), may
be driven by the presence of oxygen at nanomolar levels
(Wang et al., 2018). Pure cultures of the ubiquitous aero-
bic methanotrophs Methylococcales have indeed been shown
to survive under hypoxia conditions by oxidizing methane
and with nitrate (Kits et al., 2015), by switching to iron
reduction (Zheng et al., 2020), or even by exploiting their
methanobactins to generate their own oxygen to fuel their
methanotrophic activity (Dershwitz et al., 2021). The lat-
ter study also showed that the alphaproteobacterial methan-
otroph Methylocystis sp., strain SB2, can couple methane ox-
idation and iron reduction. However, whether these aerobic
methanotrophic bacteria are able to oxidize methane under
strictly anoxic conditions and which electron acceptors facil-
itate that activity are still not known.
In the current study, we used long-term anaerobic incuba-
tions to assess the dynamics of methane-oxidizing microbes
under anoxic conditions and to quantify the respective avail-
abilities of different electron acceptors for AOM. To that
end, we diluted fresh methanogenic sediments from Lake
Kinneret with original porewater from the same depth and
amended the sediment with 13C-labeled methane. Our ex-
periment design comprised two stages, the first of which in-
cluded the enrichment of the microbial population involved
in AOM, while the second involved an additional slurry
dilution and several manipulations with different electron
acceptors and inhibitors. We measured methane oxidation
rates (based on 13C-DIC (dissolved inorganic carbon) en-
richment), determined the characteristics of each electron ac-
ceptor (via its turnover) and evaluated changes in microbial
diversity over various incubation periods (based on metage-
nomics and lipid biomarkers). The results from the long-term
anaerobic incubations were compared to those of batch and
semi-continuous bioreactor experiments.
Biogeosciences, 19, 2313–2331, 2022 https://doi.org/10.5194/bg-19-2313-2022
H. Vigderovich et al.: Long-term incubations provide insight into the mechanisms of anaerobic oxidation 2315
2 Methods
2.1 Study site
Lake Kinneret (Sea of Galilee) is a warm, monomictic, fresh-
water lake that is 21 km long and 13 km wide and located
in northern Israel. Its maximum depth is ∼42 m at its cen-
ter (station A, Fig. S1), and its average depth is 24m. From
March to December, the lake is thermally stratified, and from
April to December, the hypolimnion is anoxic. Surface wa-
ter temperatures range from 15 ◦C in the winter (January) to
32 ◦C in the summer (August), and the lake’s bottom wa-
ter temperatures remain in the range of 14–17 ◦C through-
out the year. The sediment from the deep methanogenic zone
used in this study (sediment samples taken from a sedi-
ment depth of ∼20 cm from the water–sediment interface at
the lake’s center) contains 50% carbonates, 30% clay and
7 % iron (Table S1). The dissolved organic carbon (DOC)
concentration of the porewater increases with depth, rang-
ing from ∼6 mg C L−1at the sediment–water interface to
17 mg C L−1at a depth of 25 cm (Adler et al., 2011). The
concentrations of dissolved methane in the sediment pore-
water increase sharply with sediment depth, reaching a max-
imum of more than 2 mM at a depth of 15cm, after which the
amounts of dissolved methane gradually decrease with depth
to 0.5 mM at a depth of 30 cm (Adler et al., 2011; Sivan et
al., 2011; Bar-Or et al., 2015).
2.2 Experimental setup
2.2.1 General
In this study we compared three incubation strategies
(Fig. 1a, b, c) in Lake Kinneret methanogenic sediments
(sediment depths >20 cm), which were amended with orig-
inal porewater from the same depth, 13C-labeled methane
(0.05–2 mL; Table 1), different potential electron acceptors
for AOM (nitrite, nitrate, iron and manganese oxides and hu-
mic substances) and activity inhibitors. We inhibited the mcr
gene with 2-bromoethanesulfonate (BES), methanogenesis
and methanotrophy with acetylene, and sulfate reduction and
sulfur disproportionation with Na-molybdate (Nollet et al.,
1997; Oremland and Capone, 1988; Lovley and Klug, 1983).
Below we describe the three incubation strategies (Fig. 1).
a. Setup A. Long-term two-stage slurry incubations were
performed with a 1 :1 sediment-to-porewater ratio and
high methane content for the first 3 months (first stage)
to ensure the enrichment of the microorganisms in-
volved in AOM. After 3 months, the slurry was diluted
with porewater to a 1 :3 ratio (second stage) and differ-
ent reactants were added to the incubations, which were
subsequently monitored for up to 18 months.
b. Setup B. Semi-continuous bioreactor experiments were
performed in which sediments were collected up to 3 d
before the experiment was set up (freshly sampled sed-
iments). The sediment-to-porewater ratio was 1 :4, and
porewater was exchanged regularly.
c. Setup C. Batch incubation experiments were performed
with freshly sampled sediments and porewater at a 1 :5
ratio, respectively, and amended with hematite. This ex-
perimental setup was described in our previous studies
(Bar-Or et al., 2017; Elul et al., 2021).
The sediments for the slurries conducted in the current
work were collected during seven day-long sampling cam-
paigns aboard the research vessel Lillian between 2017 and
2019 from the center of the lake (Station A, Fig. S1) using
a gravity corer with a 50 cm Perspex core liner. The length
of the sediment in each core was 35–45 cm. During each
sampling campaign, 1–2 sediment cores were collected for
the incubations and 10 cores were collected for the pore-
water extraction. Sediments from the deeper methanogenic
zone (sediment depths >20 cm) for the experiments were di-
luted with porewater from the methanogenic zone of parallel
cores sampled on the same day. The bottom part of the sed-
iment cores (below 20 cm) was transferred, as a bulk, to a
dedicated 5 L plastic container on board. The cores and the
container were brought back to the lab, where the cores were
kept at 4 ◦C, and the porewater was extracted on the same day
of sampling. In the lab, sediments were collected from the
container with 20 mL cutoff syringes and moved to 50mL
falcon tubes. The porewater was extracted by centrifugation
at 9300 g for 15 min at 4 ◦C, syringe-filtered by 0.22 µM fil-
ters into 250 mL pre-autoclaved glass bottles, crimp-sealed
with rubber stoppers and flushed for 30 min with N2. The
extracted porewater was kept under anaerobic conditions at
4◦C until its use. The sediments for the incubations were
subsampled from the liners, diluted no later than 3 d after
their collection from the lake and treated further according to
the experimental strategies described above (setup A or B).
2.2.2 Experiment type-A setup: long-term two-stage
incubations (henceforth referred to as
“two-stage” for simplicity)
Experiment A comprised 10 two-stage incubation experi-
ments (experiment serial number (SN) 1–10; Table 1) with
different treatments (electron acceptors/shuttling/inhibitors).
In the first stage (pre-incubation slurry), the sediment core
was sliced under continuous N2flushing and sediments from
depths >20 cm were collected into zipper bags. The sedi-
ment was homogenized by shaking the sediment in the bag,
and between 80–100 g was transferred into 250mL glass bot-
tles under continuous N2flushing. The sediments were di-
luted with the extracted porewater to create a 1 :1 sediment-
to-porewater slurry with a headspace of 70–90mL (Fig. 1).
The slurries were sealed with rubber stoppers and crimped
caps and were flushed with N2(99.999 %, Maxima, Israel)
for 30 min. Methane (99.99 %, Maxima, Israel) was injected
https://doi.org/10.5194/bg-19-2313-2022 Biogeosciences, 19, 2313–2331, 2022
2316 H. Vigderovich et al.: Long-term incubations provide insight into the mechanisms of anaerobic oxidation
Figure 1. Flow diagram of the experimental design. Three types of experiment were set up to investigate the methanogenic-zone sediments
(deeper than 20 cm): (a) Two-stage slurry experiments, with 1 :1 ratio of sediment-to-porewater incubations and then with diluted pre-
incubated slurries and porewater (1 :3 ratio of sediment to porewater). (b) Semi-continuous bioreactor experiment with freshly collected
sediment. (c) Fresh-batch experiment – slurry experiment with freshly collected sediments (Bar-Or et al., 2017).
using a gastight syringe for a final content of 20 % in the
headspace, where 10 % of the injected methane was 13C-
labeled methane (99 %, Sigma-Aldrich). When significant
AOM activity was observed based on the increase in δ13CDIC
after approximately 3 months (Fig. S2), some of the incu-
bations were further diluted during the second stage of the
experiments. The remainder of the incubations continued to
run with porewater exchange while the δ13CDIC values were
monitored every 3 months.
All the experiments were set up similarly (see dates and
detailed protocols in the Supplement): the pre-incubation
bottle was opened, and subsamples (∼18 g each) were trans-
ferred with a syringe and a Tygon® tube under a laminar
hood and continuous flushing of N2gas into 60 mL glass
bottles. The subsamples were then diluted with fresh anoxic
porewater from the methanogenic zone (as described above)
to achieve a 1 :3 sediment-to-porewater ratio (Fig. 1) while
leaving 24 mL of headspace in each bottle. The bottles were
crimp-sealed, flushed with N2gas for 5 min, shaken vig-
orously and flushed again (three times). Then 13C-labeled
methane was added to all of the bottles as described in Ta-
ble 1. The “killed” control slurries in each experiment were
autoclaved twice and cooled, only after which they were
amended with the appropriate treatments and 13C-labeled
methane.
To the diluted (1 :3) batch slurries, electron acceptors
were added either as a powder (hematite – experiment no. 1,
magnetite – experiment no. 2, clay and humic substances
– experiment no. 7, MnO2– experiment no. 3) or in dis-
solved form in double-distilled water (DDW) (KNO3– ex-
periment no. 4, NaNO2– experiment no. 5). In addition,
the potential involvement of sulfur cycling in the transfer
of electrons was tested in experiment no. 2 via its inhibi-
tion with Na-molybdate (Lovley and Klug, 1983). The syn-
thetic analog for humic substances, i.e., 9,10-anthraquinone-
2,6-disulfonate (AQDS), was dissolved in DDW (detailed
in the Supplement) and added to the bottles of experiment
no. 6 until a final concentration of 5 mM was achieved in
each bottle. Amorphous iron (Fe(OH)3) was prepared in the
lab by dissolving FeCl3in DDW that was then titrated with
NaOH of 1.5 M up to pH 7 and injected into the bottles
of experiment no. 2. The final concentration of each addi-
tion is detailed in Table 1. The 13C-labeled methane was in-
jected into all of the experimental bottles at the beginning
of each experiment (unless described otherwise) by using a
gastight syringe from a stock bottle filled with 13C-labeled
methane gas (which was replaced with saturated NaCl solu-
tion). Three different inhibitors were added to three different
experiments: molybdate was added to experiment no. 1 (to
one bottle of methane-only treatment, magnetite treatment
and amorphous iron treatment) to detect the feasibility of an
Biogeosciences, 19, 2313–2331, 2022 https://doi.org/10.5194/bg-19-2313-2022
H. Vigderovich et al.: Long-term incubations provide insight into the mechanisms of anaerobic oxidation 2317
active sulfur cycle; BES was added to experiment no. 8 at the
start of the experiment; and acetylene was added to experi-
ment no. 9, wherein it was injected during the experiment
into two bottles at different time points after 13C enrichment
was observed in the DIC (Table 1).
All live treatments were set up in duplicate or triplicate,
depending on the target amount of the pre-incubated slurry
for each experiment, and the results are presented as the av-
erage with an error bar. In two experiments, only one killed
control bottle was set up, and the remainder of the slurry
was prioritized for other treatments because the killed con-
trols repeatedly had shown no activity in several previous
experiments. The humic substrate experiment used a natu-
ral (humic) substance that was extracted from a lake near
Fairbanks, Alaska, where iron reduction was observed in the
methanogenic zone. One experiment was set up without any
additional electron acceptor to assess the rate of methano-
genesis in the two-stage slurries. Porewater was sampled
anaerobically for δ13CDIC and dissolved Fe(II) measure-
ments in duplicate (2 mL), and methane was measured from
the headspace. Variations in the δ13CDIC values between the
experiments resulted from different amounts of 13C–labeled
methane injected at the start of each experiment (geochemi-
cal measurements detailed in the analytical methods section
below).
