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Iron-coupled anaerobic oxidation of methane performed by a mixed bacterial-archaeal community based on poorly-reactive minerals Itay Bar-Or, Marcus Elvert, Werner Eckert, Ariel Kushmaro, Hanni Vigderovich, Qingzeng Zhu, Eitan Ben-Dov, and Orit Sivan Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.7b03126 • Publication Date (Web): 01 Oct 2017 Downloaded from http://pubs.acs.org on October 3, 2017

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Iron-coupled anaerobic oxidation of methane performed by a mixed bacterial-

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archaeal community based on poorly-reactive minerals

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Itay Bar-Or†., Marcus Elvert*∥., Werner Eckert‡., Ariel Kushmaro§., Hanni Vigderovich†.,

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Qingzeng Zhu∥., Eitan Ben-Dov§⊥., and Orit Sivan*†

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Department of Geological and Environmental Sciences, Ben Gurion University of the Negev, BeerSheva 84105, Israel MARUM - Center for Marine Environmental Sciences and Department of Geosciences, University of Bremen, Leobener Strasse 8, 28359 Bremen, Germany ‡

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Israel Oceanographic and Limnological Research, The Yigal Allon Kinneret Limnological Laboratory, P.O. Box 447, 14950 Migdal, Israel

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§

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Avram and Stella Goldstein-Goren Department of Biotechnology Engineering, Faculty of Engineering Sciences and The Ilse Katz Center for Meso and Nanoscale Science and Technology, Ben-Gurion University of the Negev, P.O. Box 653, Beer-Sheva 84105, Israel Department of Life Sciences, Achva Academic College, Achva, M.P. Shikmim 79800, Israel *Corresponding authors: Orit Sivan, Department of Geological and Environmental Sciences, Ben Gurion University of the Negev, Beer-Sheva 84105, Israel, Tel: +972-8-6477504, Fax: +972-86472997, [email protected]; Marcus Elvert, MARUM - Center for Marine Environmental Sciences and Department of Geosciences, University of Bremen, Leobener Strasse 8, 28359 Bremen, Germany, Tel: +49-421-21865706, Fax: +49-421-21865715, [email protected].

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Key words: anaerobic oxidation of methane, iron reduction, methanogenic archaea, lake sediment,

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sodium molybdate, 2-bromoethanesulfonate, methanotrophic bacteria, fatty acids, isoprenoid

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hydrocarbons, stable carbon isotopes

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Abstract

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Anaerobic oxidation of methane (AOM) was shown to reduce methane emissions by over 50% in

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freshwater systems, its main natural contributor to the atmosphere. In these environments iron oxides

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can become main agents for AOM, but the underlying mechanism for this process has remained

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enigmatic. By conducting anoxic slurry incubations with lake sediments amended with

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methane and naturally abundant iron oxides the process was evidenced by significant 13C-enrichment

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of the dissolved inorganic carbon pool and most pronounced when poorly-reactive iron minerals such

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as magnetite and hematite were applied. Methane incorporation into biomass was apparent by strong

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uptake of 13C into fatty acids indicative of methanotrophic bacteria, associated with increasing copy

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numbers of the functional methane monooxygenase pmoA gene. Archaea were not directly involved

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in full methane oxidation, but their crucial participation, likely being mediators in electron transfer,

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was indicated by specific inhibition of their activity that fully stopped iron-coupled AOM. By

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contrast, inhibition of sulfur cycling increased

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involvement in a competing process. Our findings suggest that the mechanism of iron-coupled AOM

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is accomplished by a complex microbe-mineral reaction network, being likely representative of many

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similar but hidden interactions sustaining life under highly-reducing low energy conditions.

13C-methane

13C-labeled

turnover, pointing to sulfur species

XFe2+ 13CH 4

8Fe(III)

(Fe2O3, Fe3O4)

Methanogens (not assimilating 13CH4)

intermediates

Methanotrophic bacteria (directly or indirectly assimilating 13CH4 carbon)

42

13CO

2

(8-X)Fe2+

43

TOC Art: A schematic description of the probable pathway involved in iron-coupled anaerobic oxidation of methane in

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Lake Kinneret sediments. Methane and the poorly-reactive but conductive iron minerals hematite and magnetite are

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utilized by methanogens (without assimilation of methane), releasing unknown intermediates that are ultimately turned

46

over by methanotrophic bacteria (assimilating either methane directly or indirectly via potential intermediates) to

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dissolved inorganic carbon and Fe2+.

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Introduction

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Microbial methane (CH4) production (methanogenesis) is known to be the terminal carbon

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remineralization process in deep sediments, after the other electron acceptors (oxygen, nitrate,

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manganese oxides, iron oxides and sulfate) have been exhausted in dissimilatory respiration 1. In

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aquatic systems, microbial methane oxidation (methanotrophy) is the main process controlling the

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release of this potent greenhouse gas to the atmosphere 2. While under oxic conditions, aerobic

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methanotrophs effectively oxidize CH4 to carbon dioxide (CO2) 3, anaerobic oxidation of methane

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(AOM) coupled to sulfate reduction (known as sulfate-dependent AOM) has been shown to consume

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up to 90% of methane at the sulfate-methane transition zone in marine sediments 1. Sulfate-dependent

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AOM is typically performed by consortia of archaea (ANaerobic MEthanotrophs - ANME) and

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sulfate-reducing bacteria 4–6. The process had been hypothesized to be the reverse of methanogenesis

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carried out by the archaea themselves

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found in the ANME genome, indicating the potential for true reverse methanogenesis

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Nonetheless, AOM mediated solely by ANME was reported by Milucka et al.

