温泉科学（J. Hot Spring Sci.），63，100-117（2013）

原著

Bacterial Community Structures in the Solfataric-Acidic Ponds
in the Kirishima Geothermal Area, Kagoshima Prefecture
Tomoko Satoh1）, Keiko Watanabe1）, Hideo Yamamoto1）,
Shuichi Yamamoto1） and Norio Kurosawa1）*(Received Mar. 25, 2013, Accepted Jun. 13, 2013)鹿児島県霧島地域の酸性硫黄源泉
における細菌群集構造の解析
佐藤智子1)，渡邉啓子1)，山本英夫1)，山本修一1)，黒沢則夫1)*要

旨

温度や化学成分が異なる温泉間で細菌群集構造を比較するため，鹿児島県霧島地域に分布す
る 4 つの酸性硫黄泉における細菌群集構造を，16S rRNA 遺伝子クローン解析法を用いて解析した．選択した温泉の温度および総化学成分量は次の通りである．1）Pond-A：93oC，1,679 mg L－1，
2）Pond-B：66oC，2,248 mg L－1，3）Pond-C：88oC，198 mg L－1，4）Pond-D：67oC，340 mg L－1．
相同性検索による種の同定を行った結果，4 つの温泉由来の計 372 クローンは 35 系統群に分類され，何れの温泉においても γ-Proteobacteria 綱が優占していた．最も多様性が高かったのは，
温度と総化学成分量が共に相対的に低い Pond-D であり，この温泉では Acinetobacter junii に近縁な種が全クローンの 37% を占めていた．Pond-D と同程度の温度ながら総化学成分量が相対的に高い Pond-B では，Acidithiobacillus caldus の近縁種および δ-Proteobacteria 綱に属す
る未培養細菌が優占していた．一方，温度が相対的に高い Pond-A と C では Acinetobacter
johnsonii に近縁な種が全クローンの 57% 以上を占めていた．本研究により，霧島地域の温度や化学成分が異なる酸性硫黄泉間における，細菌の群集構造および多様性の具体的な違いが明らかとなった．
キーワード：霧島温泉群，細菌，群集構造，多様性，化学成分，16S rRNA 遺伝子

Abstract
The bacterial 16S rRNA gene composition and environmental characteristics of four
distinct solfataric-acidic ponds in the Kirishima geothermal area, Kagoshima Prefecture,
1)

100

Division of Environmental Engineering for Symbiosis, Graduate School of Engineering, Soka
University, 1-236 Tangi-machi, Hachioji, Tokyo 192-8577, Japan. 1）創価大学大学院工学研究科環境共生
工 学 専 攻 〒192-8577 東 京 都 八 王 子 市 丹 木 町 1-236．*Corresponding author：E-mail kurosawa@soka.ac.jp, TEL +81-42-691-8175, FAX +81-42-691-8175.

第 63 巻（2013）鹿児島県霧島地域の酸性硫黄源泉における細菌群集構造の解析

Japan, were compared. The four ponds were selected based on differences in temperatureand the total concentration of examined chemical components : 1) Pond-A : 93℃ and 1679
mg L－1 ; 2) Pond-B : 66℃ and 2248 mg L－1 ; 3) Pond-C : 88℃ and 198 mg L－1 ; and 4) Pond-D :67℃ and 340 mg L－1. In total, 372 clones of the 16S rRNA gene were classified into 35 phylotypes. The dominant bacterial group was the class γ-Proteobacteria. Bacterial diversity was
greatest in Pond-D, and the dominant phylotype detected (37% of all clones) was closely related to Acinetobacter junii. Pond-B had the highest relative total concentration of examinedchemical components, and the bacterial community was dominated by a phylotype closely
related to Acidithiobacillus caldus as well as an uncultured species of δ-Proteobacteria.
Pond-A and Pond-C had the highest relative temperatures and were dominated by aphylotype closely related to Acinetobacter johnsonii (accounted for more than 57% of theidentified clones). This study highlights the different bacterial species composition andbiodiversity present in solfataric-acidic ponds characterized by different temperatures andchemical components.
Key words : Kirishima geothermal area, bacteria, community structure, diversity, chemicalcomponent, 16S rRNA

1.