2.2.3 Experiment type-B setup: semi-continuous
bioreactor
Semi-continuous bioreactors were used to monitor the re-
dox state regularly at close-to-natural in situ conditions
for 15 months in freshly collected sediments. Two 0.5 L
semi-continuous bioreactors (Fig. 1) (Lenz, Wertheim, Ger-
many) were set up with freshly sampled sediments from
the methanogenic zone (25–40 cm) and extracted porewa-
ter from the same depth from Station A on Lake Kinneret
immediately after their collection. Both reactors were filled,
headspace-free, with a slurry at a 1 :4 sediment-to-porewater
ratio. One bioreactor was amended with 10 mM of hematite,
while the second, which was a control, was not amended.
To dissolve 13C-labeled methane in the porewater, 15mL of
porewater was replaced with 15mL of methane gas (13 mL
of 12CH4and 2 mL of 13CH4) to produce a methane-only
headspace for 24 h, during which time the reactors were
shaken repeatedly. After 24 h, the gas was replaced with
anoxic porewater, thus eliminating the headspace, which re-
sulted in lower methane concentrations (0.2 mM) than in
either the two-stage incubations or the fresh-batch experi-
ment (∼2 mM). The redox potential was monitored contin-
uously using a platinum/glass electrode (Metrohm, Herisau,
Switzerland) to verify anoxic conditions and to determine the
redox state throughout the incubation period. The bioreactors
were subsampled weekly to bi-weekly, and the sample vol-
ume (5–10 mL) was replaced immediately by preconditioned
anoxic (flushed with N2gas for 15 min) porewater from the
methanogenic zone. As outlined below, samples were ana-
lyzed for dissolved Fe(II), methane and δ13CDIC. Additional
subsamples for metagenome and lipid analyses were taken at
the beginning of the experiment and on days 151 and 382,
respectively.
2.2.4 Experiment type-C setup: fresh-batch experiment
Sediments for this experiment were collected in August 2013
at Station A using a protocol similar to that used to collect
the sediments for the pre-incubations. Sediments from depths
greater than 26 cm were diluted under anaerobic conditions
with porewater from the same depth to obtain a ratio of sed-
iment to porewater of 1 :5. The resulting slurry was then
divided between 60 mL glass bottles (40 mL slurry in each
bottle). The sampling and experimental setup are described
in detail in our earlier study (Bar-Or et al., 2017). Here we
present our results of the δ13CDIC, metagenome and lipid
analyses of two treatments: natural (with only 13C-labeled
methane) and hematite. The experiment ran for 15 months.
2.3 Analytical methods
2.3.1 Geochemical measurements
Measurements of δ13CDIC were performed on a DELTA V
Advantage Thermo Scientific isotope-ratio mass spectrome-
ter (IRMS). Results are reported referred to the Vienna Pee
Dee Belemnite (VPDB) standard. For these measurements,
about 0.3 mL of filtered (0.22 µm) porewater was injected
into a 12 mL glass vial with a He atmosphere and 10 µL
of 85 % H3PO4to acidify all the DIC species to CO2(g).
The headspace autosampler (CTC Analytics, type PC PAL)
sampled the gas from the vials and measured the δ13CDIC
of the sample on the GasBench interface with a precision
of ±0.1 ‰. DIC was measured on the IRMS using the
peak height and a precision of 0.05 mM. Dissolved Fe(II)
concentrations were determined using the ferrozine method
(Stookey, 1970) by a Hanon i2 visible spectrophotometer at
a 562 nm wavelength with a detection limit of 1 µmolL−1. A
100 µL headspace sample was taken for methane measure-
ments with a gastight syringe and was analyzed by a gas
chromatograph (FOCUS GC, Thermo Fisher) equipped with
a flame ionization detector (FID) and a packed column (Shin-
Carbon ST) with a helium carrier gas (UHP) and a detec-
tion limit of 1 nmol of methane. Bottles to which acetylene
was added were also measured by the GC with the same col-
umn and carrier gas for ethylene to determine the acetylene
turnover with the N cycle.
2.3.2 Lipid analysis
A sub-set of samples (Table 3) was investigated for the as-
similation of 13C-labeled methane into polar lipid-derived
fatty acids (PLFAs) and intact ether lipid-derived hydro-
carbons. A total lipid extract (TLE) was obtained from
https://doi.org/10.5194/bg-19-2313-2022 Biogeosciences, 19, 2313–2331, 2022
2318 H. Vigderovich et al.: Long-term incubations provide insight into the mechanisms of anaerobic oxidation
Table 1. Details of the three types of experiments: two-stage, semi-aerobic bioreactor and fresh-batch experiments.
Experiment Experiment Treatment No. of CH413CH4Fe2O3Fe3O4Fe(OH)3MnO2NO−
2NO−
3AQDS Humic Fe-bearing Na2molybdate BES Acetylene Temp Duration Comments
serial bottles [mL] [mL] [mM] [mM] [mM] [mM] [mM] [mM] [mM] substances nontronite [mM] [mM] [µL] [◦C] [d]
number [mM] (clay)
(SN) [g]
1 Hematite 13CH42 1 20 201
13CH4+hematite 2 1 10 20
2 Magnetite 13CH42 1 1 16 447 The methane that was added at
the beginning of the experiment
was not labeled, so 13C-labeled
methane was added after 105 d.
Na2molybdate was added to one of
the bottles on day 365.
13CH4+magnetite 2 1 10 1 16 Na2molybdate was added to one of
the bottles on day 365.
13CH4+Fe(OH)32 1 10 1 16
Killed +13CH4+magnetite 1 1 10 16
3 MnO213CH42 1.2 20 201 200 µL of 13CH4was added on
day 1; then another 1 mL was added
on day 24.
13CH4+MnO22 1.2 10 20 200 µL of 13CH4was added on
day 1; then another 1 mL was added
on day 24.
4 Nitrate 13 CH4+NO−
3(high conc.) 2 1 0.5 12 1 20 306
13CH4+hematite 2 1 0.5 12 20
13CH4+NO−
3(high conc.) +hematite 2 1 0.5 12 1 20
13CH4+NO−
3(low conc.) +hematite 2 1 0.5 12 0.2 20
Killed +13CH4+NO−
3(high conc.) +hematite 1 1 0.5 12 1 20
5 Nitrite 13CH43 1 0.5 20 493
13CH4+NO−
2(high conc.) +hematite 2 1 0.5 10 0.5 20
13CH4+NO−
2(low conc.) +hematite 2 1 0.5 10 0.1 20
Killed +13CH4+NO−
2(high conc.) +hematite 2 1 0.5 10 0.5 20
6 AQDS 13CH43 1 20 264
13CH4+AQDS 2 1 5 20
13CH4+AQDS +hematite 2 1 10 5 20
Killed +13CH4+AQDS 2 1 20
7 Natural humic
acids and clay
13CH42 1 20 169 The headspace of the experiment
bottles was flushed with N2on
day 51, and 13CH4was added. This
was done to match the clay bottles.
13CH4+hematite 2 1 10 20
13CH4+humic acid 2 1 0.5 20
13CH4+clay 2 1 1 20 Clay was added on day 43, and the
bottles were flushed again with N2;
13CH4was added again on day 51.
Killed +13CH4+hematite 2 1 10 20
8 Bromoethanesulfonate
(BES)
13CH4+hematite 2 9 1 10 20 493
13CH4+hematite +BES 2 9 1 10 20 20
9 Acetylene 13CH4+hematite 4 1 0.5 10 120 20 321
13CH4+hematite +acetylene 2 1 0.5 10 120 20 Acetylene was injected into each
bottle at different time points
during the experiment.
Killed +13CH4+hematite 2 1 0.5 10 20
10 No electron acceptor No additions 3 20 147
13CH43 1 20
Semi-bioreactor 13CH415 16 345
13CH4+hematite 15 10 16 677
Freshly collected
sediment exp.
13CH40.05 20 467
13CH4+hematite 0.05 20 20
Biogeosciences, 19, 2313–2331, 2022 https://doi.org/10.5194/bg-19-2313-2022
H. Vigderovich et al.: Long-term incubations provide insight into the mechanisms of anaerobic oxidation 2319
0.4 to 1.6 g of the freeze-dried sediment or incubated
sediment slurry using a modified Bligh and Dyer pro-
tocol (Sturt et al., 2004). Before extraction, 1 µg each
of 1,2-diheneicosanoyl-sn-glycero-3-phosphocholine and 2-
methyloctadecanoic acid was added as internal standards.
PLFAs in the TLE were converted to fatty acid methyl es-
ters (FAMEs) using saponification with KOH/MeOH and
derivatization with BF3/MeOH (Elvert et al., 2003). Intact
archaeal ether lipids in the TLE were separated from the ap-
olar archaeal lipid compounds using preparative liquid chro-
matography (Meador et al., 2014) followed by ether cleav-
age with BBr3in dichloromethane-forming hydrocarbons
(Lin et al., 2010). Both FAMEs and ether-cleaved hydrocar-
bons were analyzed by a GC–mass spectrometer (GC-MS;
Thermo Finnigan TRACE GC coupled to a TRACE MS) for
identification and by a GC-IRMS (Thermo Scientific TRACE
GC coupled via a GC IsoLink interface to a DELTA V Plus)
to determine δ13C values by using the column and tempera-
ture program settings described by Aepfler et al. (2019). The
δ13C values are reported with an analytical precision better
than 1 ‰ as determined by long-term measurements of an
n-alkane standard with known isotopic composition of each
compound. Reported fatty acid isotope data (Table 3) are cor-
rected for the introduction of the methyl group during deriva-
tization by mass balance calculation that is similar to Eq. (1)
(see below) using the measured δ13C value of each FAME
and the known isotopic composition of methanol as input pa-
rameters.
2.3.3 Metagenomic analysis
For the metagenomic analyses, total genomic DNA was ex-
tracted from the semi-aerobic bioreactor with hematite ad-
dition (duplicate samples), pre-incubation slurries (13CH4-
only control, 13CH4+hematite) and their respective initial
slurries (t0) by using the DNeasy PowerLyzer PowerSoil Kit
(Qiagen). Genomic DNA was eluted using 50µL of elution
buffer and stored at −20 ◦C. Metagenomics libraries were
prepared at the sequencing core facility at the University of
Illinois Chicago using the Nextera XT DNA library prepa-
ration kit (Illumina, USA). Between 19 and 40 million 2 ×
150 bp paired-end reads per library were sequenced using Il-
lumina NextSeq 500. Metagenomes were co-assembled from
the concatenated reads of all of the metagenomic libraries
with SPAdes v3.12 (Bankevich et al., 2012; Nurk et al., 2013)
after decontamination, quality value (QV =10) and adapter
trimming with the BBDuk tool from the BBMap suite (Brian
Bushnell, http://sourceforge.net/projects/bbmap/, last access:
1 June 2020). Downstream analyses, including reading cov-
erage estimates, automatic binning with MaxBin (Wu et al.,
2014) and MetaBAT 2 (Kang et al., 2019) bin refining with
the DAS Tool (Sieber et al., 2018), were performed within
the SqueezeMeta framework (Tamames and Puente-Sánchez,
2019). GTDB-Tk was used to classify the metagenome-
assembled genomes (MAGs) based on the Genome Taxon-
Figure 2. The change in methane concentrations with the time of
a representative incubated second-stage long-term slurry experi-
ment, showing apparent net methanogenesis with the average rate
of 25 nmol per gram of dry weight per day.
omy Database release 95 (Parks et al., 2021). The principal
component analysis biplot was constructed with PAST v4.03
(Hammer et al., 2001).