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sulfur was shown to be a key intermediate in the process.

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Other terminal electron acceptors available to AOM, such as nitrate or nitrite, have been identified

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during the last decade

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("Methylomirabilis oxyfera", NC10 group), which reduce nitrite and intermediately produce oxygen

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to oxidize the methane in non-marine anoxic environments

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specific members of the ANME clade (ANME-2d) were shown to be capable of AOM, either in a co-

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culture with M. oxyfera or in a syntrophic relationship with an anaerobic ammonium-oxidizing

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(Anammox) bacterium 14.

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Evidence for AOM via iron reduction has been provided by methane turnover in sediment slurries

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derived from marine cold seeps 16,17, and by modeling approaches using pore water profiles of marine

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sediments

18,19,

12–14.

7,8,

and indeed most of the genes for methanogenesis were

11,

9,10.

where elemental

Nitrite-dependent AOM is performed by oxygenic bacteria

brackish and coastal sediments

20–22,

15.

In the presence of nitrate, however,

and lake sediments

23–25.

In freshwater 3

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environments, AOM is responsible for the removal of over 50% of the produced methane

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because of low levels of sulfate, iron-coupled AOM can become the major process consuming

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methane 23. However, although the global importance of iron-coupled AOM was emphasized, neither

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its mechanism nor the microbial community members involved have been described in environmental

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samples so far. Nonetheless, Scheller et al.

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methane in the presence of artificial oxidants such as soluble ferric citrate and ferric-EDTA using

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deep-sea sediments, and Ettwig et al

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“Candidatus Methanoperedens nitroreducens” in reducing dissolved Fe(III) and ferrihydrite by AOM

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in a freshwater enrichment culture.

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In order to obtain insight into iron-coupled AOM, we used anoxic sediment slurry incubations

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amended with 13C-labeled methane from the methanogenic zone in Lake Kinneret (Israel) known to

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harbor a microbial community capable of this process 28. The principle of this stable isotope labeling

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is to pinpoint AOM by the transformation of 13C-labeled methane to 13C-enriched dissolved inorganic

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carbon (DIC). Iron-coupled AOM can be indicated when the

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with the addition of specific iron oxides than without them. Experiments were performed using

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addition of the naturally abundant iron oxide minerals and inhibitors for sulfate reduction/sulfur

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disproportionation and methanogenesis. They were analyzed for methane and Fe(II) concentrations

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and carbon isotope composition (δ13C in ‰: ((13C/12C)sample/(13C/12C)standard) - 1) x 1000) of the

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DIC (δ13CDIC) for more than a year, as we expected the process to be rather slow given the low energy

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yield of the reaction. The set of incubations was additionally investigated at the beginning and the

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end for targeted qPCR of functional genes and the uptake of 13C-methane carbon into bacterial and

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archaeal lipid biomarker components.

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Study site

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Lake Kinneret is a monomictic lake located in the north of Israel, with maximum and average depths

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of 42 m and 24 m, respectively. Spring is characterized by the development of phytoplankton blooms

25

27

and,

showed the potential of ANME 2a and 2c to oxidize

emphasized the capability of Methanosarcinales related to

13C-enrichment

of the DIC is higher

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in the epilimnion, supported by the nutrient contribution from the overturn and the winter floods.

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During this time the continuous heating of the surface water initiates thermal stratification and the

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formation of a thermocline 29. In May, as the bloom declines, the hypolimnion becomes enriched with

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particulate organic carbon which is utilized by heterotrophic microorganisms thus gradually depleting

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oxygen and nitrate until sulfate becomes the dominant electron acceptor 30. Typical concentrations of

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major electron acceptors in the water column during the mixed period are 35–50 µM nitrate and 600

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µM sulfate

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throughout the year

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production maximizing at 7-12 cm 31 and sulfate is depleted (below 10 µM). Below that zone, ferrous

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iron concentrations increase to ~200 µM

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with depth down to 18 cm and stabilizes at around 550 µmol g−1 dry weight (dw) 34. Total organic

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carbon content of the sediment is about 2-3% per gram dry weight (dw)23). Our previous work on

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Lake Kinneret sediments showed evidence for iron-coupled AOM below the zone of intense

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methanogenesis based mainly on in situ porewater profiles and the output from a reaction-transport

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model

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platform) showed an increase in Methanosarcinales with depth toward the zone of iron-coupled AOM

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while Methanomicrobiales decreased

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archaeal communities, which opened different biogeochemical avenues for bacterial groups being

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involved in iron-coupled AOM28. Among these avenues bacteria were speculated to be involved

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either by iron reduction directly coupled to methane oxidation or indirectly. This is through the

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oxidation of sulfide to sulfur intermediates followed by disproportionation to sulfide and sulfate with

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the latter finally being accessible to sulfate-driven AOM 35, through other intermediates, or/and even

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utilization of methane in an unexpected manner through a hidden aerobic methane oxidation pathway

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in an anaerobic environment.

