Laguna (2022) 29: 133-143

ISSN 2185-2995

Methanogenic archaeal community structure in estuary sedimentsof the Onga River, northern Kyushu Island, Japan
Wipoo Prasitwuttisak1, Shingo Araki1 and Katsunori Yanagawa1*
Abstract: Methane, which contributes to global warming, is one of the microbial end-products ofanaerobic organic matter remineralization in anoxic sedimentary environments. Estuary sedimentwith high primary production is known as the most active methane source because the enhanced
microbial activity ultimately releases metabolic products such as methane and nutrients to theoverlying water. To date, microbial methane production was thought to be phylogenetically limited
to the archaeal phylum Euryarchaeota. However, advances in metagenomics-based studies haverevealed that unsuspected lineages of archaea may contain key enzymes for methanogenesis, which
expanded our view of methane metabolism. In this study, brackish water sediments of the Onga

River, northern Kyushu, Japan were examined to assess the diversity of methanogenic archaea,
through comparative phylogenetic analysis of 16S rRNA genes and functional genes necessary

for methane production. Members of Methanosarcinales were only detected in the 16S rRNA
gene amplicons, while the taxonomic classification of the functional genes showed the existenceof diverse archaeal lineages, particularly hydrogenotrophic Methanomicrobiales. Furthermore,

yet-uncultivated methanogens such as Verstraetearchaeota and Methanofastidiosales were also
detected, indicating the importance of hydrogen-dependent methane generation from methanol,

methylated amines, and dimethyl sulfide. Estuary methane production might be conducted by more
phylogenetically widespread archaea than previously thought. Therefore, clone library analysis forthe functional genes showed the potential to assess the diversity of methanogens not identified by

the 16S rRNA gene amplicon analysis, which may improve our understanding of methane origins inestuary systems.

Key words: estuary sediment, methane, methanogenic archaea, mcrA

greater than carbon dioxide. Natural sources of methane

Introduction

include anaerobic environments in the hydrosphere, such

Methane is one of the main contributors to greenhouseas wetlands, lakes, paddy fields, and oceans. Intestinal

effect because it has a warming potential 25 times

1

systems of ruminants and wood-feeding insects are

Faculty of Environmental Engineering, The University of Kitakyushu, Kitakyushu 808-0135, Japan.

* Corresponding Author

受付日：2022 年 6 月 3 日，受理日：2022 年 8 月 5 日，WEB 掲載日：2022 年 9 月 12 日

133

Wipoo Prasitwuttisak, Shingo Araki, and Katsunori Yanagawa

also known to supply large amount of methane. In

matter and nutrients from domestic wastewater (Egger etseveral substrates including hydrogen, formate, acetate,located at the downstream end of a river, which delivers

those habitats, methanogenic archaea can convertal., 2016). In addition, the brackish water of an estuary is

methylated compounds, and methanol into methane

large amounts of suspended solids to the estuary. It is(Conrad, 2009). Approximately 70% of the global

estimated that 95% of the suspended solid is deposited

supply of methane originates from microbial activity,

at an estuary during high and low tides when the water

which is presumably equal to as high as one billion tons

flow is slower. In particular, Japanese rivers tend to erode(Reeburgh, 2007). Methane cannot permanently persist

and form steep gradients because Japan correspondsin the atmosphere as it is lost through photochemical

to a relatively high rainfall region in the world. These

reactions with OH radicals, with a persistence time ofsuspended sediments are composed of clay minerals andup to 10 years. This is very short compared to the 5-200

organic matter. The organic portion is decomposed by

years for carbon dioxide, which raises concerns about

microbial aerobic respiration, which reduces dissolved

the short-term impacts of methane. However, methane

oxygen in the surface sediment environment. Finally,has been steadily increasing at about 1% per year

sulfate reduction and methanogenesis proceed as the lastsince the Industrial Revolution (Schaefer et al., 2016).

step of organic matter decomposition. For these reasons,

Therefore, it is a major challenge to study the suppression

although estuaries cover only 0.4% of the total oceanof methane in a long-term time scale framework, andarea, they could be major sources of methane emissions,

to comprehensively understand the methane sources,

accounting for about 75% of the methane released fromemission mechanisms, and fluxes.

the entire ocean (Bange et al., 1994).

