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Rinnakkaistallenteet Luonnontieteiden ja metsätieteiden tiedekunta

2019

Archaeal nitrification is a key driver of high nitrous oxide emissions from

arctic peatlands

Siljanen, Henri M P

Elsevier BV

Tieteelliset aikakauslehtiartikkelit

© Elsevier Ltd.

CC BY-NC-ND https://creativecommons.org/licenses/by-nc-nd/4.0/

http://dx.doi.org/10.1016/j.soilbio.2019.107539

https://erepo.uef.fi/handle/123456789/7730

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Accepted Manuscript

Archaeal nitrification is a key driver of high nitrous oxide emissions from arctic peatlands

Henri M.P. Siljanen, Ricardo J.E. Alves, G. Ronkainen Jussi, Richard E. Lamprecht, Hem R. Bhattarai, Alexandre Bagnoud, Maija E. Marushchak, Pertti J. Martikainen, Christa Schleper, Christina Biasi

PII: S0038-0717(19)30203-2

DOI: https://doi.org/10.1016/j.soilbio.2019.107539 Article Number: 107539

Reference: SBB 107539

To appear in: Soil Biology and Biochemistry Received Date: 14 March 2019

Revised Date: 1 July 2019 Accepted Date: 10 July 2019

Please cite this article as: Siljanen, H.M.P., Alves, R.J.E., Ronkainen Jussi, G., Lamprecht, R.E., Bhattarai, H.R., Bagnoud, A., Marushchak, M.E., Martikainen, P.J., Schleper, C., Biasi, C., Archaeal nitrification is a key driver of high nitrous oxide emissions from arctic peatlands, Soil Biology and Biochemistry (2019), doi: https://doi.org/10.1016/j.soilbio.2019.107539.

This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

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Archaeal nitrification is a key driver of high nitrous oxide emissions from arctic peatlands 1

2 3

Siljanen Henri M. P.1,2*, Alves Ricardo J. E.2,&, Ronkainen Jussi G.1, Lamprecht Richard E.1, 4

Bhattarai Hem R1, Bagnoud Alexandre2, Marushchak Maija E.1, Martikainen Pertti J.1, Schleper 5

Christa2*, Biasi Christina1 6

7

1University of Eastern Finland, Department of Environmental and Biological Sciences, P.O. Box 8

1627, 70211 Kuopio, Finland 9

2University of Vienna, Department of Ecogenomics and Systems Biology, Archaea Biology and 10

Ecogenomics Division, Althanstrasse 14, A-1090 Vienna, Austria 11

12

&

Present address: Lawrence Berkeley National Laboratory, Climate and Ecosystem Sciences 13

Division, Earth and Environmental Sciences Area, 1 Cyclotron Road, Berkeley, CA 94720, USA 14

15

Keywords: ammonia oxidation; AOA; permafrost; climate change 16

17

* Correspondence to: henri.siljanen@uef.fi, christa.schleper@univie.ac.at 18

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Abstract 23

Bare peat surfaces created by frost action and wind erosion in permafrost peatlands show high 24

nitrous oxide (N2O) emissions. With global warming, emissions of this highly potent greenhouse 25

gas are expected to increase in Arctic permafrost peatlands. In natural unmanaged soils with low 26

nitrogen deposition, such as Arctic soils, nitrification is the main source of nitrite and nitrate, thus a 27

key driver of N2O emissions. Here, we investigated nitrification, ammonia oxidizer populations and 28

N2O production in vegetated and bare peat soils from four distant Arctic locations. Through a 29

combination of molecular analyses and group-specific inhibitor assays, we show that ammonia 30

oxidation, the first step in nitrification, is mainly performed by ammonia-oxidizing archaea (AOA).

31

All soils from different geographical locations, including bare peat soils with high N2O emissions, 32

harbored only two AOA phylotypes, including an organism closely related to Ca. Nitrosocosmicus 33

spp.. This indicates that high N2O emissions from these ecosystems are primarily fueled by 34

nitrification mediated by very few archaeal species. To our knowledge, Arctic peat soils in this 35

study are the first natural environments where high N2O emissions have been linked to AOA. Any 36

changes in archaeal nitrification induced by global warming will therefore impact on N2O emissions 37

from the permafrost peatlands.

38 39 40 41

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Introduction 42

Nitrous oxide (N2O) is the major ozone-depleting compound (Ravishankara et al., 2009) and a 43

greenhouse gas with a global warming potential 298 times that of carbon dioxide (CO2) over a 44

period of 100 years (Myhre et al., 2013). Tropical soils and oceans have long been known to be the 45

major natural sources of N2O (Myhre et al., 2013; van Lent et al., 2015). The role of Arctic 46

ecosystems in the global N2O budget has been largely overlooked, as they are generally N-limited 47

(Christensen et al., 1999; Ludwig et al., 2006; Rodionow et al., 2006; Ma et al., 2007; Takakai et 48

al., 2008) and microbial processes such as nitrification and denitrification are generally assumed to 49

be constrained by low temperatures. However, this view has been challenged by growing evidence 50

that gross nitrification rates in at least some soils are within the same range as those in temperate 51

environments (Booth et al., 2005; Alves et al., 2013), and that some Arctic terrestrial ecosystems 52

may be globally significant sources of N2O – for instance, high N2O emissions have been measured 53

from areas of bare peat on peat plateaus (Repo et al., 2009) and palsa mires (peatlands raised by 54

permafrost) (Marushchak et al., 2011). High N2O emissions from these surfaces are sustained by 55

low carbon (C) to nitrogen (N) ratios (C/N), or high mineral nitrogen availability, the absence of 56

vegetation, and intermediate soil moisture, which allows oxic and anoxic microbial processes to 57

take place simultaneously (Marushchak et al., 2011). Moreover, N2O emissions from both bare and 58

vegetated permafrost peatlands can rise substantially with warming (Voigt et al., 2017a) and 59

permafrost thawing (Voigt et al., 2017b). Together, these observations puts N2O high on the agenda 60

of Arctic research and shows that not only C but also N, should be considered when evaluating 61

climate feedbacks from high-latitude soils.