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Materials and Methods

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Sampling and experimental setup

23,31.

31–33.

At the uppermost part of the lake sediment, sulfate reduction is the main process 30.

Below 5 cm depth, methanogenesis becomes dominant with methane

28,31.

Total iron content (Fe(tot)) in the sediment increases

Sediment profiles of microbial community using 16S rRNA gene sequencing (454

28.

The bacterial communities were much more diverse than

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Sediment cores for the experiment were collected in August 2013, from the center of Lake Kinneret

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(Station A; which is located at 42 m depth) by means of a gravity corer. Cores were dissected under

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N2 atmosphere to prepare slurries from the sediment zone between 26 and 41 cm at a porewater to

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sediment ratio of 5:1. The additional porewater was extracted from parallel sediment samples (from

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other cores at the same geochemical zone) by centrifugation at 27,000 g at 4ºC. The homogenized

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slurry was transferred under continuous N2 flushing in 40 ml portions to 60 ml crimp bottles and

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sealed.

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Sediment slurries were amended with 13C-labeled methane and except the natural sample treated with

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different iron oxide minerals. Moreover, each individual sample set was kept (I) without inhibitors,

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(II) with inhibition of sulfate reduction and sulfur disproportionation by sodium molybdate

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(Na2MoO4) addition and (III) inhibition of methanogenesis by 2-bromoethanesulfonate (BES)

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addition. One of the sample sets was autoclaved as a control. The various treatments are summarized

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in Table S1. The experiment was conducted over the course of 470 days and highest level of

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precaution was given to any oxygen leakage into the bottles (see below). In detail, duplicate bottles

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were treated with 0.1 g of different iron oxide minerals (amorphous iron, goethite, hematite or

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magnetite; for details, see Table S1) and kept at 20°C in the dark. Amorphous Fe(III) oxyhydroxide

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was formed by neutralizing of FeCl3 to a pH of 7 with NaOH. The other iron oxides were grinded

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from supplied minerals identified as pure iron minerals. Molybdate and BES were added to final

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concentrations of 1 mM and 20 mM, respectively. To avoid oxygen contamination all slurries were

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prepared in an anaerobic chamber and the bottles were sealed with special butyl rubber septa and

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purged again twice for 3 minutes with N2 before the addition of 50 µL of 100% 13C-labeled methane.

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The bottles were kept upside down with no contact between headspace and the septa. One of the

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experimental duplicates with amorphous iron and natural slurry did not show any activity with time

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and were thus discarded form the results. The significant patterns of increasing Fe(II) concentration

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and pmoA numbers and of active methanogenesis only in all non-killed treatments and not randomly

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(see results chapter) highlight the absence of oxygen leakage. In addition, a set of three additional 6 ACS Paragon Plus Environment

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control bottles with natural sediment slurries, 13C-labeled methane, without inhibitors and equipped

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with a highly-sensitive oxygen sensor (Fig. S1) was incubated for a year in order to trace oxygen

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leakage, and we did not detect any intrusion of oxygen into these bottles.

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Analytical methods

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The slurries were subsampled throughout the year for methane, ferrous iron and δ13CDIC

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determination. Methane concentrations were measured directly from the headspace of the slurries on

156

a Thermo Scientific gas chromatograph (GC) equipped with a flame ionization detector (FID) at a

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precision of 2 μmol∙L-1. Ferrous iron concentrations were determined from 1 ml of slurry water that

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was fixed immediately after the extraction using Ferrozine. The supernatant was filtered through 0.2

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μm filters and analyzed for dissolved Fe(II) by measuring the absorbance at 562 nm on a

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spectrophotometer 36, with an error of less than 7 µmol L-1. The δ13CDIC of the slurry water (1 ml) was

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measured on an isotopic ratio mass spectrometer (Gas Source-IRMS, Thermo). The measurement is

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reported in per mil units (‰, 1/10 of the percentage unit) versus the Vienna Pee Dee Belemnite

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(VPDB) standard with a precision of ± 0.1‰. Total iron extraction was determined using heat and 6

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N hydrochloride acid 37. The different fractions of various reactive iron minerals were extracted based

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on the Poulton and Canfield 38 method. Sulfate concentrations were measured by inductively coupled

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plasma (ICP)–atomic emission (Perkin-Elmer optima 3300) with a precision of 2%. A fiber optic

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oxygen meter (Fibox 3 trace, PreSens) with oxygen sensor (type PSt6) was glued to the inside of the

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experiment bottle wall. The detection limit of the PSt6 sensor is 1 ppb oxygen.