Introduction

Extreme environments are unique locations for studying how organisms interact with andadapt to their surroundings. In particular, some high temperature environments such as
terrestrial hot springs and oceanic hydrothermal vents may resemble the volcanic habitats thatare thought to have existed on early Earth (Pace, 1991 ; Miller and Lazcano, 1995 ; Baross, 1998).
Indeed, some of the bacterial and archaeal lineages identified from hot springs appear to berelated to lineages close to the root of the phylogenetic tree (Pace, 1997).
Culture-dependent methods have traditionally been the primary means of surveying microbial diversity. However, these methods may underestimate the diversity of microorganisms andcan potentially provide unrealistic descriptions of the microbial community structure. Utilizationof molecular methods targeting the small-subunit (SSU ; 16S or 18S) rRNA gene in environmental
samples has revealed great diversity of uncultured microbes in the natural environment. Given
these new molecular findings, it is currently assumed that cultured species only account for 1%
or less of all prokaryotes present on Earth (Amann et al., 1995).
Prokaryotes are divided into two domains, the Bacteria and the Archaea, based on 16S rRNA
gene phylogenetic analysis (Woese and Fox, 1977 ; Woese et al., 1990). Hot spring prokaryotic
microbial communities have been extensively studied using the 16S rRNA gene in areas such as
Yellowstone National Park in the United States (Barns et al., 1994 ; Barns et al., 1996 ; Hugenholtz
et al., 1998 ; Reysenbach et al., 2000 ; Blank et al., 2002 ; Meyer-Dombard et al., 2005), Kamchatka
hot springs in Russia (Perevalova et al., 2008), Montserrat and Saint Lucia in the islands of theLesser Antilles (Burton and Norris, 2000 ; Stout et al., 2009), Icelandic hot springs (Perevalova etal, 2008 ; Kvist et al., 2007), Mt. Unzen hot springs in Japan (Takai and Sako, 1999), Ohwakudani
hot springs in Japan (Kato et al., 2011), Pisciarelli hot springs in Italy (Kvist et al., 2005), Bor
Khlueng hot springs in Thailand (Kanokratana et al., 2004), the Wai-o-tapu geothermal area in
New Zealand (Childs et al., 2008), and the Tengchong hot springs in China (Song et al., 2010).
These pioneering studies have improved our understanding of prokaryotic communities living inhigh temperature environments. However, despite decades of research, we still know little101佐藤智子，渡邉啓子，山本英夫，山本修一，黒沢則夫

温泉科学

about the relationship between the environmental characteristics of a given hot springs and its
prokaryotic community. It is important to identify the environmental factors that affectprokaryotic community structures in individual hot spring habitats. Temperature has perhaps
received the most attention, but other potential constraining factors include pH, oxidation redox
potential, elemental composition, and organic matter composition, among others.
We have surveyed a relatively wide geothermal field, the Kirishima geothermal area inJapan, and have found that this field contains many acidic ponds of various temperatures andchemical compositions. The temperature and concentration of chemical components in theseponds ranges from 63 to 94℃ and from 92 to 2,248 mg L－1, respectively. Recently, we investigated the archaeal community structures in these ponds and found that the archaeal species
diversity and composition differed between ponds (Satoh et al., 2013). However, little is known
about the distribution of bacterial communities among these ponds and how this is affected bylarger environmental variables (e.g., temperature and chemical compositions). In this study, thebacterial community structures and diversity of four distinct solfataric-acidic ponds in the
Kirishima geothermal area, Kagoshima Prefecture, Japan, were compared by 16S rRNA gene
phylogenetic analysis.

2.
2. 1

Experiments

Sample collection and analysis of chemical composition
The ponds investigated in this study were all located in a 1 km2 field in/near the region of

the Tearai hot spring (Tsuyuki, 1980). This district is situated 3 km southwest of the Ohnami-Ike
volcanic crater lake, in the Kirishima geothermal area, Kagoshima Prefecture (Fig. 1, Table 1).

Fig. 1 Map of the sampling sites in/near the region of the Tearai hot spring, the Kirishima
geothermal area, Kagoshima Prefecture.

102

第 63 巻（2013）鹿児島県霧島地域の酸性硫黄源泉における細菌群集構造の解析

Table 1 Characteristics of sampling sites, pond waters and sediments in the Kirishima
geothermal area.
Pond-A

Pond-B

Temperature (℃)
93
66
pH
2.6
2.0
Chemical concentration (mg L－1)/composition (%)
Fe
388.9
23
1149
51
S
663.2
40
702.8
31
Al
433.6
26
287.9
13
Mg
   86.74   5   46.77   2
Si   47.88   3   45.52   2
Ca   54.81   3   10.88   0
P    2.85   0    4.711   0Na    0.001   0    0.001   0
K    0.001   0    0.001   0
As    9.079   0    1.137
   0
Total
1,679
100
2,248
100
Latitude (N)31°54′37.7″
31°54′52.4″
Longitude (E)130°49′00.6″
130°48′50.3″
Altitude (m)759842Color of sediments
light brownlight brown

Pond-C

Pond-D

88
2.4

67
2.3

   9.630
   5
59.76
30
14.57
   7
   0.001
   0
103.9
53
   7.498   4   1.265   1   0.001   0   0.001   0   0.879
   0
197.5
100
31°55′05.0″
130°48′41.1″
884
gray

27.18
   8
61.90
18
   2.021
   1
43.35
13
148.4
44
39.26
12
   1.266   0   8.442   2   7.384   2   0.856
   0
340.1
100
31°55′04.5″
130°48′41.0″
885
gray

Detection limit is 0.001 mg L－1.

The Kirishima geothermal region has been characterized by extensive volcanic activity since
the Pleistocene epoch and this is continuing : this activity has resulted in the deposition of a
thick pile of volcanic rocks (Goko, 2000). The Kirishima volcano, which is one of the largest
Quaternary volcanoes in Japan, is part of the northern section of the Kagoshima graben, a
volcano-tectonic depression (Tsuyuki, 1969) caused by the subduction of the Philippine Sea plate.
The volcano occupies a 20 km×30 km area that is elongated in the northwest-to-southeast direction and contains more than 20 small volcanoes (Imura et al., 2001).
The sampling location within the Kirishima geothermal area is located on private land, andthus, the area is not usually exposed to human activity. We obtained permission from an ownerof the land to sample the hot springs and pond water as well as soil and various other samplesof organisms native to the area. There are many hot springs and muddy ponds present in thearea, and these have a variety of temperatures and elemental compositions.
Muddy water samples from each pond were collected in sterile 100 mL glass bottles. The
temperature and pH of the samples were measured at each sampling site. Part of each sample
was filtered using a 0.22 μm membrane filter (Asahi Glass) and used for analysis of the chemicalcomposition, which was performed by inductively coupled plasma optical emission spectroscopy(ICPS-7000 Ver.2, Shimadzu). We selected four ponds characterized by a wide range of temperatures and chemical compositions for the bacterial community analysis.
2. 2