62 63

Under oxic conditions, N2O is mainly produced in the soil through the ammonia oxidation step of 64

nitrification, whereas under anaerobic conditions, denitrification by heterotrophic microbes is the 65

main source of N2O. Additionally, ammonia oxidizers can also contribute to N2O production via 66

nitrifier-denitrification under low oxygen conditions (Jia and Conrad, 2009; Butterbach-Bahl et al., 67

2013; Zhu et al., 2013; Hu et al., 2015). Laboratory experiments have shown that subarctic bare 68

sub—Arctic peat soils have a high potential for denitrification under anoxic conditions (Palmer et 69

al., 2012), and 15N-site preference values of N2O in these soils have indicated that denitrification is 70

involved in N2O production especially in deeper peat layers (Gil et al., 2017). Consistent with this, 71

denitrifiers were found to be highly abundant in bare peat soils with their community composition 72

being distinct from adjacent vegetated peat surfaces, mainly reflecting the predominance of few 73

specific phylotypes in the former (Palmer et al., 2012). However, denitrification is largely 74

dependent on nitrite (NO2-

) and nitrate (NO3-

) supplied by nitrification, especially in natural 75

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unfertilized ecosystems, such as Arctic soils, where N deposition is low and mineralization of 76

organic matter to ammonium (NH4+) is the main source of inorganic N (Reay et al., 2008;

77

Kanakidou et al., 2016). Consequently, nitrification can be considered a key limiting step in N2O 78

emissions from Arctic peatlands, as it regulates the supply of NO2-

and NO3-

for N2O production 79

through denitrification. Moreover, 15N-site preference values of N2O have also identified 80

nitrification as a N2O source, particularly in bare peat during dry years with low surface emissions 81

(Gil et al., 2017). Thus, nitrification has an important dual role in N2O production in bare peat, both 82

indirectly by fueling denitrification and by directly producing N2O (Hu et al., 2015; Kozlowski et 83

al., 2016). Nevertheless, nothing is known about the nitrifying communities and their activity in 84

bare peat soils releasing high amounts of N2O in arctic permafrost ecosystems. Therefore, 85

identification of nitrifier populations and a better knowledge of the factors regulating their activity 86

are paramount to understanding and predicting N2O emissions from these vulnerable ecosystems 87

under current climate change.

88 89

Here, we investigated ammonia oxidizer populations, which catalyze the first and rate-limiting step 90

in nitrification, in permafrost peat soils from four distant Arctic locations spanning Northern 91

Finland, Northwestern Russia, and Northern Central Russia. All bare peat soils at these sites emitted 92

N2O at high net rates, contrary to the adjacent vegetated peat surfaces, which showed very low to 93

negative net N2O emissions (i.e., N2O uptake). Diversity and abundance of ammonia oxidizers were 94

studied based on amoA genes (encoding ammonia monooxygenase subunit A), and the relative 95

contributions of ammonia-oxidizing bacteria (AOB) and ammonia-oxidizing archaea (AOA) to 96

nitrification in a model arctic peatland site were determined using 15N pool dilution assays and 97

group-specific nitrification inhibitors.

98 99

Materials and Methods:

100 101

Study sites and sample collection 102

Soil samples were collected from four Arctic or sub-Arctic peatlands located in northern Russia 103

(Seida, Taymyr and Tazovsky) and northern Finland (Kevo). Bare peat surfaces with high N2O 104

emissions in Seida and Kevo were first identified and characterized by Repo et al. (2009) and 105

Marushchak et al. (2011) (Fig. S1), respectively, whereas the sites in Taymyr and Tazovsky 106

represent previously uncharacterized peatlands. Briefly, bare peat surfaces on permafrost peat 107

plateaus in Seida are approximately 10-500 m2 in area and comprise 3-5% of the total area in the 108

region, where the peat plateau constitutes about 20% of the local landscape (Repo et al., 2009; Biasi 109

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et al., 2014). Soil samples were collected during the season of high biological activity (June- 110

August) in 2011 (Seida), 2016 (Kevo), 2011 (Taymyr) and 2012 (Tazovsky) (Table S1.).

111 112

Sampling locations were characterized as bare surfaces and surrounding vegetated surfaces.

113

According to current understanding, bare peat surfaces are created created by wind erosion due to 114

higher elevation compared to surrounding surfaces, or near-surface frost action, or by both of these 115

factors concurrently (Seppälä et al., 2003; Kaverin et al., 2018). At each site, we collected 2-4 116

replicate samples of each surface type (10-30 m apart), and three technical replicates for each 117

(within 0.2-0.5 m distance). Sampling was performed either with a 8 cm x 8 cm box corer, or by 118

using a knife to cut out peat bricks with surface dimensions 15 cm by 15 cm. The top peat layers 119

varied between 5 to 10 cm depth, and were collected depending on peat degradation status. The 120

collected peat samples were stored in re-sealable plastic bags to prevent water loss and kept in 121

cooling boxes with ice bags during transport to the laboratory.

