(2021) 8:62
Urai et al. Prog Earth Planet Sci
https://doi.org/10.1186/s40645-021-00450-7

PAPER WITH FULL DATA ATTACHED

Progress in Earth andPlanetary Science

Open Access

Detection of planktonic coenzyme factor
430 in a freshwater lake: small‑scale analysis
for probing archaeal methanogenesis
Atsushi Urai1,2* , Makoto Matsushita1,3, Ho‑Dong Park4 , Hiroyuki Imachi5 , Miyuki Ogawara5,
Hiroki Iwata4 , Masanori Kaneko1,3 , Nanako O. Ogawa1 , Naohiko Ohkouchi1 and Yoshinori Takano1*

Abstract
We present the first data describing molecular evidence of planktonic coenzyme factor 430 (hereafter referred to asF430), a key signature of methanogenic archaea, obtained from a water column sample in a freshwater lake in Japan.
We report concentrations of native F430 ranging from 6.8–35 × ­102 femto mol g-wet−1 and 8.5–86 × ­102 femto mol
g-wet−1 in the water column and core-top sediment, respectively. Among these profiles, the epimer F430 of the deac‑
tivated chemical formula was very low overall in both planktonic and benthic environments. Small subunit (SSU) rRNA
gene sequencing revealed that the planktonic microbial community was clearly different from that of the benthic
sediment. Planktonic cyanobacteria (e.g., Microcystis) were predominant in the water column, whereas a wide varietyof bacteria and archaea, including methanogens (e.g., Methanobacterium, Methanoregula, Methanothrix, Methanosarcina, and Methanocella), were observed in the core-top sediment. These results suggest that the planktonic cyano‑bacterial community may be rapidly degraded at the water–sediment interface driven by activated benthic microbial
heterotrophic processes.
Keywords: Planktonic methanogen, Coenzyme F430, mcrA, Lake Suwa, Surface hydrosphere
1 Introduction
Freshwater lakes are considered one of the main
natural sources of methane (­CH4) emissions in terrestrial environments, accounting for 6–16% of C
­ H4
originating from natural sources (e.g., Bastviken et al.
2004; Cole et al. 2007; Holgerson and Raymond 2016;
Günthel et al. 2019). The major ­C H4 fraction released
from freshwater lakes is produced by methanogenic
archaea in anoxic sediments, and this is the terminal step of organic matter decomposition (e.g., Zepp
Falz et al. 1999; Chan et al. 2005; Thauer et al. 2008;
Conrad 2009; Borrel et al. 2011; Bukin et al. 2018).
Among these biogeochemical processes, heterotrophic*Correspondence: uraia@jamstec.go.jp; takano@jamstec.go.jp
1
Biogeochemistry Research Center (BGC), Japan Agency for Marine-Earth
Science and Technology (JAMSTEC), Yokosuka, Japan
Full list of author information is available at the end of the article

microbes degrade organic matter into H­ 2, ­CO2, acetate,
and methylated compounds, which are then adopted
as the principal substrates for hydrogenotrophic, aceticlastic, or methylotrophic methanogenic pathways bymethanogenic archaea. The ­C H4 occurring in anoxic
sediments then diffuses into the atmosphere or is oxidized via anaerobic or aerobic microbial processes in
the lacustrine water column (e.g., Bastviken et al. 2002;
Thauer et al. 2008; Kojima et al. 2014; Deutzmann et al.
2014; Donis et al. 2017; Iwata et al. 2018).
To date, biogeochemical evidence of C
­ H4 accumulation in oxygen-saturated freshwater and marine environments, commonly known as the methane paradox, has
emerged (e.g., Repeta et al. 2016; Fernández et al. 2016;
Tang et al. 2016; Sasakawa et al. 2008; Günthel et al.
2020). Three main hypotheses have been proposed to
explain this enigmatic phenomenon: (1) methanogenesisby methanogenic archaea in anoxic microenvironments,© The Author(s) 2021. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which
permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to theoriginal author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images orother third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line
to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory
regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of thislicence, visit http://​creat​iveco​mmons.​org/​licen​ses/​by/4.​0/.

Urai et al. Prog Earth Planet Sci(2021) 8:62

Page 2 of 17

such as detritus or animal guts (e.g., Oremland 1979;
Burke et al. 1983; de Angelis and Lee 1994; Schmale et al.
2018; Wäge et al. 2020); (2) release of ­CH4 as a byproductof the bacterial decomposition of potential precursors(e.g., methylphosphonate and dimethylsulfoniopropionate) under aerobic conditions (e.g., Damm et al. 2010;
Wang et al. 2017; Khatun et al. 2019); and (3) methanogenesis by methanogenic archaea associated with photoautotrophic consortia in lacustrine environments (e.g.,
Grossart et al. 2011; McGinnis et al. 2015; Li et al. 2021).
In addition to the abovementioned sources, we note theother origins of seep methane derived from deep terrestrial and/or oceanic sources along with some geologicalfactors (e.g., Milkov and Sassen 2002; Naudts et al. 2006;
Ritt et al. 2010; Valentine 2011 and the literature therein).
Within the context of planktonic methane production,
Grossart et al. (2011) reported the coexistence of planktonic methanogen and cyanobacteria in the water column of an oligotrophic lake (Lake Stechlim, Germany)
based on molecular analyses targeting the small subunit(SSU) rRNA gene and the methyl coenzyme M reductase A gene (mcrA) (cf. methyl coenzyme M reductase,
McGinnis et al. 2015). It has been suggested that thesecyanobacterial blooms may stimulate benthic ­CH4 production in sediment by increasing the supply of organic
matter (Wang et al. 2006; Yan et al. 2017). In addition,Bižić et al. (2020) demonstrated C­ H4 production via
pure cultures of cyanobacteria living in marine, freshwater, and terrestrial environments. Although it has beensuggested that certain versatile methanogenic archaea
thrive in anoxic microenvironments within planktonic

cyanobacterial consortia (Batista et al. 2019) and/or in
the interior of floating fecal pellets (Wäge et al. 2020), theentire ­CH4 production process in water column environments remains unclear.
To elucidate enigmatic planktonic methane biogeochemistry, we applied a new tool, namely, archaeal
methanogen-specific coenzyme factor 430 (F430), withultrasmall-scale approaches (e.g., Takano et al. 2013;
Kaneko et al. 2014, 2016). F430 is a hydrocorphinoid
nickel complex and is the prosthetic group of methylcoenzyme M reductase, which catalyzes the final stepof all methanogenesis pathways (e.g., Diekert et al. 1981;
Thauer et al. 2008). F430 quantification indicates theongoing activities of methanogenic archaea via rapid
decomposition into its relic forms after the death of thesearchaea (e.g., Inagaki et al. 2015; Urai et al. 2021). To ourknowledge, this is the first study to report the planktonic
F430 concentration in a freshwater lake environment.
Molecular SSU rRNA and mcrA gene analyses were also
performed to assess the microbial community structure
in both planktonic and benthic prokaryotic habitats.

