Abundant and diverse arsenic-metabolizing
microorganisms in peatlands treating arsenic-
contaminated mining wastewaters
Katharina Kujala ,1* Johannes Besold,2
Anu Mikkonen,3 Marja Tiirola3 and
Britta Planer-Friedrich2
1Water Resources and Environmental Engineering
Research Unit, University of Oulu, Oulu, Finland.
2Environmental Geochemistry, Bayreuth Center for
Ecology and Environmental Research (BayCEER),
University of Bayreuth, Bayreuth, Germany.
3Department of Biological and Environmental Science,
Nanoscience Center, University of Jyväskylä, Jyväskylä,
Finland.
Summary
Mining operations produce large quantities of waste-
water. At a mine site in Northern Finland, two natural
peatlands are used for the treatment of mining-
influenced waters with high concentrations of sulphate
and potentially toxic arsenic (As). In the present study,
As removal and the involved microbial processes in
those treatment peatlands (TPs) were assessed.
Arsenic-metabolizing microorganisms were abundant
in peat soil from both TPs (up to 108 cells gdw
−1), with
arsenate respirers being about 100 times more abun-
dant than arsenite oxidizers. In uninhibited microcosm
incubations, supplemented arsenite was oxidized
under oxic conditions and supplemented arsenate was
reduced under anoxic conditions, while little to no oxi-
dation/reduction was observed in NaN3-inhibited
microcosms, indicating high As-turnover potential of
peat microbes. Formation of thioarsenates was
observed in anoxic microcosms. Sequencing of the
functional genemarkers aioA (arsenite oxidizers), arrA
(arsenate respirers) and arsC (detoxifying arsenate
reducers) demonstrated high diversity of the As-
metabolizing microbial community. The microbial com-
munity composition differed between the two TPs,
which may have affected As removal efficiencies. In
the present situation, arsenate reduction is likely the
dominant net process and contributes substantially to
As removal. Changes in TP usage (e.g. mine closure)
with lowered water tables and heightened oxygen
availability in peat might lead to re-oxidation and re-
mobilization of bound arsenite.
Introduction
Mining operations produce large amounts of wastewater,
which have to be purified prior to their release into the
environment (Ledin and Pedersen, 1996). Mining-
affected waters contain a variety of contaminants. The
contaminant content depends on the type of ore mined
and on the ore beneficiation processes. Typical contami-
nants in mining-affected waters include nitrogen com-
pounds (from remnant explosives or the ore beneficiation
process), sulphate (from oxidation of sulphidic ores)
as well as (potentially toxic) metals and metalloids
(Nordstrom, 2011). Arsenic (As) minerals often accom-
pany gold and copper ores, since they all share the
same chalcophillic behaviour, and beneficiation of these
ores can release As via process waters into the environ-
ment (Matschullat, 2000; Bissen and Frimmel, 2003;
Nordstrom, 2011). Here, the mobility, bioavailability and
toxicity of As strongly depends on As speciation. In most
terrestrial environments, the oxyanions arsenate
(HxAs
VO4
x-3, x = 1–3) and arsenite (HxAs
IIIO3
x-3, x = 1–3)
dominate under oxidizing and reducing conditions
respectively (Bissen and Frimmel, 2003).
Wetlands, including natural peatlands, are widely used
for the treatment of different kinds of runoffs and waste-
waters, as they retard the water flow and provide a large
active surface area (Ledin and Pedersen, 1996; Sheoran
and Sheoran, 2006; Vymazal, 2011). Contaminants are
removed from the water by plant uptake, microbially
catalysed redox-processes, precipitation and adsorption
onto plant roots and soil particles (Sheoran and
Sheoran, 2006).
Under oxic conditions, mostly in the upper peat layers,
As can adsorb to (oxyhydr-)oxides of iron, manganese,
or aluminium (Bissen and Frimmel, 2003). Under suboxic
Received 27 August, 2018; revised 17 January, 2020; accepted 20
January, 2020. *For correspondence. E-mail katharina.kujala@oulu.
fi; Tel. +358 44 9645055.
© 2020 The Authors. Environmental Microbiology published by Society for Applied Microbiology and John Wiley & Sons Ltd.
This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, which permits use,
distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.
Environmental Microbiology (2020) 22(4), 1572–1587 doi:10.1111/1462-2920.14922
to anoxic conditions and in the presence of sulphur,
(hydr-)oxides may dissolve. The released or newly
formed arsenite can either react with zerovalent sulphur
and sulphide to form thioarsenates (HxAs
VS-IInO4−
nx-3;
n = 1–4; x = 1–3) at neutral to alkaline pH (Planer-
Friedrich et al., 2015; Besold et al., 2018) or bind to natu-
ral organic matter (NOM) via sulfhydryl groups at slightly
acidic pH (Hoffmann et al., 2012; Langner et al., 2012;
Besold et al., 2018). At strongly acidic pH and in
extremely reducing microenvironments arsenite eventu-
ally precipitate as As-sulphides. While at acidic condi-
tions, thiol-binding and As-sulphide formation are
considered rather stable, even if the peat gets intermit-
tently oxic (Langner et al., 2012, 2014), thioarsenate for-
mation may lead to (re-)mobilization of As at neutral to
alkaline pH in presence of reduced inorganic sulphur
(Besold et al., 2018).
Microorganisms can use the oxoacids of As in their
metabolism (Oremland and Stolz, 2003; Stolz et al.,
2006). Arsenite oxidizing microorganisms (e.g. found
within the Proteobacteria, Deinococci and Crenarchaeota)
conserve energy from the oxidation of arsenite to arsenate
and can be autotrophs or heterotrophs (Oremland and
Stolz, 2003). Strains capable of arsenite oxidation have
been isolated from soils, sediments and As contaminated
waters (Salmassi et al., 2006; Garcia-Dominguez et al.,
2008; Osborne et al., 2010), and arsenite oxidizing bacte-
ria can be used for bioremediation purposes (Battaglia-
Brunet et al., 2002). The arsenite oxidase (AioAB) is the
key enzyme in arsenite oxidation, and aioA has been fre-
quently used as a genetic marker for arsenite oxidation
(e.g. Inskeep et al., 2007; Escudero et al., 2013;
Hamamura et al., 2013; Zhang et al., 2015). In wetlands,
arsenite oxidation is likely restricted to the uppermost
layers, as the water-saturated conditions prevent diffusion
of oxygen into deeper layers.
Under anoxic conditions, microorganisms can con-
serve energy via dissimilatory reduction of arsenate to
arsenite (i.e. arsenate respiration; Oremland and Stolz,
2003; Stolz et al., 2006). Microbial arsenate reduction
has been observed in many anoxic soils and sediments
(Dowdle et al., 1996; Kulp et al., 2006; Hery et al., 2008),
and arsenate respirers have been isolated from these
systems (Hery et al., 2008; Kudo et al., 2013; Abin and
Hollibaugh, 2017). The dissimilatory arsenate reductase
(ArrAB) is the key enzyme in arsenate respiration, and
arrA has been frequently used as a genetic marker
(e.g. Malasarn et al., 2004; Lear et al., 2007; Song et al.,
2009; Escudero et al., 2013). Arsenate respiration is
feasible in lower layers of wetlands, where oxygen is
scarce and reducing conditions prevail. Furthermore,
arsenate can be reduced by the detoxifying arsenate
reductase ArsC (Oremland and Stolz, 2003), and arsC
has been used as a genetic marker for As detoxification
(e.g. Escudero et al., 2013; Costa et al., 2014; Zhang
et al., 2015). By catalysing kinetically limited transforma-
tions of As species, microorganisms can control the
retention of As in treatment peatlands (TPs) and can thus
be an important factor in the As biogeochemistry in such
systems.
Efficient removal of As in TPs is observed in the field
(Palmer et al., 2015; Kujala et al., 2018), but the role of
microorganisms in As removal remains elusive. To fill this
knowledge gap, As concentrations and As speciation in
surface and porewaters of two TPs treating mine process
waters (TP A) and drainage waters (TP B) were
assessed in the field to elucidate As transformation pro-
cesses. Then, the potential of peat soil from different
depths to oxidize/reduce arsenite/arsenate was investi-
gated in laboratory incubations in order to elaborate
potential links of As field speciation to microbial activity.
Moreover, microorganisms capable of As turnover and
resistance were quantified and the microbial community
composition was determined to see how numerous and
diverse As-cycling microorganisms are in TPs and to
identify potential key players in As species
transformation.
The obtained results about the role of microorganisms
in As removal provide valuable information for the contin-
ued use of TPs in the treatment of mining-affected
waters.
Results
Total As concentrations and speciation in TPs
As concentrations in surface water and porewater were
assessed in two TPs, one receiving mine process water
(TP A) and receiving drainage water (TP B; Fig. S1, see
Materials and Methods for full description of TPs). Total
As concentrations (Astot) in surface water were 21–28
and 33 μg L−1 near the inlet of TP A and TP B respec-
tively (Table S1). In TP A, Astot decreased rapidly with
increasing distance from the inlet (TP A1 à TP A7;
Fig. S1) to mostly below 1 μg L−1. In TP B, there was
only a slight decrease to 28 μg L−1 close to the outlet
(TP B3; Fig. S1). Arsenate was the dominant As species
in all surface water samples for which As speciation was
analysed (TP A1, A2 and TP B1, B2, B3). However, the
arsenite contribution increased in TP B with increasing
distance from the inlet (TP B1 à TP B3) from below
detection limit (TP B1) to 16% of detected species
(TP B3; Table S1).
Total As concentrations in the porewater at sampling
points/depths used for incubations and microbial commu-
nity studies ranged from 6.1 to 132 μg L−1 (Table S2). In
porewater samples, arsenate was the dominant species
at 10 cm depth near the inlet (TP A1), while arsenite was
© 2020 The Authors. Environmental Microbiology published by Society for Applied Microbiology and John Wiley & Sons Ltd.,
Environmental Microbiology, 22, 1572–1587
Arsenic-metabolizing microorganisms in peatlands 1573
the dominant species at 60 cm depth (Table S2). In addi-
tion, inorganic thiolated, methylated and methylthiolated
arsenate species were detected in the TP A1 profile,
while only methylated As species and arsenite were
detected in porewater samples from TP A5 (73%–75%
and 6%–7% of detected As species respectively).