122 123

In the laboratory, soil samples were homogenized by breaking the peat structure by hand. Bags 124

were kept sealed during homogenization, and visible plant material (roots and leaves) and stones 125

were removed using sterilized tweezers. After homogenization, samples were collected in zip-lock 126

plastic bags for further chemical analyses (soil pH, NO3-, and NH4+ contents) using methods 127

previously described (Marushchak et al., 2011; Alves et al., 2013). Sub-samples for molecular 128

analyses were collected in 15 ml plastic tubes and immediately flash frozen with liquid nitrogen.

129

Samples collected at the Russian tundra sites were stored in RNAlater® (Thermo Fisher) during 130

transport to the laboratory. In the laboratory, RNAlater® was removed repeatedly washing soil 131

samples with phosphate-buffered saline buffer solution (1x PBS), using ultra-centrifugation, and 132

washed samples were stored at -80°C.

133

Frozen sub-samples for molecular analysis were ground to a very fine powder using a mortar and 134

pestle with liquid nitrogen. The equipment was sterilized by heating at +400°C for 4 h, or 135

autoclaving, and was also wiped with 70% ethanol. Samples were stored at -80°C until extraction.

136 137

Measurements of nitrous oxide fluxes 138

In situ gas flux measurements were performed using the static chamber method (Marushchak et al., 139

2011; Nykänen et al., 1995) on three different bare peat and adjacent vegetated surfaces within the 140

same peat plateau or palsa mire complex.

141 142

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In brief, for in situ gas flux measurements, aluminum collars (dimensions: 60 cm x 60 cm x 15 cm, 143

W x L x H) were installed permanently at the Seida sites in June 2009. Collars were installed on 144

three different bare peat and adjacent vegetated surfaces within the same peat plateau complex. The 145

collar was pressed into the peat down to 5-10 cm depth, and the upper part of the collar had a 146

groove filled with water to create an airtight seal between the chamber and the collar during gas 147

sampling. Each chamber had a circular vent tube to prevent the development of under pressure 148

during sampling (Nykänen et al., 1995). The chambers were equipped with a fan to ensure good 149

mixing of air inside the chamber. Gas samples were collected by closing the chamber (dimensions:

150

60cm x 60cm x 10cm; vol. 36 dm3) for a period of 40 min. At the Kevo and Taymyr study sites, 151

fluxes were measured with a cylindrical stainless-steel chamber (volume ~15 dm3). The open 152

bottom part of the chambers was pushed into the peat to a depth of 3-7 cm, and gas samples were 153

collected at intervals of 5, 10, 20 and 40 min with polypropylene syringes (Terumo®, equipped with 154

three-way stopcocks). Gas samples were transferred into pre-evacuated and N2-flushed glass vials 155

closed with rubber septa within 24 hours (Labco® Exetainer). Air and chamber temperature were 156

measured at the start and end of each measurement.

157

Gas samples were analyzed with an Agilent gas chromatograph (GC) equipped with a Hayesep Q 158

80/100 mesh column (length 1.8 m) and an electron capture detector (ECD) (Nykänen et al., 1995).

159

Flux rates were calculated from the increase in the N2O concentrations with sampling times using a 160

linear regression model. A correlation coefficient > 0.90 was used as quality criterion to accept the 161

flux values.

162 163 164

Soil incubations with the group-specific ammonia oxidation inhibitors.

165

Samples for the inhibitor experiment were collected in triplicate from soil profiles of bare peat in 166

Seida, NW-Russia in August 2014 at depth of 0-10 cm with a box corer. Peat was homogenized by 167

hand mixing, and visible roots and non-degraded plant material were removed. Three microcosms 168

of each replicate (nine in total) were prepared with 20 g of peat in 550 ml incubation bottles.

169

Nitrification in soil was inhibited with allylthiourea (ATU) and carboxy-PTIO (PTIO), which 170

selectively inhibit AOB or AOA, respectively (Shen et al., 2013) The experiment was conducted at 171

natural peat moisture, which was kept constant throughout the incubation period of 30 days. The 172

bottles were closed with rubber septa but the headspace was flushed twice a week with technical air 173

(AGA, Finland) to keep the headspace oxic. Evaporated water due to headspace flushing was 174

compensated. Inhibitor concentrations used in the experiments were selected based on the tests with 175

pure cultures of Nitrososphaera viennensis EN76 (AOA) and Nitrosospira multiformis (AOB) in a 176

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previous study (Shen et al. 2013) (note that the actual concentrations of the two specific inhibitors 177

(ATU and PTIO) were different based on the tests). Very high inhibitor concentrations were 178

avoided because at a high concentration these inhibitors lose their specificity against AOB (ATU) 179

and AOA (PTIO). The inhibitors were added twice a week. During the last two weeks of the 180

experiment, the final concentrations of ATU and PTIO were 12 µM and 95 µM, respectively.

181 182

Determination of gross nitrification rates 183

Gross nitrification rates were determined using the 15N pool dilution method (Inselsbacher et al., 184

2007) for each treatment at the end of the inhibitor experiments. Five hundred microliter of 10 at%

185

Na15NO3 (0.301 g l-1) were) was added to 2 g of peat soil in 50 ml flasks, and soils were extracted 186

with 25 ml 2 M potassium chloride (KCl) in duplicates after incubation for 4 h and 24 h (start and 187

end time-points, respectively). Extraction was performed by shaking the peat slurry at 175 rpm min- 188

1 for one hour in plastic 50 ml tubes and filtering the slurry through plastic funnels containing 185 189

mm diameter ashless Whatman® filter paper. Samples for EA-IRMS analysis were prepared with 10 190

ml of extracted sample solution by reducing NO3-

to NH4+

using Devarda´s alloy, after removing 191

ammonium present in the extracts with addition of MgO. This was done by shaking the extracts 192

with acid traps (~6 mm in diameter) at 135 rpm in 20 ml scintillation vials at 35°C for five days.