The largest reservoir of methane exists beneath the

Recently, next-generation sequencing (NGS) has been

seafloor (Kvenvolden, 1988; Yanagawa et al., 2012).

widely applied in the field of environmental microbiologyhydrosphere and the atmosphere should be carefully

method allows us to explore microbial communities

Therefore, methane released from the seafloor to theto obtain a large number of gene sequences. This

monitored. However, its contribution is relatively small

and reveal complex interactions among many microbial

because of biological process in sediment, called

populations. Most of the NGS-based amplicon analysis

anaerobic oxidation of methane. In this reaction,

targets the 16S rRNA genes. Other highly conserved

anaerobic methane-oxidizing archaea and sulfate-genes such as rpoB, gyrB, and recA are also useful

reducing bacteria syntrophically oxidize methane toin determining taxonomic classification (Rajendhran

carbon dioxide (Borowski et al., 1996; Knittel andand Gunasekaran, 2011). To detect methane-producing

Boetius, 2009). It has been estimated that anaerobicarchaea, the mcrA gene encoding the alpha subunit

oxidation of methane consumes 90% of the methaneof the methyl-coenzyme M reductase that catalyzes

released f rom ma r ine sediments ( Valentine andthe last step of methanogenesis, is frequently used in

Reeburgh, 2000). Furthermore, competition between

molecular ecological analysis (Hales et al., 1996). The

methanogenic archaea and sulfate-reducing bacteria ismolecular biological evidence has shown that the archaea

indirectly involved in the suppression of methane flux.

involved in methane production span seven orders:

Methanogenic archaea compete with sulfate-reducing

Methanobacteriales, Methanocellales, Methanococcales,

bacteria for hydrogen and acetate, and sulfate-reducing

Meth a nom assiliicoccales, Meth a nomicrobiales,

bacteria tend to dominate due to their higher substrate

Methanopyrales, and Methanosarcinales. However,affinity (King, 1984). Therefore, methanogenic archaea

recent advances in microbiology have revealed thatare not detected in typical sulfate-bearing shallow

several uncultured archaeal lineages contain genes

sediments.

involved in methanogenesis, suggesting that archaea

Estuaries and coastal areas are distinctive environments

engaged in methanogenesis are phylogenetically more

where the enhanced supply of organic matter due

widespread than previously thought. For instance,

to active biological production causes promotion ofm e t h a n e p r o d u c t io n p o t e nt i a l of "C a n d i d a t u smethane production. These environments are susceptible

Bathyarchaeota" (formerly known as the Miscellaneous

to eutrophication because of the direct input of organic

Crenarchaeota Group, MCG) were recently identified
134

Methanogenic archaeal community structure in estuary sediments of the Onga River, northern Kyushu Island, Japan

based on genome-centric metagenomics (Evans et al.,µL reaction volume with initial denaturation at 98 °C

methods have successfully detected the mcrA gene,annealing at 50 °C (for universal 16S rRNA gene) or 52

2015). On the other hand, conventional PCR-dependentfor 2 min, 50 cycles of denaturation at 98 °C for 10 s,presumably from the Ca. Bathyarchaeota, in the°C (for archaeal 16S rRNA gene) for 45 s, and elongationhydrothermal sediments of Yellowstone National Parkat 72 °C for 30 s. The mcrA gene, a functional key gene

(McKay et al., 2017). The construction of a PCR clone

for methanogenesis, was quantified using SYBR Green-

library focusing on a specific functional gene remains

based qPCR assay with the specific primers (ME3MF

a useful tool for exploring microbial populations, while

and ME2r’, Nunoura et al., 2008) and MightyAmp for

it is sometimes not suitable for searching unknown

Real-Time PCR (TaKaRa Bio) under the following

methanogenic lineages. In this study, we focused on

amplification conditions: initial denaturation at 94 °C

the methanogenic archaea in brackish environment by

for 2 min, 40 cycles of denaturation at 94 °C for 40 s,comparing the 16S rRNA gene amplicon analysis withannealing at 52 °C for 30 s, and elongation at 68 °C for

the functional gene analysis based on the clone library

1 min. All targeted gene abundances were normalized toconstruction.

the ROX reference dye and quantified in triplicate using
a real-time PCR system qTOWER3 G Touch (Analytik
Jena).