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The set of incubations was additionally investigated at the beginning and the end in terms of targeted

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qPCR and for the uptake of

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intact ether lipid-derived hydrocarbons. PLFAs were released and converted to fatty acid methyl

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esters (FAME) 39. Intact archaeal ether lipids were separated from the apolar lipid compounds40 and

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processed to form hydrocarbons

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using a preparative Inertsil Diol column (5µm, 150*10mm, GL Sviences Inc., Tokyo, Japan)

13C-methane

41.

carbon into polar lipid-derived fatty acids (PLFAs) and

In brief, separation into apolar and polar lipids was performed

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connected to an Agilent 1200 series HPLC that was equipped with an Agilent 1200 series fraction

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collector. The flow rate was set to 3 mL min-1 and the eluent gradient was: 100% A to 10% B in 5

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min, to 85% in 1 min, hold at 85% B for 9 min, then column re-equilibration with 100% A for 6 min,

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where eluent A was composed of n-hexane/2-propanol (85:15, v:v) and eluent B was 2-

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propanol/MilliQ water (90:10, v:v). The fraction collection time windows are from 0.1 to 5min for

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apolar fraction and from 5 to 15min for polar fraction. Both FAMEs and ether-cleaved hydrocarbons

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were analyzed by GC-mass spectrometry (GC-MS) for identification and GC-IRMS for

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determination of δ13C values

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derivative formation and GC-MS verification 42,43. Uptake of 13C-methane into PLFAs was calculated

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as the product of excess

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measurements 53. Excess 13C is the difference between the fractional abundance (F) of 13C in PLFAs

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after 470 days relative to the T0 sample where F =

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from the measured δ13C values as R = (

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Total genomic DNA was extracted from duplicate samples of the slurries using the MoBio Power

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Soil DNA isolation kit (MoBio Laboratories, Solana Beach, CA). Genomic DNA was eluted using

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80 µl of elution buffer and stored at −20°C. Reaction mix for qPCR included the following: 12.5 µl

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KAPA SYBR Fast Universal Readymix (KAPA Biosystems, Woburn, MA); 0.5 µl of each primer

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(100 nM), 1 µl template (extracted DNA) and DDW to complete to 25 µl. PCR protocol was: initial

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denaturation step at 95°C, followed by 40 cycles of 95°C for 30 sec; annealing temperatures as

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described in Table S3 for 30 sec; and 72°C for 30 sec. Acquisition was performed at the completion

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of each cycle, following a short (2 sec) step at 78°C to ensure primer dimer denaturation. Calibration

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curves for mcrA and pmoA, encode for functional genes at a known concentration with six serial

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dilution points (in steps of 10-fold). All runs included a no-template control. Calibration curves had

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R2 > 0.98, and the slope was between -3.0 and -3.9. Amplification reactions were carried out in a

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Rotor-GeneTM 6000 thermocycler (Corbett Life Science, Concorde, NSW, Australia). Primer

13C

53,54.

Double bond positions in FAMEs were identified by pyrrolidide

and the amount of PLFA carbon based on quantification via GC-FID

13C/(13C+12C)

13C/1000+1)

= R/(R+1), with R being derived

× RVPDB.

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sequences are detailed in table S3. Quality control values were exported into a Microsoft Excel

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worksheet for further statistical analysis.

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Results

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Reactive iron minerals extracted from the sediments demonstrated that they comprise 10-15% of the

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total iron (Fig. S2). Magnetite, an iron mineral containing Fe(II) and Fe(III) that can be dissimilatory

205

reduced by microbes as a product of iron reduction, was found in a concentration of 0.06% dw

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equivalent to 2 µmol g dw-1 at the top of the sediment core, and increased to 0.19% or 8 µmol g dw-1

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at the bottom. All other iron minerals (i.e. ferrihydrite, hematite, goethite and others) ranged from

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0.3% dw or 20-25 µmol g dw-1 at the top to ~0.4% dw or 35 µmol g dw-1 at the bottom part,

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respectively. The availability of these iron oxides is a basic prerequisite for iron-coupled AOM in

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Lake Kinneret.

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Measurements of δ13CDIC in the slurries without inhibitors and only with addition of

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methane and minerals) revealed no change during the first three months of the incubation (Fig. 1A).

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After ten months we observed a significant increase in δ13CDIC values, indicating the turnover of 13C-

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methane, while autoclaved controls remained unchanged throughout the experiment. Magnetite and

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hematite additions introduced the most dramatic increase in δ13CDIC values by up to 250‰. Increase

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of methane oxidation, as indicated by δ13CDIC values of up to 450‰, was found when molybdate was

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added to the slurries (Fig. 1B). During addition of molybdate the largest increase in δ13CDIC values

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occurred in incubations where amorphous iron was used, followed by hematite, goethite, and finally

219

magnetite. When BES was added to the slurries no positive deviations of δ13CDIC values was observed

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in all treatments (Fig. 1C), highlighting the essential role of methanogens during iron-coupled AOM.

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The natural slurry without any iron additions also showed an increase in δ 13CDIC values up to 80‰,

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which suggests that the inhibition of microbial sulfate reduction stimulates AOM even for samples

223

containing natural amounts of iron minerals.