193

The acid traps were prepared by adding 7.5 µl of 2.5 M KHSO4 to filter paper discs, which were 194

placed and sealed in Teflon tape. After five days of incubation with MgO, the acid traps containing 195

the ammonium initially in the extract were replaced with new acid traps, followed by addition of 196

0.05 g Devarda´s alloy to convert nitrate to ammonium. Samples were shaken at the same speed, 197

temperature and time. Acid traps were gently washed with Milli-Q® H2O and kept in 2 ml 198

microsentrifuge vials with the cap open. The traps were dried for 24 h in a desiccator containing 199

sulphuric acid (≥ 97 %, Sigma-Aldrich). After 24 hours, the traps were opened carefully and folded 200

inside the tin cup for analyses using Isotopic Ratio Mass Spectrometer (Thermo Finnigan), as 201

described in Gil et al., (2017).

202 203

Nucleic acid extraction and purification 204

For DNA extraction, 1 ml (~0.1-0.2 g) homogenized peat soil was transferred into a pre-cooled 205

Lysing tube E (MP Biomedicals, USA) with a sterilized spoon. Lysing matrix tubes were placed in 206

water-ice-bath and 700 µl of preheated (65 °C) CTAB lysing buffer (6 % Cetyltrimethyl 207

Ammonium Bromide (Sigma Life Science, Germany), 1.5 M NaCl 5%, with buffer 250 mM 208

NaPO4, pH 8.0) was added. After addition of buffer-saturated phenol/chloroform/isoamylalcohol 209

(25:24:1; pH 7.5), cell lysis was performed by bead-beating using a FastPrep FP120 device 210

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(Thermo Savant, USA) for 30 s at speed 5.5 m s-1. The aqueous phase was extracted with 211

chloroform/isoamylalcohol (24:1) and DNA was precipitated with the 2x volume of 30% PEG6000 212

(Fluka Chemie, Germany) and 1.5 M NaCl solution on ice for 2 h. The tubes were then centrifuged 213

at 4°C for 20 min with 14000 g. The DNA pellet was washed with 1 ml 70% ethanol and then 214

dissolved in 50 µl DEPC-treated H2O (0.01% Diethyl pyrocarbonate, Sigma Life Science, 215

Switzerland). All centrifugation steps were done at 13,200 g for 10 min unless otherwise 216

mentioned. DNA extracts were stored at -80°C until analysis.

217

Extracted DNA was generally not amplifiable by PCR due to high concentrations of co-extracted 218

inhibitory compounds (extracts were visibly yellow to dark brown), such as humic and fulvic acids, 219

which are abundant in peat. Therefore, DNA extracts were column-purified using Sephadex G-50 + 220

15 % PVPP (Fluka/Sigma-Alrich, St Louis USA) and Q-Sepharose (Sigma-Alrich, GE Healthcare, 221

Sweden) (Mettel et al., 2010). Filter columns (0.45 µm pore diameter; GE Lifetechnologies, VWR 222

international) were each filled with 50 µl Sephadex G-50 + 15 % PVPP, followed by sterile DEPC- 223

water, and incubated at room temperature for 1 h. Columns were then centrifuged at 910 g for 5 224

min, washed with 150 µl DEPC H2O and centrifuged again at 910 g for 5 min. A volume of 600 µl 225

Q-Sepharose mixture was added on top of the wet Sephadex/PVPP mixture and columns were 226

centrifuged at 910 g for 5 min and washed twice with 300 µl 1.5 M NaCl.

227

DNA extracts were eluted through the filtration columns in 20 µl volumes with 80 µl 1.5 M NaCl as 228

eluent. Purified DNA was precipitated with 0.1 x volume of 3 M sodium-acetate (10 µl) and 2.5x 229

volume of ice-cold 100 % ethanol (250 µl) at room temperature for 1 h. DNA pellets were washed 230

with 1 ml of ice-cold 70 % ethanol and dried in a vacuum centrifuge at room temperature for 30 231

min. DNA pellets were dissolved in 20 µl DEPC-treated milliQ H2O and stored at -80 °C until 232

analysis. After purification, DNA extracts were clear, without visible dark coloration. DNA 233

concentrations were measured with Qubit® 1.0 Fluorometer (Invitrogen).

234

Samples from the inhibitor incubation for molecular analyses (0.1 g per sample) were collected at 235

the end of the experiment, immediately flash-frozen with liquid nitrogen, homogenized with a 236

mortar and then transferred into Lysing matrix E tubes (MP Biomedicals) tubes. Homogenized 237

samples were stored at -80 °C until nucleic acid extractions. Nucleic acids were extracted and 238

purified with the same protocols described above, but using instead acid phenol/chloroform/IAA 239

(25:24:1, pH 4.5, Ambion 9720) for extraction, and water containing RNase inhibitor (Thermo 240

Scientific RNaseOUT™ Recombinant Ribonuclease Inhibitor 1U µl-1) for preparation of 241

purification columns. Pellets were dried with a SpeedVac for 3 min at 30 °C and resuspended in 50 242

µ L DEPC-treated H2O. Subsamples of the nucleic acid extracts (remaining extracts were kept for 243

DNA-based analyses) were immediately treated with DNAse (1U/ µl, Promega) and incubated with 244

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RNase inhibitor (Thermo Scientific) in a heating block at 37 °C for 45 min. Reactions were 245

terminated by adding 1 µl DNAse stop solution and the samples were run for an additional 10 min 246

at 65 °C to stop the enzymatic reaction. Purified RNA extracts were stored at -80 °C until analysis.