Arsenic-utilization potential of peat microorganisms
The potential of peat microorganisms to oxidize and
reduce 50 μM supplemented arsenite and arsenate to
peat suspensions respectively, was assessed in micro-
cosm incubations prepared with deionized water. Under
oxic conditions, supplemented arsenite was oxidized to
arsenate completely within 9 days of incubation in unin-
hibited microcosms (Fig. 1B). Arsenite oxidation started
after 2 days of incubation, indicating a short lag phase in
the beginning. In microcosms where sodium azide
(NaN3) had been added as an inhibitor, no arsenite oxi-
dation was observed within the 18-day incubation period
(Fig. 1A), indicating that arsenite oxidation was catalysed
by microorganisms. NaN3 is a common inhibitor for
microbial growth and activity (e.g. Cabrol et al., 2017),
which has also been used to inhibit As redox transforma-
tions in many As-NOM studies (Buschmann et al., 2006;
Hoffmann et al., 2012; Besold et al., 2018).
Under anoxic conditions, supplemented arsenate was
reduced to arsenite completely within 9 days of incuba-
tion in uninhibited microcosms with peat from both tested
depths (Fig. 1D,F). Arsenate reduction started after a lag
phase of 2 days. Only minor arsenate reduction was
observed in NaN3 supplemented microcosms with peat
soil from 0 to 10 cm depth, while about half of the sup-
plemented arsenate was reduced to arsenite in NaN3
supplemented microcosms with peat soil from 60 to
70 cm depth (Fig. 1C,E). This finding indicates that arse-
nate reduction was not completely inhibited by NaN3 in
peat soil from 60 to 70 cm depth, which might be due to
(i) incomplete inhibition caused by rather low NaN3 con-
centrations, (ii) microorganisms that were not affected by
NaN3, or (iii) abiotic arsenate reduction with considerably
lower reaction rates. Moreover, the inhibitory effect of
NaN3 was not permanent: After 167 days of incubation,
arsenate had been reduced to arsenite in the NaN3 sup-
plemented incubations of both depths (Fig. 1C,E).
Sulphide production potential of peat microorganisms
Sulphide production potentials were determined in anoxic
microcosms with 0–10 cm peat soil from TP A5 prepared
with deionized water and additionally in incubations pre-
pared with mine process water. Initial sulphide concentra-
tions in mine process water were below the detection
limit of the assay used for the determination of sulphide
concentrations. Sulphide accumulated only in micro-
cosms without supplemented NaN3 (Fig. 2), indicating
that NaN3 almost completely inhibited sulphate reduction
in peat soil.
Using deionized water, 270 and 210 μM sulphide accu-
mulated within 167 days of incubation in microcosms with
0–10 and 60–70 cm peat respectively (Fig. 2A and 2B).
In microcosms set up with mine process water, 265 μM
sulphide had accumulated after 173 days and 330 μM
after 433 days of incubation (Fig. 2C). Accumulation of
sulphide was faster in microcosms with mine process
water than in microcosms with deionized water. This dif-
ference occurred possibly due to the more readily avail-
able sulphate in incubations with mine process water
(as mine process water contains 2100 mg L−1 sulphate).
In fact, 91 μM sulphide accumulated within 11 days in
microcosms with mine process water, while only 7 μM
Fig. 1. Arsenite-oxidation (A, B) and arsenate-reduction (C–F) poten-
tial of peat microorganisms. Incubations were conducted under oxic
(A, B) or anoxic (C–F) conditions with peat from 0 to 10 cm (A–D)
and 60 to 70 cm (E, F) depth. Microcosms were supplemented with
NaN3 to inhibit microbial activity (A, C, E) or left without inhibitor
(B, D, F) and 50 μM arsenite (A, B) or arsenate (C–F). Incubations
were done in triplicate. One replicate was analysed at all sampling
timepoints, triplicates were analysed at selected timepoints. Error
bars indicate standard errors in cases in which triplicates were
analysed.
© 2020 The Authors. Environmental Microbiology published by Society for Applied Microbiology and John Wiley & Sons Ltd.,
Environmental Microbiology, 22, 1572–1587
1574 K. Kujala et al.
sulphide accumulated within 16 days in microcosms with
deionized water (Fig. 2A,C). However, sulphide accumu-
lation in microcosms with mine process water started to
level out at later time points, indicating lower sulphate
reduction rates.
Thioarsenate production potential in peat microcosms
Thioarsenate formation was assessed in anoxic micro-
cosms prepared with deionized water and with mine pro-
cess water. Deionized water was used to avoid possible
interference of mine process water contaminants with the
formation process and to allow comparison to the arse-
nite oxidation and arsenate reduction potentials assessed
earlier, while mine process water was used to assess
the influence of increased sulphate concentrations
(2100 mg L−1 in mine process water) on thioarsenate for-
mation. Thioarsenates started to accumulate in uninhib-
ited anoxic microcosms with increasing incubation time.
After 167 days of incubation, more than half of the
detected As was in the form of thioarsenates in micro-
cosms set up with deionized water, with trithioarsenate
being the most abundant species (Fig. 1B,C). In uninhib-
ited anoxic microcosms with mine process water,
thioarsenates likewise accumulated with time (Fig. 3B).
68% of the detected As species were thioarsenates after
420 days of incubation, and trithioarsenate was the domi-
nant species as well. No thioarsenates were detected in
the NaN3 inhibited incubations with deionized or mine
process water (Figs 1C,E and 3A).
Enumeration of As-metabolizing microorganisms
As-tolerating aerobic/aerotolerant microorganisms were
abundant in TP A and TP B based on most probable
number (MPN) counts (Fig. 4). Up to 3.8 × 107 cells
gDW
−1 were detected in 0–10 cm peat soil. The cell num-
bers obtained were slightly (but not significantly) higher
with TSB than with the NB growth medium. MPNs of
arsenite-oxidizing microorganisms were about two orders
of magnitude lower than for As-tolerating microorganisms
and approximated 1.5 × 105 cells gDW
−1 in 0–10 cm peat
soil. MPNs of arsenate-respiring microorganisms ranged
from 1.6 × 106 cells gDW
−1 to 8.6 × 106 cells gDW
−1
(Fig. 4), indicating that arsenate-respiring microorganisms
were more abundant than arsenite-oxidizing microorgan-
isms in peat soil of both layers. MPNs of As-tolerating
and arsenite-oxidizing microorganisms were slightly
(but not significantly) lower in 60–70 cm peat soil,
while this trend was not observed for arsenate-respiring
microorganisms.
Fig. 2. Sulphide production in anoxic microcosms with peat soil from
TP A1. Incubations were set up in triplicate with peat from 0 to
10 cm (A, C) and 60 to 70 cm (B). Microcosms were prepared with
deionized water (A, B) or mine process water (C). Mean values with
standard errors are displayed.
Fig. 3. Influence of mine process water on thioarsenate production in
anoxic peat microcosms. Triplicate incubations were prepared with
0–10 cm peat soil (TP A1) and mine process water and were sup-
plemented with 50 μM arsenate. Microcosms were supplemented
with NaN3 to inhibit microbial activity (A) or left without inhibitor (B).
One replicate was analysed at all sampling timepoints, triplicates
were analysed at selected timepoints. Error bars indicate standard
errors in cases in which triplicates were analysed. At day 185, small
amounts of MMA(V) and DMDTA(V) were detected in microcosms
without NaN3.
© 2020 The Authors. Environmental Microbiology published by Society for Applied Microbiology and John Wiley & Sons Ltd.,
Environmental Microbiology, 22, 1572–1587
Arsenic-metabolizing microorganisms in peatlands 1575
Functional genes involved in As metabolism in TPs
Amplicon sequence libraries were obtained from two
points (one in TP A and one in TP B) and two depths per
TP in four replicates (i.e. total number of 16 amplicon
libraries per primer set) for bacterial 16S rRNA genes
and genes involved in As turnover (aioA, arrA and arsC)
with eight different primer sets (Table 1). Since two
nested approaches for arrA (As1f/r + As2f/r and
As1f/2r + As 2f/r) used the same primers in the second
PCR step, the sequences from those approaches could
not be distinguished after sequencing and are thus com-
bined in the same library. The percentages of correct
sequences (i.e. sequences that match the targeted gene)
were on average 50%, 93% and 97% for aioA, arrA and
arsC respectively. The dada2 algorithm used for quality
filtering created high-quality amplicon sequence variants
(ASVs). For the following analyses, these ASVs were
used unclustered. Amplicon sequencing of genes
involved in As turnover was most successful with the two
primer sets targeting arsC (arsC1 and arsC2), which
yielded a total of 178 470 sequences and 895 ASVs for
the non-rarefied dataset (arsC1 + arsC2) after quality fil-
tering and removal of non-target sequences. For aioA
(aioA1 and aioA2) and arrA (arrA1 and arrA2), less
sequences were obtained, with 39 691 sequences
in 582 ASVs for aioA (aioA1 + aioA2) and 65 839
sequences in 418 ASVs for arrA (arrA1 + arrA2).
PERMANOVA analysis indicated differences in commu-
nity composition obtained with different primer sets for
each gene (p < 0.001), indicating that the use of two dif-
ferent primer systems per gene likely captured a higher
diversity than the use of a single primer system.
For the estimation of diversity indicators that are
comparable between different samples, genes and
primer sets, ASV was tables rarified to a depth of
600 sequences. In the rarified ASV tables, the number of
observed ASVs was highest for arsC (Table 2). While for
aioA the number of detected ASV was only slightly lower,
significantly less ASV were detected for arrA (p = 0.04;
Table 2). Similarly, Faith’s PD was significantly higher for
aioA and arsC than for arrA (p < 0.01), indicating that the
phylogenetic diversity (PD) recovered was higher for aioA
and arsC. Shannon diversity was only slightly higher for
arrA and arsC than for aioA (not significant), while Even-
ness was significantly higher for arrA and arsC than for
aioA (p < 0.05).