2 Materials and methods
2.1 Geological setting of Lake Suwa

Lake Suwa is located in Nagano Prefecture in the central
part of Honshu Island, Japan, on the Itoigawa-Shizuoka
tectonic line (Fig. 1). The lake exhibits a surface area of
13.3 ­km2. The mean and maximum depths are 4.3 and6.4 m, respectively, with a water catchment area of 513­km2. The lake is a typical Japanese eutrophic lake affectedby anthropogenic impacts originating from nearby cities,

Yokokawa
River

Togawa Riv.

37oN
Sampling point
Nagano

Tokyo

Kyoto

NW Pacific

135o

140oE

TenryuRiv.

2 km

Lake Suwa

Kamikawa
Riv.

Miyakawa Riv.

Fig. 1 Map of the study site location. Lake Suwa is located in the central part of Honshu Island, Japan (36°2′46.92″N, 138°6′30.94″E). Samples werecollected along the southeastern shore of Lake Suwa

Urai et al. Prog Earth Planet Sci(2021) 8:62

despite being surrounded by mountains. The lake attains
a high sedimentation rate (~ 1 cm ­year−1) of organic-richsediments (e.g., Nakazato et al. 1998; Suwa Construction
Office 2019). In addition, cyanobacterial blooms, particularly those caused by Microcystis spp., have regularly
occurred during the summer since the 1970s (Park et al.
1993, 1998; Watanabe et al. 2012). In an earlier study, we
confirmed active ­CH4 emissions derived from the surface
sediments of Lake Suwa (Iwata et al. 2020; Additional
file 1: Movie S1).
2.2 Sampling procedure for water, planktonic microbes,
and sediment

Samples were collected along the southeast shore of thelake (36°2′46.92″N, 138°6′30.94″E; Fig. 2a) at a water
depth of 1.8 m on September 28, 2018, and June 29, 2019.
The water temperature and dissolved oxygen (DO) concentration were measured on-site at each depth with a
DO meter (HQ-30D; Hach, Loveland, CO, USA). Lakewater was collected in serum vials to measure the dissolved ­CH4 concentration, while cyanobacteria floatingon the surface (Fig. 2b, c) were collected with a plankton net (10-μm mesh) and placed in polypropylene bottles (Fig. 2d). Benthic sediment was collected at depthsof 0–10 cm in September 2018 and at depths of 0–3 cm
in June 2019 with a gravity core sampler (50-cm long,
4-cm diameter) (Fig. 2e). Planktonic cyanobacteria andbenthic sediment samples were preserved in an ice box
and transported to the laboratory, where they were frozen and stored at − 30 °C. The cyanobacterial samples
were microscopically observed (PX-51; Olympus, Tokyo,
Japan).
2.3 Analytical procedures
2.3.1 Measurement of dissolved ­CH4

The concentration of dissolved ­CH4 in the sampledlake water was analyzed on June 27 and September 28,
2018, and on June 28, August 29, and October 10, 2019,according to previously described methods (Itoh et al.
2015). Lake water was collected in 30-mL vials from several depths (0, 10, 50, 100, 130, 150, and 160 cm) withsyringes and tubes attached to a pier. ­CH4 was quantified using a gas chromatograph with a flame ionization
detector (GC-14B; Shimadzu, Kyoto, Japan) and a packed
column (Porapack-Q, 80/100 mesh, 1.5 m × 3.0 mm innerdiameter (i.d.); GL Sciences, Tokyo, Japan). The concentration of dissolved ­CH4 was calculated with the ideal gas
law and Bunsen solubility coefficient (Magen et al. 2014).
2.3.2 Extraction of F430 by wet chemistryF430 analysis was performed according to a previously
described method (Takano et al. 2013; Kaneko et al.
2014). In summary, F430 was extracted from planktonic

Page 3 of 17

cyanobacteria and benthic core-top sediments by using
1% formic acid under ultrasonication for 30 min on ice
and centrifugation (10,000g; 30 min; 4 °C). The supernatant was then recovered, and this step was repeated threetimes. The combined supernatants were introduced into
an anion-exchange column (Q Sepharose; GE Healthcare,
IL, USA) equilibrated with 50 mM Tris–HCl (pH 7.5) andwashed with deionized water before use. The recovered
eluent was introduced into a ­C18 SPE column (Sep-Pack;
Waters, MA, USA) equilibrated with methanol and conditioned with 1% formic acid. F430 was eluted with methanol and converted into F430 methyl ester (F430M) via
derivatization with ­BF3–methanol (40 °C; 3.5 h) before
extraction with dichloromethane. To remove the organic
matrix, the F430M fraction extracted from the samples
was purified via silica gel chromatography (Kaneko et al.
2016). This pretreatment eliminates any potential analytical artifacts that may affect ultrasmall-scale analyses(~ femto mol; e.g., Kaneko et al. 2014; Inagaki et al. 2015;
Isaji et al. 2020) of tetrapyrrole compounds through chromatographic separation, which may induce ion suppression and enhancement effects in liquid chromatography/
electrospray ionization-mass spectrometry (LC/ESI-MS).
2.3.3 Qualification and quantification of F430 using LC/
ESI‑MS

The concentration of extracted F430M was determined
via high-performance liquid chromatography/electrospray ionization-mass spectrometry (HPLC/ESI-MS/
MS; 1260 Infinity II LC System coupled to a 6490 Triple
Quadrupole LC–MS system with an Agilent jet stream;
Agilent Technologies, CA, USA) in positive ion mode.
Chromatographic separation was performed with a ZORBAX Eclipse XDB-C18 column (0.5 × 150 mm; 5 μm,
Agilent Technologies). Multiple reaction monitoring(MRM) analysis was performed at a fragmentor voltageof 380 V and a collision energy of 70 V. The F430M product ion was set to m/z 844.3. The mobile phases included
10 mM ammonium acetate with 1% acetonitrile (A) and
acetonitrile (B) at a flow rate of 16 μL ­min−1 and the following gradient: 0% B, 30% B after 3 min, and 90% B after
90 min (Mayr et al. 2008). The F430M concentration wasdetermined with an external F430M standard (Kaneko
et al. 2014, 2016).
2.3.4 SSU rRNA gene tag sequencing