13C-labeled

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Changes in δ13C values of PLFAs and intact ether-lipid derived hydrocarbons in sediment slurries are

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summarized in Table S2A and B. At the end of the experiment, the strongest

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observed for monounsaturated hexadecanoic fatty acids (C16:15 and a cluster including C16:19, C16:18

227

and C16:17, with the latter dominating) as indicators of bacteria in most active treatments, ranging in

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δ13C values between 440‰ and 3,200‰ compared to -47‰ at T0. By contrast, archaeal-derived

229

isoprenoid hydrocarbons phytane and biphytane revealed only marginal 13C-enrichment of 19‰ and

230

3‰ relative to T0, respectively. In accordance with the δ13CDIC data, fatty acids were 13C-enriched

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only in active treatments as opposed to the autoclaved control and those treatments where methanogen

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activity was inhibited by BES addition. When molybdate was added the

233

was significantly higher. Highest specific uptake with δ13C values of more than 3,200‰ was

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characteristically found for C16:15, which is depicted as a number next to various experiments in Figs.

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1A to C. Total 13C-uptake into PLFAs is presented in Table S2B and was highest for the C16:1 cluster

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(~2.8 to ~5 ng 13C gdw-1) and C16:15 (~0.7 to ~1.5 ng 13C gdw-1) in all experiments with molybdate

237

addition but especially high in the slurry experiment where only hematite was added (~3.6 and ~1.1

238

ng 13C gdw-1, respectively).

239

The net changes in δ13CDIC values, as well as methane and Fe(II) concentrations after 470 days are

240

displayed in Figs. 2A to C. Change in δ13CDIC values was highest for magnetite without any inhibitors

241

and highest for amorphous iron with the addition of molybdate (Fig. 2A). Methane concentrations

242

increased with time in all non-autoclaved slurries except those treated with BES (Fig. 2B), pointing

243

towards the co-existence of net methanogenesis and iron-coupled AOM. Methane concentrations in

244

the treatments with molybdate addition were lower by 100-300 µM than those without molybdate,

245

indicating enhanced methane consumption and supporting the most positive δ13CDIC values that

246

evidence enhanced AOM. Iron oxide mineral treated slurries demonstrated significant microbial iron

247

reduction and increase in ferrous iron by about ~20-50 µM over the course of the experiments with

248

and without molybdate addition (Fig. 2C). The high ferrous iron concentration in slurries with BES

13C-enrichment

13C-enrichment

was

of PLFAs

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addition and specifically in the autoclaved BES sample points towards abiotic reaction of BES with

250

iron minerals.

251 252

Figure 1: Change of δ13CDIC values over time in duplicate incubations using addition of 13C-labeled methane and a variety

253

of iron oxide minerals (amorphous iron, goethite, hematite, and magnetite) with and without inhibitors. (A) Without

254

inhibitor addition, (B) Inhibition of sulfate reduction by molybdate addition, and (C) Inhibition of methanogenesis by

255

BES addition. All sample types were incubated with and without sterilization (autoclaved and natural, respectively). The

256

colored marked numbers in all panels represent the δ13C value (‰) of the C16:15 fatty acid at the end of each experimental

257

type (magnetite was not measured). n.d.: samples where the determination of δ13C values of C16:15 was impossible due

258

to low concentrations. The analytical error is smaller than the symbol size.

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δ13CDIC change (‰)

A 450 400

No

inhibitors

350

BES

300

Molybdate

addition addition

250 200 150 100 50 0 -50

B 1200

CH4 change (µM)

1000 800 600 400 200 0 -200 C 120

Fe(II) change (µM)

100 80 60 40 20 0

Autoclaved

Natural Goethite Amorphous Hematite iron

Magnetite

259 260

Figure 2: Net change of (A) δ13CDIC values, (B) methane concentrations and (C) Fe(II) concentrations after 470 days

261

using addition of 13C-labeled methane and iron oxide minerals with and without inhibitors. Solid blue: without inhibitor

262

addition; Fence red: inhibition of methanogenesis by BES addition; Dot green: inhibition of sulfate reduction by

263

molybdate addition. All three sample types were incubated with and without sterilization (autoclaved and natural,

264

respectively) and in addition with different iron minerals (amorphous iron, goethite, hematite, magnetite). Positive

265

methane concentrations reflect net methanogenesis during iron-coupled AOM. The high ferrous iron concentration in all

266

slurries with BES including the autoclaved sample points towards additional abiotic reaction of BES with iron minerals.

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The copy number of the pmoA functional gene of methanothrophs at the end of the experiment is

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shown in Fig 3. In incubations with molybdate additions, there is a significant increase in pmoA copy

269

numbers by a factor between 2 and 10 relative to those where BES was added. This is generally

270

corroborating the trends of the DIC and lipid analyses but with the exception of higher pmoA copy

271

numbers found in the hematite incubation without additions. A

pmoA copy number/gr slurry

8.E+06 No inhibitors 7.E+06 BES addition Molybdate 6.E+06

addition

5.E+06 4.E+06 3.E+06 2.E+06 1.E+06 0.E+00

Natural Amorphous Goethite iron

Hematite

Magnetite

272 273

Figure 3: Copy numbers of the pmoA functional gene in the different treatments after 470 days. Solid blue: no inhibitor

274

addition; Fence red: inhibition of methanogenesis by BES addition; Dot green: inhibition of sulfate reduction by

275

molybdate addition. The copy number of pmoA in the original untreated sediment was about 0.4·10-6 per gram of slurry.