16S rRNA gene clone libraries and sequencing
Environmental DNA was extracted from 10 g of each muddy water sample using the UltraClean103佐藤智子，渡邉啓子，山本英夫，山本修一，黒沢則夫

温泉科学

Soil DNA Kit Mega Prep (Mo Bio Laboratories) according to the manufacturer’s instructions.
The purified DNA was then used as the template for amplification of the bacterial 16S rRNA
gene using the bacteria-specific primer B27F (5′-AGAGTTTGATCCTGGCTCAG-3′) and theuniversal primer U1492R (5′-GGYTACCTTGTTACGACTT-3′). The PCR conditions included an
initial denaturation step at 94℃ for 3 min, followed by 35 cycles of denaturation at 94℃ for 30 s,
annealing at 58℃ for 30 s, and extension at 72℃ for 2 min using Ex Taq DNA polymerase (Takara
Bio). This was followed by a final extension step at 72℃ for 10 min.
The PCR products were purified using a GFX PCR DNA and Gel Band Purification Kit (GEHealthcare) and ligated into the pT7 Blue T-Vector (Novagen). Escherichia coli DH5α cells weretransformed with the plasmid library and plated onto LB plates including 100 µg mL－1 ampicillin,
40 µg mL－1 X-gal, and 0.5 mM IPTG. Blue/white selection was performed by randomly picking
and subculturing individual white colonies in 100 μL of 2×YT medium containing 100 μg mL－1
ampicillin in a 96-well plate at 37℃ overnight. The inserted 16S rRNA gene was amplified using
1 μL of the culture as the template with the forward primer T7P-F (5′-TAATACGACTCACTATAGGG-3′) and reverse primer T7U-R (5′-GTTTTCCCAGTCACGACGT-3′). About 800 bp of the5′-region of each 16S rRNA gene clone was sequenced using the aforementioned bacteria-specificprimer B27F and used for the taxonomic and phylogenetic analyses.
2. 3

Identiﬁcation of 16S rRNA gene clones and phylogenetic analysis
16S rRNA gene sequences were edited using MEGA5 (Molecular Evolutionary Genetics

Analysis, http : //www.megasoftware.net/) (Tamura et al., 2011). We also searched for chimera
sequences by manually checking the sequence alignments using GENETYX Ver.10.0.3 software(Genetyx). Clones with 97% or greater sequence similarity were treated as a phylotype. The
representative sequences of each phylotype were compared with 16S rRNA gene sequences
published in the National Center for Biotechnology Information DNA database using BLAST(BLASTN ; http : //www.ncbi.nlm.nih.gov/BLAST/) (Altschul et al., 1990) to identify individualclones. The representative sequences of each phylotype and related sequences in the GenBank
database were aligned using CLUSTALW Ver.1.83 (Thompson et al., 1994). A maximum likelihood
tree including bootstrap probabilities (1000 samplings) was constructed using MEGA5.
2. 4

Statistical analyses
Measurements of diversity ideally include richness, which is the number of different species

or groups present, and evenness, which is the distribution of those groups (Hurlbert, 1971 ;Stirling and Wilsey, 2001). The Shannon-Weaver index (Shannon et al., 1949), H′＝－Σ (pi) (ln pi),and Simpson’s reciprocal index (Simpson, 1949), 1/D, where D＝Σ (pi)2 and pi is the proportion ofphylotypes i relative to the total number of phylotypes, both consider richness and evenness(Stirling and Wilsey, 2001 ; Stout et al., 2009). In this study, the Shannon-Weaver index andSimpson’s reciprocal index were calculated using ESTIMATES 8.0 (Colwell, 2006). Evenness ( J′＝H′/ln S) was also calculated (Pielou, 1969). ESTIMATES 8.0 was also used to calculate theChao1 nonparametric richness estimator (Chao, 1987) and the abundance-based coverage
estimator of species richness (ACE) (Chao et al., 2000). These coverage estimators determine thenumber of probable phylotypes in the environment compared with the number observed in the104

第 63 巻（2013）鹿児島県霧島地域の酸性硫黄源泉における細菌群集構造の解析

sample. Homologous coverage (biodiversity coverage) C was determined using the following
equation : C＝1－(N/n), where N is the number of phylotype sequences detected and n is thetotal number of clones analyzed (Good, 1953 ; Singleton et al., 2001). Statistical analysis also
included principal components analysis, which was used to determine correlations among
bacterial diversity and environmental factors including temperature and chemical composition.
Canonical correlation analysis was also used to detect correlations between bacterial groups andtemperature or chemical components using XLSTAT software (Addinsoft, New York, NY).
2. 5

Nucleotide sequence accession numbers
Representative nucleotide sequences of the phylotypes are available in the DDBJ/EMBL/

GenBank databases under accession numbers AB762419-AB762465.