Phylogenetic analysis indicated five, seven and
11 groups for aioA, arrA and arsC respectively, with indi-
vidual groups containing 2–44 ASVs or 0.5%–34% of all
sequences per gene (Fig. 5). The aioA ASVs were
related to Burkholderia multivorans and Sinorhizobium
sp. (group 1; 34%), Thiobacillus sp. and Bradyrhizobium
sp. (group 3; 8.2%), Pseudomonas arsenicoxydans,
Thiomonas sp. and Ralstonia syzygii (group 4; 3.7%)
as well as to Limnobacter sp. and Hydrogenophaga
sp. (group 5; 1.1%; Fig. 5A). The arrA ASVs were
related to arrA of Sulfuritalea hydrogenivorans and
Exiguobacterium sp. (groups 1 and 4; Fig. 5B), Geo-
bacter spp. and Desulfuromonas sp. (group 3), Geo-
bacter uraniireducens, Citrobacter sp. and Aeromonas
sp. (group 6), or were not closely related to arrA of cul-
tured organisms (groups 2, 5 and 7). The arsC ASVs
were related to Syntrophobacter sp., Syntrophus spp.
and Smithella sp. (groups 1 and 5; Fig. 5C), Sedimen-
tisphaera spp. and Chitinispirillum alkaliphilum (group 2),
fungal arsC (group 3), Bosea thiooxidans (group 6),
Bacillus spp. and Lactobacillus spp. (group 7) and Geo-
bacillus pelophilus (group 8). Sequences of group 4 were
not closely related to arsC of cultured organisms. 16S
rRNA gene amplicons were dominated by Chloroflexi,
Proteobacteria and Acidobacteria (Fig. 6).
For all As genes and primer sets, PERMANOVA analy-
sis indicated significant differences in community compo-
sition between the two TPs (p < 0.05; Fig. 6). For aioA
and arrA, depth did not affect community composition
(p ≥ 0.1), while for arsC communities differed between
depths (p < 0.01). ANCOM did not indicate any specific
ASVs characteristic for either one of the TPs or depth,
indicating that the differences in community composition
were not caused by single ASVs but rather by groups of
ASVs. The aioA groups 1 and 2 were on average more
Fig. 4. Most probable numbers (MPNs) of aerobic heterotrophic,
arsenic-tolerating, arsenite-oxidizing and arsenate-reducing prokary-
otes in peat soil from TP A1 and TP B2. MPNs and 95% confidence
intervals are shown. Incubations were conducted under oxic (aerobic
heterotrophs, arsenic-tolerating and arsenite-oxidizing) or anoxic
(arsenate-reducing) conditions. Eight replicates were used for MPNs
of aerobic heterotrophs, arsenic-tolerating microorganisms and
arsenite-oxidizing microorganism; three replicates were used for
MPNs of arsenate-reducers. Aerobic heterotrophs and arsenic-
tolerating MPNs were estimated using two different growth media
(nutrient broth = NB and tryptic soy broth = TSB).
© 2020 The Authors. Environmental Microbiology published by Society for Applied Microbiology and John Wiley & Sons Ltd.,
Environmental Microbiology, 22, 1572–1587
1576 K. Kujala et al.
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© 2020 The Authors. Environmental Microbiology published by Society for Applied Microbiology and John Wiley & Sons Ltd.,
Environmental Microbiology, 22, 1572–1587
Arsenic-metabolizing microorganisms in peatlands 1577
abundant in TP B, while aioA group 4 was on average
more abundant in TP A (Fig. 6). The arrA groups 3 and
5 were more prominent in TP A, while arrA groups 1, 4
and 6 were more prominent in TP B. The arsC groups
1, 7 and 8 were on average more abundant in TP A,
while arsC groups 2 and 6 were on average more abun-
dant in TP B (Fig. 6). Based on 16S rRNA gene analysis,
bacterial phyla were of similar relative abundance in both
TPs (Fig. 6).
Discussion
Wetlands including peatlands are widely used for the
treatment of metal-/metalloid-contaminated waters
(Sheoran and Sheoran, 2006; Vymazal, 2011). The stud-
ied peatlands have been rather effectively removing As
from mining-affected waters for up to 10 years and have
accumulated As in the peat (Palmer et al., 2015). High
retention of As was confirmed in the present study since
most of the As was retained near the inlet in mine pro-
cess water receiving TP A (less in TP B; Table S1), and
most of the As accumulated in 0–10 cm peat. Natural
peatlands have been reported to accumulate very high
concentrations of As of more than 3000 mg kgdw
−1
(González et al., 2006; Bauer et al., 2008), indicating the
potential of the TPs to accumulate even more As in future
years and thus allowing for their continued use as a puri-
fication system for mining-affected waters.
Microorganisms are capable of using different As spe-
cies in their energy metabolism or when detoxifying As
(Stolz et al., 2006) and may affect As speciation in peat.
Changes in As speciation within the TPs and/or along
depth profiles can thus indicate microbial As turnover in
peat. This was indeed observed in the field: As enters
the TPs mainly as arsenate due to the strongly oxidizing
nature of the gold extraction process (cyanide leaching),
and mainly arsenate was found in surface waters as
arsenate reduction was likely prevented in most parts by
the rather oxic conditions in those waters. However, a
higher percentage of arsenite was found near the outlet
of TP B, indicating ongoing arsenate reduction even in
rather oxic surface waters. Moreover, arsenite was
detected in all profiles and was the dominant As species
in the TP A1 profile in 50 and 60 cm depth (Table S2),
which shows that most of the arsenate reduction in TPs
is likely found in deeper, anoxic peat layers.
The high potential of the TP peat for microbially
catalysed arsenate reduction under anoxic conditions
Table 2. Diversity of different microbial groups along the gradients in TP A and TP B.
No. of sequences
ASVs
Faith PD Shannon Evenness(observed)
Arsenite oxidase
(aioA)
aioA1 (220)a TP A (0–10 cm) 3102 (1901–3696) 38 ± 15 7.33 ± 2.25 3.29 ± 1.03 0.63 ± 0.13
TP A (60–70 cm) 2298 (398–3497)b 29 ± 13 7.93 ± 3.08 2.43 ± 0.92 0.50 ± 0.12
TP B (0–10 cm) 1746 (951–3570) 34 ± 5 6.58 ± 1.06 4.12 ± 0.75 0.81 ± 0.16
TP B (60–70 cm) 1025 (197–2964)b 25 8.23 2.13 0.46
aioA2 (220) TP A (0–10 cm) 729 (263–1145)b 24 ± 1 7.05 ± 1.38 3.99 ± 0.11 0.87 ± 0.01
TP A (60–70 cm) 887 (167–2897)c 20 3.58 2.27 0.52
TP B (0–10 cm) 1853 (346–3341)b 21 ± 5 7.12 ± 2.04 2.3 ± 0.82 0.54 ± 0.25
TP B (60–70 cm) 767 (106–1847)c 9 ± 6 6.32 ± 1.99 0.51 ± 0.31 0.16 ± 0.05
Dissimilatory arsenate
reductase (arrA)
arrA1 (220) TP A (0–10 cm) 1944 (768–4362) 12 ± 3 4.36 ± 2.32 2.45 ± 0.94 0.69 ± 0.21
TP A (60–70 cm) 1626 (764–2245) 11 ± 3 4.29 ± 0.78 2.32 ± 0.49 0.67 ± 0.08
TP B (0–10 cm) 5476 (4769–6050) 29 ± 5 4.68 ± 2.07 3.96 ± 0.33 0.82 ± 0.03
TP B (60–70 cm) 3408 (2057–4509) 19 ± 4 3.67 ± 0.98 3.4 ± 0.36 0.8 ± 0.04
arrA2 (220) TP A (0–10 cm) 488 (231–856)d 13 4.34 2.96 0.80
TP A (60–70 cm) 635 (444–977)c 21 4.36 3.74 0.85
TP B (0–10 cm) 1821 (1493–2153) 17 ± 5 2.51 ± 0.43 3.23 ± 0.34 0.8 ± 0.03
TP B (60–70 cm) 1353 (1016–2042) 21 ± 7 4.71 ± 2.25 3.54 ± 0.57 0.81 ± 0.04
Detoxifying arsenate
reductase (arsC)
arsC1 (270) TP A (0–10 cm) 4857 (4455–5279) 23 ± 5 6.41 ± 0.92 3.15 ± 0.13 0.70 ± 0.02
TP A (60–70 cm) 5672 (4349–6855) 26 ± 2 8.24 ± 0.85 3.36 ± 0.28 0.71 ± 0.04
TP B (0–10 cm) 3587 (2544–4149) 21 ± 7 6.79 ± 1.72 2.77 ± 0.51 0.64 ± 0.04
TP B (60–70 cm) 3647 (2320–5191) 17 ± 5 6.33 ± 1.04 2.80 ± 0.20 0.69 ± 0.05
arsC2 (270) TP A (0–10 cm) 6470 (2092–8350) 25 ± 12 7.71 ± 5.15 3.36 ± 1.22 0.74 ± 0.16
TP A (60–70 cm) 6022 (4454–7721) 30 ± 6 13.75 ± 3.29 3.90 ± 0.30 0.80 ± 0.04
TP B (0–10 cm) 10,446 (8961–12,068) 48 ± 11 13.11 ± 4.90 4.34 ± 0.55 0.78 ± 0.05
TP B (60–70 cm) 6385 (3445–8165) 27 ± 8 7.93 ± 2.23 3.79 ± 0.37 0.81 ± 0.03
Number of sequences is obtained from the original ASV tables, while all other diversity indicators are based on rarified ASV tables (rarefied at a
depth of 600 sequences).