2.3.4 Rate calculations
Methanogenesis rates were calculated from temporal
changes in methane concentration in a representative pre-
incubated slurry experiment (Fig. 2). The amount of methane
oxidized was calculated by a simple mass balance calculation
according to Eqs. (1) and (2):
x×F13CH4+(1−x)×FDI13Ci=FDI13Cf,(1)
[CH4]ox =x×[DIC]f.(2)
The final DIC pool comprises two end-members, the initial
DIC pool and the oxidized 13C CH4. The term xdenotes the
fraction of oxidized 13C CH4, while 1 −xdenotes the frac-
tion of the initial DIC pool out of the final DIC pool. F13CH4
is the fraction of the total CH4that is 13C at t0(idenotes
initial); FDI13Ciis the fraction of the total DIC that is 13C
at t0; and FDI13Cfis the fraction of the total DIC that is 13C
at tfinal. [CH4]ox is the amount (concentration in porewater)
of the methane oxidized throughout the full incubation pe-
riod, and [DIC]fis the DIC concentration at tfinal. It was as-
sumed that the isotopic composition of the labeled CH4did
not change significantly throughout the incubation period.
3 Results
In 10 sets of slurry incubation experiments, we followed the
progress of the methane oxidation process in Lake Kinneret
methanogenic sediments in type-A two-stage long-term incu-
bations. This is done by monitoring the changes in δ13CDIC
https://doi.org/10.5194/bg-19-2313-2022 Biogeosciences, 19, 2313–2331, 2022
2320 H. Vigderovich et al.: Long-term incubations provide insight into the mechanisms of anaerobic oxidation
Figure 3. Comparison of δ13CDIC values among the three types
of experiments with 13C-labeled methane addition: setup A, three
two-stage slurry experiments (at the second stage of the 1 :3 ratio
of sediment to porewater); setup B, the semi-continuous bioreactor
experiment; and setup C, the slurry batch experiment with freshly
collected sediments (Bar-Or et al., 2017). In each experiment, two
treatments are shown, with hematite (filled symbol) and without
hematite (empty symbols). The error bars represent the average de-
viation of the mean of duplicate/triplicate bottles.
values and by running metagenomic and specific isotope
lipid analyses. We also followed methane oxidation in a
semi-continuous bioreactor system (type B) with freshly col-
lected sediments with or without the addition of hematite
(Fig. 3). The results were compared to those of fresh-batch
slurry incubations (type C) from the same methanogenic
zone, presented by Bar-Or et al. (2017) and Elul et al. (2021).
3.1 Geochemical trends in the long-term two-stage
experiments
In the second-stage (1 :3 ratio of sediment to porewa-
ter) long-term batch slurry experiments (type A) from
the methanogenic zone, methanogenesis occurred with net
methanogenesis rates of ∼25 nmol g−1d−1(grams are of dry
weight here and throughout the rest of the paper; Fig. 2, Ta-
ble S2), which are similar to those of fresh incubation exper-
iments (Bar-Or et al., 2017). At the same time there was a
conversion of 13C methane to 13C DIC in all the non-killed
slurries amended with 13C methane, indicating AOM (Figs. 3
and 4). The δ13CDIC values of the “methane-only” control
slurries reached values as high as 743 ‰. The average AOM
rate in the methane-only controls was 2.0 ±0.4 nmol g−1d−1
(Table 2). AOM was also observed in these geochemical ex-
periments with the addition of electron acceptors, and the po-
tential of several electron acceptors to perform and stimulate
the AOM process is detailed below.
3.1.1 Metals as electron acceptors
Iron and manganese oxides were added as potential elec-
tron acceptors to the second-stage long-term slurries. The ad-
dition of hematite to three different experiments increased
the δ13CDIC values over time to 694 ‰, which is simi-
lar to the behavior of the methane-only controls and in
a different pattern than the fresh experiments (Fig. 3).
The average AOM rate in those two-stage treatments was
1.0 ±0.3 nmol g−1d−1(Table 2). Magnetite amendments re-
sulted in a minor increase in δ13CDIC values compared to
the methane-only controls (200 ‰ and 265 ‰, respectively,
Fig. 4a) with an AOM rate of 1.8nmol g−1d−1. Amorphous
iron amendments resulted in only a 22 ‰ increase in δ13CDIC
and a lower AOM rate (0.1 nmol g−1d−1, Fig. 4a and Ta-
ble 2). The addition of iron-bearing clay nontronite did not
cause any increase in the δ13CDIC values (Fig. 4b), but the
concentration of dissolved Fe(II) increased compared to the
natural methane-only control (Fig. 5). Based on δ13CDIC es-
timates, no AOM was detected 200d after the addition of
MnO2, whereas the δ13CDIC values of the methane-only con-
trols increased to over 500‰ (Fig. 4f).
3.1.2 Sulfate as an electron acceptor
The involvement of sulfate in the AOM in the incubations
was tested, even in the absence of detectable sulfate in the
methanogenic sediments. This is because sulfate could the-
oretically still be a short-lived intermediate for the AOM
process in an active cryptic sulfur cycle (Holmkvist et al.,
2011). It was quantified directly by adding Na-molybdate to
the methane-only controls and the magnetite-amended treat-
ments in the second-stage long-term incubations (Fig. 4a).
The addition of Na-molybdate did not affect the increasing
trend of δ13CDIC with time, and therefore, the AOM rates re-
mained unchanged, which is similar to the observation in the
fresh-batch incubations (Bar-Or et al., 2017).
3.1.3 Nitrate and nitrite as electron acceptors
Nitrate and nitrite involvement in the AOM was tested for
the feasibility of an active cryptic nitrogen cycle, even in the
absence of detectable amounts of nitrate and nitrite in the
sediments (Nüsslein et al., 2001; Sivan et al., 2011). Nitrate
was added at two different concentrations (0.2 and 1mM,
Fig. 4c) to the second-stage long-term slurries amended with
hematite, as these concentrations were shown previously to
promote AOM in other settings (Ettwig et al., 2010). The
addition of hematite alone increased the δ13CDIC values by
∼200 ‰ during the 306 d of the experiment. The δ13CDIC
in the bottles with the addition of 1 mM of nitrate, with and
without hematite (Fig. 4c; the data points of the two treat-
ments are on top of each other), decreased from 43 ‰ at
the beginning of the experiment to 35‰ after 306 d. The
δ13CDIC in the bottles with the addition of 0.2 mM of ni-
Biogeosciences, 19, 2313–2331, 2022 https://doi.org/10.5194/bg-19-2313-2022
H. Vigderovich et al.: Long-term incubations provide insight into the mechanisms of anaerobic oxidation 2321
Figure 4. Potential of different electron acceptors for AOM in Lake Kinneret in the two-stage long-term slurry experiments (at the second
stage of the 1 :3 ratio of sediment to porewater) with 13C-labeled methane and the following treatments: (a) with and without the addition
of magnetite and amorphous iron (Fe(OH)3) – the dashed line represents the specific time of 13C-labeled methane addition, and the black
arrow represents the addition of Na-molybdate as an inhibitor for sulfate reduction. (b) With clay and natural humic substance – the green
arrow represents the time clay was added to the relevant bottles; the dashed line represents the time the headspace of each bottle was flushed
again with N2; and the black arrow represents the second injection of 1 mL of 13C-labeled methane. (c) With the addition of hematite and
two different concentrations of nitrate. (d) With the addition of hematite and two different concentrations of nitrite. (e) With the addition of
AQDS. (f) With and without the addition of 13C-labeled methane to all the bottles (see Table 1 for specific experimental details). Error bars
represent the average deviations of the data points from their means of duplicate/triplicate bottles.
https://doi.org/10.5194/bg-19-2313-2022 Biogeosciences, 19, 2313–2331, 2022
2322 H. Vigderovich et al.: Long-term incubations provide insight into the mechanisms of anaerobic oxidation
Figure 5. Change in dissolved Fe(II) in the second stage of experi-
ment no. 7 containing clay and natural humic acid. The green arrow
represents the time at which clay was added to the specific bottles
and those bottles were flushed with N2; the dashed line represents
the time at which the rest of the bottles were flushed; and the black
arrow represents the time at which 13C-labeled methane was added
again. Error bars represent the average of the absolute deviations of
the data points from their means.
trate and hematite increased by 27 ‰ at the end of the exper-
iment. Following the addition of 0.5mM of nitrite, we ob-
served no increase in δ13CDIC values during the first 222 d
(Fig. 4d), after which they increased from 34 ‰ to 54 ‰ by
the end of the experiment. The AOM rate of the high-nitrite-
concentration treatment was 0.2 nmolg−1d−1(Table 2). Fol-
lowing the addition of 0.1 mM of nitrite, δ13CDIC increased
only after 130 d to 158 ‰ on day 493. The AOM rate of the
low-nitrite-concentration treatment was 0.5 nmol g−1d−1. In
the methane-only controls, the δ13CDIC value reached a max-
imum of 330 ‰.
3.1.4 Organic compounds as electron acceptors
Two of the second-stage long-term incubation experiments
were amended with synthetic and natural organic electron
acceptors to test the potential of organic electron acceptors.
The addition of AQDS to slurries with and without hematite
caused a decrease in δ13CDIC values over the entire duration
of the experiment (Fig. 4e). Dissolved Fe(II) increased by
50 µM in these treatments, while in those without AQDS, it
exhibited an increase of 20 µM (Fig. S3). We further tested
the effect of naturally occurring humic substances by us-
ing those isolated from a different natural lake. The results
show that the δ13CDIC values did not change at the begin-
ning of the experiments (Fig. 4b), while a steep increase of
∼90 µM in their Fe(II) concentration was observed (Fig. 5).
After 20 d, the δ13CDIC values of these slurries started to in-
crease dramatically from 84 ‰ to 150 ‰ with an AOM rate
of 1.2 nmol g−1d−1(Fig. 4b, Table 2). Dissolved Fe(II) con-
centrations mirrored the trend of δ13CDIC with a steep in-
crease during the first 20 d followed by a decrease of 37µM
(Fig. 5).
3.1.5 Metabolic pathways
To elucidate which metabolic processes drive AOM, we an-
alyzed δ13CDIC following the addition of inhibitors to the
second-stage long-term slurries: (i) BES, a specific inhibitor
for methanogenesis (Nollet et al., 1997), and (ii) acetylene,
a non-specific inhibitor for methanogenesis and methanotro-
phy (Oremland and Capone, 1988). In both cases and simi-
larly to the killed control, labeled 13C-DIC production was
completely inhibited following the addition (Fig. 6). Though
acetylene can also inhibit nitrogen cycling in some cases,
it has been shown to result in the production of ethylene
(Oremland and Capone, 1988). In our case, however, no ethy-
lene was detected, supporting the conclusion that only the
methanogenesis activity was inhibited.
3.2 Microbial dynamics
Analyses of taxonomy and coverage of metagenome-
assembled genomes suggest that in the pre-incubated two-
stage slurries, Bathyarchaeia are the dominant archaea,
together with putative methanogens such as Methanofas-
tidiales (Thermococci), Methanoregulaceae (Methanomicro-
bia) and Methanotrichales (Methanosarcina) (Supplement
table). Bona fide ANMEs (ANME-1) were detected with
substantial coverage of approximately 1 (the 27th most
abundant from among the 195 MAGs detected) in all
of the treatments. Among the bacteria, the sulfate reduc-
ers Desulfobacterota and Thermodesulfovibrionales (Nitro-
spirota) were prominent together with the GIF9 Dehalococ-
coidia lineage, which is known to metabolize chlorinated
compounds in lake sediments (Biderre-Petit et al., 2016).