3.
3. 1

Results and Discussion

Water chemistry
The four ponds in the Kirishima geothermal area were selected based on their different

temperatures and total concentration of examined chemical components : 1) Pond-A : 93℃ and
1,679 mg L－1 ; 2) Pond-B : 66℃ and 2,248 mg L－1 ; 3) Pond-C : 88℃ and 198 mg L－1 ; and 4) Pond-D :67℃ and 340 mg L－1. The characteristics of the sampling sites and these ponds are shown in
Table 1. The pH value of the ponds ranged from 2.0-2.6. In the ponds with higher concentrations of the examined chemical components, the concentration and percentage of Fe, S, and Al,
in particular, were higher than in the other ponds.
To clarify the relationships between temperature and chemical composition or among thechemical components of the four ponds, Pearson’s correlation coefficients (r) were calculated(Table 2). Several chemical components were found to be correlated with each other. For
Table 2 Correlation matrix showing r values for Pearson’s correlation among factors in the pond
waters of the Kirishima geothermal area.
Variables

Temp.

Fe

S

Al

Mg

Si

Ca

P

Na

K

As

Total
conc.

Shannon

Temp.
Fe
S
Al
Mg
Si
Ca
P
Na
K
As
Total conc.
Shannon

1.00
－0.40
0.05
0.31
0.12
－0.29
0.29
－0.29
－0.55
－0.55
－0.01
－0.14
－0.34

－0.40
1.00
0.84
0.62
0.34
－0.76
－0.26
0.99
－0.46
－0.46
0.90
0.92
－0.68

0.05
0.84
1.00
0.95
0.71
－0.93
0.21
0.91
－0.57
－0.57
0.99
0.98
－0.74

0.31
0.62
0.95
1.00
0.82
－0.90
0.44
0.72
－0.57
－0.57
0.90
0.87
－0.68

0.12
0.34
0.71
0.82
1.00
－0.49
0.82
0.44
－0.02
－0.02
0.61
0.64
－0.14

－0.29
－0.76
－0.93
－0.90
－0.49
1.00
0.00
－0.83
0.84
0.84
－0.94
－0.89
0.93

0.29
－0.26
0.21
0.44
0.82
0.00
1.00
－0.15
0.33
0.33
0.07
0.08
0.32

－0.29
0.99
0.91
0.72
0.44
－0.83
－0.15
1.00
－0.51
－0.51
0.95
0.97
－0.72

－0.55
－0.46
－0.57
－0.57
－0.02
0.84
0.33
－0.51
1.00
1.00
－0.62
－0.51
0.96

－0.55
－0.46
－0.57
－0.57
－0.02
0.84
0.33
－0.51
1.00
1.00
－0.62
－0.51
0.96

－0.01
0.90
0.99
0.90
0.61
－0.94
0.07
0.95
－0.62
－0.62
1.00
0.99
－0.79

－0.14
0.92
0.98
0.87
0.64
－0.89
0.08
0.97
－0.51
－0.51
0.99
1.00
－0.71

－0.34
－0.68
－0.74
－0.68
－0.14
0.93
0.32
－0.72
0.96
0.96
－0.79
－0.71
1.00

Values in bold are different from 0 with a significance level α＝0.10. The only Shannon-Weaver index for bacterial clone
libraries is shown. Temp., Total conc. and Shannon indicate Temperature, total concentration of examined chemicalcomponents and Shannon-Weaver index, respectively.

105佐藤智子，渡邉啓子，山本英夫，山本修一，黒沢則夫

温泉科学Fig. 2 Principal components analysis showing the environmental variables of the four ponds.  
(a) Factor loadings on principal components 1 and 3, (b) relationships between the four
ponds and the principal components.

example, Fe was strongly correlated with P, and As, and S was strongly correlated with Al, Si, P,
and As. The total concentration of the examined chemical components was also strongly
correlated with Fe, S, P, and As. Temperature was not statistically correlated with any of thechemical components.
We also attempted to perform the principal components analysis to distinguish the four
ponds based on environmental variables (Fig. 2). All the variables characterizing the sites wereexplained by three principal factors : Factor 1 (F1) 61%, Factor 2 (F2) 21%, and Factor 3 (F3)18%. F1 was strongly loaded by Si (positively) and S, As, and Al (negatively) ; F2 was strongly
loaded by Ca ; and F3 was strongly loaded by temperature. In this analysis, we focused on theprincipal components 1 and 3 (PC1 and PC3), which affected F1 and F3, respectively. Strong
contributions to PC1 were made by S, As, Al, and Si and moderate contributions were made by
P, Fe, K, and Na. Temperature contributed strongly to PC3 (Fig. 2a). These environmental
variables were defining characteristics of the four ponds (Fig. 2b), and we therefore discuss thebacterial community structures by concentrating on these elements and the different temperatures of the ponds in the following sections.
3. 2Bacterial 16S rRNA gene clone libraries
The 16S rRNA gene clone libraries of domain Bacteria were successfully constructed using

environmental DNA extracted from four muddy water samples. A total of 372 clones (Pond-A :95, Pond-B : 94, Pond-C : 92, Pond-D : 91 clones) of the bacterial 16S rRNA gene were analyzed.
No chimerical sequences were detected. The clones were classified into 35 phylotypes on thebasis of the sequence similarity values, and these consisted of 10 classes : Flavobacteria,
γ-Proteobacteria, β-Proteobacteria, α-Proteobacteria, Nitrospirae, δ-Proteobacteria, Bacilli, Actinobacteria, Thermotogae, and Aquificae (Table 3, Fig. 3).