Average values of 1–4 replicates per sampling point are given.
a. Number in parenthesis indicates sequence length after dada2.
b. Three replicates used for diversity calculations.
c. Two replicates used for diversity calculations.
d. One replicate used for diversity calculations.
© 2020 The Authors. Environmental Microbiology published by Society for Applied Microbiology and John Wiley & Sons Ltd.,
Environmental Microbiology, 22, 1572–1587
1578 K. Kujala et al.
was demonstrated also in microcosm incubations
(Fig. 1), and arsenate respirers as well as As-tolerating
microorganisms were abundant in TPs (106–107 and
~107 cells gdw
−1 respectively) and accounted for about
36% and 50% of the general aerobic heterotrophs
(Fig. 4). The high abundance of arsenate respirers and
As-tolerators is likely responsible for fast arsenate
reduction in deeper peat layers and might thus contribute
to efficient As removal in the TPs (see below for discus-
sion of removal processes).
Arsenate reduction has been reported from a variety of
anoxic soils and sediments (Dowdle et al., 1996;
Oremland and Stolz, 2003; Kulp et al., 2006), and arse-
nate respirers have been isolated from many anoxic As-
Fig. 5. Phylogenetic trees of aioA (A), arrA (B) and arsC (C) representative sequences detected in TPs (TP A1 and TP B2). Reference
sequences from cultured species and uncharacterized microorganisms were obtained from public databases. Neighbour Joining trees were con-
structed in ARB from translated amino acid sequences of full-length references sequences using frequency-based position filters (390, 410 and
115 alignment positions used for aioA, arrA and arsC respectively), and own sequences were added to the reference trees using ARB parsimony
and frequency-based position filters tailored to the length of the added sequences. ASVs generated with the two primer sets per gene were com-
bined after normalization to relative abundances. Bootstrap values (1000 replications) are indicated, bootstrap values <50% have been omitted.
Reference sequences not closely related to TP ASVs were omitted from the final tree representation to improve readability.
© 2020 The Authors. Environmental Microbiology published by Society for Applied Microbiology and John Wiley & Sons Ltd.,
Environmental Microbiology, 22, 1572–1587
Arsenic-metabolizing microorganisms in peatlands 1579
contaminated environments (Oremland and Stolz, 2003).
However, limited information is available on arsenate
reduction and arsenate reducers in peatlands (natural or
disturbed). Thus, the present study contributes to a better
understanding of arsenate reducers in peatlands. Arse-
nate can be reduced by arsenate respiring as well as
arsenate detoxifying microorganisms. The ability to
detoxify As is important for the survival and functioning of
microorganisms in environments with elevated As con-
centrations such as the studied TPs, since As can be
toxic at rather low concentrations (Paez-Espino et al.,
2009). Moreover, soil processes such as respiration,
microbial biomass as well as functioning of enzymes like
alkaline phosphatase are inhibited by As concentrations
as low as 40–100 mg As kgDW
−1 (Ghosh et al., 2004;
Bhattacharyya et al., 2008; Liu et al., 2019), which is
much lower than the concentrations that were detected in
TP peat (around 200 mg kgDW
−1). As-tolerating bacteria
have been detected and isolated from a variety of
As-contaminated soils and can tolerate up to 15 g L−1 As
(Villegas-Torres et al., 2011; Escudero et al., 2013; Xiao
et al., 2017). On the other hand, As-sensitive microorgan-
isms such as Aliivibrio fischeri are inhibited already by
As concentrations <2 mg L−1 (Fulladosa et al., 2005).
Thus, there is a high need to detoxify As in TPs, which
would explain the high observed diversity and abundance
of As-tolerating microorganisms. Sequences of arsC from
TPs were related to arsC from bacteria, archaea and
fungi (Fig. 5C), highlighting the importance of an arsenic
detoxification mechanism for microorganisms in TPs.
Arsenic detoxification moreover contributes to arsenate
reduction and might be in part responsible for arsenate
reduction observed in microcosm studies or in the field.
Arsenate respirers from TPs as assessed by arrA
sequencing were mostly not related to arrA of cultured
microorganisms (Fig. 5B), indicating a high potential of
yet unknown arsenate respirers in TPs. These hitherto
uncharacterized arsenate respirers are likely well
adapted to the conditions in the TPs, including cold cli-
mate conditions and high contaminant loads. Some
detected groups of arrA were related to Geobacter spp.
and Sulfuritalea hydrogenivorans, species which are
known to reduce arsenate under anoxic conditions and
have been detected in many As-contaminated environ-
ments (Lear et al., 2007; Hery et al., 2008; Ohtsuka
et al., 2013; Watanabe et al., 2017). However, based on
16S rRNA gene sequencing, the overall abundance of
Geobacter and Sulfuritalea is rather low in the studied
TPs (0.5%–0.9% relative abundance; Kujala et al., 2018,
this study), highlighting the importance of the yet
unknown arsenate respirers in the system and their pos-
sible contribution to As removal. Even though arsenate
respirers were almost equally abundant in TP A and TP
B (Fig. 4), the arsenate respirer community differed
strongly between the two TPs (Fig. 6). Different kinds of
arsenate respirers likely differ in their habitat preferences
and arsenate turnover rates. Differences in TP usage
(e.g. different flow regimes, different inflow water compo-
sition different TP ages), as well as initial differences
between the TPs (e.g. peat type, peat depth), might have
selected for different microbial communities which in turn
might contribute to the observed differences in As
removal efficiencies. Arsenate respirers of arrA group
3 (related to Geobacter spp. and Desulfuromonas sp.)
and arsenate tolerators of group 1 (related to Syn-
trophobacter sp., Syntrophus spp. and Smithella sp.)
were more abundant in TP A (receiving mine process
water), indicating that those groups might be in part
responsible for the higher As removal in TP A. However,
microbial arsenic reduction is likely not the only factor
determining removal efficiencies of As in TPs, since other
factors like hydraulic load and water residence time also
contribute. Since hydraulic load is much higher for TP B
Fig. 6. Heatmap showing the relative abundance of aioA, arrA and
arsC groups as well as 16S rRNA gene phyla in TPs receiving
mining-affected waters (TP A1 and TP B2). The heatmap was gener-
ated in R (‘annHeatmap2’) from relative abundance data of the
observed groups. Average relative abundances per group were cal-
culated from relative abundances obtained for the two primer sets
per gene. Columns were clustered using average linkage hierarchi-
cal clustering based on the Bray–Curtis dissimilarity matrix of the
dataset (‘vegdist’).
© 2020 The Authors. Environmental Microbiology published by Society for Applied Microbiology and John Wiley & Sons Ltd.,
Environmental Microbiology, 22, 1572–1587
1580 K. Kujala et al.
than for TP A (38 vs. 6.1 mm day−1; Palmer et al., 2015),
this also negatively affects As removal in TP B.
Oxic microcosm incubations with supplemented arse-
nite demonstrated the potential for arsenite oxidation in
peat soil (Fig. 1) and the arsenite oxidizer community
was rather diverse (Figs 5A and 6). The potential arsenite
oxidation rate was comparable to the potential arsenate
reduction rate assessed in anoxic microcosm incubations
with supplemented arsenate (all arsenite/arsenate oxi-
dized/reduced within 9 days, Fig. 1), indicating a similar
process potential for both arsenite oxidation and arsenate
reduction. However, arsenite oxidizers were less abun-
dant in the studied TPs (105 cells gdw
−1, ~0.5% of gen-
eral aerobic heterotrophs; Fig. 4). As the TPs are
permanently water-saturated, oxygen availability in the
peat is likely low, which would restrict the growth of arse-
nite oxidizers. Abundant aioA were related to Hydro-
genophaga sp., Thiocapsa marina and Bradyrhizobium
sp. (Fig. 5A). These organisms are known arsenite oxi-
dizers and have been detected and/or isolated from a
variety of As-contaminated environments including soils,
sediments and Hot Creeks (Salmassi et al., 2006;
Garcia-Dominguez et al., 2008). However, many ASVs
were not closely related to known aioA, indicating phylo-
genetic novelty of arsenite-oxidizers in the studied TPs.
These novel arsenite-oxidizers are likely well-adapted to
the conditions in the TPs.
Both arsenite oxidation and arsenate reduction are
feasible processes in the studied TPs. Moreover, it is
conceivable that As cycling occurs within the peatlands,
leading to a reduction of arsenate in the lower, anoxic
peat layers or anoxic microenvironments in the upper
layers followed by oxidation of arsenite in the upper,
oxic layers. Such internal cycling might even occur
repeatedly. Arsenite oxidizers, arsenate respirers and
arsenic-tolerating microorganisms were detected in both
layers based on MPN counts and functional gene analy-
sis (Figs 4 and 6), indicating that those functional
groups are present in the same layers, which might
allow for switching between oxidizing and reducing pro-
cesses even within the same layer with possible
changes of environmental parameters. However, it was
not possible to determine if and how often oxidation–
reduction cycling occurred in situ, and arsenate reduc-
tion to arsenite was the observed net process. Thus, for
net As cycling, arsenate reduction is likely the dominat-
ing process as (i) arsenate is the dominating As species
in the inflow, (ii) anoxic conditions prevail through most
of the peat which would support arsenate reduction,
(iii) arsenite is found in the porewater likely as a result of
arsenate reduction, and (iv) arsenite oxidizers are less
abundant in TPs than arsenate reducers (arsenate
respirers and arsenate tolerators). However, the contri-
bution arsenite oxidation to net As cycling might
increase when changes in the water table become more
prominent, as might be the case when the use of the
TPs for water treatment is discontinued (e.g. due to
mine closure or changes in the water treatment pro-
cess). Lowered water tables would lead to enhanced dif-
fusion of oxygen into the peat and might thus allow for
the re-oxidation and re-mobilization of bound arsenite
(Langner et al., 2014), which might, in turn, lead to
leaching of bound As from the TPs.