Some Methylomirabilales (NC10) were found (average cov-
erage of 0.32 ±0.06), and no Methanoperedens were de-
tected. Methylococcales methanotrophs were found in the
natural sediments and the fresh-batch and bioreactor incu-
bations (average of 0.34±0.02), in contrast to their average
coverage of 0.09 ±0.04 in the long-term incubations. Methy-
lococcales comprised the Methyloterricola,Methylomonas
and Methylobacter genera (Supplement table). The methy-
lotrophic partners of aerobic methanotrophs, Methylotenera,
were found in fresh-batch and bioreactor incubations, where
Methylomonas was found, findings that are in line with those
of previous studies that showed their association (Beck et al.,
2013). Principal component analysis shows the grouping of
long-term pre-incubated slurries; semi-aerobic bioreactor in-
cubations; and fresh-batch experiments (Fig. 7), emphasizing
the microbial dynamics over time.
Biogeosciences, 19, 2313–2331, 2022 https://doi.org/10.5194/bg-19-2313-2022
H. Vigderovich et al.: Long-term incubations provide insight into the mechanisms of anaerobic oxidation 2323
Figure 6. Change in δ13CDIC values over time in the second-stage long-term sediment slurry incubations amended with hematite and 13C-
labeled methane. (a) With/without BES and (b) with/without acetylene. Black arrows represent the time at which acetylene was injected into
the experiment bottle. The error bars are smaller than the symbols.
Table 2. AOM rates and AOM role in experiment type-A second-stage slurries amended with 13C-labeled methane and different electron
acceptors (assuming methanogenesis rate of 24.8 nmol g−1d−1).
Experiment Treatment AOM rate AOM /
serial number [nmol g−1d−1] methanogenesis
(SN) [%]
10 methane only 1.1 4.4
1 methane only 1.6 6.4
methane +hematite 0.5 2.1
2 methane only 2.4 8.2
methane +magnetite 1.8 6.3
methane +amorphous iron 0.1 0.5
7 methane only 1.4 6.4
methane +hematite 1.3 6.0
methane +humics 1.2 5.4
5 methane only 1.0 4.6
methane +hematite 1.0 4.6
methane +hematite +nitrite 0.5 mM 0.2 0.8
methane +hematite +nitrite 0.1 mM 0.5 2.1
3.3 Lipid analysis
The δ13C values of the archaeol-derived isoprenoid phy-
tane were between −5 ‰ and −17‰ in the long-term
pre-incubated samples and thus showed 13C enrichment of
15 ‰–27 ‰ relative to the original sediment. This is in-
dicative of methane-derived carbon assimilation by archaea
(Table 3). Acyclic biphytane, derived mainly from caldar-
chaeol, exhibited a less pronounced 13C enrichment of 5 ‰–
10 ‰. For bacterial-derived fatty acids, δ13C values simi-
larly shifted by up to 10 ‰ relative to the original sediment.
Nonetheless, one would have expected much higher values if
aerobic methanotrophs were active, as was previously indi-
cated by strong 13C enrichments of up to 1650 ‰ in C16:1ω5c
observed in freshly incubated batch samples (Bar-Or et al.,
2017).
4 Discussion
4.1 Anaerobic oxidation of methane in the
methanogenic sediment incubation experiments
The in situ geochemical and microbial diversity profiles (Bar-
Or et al., 2015) and the geochemical (Sivan et al., 2011; Bar-
Or et al., 2017; Fig. 3) and metagenomic (Elul et al., 2021)
analyses of batch incubations with fresh sediments provided
https://doi.org/10.5194/bg-19-2313-2022 Biogeosciences, 19, 2313–2331, 2022
2324 H. Vigderovich et al.: Long-term incubations provide insight into the mechanisms of anaerobic oxidation
Table 3. The δ13C values (in ‰) of fatty acids and isoprenoid hydrocarbons from different experiments compared to values obtained from
the original sediment in the methanogenic zone.
Fatty acids Hydrocarbons
Description Temperature (◦C) Sampling (d) C16:1bC16:1ω5Phytane Biphytane
Pre-incubated slurry +13CH4+hematite 20 411 −40 −43 −17 −23
Pre-incubated slurry +13CH4(bottle A) 20 411 −40 −43 −13 −24
Pre-incubated slurry +13CH4(bottle B) 20 1227 −36 −41 −5−38
Fresh-batch experiment +13 CH4+hematitea20 470 610 1600 −14 −28
Semi-bioreactor +13CH4+hematite 16 382 n.d. n.d. n.d. n.d.
Original sediment (28–30 cm) 14 −44 −51 −32 −33
aBar-Or et al. (2017). n.d.: not detected. bA mixture of three fatty acid double isomers at positions 9, 8 and 7.
Figure 7. Principal component analysis comparison of three types of samples: long-term pre-incubated slurries (blue – experiment A), semi-
continuous bioreactor (pink – experiment B) and fresh-batch experiments (orange – experiment C). One asterisk represents t0; two asterisks
denote methane-only treatments; three asterisks represent hematite treatment.
strong support for the occurrence of Fe-AOM in sediments
of the methanogenic zone below 20 cm. Such profiles and
alongside incubations showed an unexpected presence of aer-
obic bacterial methanotrophs together with anaerobic mi-
croorganisms, such as methanogens and iron reducers (Adler
et al., 2011; Sivan et al., 2011; Bar-Or et al., 2015,2017; Elul
et al., 2021). These findings suggested that both mcr-gene-
bearing archaea and aerobic bacterial methanotrophs mediate
methane oxidation. In the current study, we have supportive
evidence of considerable AOM in the long-term incubations,
even after the two treatment stages and considering the low
abundance of the microbial populations.
The data from the two-stage incubations show a simi-
lar increasing trend in the δ13CDIC values of both the nat-
ural (methane-only) and the hematite-amended treatments
(Fig. 3). This deviates from our observations during exper-
iments B and C with fresh sediment, wherein higher δ13CDIC
values were obtained after the addition of hematite than in
the methane-only treatment (Fig. 3 and Bar-Or et al., 2017).
This was particularly dramatic in the batch slurries (exper-
iment C), but it was also observed in the semi-continuous
bioreactor (experiment B). We assume that the observed dif-
ference in the bioreactors would have been more pronounced
if methane concentrations had been higher, but it is still a
relevant finding. We also note that the difference between
the bioreactor results may also be due to the fact that each
bioreactor community developed separately. The results of
the type-A experiments (compared to those of types B and
C) suggest that either hematite lacks the potential to stimu-
late the AOM activity during the two-stage experiments or
Biogeosciences, 19, 2313–2331, 2022 https://doi.org/10.5194/bg-19-2313-2022
H. Vigderovich et al.: Long-term incubations provide insight into the mechanisms of anaerobic oxidation 2325
there is enough natural Fe(III) in the sediments to sustain the
maximum potential of Fe-AOM. Below we characterize the
AOM process in the long-term two-stage incubation experi-
ments.
4.2 Potential electron acceptors for AOM in the
long-term two-stage incubation experiments
4.2.1 Metal oxides as electron acceptors
Measurements of δ13CDIC show that the additions of mag-
netite, amorphous iron, clays and manganese oxide in the
second-stage incubations resulted in a less pronounced in-
crease in the δ13CDIC values compared to those of the
methane-only controls (Fig. 4). A possible explanation for
the latter may be that these metal oxides inhibit AOM, ei-
ther directly or via a preference for organoclastic iron re-
duction over Fe-AOM, which adds a natural, more negative
carbon isotope signal from the organic materials rather than
the heavy carbon from the 13C-labeled methane. Using mass
balance estimations in the methane-only and in the amor-
phous iron treatments and considering the DIC concentra-
tions and δ13CDIC values of the methane-only treatments at
the beginning of the experiment (6mM and 60 ‰, respec-
tively) and the values at the end (6.5mM and 360 ‰, respec-
tively), about 0.5mM of the DIC was added by the AOM
of methane with δ13C of ∼4000 ‰. The DIC and δ13CDIC
values of the amorphous iron treatment at the beginning of
the experiment were 5.4 mM and 60 ‰, respectively, and by
the end were 6.1 mM and 120‰, respectively. Assuming the
same δ13C of the added methane of 4000 ‰ and a δ13CTOC
of −30 ‰ (Sivan et al., 2011), 0.1 mM of the DIC should de-
rive from AOM and 0.6 mM from organoclastic metabolism.
This means that adding amorphous iron to the system en-
couraged iron reduction that was coupled to the oxidation of
organic compounds other than methane. Intrinsic microbes,
particularly the commonly detected ex-deltaproteobacterial
lineages such as Geobacterales, may catalyze Fe(III) metal
reduction, regardless of AOM (Xu et al., 2021). Manganese
oxides are found in very low abundance in Lake Kinneret
sediments (0.1 %; Table S1 and Sivan et al., 2011). Thus,
their role in metal AOM is likely minimal.
4.2.2 Sulfate as an electron acceptor
Sulfate concentrations in the methanogenic Lake Kinneret
sediments have been below the detection limit in years past,
similarly to their representation in the natural sediments we
used for the incubations (<5 µM; Bar-Or et al., 2015; Elul
et al., 2021). Sulfide concentrations have also been reported
to be minor (<0.3 µM; Sivan et al., 2011). However, sulfate
could theoretically still be a short-lived intermediate for the
AOM process, as pyrite and FeS precipitate in the top sed-
iments and cryptic cycling via pyrite or FeS may replenish
the sulfate, thus rendering it available for AOM (Bottrell et
al., 2000). The addition of Na-molybdate to the second-stage
slurries, including those amended with and without mag-
netite, did not change the δ13CDIC dynamics, which remained
similar to those from before the addition of the inhibitor
(Fig. 4a). This finding is in line with that in fresh-batch sedi-
ment slurries (Bar-Or et al., 2017) and suggests that sulfate is
not a potent electron acceptor for AOM in this environment.
Furthermore, although sulfate-reducing bacteria were abun-
dant, none of the reducers belonged to the known clades of
ANME-2d partners, which were connected previously to the
Fe–S–CH4-coupled AOM (Su et al., 2020; Mostovaya et al.,
2021).
4.2.3 Nitrogen species as electron acceptors
Nitrate and nitrite concentrations are also undetectable in the
porewater of Lake Kinneret sediments (Nüsslein et al., 2001;
Sivan et al., 2011) but again may appear as short-lived inter-
mediate products of ammonium oxidation that is coupled to
iron reduction (Tan et al., 2021; Ding et al., 2014; Shrestha
et al., 2009; Clement et al., 2005). We thus assessed the
roles of nitrate and nitrite as electron acceptors in the two-
stage slurries. Our results indicate that the addition of nitrate
did not promote AOM, likely due to the absence of ANME-
2d, which is known to use nitrate (Arshad et al., 2015; Ha-
roon et al., 2013). In the case of nitrite, even low concentra-
tions appeared to delay the increase in δ13CDIC values, sug-
gesting that organoclastic denitrification outcompetes AOM,
and despite the occurrence of Methylomirabilia, the role of
nitrite-AOM is not prominent in the two-stage incubations
(Fig. 4c, d).
4.2.4 Humic substances as electron acceptors
Humic substances may promote AOM by continuously shut-
tling electrons to metal oxides (Valenzuela et al., 2019).
Though humic substances were not measured directly in
Lake Kinneret sediments, the DOC concentrations in the
methanogenic depth porewater were previously found to be
high (∼1.5 mM; Adler et al., 2011), suggesting that they may
play a role in AOM. Compared to the methane-only treat-
ments, the treatment with the synthetic humic analog AQDS
caused an increase in dissolved Fe(II) concentrations, but it
did not cause 13C-DIC enrichment. This may be explained by
the behavior of AQDS as a strong electron shuttle in organ-
oclastic iron reduction (Lovley et al., 1996), which produces
isotopically more negative carbon that masks the AOM signal
(Figs. 4e, S3). Yet, as was done by Valenzuela et al. (2017),
the addition of natural humic substances did promote AOM,
compared to the rest of the electron acceptors tested, and
may thus support AOM (Fig. 4b). In our incubations, the
natural humic substances promoted first the oxidation of or-
ganic matter by iron reduction, probably by shuttling elec-
trons from the broad spectrum of organic compounds to nat-
ural iron oxides (Figs. 4b and 5). When the availability of
https://doi.org/10.5194/bg-19-2313-2022 Biogeosciences, 19, 2313–2331, 2022
2326 H. Vigderovich et al.: Long-term incubations provide insight into the mechanisms of anaerobic oxidation
the iron oxides or the organic matter decreased, humic sub-
stances likely took over to facilitate the AOM (Fig. 4b).