106

第 63 巻（2013）鹿児島県霧島地域の酸性硫黄源泉における細菌群集構造の解析

Table 3 Affiliation and closest published species or clones of 35 phylotypes of bacteria detectedin the ponds of the Kirishima geothermal area.
Phylotypes

Affiliation

Closest species or clones (accession number)

16S rRNAgene
similarity(%)

Number of clones detectedfrom each site
Pond
-A

Pond
-B

Pond
-C

Pond
-D

3

6

class Flavobacteria
ST16B10-59

Elizabethkingia miricola

Elizabethkingia miricola (EU375848)

99.0

ST8B3-52

Chryseobacterium aquaticum
class γ-Proteobacteria

Chryseobacterium aquaticum (AM748690)

100.0

2

ST8B3-2Acinetobacter johnsonii

Acinetobacter johnsonii (NR044975)

98.9

64

ST15B2-3

Acinetobacter junii

Acinetobacter junii (NR026208)

99.7

ST8B3-33

Acinetobacter sp.

Subsurface groundwater clone BANW433 (DQ264432)

96.8

Acidithiobacillus caldus

Acidithiobacillus caldus (NR026517)

99.6

ST8B3-10

Pseudomonas poae

Pseudomonas poae (AJ492829)

99.4

7

ST8B3-13

Uncultured Pseudomonadaceae

Maple sap clone 100p3_613 (FJ934668)

95.4

1

ST16B4-80

Uncultured Pseudomonadales

Subsurface groundwater clone BANW563 (DQ264531)

97.1

ST15B8-95

Uncultured Pseudomonadales

Coastal urnaban watershed clone C01JMA (JF692239)

95.3

ST8B3-37

Uncultured Pseudomonadales

Subsurface groundwater clone BANW416 (DQ264418)

98.0

2

ST8B3-15

Uncultured Pseudomonadales
Uncultured γ-Proteobacteria

Lake stream water clone D-79 (HQ860678)

94.4

1

Bioleaching pulp with pH < 2.0 clone zy-5 (EF672753)

92.5

ST15B2-44

Uncultured γ-Proteobacteria
class β-Proteobacteria

Acinetobacter junii (NR026208)

90.8

ST8B3-23

Acidovorax temperans

Acidovorax temperans (NR028715)

99.2

Delftia tsuruhatensis

Delftia tsuruhatensis (NR024786)

99.5

8

5

Naxibacter alkalitolerans

Massilia alkalitolerans (AY679161)

98.0

3

3

ST16B4-10

Paracoccus marinus

Paracoccus marinus (AB185957)

98.4

ST8B3-40

Curvibacter lanceolatus

Curvibacter lanceolatus (NR024702)

99.5

ST2B4-26

Ralstonia pickettii

Ralstonia pickettii (NR043152)

100.0

ST8B3-18

Methylophilus leisingeri

Methylophilus leisingeri (NR041258)

99.5

ST16B5-42

Uncultured Comamonadaceae

Spacecraft assembly clean room Delftia sp. clone GI5-13-D06 (FJ192433)

98.5

ST8B3-46

Uncultured Methylophilaceae

1

Uncultured Methylophilaceae
class α-Proteobacteria

Uranium-contaminated aquifer clone 1013-28-CG9 (AY532564)
River site β-proteobacterium clone RBE2CI-98 (EF111184)

93.4

ST8B3-58

91.1

1

ST2B3-49

Acidicaldus organivorans

Acidicaldus organivorans (AY140238)

99.6

1

(=ST15B2-2)

52(=ST16B3-5)
34
1

1(=ST2B3-83)
ST2B3-1

41

4(=ST15B3-22)

1

2(=ST15B8-1)

ST2B3-60

2

1
1
3

11

(=ST16B3-18)
ST16B3-9(=ST15B2-50)
ST16B3-16(=ST15B3-82)
6
1
1
1
1

2

(=ST15B2-13)class Nitrospirae
ST2B3-57

Uncultured Nitrospirales
class δ-Proteobacteria

Acid mine drainage sediment clone H50 (DQ328622)

99.6

1

ST2B3-15

Uncultured δ-Proteobacteria

Extreme acid mine drainage clone BA71 (AF225447)

97.3

41

Staphylococcus epidermidis

Staphylococcus epidermidis (NR036904)

100.0

1

ST16B3-94

Uncultured Paenibacillaceae

Bacillus sp. YNPRH6P-1 (AF465647)

99.2

ST2B3-86

Uncultured Bacillales

Drinking bulk water clone SW-3S_A04 (JX286150)

99.5

ST8B3-7

Uncultured Bacillales

Banana plantation soil clone WB128 (JX133663)

88.0

5

Propionibacterium acnes

Propionibacterium acnes (NR040847)

99.3

5

Uncultured Acidimicrobiales

Hot spring clone SK299 (AY882848)

99.2

1

Thermal spring sediment clone kma134 (HM149925)

98.6

2

Hot spring Hydrogenobaculum sp. clone KOZ166 (EF156606)

97.6

class Bacilli
ST2B3-24

13(=ST15B2-14)73class Actinobacteria
ST8B3-32

10(=ST15B9-35)
ST2B3-20class Thermotogae
ST2B4-6

Uncultured Thermotogae1(=ST15B8-31)
class Aquificae
ST15B2-55
Total

Hydrogenobaculum sp.