247

DNA contamination was checked with archaeal amoA qPCR (see below), and RNA concentrations 248

were measured with the Qubit® RNA HS assay kit (Invitrogen). The yield of DNase-treated RNA 249

was 77 to 112 pg. Complementary (cDNA) was synthesized by incubating random hexamer primers 250

(Thermo Scientific), dNTP mixture and RNA at 65 °C for 5 min, followed by addition of 100 units 251

of RevertAid H Minus Reverse Transcriptase (Thermo Scientific) and 20 units of RNase inhibitor, 252

and incubation at 65°C for 2 h.

253 254

Quantification of amoA genes and transcripts 255

Quantitative PCR (qPCR) of archaeal and bacterial amoA genes was performed using the reaction 256

and cycling conditions indicated in Tables S8 and S9, respectively. All reactions were performed in 257

duplicates. Quantification of archaeal and bacterial amoA genes was based on 10-fold dilutions 258

(101-108) of amoA gene fragments from N. viennensis EN76 and N. multiformis, respectively, 259

amplified from cloned gene fragment with vector specific primers. For archaeal amoA genes, the 260

qPCR efficiency was 76 %, with a detection limit between 6.55x102 and 6.55x107 genes per 261

reaction. For bacterial amoA genes, the qPCR efficiency was 92 %, with a detection limit between 262

1.88x103 and 1.88x108 genes µl-1. The specificity of qPCR amplification products was verified by 263

melting-curve analysis and gel electrophoresis.

264 265

Sequencing and identification of amoA genes 266

Archaeal and bacterial amoA gene fragments of 632 bp and 491 bp, respectively, were amplified 267

with the group-specific primers shown in Table S8 and sequenced with Illumina MiSeq PE250 268

(LGC, Munich, Germany). Given the difficulty in amplifying amoA genes from several samples due 269

to inhibiting humic acids, we tested the PCR amplification efficiency of archaeal amoA genes from 270

each DNA sample using several different DNA polymerases: GoTaq (Promega), DreamTaq 271

(Thermo Fisher), Phusion (Thermo Fisher), Phire II HS (Thermo Fisher). The Phire II HS 272

polymerase, which contains a helping dsDNA-binding domain, yielded the highest amplification 273

efficiency and was thus used in all PCR assays for sequencing. We optimized the PCR conditions 274

for each primer pair by testing different annealing temperatures (56-64.3 °C), primer concentrations 275

(0.156-0.625 µM) and template DNA concentrations (depending on the amount of DNA extracted 276

and soil type). The sufficient amount of DNA template per PCR reaction was selected after testing 277

for potential inhibitory effects on the amplification of archaeal amoA genes. This was done over a 278

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dilution series of template DNA spiked and not spiked with a known amount of positive control 279

DNA from all samples to omit the possibility of inhibitory effects of humic acids. The PCR reaction 280

and cycling conditions selected are shown in Tables S9 and S10. Positively amplified (PCR product 281

visible in the agarose gel electrophoresis) of eightfold replicated PCR products were pooled per 282

sample and purified with a PCR product purification kit (Qiagen), according to the manufacturer’s 283

protocol, after verifying the specificity of all PCR products by gel electrophoresis.

284

To check specificity of PCR, unspecific (wrong size) bands were ligated (CloneJET PCR Cloning 285

KIT; Thermo Scientific), cloned into competent cells (One Shot TOP10 kit; Invitrogen) according 286

to manufacturer’s protocol. These clones were sequenced with end-termination chemistry 287

(Macrogen Inc., Netherlands). Obtained correct size AOB PCR products (positive result in 6 out of 288

28 analyzed samples) were sequenced similarly as AOA PCR products with MiSeq PE250, and 289

sequencing reads were quality filtered as described below. The resulted correct and incorrect size 290

bacterial amoA genes were analyzed with BLASTN, (Altschul et al., 1990) and it was shown that 12 291

% of these reads (in total about 140,000 reads were sequenced) were non-specific sequences other 292

than amoA and rest were contaminated with positive control of the laboratory (100 % identical to 293

the amoA gene of N. multiformis).

294 295

Archaeal amoA gene reads were analyzed using the DADA2 workflow (Callahan et al., 2016).

296

Reads were truncated to a length of 200 bp, and those with an expected error greater than 2 were 297

discarded. Given the general lower quality of the reverse reads, only forward reads were used. Non- 298

specific amplicons (i.e., not amoA genes) were identified and discarded by assigning the Amplicon 299

Sequence Variants (ASVs) inferred by DADA2 to the global amoA gene database by Alves et al., 300

(2018) using an identity cut-off lower than 55 % with USEARCH8, (Edgar, 2010) and further 301

inspection of abundant ASVs with BLASTN (Altschul et al., 1990) against the GenBank database.

302

In addition to the read quality and chimera filtering performed by DADA2, additional chimeras 303

were filtered out with UCHIME (Edgar et al., 2011) using the chimera-free reference database by 304

Alves et al. (2018). After quality filtering and chimera removal about 879,000 archaeal amoA gene 305

sequences were classified using the reference database and taxonomy by Alves et al. (2018) with 306

the UCLUST method implemented in QIIME (Caparaso et al., 2010). Data analysis and 307

representation were performed with R 3.4.4. (R Core Team, 2018) using packages Biostrings (Pagés 308

et al., 2017), vegan (Oksanen et al., 2018), string (Wickham, 2018), RColorBrewer (Neuwirth, 309

2014), reshape2 (Wickham, 2007) and ggplot2 (Wickham, 2009).

310 311

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We wrote a script that complies the amplicon analysis pipeline used, which can be found at this 312

Github repository: https://github.com/alex-bagnoud/arctic-nitrifiers. The raw primer-free 313

sequencing data were deposited to NCBI SRA under accession number PRJNA488558.