Materials and Methods
Sample collection and preparation

Microbial community composition analysis based onRiver, northern Kyushu (33°53’24.2’’ N, 130°40’26.5’’

To determine the microbial community composition,

16S rRNA gene and mcrA gene

Samples were collected in the estuary of the Onga

E). The Onga River is the most important source ofthe hypervariable V3–V4 region of the 16S rRNA geneof about 944×10 6 m 3 yr-1. On August 16, 2018, surface

MightyAmp DNA Polymerase Ver.3 (Takara Bio) and the

freshwater flowing into the Hibiki Sea, with a flow rate

was PCR-amplified from the extracted DNA using

sediments were collected using a cylindrical corer

universal primers (515F/806R, Caporaso et al., 2011).

(Wildco, Yulee, FL, USA) from the estuary of the Onga

The amplification protocol comprised initial denaturation

River. The temperature and salinity at the sampling site

at 98 °C for 5 min, then 35 cycles of denaturation atwere 24.9°C and 1.2%, respectively. Sediment layers were

98°C for 30 s, annealing at 55°C for 30 s, extension

sampled at depths of 0-1, 1-2, 2-3, and 3-4 cm. Samples

at 68°C for 30 s, and a final extension at 68 °C for 5

for molecular biological analysis were kept at -80°C untilmin. The amplified products were purified, indexed,further processing.

and sequenced using the Illumina MiSeq platform. The

acquired data were processed using QIIME2 (Bolyen

Quantification of microbial gene abundance

et al., 2019). The mcrA gene was amplified using a

To estimate the microbial biomass in the samples, gene

specific primer set as described in real-time quantitative

quantification by real-time quantitative polymerase

PCR. After gel extraction and purification, the PCR

chain reactions (qPCR) was performed based on

products were used to generate a clone library as

previously described methods (Yanagawa et al., 2019).

previously described (Yanagawa et al., 2019). Molecular

Prokaryotic DNA in sediment samples was extracted

phylogenetic tree of the mcrA gene was constructedusing the DNeasy PowerSoil Kit (Qiagen) according

using ARB software (Ludwig et al., 2004). Molecular

to the manufacturer’s instructions. Prokaryotic 16S

phylogeny and compositional ratio were determined byrRNA gene numbers were quantified using the Taqman

referring to known sequences in the database at the 95%

probe-based qPCR method with the universal primer-

dissimilatory cut-off levels. The mcrA gene sequences

probe set (Uni340F/Uni806R/Uni516F probe), thewere deposited in the DDBJ/EMBL/GenBank databases

archaea-specific primer-probe set (Arch349F/Arch806R/

under the accession numbers, LC720689–LC720720.

Arch516F probe, Takai and Horikoshi, 2000), and theinnuDry qPCR MasterMix Probe (Analytik Jena AG,

Germany). The amplification was conducted in a 20135

Fig. 1 Prasitwuttisak et al.
Wipoo Prasitwuttisak, Shingo Araki, and Katsunori Yanagawa

(a)

(b)

(c)

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① Euryarchaeota; Methanomicrobia

Genes g-1 sediment
Prokaryotic 16S rRNA gene
Archaeal 16S rRNA gene

② Woesearchaeota

Archaea
Bacteria

Archaea⑪ Parcubacteria⑫ Planctomycetes③ Acidobacteria⑬ Proteobacteria; Alphaproteobacteria④ Actinobacteria⑭ Proteobacteria; Betaproteobacteria⑤ Bacteroidetes⑮ Proteobacteria; Gammaproteobacteria⑥ Chloroflexi⑯ Proteobacteria; Deltaproteobacteria⑦ Cyanobacteria⑰ Proteobacteria; Epsilonproteobacteria⑧ Firmicutes⑱ Verrucomicrobia⑨ Ignavibacteriae⑲ Other(Bacteria)⑩ NitrospiraeFig. 1. (a) Number of microbial 16S rRNA genes in the estuary sediments quantified

by qPCR. The number of genes g-1 sediment was plotted logarithmically in the depth

direction. Error bars in the plots indicate the standard deviation in triplicate assays. In
some cases, the error bars are hidden within the symbols. (b) Microbial community

composition at the domain level based on 16S rRNA gene amplicon analysis. (c)Microbial community composition at the phylum and class level.