Total DNA was extracted from the cyanobacteria andbenthic sediments collected in September 2018 using
a Plant Genomic DNA Extraction Miniprep System(Viogene, Taipei, Taiwan) and a DNeasy Power Soil Kit(Qiagen, CA, USA), respectively, which were selected toachieve the most efficient DNA extraction from thesesamples. The concentration of the extracted DNA wasUrai et al. Prog Earth Planet Sci(2021) 8:62

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Fig. 2 Photographs of the sampling site and samples in June 2019. a Sampling site in the present study. The pier extends ~ 40 m from the lakeshore
and attains a depth of ~ 1.8 m. b, c Floating cyanobacteria near the sampling site. d Planktonic cyanobacterial sample collected in a polypropylene
bottle. e Sediment core collection with a gravity core sampler

Urai et al. Prog Earth Planet Sci(2021) 8:62

measured with a Quant-iT™ dsDNA HS Assay Kit and a
Qubit Fluorometer (Thermo Fisher Scientific, MA, USA).
The SSU rRNA genes in the extracted DNA were amplified via polymerase chain reaction (PCR) using TaKaRa
LA Taq (TaKaRa Bio, Shiga, Japan) according to the manufacturer’s protocol. The 530F/907R primer set (V4–V5
regions) covering most bacterial and archaeal SSU rRNA
genes (Nunoura et al. 2012) was used. This primer set canalso detect some eukaryotic SSU rRNA gene sequences,
but it does not cover all eukaryotes. Therefore, eukaryote-derived sequences were excluded, and archaea- andbacteria-derived sequences, approximately 380 bp longof merged sequences that are the two-ended reads, wereused to analyze the microbial community structure. The
PCR amplification conditions were as described previously (Hirai et al. 2017). The amplified SSU rRNA genesequences were analyzed using MiSeq (Illumina, CA,
USA). Paired-end reads were merged using PEAR (Zhang
et al. 2014). Low-quality (a Q score < 30 in over 3% of
all sequences), short reads (< 150 bp) and long reads(> 500 bp) were filtered out with a customized Perl script.
After chimeric sequences had been removed with Usearch61 (Edgar 2010) in QIIME (Caporaso et al. 2010),
operational taxonomic units (OTUs) at a 97% similarity level were selected using UCLUST (Edgar 2010) andassigned taxonomically (at the phylum, class, order, family, and genus levels) based on the SILVA 132 database(Quast et al. 2012).
2.3.5 Nucleotide sequence accession numbers

The SSU rRNA gene tag sequence data reported in thismanuscript have been deposited in BioProject underaccession number DRA009781.
2.3.6 PCR amplification of the archaeal 16S rRNA andmcr A genes

To confirm the presence of methanogenic archaea in thesamples, the archaeal 16S rRNA and mcrA genes were
amplified considering the extracted DNA by PCR with
TaKaRa LA Taq (TaKaRa Bio) according to the manufacturer’s protocol. The archaeal 16S rRNA gene wasamplified with the 340F/1000R primer set (Gantner et al.
2011), while the mcrA genes were amplified using the
Luton-mcrA F/R, MCR F/MCR R, ME 3F/ME 2R, andmlas/mcrA-rev primer sets (Springer et al. 1995; Lutonet al. 2002; Steinberg and Regan 2008; Sørensen et al.
2009). The PCR conditions involved denaturation at 95 °C
for 9 min, followed by 45 cycles of denaturation at 94 °C
for 40 s, annealing at 50 °C, 52 °C, or 55 °C for 30 s, extension at 72 °C for 40 s, and a final extension step at 72 °C
for 7 min. The size of the PCR products was assessed

Page 5 of 17

via electrophoresis through a 1.5% agarose gel stainedwith RedSafe™ Nucleic Acid Stain Solution (FroggaBio,
Toronto, Canada).
2.3.7 A culture experiment using the cyanobacteria

We performed a short-term culture experiment using the
cyanobacterial bloom sample collected from Lake Suwa
(date: 29-June-2019). The laboratory-based incubation
was previously described in Han et al. (2012). Briefly, thecyanobacterial bloom sample was cultured in 10L plastic
bottle with MA growth medium. The light/dark cycles
was 12:12 (light: 9:00 to 21:00) and incubation temperature was 23 °C. C­ H4 in the head space was analyzed by
Ultraportable Greenhouse Gas Analyzer (Los Gatos
Research, USA) under bright light conditions.
2.3.8 Carbon and nitrogen measurement

The total organic carbon (TOC) and total nitrogen (TN)contents and their stable isotopic ratios (13C/12C and15
N/14N, respectively) were measured in the planktonic
cyanobacteria and core-top sediment collected in September 2018. All samples were freeze-dried, crushed, andhomogenized prior to analysis. The benthic sediment was
treated with 1 M HCl to remove carbonates and centrifuged (~ 2000g) for 5 min, and the precipitate was thoroughly washed with deionized water. This procedure wasrepeated three to five times before the sample was dried
and pulverized. Measurements were conducted with anultrasensitive elemental analyzer connected to an isotope ratio mass spectrometer (Flash EA1112 coupled toa Thermo Finnigan Delta plus XP via ConFlo III; Thermo
Finnigan, CA, USA), as described previously (Ogawa
et al. 2010). The isotopic composition was expressed inconventional δ notation:
Rsample− 1 × 1000(‰),δ=
Rstandard
where R denotes the 13C/12C or 15N/14N ratio. The carbon and nitrogen isotope standards were Vienna Pee
Dee Belemnite (VPDB) and atmospheric ­N2 (AIR),
respectively. The carbon and nitrogen contents andtheir isotopic compositions were calibrated against
three reference materials: l-tyrosine (BG-T: C, 59.7%;
N, 7.74%; δ13C, − 20.83 ± 0.10 ‰; δ15N, + 8.74 ± 0.09‰), dl-alanine (CERKU-01: C, 40.4%; N, 15.7%;
δ13C, − 25.36 ± 0.08 ‰; δ15N, − 2.89 ± 0.04 ‰), and glycine (CERKU-03: C, 32.0%; N: 18.7%; δ13C, − 34.92 ± 0.07‰; δ15N, + 2.18 ± 0.04 ‰) (Tayasu et al. 2011). The analytical errors in the isotopic composition estimated via
repeated BG-T analyses (5.8–22.7 µg C; 0.75–2.9 µg N)
were ± 0.07 ‰ (1σ; n = 9) for δ13C and ± 0.18 ‰ (1σ;n = 9) for δ15N.