In systems with high concentrations of arsenite and
reduced sulphur species, thioarsenate formation may
occur. Thioarsenates have been studied extensively in
extreme environments like hot springs (e.g. Planer-
Friedrich et al., 2007; Ullrich et al., 2013) or in groundwa-
ters (Wallschläger and Stadey, 2007; Planer-Friedrich
et al., 2018), while peatlands have received less atten-
tion. However, thioarsenates have been detected in a
natural As-enriched peatland just recently (Besold et al.,
2018), indicating that they may be indeed widespread in
anoxic, sulphidic environments. In the studied TPs, sul-
phate concentrations are very high, especially in TP A,
which receives mine process waters (Palmer et al.,
2015). Anoxic conditions in deeper peat layers allow for
microbial sulphate reduction to elemental sulphur and fur-
ther on to sulphide. Indeed, sulphide accumulation was
observed in anoxic microcosms (Fig. 2). After microbially
catalysed arsenate reduction to arsenite (Figs 1 and 3),
high sulphide concentrations can then lead to an abiotic
formation of thioarsenates at neutral to alkaline pH
(Planer-Friedrich et al., 2010) and a subsequent mobiliza-
tion of As in soils (Sun et al., 2016; ThomasArrigo et al.,
2016). Abiotic reduction of arsenate with sulphide can be
neglected in the microcosms (pH 6–7) as it becomes
kinetically relevant only at much lower pH (Rochette
et al., 2000).
Thioarsenate formation was observed in anoxic, unin-
hibited microcosms, and thioarsenates contributed to up
to 80% of the detected As species (Figs 1 and 3). Di-
and tri-thioarsenate were the dominating thioarsenates
formed in the microcosms. Earlier studies have shown
that high S:As ratios favour the formation of di- and tri-
thioarsenate rather than mono-thioarsenate (Planer-
Friedrich et al., 2010). S:As ratios in the microcosm
incubations were >10 in all cases, thus the observed
dominance of di- and tri-thioarsenate is in line with the
earlier studies.
Even though the results obtained from the microcosm
incubations cannot be transferred directly to the situa-
tion in situ, (re-)mobilization of bound arsenite due to
thioarsenate formation is feasible in the TPs. This study
found first indications that in peat layers where (micro-
bially formed) arsenite coincides with high microbial
sulphate reduction rates, thioarsenate formation may
occur.
© 2020 The Authors. Environmental Microbiology published by Society for Applied Microbiology and John Wiley & Sons Ltd.,
Environmental Microbiology, 22, 1572–1587
Arsenic-metabolizing microorganisms in peatlands 1581
Conclusions and outlook
The present study characterized the microbial community
composition within two TPs receiving mining-affected
waters using functional gene analysis and their As oxida-
tion and reduction potential. The most important findings
are summarized in Fig. 7. Both TPs efficiently removed
As, even though removal efficiencies were lower in TP
B. In TP A, total As concentrations were high and arse-
nate was the major As species in the inflow water, while
total As concentrations were low in the outflow. In TP B,
differences in the total As concentration between inflow
and outflow were low, reflecting the smaller removal effi-
ciencies of TP B. Like in TP A, arsenate was the domi-
nant As species, however, the contribution of arsenite
increased in TP B with increasing distance from the
inflow.
Peat microorganisms showed the potential to oxidize
and reduce arsenite and arsenate respectively, and
especially arsenate reducers were abundant in peat.
Based on the analysis of functional genes, As-
metabolizing microbes in TPs were diverse and many
detected ASVs were not closely related to cultured micro-
organisms. Sulphide and thioarsenate production were
observed in anoxic microcosms, and the formation of
thioarsenates might lead to lowered As removal or
even As remobilization. Thus, the collective data indicate
that (i) net arsenate reduction occurs in situ and is
likely catalysed by As-metabolizing microorganisms,
(ii) hitherto uncultivated arsenic-metabolizing microorgan-
isms contribute to As removal in TPs, (iii) thioarsenate
formation might lead to remobilization of bound As, and
(iv) changes in water table (e.g. after mine closure) might
lead to oxidation of bound arsenite by hitherto uncultured
arsenite oxidizers and subsequent remobilization of
bound As.
Even though the present study gives a good insight into
the As-metabolizing potential of peat microorganisms,
open questions remain that should be addressed in future
research. Future approaches might include
(i) the isolation and characterization of As-metabolizing
microorganisms from peat soil, (ii) metagenomic analyses
to overcome the issue of primer bias encountered
in amplicon-based approaches, (iii) in situ detection
and quantification of thioarsenates in TPs, and
(iv) investigation of in situ binding mechanisms and As
speciation in TP peat.
Experimental procedures
Sampling site and peat sampling
Samples were taken from two peatlands treating mining-
affected waters near a gold mine in Finnish Lapland
(about 68
 northern latitude; Fig. S1). Treatment peatland
A (TP A) is used for purification of pretreated process
waters, while treatment peatland B (TP B) is used for the
purification of drainage water. Average inflow concentra-
tions of As were 1.3 and 0.4 μM to TP A and TP B
respectively and average removal efficiencies were 98%
and 57% in TP A and TP B respectively (average
2013–2017, obtained from monitoring data provided by
the mining company). The pH in surface water and
porewater of both TPs varied from 5.0 to 7.5 and the
redox potential varied from −150 to 0 mV in TP A and
−100 to 100 mV in TP B. In TP A, porewater sulphide
concentrations were 2.0 and 11 μM in 10 and 60 cm
depth respectively, while porewater Fe(II) concentrations
were 2.9 and 113 μM in 10 and 60 cm depth respectively.
In TP B, porewater sulphide concentrations were 0.2 and
1.0 μM in 10 and 60 cm depth respectively, while
porewater Fe(II) concentrations were 226 and 1190 μM in
10 and 60 cm depth respectively. A more detailed site
description is provided in Palmer and colleagues (2015).
Peat samples were taken on several occasions (MPN
counts and molecular work September 2015, microcosm
incubations March 2016) with a soil corer from 0 to
Fig. 7. Conceptual model of microbial As turnover
in TPs. Processes are indicated by arrows. Micro-
bial groups contributing to As turnover are repre-
sented as spheres. The relative abundance of an
Asmetabolizing group is indicated by the size of
the sphere, while the diversity of the group is indi-
cated by the number of pie sectors. The peat is
water-saturated and thus mainly anoxic. Arsenic
and sulphate pore water concentrations decrease
with increasing peat depth. Under anoxic condi-
tions, arsenate is reduced to arsenite. Repeated
As cycling, i.e. (re-)reduction and (re-)oxidation
might occur. Sulphate is reduced in anoxic peat
layers, leading to the production of reduced sulphur
species and the subsequent formation of
thioarsenates.
© 2020 The Authors. Environmental Microbiology published by Society for Applied Microbiology and John Wiley & Sons Ltd.,
Environmental Microbiology, 22, 1572–1587
1582 K. Kujala et al.
10 cm peat and 60 to 70 cm peat. Peat As concentrations
were 196 and 5.1 mg kg−1 in 0–10 and 60–70 cm peat
respectively, at sampling point TP A1, and 65.7 and
31.0 mg kg−1 in 0–10 and 60–70 cm peat respectively, at
point TP B2 (Table S2). Samples intended for DNA
extraction and subsequent analysis of the As metaboliz-
ing microbial community were flash-frozen on dry ice in
the field and stored at −20
C. Samples intended for
determination of cell numbers and for incubation experi-
ments were stored at 4
C in the dark until sample
processing. Incubation experiments were started within
2–3 weeks after sampling to prevent the impact of stor-
age on process potentials.
Determination of aqueous total As concentrations and
speciation in TPs
Surface water was sampled in summer 2017 at seven
sampling points along TP A and three sampling points
along TP B (Fig. S1). For total As determination, samples
were filtered through 0.2 μm filters (cellulose acetate, CA;
Macherey-Nagel), stabilized in 0.5% H2O2 and 0.8%
HNO3, and analysed by inductively coupled mass spec-
troscopy (ICP-MS). Surface water samples for As specia-
tion were filtered through 0.2 μm filters and acidified with
0.2% (v/v) HCl to avoid precipitation of Fe mineral phases
and As loss due to co-precipitation or sorption. All sam-
ples with total As concentrations >0.5 μg L−1 were
analysed for their As speciation using anion exchange
chromatography with a 20–100 mM gradient NaOH elu-
ent and suppressor coupled to ICP-MS (AEC-ICP-MS) as
described earlier (Planer-Friedrich et al., 2007). Addition-
ally, pore water samples were obtained at sampling
points TP A1 and TP A5 at the depths where samples
were collected for incubation experiments and microbial
community studies (see below). Since the potential
occurrence of thioarsenates was expected in these pore
water samples and acidification leads to their precipitation
as AsS mineral phases (Smieja and Wilkin, 2003), filtra-
tion and on-site flash-freezing on dry ice for species pres-
ervation was used instead of HCl acidification as
described earlier (Planer-Friedrich et al., 2007). Total As
for these samples was analysed as described above. All
samples with total As concentrations >0.1 μg L−1 were
analysed for their As speciation using AEC-ICP-MS as
well but with a 2.5–100 mM gradient NaOH eluent leaving
out the suppressor, to enable detection of methylated spe-
cies, as described earlier (Planer-Friedrich et al., 2007).
Incubation experiments
Soil slurry incubations were set up with field-fresh peat
soil from sampling point TP A5 (0–10 cm depth) and TP
A1 (60–70 cm depth) to test for the potential of peat
microorganisms to oxidize and reduce arsenite or arse-
nate respectively. 0–10 cm peat from TP A5 was chosen
to prevent masking of target processes by potential
leaching of the high initial As content of surface peat from
TP A1. One gram wet peat soil was diluted 1:60 with
deionized water in 125 mL incubation bottles. Incubations
were set up in triplicate. Oxic and anoxic incubations sup-
plemented with 50 μM arsenite and arsenate respec-
tively, were set up with and without inhibitor. Incubations
with inhibitor were supplemented with 0.75 mmol
molcarbon
−1 sodium azide (NaN3) to inhibit biological arse-
nite oxidation/arsenate reduction (controls). The concen-
tration of NaN3 was chosen based on previous studies
investigating As binding and transformation in organic-
rich environments (Buschmann et al., 2006; Hoffmann
et al., 2012; Besold et al., 2018). For oxic incubations,
slurries were prepared with ambient air in the headspace.