314 315

Statistical analyses 316

All statistical tests were made with R statistical program version 3.4.4 (R Core Team, 2018). Prior 317

to statistical analyses, data were tested for normal distribution using histograms as well as density 318

and qq-plots coupled with the Shapiro-Wilk normality test. To test for correlation between 319

environmental and microbial variables, and N2O fluxes, we applied the Two-Way ANOVA, linear 320

regression model and the non-parametric Spearman’s correlation test. The effect of peat surface 321

type was determined with the Student t-test and pairwise comparisons with Tukey HSD. The effect 322

of inhibitor treatment on gross-nitrification was studied with the linear mixed-effect model using 323

the R package nlme (Pinheiro et al., 2018). We applied non-metric dimensional scaling analysis 324

(NMDS) to reduce data dimensionality and to visualize the variance structure of the dataset, in 325

order to identify differences between sites and surface types in terms of soil archaeal amoA 326

diversity. The effect of sites and surface type on amoA diversity was tested with a PERMANOVA 327

test with adonis function using R package vegan (Oksanen et al., 2018).

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329 330

Results 331

Soil N2O fluxes 332

We measured N2O emission rates in three out of five Arctic permafrost peatlands located in Kevo 333

(Northern Finland), Seida (Komi Republic, NW-Russia) and Taymyr peninsula (central Siberia, 334

Russia) regions (Fig. 1A, Table S1, Fig. S1), all characterized by significant areas of bare peat 335

surfaces. The three bare peat locations showed high N2O emissions (average flux 28.4 µg N2O m-2 336

h-1, ranging from 5.9 to 42.2 µg N2O m-2 h-1), while emissions from vegetated surfaces were 337

generally low, and occasionally even negative, i.e., N2O uptake (average flux 3.0 µg N2O m-2 h-1, 338

ranging from -1.6 to 6.9 µg N2O m-2 h-1) (Fig. 1B). Nitrous oxide fluxes from bare peat surfaces 339

were lower than those reported earlier from the Seida and Kevo sites (from 2007 to 2013) 340

(Marushchak et al., 2011; Voigt et al., 2017a) (Table 1). However, the fluxes were still high 341

compared with those reported for natural northern soils, and were in the same range as those from 342

tropical and agricultural soils (Martikainen et al., 1993; Christensen et al., 1999; Maljanen et al., 343

2010; van Lent et al., 2015).

344

Soil nitrate content indicated that net nitrification activity (i.e., nitrate accumulation) was higher in 345

the bare peat surfaces (6.64-53.18 µg NO3- g-1 dry soil) than in the vegetated peat surfaces (0.023- 346

0.59 µg NO3- g-1 dry soil) (Fig. 1C), consistent with the gross nitrification rates measured earlier in 347

bare peat soil (Gil, 2017). Soil nitrate content was correlated with the N2O fluxes based on a linear 348

model (F N2O flux vs. NO3- conc.

= 10.91, d.f.1=1, d.f.2=14, P < 0.01, R2 = 0.44).

349 350

Quantification of amoA genes 351

Surprisingly, ammonia-oxidizing archaea (AOA) were the only autotrophic ammonia oxidizers 352

detected across all peat soils from Kevo, Seida, and Taymyr, and two additional sites from 353

Tazovsky (a peat plateau and a peat bog, Western Siberia, Russia). Neither betaproteobacterial 354

AOB or comammox Nitrospira (both clade A and B) were detected based either on end-point or 355

quantitative PCR using group-specific primers for amoA genes. AOA were most abundant in bare 356

surface soils, ranging from 1.81x106 to 1.27x109 amoA genes g-1 dry soil, with the highest 357

abundance at the Taymyr and Seida sites (1.27x109 and 6.39x108 amoA genes g-1 dry soil, 358

respectively) (Fig. 1D). In contrast, archaeal amoA gene abundance was below 4.32x106 genes g-1 359

dry soil in all vegetated soils. On average, abundance of amoA genes was 225 ± 72.5 (mean ± 360

standard error) times higher in bare than in vegetated peat surfaces.

361 362

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Sequencing of amoA genes 363

High-throughput sequencing of archaeal amoA genes revealed that AOA communities had very low 364

diversity across all sites, and comprised only two phylotypes of the clades NS-ζ-1.2 and NS- 365

γ−2.3.2 clades, respectively, associated with the taxonomic order Nitrososphaerales (Fig. 2A;

366

amoA-based taxonomy defined by Alves et al. 2018). This was unexpected considering that the 367

samples were collected from very distant arctic geographic locations. Nevertheless, this was 368

consistent with the relatively low diversity of denitrifiers previously observed in bare peat surfaces 369

at the Seida site by Palmer et al., (2012). While clade NS-γ does not have any cultivated 370

representatives, clade NS-ζ corresponds to the recently characterized candidate genus 371

Nitrosocosmicus. The closest cultivated relatives of the most abundant clade NS-ζ amoA gene 372

amplicon sequence variants (ASVs) (Fig. S2) were Candidatus Nitrosocosmicus arcticus Kfb 373

(Alves et al. in review), enriched from a high arctic soil, with 89-92% sequence similarity, followed 374

by Ca. Nitrosocosmicus oleophilus MY3 with 88-90% similarity (Jung et al., 2016). In most soils, 375

the relative abundance of clade NS-ζ was much higher than that of NS-γ, which only dominated at 376

the Tazovsky peat plateau site. The estimated absolute abundance (calculated by multiplying 377

relative abundances of clades by the total amoA gene abundance) of these clades showed that clade 378