Overall, the results of our long-term two-stage experi-
ments indicate that sulfate, nitrate, nitrite and manganese ox-
ides do not support AOM in the methanogenic sediments of
Lake Kinneret. The candidate electron acceptors for AOM
in the long-term experiments are natural humic substances
and/or naturally abundant iron minerals. Future experiments
can simulate iron limitation and the involvement of iron ox-
ides in the AOM by removing natural iron oxides from the
sediments.
4.3 Main microbial players in the long-term two-stage
slurries
Methane oxidation in the pre-incubated Lake Kinneret sedi-
ments is likely mediated by either ANMEs or methanogens,
as the addition of BES and acetylene immediately stopped
the AOM (Fig. 6), similarly to the results of the killed bottles
and the BES treatment in the fresh-batch experiment (Bar-Or
et al., 2017). Apart from being methane-metabolizing, acety-
lene can inhibit nitrogen cycling, which results in ethylene
production (Oremland and Capone, 1988). This was not the
case in our incubations as no ethylene was produced. The
increase in δ13C values in phytane and biphytane (Table 3)
also indicates the presence of active archaeal methanogens
or ANMEs (Wegener et al., 2008; Kellermann et al., 2012;
Kurth et al., 2019).
Using the isotopic compositions of specific lipids and
metagenomics, we identified a considerable abundance of
aerobic methanotrophs and methylotrophs in the fresh sed-
iments but not in the long-term slurries (Table 3, Fig. 7). In
the natural sediments, micro-levels (nanomolar) of oxygen
could be trapped in clays and slowly released to the pore-
water (Wang et al., 2018). However, if such micro-levels of
oxygen still existed during the time of the pre-incubation,
they were probably already exhausted. Indeed, the results
of our specific lipids and metagenomics analyses suggest
that the aerobic methanotrophs lineages play only a minor
role in the long-term slurries, probably due to complete de-
pletion of the oxygen. The metagenomic data (Fig. 7, Sup-
plement table) also indicate that Bathyarchaeia, which may
be involved in methane metabolism (Evens et al., 2015),
were enriched in the bioreactor incubations, yet their role in
Lake Kinneret AOM remains to be evaluated. We also ob-
served changes in the abundance of bacterial degraders of
organic matter and necromass: for example, GIF9 Dehalo-
coccoidia, which can metabolize complex organic materi-
als under methanogenic conditions (Cheng et al., 2019; Hug
et al., 2013), were most abundant in the long-term incuba-
tions (Fig. 7, Supplement table). Though ANME-1 archaea
are likely mediators of AOM in these sediments, methane
oxidation via reverse methanogenesis is feasible for some
methanogens in Lake Kinneret sediments (Elul et al., 2021).
4.4 Mechanism of methane oxidation in the long-term
two-stage incubations
Our results indicate net methanogenesis in the two-
stage incubation experiments with an average rate of
25 nmol g−1d−1(Fig. 2 and Table S2), which is similar
to those from fresh incubation experiments (Bar-Or et al.,
2017). This is despite the overall trend of increasing δ13CDIC
values, a result representing potential methane turnover
(Figs. 3 and 4). A likely explanation for the presence of
both signals is an interplay between methane production
and oxidation, which is possibly triggered by reversal of
the methanogenesis pathway in bona fide ANMEs or cer-
tain methanogens (Hallam et al., 2004; Timmers et al., 2017).
Due to the overall production of methane and the lack of in-
tense stimulation of AOM by any electron acceptor added,
the increase in δ13CDIC values could theoretically result from
the occurrence of carbon back flux during methanogenesis,
which is feasible in environments that are close to thermody-
namic equilibrium (Gropp et al., 2021). To test this, we used
DIC mass balance calculations to determine the strength of
back flux in our incubations. Based on Eqs. (1) and (2), the
observed level of 13C enrichment indicates that 3 %–8 % of
the 13C methane should be converted into DIC. These es-
timates are orders of magnitude higher than the previously
reported values of 0.001 %–0.3 % for methanogenesis back
flux in cultures (Zehnder and Brock, 1979; Moran et al.,
2005), but they are in the same range as the back flux of 3.2 %
to 5.5 % observed in ANME enrichment cultures (Holler
et al., 2011). For the latter, however, modeling approaches
from AOM-dominated marine sediment samples and associ-
ated ANME enrichment cultures indicated the absence of net
methanogenesis (Yoshinaga et al., 2014; Chuang et al., 2019;
Meister et al., 2019; Wegener et al., 2021). Thus, it seems
unlikely that back flux alone can account for the methane-
to-DIC conversion in Lake Kinneret sediments. Moreover,
the occurrence of back flux alone in marine methanogenic
sediments with similar net methanogenesis rates and abun-
dant methane-metabolizing archaea did not yield consider-
able 13C enrichment in the DIC pool following sediment in-
cubations (Sela-Adler et al., 2015; Vigderovich et al., 2019;
Yorshansky, 2019) (Table S3). It is, therefore, less likely
that the observed DIC values in our study were sustained by
methanogenesis back flux alone (without an external electron
acceptor) than by active AOM, which, in this case, is proba-
bly performed by ANME-1 archaea or by methanogens, with
the latter performing reverse methanogenesis to some extent.
5 Conclusions
Previous results of geochemical and microbial profiles as
well as incubations with fresh sediments from Lake Kin-
neret constitute evidence of the occurrence of Fe-AOM in the
methanogenic zone. The process is performed by anaerobic
Biogeosciences, 19, 2313–2331, 2022 https://doi.org/10.5194/bg-19-2313-2022
H. Vigderovich et al.: Long-term incubations provide insight into the mechanisms of anaerobic oxidation 2327
archaeal methanogens and bacterial methanotrophs, which
remove about 10%–15 % of the methane produced in the
lake’s sediment. In the current study, we found that after
two incubation stages and intensive purging for a prolonged
duration, AOM was still significant, consuming 3%–8 % of
the methane produced. However, the abundance of aerobic
methanotrophs decreased and anaerobic archaea (ANME-1
or specific methanogens) appeared to be solely responsible
for methane turnover. AOM could be a result of carbon back
flux as the methanogenic/AOM pathway is reversible; how-
ever, the high δ13CDIC signal points to a metabolic reaction.
Terminal electron acceptors or electron shuttles stimulating
Fe-AOM are hematite and/or humic substances. The role
of the aerobic methanotrophs of the order Methylococcales,
which were found in the freshly collected sediment experi-
ments, remains to be examined.
Code availability. The markdown file is available at
https://doi.org/10.6084/m9.figshare.19585933.v1 (Rubin-Blum,
2022).
Data availability. Metagenomic reads were submit-
ted to NCBI Sequence Read Archive, BioProject PR-
JNA826318, and the geochemical data sets can be accessed
at https://doi.org/10.5281/zenodo.6489360 (Vigderovich, 2022)
Supplement. The supplement related to this article is available on-
line at: https://doi.org/10.5194/bg-19-2313-2022-supplement.
Author contributions. HV, WE and OS designed the research. HV,
ME, MRB and ME analyzed the samples and the data. WE and
OS supervised HV and provided resources and funding. HV and
OS synthesized the data and wrote the original draft. HV wrote the
paper with contributions from all the co-authors.
Competing interests. The contact author has declared that neither
they nor their co-authors have any competing interests.
Disclaimer. Publisher’s note: Copernicus Publications remains
neutral with regard to jurisdictional claims in published maps and
institutional affiliations.
Acknowledgements. We would like to thank Benni Sulimani and
Oz Tzabari from the Yigal Allon Kinneret Limnological Labo-
ratory for their onboard technical assistance. We thank all of O.
Sivan’s lab members for their help during sampling and express
especially heartfelt thanks to Noam Lotem for the invaluable as-
sistance with the mass balance calculations and the fruitful discus-
sions and to Efrat Eliani-Russak for her technical assistance. Many
thanks to Kai Hachmann from Marcus Elvert’s lab for his help dur-
ing lipid analysis and to Jonathan Gropp for insightful discussions
about the back flux. This work was supported by ERC Consol-
idator (818450) and Israel Science Foundation (857-2016) grants
awarded to Orit Sivan. Funding for Marcus Elvert was provided by
the Deutsche Forschungsgemeinschaft (DFG) under Germany’s Ex-
cellence Initiative/Excellence Strategy through the clusters of ex-
cellence EXC 309 “The Ocean in the Earth System” (project no.
49926684) and EXC 2077 “The Ocean Floor – Earth’s Uncharted
Interface” (project no. 390741601). Funding for Maxim Rubin-
Blum was provided by the Israel Science Foundation (913/19), the
U.S.-Israel Binational Science Foundation (2019055), and the Is-
rael Ministry of Science and Technology (1126). Hanni Vigderovich
was supported by a student fellowship from the Israel Water Author-
ity.
Financial support. This research has been supported by the H2020
European Research Council (MERIR (grant no. 818450)), the Israel
Science Foundation (grant nos. 857-2016 and 913/19), the Deutsche
Forschungsgemeinschaft (project no. 49926684), the U.S.-Israel Bi-
national Science Foundation (grant no. 2019055), and the Israel
Ministry of Science and Technology (grant no. 1126).
Review statement. This paper was edited by Tina Treude and re-
viewed by four anonymous referees.
References
Adler, M., Eckert, W., and Sivan, O.: Quantifying rates of methano-
genesis and methanotrophy in Lake Kinneret sediments (Israel)
using porewater profiles, Limnol. Oceanogr., 56, 1525–1535,
https://doi.org/10.4319/lo.2011.56.4.1525, 2011.
Aepfler, R. F., Bühring, S. I., and Elvert, M.: Substrate characteristic
bacterial fatty acid production based on amino acid assimilation
and transformation in marine sediments, FEMS Microbiol. Ecol.,
95, 1–15, https://doi.org/10.1093/femsec/fiz131, 2019.
Arshad, A., Speth, D. R., De Graaf, R. M., Op den Camp, H.
J. M., Jetten, M. S. M., and Welte, C. U. A: Metagenomics-
based metabolic model of nitrate-dependent anaerobic oxidation
of methane by Methanoperedens-like archaea, Front. Microbiol.,
6, 1–14, https://doi.org/10.3389/fmicb.2015.01423, 2015.
Bai, Y. N., Wang, X. N., Wu, J., Lu, Y. Z., Fu, L.,
Zhang, F., Lau, T. C., and Zeng, R. J.: Humic sub-
stances as electron acceptors for anaerobic oxidation of
methane driven by ANME-2d, Water Res., 164, 114935,
https://doi.org/10.1016/j.watres.2019.114935, 2019.
Bankevich, A., Nurk, S., Antipov, D., Gurevich, A. A., Dvorkin, M.,
Kulikov, A. S., Lesin, V. M., Nicolenko, S. I., Pham, S., Prjibel-
ski, A. D., Sirotkin, A. V., Vyahhi, N., Tesler, G., Aleksyev, A.
M., and Pevzner, P. A.: SPAdes: A New Genome Assembly Al-
gorithm and Its Applications to Single-Cell Sequencing, J. Com-
put. Biol., 19, 455–477, https://doi.org/10.1089/cmb.2012.0021,
2012.