Urai et al. Prog Earth Planet Sci(2021) 8:62

3 Results
3.1 Water column chemical profiles with the carbon
and nitrogen contents

Figure 3a shows the water column profiles based on themeasurements conducted in September 2018. Both thewater temperature and the DO decreased with depth andranged from 20.8 to 17.2 °C and 10.97 to 6.76 mg ­L−1,
respectively. The DO saturation ranged from 134 to 77%,
suggesting that the water column was highly oxygenated from the surface to the bottom. The maximum ­CH4
concentration was observed between depths of 100 and
160 cm (3.5–3.6 μM) and decreased from 3.5 to 1.5 μM
in water shallower than 100 cm. Similar trends wereobserved on the other measurement days (Fig. 3b).
We also analyzed the carbon and nitrogen contents
and stable isotopic ratios of the samples collected in September 2018 (Table 1). Among the cyanobacterial samples, the TOC and TN contents were 41.1 ± 1.8 wt.%
and 7.7 ± 1.08 wt.%, respectively, with δ13C and δ15N
values of − 26.5 ± 0.3 ‰ and + 8.8 ± 0.5 ‰, respectively.
Conversely, the sediment samples exhibited lower TOC
and TN contents of 5.5 ± 0.9 wt.% and 0.3 ± 0.04 wt.%,
respectively, with δ13C and δ15N values of − 27.6 ± 0.4 ‰and + 3.0 ± 0.9 ‰, respectively. The observed carbon andnitrogen isotopic compositions were typical of the lacustrine range in Lake Suwa (cf. Yoshioka et al. 1988, 1994),
and the cyanobacterial and sediment samples exhibited
TOC/TN ratios of 5.4 ± 0.6 and 17.2 ± 0.6, respectively.
The carbon and nitrogen isotope ratios presented in thisstudy are in the typical cyanobacterial profiles (i.e., native
feature of phototrophic N­ 2-fixation) and are consistent
with the findings presented in previous reports (Yoshioka
et al. 1988; Ohkouchi and Takano 2014).
3.2 Concentration of F430

We detected F430 in the planktonic and benthic samples by using LC/ESI-MS/MS in MRM mode (Fig. 4).
The planktonic samples collected in September 2018 andJune 2019 exhibited F430 concentrations of 6.8 × ­102 and3.5 × ­103 femto mol g-wet−1, respectively (Table 2), or
9.2 × ­103 and 5.6 × ­104 femto mol g-dry−1, respectively,
considering the water content in the cyanobacteria, i.e.,
the water contents in both cyanobacterial samples were
92.5 and 93.8%, respectively. Conversely, the F430 concentrations in the core-top sediment obtained in September 2018 and June 2019 were 8.5 × ­102 and 8.6 × ­103
femto mol g-wet−1, respectively. The peak ratios of native
F430 to its epimers were 3.3 and 3.8 in the cyanobacteria and 9.0 and 11.1 in the benthic sediment, respectively(Table 2). The small amounts of F430M epimers detectedin the samples collected in this study (Fig. 4b, c) indicatedthat most methanogenic archaea were activated.

Page 6 of 17

3.3 Microbial community structure in the planktonic
and surface sediment samples

First, Fig. 5 shows a photomicrograph of the planktonic
cyanobacteria collected in June 2019, in which large
numbers of cells were confluent and formed colonies
with a morphology similar to that of cyanobacteria of thegenus Microcystis (Xu et al. 2016). The detailed microbialcommunities in the cyanobacteria and core-top sediment collected in September 2018 were investigated via
SSU rRNA gene tag sequencing analysis. A total of 65,884
reads were obtained from the planktonic cyanobacteria, of which 99.5% were assigned to bacteria (Fig. 6a, b).
More than 50% of the bacterial reads were assigned to asingle OTU and were closely related to the cyanobacterium genus Microcystis in the order Nostocales (Fig. 6c).
We detected another cyanobacterium genus, Pseudanabaena, in the order Pseudanabaenales. In addition to
cyanobacteria, bacteria closely related to the orders
Acetobacterales (mainly Acetobacteraceae), Betaproteobacteriales (mainly uncultured Nitrosomonadaceae,
Azohydromonas, Ramlibacter, and Noviherbaspirillum),
Caulobacterales (mainly uncultured Caulobacteraceae),
and Cytophagales (mainly uncultured Microscillaceae)
were detected, which are generally regarded as aerobic
heterotrophic or aerobic ammonia-oxidizing bacteria.
A small proportion (0.3%) of the total sequence reads
was assigned to eukaryotic 18S rRNA genes, mainly
stemming from Cnidaria, Conthreep, Bilateria, andHeterotrichea.
Second, a total of 46,182 reads were obtained from thebenthic sediment, of which 92.8 and 6.9% were assigned
to bacteria and archaea, respectively (Fig. 6d). Methanogenic archaea belonging to the classes Methanobacteria (Methanobacterium) and Methanomicrobia (largely
Methanoregula, Methanothrix, Methanosarcina, andMethanocella) were confirmed in the archaeal community (Fig. 6e). The majority of the archaeal reads wereassigned to the candidate phyla Bathyarchaeota and
Woesearchaeota and the class Thermoplasmata (largely
Marine Benthic Group-D). Although these predominant archaeal groups are also frequently encountered inmarine and freshwater ecosystems, groundwater, andthermal springs, little is known about their physiology ormetabolism due to the lack of cultured representatives(e.g., Evans et al. 2015; Tarnovetskii et al. 2018; Zhou et al.
2018, 2019). Compared to the planktonic cyanobacteria,
the bacterial community in the sediment samples was
extremely diverse (Fig. 6f ), with relatively abundant bacterial reads closely related to the orders Betaproteobacteriales (mostly Sulfuritalea, Quatrionicoccus, uncultured
Nitrosomonadaceae, and uncultured Burkholderiaceae),
Gaiellales (mostly uncultured), Anaerolineales (mostly
uncultured Anaerolineaceae), and Clostridiales (mostlyUrai et al. Prog Earth Planet Sci(2021) 8:62

Page 7 of 17

Fig. 3 a Cross-section of Lake Suwa and water column profiles
measured in September 2018. Here, we note that planktonic
cyanobacteria move toward a lower water layer at night and riseto the surface layer before dawn (Reynolds 1987). b Principal
component loading for the water depth (cm), water temperature (°C),
dissolved oxygen (mg/L), ­CH4 (mmol/L) in the sampling site at Lake
Suwa for early summer season (June in 2018 and 2019, n = 12) and
autumn season (September to October in 2018 and 2019, n = 13)

Water temperature (oC)

(a)

14

16

18

20

22

DO (mg L−1 )
0

4

6

8

10

12

Water depth (cm)

20
40

Temp.