NS-ζ dominated AOA communities in Kevo and Seida bare surfaces and in Taymyr vegetated 379

surfaces (Fig. 2B). The fold-difference of clade NS-ζ over NS-γ varied from 2.1 to 20770 in bare 380

soils and from 1.3 to 5.4 in vegetated surfaces (except at the Tazovsky peat plateau in both cases) 381

(Fig. 2C). Soil nitrate concentrations correlated positively with total amoA gene abundance (rho = 382

0.45, P < 0.05) and with the absolute abundance of each clade (rhoNS-γ = 0.45, P < 0.05; and rhoNS-ζ 383

= 0.41; P < 0.05). The abundance of both clades and soil nitrate concentrations had a significant (P 384

< 0.005) interactive effect on N2O fluxes. The absolute abundance of clade NS-ζ together with soil 385

nitrate content had the best explanatory power (F = 14.19, d.f.1=3, d.f.2=12, R2 = 0.78, P < 0.005) 386

for the N2O fluxes measured (Table S6). Despite the low diversity of AOA, archaeal amoA genes 387

exhibited some micro-diversity, as seen among ASVs (Fig. S3), which showed considerable site- 388

related distribution patterns (PERMANOVA (sites) P < 0.05). The consistent micro-diversity 389

between sites also confirmed that the unusual low phylotype diversity across distant geographical 390

locations reflected natural populations and not potential cross-contamination between samples 391

during laboratory analyses (Fig. S2). The average identity between ASVs from clades NS-ζ and 392

NS-γ was 78% (based on consensus cluster sequences).

393 394

Gross nitrification and amoA transcription 395

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Gross nitrification rates were approximately 2.5 mg NO3--N kg-1 dry soil h-1 in control soil.

396

incubations (i.e., without inhibitors), which are in the upper range of those measured earlier in 397

Arctic soils (Alves et al., 2013), and about 20-50 times higher than those measured earlier at the 398

Seida site and other tundra ecosystems (Gil, 2017; Wild et al., 2015). Carboxy-PTIO, the AOA- 399

specific inhibitor, significantly reduced gross nitrification rates to approximately 60% of the rates in 400

soils without inhibitor treatments and completely inhibited archaeal amoA gene transcription (Fig.

401

3). In contrast, ATU at concentration known to inhibit only AOB and comammox Nitrospira, had 402

no significant effect on gross nitrification rates, whereas net nitrification was even slightly increased 403

(Fig. S4), consistent with the fact that no AOB or comammox were detected. These results indicated 404

that AOA was specifically inhibited by carboxy-PTIO and that they were the main active ammonia 405

oxidizers in this soil (Fig. 3). Carboxy-PTIO did not, however, lead to full inhibition of nitrification 406

(see discussion below), and did not significantly change the amoA gene abundance, transcription of 407

archaeal 16S rRNA genes, nor soil NO3-

content (Fig. S4).

408 409 410

Discussion 411

In natural soils subject to low inorganic N inputs, such as those in the Arctic, nitrification is the 412

main source of NO2- and NO3-,and is thus also directly or indirectly the first and limiting step of the 413

N2O production. Bare surfaces on permafrost peatlands are known to be significant emitters of N2O 414

in the Arctic (Repo et al., 2009) and recent findings have indicated that global warming enhances 415

these emissions (Voigt et al., 2017a). Here, we identified the key microbial populations driving 416

ammonia oxidation, the rate-limiting step of nitrification, which strongly regulates substrate 417

availability for N2O production across a broad geographical range of arctic peatlands with high N2O 418

emissions. High N2O emissions in these soils are related to optimal soil moisture (0.30-0.70 m3/m-3) 419

and NO3- content (> 5 mg g-1), as previously observed for high N2O-emitting organic soils in the 420

temperate and tropical regions (Pärn et al., 2018).

421 422

Denitrification is generally considered a more important source of N2O than nitrification (Hu et al., 423

2015). Consistent with this assumption, denitrification has been shown to produce high amounts of 424

N2O in bare peat soils from Seida under anoxic conditions (Palmer et al., 2012). Here, we show that 425

archaea were the main active ammonia oxidizers in these soils and thus the main mediators of N2O 426

emissions through nitrite production. Nitrous oxide can then be produced through denitrification of 427

both nitrite and nitrate, and thus archaeal ammonia oxidation not only provides the substrate for 428

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nitrate production by nitrite-oxidizing bacteria, but may also feed denitrification directly bypassing 429

the nitrite oxidation step. Moreover, previous 15N-site preference studies have also indicated that 430

nitrification can contribute directly to N2O emissions in these soils, especially during dry seasons 431

(Gil et al., 2017). AOA can produce N2O both under both aerobic and anaerobic conditions through 432

the hybrid formation from NO and hydroxylamine, although production rates are higher under oxic 433

conditions, which prevail in dry soils (Stieglmeier et al., 2013; Kozlowski et al., 2016).

434

Additionally, NO produced by AOA may also generate N2O in peat soils through chemical 435

reactions with abundant humic acids (Zhu-Barker et al., 2015; Kozlowski et al., 2016). Therefore, 436

in addition to fueling denitrification, AOA may also contribute directly to the high N2O emissions 437

from these arctic bare peat soils.

438 439

Ammonia-oxidizer communities in bare and vegetated peat soils were characterized through 440

quantification of amoA genes and gene transcripts, and high-throughput sequencing of amoA genes.