8
95

94

92

91

107

佐藤智子，渡邉啓子，山本英夫，山本修一，黒沢則夫

温泉科学Fig. 3 Phylogenetic tree of bacterial 16S rRNA gene clones detected in the four ponds from theKirishima geothermal area.  Bootstrap values (>50%) based on 1000 replicates are indicated at
nodes.   The scale bar indicates the number of nucleotide substitutions per position.   Thenumber in parenthesis with next to the phylotype name represents the number of clones fromeach phylotype.   The DNA database accession numbers are also indicated in parentheses.  
Archaeoglobus fulgidus was used as an outgroup species.  The phylotype names derived from
Ponds-A, B, C, and D are shown in blue, yellow, red, and green, respectively.

108

第 63 巻（2013）
3. 3

鹿児島県霧島地域の酸性硫黄源泉における細菌群集構造の解析

Bacterial community in Pond-A
Pond-A was characterized by relatively high temperature and high total concentration of

the examined chemical components. Analysis of 16S rRNA gene sequence similarities of the 95
clones derived from the pond revealed 14 phylotypes, which was the largest number of phylotypes detected of all four ponds (Table 3). Of the sequences derived from this pond, 87% werevery similar to those of cultured species (＞98.9%), including Chryseobacterium aquaticum (Kim etal., 2008) from the class Flavobacteria ; Acinetobacter johnsonii (Bouvet and Grimont, 1986) and
Pseudomonas poae (Behrendt et al., 2003) from the class γ-Proteobacteria ; Acidovorax temperans(Willems et al., 1990), Curvibacter lanceolatus (Ding and Yokota, 2004) and Methylophilus leisingeri(Doronina and Trotsenko, 1994) from the class β-Proteobacteria ; and Propionibacterium acnes
from the class Actinobacteria (Douglas and Gunter, 1946 ; Moore and Cato, 1963 ; Bojar andHolland, 2004). The largest number of clones was assigned to a single phylotype, ST8B3-2, which
accounted for 67% of all clones derived from this pond. This phylotype was also dominant in
Pond-C and was very similar to the sequence of A. johnsonii (98.9%), which is an aerobic, gramnegative, heterotrophic bacteria with an optimal growing temperature of 15-30℃ ; no growthoccurs at 37℃. The genus Acinetonbacter is widely distributed in soil, water (Baumann, 1968),
and sewage (Warskow and Juni, 1972). The second dominant phylotype was ST8B3-10, which
was very similar to the P. poae sequence (99.4%). This species is an aerobic, gram-negative,
heterotrophic, fluorescent bacteria that has an optimal growth temperature of 21℃ ; no growthoccurs at 41℃. The bacteria was isolated from the phyllosphere of grasses (Behrendt et al.,2003). These were unexpected results because these mesophilic microbes should not have beenable to grow in Pond-A given its high temperature. At the moment, we have no reasonable
explanation for these findings, but it is known that some species with closely related 16S rRNA
gene sequences have different optimal growth temperatures. For example, we recently describeda novel Paenibacillus species that is the only thermophilic strain of the genus Paenibacillus,
which has to date only consisted of mesophilic species (Ueda et al., 2013). On the other hand, theremaining 13% of all clones derived from Pond-A were classified into seven phylotypes, and they
did not show any significant similarity with any cultured species. The Shannon-Weaver index
score for Pond-A was the third highest among these four ponds ; it was lower than those of
Pond-C and Pond-D but higher than that of Pond-B (Table 4).
3. 4

Bacterial community in Pond-B
Pond-B was characterized by a relatively low temperature and a high total concentration of

the examined chemical components ; it had the lowest Shannon-Weaver index diversity score of
all four ponds (Table 4). A total of 94 clones were derived from Pond-B, and these were
determined to constitute 11 phylotypes (Table 3). Nearly half of the sequences in this pond
showed a significantly close relationship with one of the following four cultured species (＞99.6%) :Acidithiobacillus caldus (Hallberg and Lindstörm, 1994 ; Kelly and Wood, 2000) from the classγ-Proteobacteria ; Ralstonia pickettii (Ralston et al., 1973 ; Yabuuchi et al., 1995) from the class
β-Proteobacteria ; Acidicaldus organivorans (Johnson et al., 2006) from the class α-Proteobacteria ;and Staphylococcus epidermidis from the class Bacilli (Schleifer and Kloos, 1975). Almost all theclones were assigned to a single phylotype, ST2B3-1, which was very similar to the sequence of109佐藤智子，渡邉啓子，山本英夫，山本修一，黒沢則夫

温泉科学

A. caldus (99.6%) ; these clones accounted for 44% of all clones derived from this pond. A. caldus
is an aerobic, gram-negative, moderately thermophilic, sulfur-oxidizing acidophile with an optimal
growth pH of 2-2.5 and temperature of 45℃. This species is also capable of chemolithotrophic
growth on reduced sulfur and molecular hydrogen. On the other hand, 53% of the Pond-B clones
constituted seven phylotypes that showed no significant similarity with any cultured species ;this was the highest percentage of cultured species among the four ponds. Most of the uncultured
clones were assigned to the phylotype ST2B3-15, which affiliated with the class δ-Proteobacteria(Fig. 3). This phylotype showed the closest match to a published environmental clone BA71,
which was detected from a lithotrophic biofilm at an extreme acid mine drainage site (DNAdatabase Accession No. AF225447) (Bond et al., 2000). The clones of this phylotype were the mostdominant in this pond, similar to the aforementioned ST2B3-1 phylotype.
3. 5