60

DO

Romboutsia, Clostridium, and Sarcina). These bacteria
include aerobic heterotrophic (Burkholderiaceae), anaerobic autotrophic (Sulfuritalea), anaerobic heterotrophic(Anaerolineales, Clostridiales), and ammonia-oxidizing(Nitrosomonadaceae) species, which have often beenreported in the sediments of freshwater lakes (Buckles
et al. 2013; Watanabe et al. 2017; Chen et al. 2017).

80
100
120

3.4 Genomic indicators of the methanogenic archaea

140

180

(b)

To detect methanogenic archaea in both the planktonic
and the benthic samples, we amplified the archaeal 16S
rRNA and mcrA genes in the total extracted DNA using
PCR with the above one and four primer sets, respectively. The archaeal 16S rRNA and mcrA genes were successfully amplified from the benthic sediment (Table 3),
while the PCR amplicons from the cyanobacteria were
not significant after repeated attempts. A wet-chemical
improvement to eliminate the sample matrix effect (e.g.,
extracellular polysaccharides stemming from cyanobacteria) is required for further confirmation of the current
preliminary results.

CH4

160
0

1

2
3
CH4 (mM)

4

Principal component loading in June (PC1)

Depth

CH4

3.5 The head‑space methane during the culture
experiment

Temp.
DO
-1.0

-0.5

0.0

0.5

1.0

Principal component loading in Sept. & Oct. (PC1)
Depth

CH4
DO
Temp.
-1.0

-0.5

0.0

0.5

1.0

Figure 7 showed the concentration ­CH4 profile in thehead-space with the incubation time. The ­CH4 concentration was normalized by the difference of initialconcentration (t = 0, hour) to each corresponding time(< t = 9). We confirmed a rapid increase in methane concentration within the incubation time. Therefore, the preliminary results indicated that the cyanobacterial bloom
sample produced ­CH4 under aerobic condition (cf. Bižić
et al. 2020), and its production rate was determined
about 1.39 nM ­h−1. The data presented in this preliminary culture experiment supports the evidence for in-situ
methane production (Fig. 7). In our future survey, it isnecessary to conduct culture studies with different conditions (i.e., light and dark conditions, water temperature,
medium) with a microbial ecological link to methane
producing archaea.

Urai et al. Prog Earth Planet Sci(2021) 8:62

Page 8 of 17

Table 1 Carbon and nitrogen contents and their stable isotopic compositions in the planktonic and benthic samples
TOC

TN

δ13C

δ15N

TOC/TN

(wt%)

(wt%)

(‰, vs VPDB)(‰, vs AIR)

(wt%/wt%)

Planktonic cyanobacteria(September 2018)41.1 ± 1.8

7.7 ± 1.1

− 26.5 ± 0.3+ 8.8 ± 0.5

5.4 ± 0.6

Sediment 0–10 cm depth(September 2018)

5.5 ± 0.9

0.3 ± 0.0

− 27.6 ± 0.4+ 3.0 ± 0.9

17.2 ± 0.6

Sample(a)Fig. 4 a Structure of coenzyme factor 430 (F430), which has a chemical formula of C
­ 42H51N6NiO13. F430 is a hydrocorphinoid nickel complex thatfunctions as an active site in MCR. The MCR–F430 complex catalyzes the last step of methanogenesis involving the reduction of methyl coenzyme
M into ­CH4. b, c Chromatograms of the planktonic cyanobacterial samples analyzed via LC/ESI–MS/MS in MRM mode (Kaneko et al. 2014). The
F430M product ion was set to m/z 844.3. The concentration of native F430 with assessment of the F430 epimer ratio enabled us to estimate thebiomass of the in situ living methanogenic archaea (Kaneko et al. 2021)

Urai et al. Prog Earth Planet Sci(2021) 8:62

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Table 2 Concentrations of coenzyme F430 and its epimer ratios in the planktonic and sediment samples collected from Lake Suwa
Sample type

Sample nameConcentration

Planktonic microbes

Cyanobacteria(September 2018)

6.8 × ­102

Cyanobacteria(June 2019)
Sediment

F430/F430
epimer

References

femto mol g-wet−1

3.3

This study

3.5 × ­103

femto mol g-wet−1

3.8

This study

Sediment 0–10 cm depth(September 2018)

8.5 × ­102

femto mol g-wet−1

9.0This study

Sediment 0–3 cm depth(June 2019)

8.6 × ­103

femto mol g-wet−1

11.1

This study

Kawatabi(Paddy soil)

8.7 × ­102

femto mol g-wet−1–

Kaneko et al. (2014)

Shimokita 11–4
(Marine sediment)

6.3 × ­101

femto mol g-wet−1–

Kaneko et al. (2014)

We include a compilation of previous reference data (Kaneko et al. 2014)

Fig. 5 Photomicrograph of the planktonic cyanobacterial sample collected in June 2019. The cyanobacteria in Lake Suwa mainly include
Microcystis (a) in addition to other cyanobacteria, such as Aphanizomenon (b). We note previous studies regarding the average cellular dry weight
and average cellular volume of Microcystis aeruginosa (2.0 × ­10−11 g ­cell−1, Li et al. 2014; 65 µm3 ­cell−1, Olenina et al. 2006)

4 Discussion
4.1 Planktonic and benthic concentrations of F430
for potential methane production

F430 is unstable and rapidly epimerizes to its relic forms(13-epi-F430 and 12,13-diepi-F430) via a process occurring on a daily basis, even at room temperature (Diekert
et al. 1981; Mayr et al. 2008; Inagaki et al. 2015); therefore,
the native form of F430 is unlikely to accumulate in theenvironment after the death of methanogenic archaeal
cells. The concentration of native F430 with assessment of the F430 epimer ratio enabled us to estimate

the biomass of the in situ living methanogenic archaea(Kaneko et al. 2014, 2021). In this study, we detected
native F430 in the planktonic cyanobacterial sample(i.e., 6.8 × ­102 to 3.5 × ­103 femto mol g-wet–1), indicating the presence of methanogenic archaea in the watercolumn environment (Fig. 4, Table 2). Although active
photosynthesis simultaneously generates oxygen, certain
methanogenic archaea are considered to tolerate oxygen
exposure for long periods (Angel et al. 2011). Assemblages of heterotrophic bacteria are contained within
the cyanobacterial phycosphere, and their respiration