Microbial community structures

Results and Discussions

Microbial community composition in each sediment

Microbial gene abundance

sample was determined by the 16S rRNA gene amplicon

Microbial gene distribution against sediment depth

sequencing. In the present study, a total of 12,171

was quantified by qPCR. Prokaryotic 16S rRNA genereads were obtained from the sediment samples withnumbers ranged from about 4.2×10 to 1.3×10 genes g
9

10

an average length of 464 bp. Bacterial communities-1

sediment (Fig. 1a). The archaeal gene numbers ranged

were dominant in the estuary sediments, at over 98.5%,

from 5.0×10 to 9.6×10 genes g sediment. The highest
77

and archaea accounted for less than 1.4% (Fig. 1b). In-1

archaeal gene abundance was found at a depth of 3-4

comparison, this ratio was consistent with the result

cm among the analytical samples. The ratio of archaeal

obtained from qPCR analysis (0.6-1.3%).

16S rRNA genes to prokaryotic 16S rRNA genes was

Ta xonom ic classi f icat ion at t he phylu m level

0.6-1.3%, indicating archaea were low in abundance

showed that Bacteroidetes and Proteobacteria wereat all depths. These values are generally consistentdominant among the bacterial population (Fig. 1c).

ecosystems around the world (Liu et al., 2018).

Gammaproteobacteria and Deltaproteobacteria. The

with relative abundances obtained in other estuarine

The dominant members in the Proteobacteria were
Methanomicrobia, methanogenic archaea belonging
to the Euryarchaeota, were detected with a proportion
136

Fig. 2 Prasitwuttisak et al.

Methanogenic archaeal community structure in estuary sediments of the Onga River, northern Kyushu Island, Japan

0

(a)

(b)
(26)

1

Depth (cmbsf)

(25)
2
(32)
3
(21)
4 7
10

108

Genes g sediment-1

mcrA genes

Methanomicrobiales

Methanosarcinales

Methanobacteriales

Methanocellales

Methanomassilicoccales

Methanofastidiosales

Verstraetearchaeota

Fig. 2. (a) Vertical distribution of the mcrA gene abundance. The number of genes g-1
sediment was quantified by qPCR and plotted logarithmically in the depth direction.

Error bars in the plots indicate the standard deviation in triplicate assays. In some cases,
the error bars are hidden within the symbols. (b) Phylogenetic composition of the mcrA

gene based on the phylogenetic affiliation shown in Fig. 3. The number of mcrA clones isindicated in the brackets.

of 0.4 - 0.7%. T hese a rchaea were ta xonom icallysediments at depth of 0-3 cm (Fig. 2a). This indicatedMethanosarcinales. In addition, Ca. Woesearchaeota

the surface layer of the sediments that are easily exposedclassified to the family Methanosaetaceae in the orderthat large amounts of the mcrA gene were distributed in(formerly called DEVEG-6) was detected at the top

to oxygen. In organic-rich sediments, aerobic bacteria

layer of sediment with a ratio of 1% (Fig. 1c), as shown

actively consume molecular oxygen, resulting in thein the other oxygen-limited environments (Liu et al.,formation of anaerobic environments and the production2018). The deltaproteobacterial sulfate-reducing bacteria,of methane as the final product of organic matter

affiliated with Desulfobacterales, Desulfuromonadales,

decomposition. The nucleotide sequences of the amplified

and Desulfarculales, were dominant throughout themcrA gene were determined using a clone library method.

sediment core. Next-generation sequencing has proved to

Phylogenetic composition of the mcrA gene sequences

be a useful tool used for a comparison of the microbial

obtained in this study is shown in Fig. 2b, and therare populations that are probably difficult to identify bytree is shown in Fig. 3. At all depths of sediment, mostcommunity among multiple samples and detection ofmolecular phylogenetic classification on the phylogenetic

conventional community composition analysis based onof the obtained mcrA genes were classified into the orderthe clone library method.

Methanomicrobiales, accounting for 81.3-92.3% of

the total sequences. Methanosarcinales-derived mcrA

Phylogenetic diversity based on mcrA gene

genes were the second most abundant, accounting for

Quantitative real-time PCR showed that the mcrA gene

3.8-12.5%. The Methanosarcinales mcrA contained

ranged from 2.4×10 to 6.6×10 genes g of the surface
7

7

genes closely related to the family Methanosaetaceae,

-1

137

Fig. 3 Prasitwuttisak et al.
Wipoo Prasitwuttisak, Shingo Araki, and Katsunori Yanagawa

group e (ANME−2a)