Bacterial community in Pond-C
Pond-C was another pond with a relatively high temperature, and 92 clones were derived

from this pond. These were classified into nine phylotypes, which is the lowest value of species
richness among the four ponds (Table 4). The diversity index score in Pond-C was the second
highest among the four ponds, i.e., it was lower than that of Pond-D but higher than those of
Pond-A and Pond-B. Ninety percent of the sequences from this pond were very similar to thefollowing cultured species (＞98.0%) : Elizabethkingia miricola (Kim et al., 2005) from the class
Flavobacteria ; A. johnsonii from the class γ-Proteobacteria ; and A. temperans, Delftia tsuruhatensis(Shigematsu et al., 2003), Massilia alkalitolerans (Kämpfer et al., 2011) and Paracoccus marinus(Khan et al., 2008) from the class β-Proteobacteria (Table 3). Most clones were assigned to asingle phylotype, ST8B3-2, which was also dominant in Pond-A, and accounted for 57% of theclones derived from Pond-C. The second most dominant phylotype was ST8B3-23, which wasvery similar to the A. temperans sequence (99.2%). A. temperans is an aerobic, gram-negative
bacteria that, has been reported as an abundant member of activated sludge microbial communities (Willems et al., 1990 ; Heijstra et al., 2009). On the other hand, the remaining 10% of theclones in Pond-C were allocated to three phylotypes that did not show any significant similarity
with any cultured species.
3. 6

Bacterial community in Pond-D
Pond-D, which was characterized by a relatively low temperature and a low total

concentration of the examined chemical components, was the most diverse of the four ponds, asassessed by the Shannon-Weaver index and Simpson’s reciprocal index (Table 4). A total of 91
clones were derived from this pond and these consisted of 13 phylotypes. Eighty-two percentof the sequences from this pond were very similar to those of the following cultured species(＞98.0%) : E. miricola from the class Flavobacteria ; A. junii (Bouvet and Grimont, 1986) and A.
caldus from the class γ-Proteobacteria ; D. tsuruhatensis and M. alkalitolerans from the class
β-Proteobacteria ; and S. epidermidis from the class Bacilli and P. acnes of the class Actinobacteria(Table 3). A single phylotype, ST15B2-3, contributed 37% of all clones derived from this pond.
This phylotype was only detected in this pond and was very similar to the A. junii sequence(99.7%). A. junii is an aerobic, gram-negative, heterotrophic bacteria with an optimal growth110

第 63 巻（2013）鹿児島県霧島地域の酸性硫黄源泉における細菌群集構造の解析

temperature of 15-30℃ ; no growth occurs at 44℃. The second most dominant phylotype was
ST2B3-24, which accounted for 14% of the clones in this pond. This phylotype was very similar
to the S. epidermidis sequence (100.0%). S. epidermidis is an aerobic, gram-positive, heterotrophic
bacteria that is ubiquitous in the environment. It has been isolated from human skin ; animal
products such as meat, milk, and cheese ; and other sources including soil, sand, seawater,
freshwater, dust, and air (Kloos et al., 1991 ; Wieser and Busse, 2000). On the other hand, 18% of
the clones from Pond-D consisted of six phylotypes that did not show any significant similarity
to any cultured species. Most of these uncultured clones were assigned to the ST15B2-55
phylotype, which is affiliated with the class Aquificae (Fig. 3). This phylotype was only detectedin this pond and showed the closest match to a published environmental clone KOZ166 (97.6%)
detected from Yellowstone National Park (DNA database Acc. No. EF156606).
3. 7 Bacterial diversity and community structure in relation to different temperaturesand different total concentrations of the examined chemical components
At least 85% of the 16S rRNA gene sequences from each pond could be analyzed since thehomologous coverage values were 0.85 or above for all ponds (Table 4). When diversity wascompared for ponds of different temperatures (Temp. approx. 90℃, Pond-A＋Pond-C vs. Temp.
approx. 70℃, Pond-B＋Pond-D), the lower temperature ponds showed higher diversity according
to the Shannon-Weaver index and Simpson’s reciprocal index values (Table 4). On the other
hand, when ponds with different concentrations of the examined chemical components werecompared, the diversity indices for the ponds with lower concentrations of the chemical components (Pond-C＋Pond-D, Total conc. ＜350 mg L－1) were higher than those for the ponds withhigher concentrations (Pond-A＋Pond-B, Total conc. ＞1,600 mg L－1). As a result, the bacterial
diversity was highest in the pond characterized by a lower temperature and a lower concentration of chemical components (Pond-D). In contrast, the combination of higher temperature andTable 4 Diversity index scores for clone libraries of bacteria detected in the ponds of the Kirishima
geothermal area.
SamplePond-A
Pond-B
Pond-C
Pond-D
Temp. approx. 90℃(Pond-A＋Pond-C)
Temp. approx. 70℃(Pond-B＋Pond-D)
Total conc. >1600 mgL－1(Pond-A＋Pond-B)
Total conc. <350 mgL－1(Pond-C＋Pond-D)