Urai et al. Prog Earth Planet Sci(2021) 8:62

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SSU rRNA genes
Archaea

Bacteria

Archaeal 16S rRNA genes
Bathyarchaeota

Woesearchaeota

Thermoplasmata

Methanomicrobia

Nanohaloarchaeota

OthersMethanobacteria

Bacterial 16S rRNA genes
Nostocales

Acetobacterales

Betaproteobacteriales

Uncultured bacterium

Pseudanabaenales

Gaiellales

Anaerolineales

Clostridiales

Kryptoniales

RBG-13-54-9

Caulobacterales

Syntrophobacterales

SBR1031Bacteroidales

Ignavibacteriales

OPB41

Pirellulales

Cytophagales

SJA-15

Methylococcales

OthersUnclassified

Fig. 6 Cross-section of SSU rRNA gene tag sequencing analysis of the samples collected in September 2018. a, b, c Planktonic cyanobacterial
sample. d, e, f Benthic sediment sample. Relative abundance of each domain (a, d), archaeal community (b, e), and bacterial community (c, f)based on the number of sequence reads obtained. Within archaeal sequences of the planktonic sample, two reads of the archaeal sequenceswere assigned to methanogenic archaea. They were affiliated with the hydrogenotrophic genus Methanoregula and hydrogen-dependent
methylotrophic family Methanomassiliicoccacea. Those two sequences were not found in the benthic sample

leads to an oxygen gradient (e.g., Ploug 2008; Dziallas andGrossart 2012; Batista et al. 2019). Very small amountsof F430 epimers were also detected from the planktonic

cyanobacterial samples based on the ratio of native F430
to the epimer in these samples ranging from 3.3 to 3.8(Table 2), suggesting that native F430 occurs in an active

Urai et al. Prog Earth Planet Sci(2021) 8:62

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Table 3 PCR amplification of the archaeal 16S rRNA and mcrA genes. The PCR products were loaded onto a 1.2% agarose gel withnegative and positive controls and a DNA size standard
TargetArchaeal 16S rRNA genemcrA gene

PCR primer set

340F/1000R

Luton-mcrA
F/R

MCR F/MCR R

ME 3F/ME 2R

mlas/mcrA-rev

Planktonic cyanobacteria(September 2018)

−

−

−

−

−

Sediment 0–10 cm depth(September 2018)

+

+

−

+

+

The presence or absence of the PCR product is indicated as ( +) and ( −), respectively. The annealing temperature for each primer set is listed in Table 4

Table 4 PCR primers for archaeal 16S rRNA and mcrA genes for the present initial report
TargetPrimer nameArchaeal 16S
rRNA gene

340F
1000R

mcrA genemcrA genemcrA genemcrA geneDirection

Sequences (5′ → 3′)

Hybridization
temperature (°C)

References

Forward

CCC​TAY​GGG​GYG​CASCAG​

52

Gantner et al. (2011)

ReverseGGC​CAT​GCA​CYW​CYT​C TC​
50

Luton et al. (2002)50

Springer et al. (1995)

55

Sørensen et al. (2009)55

Steinberg and Regan (2008)

Luton-mcrA F

Forward

GGT​GGT​GTMGGA​T TC​ACA​CAR​TAY​GCW​ACAGC​

Luton-mcrA R

Reverse

TTC​ATT​GCR​TAG​T TW​GGR​TAGTT​MCR F

ForwardTAY​GAY​CARATHTGGYT​

MCR RReverseACRITCATNGCR​TAR​T T

ME 3F

ForwardATGTCNGGTGGHGTMGGSTTYAC​

ME 2R

ReverseTCATBGCR​TAG​T TDGGR​TAG​T

mlas

Forward

GGT​GGT​GTMGGDTTCACMCARTA​

mcrA-rev

ReverseCGT​TCA​TBGCG​TAG​T TVGGR​TAG​T

state in the water column (cf. Urai et al. 2021). Therefore, the planktonic methanogen coexisting in the watercolumn may produce ­CH4 when oxygen production via
photosynthesis ceases at night, as proposed by Bižic et al.
(2020). We determined the gene extraction method forcyanobacterial bloom after comparing several extraction
kits. Previous study reported that cyanobacterial cells arerich in polysaccharides, which make it difficult to obtainhighly purified nucleic acid (e.g., Yoshida et al. 2003).
However, we detected archaeal gene reads in cyanobacterial bloom, indicating that the method can detectarchaeal gene from cyanobacteria. To evaluate the actual­CH4 production rate in the water column of Lake Suwa,
preliminary short-term incubation experiments were
performed by using the same planktonic cyanobacterial
samples (Fig. 7).
SSU rRNA gene tag sequencing analysis detected alarge number of 16S rRNA genes originating from aerobic heterotrophic bacteria, including Acetobacterales
and Betaproteobacteriales, in the cyanobacterial sample(Fig. 6). Some Acetobacterales species produce acetate
as a metabolite (Vu et al. 2019); therefore, these heterotrophic bacteria may supply methanogenic archaeawith methanogenic substrates via decomposition of theorganic matter produced during cyanobacterial photosynthesis. Berg et al. (2014) proposed that hydrogenotrophic methanogenic archaea utilize the hydrogengenerated by cyanobacteria during nitrogen fixation;
however, since Microcystis, which was dominant in our
samples (Fig. 6c), lacks nitrogenase required for nitrogen fixation (Kim et al. 2019), its contribution to C
­ H4
production appears to be quite small in surface water.
Although we detected F430 in the planktonic cyanobacterial samples (Fig. 4), the samples contained extremely
small numbers of SSU rRNA gene sequences fromknown methanogenic archaea, and no PCR amplicons
from archaeal 16S rRNA and mcrA genes were obtained(Fig. 4, Table 3). Previous studies have estimated thein situ cellular abundance of methanogenic archaea basedon the F430 concentration (Takano et al. 2013; Kaneko
et al. 2014); however, a technical discrepancy between
the F430 concentration and molecular analyses has beenreported (e.g., Inagaki et al. 2015; Kaneko et al. 2016; Uraiet al. 2021). Although an equation has been proposed toconvert the F430 concentration into the number of methanogenic archaea, deep insights are currently lacking to
widely apply the equation. Therefore, method development is required in this preliminary study to refine theUrai et al. Prog Earth Planet Sci(2021) 8:62