Bar-Or, I., Ben-Dov, E., Kushmaro, A., Eckert, W., and Sivan, O.:
Methane-related changes in prokaryotes along geochemical pro-
files in sediments of Lake Kinneret (Israel), Biogeosciences, 12,
2847–2860, https://doi.org/10.5194/bg-12-2847-2015, 2015.
https://doi.org/10.5194/bg-19-2313-2022 Biogeosciences, 19, 2313–2331, 2022
2328 H. Vigderovich et al.: Long-term incubations provide insight into the mechanisms of anaerobic oxidation
Bar-Or, I., Elvert, M., Eckert, W., Kushmaro, A., Vigderovich,
H., Zhu, Q., Ben-Dov, E., and Sivan, O.: Iron-Coupled
Anaerobic Oxidation of Methane Performed by a Mixed
Bacterial-Archaeal Community Based on Poorly Reac-
tive Minerals, Environ. Sci. Technol., 51, 12293–12301,
https://doi.org/10.1021/acs.est.7b03126, 2017.
Bastviken D.: Methane, in: Encyclopedia of Inland waters, Oxford,
Elsevier, 783–805, https://doi.org/10.1016/B978-012370626-
3.00117-4, 2009.
Beck, D. A. C., Kalyuzhnaya, M. G., Malfatti, S., Tringe, S.
G., del Rio, T. G., Ivanova, N., Lidstorm, M. E., and Chis-
toserdova, L.: A metagenomic insight into freshwater methane-
utilizing communities and evidence for cooperation between the
Methylococcaceae and the Methylophilaceae, PeerJ, 1, 1–23,
https://doi.org/10.7717/peerj.23, 2013.
Biderre-Petit, C., Dugat-Bony, E., Mege, M., Parisot, N., Adrian,
L., Moné, A., Denonfoux, J., Peyretaillade, E., Debroas.
D., Boucher, D., and Peyret, P.: Distribution of Dehalococ-
coidia in the anaerobic deep water of a remote meromic-
tic crater lake and detection of Dehalococcoidia-derived re-
ductive dehalogenase homologous genes, Plos One, 11, 1–19,
https://doi.org/10.1371/journal.pone.0145558, 2016.
Boetius, A., Ravenschlag, K., Schubert, C. J., Rickert, D.,
Widdel, F., Gieseke, A., Amann, R., Jørgensen, B. B.,
Witte, U., and Pfannkuche, O.: A marine microbial con-
sortium apparently mediating AOM, Nature, 407, 623–626,
https://doi.org/10.1038/35036572, 2000.
Bottrell, S. H., Parkes, R. J., Cragg, B. A., and Raiswell, R.: Isotopic
evidence for anoxic pyrite oxidation and stimulation of bacterial
sulphate reduction in marine sediments, J. Geol. Soc., 157, 711–
714, https://doi.org/10.1144/jgs.157.4.711, 2000.
Cabrol, L., Thalasso, F., Gandois, L., Sepulveda-Jauregui, A.,
Martinez-Cruz, K., Teisserenc, R., Tananaev, N., Tveit, A.,
Svenning, M. M., and Barret, M.: Anaerobic oxidation of
methane and associated microbiome in anoxic water of North-
western Siberian lakes, Sci. Total Environ., 736, 139588,
https://doi.org/10.1016/j.scitotenv.2020.139588, 2020.
Cai, C., Leu, A. O., Xie, G.-J., Guo, J., Feng, Y., Zhao, J.-X., Tyson,
G. W., Yuan, Z., and Hu, S.: A methanotrophic archaeon couples
anaerobic oxidation of methane to Fe(II) reduction, ISME J., 12,
1929–1939, https://doi.org/10.1038/s41396-018-0109-x, 2018.
Cheng, L., Shi, S. bao, Yang, L., Zhang, Y., Dolfing, J., Sun, Y., Liu,
L., Li, Q., Tu, B., Dai, L., Shi, Q., and Zhang, H.: Preferential
degradation of long-chain alkyl substituted hydrocarbons in
heavy oil under methanogenic conditions, Org. Geochem., 138,
103927, https://doi.org/10.1016/j.orggeochem.2019.103927,
2019.
Chuang, P. C., Yang, T. F., Wallmann, K., Matsumoto, R., Hu,
C. Y., Chen, H. W., Lin, S., Sun, C.-H., Li, H.-C., Wang, Y.,
and Dale, A. W.: Carbon isotope exchange during anaerobic
oxidation of methane (AOM) in sediments of the northeastern
South China Sea, Geochim. Cosmochim. Ac., 246, 138–155,
https://doi.org/10.1016/j.gca.2018.11.003, 2019.
Clement, J.-C., Shrestha, J., Ehrenfeld, J. G., and Jaffe,
P. R.: Ammonium oxidation coupled to dissimilatory
iron reduction under anaerobic conditions in wetland
soils, Soil biology and biochemistry, 37, 2323–2328,
https://doi.org/10.1016/j.soilbio.2005.03.027, 2005.
Conrad, R.: The global methane cycle: Recent advances in
understanding the microbial processes involved, Environ.
Microbiol. Rep., 1, 285–292, https://doi.org/10.1111/j.1758-
2229.2009.00038.x, 2009.
Crowe, S. A., Katsev, S., Leslie, K., Sturm, A., Magen, C.,
Nomosatryo, S., Pack, M. A., Kessler, J. D., Reeburgh,
W. S., Roberts, J. A., González, L., Douglas Haffner, G.,
Mucci, A., Sundby, B., and Fowle, D. A.: The methane
cycle in ferruginous Lake Matano, Geobiology, 9, 61–78,
https://doi.org/10.1111/j.1472-4669.2010.00257.x, 2011.
Damgaard, L. R., Revsbech, N. P., and Reichardt, W.: Use of an
oxygen-insensitive microscale biosensor for methane to measure
methane concentration profiles in a rice paddy, Appl. Environ.
Microbiol., 64, 864–870, https://doi.org/10.1128/aem.64.3.864-
870.1998, 1998.
Dershwitz, P., Bandow, N. L., Yang, J., Semrau, J. D., McEl-
listrem, M. T., Heinze, R. A., Fonseca, M., Ledesma, J. C.,
Jennett, J. R., DiSpirito, A. M., Athwal, N. S., Hargrove, M.
S., Bobik, T. A., Zischka, H., and DiSpirito, A. A.: Oxygen
Generation via Water Splitting by a Novel Biogenic Metal
Ion-Binding Compound, Appl. Environ. Microbiol., 87, 1–14,
https://doi.org/10.1128/aem.00286-21, 2021.
Ding, L. J., An, X. L., Li, S., Zhang, G. L., and Zhu, Y. G.: Nitro-
gen loss through anaerobic ammonium oxidation coupled to iron
reduction from paddy soils in a chronosequence, Environ. Sci.
Technol., 48, 10641–10647, https://doi.org/10.1021/es503113s,
2014.
Elul, M., Rubin-Blum, M., Ronen, Z., Bar-Or, I., Eckert, W., and
Sivan, O.: Metagenomic insights into the metabolism of mi-
crobial communities that mediate iron and methane cycling in
Lake Kinneret iron-rich methanic sediments, Biogeosciences,
18, 2091–2106, https://doi.org/10.5194/bg-18-2091-2021, 2021.
Elvert, M., Boetius, A., Knittel, K., and Jørgensen, B. B.: Char-
acterization of specific membrane fatty acids as chemotaxo-
nomic markers for sulfate-reducing bacteria involved in anaer-
obic oxidation of methane, Geomicrobiol. J., 20, 403–419,
https://doi.org/10.1080/01490450303894, 2003.
Ettwig, Katharina F, Butler, M. K., Le Paslier, D., Pelletier, E.,
Mangenot, S., Kuypers, M. M. M., Schreiber, F., Dutilh, B. E.,
Zedelius, J., de Beer, D. Gloerich, J., Wessels, H. J. C. T., van
Alen, T., Luesken, F., Wu, M. L., van de Pas-Schoonen K. T., Op
den Camp, H. J. M., Jansen-Megens, E. M., Francojs, K. J., Stun-
nenberg, H., Weissenbach, J., Jetten, M. S. M., and Strous, M.:
Nitrite-driven anaerobic methane oxidation by oxygenic bacte-
ria, Nature, 464, 543–548, https://doi.org/10.1038/nature08883,
2010.
Ettwig, K. F., Zhu, B., Speth, D., Keltjens, J. T., Jetten, M. S. M.,
and Kartal, B.: Archaea catalyze iron- dependent anaerobic oxi-
dation of methane, P. Natl. Acad. Sci. USA, 113, 12792–12796,
https://doi.org/10.1073/pnas.1609534113, 2016.
Evans, P. N., Parks, D. H., Chadwick, G. L., Robbins, S. J.,
Orphan, V. J., Golding, S. D., and Tyson, G. W.: Methane
metabolism in the archaeal phylum Bathyarchaeota revealed
by genome-centric metagenomics, Science, 350, 434–438,
https://doi.org/10.1126/science.aac7745, 2015.
Fan, L., Dippold, M. A., Ge, T., Wu, J., Thiel, V., Kuzyakov,
Y., and Dorodnikov, M.: Anaerobic oxidation of methane in
paddy soil: Role of electron acceptors and fertilization in
Biogeosciences, 19, 2313–2331, 2022 https://doi.org/10.5194/bg-19-2313-2022
H. Vigderovich et al.: Long-term incubations provide insight into the mechanisms of anaerobic oxidation 2329
mitigating CH4fluxes, Soil Biol. Biochem., 141, 107685,
https://doi.org/10.1016/j.soilbio.2019.107685, 2020.
Froelich, P. N., Klinkhammer, G. P., Lender, M. L., Luedtke, N. A.,
Heath, G. R., Cullen, D., Dauphin, P., Hammond, D., Hartman,
B., and Maynard, V.: Geochem. Cosmochim. Ac., 43, 1075–
1090, https://doi.org/10.1016/0016-7037(79)90095-4, 1979.
Gropp, J., Iron, M. A., and Halevy, I.: Theoretical es-
timates of equilibrium carbon and hydrogen isotope ef-
fects in microbial methane production and anaerobic oxida-
tion of methane, Geochem. Cosmochim. Ac., 295, 237–264,
https://doi.org/10.1016/j.gca.2020.10.018, 2021.
Hallam, S. J., Putnam, N., Preston, C. M., Detter, J. C., Rokhsar, D.,
Richardson, P. H., and DeLong, E. F.: Reverse methanogenesis:
Testing the hypothesis with environmental genomics, Science,
305, 1457–1462, https://doi.org/10.1126/science.1100025, 2004.
Hammer, Ø., Harper, D. A. T., and Ryan, P. D.: Past: paleontolog-
ical statistics software package for education and data analysis,
Palaeontol. Electron., 4, 9 pp., 2001.
Haroon, M. F., Hu, S., Shi, Y., Imelfort, M., Keller, J., Hugenholtz,
P., Yuan, Z., and Tyson, G. W.: Anaerobic oxidation of methane
coupled to nitrate reduction in a novel archaeal lineage, Nature,
500, 567–570, https://doi.org/10.1038/nature12375, 2013.
Hoehler, T. M., Alperin, M. J., Albert, D. B., and Martens,
C. S.: Field and laboratory, evidence for a methane-sulfate
reducer consortium, Global Biogeochem. Cy., 8, 451–463,
https://doi.org/10.1029/94GB01800, 1994.
Holler, T., Wegener, G., Niemann, H., Deusner, C., Ferdelman, T.
G., Boetius, A., Brunner, B., and Widdel, F.: Carbon and sulfur
back flux during anaerobic microbial oxidation of methane and
coupled sulfate reduction, P. Natl. A. Sci. USA., 108, E1484–
E1490, https://doi.org/10.1073/pnas.1106032108, 2011.