36

Methanococcoides

95

group f (ANME−3)
47

Methanosarcina barkeri Fusaro, Y00158
Methanosarcina mazei MT, AY260440
Methanosarcina lacustris MS, AY260439
ONG02_mcrA117 (2)ONG04_mcrA109
group c−d(ANME−2c)

57

61

30
65

96
55

33

63
97

29
40

77
74

91
96

89
45

93
75
52

87
98

Rice cluster I MRE50, AY683452
Wakasa Bay sediment WB_Jul_mcrA_21, AB775749
Order Methanocellales
Methanocella paludicola SANAE, AB300467
ONG_02_mcrA205
Methanomassilicoccus luminyensis, HQ896500
ONG_03_mcrA210
Paddy soil clone, AB301345
ONG03_mcrA05
Order MethanomassilicoccalesSouth China Sea sediment E702S−01, KF595310
ONG03_mcrA121
Methanogranum caenicola, AB749768
Methanopyrus kandleri AV19, AE009439
59
Budo3_mcrA09
ONG02_mcrA07
Sediment K2_71, JX942713
Ca. Verstraetearchaeota
Ca. Methanomethylicus mesodigestum V1
Ca. Methanosuratus petracarbonis V4
Methanococci
Methanothermaceae

54

Methanonatronarchaeia

40

66

Order Methanosarcinales

ONG01_mcrA08
Sediment clone M1_66, JX942646
Estuary
Estuary sediment 6−3_FLINP_1, JN684176 Group
Riparian soil clone PMmcr23, AJ607421

ONG02_mcrA101
ONG03_mcrA116
ONG03_mcrA101 (2)Methanosaeta concilii DSM3671, AF313802
Methanosaetaceae
78
Methanosaeta harudinacea 6Ac, AY970349
97
Peru Trench 1230A2, EU161879
Soda lake S_Orig_10, LK391606
45
ONG02_mcrA05
55
ONG03_mcrA111
29
ONG02_mcrA06 (2)25
ONG02_mcrA102 (17)
ONG02_mcrA104 (7)1535
ONG02_mcrA108
55
ONG01_mcrA115 (3)ONG01_mcrA18
83
26
ONG02_mcrA123 (4)68
ONG03_mcrA08 (5)43ONG03_mcrA120
44
ONG04_mcrA103
48
Mire soil A57H12, LN716803
Order Methanomicrobiales
ONG02_mcrA107 (3)92River sediment 750Bmcra9, KR107093
87
River sediment ZmcrA60, KR107102
76
ONG02_mcrA119 (10)64
ONG02_mcrA109
40
FenQMCR, AJ489777
41
Paddy soil J9P100, KF760943
ONG02_mcrA120
36
ONG01_mcrA13
96
ONG_04_mcrA212
89
Methanofollis liminatans, KM041257
ONG_04_mcrA216
34
28
Methanoculleus bourgensis MS2, AB300787
Methanolinea tarda NBRC102358, AB703641
87
ONG_02_mcrA202
48
96
Methanospirillaceae
98

24

Methanosarcinaceae

60
43
67
59

Biogas plant H1RTCR208, DQ260483
ONG01_mcrA19
Methanobacterium formicium BRM9, CP006933
Order Methanobacterales
Methanobacterium MO−MB1, AB598291
Methanobrevibacter arboriphilus DSM7056, AB300777
Methanothermobacter wolfeii NBRC100332, AB703638
ONG_04_mcrA211
biogas plant C10RTCR540, DQ261748
Order Methanofastidiosales
Munical wastewater sludge mcrA_dig_E17, EU980410
mcrA group a−b (ANME−1)
Ca. Bathyarchaeota

0.10

Fig. 3. Phylogenetic tree of the mcrA gene sequences detected in the estuary sediments.
Only one representative of sequence group >95% identical is shown in this tree. The
parenthetic numbers show the total number of phylotypes. The sequences obtained in thisstudy are shown in the underline. Scale bar indicates the number of substitutions per site.

138

Methanogenic archaeal community structure in estuary sediments of the Onga River, northern Kyushu Island, Japan

which were also detected as minority by 16S rRNA geneare capable of acetoclastic methanogenesis, whichof Methanocellales and uncultured methanogenic

atmospheric methane. Members of Methanosarcinales

amplicon analysis (3.8%). At a depth of 0-1 cm, members

is thought to be an important factor for increasingarchaea of Ca. Verstraetearchaeota (previously known

also use other substrates such as CO 2 /H 2 , formate,

TMCG) were present in about 4% of the total sequences.