Page 12 of 17

Table 6 Water column profiles at the sampling site between
June 2018 and October 2019
Date

2018.6.27

Fig. 7 The time profiles of ­CH4 concentration in head space by ashort-term culture experiment. The data showed the average value ofthe measurement of ­CH4 in the gas phase within the incubation time(t = 0, 4, 6, 9 h; t = 0 as initial concentration)comparison to rRNA gene sequencing and quantitative
examinations.
Regarding the benthic methane production process, we quantified F430 in the benthic sediment samples collected in September 2018 (8.5 × ­102 femto mol
g-wet–1) and June 2019 (8.6 × ­103 femto mol g-wet–1),
revealing levels similar to or higher than those previously
reported in marine sediment (0.026–1.9 × ­103 femto
mol g-wet–1) and paddy soil (0.3–2.0 × ­103 femto mol
g-wet–1) (Kaneko et al. 2014, 2016), suggesting ongoingarchaeal methanogenesis in the benthic sediment. The­CH4 production rate in the benthic sediment (5–30 cm
depth) of Lake Suwa has been reported to range from
Table 5 Correlation matrix of the water depth (cm), watertemperature (°C), dissolved oxygen (mg/L), and ­CH4 (mmol/L) inthe sampling site at Lake Suwa; (a) early summer season (Junein 2018 & 2019, n = 12) and (b) autumn season (September to
October in 2018 and 2019, n = 13)
Depth

Temp.

DO

(a) June in 2018 and 2019 (n = 12)

Depth

1

Temp

− 0.042

1

0.844

0.844

1

0.657

0.059

− 0.3791− 0.920

0.665

DO
CH4

− 0.475− 0.042− 0.475

CH4(b) September to October in 2018 and 2019 (n = 13)

Depth

1

Temp

− 0.954

1

0.945

0.945

1

0.665

− 0.673− 0.450DO
CH4− 0.920− 0.954

0.657
0.059
− 0.379− 0.673− 0.4501

Principal component statistics and raw data profiles are shown in the Fig. 3b andTable 6, respectively

2018.9.28

2019.6.28

2019.8.29

Depth

Temp

DO

CH4

cm

°C

mg/L

mmol/L

0

–

–

1.80

5

24.5

8.61

–

10

24.5

8.61

2.09

20

24.5

8.61

–

50

24.5

8.66

2.05

75

24.5

8.58

–

100

24.5

8.64

2.26

130

24.5

8.43

1.83

150

24.5

7.83

2.05

160

24.5

7.16

2.36

180

24.5

6.48

–

0

–

–

–

5

20.8

10.97

1.52

10

20.7

10.11

1.73

20

20.2

9.34

–

50

19.1

8.74

2.13

75

17.9

7.50

–

100

17.5

7.68

3.50

130

17.3

7.67

3.60

150

17.2

7.24

3.53

160

17.2

6.76

3.45

180

17.2

6.80

–

0

–

–

0.92

5

22.9

7.16

–

10

22.9

7.13

1.07

20

23.0

7.12

–

50

23.0

7.11

1.17

75

23.0

6.94

–

100

23.0

6.85

1.43

130

22.9

6.31

2.25

150

22.8

5.75

2.76

160

22.7

4.92

3.03

180

22.7

4.84

–

0

–

–

2.78

5

25.7

7.49

–

10

25.6

7.51

0.61

20

25.5

7.54

–

50

25.4

7.40

0.37

75

24.4

3.22

–

100

23.9

1.32

0.23

130

23.4

2.77

0.94

150

22.6

1.86

3.38

160

22.4

1.22

13.59

180

22.3

0.83

–

Urai et al. Prog Earth Planet Sci(2021) 8:62

Page 13 of 17

Table 6 (continued)
Date2019.10.10

Depth

Temp

DO

CH4

cm

°C

mg/L

mmol/L

0

–

–

0.32

5

20.9

10.06

–

10

20.9

10.06

0.29

20

20.9

10.08

–

50

20.8

10.06

0.99

75

18.9

8.98

–

100

17.8

7.01

0.90

130

16.9

5.50

1.83

150

16.9

5.45

2.36

160

16.8

5.23

2.37

180

16.8

5.07

–

7.8–19.8 nmol g-dry–1 ­h–1 at the typical summer maximum surface sediment temperature (Iwata et al. 2020).
Since Lake Suwa is a eutrophic lake, its benthic sedimentcontains high concentrations of organic carbon (Table 1);
therefore, this nutrient-rich substrate could support
benthic ­CH4 production (e.g., Zepp Fal et al. 1999). The
correlation matrix of the water depth (cm), water temperature (°C), DO (mg/L), and C­ H4 (mmol/L) in the earlysummer (n = 12) and autumn (n = 13) seasons during
2018–2019 is shown in Table 5.
4.2 Drastic change between the planktonic and benthic
microbial communities

Archaeal 16S rRNA and mcrA gene analysis detected
the presence of methanogenic archaea closely related
to Methanobacteriales and Methanomicrobiales in thebenthic sediment (Fig. 6, Table 3), including hydrogenotrophic, aceticlastic, and methylotrophic methanogenic archaea (Sakai et al. 2012; Schirmack et al. 2014).
The 16S rRNA genes of anaerobic heterotrophic bacteria
were also detected in the benthic sediment (Fig. 6). Members of Anaerolineales and Clostridiales anaerobicallydecompose organic matter via fermentation and supply
methanogenic archaea with their metabolites, such as­H2, acetate, formate, and methanol (Yamada et al. 2006;
Nishiyama et al. 2009). Although the bottom lake watercontained DO (Fig. 3a), this DO may be rapidly consumed by aerobic heterotrophic bacteria in the benthic
sediment, suggesting that C­ H4 is produced in the benthic sediment via the anaerobic decomposition of organic
matter by fermentative bacteria and methanogenic
archaea. The benthic sediment was dominated by the 16S
rRNA genes of archaea closely related to Bathyarchaeota,