Bottles were closed with rubber stoppers, and stoppers
were removed regularly for aeration (1–2 times day−1) as
well as for sampling. For anoxic incubations, slurries
were prepared in a glovebag (Coy Laboratory Products),
which was operated with a gas mix of 95% N2 and 5%
H2. Bottles were closed with butyl-rubber stoppers and
crimp-sealed to preserve anoxic conditions. Anoxic incu-
bations were sampled inside the glovebag using a
syringe. Peat soil slurries were incubated at room tem-
perature on a shaker in the dark and sampled after 0, 1,
2, 5, 9, 12, 19 and 167 days. Concentrations of produced
sulphide were determined after 16 and 167 days using
the methylene blue method (Cline, 1969). Additional incu-
bations were set up with peat soil and mine process
water (sulphate = 2100 mg L−1) to assess the effect of
increased sulphate concentrations on thioarsenate forma-
tion. These incubations were set up with 0–10 cm peat
soil under anoxic conditions with and without NaN3 and
were supplemented with 50 μM arsenate. Samples were
taken at least six times from 2 to 433 days for determina-
tion of As speciation and sulphide concentration. Sam-
ples were filtered (0.2 μm, Chromafil CA; Macherey-
Nagel, Germany) and flash-frozen immediately to prevent
changes in As speciation. After thawing the flash-frozen
samples in a glovebag, aqueous As speciation was
analysed by AEC-ICP-MS as described in Planer-
Friedrich and colleagues (2007).
Enumeration of As-utilizing prokaryotes by MPN counts
MPN counts were set up targeting arsenite-oxidizers, aer-
obic As-tolerating microorganisms and arsenate
respirers. Incubations were set up with soil from TP A1
and TP B2 (0–10 and 60–70 cm depth). An artificial
porewater solution containing minerals, trace elements
and vitamins (modified from Balch et al., 1979;
Kuhner et al., 1996) was prepared with the following
© 2020 The Authors. Environmental Microbiology published by Society for Applied Microbiology and John Wiley & Sons Ltd.,
Environmental Microbiology, 22, 1572–1587
Arsenic-metabolizing microorganisms in peatlands 1583
concentrations (in mg L−1): (NH4)2 SO4, 12.6; Na2SO4,
13.5; CaCl2 × 2 H2O, 10.0; MgCl2 × 2 H2O, 10.0; FeCl2
× 4 H2O, 10.0; KH2PO4, 0.4; MnSO4 × 1 H2O, 5.0;
FeSO4 × 7 H2O, 1.0; CoCl2 × 6 H2O, 1.0; CaCl2 × 2
H2O, 1.0; ZnSO4 × 7 H2O, 1.0; CuSO4 × 5 H2O, 0.1;
AlK(SO4)2 × 12 H2O, 0.2; H3BO3, 0.1; Na2MoO4 × 2
H2O, 0.1; and nitrilotriacetic acid, 15; biotin, 0.004; folic
acid, 0.004; pyridoxine-HCl 0.02; thiamine-HCl, 0.01;
riboflavin, 0.01; niacin, 0.01; DL-Ca-pantothenic acid,
0.01; vitamin B12, 0.0002; p aminobenzoic acid, 0.01;
lipoic acid, 0.01. Growth medium was prepared using arti-
ficial porewater solution supplemented with 2 mM arse-
nite and 2 mM HCO3
− for arsenite-oxidizers, with 2 mM
arsenite, 2 mM arsenate and nutrient broth (NB, Sigma-
Aldrich; to a final concentration of 2.5 g L−1) or tryptic soil
broth (TSB, Sigma-Aldrich; to a final concentration of
3.0 g L−1) for aerobic As-tolerating microorganisms, with
2 mM arsenate, 2 mM lactate and 2 mM acetate for arse-
nate respirers, and with NB (at a final concentration of
2.5 g L−1) and TSB (at a final concentration of 3.0 g L−1)
for general aerobic heterotrophs. The pH of all growth
media was adjusted to 7.0. Incubations for arsenite-
oxidizers and As-tolerating microorganisms were con-
ducted in 96-well plates with eight replicates per dilution
step. Incubations for arsenate respirers were conducted
in triplicates in 50 ml serum bottles with sterile N2 in the
headspace. Plates and bottles were incubated at 20
C
for 3 months in the dark. Production of arsenate or arse-
nite was qualitatively determined in the arsenite oxidizer
and arsenate respirers MPN respectively, using a KMnO4
screening technique (Salmassi et al., 2002, 2006). Forty
microliters or 60 μl of 0.01 M KMnO4 was added to
300 or 500 μl of an arsenite oxidizer or arsenate respirer
incubation respectively. A purple colour indicated the
presence of arsenate, while an orange colour indicated
the presence of arsenite. Arsenite-oxidizer incubations
were scored positive, when the KMnO4 test indicated
mainly arsenate in the growth medium, arsenate respirer
incubations were scored positive, when the KMnO4 test
indicated mainly arsenite in the growth medium, and As-
tolerating and general aerobic heterotrophic incubations
were scored positive when growth was observed in the
wells by visual inspection.
DNA extraction and barcoded amplicon sequencing
DNA was extracted from four replicate samples per site
(TP A1 and TP B2) and depth (0–10 and 60–70 cm)
using the PowerLyzer PowerSoil DNA isolation kit
(MoBio Laboratories). Samples were freeze-dried,
homogenized, and rewetted (0.1 g of dried soil +150 μl
water) prior to extraction. In total, 17 previously published
primer sets for genes involved in microbial As metabolism
were tested, and functional genes were successfully
amplified and sequenced with two (aioA), two (arsC), and
three (arrA) primer sets (Table 1). Moreover, bacterial
16S rRNA genes were amplified from all samples as
described earlier (Kujala et al., 2018). PCRs were set up
in 25 μl reactions with the following composition: Maxima
SYBR Green/Fluorescein qPCR 2× Master Mix (Thermo
Scientific), 0.4 μM of each primer (Biomers), and 0.02%
Bovine Serum Albumin (Thermo Scientific), 1–5 ng tem-
plate DNA. Primers and PCR conditions are given in
Table 1. Additional primer sets were tested (Table S3),
but no PCR product was obtained with those despite
thorough testing, or no correct sequences were obtained
from the PCR products. Following the initial PCR,
barcodes and sequencing primers were added in a sec-
ond PCR (Table 1). PCR products from the second PCR
were purified and pooled in equimolar concentrations
prior to sequencing on the Ion Torrent PGM. Sequencing
templates were prepared using the Ion PGM Hi-Q OT2
Kit. For sequencing, the Ion PGM Hi-Q OT2 Kit and an
Ion 316 Chips v2 (Thermo Fisher) were used as
described earlier (Mäki et al., 2016; Kujala et al., 2018).
Sequence analysis
Sequence analysis was done in Qiime2 (Boylen et al.,
2019). After demultiplexing, during which sequences with
incorrect primer (>1 mismatch) or barcode (>1 mismatch)
were removed, sequences were quality-filtered using the
dada2 plugin for IonTorrent sequences (‘denoise-pyro’)
with the following modifications to the default parameters:
At the 50 end of the sequences, primers were removed
(‘-p-trim-left’; 41–44 bp, depending on analysed gene)
and sequences were trimmed at the 30 end to achieve
equal lengths for all sequences of a gene (‘-p-trun-len’;
261–314 bp depending on gene). The length for trimming
was selected to retain a reasonable number of
sequences with the fragments being as long as possible.
This resulted in final sequence lengths after using dada2
of 220, 220 and 270 bp for aioA, arrA and arsC respec-
tively. ASVs obtained after dada2 quality filtering were
used without further clustering unless indicated other-
wise. Feature classifiers were trained using aioA, arrA
and arsC sequences of pure cultures (114, 35 and
600 sequences respectively) with the Qiime2 plugin ‘fea-
ture-classifier’. For classifier training, only the part of the
sequence corresponding to the amplified genes was
used. Classifiers were used mainly to identify and
remove non-target sequences, which accounted for 50%,
7% and 3% of all aioA, arrA and arsC amplicons. While
trained classifiers allowed the identification of amplicon
sequences on the phylum level, they did not allow for
classification at lower taxonomic levels. Taxonomic affili-
ations of amplicon sequences on lower taxonomic levels
were obtained by BLAST search of sequences and by
© 2020 The Authors. Environmental Microbiology published by Society for Applied Microbiology and John Wiley & Sons Ltd.,
Environmental Microbiology, 22, 1572–1587
1584 K. Kujala et al.
the construction of phylogenetic trees. Closely related ref-
erence sequences to ASV representative sequences
were identified by BLAST (Altschul et al., 1990;
Table S4). For the construction of phylogenetic trees, the
same collection of pure culture sequences was used as
for the classifier training, albeit with full-length
sequences. Alignment of in silico translated reference
and own sequences, as well as the construction of phylo-
genetic trees, was done in ARB (Ludwig et al., 2004).
ARB allows for the construction of trees based on full-
length reference sequences, thus creating more robust
phylogenetic trees. Frequency-based position filters were
applied for the construction of reference phylogenies,
i.e. only alignment positions in which the majority of the
sequences had an amino acid were considered. This
resulted in the use of 390, 410 and 115 alignment posi-
tions for aioA, arrA and arsC respectively. Individual
shorter sequences (i.e. own sequences from the present
study and related environmental sequences) were added
to the existing tree using ARB parsimony using a
frequency-based position filter for those shorter
sequences (resulting in the use of 73, 72 and 86 align-
ment positions for aioA, arrA and arsC respectively). The
addition of shorter sequences does not affect the overall
tree topology. This approach of adding shorter sequenc-
ing to a preexisting tree has been frequently used in stud-
ies of ribosomal RNA as well as functional genes (see
e.g. Glöckner and Meyerdierks, 2006; Pester et al., 2012;
Gutierrez et al., 2013; Pjevac et al., 2017). Own
sequences were grouped based on their positioning in
the phylogenetic trees. A heatmap showing the occur-
rence of the aforementioned clusters of aioA, arrA and
arsC as well as the major phyla (>1% relative abun-
dance) based on 16S rRNA gene sequencing were con-
structed in R using ‘annHeatmap2’ of the Heatplus
package (Ploner, 2015).