276

Complementary functional mcrA gene analysis of methanogens indicates a minor decrease in copy

277

numbers of methanogens when iron minerals were added to the slurries (Fig. S3). When BES was

278

applied, the concentration of mcrA was strongly reduced in all treatments, while molybdate additions

279

led to a slight decrease relative to the natural sample. An exception is again seen in the hematite

280

incubation. In general, copy numbers of mcrA had low variability across all slurries (Fig. S3).

281

Discussion

282

This study provides evidence for iron-coupled AOM in a slurry incubation experiment with sediments

283

from the deep methanogenic zone of Lake Kinneret based on turnover of 13C-labeled methane and

284

production of 13C-enriched DIC. In this sedimentary zone, sulfate and nitrate, two oxidants commonly

285

associated with AOM, are below the detection limit. The addition of various iron oxide minerals, 13 ACS Paragon Plus Environment

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286

including the less reactive but still conductive (electron transferring) forms hematite and magnetite

287

(e.g.44), led to a significant increase in methane turnover evidenced by significantly higher δ 13CDIC

288

values compared to experiments without iron additions (Fig. 1). Hereon, we explore the possible

289

microorganisms that could be involved in the process, clarify the potential relation to cryptic sulfur

290

cycling in sediments with sulfate levels below detection limit and define the availability of different

291

iron minerals to iron-coupled AOM in aquatic sediments.

292

Likely microbial candidates involved in iron-coupled AOM

293

Our findings highlight the essential role and participation of methanogens and methanotrophic

294

bacteria in the process of iron-coupled AOM. We provide for the first-time direct evidence of their

295

active involvement, and present a possible microbial reaction network in this highly reduced

296

sedimentary setting.

297

The role of methanogens was indicated by the addition of BES that completely stopped methane

298

production (Fig. 2C) as well as consumption of the added 13C-labeled methane, with the latter shown

299

by the lack of a positive change in δ13CDIC values (Fig. 1C, Fig. 2A). All other non-BES inhibited

300

slurry incubations yielded positive changes in δ13CDIC values and thus provide evidence of iron-

301

coupled AOM (Fig. 2B). The mcrA gene analysis shows that methanogens were found in all the

302

experiments but generally in lower numbers in the BES treated slurries (Fig S3).

303

The methanogens can be involved in the iron reduction as the ability of methanogens to reduce iron

304

oxides has already been shown in pure culture experiments 45,46 and the process also seems to compete

305

with methanogenesis 47. The capability of methanogens to switch to iron reduction could be due to

306

reactivation of iron minerals at nearly identical ΔG° for methanogenesis and iron reduction,

307

particularly for poorly-reactive iron oxides such as hematite that is present in Lake Kinneret

308

Therefore, at high concentrations of methane iron reduction coupled to methane oxidation could

309

become more favorable than methanogenesis, providing methanogens an advantage over iron-

310

reducing bacteria. Moreover, iron oxide can become a feasible substrate surface to methanogens due

48.

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311

to membrane-bound methanophenazines in some species. Methanophenazines are isoprenoid

312

quinones with known electron shuttling ability 49 that may overcome the physical barrier of reducing

313

iron minerals

314

involved in iron-coupled AOM could be Methanosarcinales that increased with depth in sediments

315

of Lake Kinneret 28. Archaea of the order Methanosarcinales are very promising players since also

316

other studies provided evidence that similar or related species are capable of coupling iron reduction

317

to the oxidation of methane in freshwater environments 25,52.

318

We cannot fully pinpoint the exact Methanosarcina species involved and their mechanistic

319

functioning at the moment, but refer to recent studies where intercellular

320

electron transport by ANME in sulfate-dependent AOM has been demonstrated, which might suggest

321

a similar fashion during iron-coupled AOM. However, ANME-1 and 2 were only found in very low

322

abundance in Lake Kinneret

323

The non-involvement of ANMEs is also supported by the very low 13C-enrichment found for intact

324

archaeal lipid derived phytane and biphytane (Table S2A), because such lipid biomarkers are usually

325

detected with much stronger imprint of the methane stable carbon isotope signature 43,55. Accordingly,

326

this very minor change in 13C-values of these lipids indicates that involved archaea dominantly use

327

a non 13C-enriched carbon source putatively being acetate or methylated substrates, which are both

328

accessible to archaea of the genus Methanosarcina.

329

The other most relevant microbial players involved in iron-coupled AOM are methanotrophic

330

bacteria. These are identified by very strong 13C-enrichment of and high 13C-uptake into indicative

331

monounsaturated PLFAs (Tables S2 A and B) going along with the increase in copy numbers of pmoA

332

functional genes of methanotrophs (Fig. 3), likely being Methylococcales as reported in this depth in

333

Lake Kinneret

334

lake sediments using combined PLFA- and DNA-stable isotope probing

335

included C16:19, C16:18, C16:17, and C16:15, which all have been reported to be found in type I

50,51.