Holmkvist, L., Ferdelman, T. G., and Jørgensen, B. B.: A cryptic
sulfur cycle driven by iron in the methane zone of marine sed-
iment (Aarhus Bay, Denmark), Geochim. Cosmochim. Ac., 75,
3581–3599, https://doi.org/10.1016/j.gca.2011.03.033, 2011.
Hug, L. A., Castelle, C. J., Wrighton, K. C., Thomas, B. C., Sharon,
I., Frischkorn, K. R., Williams, K. H., Tringe, S. G., and Ban-
field, J. F.: Community genomic analyses constrain the distribu-
tion of metabolic traits across the Chloroflexi phylum and in-
dicate roles in sediment carbon cycling, Microbiome, 1, 1–17,
https://doi.org/10.1186/2049-2618-1-22, 2013.
Kang, D. D., Li, F., Kirton, E., Thomas, A., Egan, R., An, H., and
Wang, Z.: MetaBAT 2: An adaptive binning algorithm for ro-
bust and efficient genome reconstruction from metagenome as-
semblies, PeerJ, 2019, 1–13, https://doi.org/10.7717/peerj.7359,
2019.
Kellermann, M. Y., Wegener, G., Elvert, M., Yoshinaga, M.
Y., Lin, Y. S., Holler, T., Mollar, P. X., Knittel K.,
and Hinrichs, K. U.: Autotrophy as a predominant mode
of carbon fixation in anaerobic methane-oxidizing micro-
bial communities, P. Natl. A. Sci. USA, 109, 19321–19326,
https://doi.org/10.1073/pnas.1208795109, 2012.
Kits, K. D., Klotz, M. G., and Stein, L. Y.: Methane
oxidation coupled to nitrate reduction under hypoxia by
the Gammaproteobacterium Methylomonas denitrificans, sp.
nov. type strain FJG1, Environ. Microbiol., 17, 3219–3232,
https://doi.org/10.1111/1462-2920.12772, 2015.
Knittel, K. and Boetius, A.: Anaerobic oxida-
tion of methane: Progress with an unknown
process, Annu. Rev. Microbiol., 63, 311–334,
https://doi.org/10.1146/annurev.micro.61.080706.093130,
2009.
Kurth, J. M., Smit, N. T., Berger, S., Schouten, S., Jetten, M.
S. M., and Welte C. U.: Anaerobic methanotrophic archaea
of the ANME-2d clade feature lipid composition that differs
from other ANME archaea, FEMS Microbiol. Ecol., 95, fiz082,
https://doi.org/10.1093/femsec/fiz082, 2019.
Lin, Y. S., Lipp, J. S., Yoshinaga, M. Y., Lin, S. H., Elvert, M., and
Hinrichs, K. U.: Intramolecular stable carbon isotopic analysis
of archaeal glycosyl tetraether lipids, Rapid Commun. Mass Sp.,
24, 2817–2826, https://doi.org/10.1002/rcm.4707, 2010.
Lovley, D. R. and Klug, M. J.: Sulfate reducers can
outcompete methanogens at freshwater sulfate con-
centrations, Appl. Environ. Microbiol., 45, 187–192,
https://doi.org/10.1128/aem.45.1.187-192.1983, 1983.
Lovley, D. R., Coates, J. D., Blunt-Harris, E. L., Phillips, E.
J. P., and Woodward, J. C.: Humic substances as electron
acceptors for microbial respiration, Nature, 382, 445–448,
https://doi.org/10.1038/382445a0, 1996.
Lu, Y. Z., Fu, L., Ding, J., Ding, Z. W., Li, N., and Zeng,
R. J.: Cr(VI) reduction coupled with anaerobic oxidation of
methane in a laboratory reactor, Water Res., 102, 445–452,
https://doi.org/10.1016/j.watres.2016.06.065, 2016.
Martinez-Cruz, K., Leewis, M., Charold, I., Sepulveda-Jauregui,
A., Walter, K., Thalasso, F., and Beth, M.: Science of the To-
tal Environment Anaerobic oxidation of methane by aerobic
methanotrophs in sub-Arctic lake sediments, Sci. Total Environ.,
607/608, 23–31, https://doi.org/10.1016/j.scitotenv.2017.06.187,
2017.
Meador, T. B., Gagen, E. J., Loscar, M. E., Goldhammer, T.,
Yoshinaga, M. Y., Wendt, J., Thomm, M., and Hinrichs, K.
U.: Thermococcus kodakarensis modulates its polar mem-
brane lipids and elemental composition according to growth
stage and phosphate availability, Front. Microbiol., 5, 1–13,
https://doi.org/10.3389/fmicb.2014.00010, 2014.
Meister, P., Liu, B., Khalili, A., Böttcher, M. E., and Jørgensen, B.
B.: Factors controlling the carbon isotope composition of dis-
solved inorganic carbon and methane in marine porewater: An
evaluation by reaction-transport modelling, J. Mar. Syst., 200,
103227, https://doi.org/10.1016/j.jmarsys.2019.103227, 2019.
Moran, J. J., House, C. H., Freeman, K. H., and Ferry,
J. G.: Trace methane oxidation studied in several Eur-
yarchaeota under diverse conditions, Archaea, 1(5), 303–309,
https://doi.org/10.1155/2005/650670, 2005.
Mostovaya, A., Wind-Hansen, M., Rousteau, P., Bristow, L.
A., and Thamdrup, B.: Sulfate- and iron- dependent anaer-
obic methane oxidation occuring side-by-side in fresh-
water lake sediments, Limnol. Oceanogr., 67, 231–246,
https://doi.org/10.1002/lno.11988, 2021.
Nollet, L., Demeyer, D., and Verstraete, W.: Effect of 2-
bromoethanesulfonic acid and Peptostreptococcus productus
ATCC 35244 addition on stimulation of reductive aceto-
genesis in the ruminal ecosystem by selective inhibition
of methanogenesis, Appl. Environ. Microbiol., 63, 194–200,
https://doi.org/10.1128/aem.63.1.194-200.1997, 1997.
Norði, K. Á. and Thamdrup, B.: Nitrate-dependent
anaerobic methane oxidation in freshwater sedi-
https://doi.org/10.5194/bg-19-2313-2022 Biogeosciences, 19, 2313–2331, 2022
2330 H. Vigderovich et al.: Long-term incubations provide insight into the mechanisms of anaerobic oxidation
ment, Geochim. Cosmochim. Ac., 132, 141–150,
https://doi.org/10.1016/j.gca.2014.01.032, 2014.
Norði, K Á., Thamdrup, B., and Schubert, C. J.: Anaero-
bic oxidation of methane in an iron-rich Danish fresh-
water lake sediment, Limnol. Oceanogr., 58, 546–554,
https://doi.org/10.4319/lo.2013.58.2.0546, 2013.
Nurk, S., Bankevich, A., Antipov, D., Gurevich, A., Korobeynikov,
A., Lapidus, A., Prjibelsky, A., Pyshkin, A., Sirotkin, A.,
Sirotkin, Y, Stepanauskas, R., McLean, J., Lasken, R., Clin-
genpeel, S. R., Woyke, T., Tesler, G., Alekseyev, M. A., and
Pevzner, P. A.: Assembling genomes and mini-metagenomes
from highly chimeric reads, in: Research in Computational
Molecular Biology, RECOMB 2013, Lecture Notes in Com-
puter Science, Vol. 7821, edited by: Deng, M., Jiang, R.,
Sun, F., and Zhang, X., Springer, Berlin, Heidelberg, 158–170,
https://doi.org/10.1007/978-3-642-37195-0, 2013.
Nüsslein, B., Chin, K. J., Eckert, W., and Conrad, R.: Ev-
idence for anaerobic syntrophic acetate oxidation during
methane production in the profundal sediment of subtropi-
cal Lake Kinneret (Israel), Environ. Microbiol., 3, 460–470,
https://doi.org/10.1046/j.1462-2920.2001.00215.x, 2001.
Oremland, R. S. and Capone, D. G.: Use of “Specific” Inhibitors in
Biogeochemistry and Microbial Ecology, in: Advances in micro-
bial ecology, Vol. 10, edited by: Marshall, K. C., Plenum Press,
New York and London, 285–362, https://doi.org/10.2307/4514,
1988.
Orphan, V. J., House, C. H., and Hinrichs, K.: Methane-
Consuming Archaea Revealed by Directly Coupled Iso-
topic and Phylogenetic Analysis, Science, 293, 484–488,
https://doi.org/10.1126/science.1061338, 2001.
Oswald, K., Milucka, J., Brand, A., Hach, P., Littmann, S., Wehrli,
B., Albersten, M., Daims, H., Wagner, M., Kuypers, M. M.
M., Schubert, C. J., and Milucka, J.: Aerobic gammapro-
teobacterial methanotrophs mitigate methane emissions from
oxic and anoxic lake waters, Limnol. Oceanogr., 61, 101–118,
https://doi.org/10.1002/lno.10312, 2016.
Parks, D. H., Chuvochina, M., Rinke, C., Mussig, A. J., Chaumeil,
P.-A., and Hugenholtz, P.: GTDB: an ongoing census of bacte-
rial and archaeal diversity through a phylogenetically consistent,
rank normalized and complete genome-based taxonomy, Nucl.
Acids Res., 202, 1–10, https://doi.org/10.1093/nar/gkab776,
2021.
Raghoebarsing, A. A., Pol, A., Van De Pas-Schoonen, K. T., Smol-
ders, A. J. P., Ettwig, K. F., Rijpstra, W. I. C., Schouten, S.,
Sinninghe Damsté, J. S., Op den Camp, H. J. M., Jetten, M.
S. M., and Strous, M.: A microbial consortium couples anaer-
obic methane oxidation to denitrification, Nature, 440, 918–921,
https://doi.org/10.1038/nature04617, 2006.
Reeburgh, W. S.: Oceanic Methane Biogeochemistry, Chem. Rev.,
38, 486–513, https://doi.org/10.1002/chin.200720267, 2007.
Rosentreter, J. A., Borges, A. V., Deemer, B. R., Holgerson, M.
A., Liu, S., Song, C., Melack, J., Raymond, P. A., Duarte, C.
M., Allen, G. H., Olefeldt, D., Poulter, B., Battin, T. I., and
Eyre, B. D.: Half of global methane emissions come from highly
variable aquatic ecosystem source, Nat. geosci., 14, 225-230,
https://doi.org/10.1038/s41561-021-00715-2, 2021.
Rubin-Blum, M.: Vigderovich et al., 2022 markdown file, figshare
[code], https://doi.org/10.6084/m9.figshare.19585933.v1, 2022.
Saunois, M., Stavert, A. R., Poulter, B., Bousquet, P., Canadell, J.
G., Jackson, R. B., Raymond, P. A., Dlugokencky, E. J., Houwel-
ing, S., Patra, P. K., Ciais, P., Arora, V. K., Bastviken, D., Berga-
maschi, P., Blake, D. R., Brailsford, G., Bruhwiler, L., Carl-
son, K. M., Carrol, M., Castaldi, S., Chandra, N., Crevoisier, C.,
Crill, P. M., Covey, K., Curry, C. L., Etiope, G., Frankenberg,
C., Gedney, N., Hegglin, M. I., Höglund-Isaksson, L., Hugelius,
G., Ishizawa, M., Ito, A., Janssens-Maenhout, G., Jensen, K.
M., Joos, F., Kleinen, T., Krummel, P. B., Langenfelds, R. L.,
Laruelle, G. G., Liu, L., Machida, T., Maksyutov, S., McDon-
ald, K. C., McNorton, J., Miller, P. A., Melton, J. R., Morino,
I., Müller, J., Murguia-Flores, F., Naik, V., Niwa, Y., Noce, S.,
O’Doherty, S., Parker, R. J., Peng, C., Peng, S., Peters, G. P.,
Prigent, C., Prinn, R., Ramonet, M., Regnier, P., Riley, W. J.,
Rosentreter, J. A., Segers, A., Simpson, I. J., Shi, H., Smith, S.