ASV tables were rarefied, i.e. subsampled at a depth
of 600 sequences for all genes to allow for comparison of
diversity in the two TPs and depths and between the
three genes. Alpha diversity measures (number of
observed ASVs, Faith’s PD, Shannon diversity index H0,
Pielou’s Evenness) were calculated based on these
rarified ASV tables. Library coverage and richness esti-
mators were not calculated since the dada2 algorithm
removes singletons during its chimera detection step.
The non-rarefied libraries were tested for community dif-
ferences between peatlands, depths and the two primer
sets per gene using adonis PERMANOVA on weighted
unifrac distance matrices (Anderson, 2001; Oksanen
et al., 2018). ANCOM (Mandal et al., 2015) was used to
identify ASVs that differed in abundance between the
two TPs or depths. Sequences were deposited in the
NCBI sequence read archive under accession number
SRP158809.
Acknowledgements
Funding for this work was provided by the Academy of Fin-
land (Project 287397 ‘Microbial transformations of arsenic and
antimony in Northern natural peatlands treating mine waste
waters’). Additional support was provided by the European
Research Council (ERC grant awarded to MT, Grant Agree-
ment No. 615146, FP/2007-2013), the Bavarian Funding Pro-
gram for the Initiation of International Projects and the
German Research Foundation (grants awarded to BPF,
BayIntAn_UBT_2017_23 and DFG PL 302/20-1). Further-
more, the authors would like to thank Anne Eberle for provid-
ing some aqueous As data from her master thesis.
References
Abin, C.A., and Hollibaugh, J.T. (2017) Desulfuribacillus
stibiiarsenatis sp. nov., an obligately anaerobic, dissimila-
tory antimonate- and arsenate-reducing bacterium isolated
from anoxic sediments, and emended description of the
genus Desulfuribacillus. Int J Syst Evol Microbiol 67:
1011–1017.
Altschul, S., Gish, W., Miller, W., Myers, E.W., and
Lipman, D.J. (1990) Basic local alignment search tool.
J Mol Biol 215: 403–410.
Anderson, M.J. (2001) A new method for non-parametric
multivariate analysis of variance. Austral Ecol 26: 32–46.
Balch, W.E., Fox, G.E., Magrum, L.J., Woese, C.R., and
Wolfe, R.S. (1979) Methanogens: reevaluation of a unique
biological group. Microbiol Rev 43: 260–296.
Battaglia-Brunet, F., Dictor, M.C., Garrido, F., Crouzet, C.,
Morin, D., Dekeyser, K., et al. (2002) An arsenic(III)-
oxidizing bacterial population: selection, characterization,
and performance in reactors. J Appl Microbiol 93:
656–667.
Bauer, M., Fulda, B., and Blodau, C. (2008) Groundwater
derived arsenic in high carbonate wetland soils: sources,
sinks, and mobility. Sci Tot Environ 401: 109–120.
Besold, J., Biswas, A., Suess, E., Scheinost, A.C.,
Rossberg, A., Mikutta, C., et al. (2018) Monothioarsenate
transformation kinetics determines arsenic sequestration
by sulfhydryl groups of peat. Environ Sci Technol 52:
7317–7326.
Bhattacharyya, P., Tripathy, S., Kim, K., and Kim, S.H.
(2008) Arsenic fractions and enzyme activities in arsenic-
contaminated soils by groundwater irrigation in West Ben-
gal. Ecotoxicol Environ Saf 71: 149–156.
Bissen, M., and Frimmel, F.H. (2003) Arsenic – a review.
Part I: occurrence, toxicity, speciation, mobility. Acta
Hydrochim Hydrobiol 31: 9–18.
Boylen, E., Rideout, J.R., Dillon, M.R., Bokulich, N.A.,
Abnet, C.C., Al-Ghalith, G.A., et al. (2019) Reproducible,
interactive, scalable and extensive micobiome data sci-
ence using QIIME 2. Nat Biotechnol 37: 852–857.
Buschmann, J., Kappeler, A., Lindauer, U., Kistler, D.,
Berg, M., and Sigg, L. (2006) Arsenite and arsenate bind-
ing to dissolved humic acids: influence of pH, type of
humic acid, and aluminum. Environ Sci Technol 40:
6015–6020.
Cabrol, L., Quéméneur, M., and Misson, B. (2017) Inhibitory
effects of sodium azide on microbial growth in
© 2020 The Authors. Environmental Microbiology published by Society for Applied Microbiology and John Wiley & Sons Ltd.,
Environmental Microbiology, 22, 1572–1587
Arsenic-metabolizing microorganisms in peatlands 1585
experimental resuspension of marine sediment.
J Microbiol Methods 133: 62–65.
Cline, J.D. (1969) Spectrophotometric determination of
hydrogen sulfide in natural waters. Limnol Oceanogr 14:
454–458.
Costa, P.S., Scholte, L.L.S., Reis, M.P., Chaves, A.V.,
Oliveira, P.L., Itabayana, L.B., et al. (2014) Bacteria and
genes involved in arsenic speciation in sediment impacted
by long-term gold mining. PLoS One 9: e95655.
Dowdle, P.R., Laverman, A.M., and Oremland, R.S. (1996)
Bacterial dissimilatory reduction of arsenic(V) to
arsenic(III) in anoxic sediments. Appl Environ Microbiol
62: 1664–1669.
Escudero, L.V., Casamayor, E.O., Chong, G., Pedros-
Alio, C., and Demergasso, C. (2013) Distribution of micro-
bial arsenic reduction, oxidation and extrusion genes
along a wide range of environmental arsenic concentra-
tions. PLoS One 8: e78890.
Fulladosa, E., Murrat, J.C., Martínez, M., and Villaescusa, I.
(2005) Patterns of metals and arsenic poisoning in Vibrio
fischeri bacteria. Chemosphere 60: 43–48.
Garcia-Dominguez, E., Mumford, A., Rhine, E.D.,
Paschal, A., and Young, L.Y. (2008) Novel autotrophic
arsenite-oxidizing bacteria isolated from soil and sedi-
ments. FEMS Microbiol Ecol 66: 401–410.
Ghosh, A.K., Bhattacharyya, P., and Pal, R. (2004) Effect of
arsenic contamination on microbial biomass and its activi-
ties in arsenic contaminated soils of Gangetic West Ben-
gal, India. Environ Int 30: 491–499.
Glöckner, F.O., and Meyerdierks, A. (2006) Metagenome
analyses. In Molecular Identification, Systematics and
Population Structure of Prokaryotes, Stackebrandt, E.
(ed). Heidelberg: Springer, pp. 261–281.
González, Z.I., Krachler, M., Cheburkin, A.K., and
Shotyk, W. (2006) Spatial distribution of natural enrich-
ments of arsenic, selenium, and uranium in a min-
erotrophic peatland, Gola di Lago, Canton Ticino,
Switzerland. Environ Sci Technol 40: 6568–6574.
Gutierrez, T., Berry, D., Yang, T., Mishamandani, S.,
McKay, L., Teske, A., and Aitken, M.D. (2013) Role of
bacterial exopolysaccharides (EPS) in the fate of the oil
released during the Deepwater horizon oil spill. PLos One
8: e67717.
Hamamura, N., Fukushima, K., and Itai, T. (2013) Identifica-
tion of antimony- and arsenic-oxidizing bacteria associated
with antimony mine tailing.Microbes Environ 28: 257–263.
Hery, M., Gault, A.G., Rowland, H.A.L., Lear, G., Polya, D.
A., and Lloyd, J.R. (2008) Molecular and cultivation-
dependent analysis of metal-reducing bacteria implicated
in arsenic mobilization in south-east Asian aquifers. Appl
Geochem 23: 3215–3223.
Hoffmann, M., Mikutta, C., and Kretzschmar, R. (2012) Bisul-
fide reaction with natural organic matter enhances arse-
nite sorption: insights from X-ray adsorption spectroscopy.
Environ Sci Technol 46: 11788–11797.
Inskeep, W.P., Macur, R.E., Hamamura, N., Warelow, T.P.,
Ward, S.A., and Santini, J.M. (2007) Detection, diversity
and expression of aerobic bacterial arsenite oxidase
genes. Environ Microbiol 9: 934–943.
Kudo, K., Yamaguchi, N., Makino, T., Ohtsuka, T.,
Kimura, K., Dong, D.T., and Amachi, S. (2013) Release of
arsenic from soil by a novel dissimilatory arsenate-
reducing bacterium, Anaeromyxobacter sp. strain PSR-1.
Appl Environ Microbiol 79: 4635–4642.
Kuhner, C.H., Drake, H.L., Alm, E., and Raskin, L. (1996)
Methane production and oxidation by soils from acidic for-
est wetlands of east-central Germany. 96th General Meet-
ing of the American Society for Microbiology, p. 304.
Kujala, K., Mikkonen, A., Saravesi, K., Ronkanen, A.K., and
Tiirola, M. (2018) Microbial diversity along a gradient in
peatlands treating mining-affected waters. FEMS
Microbiol Ecol 94:fiy145.
Kulp, T.R., Hoeft, S.E., Miller, L.G., Saltikov, C., Murphy, J.
N., Han, S., et al. (2006) Dissimilatory arsenate and sul-
fate reduction in sediments of two hypersaline, arsenic-
rich soda lakes: mono and Searles lakes, California. Appl
Environ Microbiol 72: 6514–6526.