28,

Possible methanogens known to contain methanophenazines and thus to be

28

53

and extracellular

54

and thus cannot be considered as likely participants in the process.

or more specifically Methylobacter species as reported for anaerobic sub-Arctic 56. 13C-labeled

fatty acids

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336

methanotrophs 57. This is while no significant 13C-enrichment was observed in 10Me-C16:0 (data not

337

shown), a fatty acid that has been characterized to be a diagnostic biomarker for various bacteria such

338

as Methylomirabilis oxyfera, Geobacter or Desulfobacter species 58–60. Moreover, as the fatty acids

339

were

340

participating bacteria directly or indirectly incorporate high portions of methane-derived carbon and

341

do not use DIC as main substrate as previously evidenced for sulfate-reducing bacteria involved in

342

AOM in marine

343

environments 61. A similar combined finding of diagnostic fatty acids of methanotrophs and pmoA

344

abundance was reported from the deep anoxic water column of Alpine Lake Lugano

345

authors described a bacterial methanotrophic community mainly related to Methylobacter species

346

being responsible for the methane consumption, also without the detectable contribution from

347

archaeal methanotrophs, near the zone of increasing ferrous iron concentrations. It was speculated,

348

based on anoxic laboratory incubation experiments in the dark, that there may be an alternative

349

electron acceptor system operating for methane oxidation other than free oxygen.

350

Methanotrophic activity was evident only in treatments where methanogens were not inhibited by

351

BES and was enhanced by molybdate addition. However, if the biochemical pathway for iron

352

reduction is disconnected from the methane production pathway BES should not stop the activity of

353

the methanogens 51. On the other hand, as mentioned above, they do not assimilate methane or its

354

carbon derivatives as a carbon source. This contrasting suppression of methanotrophic activity during

355

inhibition of methanogens thus highlights the interplay between the two groups of microorganisms.

356

Accordingly, iron-coupled AOM is likely performed by a complex sedimentary community with

357

methanogens, besides producing methane, being involved in reducing iron oxides and producing

358

intermediates that are required for the methanotrophic bacteria. Such interaction suggests that other

359

processes such as a full "back reaction" of methanogenesis or carbon isotope equilibration cannot be

360

held responsible 63–65, even though the rates of the AOM are pretty low.

13C-enriched

by more than 1000 ‰ relative to co-occurring DIC, it is very likely that the

43,55

or the intra-aerobic methanotroph Methylomirabilis oxyfera in freshwater

62.

There, the

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361

The net reaction of iron-coupled AOM could be described by Eq. 1 with iron oxides as terminal

362

electron acceptor and methane as electron donor.

363

1) CH4+ 8Fe(OH)3+15H+→ HCO3-−+8Fe2++21H2O

364

According to our experimental isotopic data, it seems that about half of the injected 13C-methane (i.e.

365

1.06 µmol) was converted to 13C-DIC, thus resulting in a significant change of the existing 13C-DIC

366

pool (i.e. 4.49 µmol, assuming ~10 mM DIC in 40 ml of slurry) and a δ13CDIC increase of ~240 ‰.

367

Based on the stoichiometry of 1:8 between methane and iron, the net reaction should produce about

368

200 µM Fe2+, which is indeed within the measured range, considering also precipitation of some of

369

the Fe2+ as siderite and other minerals 23,67.

370

A plausible mechanism for iron-coupled AOM that would be consistent with our combined

371

observations of BES inhibition and

372

partial oxidation of

373

running in reverse and reducing Fe(III) and transfer of the intermediates to the methanotrophs. Such

374

a process would circumvent the requirement of oxygen as electron acceptor for the methane oxidation,

375

as could be speculated from our data, but which does not have any basis. In order to gain metabolic

376

energy, the methanotrophs would have to couple the methyl group oxidation to iron oxide reduction

377

via a currently unknown pathway. Such a syntrophic transfer of electrons from methanotrophs to

378

methanogens could explain the stimulation of

379

conductive iron minerals hematite and magnetite (see discussion below) but which has to be further

380

explored in the future. No matter which mechanism will hold true, investigation of iron-coupled AOM

381

will certainly extend our global understanding of energy-limited processes because iron minerals are

382

very abundant in aquatic environments with high sedimentation rates such as lakes or continental

383

margins.

384

The competition between iron-coupled AOM and sulfur cycling

385

As iron minerals support the production of sulfate in a "cryptic" sulfur cycle

386

levels, sulfate could also be intermediately formed in concentrations that are below the detection limit

13C-methane

13C-incorporation

to

13C-labeled

ΔG°=~ –572 kJ/mol 66

into methanotroph biomass may involve the

methyl intermediates catalyzed by methanogens

13C-methane

oxidation by the addition of the

35

at low steady state

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387

(i.e. micromolar levels) and could thus sustain classical sulfate-dependent AOM 68. If AOM involves

388

microbial sulfate reduction and/or sulfur disproportionation in Lake Kinneret sediments, molybdate

389

addition should inhibit methane turnover in our experiment. This was not the case, and molybdate

390

addition rather led to increased positive changes in δ13CDIC values (Figs. 1C and 2A). Generally,

391

molybdate inhibits microbial sulfate reduction through an enzymatic reaction with ATP 69 as well as

392

elemental sulfur and thiosulfate disproportionation 70,and yet, molybdate has not been shown to have

393

any effect on methanogenesis in marine sediments

394

hand, if sulfate-dependent AOM is inactive and methane is turned over via iron reduction, as depicted

395

in Eq. 1, and sulfur and iron cycling is coupled by some cryptic redox cycle independent of methane

396

oxidation, sulfur cycling will compete with methanogenesis for available iron species. In such a case,

397

molybdate addition will slow down any sulfur cycling, thus accelerating iron reduction by

398

methanogens.