J., Steele, L. P., Thornton, B. F., Tian, H., Tohjima, Y., Tubiello,
F. N., Tsuruta, A., Viovy, N., Voulgarakis, A., Weber, T. S.,
van Weele, M., van der Werf, G. R., Weiss, R. F., Worthy, D.,
Wunch, D., Yin, Y., Yoshida, Y., Zhang, W., Zhang, Z., Zhao,
Y., Zheng, B., Zhu, Q., Zhu, Q., and Zhuang, Q.: The Global
Methane Budget 2000–2017, Earth Syst. Sci. Data, 12, 1561–
1623, https://doi.org/10.5194/essd-12-1561-2020, 2020.
Schubert, C. J., Vazquez, F., Lösekann-Behrens, T., Knittel,
K., Tonolla, M., and Boetius, A.: Evidence for anaero-
bic oxidation of methane in sediments of a freshwater sys-
tem (Lago di Cadagno), FEMS Microbiol. Ecol., 76, 26–38,
https://doi.org/10.1111/j.1574-6941.2010.01036.x, 2011.
Segarra, K. E. A., Schubotz, F., Samarkin, V., Yoshinaga, M.
Y., Hinrichs, K.-U., and Joye, S. B.: High rates of anaero-
bic methane oxidation in freshwater wetlands reduce poten-
tial atmospheric methane emissions, Nat. Commun., 6, 1–8,
https://doi.org/10.1038/ncomms8477, 2015.
Sela-Adler, M., Herut, B., Bar-Or, I., Antler, G., Eliani-Russak, E.,
Levy, E., Makovsky, Y., and Sivan, O.: Geochemical evidence
for biogenic methane production and consumption in the shal-
low sediments of the SE Mediterranean shelf (Israel), Cont. Shelf
Res., 101, 117–124, https://doi.org/10.1016/j.csr.2015.04.001,
2015.
Shrestha, J., Rich, J. J., Ehrenfeld, J. G., and Jaffe, P. R.:
Oxidation of ammonium to nitrite under iron-reducing con-
ditions in wetland soils: Laboratory, field demonstrations,
and push-pull rate determination, Soil Sci., 174, 156–164,
https://doi.org/10.1097/SS.0b013e3181988fbf, 2009.
Sieber, C. M. K., Probst, A. J., Sharrar, A., Thomas, B.
C., Hess, M., Tringe, S. G., and Banfield, J. F.: Recov-
ery of genomes from metagenomes via a dereplication, ag-
gregation and scoring strategy, Nat. Microbiol., 3, 836–843,
https://doi.org/10.1038/s41564-018-0171-1, 2018.
Sinke, A. J.C., Cornelese, A. A., Cappenberg, T. E., and
Zehnder, A. J. B.: Seasonal variation in sulfate reduction
and methanogenesis in peaty sediments of eutrophic Lake
Loosdrecht, The Netherlands, Biogeochemistry, 16, 43–61,
https://doi.org/10.1007/BF02402262, 1992.
Sivan, O, Adler, M., Pearson, A., Gelman, F., Bar-Or, I., John, S. G.,
and Eckert, W.: Geochemical evidence for iron-mediated anaer-
obic oxidation of methane, Limnol. Oceanogr., 56, 1536–1544,
https://doi.org/10.4319/lo.2011.56.4.1536, 2011.
Biogeosciences, 19, 2313–2331, 2022 https://doi.org/10.5194/bg-19-2313-2022
H. Vigderovich et al.: Long-term incubations provide insight into the mechanisms of anaerobic oxidation 2331
Stookey, L. L.: Ferrozine-a new spectrophotomet-
ric reagent for iron, Anal. Chem., 42, 779–781,
https://doi.org/10.1021/ac60289a016, 1970.
Sturt, H. F., Summons, R. E., Smith, K., Elvert, M., and
Hinrichs, K.-U.: Intact polar membrane lipids in prokary-
otes and sediments deciphered by high-performance liquid
chromatography/electrospray ionization multistage mass spec-
trometry – New biomarkers for biogeochemistry and mi-
crobial ecology, Rapid Commun. Mass Sp., 18, 617–628,
https://doi.org/10.1002/rcm.1378, 2004.
Su, G., Zopfi, J., Yao, H., Steinle, L., Niemann, H., and Lehmann,
M. F.: Manganese/iron-supported sulfate-dependent anaerobic
oxidation of methane by archaea in lake sediments, Lim-
nol. Oceanogr., 65, 863–875, https://doi.org/10.1002/lno.11354,
2020.
Tamames, J. and Puente-Sánchez, F.: SqueezeMeta,
A Highly Portable, Fully Automatic Metagenomic
Analysis Pipeline, Front. Microbiol., 9, 3349,
https://doi.org/10.3389/fmicb.2018.03349, 2019.
Tan, X., Xie, G. J., Nie, W. B., Xing, D-F., Liu, B. F., Ding,
J., and Ren, N. Q.: Fe(III)-mediated anaerobic ammonium ox-
idation: A novel microbial nitrogen cycle pathway and poten-
tial applications, Crit. Rev. Environ. Sci. Technol., 0, 1–33,
https://doi.org/10.1080/10643389.2021.1903788, 2021.
Timmers, P. H. A., Welte, C. U., Koehorst, J. J., Plugge, C. M.,
Jetten, M. S. M., and Stams, A. J. M.: Reverse Methanogene-
sis and Respiration in Methanotrophic Archaea, Archaea, 2017,
1654237, https://doi.org/10.1155/2017/1654237, 2017.
Treude, T., Niggemann, J., Kallmeyer, J., Wintersteller, P., Schu-
bert, C. J., Boetius, A., and Jørgensen, B. B.: Anaerobic oxida-
tion of methane and sulfate reduction along the Chilean con-
tinental margin, Geochim. Cosmochim. Ac., 69, 2767–2779,
https://doi.org/10.1016/j.gca.2005.01.002, 2005.
Treude, T., Krause, S., Maltby, J., Dale, A. W., Coffin, R., and
Hamdan, L. J.: Sulfate reduction and methane oxidation ac-
tivity below the sulfate-methane transition zone in Alaskan
Beaufort Sea continental margin sediments: Implications for
deep sulfur cycling, Geochim. Cosmochim. Ac., 144, 217–237,
https://doi.org/10.1016/j.gca.2014.08.018, 2014.
Valentine D. L.: Biogeochemistry and microbial ecol-
ogy of methane oxidation in anoxic environments:
A review, A. van Leeuw. J. Microb., 81, 271–282,
https://doi.org/10.1023/A:1020587206351, 2002.
Valenzuela, E. I., Prieto-Davó, A., López-Lozano, N. E.,
Hernández-Eligio, A., Vega-Alvarado, L., Juárez, K., García-
González, A. S., López, M. G., and Cervantes, F. J.: Anaerobic
methane oxidation driven by microbial reduction of natural or-
ganic matter in a tropical wetland, Appl. Environ. Microbiol.,
83, 1–15, https://doi.org/10.1128/AEM.00645-17, 2017.
Valenzuela, E. I., Avendaño, K. A., Balagurusamy, N., Ar-
riaga, S., Nieto-Delgado, C., Thalasso, F., and Cervantes,
F. J.: Electron shuttling mediated by humic substances
fuels anaerobic methane oxidation and carbon burial in
wetland sediments, Sci. Total Environ., 650, 2674–2684,
https://doi.org/10.1016/j.scitotenv.2018.09.388, 2019.
Vigderovich, H.: Data sets for Vigderovich et al., 2022, Zenodo
[data set], https://doi.org/10.5281/zenodo.6489360, 2022.
Vigderovich, H., Liang, L., Herut, B., Wang, F., Wurgaft, E., Rubin-
Blum, M., and Sivan, O.: Evidence for microbial iron reduc-
tion in the methanic sediments of the oligotrophic southeast-
ern Mediterranean continental shelf, Biogeosciences, 16, 3165–
3181, https://doi.org/10.5194/bg-16-3165-2019, 2019.
Wang, L., Miao, X., Ali, J., Lyu, T., and Pan, G.: Quantification of
Oxygen Nanobubbles in Particulate Matters and Potential Appli-
cations in Remediation of Anaerobic Environment, ACS Omega,
3, 10624–10630, https://doi.org/10.1021/acsomega.8b00784,
2018.
Wegener, G., Niemann, H., Elvert, M., Hinrichs, K.-U., and Boetius,
A.: Assimilation of methane and inorganic carbon by microbial
communities mediating the anaerobic oxidation of methane, En-
viron. Microbiol. 10, 2287–2298, https://doi.org/10.1111/j.1462-
2920.2008.01653.x, 2008.
Wegener, G., Gropp, J., Taubner, H., Halevy, I., and Elvert,
M.: Sulfate-dependent reversibility of intracellular re-
actions explains the opposing isotope effects in the
anaerobic oxidation of methane, Sci. Adv., 7, 1–14,
https://doi.org/10.1126/sciadv.abe4939, 2021.
Whiticar, M. J., Faber, E., and Schoell, M.: Biogenic methane
formation in marine and freshwater environments: CO2re-
duction vs. acetate fermentation-Isotope evidence, Geochim.
Cosmochim. Ac., 50, 693–709, https://doi.org/10.1016/0016-
7037(86)90346-7, 1986.
Wu, Y. W., Tang, Y.-H., Tringe, S. G., Simmons, B. A., and Singer,
S. W.: MaxBin: an automated binning method to recover indi-
vidual genomes from metagenomes using, Microbiome, 2, 4904–
4909, 2014.
Wuebbles, D. J. and Hayhoe, K.: Atmospheric methane
and global change, Earth-Sci. Rev., 57, 177–210,
https://doi.org/10.1016/S0012-8252(01)00062-9, 2002.
Xu, Z., Masuda, Y., Wang, X., Ushijima, N., Shiratori,
Y., Senoo, K., and Itoh, H.: Genome-Based Taxonomic
Rearrangement of the Order Geobacterales Including the
Description of Geomonas azotofigens sp. nov. and Ge-
omonas diazotrophica sp. nov, Front. Microbiol., 12, 737531,
https://doi.org/10.3389/fmicb.2021.737531, 2021.
Yorshansky, O.: Iron Reduction in Deep Marine Sediments of
the Eastern Mediterranean Continental Shelf and the Yarqon
Estuary, M.S. thesis, Ben Gurion University of the Negev,
https://doi.org/10.5281/zenodo.6457287, 2019.
Yoshinaga, M. Y., Holler, T., Goldhammer, T., Wegener, G.,
Pohlman, J. W., Brunner, B., Kuypers, M. M. M., Hinrichs, K.-
U., and Elvert, M.: Carbon isotope equilibration during sulphate-
limited anaerobic oxidation of methane, Nat. Geosci., 7, 190–
194, https://doi.org/10.1038/ngeo2069, 2014.
Zehnder, A. J. and Brock, T. D.: Methane formation and methane
oxidation by methanogenic bacteria, J. Bacteriol., 137, 420–432,
https://doi.org/10.1128/jb.137.1.420-432.1979 1979.
Zhang, X., Xia, J., Pu, J., Cai, C., Tyson, G. W., Yuan,
Z., and Hu, S.: Biochar-Mediated Anaerobic Oxida-
tion of Methane, Environ. Sci. Technol., 53, 6660–6668,
https://doi.org/10.1021/acs.est.9b01345, 2019.
Zheng, Y., Wang, H., Liu, Y., Zhu, B., Li, J., Yang, Y., Qin,
W., Chen, L., Wu, X., Chistoserdova, L., and Zhao, F.:
Methane-Dependent Mineral Reduction by Aerobic Methan-
otrophs under Hypoxia, Environ. Sci. Technol. Lett., 7, 606–612,
https://doi.org/10.1021/acs.estlett.0c00436, 2020.
https://doi.org/10.5194/bg-19-2313-2022 Biogeosciences, 19, 2313–2331, 2022