Shannon

Simpson

Rich

Even

SACE

SChao1

Coverage

Total clone
number

1.38
1.25
1.48
2.04

2.14
2.61
2.83
5.12

14
11
9
13

0.521
0.523
0.676
0.796

23.8
28.8
10.2
14.2

26.3
21.5
10.0
13.3

0.85
0.88
0.90
0.86

95
94
92
91

1.66

2.51

21

0.544

31.0

41.3

0.89

187

2.23

6.42

21

0.733

29.4

29.2

0.89

185

2.00

4.70

24

0.630

42.9

42.0

0.87

189

2.33

7.09

17

0.823

17.9

17.5

0.91

183

Diversity index scores measured were Shannon-Weaver (Shannon), Simpson’s reciprocal index (Simpson),Richness (Rich), Evenness (Even), the coverage estomators SACE and SChao1 and the homologous coverage.
Total conc. indicates total concentration of examined chemical components.

111佐藤智子，渡邉啓子，山本英夫，山本修一，黒沢則夫

温泉科学

higher total concentration of the examined chemical components (Pond-A) resulted in the lowest
diversity in this study.
With regard to species composition and distribution, these were different in ponds characterized by different temperatures and different total concentrations of the examined chemicalcomponents. As shown in Table 3, the dominant bacterial group across all ponds was the classγ-Proteobacteria. At a lower taxonomic level, within the class γ-Proteobacteria, phylotype
ST8B3-2, which is very similar to the A. johnsonii sequence (98.9%) and is affiliated with theorder Pseudomonadales, was only detected in the higher temperature ponds (Pond-A＋Pond-C).
On the other hand, phylotype ST2B3-1, which is very similar to the A. caldus sequence (99.6%)
and is affiliated with the order Acidithiobacillales, was only detected in the lower temperature
ponds (Pond-B＋Pond-D). These results suggest that the species composition and distribution
within the class γ-Proteobacteria differs for higher and lower temperature ponds. On the other
hand, the species composition and distribution also varied between ponds with different total
concentrations of the examined chemical components. Phylotype ST8B3-33, which is affiliatedwith the genus Acinetobacter spp., was only detected in the ponds with higher concentrations of
the total examined chemical components (Pond-A＋Pond-B). In contrast, phylotypes such as
ST16B3-9, ST16B3-16, and ST16B5-42, which are affiliated with the order Burkholderiales, were
only detected in ponds with lower total concentrations of the examined chemical components(Pond-C＋Pond-D).
3. 8

Geochemistry and bacterial diversity or group correlations
As shown in Table 2, bacterial diversity was statistically correlated with Si, Na, and K. To

clarify the relationships between bacterial groups and the temperature or chemical compositionof the four ponds, canonical correlation analysis was performed (Fig. 4). Specific bacterial groups

Fig. 4 Canonical correlation analysis showing correlations between environmental
factors and proportions of individual bacterial groups.  Bacterial groups are shownin abbreviations in a rhombus shape.  Environmental factors are shown in circles.

112

第 63 巻（2013）鹿児島県霧島地域の酸性硫黄源泉における細菌群集構造の解析

were found to be correlated with particular factors : the classes δ-Proteobacteria, α-Proteobacteria,
and Nitrospirae were strongly correlated with Fe and P, the classes Bacilli and Flavobacteriawith Si, Na, and K, and Actinobacteria with Na and K. On the other hand, the classes
γ-Proteobacteria and Thermotogae were positively and negatively correlated with temperature,
respectively. These statistical analyses indicated that there are correlations between bacterial
diversity and environmental factors, and these will allow us to begin tracing trends in environmental effects on bacterial diversity. However, linking these types of studies with culture-based
studies will provide more insight into how specific elements affect bacterial communities.

4. Conclusion
In this study, 16S rRNA gene phylogenetic analysis was performed to compare the bacterial
community structure and diversity of four distinct solfataric-acidic ponds in the Kirishima
geothermal area, Kagoshima Prefecture, Japan. The four ponds displayed a wide range oftemperatures and chemical compositions. Principal components analysis showed that these four
ponds were clearly distinguished by different chemical compositions and temperatures. In
general, the dominant bacterial group in the four ponds was the class γ-Proteobacteria followedby the classes β-Proteobacteria, δ-Proteobacteria, Bacilli, and Actinobacteria. Members of theclasses Flavobacteria, Aquificae, Thermotogae, α-Proteobacteria, and Nitrospirae were also detected, but they were not as abundant. On the other hand, the bacterial diversity and community composition at the species level was clearly different among ponds with different temperatures and chemical compositions. Bacterial diversity was most affected by temperature, andspecies composition appeared to be affected by both chemical composition and temperature.
Although other environmental factors could also have influenced the bacterial community
structure, the present data will be helpful for improving our understanding of the bacterial
ecology in the solfataric-acidic ponds. In addition, the 16S rRNA gene clones that showed nosignificant similarity with any cultured species should allow us to isolate some novel bacterial
species via culturing experiments.
Acknowledgments
We thank Mr. Fuchinoue and Mr. Wada for their support with field sampling. We also
thank Prof. Dr. Taguchi and Dr. Kok for their valuable suggestions for improving this paper.
The authors would like to thank Enago (www.enego.jp) for English language review.
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