Langner, P., Mikutta, C., and Kretzschmar, R. (2012) Arsenic
sequestration by organic sulphur in peat. Nat Geosci 5:
66–73.
Langner, P., Mikutta, C., and Kretzschmar, R. (2014) Oxida-
tion of organosulfur-coordinated arsenic and realgar in
peat: implications for the fate of arsenic. Environ Sci
Technol 48: 2281–2289.
Lear, G., Song, B., Gault, A.G., Polya, D.A., and Lloyd, J.R.
(2007) Molecular analysis of arsenate-reducing bacteria
within Cambodian sediments following amendments with
acetate. Appl Environ Microbiol 73: 1041–1048.
Ledin, M., and Pedersen, K. (1996) The environmental impact of
mine wastes – roles of microorganisms and their significance
in treatment of mine wastes. Earth Sci Rev 41: 67–108.
Liu, C., Tian, H., Li, H., Xie, W., Wang, Z., Megharaj, M., and
He, W. (2019) The accuracy in the assessment of arsenic
toxicity using soil alkaline phosphatase depends on soil
water contents. Ecol Indic 102: 457–465.
Ludwig, W., Strunk, O., Westram, R., Richter, L., Meier, H.,
Yadhukumar, et al. (2004) ARB: a software environment
for sequence data. Nucleic Acids Res 32: 1363–1371.
Mäki, A., Rissanen, A.J., and Tiirola, M. (2016) A practical
method for barcoding and size-trimming PCR templates
for amplicon sequencing. Biotechniques 60: 88–90.
Malasarn, D., Saltikov, W., Campbell, K.M., Santini, J.M.,
Hering, J.G., and Newman, D.K. (2004) arrA is a reliable
marker for As(V) respiration. Science 306: 455–465.
Mandal, S., Van Treuren, W., White, R.A., Eggesbø, M.,
Knight, R., and Peddada, S.D. (2015) Analysis of compo-
sition of microbiomes: a novel method for studying micro-
bial composition. Microb Ecol Health Dis 26: 27663.
Matschullat, J. (2000) Arsenic in the geosphere – a review.
Sci Tot Environ 249: 297–312.
Nordstrom, D.K. (2011) Hydrogeochemical processes
governing the origin, transport and fate of major and trace
elements from mine wastes and mineralized rock to sur-
face waters. Appl Geochem 26: 1777–1791.
Ohtsuka, T., Yamaguchi, N., Makino, T., Sakurai, K.,
Kimura, K., Kudo, K., et al. (2013) Arsenic dissolution from
Japanese paddy soil by a dissimilatory arsenate-reducing
bacterium Geobacter sp. OR-1. Environ Sci Technol 47:
6263–6271.
Oksanen, J., Blanchet, F.G., Kindt, R., Legendre, P.,
Minchin, P.R., and O’Hara, R.B. (2018) vegan: community
ecology package. R package version 2.3-5, 2016.
© 2020 The Authors. Environmental Microbiology published by Society for Applied Microbiology and John Wiley & Sons Ltd.,
Environmental Microbiology, 22, 1572–1587
1586 K. Kujala et al.
Oremland, R.S., and Stolz, J.F. (2003) The ecology of arse-
nic. Science 300: 939–944.
Osborne, T.H., Jamieson, H.E., Hudson-Edwards, K.A.,
Nordstrom, D.K., Walker, R.S., Ward, S.A., and Santini, J.
M. (2010) Microbial oxidation of arsenite in a subarctic
environment: diversity of arsenite oxidase genes and iden-
tification of a psychrotolerant arsenite oxidizer. BMC
Microbiol 10: 205.
Páez-Espino, D., Tamames, J., de Lorenzo, V., &
Cánovas, D. (2009) Microbial responses to environmental
arsenic. BioMetals 22:117–130.
Palmer, K., Ronkanen, A.K., and Kløve, B. (2015) Efficient
removal of arsenic, antimony and nickel from mine waste-
waters in Northern treatment peatlands and potential risks
in their long-term use. Ecol Eng 75: 350–364.
Pester, M., Knorr, K.-H., Friedrich, M.W., Wagner, M., and
Loy, A. (2012) Sulfate-reducing microorganisms in wet-
lands – fameless actors in carbon cycling and climate
change. Front Microbiol 3: 72.
Pjevac, P., Schauberger, C., Poghosyan, L., Herbold, C.W.,
van Kessel, M.A.H.J., Daebeler, A., et al. (2017) AmoA-
targeted polymerase chain reaction primers for the spe-
cific detection and quantification of comammox Nitrospira
in the environment. Front Microbiol 8: 1508.
Planer-Friedrich, B., Härtig, C., Lohmayer, R., Suess, E.,
McCann, S.H., and Oremland, R. (2015) Anaerobic
chemolithotrophic growth of the haloalkaliphilic bacterium
strain MLMS-1 by disproportionation of monothioarsenate.
Environ Sci Technol 49: 6554–6563.
Planer-Friedrich, B., London, J., McCleskey, R.B.,
Nordstrom, D.K., and Wallschläger, D. (2007)
Thioarsenates in geothermal waters of Yellowstone
National Park: determination, preservation, and geochemi-
cal importance. Environ Sci Technol 41: 5245–5251.
Planer-Friedrich, B., Schaller, J., Wismeth, F., Mehlhorn, J.,
and Hug, S. (2018) Monothioarsenate occurrence in
Bangladesh groundwater and its removal by ferrous and
zero-valent iron technologies. Environ Sci Technol 52:
5931–5939.
Planer-Friedrich, B., Suess, E., Scheinost, A.C., and
Wallschläger, D. (2010) Arsenic speciation in sulfidic
waters: reconciling contradictory spectroscopic and chro-
matographic evidence. Anal Chem 82: 10228–10235.
Ploner, A (2015) Heatplus: Heatmaps with row and/or col-
umn covariates and colored clusters. R package version
2.26.0.
Rochette, E.A., Bostick, B.C., Li, G., and Fendorf, S. (2000)
Kinetics of arsenate reduction by dissolved sulfide. Envi-
ron Sci Technol 34: 4714–4720.
Salmassi, T.M., Venkateswaren, K., Satomi, M.,
Newman, D.K., and Hering, J.G. (2002) Oxidation of arse-
nite by Agrobacterium albertimagni, AOL15, sp. nov., iso-
lated from Hot Creek, California. Geomicrobiol J 19:
53–66.
Salmassi, T.M., Walker, J.J., Newman, D.K., Leadbetter, J.
R., Pace, N.R., and Hering, J.G. (2006) Community and
cultivation analysis of arsenite oxidizing biofilms at Hot
Creek. Environ Microbiol 8: 50–59.
Sheoran, A.S., and Sheoran, V. (2006) Heavy metal removal
mechanism of acid mine drainage in wetlands: a critical
review. Miner Eng 19: 105–116.
Smieja, J.A., and Wilkin, R.T. (2003) Preservation of sulfidic
waters containing dissolved As(III). J Environ Monitor 5:
913–916.
Song, B., Chyun, E., Jaffe, P.R., and Ward, B.B. (2009)
Molecular methods to detect and monitor dissimilatory
arsenate-respiring bacteria (DARB) in sediments. FEMS
Microbiol Ecol 68: 108–117.
Stolz, J.E., Basu, P., Santini, J.M., and Oremland, R.S.
(2006) Arsenic and selenium in microbial metabolism.
Annu Rev Microbiol 60: 107–130.
Sun, J., Quicksall, A.N., Chillrud, S.N., Mailloux, B.J., and
Bostick, B.C. (2016) Arsenic mobilization from sediments
in microcosms under sulfate reduction. Chemosphere
153: 254–261.
ThomasArrigo, L.K., Mikutta, C., Lohmayer, R., Planer-
Friedrich, B., and Kretzschmar, R. (2016) Sulfidization of
organic freshwater flocs from a minerotrophic peatland:
speciation changes of iron, sulfur, and arsenic. Environ
Sci Technol 50: 3607–3616.
Ullrich, M., Pope, J., Seward, T., Wilson, N., and Planer-
Friedrich, B. (2013) Sulfur redox chemistry governs diurnal
antimony and arsenic cycles at champagne Pool, Waiotapu,
New Zealand. J Volcanol Geoth Res 262: 164–177.
Villegas-Torres, M.F., Bedoya-Reina, O.C., Salazar, C.,
Vives-Florez, M.J., and Dussan, J. (2011) Horizontal arsC
gene transfer among microorganisms isolated from arse-
nic polluted soil. Int Biodeterior Biodegrad 65: 147–152.
Vymazal, J. (2011) Constructed wetlands for wastewater
treatment: five decades of experience. Environ Sci
Technol 45: 61–69.
Wallschläger, D., and Stadey, C.J. (2007) Determination of (oxy)
thioarsenates in sulfidic waters. Anal Chem 79: 3873–3880.
Watanabe, T., Miura, A., Iwata, T., Kojima, H., and Fukui, M.
(2017) Dominance of Sulfuritalea species in nitrate-depleted
water of a stratified freshwater lake and arsenate respiration
ability within the genus. Env Microbiol Rep 9: 522–527.
Xiao, E.Z., Krumins, V., Xiao, T.F., Dong, Y.R., Tang, S.,
Ning, Z.P., et al. (2017) Depth-resolved microbial commu-
nity analyses in two contrasting soil cores contaminated
with antimony and arsenic. Environ Pollut 221: 244–255.
Zhang, S.Y., Zhao, F.J., Sun, G.X., Su, J.Q., Yang, X.R.,
Li, H., and Zhu, Y.G. (2015) Diversity and abundance of
arsenic biotransformation genes in paddy soils from south-
ern China. Environ Sci Technol 49: 4138–4146.
Supporting Information
Additional Supporting Information may be found in the online
version of this article at the publisher’s web-site:
Appendix S1: Supporting Information
© 2020 The Authors. Environmental Microbiology published by Society for Applied Microbiology and John Wiley & Sons Ltd.,
Environmental Microbiology, 22, 1572–1587
Arsenic-metabolizing microorganisms in peatlands 1587