whose genomes reportedly contain divergent homologsof the genes required for methane metabolism (Evanset al. 2015). Thus, uncultured archaea belonging to Bathyarchaeota may also be involved in ­CH4 production in
the surface sediment.
The microbial community structure differed between
the water column and benthic sediment. The planktonic
observations are consistent with a previous study (Microcystis spp., Park et al. 1993). In contrast, a wide variety ofarchaeal and bacterial taxa occurred in the benthic habitat. Although dead cyanobacterial cells originating fromthe water column rapidly sank to the water–sedimentinterface, SSU rRNA genes from cyanobacteria constituted an extremely minor fraction (~ 2% of all sequences)in the benthic sediment (Fig. 6). Yan et al. (2017) reported
that the decomposition of cyanobacterial cells produces
nutrients (nitrate, phosphate, and organic substances)that may stimulate benthic microbial ­CH4 production.
In addition, a positive relationship was clearly observed
between the C­ H4 flux rate and productivity normalized
to the chlorophyll a concentration in freshwater environments (Beaulieu et al. 2019). Furthermore, Iwata et al.
(2020) reported that the observed seasonal variation inmeteorological and limnological environments from2016 to 2017 indicated stable stratification (i.e., a difference in temperature between the surface and bottom layers) from May to September. These results suggested thatthe migration of microorganisms derived from the benthic sediment to planktonic cyanobacteria was not notable in the water column.

5 Summary(1) We reported the first detection and concentration
data of planktonic F430 in the water column by an
ultrasmall-scale analysis (~ femto mol g-wet−1),
suggesting the potential occurrence of planktonic
methanogen archaea. To support this feasibility
study, we should consider a method optimizationof DNA/RNA-based molecular analysis, such as theelimination of the sample matrix effect (e.g., extracellular polysaccharides stemming from massive
cyanobacteria) with other precise analytical protocols (e.g., Wäge et al. 2020).
(2) SSU rRNA gene analysis revealed that the microbial communities differed dramatically between thewater column and benthic sediment. After eventual
detritus sinking, therefore, the planktonic primary
producers contributed as a nutrient source to thebenthic microbial habitat mostly at the water–sediment interface.

Urai et al. Prog Earth Planet Sci(2021) 8:62

Page 14 of 17

Along with the short summary above, multiple novel
chemical and microbial approaches are required to elucidate the issues associated with the methane paradox inwater column environments.

Declarations

Abbreviations
F430: Coenzyme factor 430; HPLC: High-performance liquid chromatography;
ESI-MS: Electrospray ionization-mass spectrometry; EIC: Extracted ion chroma‑
tography; MRM: Multiple reaction monitoring; DO: Dissolved oxygen; mcrA:
Methyl coenzyme M reductase A gene; OTU: Operational taxonomic unit; PCR:
Polymerase chain reaction; SSU rRNA: Small subunit ribosome RNA; TN: Total
nitrogen; TOC: Total organic carbon.

Author details
1
Biogeochemistry Research Center (BGC), Japan Agency for Marine-Earth
Science and Technology (JAMSTEC), Yokosuka, Japan. 2 Department of Scienceand Technology, Graduate School of Medicine, Science and Technology, Shin‑shu University, Matsumoto, Japan. 3 Geological Survey of Japan (GSJ), National
Institute of Advanced Industrial Science and Technology, Tsukuba, Japan.
4
Department of Environmental Science, Faculty of Science, Shinshu University,
Matsumoto, Japan. 5 Institute for Extra-Cutting-Edge Science and Technology
Avant-Garde Research (X-Star), JAMSTEC, Yokosuka, Japan.

Supplementary Information
The online version contains supplementary material available at https://​doi.​
org/​10.​1186/​s40645-​021-​00450-7.
Additional file 1: Movie S1. Observation of lacustrine surface methane
emission near the sampling site at Lake Suwa. The surface sediment has alarge amount of ­CH4-rich gas because of microbial activity, including thatof methanogenic archaea. This movie was taken at the present study site.
Stimulation with a rod confirms that abundant bubbles are released fromthe surface sediment.
Acknowledgements
We express our sincere gratitude to Prof. W. B. Whitman (Univ. Georgia) forthe constructive review and comments provided on the earlier version of themanuscript. The authors thank two anonymous reviewers for the valuable andcritical comments, which helped to refine the initial manuscript. We thankthe Research and Education Center for Inland Water Environments at Shinshu
University for the provided assistance with our field survey. The authors thankDr. Y. Isaji (JAMSTEC), Dr. Y.Takaki (JAMSTEC) and Prof. Y. Chikaraishi (Hokkaido
Univ.) for their advice regarding lacustrine primary producers, SSU rRNA genesequence analysis and chlorophyll profiles, as well as Prof. Y. Miyabara (Shinshu
Univ.) for his knowledge of inland methane emissions and the planktonic
flora in Lake Suwa. We thank Dr. N. Futatsugi (Shinshu Univ.) for an additional
culture experiment. This study was conducted by the official collaborationagreement through the joint research project (FY2019-FY2021) between
JAMSTEC (YT) and Shinshu University (HDP).
Authors’ contributions
AU, MM, NO, and YT proposed the topic and designed the study framework.
MK, YT and NO outlined the small-scale analytical development of F430
molecules in a decade. AU, MM, HDP, YT, and HI collected the samples. AU,
MM, HI, HDP, and MO performed the experiments. AU, MM, HI, MK, NOO, NO,
and YT analyzed the samples and interpreted the results. AU and YT wrote thepresent report with contributions from NO and MM. All authors edited andapproved the final manuscript.
Funding
This work was supported by KAKENHI grants from the Japan Society for the
Promotion of Science (JSPS): 15H05332 (MK), 16H04083 (YT), 19H01005 (HI),
19H04261 (MK), 20H00208 (NO), and 20H02019 (YT).
Availability of data and materials
Declaration of nucleotide sequence accession numbers: The SSU rRNA genetag sequence data have been deposited in BioProject PRJNA 9444 underaccession number DRA009781. The Global Lake and River Ice Phenology
Database are compiled by the National Snow and Ice Data Center (NSIDC),
Data Set https://​doi.​org/​10.​7265/​N5W66​HP8. The database of fixed point
observations (temperature, dissolved oxygen, turbidity, live camera capture)in Lake Suwa is released by the project of Suwa Smart Society 5.0 at https://​sss50.​harmo​nia-​cloud.​com. The other data sets supporting the conclusions
drawn in this article are included within the article.

Competing interests
The authors declare that the research was conducted in the absence of any
commercial or financial relationships that could be construed as a potential
conflict of interest.

Received: 24 April 2021 Accepted: 28 September 2021

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