399

Our experimental results suggest that sulfate is not an intermediate formed through coupled Fe(III)

400

reduction and sulfide oxidation in the methanogenic zone of Lake Kinneret sediments, since

401

molybdate addition did not inhibit AOM, but rather enhanced it (Fig. 1B and 2A). The latter probably

402

relates to shutting down a competition between the sulfur and the iron cycles (Eq. 2) independent of

403

iron-coupled AOM. The inactivity of sulfate-driven AOM is in agreement with our natural profiles

404

of sulfate and other studies in deep sediments of continental margins and coastal environments, which

405

showed that methane oxidation is uncoupled from sulfate reduction 20,72.

406

The availability of different iron oxide minerals for iron-coupled AOM

407

The addition of different iron oxides provides important information about the availability of these

408

minerals with respect to AOM. Reduction of iron minerals occurs either by biotic or abiotic processes,

409

with the latter involving sulfide or humic acid oxidation 73. The rate of sulfide oxidation by different

410

ferric iron minerals was shown to be dependent on the mineral surface area and concentration, as well

411

as on the pH and concentrations of sulfide 74. Ferrihydrite was described as more reactive with sulfide

71

nor on iron-reducing bacteria 68. On the other

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412

than goethite and other minerals (ferrihydrite > geothite > hematite > magnetite) 73. Later, Poulton et

413

al.

414

The discrepancies between the two studies were likely due to different grain size and surface area 76.

415

Consistent across all studies, amorphous iron, including ferrihydrite, and goethite were shown to be

416

more available for reduction than hematite and magnetite, and this reactivity order was also expected

417

for biotic reactions. In light of our results, however, iron mineral additions give evidence that hematite

418

and magnetite are more available to AOM in aquatic sediments than amorphous iron and goethite

419

(Figs. 1A and 2A). The deviating availability makes sense if methanogens compete with sulfide

420

oxidizers for the different iron minerals. Iron reduction by sulfide oxidation is probably kinetically

421

favored relative to methane oxidation. Thus, more reactive amorphous iron and goethite are utilized

422

more rapidly in the competitive process of sulfide oxidation (Eq. 2) and are less accessible for iron-

423

coupled AOM (Eq. 1). However, in the natural environment of Lake Kinneret all of the iron minerals

424

of varying reactivity coexist (Fig. S2), allowing the competitive processes to occur simultaneously.

425

Using molybdate addition, sulfur cycling is completely inhibited, giving the rather slow iron-coupled

426

AOM process an advantage to utilize all iron minerals in the typical order. Alternatively, hematite

427

and magnetite were shown to transfer electrons better than other iron minerals in some cases 44,47,77,78

428

and thus may be more available to the AOM process due to these conductive characteristics, however

429

this speculation should be further explored.

430

Our results indicate that iron-coupled AOM appears in the deep methanogenic sediments, supporting

431

also suggestions in marine settings

432

microbial community composed of methanogens and methanotrophs. The calculated rate of AOM in

433

Lake Kinneret (13 nmol cm-3 per day) 31 is very similar to the average AOM rate from wetlands (20

434

nmol cm-3 per day)

435

methane was shown. There are considerations that AOM in freshwater environments consumes at

436

least 200 Tg methane per year 26, which equals to 50% of the methane emitted. As poorly-reactive

437

iron oxides are abundant in nature they likely play a significant role as electron acceptor during AOM

75

described a slightly different reactivity order (ferrihydrite > goethite > magnetite > hematite).

26,

19,20.

It co-exists with methanogenesis and is performed by a

where the role of AOM in freshwater environments as a gate keeper for

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438

in environments with low sulfate concentrations. Moreover, our findings may clarify the world wide

439

unexplained phenomena of Fe(II) increase in many deep sediments and may provide a novel globally

440

significant mechanism with implications for the Archean ferruginous world and for sustaining life

441

under highly-reducing low energy conditions.

442

Acknowledgements

443

We would like to thank B. Sulimani and E. Leibovich from Israel Oceanographic and Limnological

444

Research for their great assistance both in the field and the lab. We are also grateful for our skippers,

445

M. Diamond and O. Sabri and members of Orit’s and Ariel’s laboratories for all their help. Many

446

thanks go to A. Kamyshny and his students for their assistance with the iron extraction methods.

447

Much appreciation goes to D. Gat from Z. Ronen's lab for her assistance in qPCR work. We also

448

thank R. Aepfler, N. Meyer, S. Trojan and X. P. Mollar for support during lipid analysis. We

449

appreciate S. Turchyn and V. Orphan for their great comments on previous versions of the

450

manuscript. This research was funded partly by the Water Authority of Israel and the Israel Science

451

Foundation (#857-2016 to OS). The study was furthermore supported also by the Deutsche

452

Forschungsgemeinschaft through the Research Center/Cluster of Excellence “The Ocean in the Earth

453

System” (ME). Finally, we thank the editors and anonymous reviewers for their thorough reviews

454

and constructive comments that improved the paper significantly.

455

Supporting Information. Three tables and three figures.

456 457

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