The Methanosaetaceae were detected based on bothas Terrestrial Miscellaneous Crenarchaeota Group,and methyl compounds (methanol and methylamine).

In addition, Methanomassiliicoccales (6.2%) andthe 16S rRNA gene amplicons and mcrA gene clone

Methanofastidiosales (4.7%) were detected at a depth

libraries. They have been known to utilize only acetateof 2-3 cm and 3-4 cm, respectively. This suggests thatas a methanogenic substrate (Liu and Whitmann, 2008).

a highly diverse methanogenic archaea community

Methanobacteralaes-related mcrA genes were detected

was not recovered by the 16S rRNA gene amplicon

at a depth of 0-1 cm. Most of them have been known toanalysis in this study. It should be noted that the mcrA

use CO2/H2 and formate (Oren, 2014b). The mcrA genes

sequence ONG01_mcrA08 obtained from the top-mostfrom Methanocellales and Ca. Verstraetearchaeota wassediment (0-1 cm) showed a close relationship to only

found at a depth of 1-2 cm. All the isolated species ofthree sequences. The closest relatives were reported from

Methanocellales are known to reduce CO2 with H2 (Sakai

estuarine sediments in China and Germany (accession

et al., 2014). Ca. Verstraetearchaeota were frequently

number JX942636 and JN684176, respectively) with andetected in anaerobic environments with high methane

about 92.1% similarity. The other sequences showed

flux. Recently, the metagenomic analysis revealed that

remarkably low similarity (less than 82%) and formed

they had potential to produce methane from methanol,

their own cluster (Estuary Group on the phylogenetic tree

methanethiol, and methylamine (Vanwonterghem et al.,in Fig. 3). For the mcrA gene sequence, it is suggested

2016). The Methanomassiliicoccales, methanogenicthat the average similarity was 88.9% at a genus level andarchaea in the phylum Thermoplasmata (Iino et al., 2013),

was 83.5% at a family level (Steinberg and Regan, 2008).

was detected at a depth of 2-3 cm. They have been found

Therefore, the Estuary Group likely represents a distinct

in animal intestines, wetlands, and sewage treatment

lineage at the family level.

plants. Methanomassiliicoccales are known to generatemethane from methanol, methylamine, and dimethyl

Potential methane cycle in brackish water sediments

sulfide by using H 2 as an electron donor dependently

In this study, the Methanosaetaceae were detected(Lang et al., 2015). The Methanofastidiosales, a lineage

based on 16S rRNA gene amplicon analysis while thepreviously referred as WSA2 or Arc I (Chouari et al.,mcrA gene cloning analysis recovered more diverse

2005), were observed at a depth of 3-4 cm. This groupsequences spanning 7 phylum- or order-level lineages

has been reported in freshwater, marine sediments,

such as Methanosarcinales, Methanomicrobiales,

contaminated groundwater, and bioreactors. Recently,

the metagenomic analysis showed that they reduced

M e t h a n o c e l l a l e s, M e t h a n o m a s s i l i i c o c c a l e s,
Methanobacterales, Methanofastidiosales, and Ca.

methylated thiol for methane generation since none of

Verstraetearchaeota. This discrepancy may be due tothe essential genes in CO 2 reduction and acetoclastic

the low coverage of the 16S rRNA gene-specific PCR

methanogenesis pathway were detected (Nobu et al.,primers for the known methanogen sequences in the2016).

study site. Members of the Methanomicrobiales were

Our results suggested that surface sediments in brackishdominant based on the mcrA gene cloning. Most ofwater could be a suitable site for methanogenesis.

which produces methane from H 2 and CO 2 (Liu andmethanogenic archaea compete for acetate and hydrogenthem are known to be hydrogenotrophic methanogens,

It is well known that sulfate-reducing bacteria andWhitman, 2008). The second most dominant group wasin sulfate-containing environments, such as the seafloor,

Methanosarcinales, including Methanosarcinaceae

and sulfate-reducing bacteria can utilize them atand Methanosaetaceae. They were widely detected

lower concentrations than methanogens according toin major sources of methane emissions such as ricethermodynamic calculations. Thus, methanogenesis ispaddies, permafrost, and peat bogs (Oren, 2014a). They

less likely to proceed in sulfate-replete zones (Lueders et139

Wipoo Prasitwuttisak, Shingo Araki, and Katsunori Yanagawaal., 2001). Nonetheless, several studies have shown thatfor environmental microbiology. This approach has(Dale et al., 2008; Knab et al., 2008; Sela-Adler et al.,in environmental sample. However, when targeting

methane was detected in surface sulfate-rich sediments

made it possible to detect minor microbial populations2017). This is attributed to active methanogenesis usingrare populations, less than a few percent, multiple

specific substrates not used by sulfate-reducing bacteria,

methods should be applied for cautious verification.

such as methanol, methylamine, methanethiol, andFor example, new approaches for exploring functional

dimethyl sulfide (Oremland and Polcin, 1982). Since

genes in the pool of nucleotide sequences obtained

the present study site is a sulfate-rich environmentby metagenomic analysis have allowed researchers to

supplied by seawater, the methanogenic archaea detected

construct genome bins (Speth and Orphan, 2018). For

in our samples likely utilized those non-competitive

detection of methanogenic archaea, PCR amplification

substrates. In fact, methanogenic archaea with thetargeting the mcrA gene is still an effective method, asability to use methyl compounds have been detected

applied in this study and previous research (Wilkins

based on the mcrA gene analysis. The methylotrophic

et al., 2015). It should be noted that PCR-dependent

methanogens can be divided into two groups based

methods do not always detect all target populations dueon the presence of cytochromes. Methanosarcinales

to primer biases. Since the discovery of methanogenic

oxidizes methyl groups to CO2 via cytochrome, whereas

potential besides Euryarchaeota, i.e., Ca. Bathyarchaeota

Methanomassiliicoccales does not use cytochromes but

and Ca. Verstraetearchaeota, primer selection should

depend on hydrogen (Thauer et al., 2008). In addition,

be reconsidered to detect the potential methanogenic

Ca. Bathyarchaeota is thought to use hydrogen toa rchaea. T he present st udy showed that diverse

produce methane from methanol, methylamine, andmethanogenic archaeal components were recovered bymethyl sulfide (Evans et al., 2015). In this study, theapplying the frequently used mcrA primers.

Methanomassiliicoccales, Verstraetearchaeota, andMethanofastidiosales were expected to exhibit similar

Conclusionshydrogen-dependent metabolism. We suggest that theselineages perform methylotrophic methanogenesis andIn this study, we analyzed the microbial community

supply methane to the surface sediment in the study site.

compositions in brackish water sediments. Next-

methane (AOM) is a well-known biodegradation processclassical molecular cloning targeting the mcrA geneIn the marine environment, anaerobic oxidation ofgeneration sequencing of the 16S rRNA gene andusing sulfate as an electron acceptor. The 16S rRNA

were used to examine the potential of biogenic methanegene amplicon analysis and the mcrA gene clone library

production. The 16S rRNA gene amplicon analysis

method used in this study can detect the anaerobic

detected only the Methanosaetaceae, whereas the mcrA

methanotrophic a rchaea as well as methanogens

gene cloning analysis recovered more diverse sequences

our samples. Hence, AOM may be less likely to proceed

new candidate family-level lineage. Although the 16S(Yanagawa et al., 2019), but they were not detected inspanning 7 phylum- or order-level lineages, including a

in this brackish water environment where dilution ofrRNA gene-based sequencing is often regarded as theseawater by freshwater inflow is variable. If AOM

definitive method for microbial community analysis,

does not occur, the methane produced in the surface

this study suggested that diversity of minor populations

sediments will directly escape into the upper water andshould be assessed in combination with conventional

the atmosphere. Alternatively, coupling reactions ofcloning methods based on functional genes.

AOM and denitrification have been reported from river
sediments and intertidal zones (Shen et al., 2019; Wang

Acknowledgements

et al., 2019). Currently, mechanisms of the methane

consumption in brackish water environments are not

This work was supported in part by the Japan Society

deeply understood.

for the Promotion of Science (JSPS) KAKENHI (Grant

generation sequencing has become a major technique

Foundation.

Microbial community composition analysis using next-

Number 17K18808 and 20K05404) and the Sumitomo

140

Methanogenic archaeal community structure in estuary sediments of the Onga River, northern Kyushu Island, Japan

blanket bog peat by PCR amplification and sequence

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