441

While typically both AOA and AOB co-occur in most soils worldwide (Leininger et al., 2006; Jia 442

and Conrad, 2009; Hink et al., 2018), we could only detect archaeal amoA genes across all peat 443

soils studied here, but not those of betaproteobacterial AOB or comammox Nitrospira. Few earlier 444

studies have also shown AOA to be the only detectable or active ammonia oxidizers in some soils 445

(Stopnisek et al., 2010; Herrmann et al., 2012; Isobe et al., 2018), including in soils from high 446

Arctic (Alves et al., 2013) and sub-Arctic (Daebeler et al., 2012) ecosystems. However, to our 447

knowledge, this is the first time that the absence of AOB or sole presence of AOA was observed in 448

soils emitting a high amounts of N2O. Our incubation experiments with group-specific inhibitors 449

confirmed that nitrification activity was indeed carried out mainly by archaea and not by bacteria in 450

peat soils from our long-term experimental site in Seida. Both gross nitrification activity and 451

transcription of amoA genes, were only reduced significantly with the archaea-specific inhibitor 452

carboxy-PTIO, but not with ATU at concentrations known to inhibit specifically AOB (Shen et al., 453

2013; Sauder et al., 2017) and comammox Nitrospira (van Kessel et al., 2015). Full inhibition of 454

nitrification was, however, not achieved with carboxy-PTIO, likely due to low inhibition efficiency 455

in the complex peat matrix. However, we cannot rule out the possibility that heterotrophic nitrifiers 456

might have also contributed to the nitrification activity observed in the presence of carboxy-PTIO, 457

especially by benefitting the inhibition of AOA. While ATU has been shown to affect AOA at 458

concentrations much higher than those used here (Shen et al., 2013; Lehtovirta-Morley et al., 2013), 459

it might have had also a residual inhibitory effect on AOA, which might explain why nitrification 460

was reduced slightly with ATU, although not significantly.

461

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462

Surprisingly, we only identified two AOA phylotypes across all geographically-distant arctic 463

peatlands studied here, which effectively represent the whole detectable ammonia oxidizer diversity 464

at these sites. While only few denitrifier phylotypes were also found to dominate denitrifier 465

communities particularly in bare peat surfaces at the same Seida sites, these nevertheless 466

represented a substantially greater diversity of organisms (11-20 OTUs) (Palmer et al., 2012).

467

Likewise, a comparably low diversity of methanotrophic bacteria has also been observed in high 468

arctic wetlands (Graef et al., 2011). These observations indicate that arctic peatlands share common 469

properties that favor the specific AOA phylotypes identified here, but that might have also a more 470

general selective effect on microbial communities. The very low pH of the peat soils studied here 471

(pH ranged from 2.81 to 4.06, Table S1) is likely a major factor selecting for these two specific 472

AOA phylotypes, as previously shown for soil AOA in general (Gubry-Rangin et al., 2011; Alves et 473

al., 2018). Soil pH strongly affects NH3 oxidation by regulating the availability of NH3 (the 474

presumed substrate of ammonia oxidation) in relation to ammonium (NH4+

). Given that NH4+

has a 475

pKa value of 9.25, ammonia availability is extremely limited in highly acidic soils, the 476

predominance of AOA in acidic soils (at least of specific AOA clades) has been proposed to result 477

from their high NH3 affinity (Gubry-Rangin et al., 2011; Prosser and Nicol, 2012). Indeed, the two 478

AOA phylotypes identified here belong to two subclades (NS-γ 2.3.2 and NS-ζ 1.2.) that have been 479

mainly detected in acidic (pH ≤ 6.5) environments (Alves et al., 2018). Low temperatures have also 480

been suggested to support the prevalence of AOA over AOB in alpine and arctic soils (Alves et al., 481

2013; Daebeler et al., 2012; Nemergut et al., 2008; Siciliano et al., 2009; Lamb et al., 2011;

482

Banerjee et al., 2012; Daebeler et al., 2017) and could be a crucial selective factor for archaea as 483

primary ammonia oxidizers in these ecosystems. A recent study has also observed that Ca. N.

484

arcticus Kfb, an AOA abundant in an arctic peatland (Alves et al., 2013) and a close relative of one 485

of the dominant AOA phylotypes identified here (clade NS-ζ), has higher ammonia oxidation 486

activity at temperatures well above those typical of its native arctic environment (>16 °C) (Alves et 487

al., in review). This suggests that the warmer temperatures currently affecting arctic ecosystems 488

(IPCC, 2018) may directly stimulate soil ammonia oxidation by AOA (at least from this lineage), in 489

addition to expected increases in substrate availability through higher N mineralization rates 490

(Schaeffer et al., 2013). Given current predictions of further temperature increases in the Arctic 491

(IPCC), our results suggest that AOA-mediated nitrification could contribute to a significant 492

positive feedback to global warming by fueling higher N2O emissions from arctic peatlands.

493 494

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In conclusion, our results show that AOA have a crucial role in nitrification and high N2O 495

emissions from Arctic permafrost peatlands. High soil N2O emissions are usually associated with 496

manipulated soils, like agricultural soils, where AOB are the main drivers of N2O emissions 497

through nitrification of large inputs of N fertilizer (Hink et al., 2018). To our knowledge, Arctic 498

peat soils in this study are the first natural environments where high N2O emissions have been 499

linked to AOA. Given the large differences in ammonia oxidation and temperature kinetics 500

observed among only a few AOA (e.g., Kits et al., 2017; Alves et al., in review), this study also 501

highlights the need to better understand the physiology of AOA that play key roles in critical 502

biogeochemical processes, particularly in sensitive ecosystems such as permafrost soils. This 503

information will be essential to inform biogeochemical models of the N cycle in these systems and 504

improve our predictions of potential non-carbon feedbacks to climate changes.

505 506 507

Acknowledgments:

508

We thank Simo Jokinen for technical assistance. This work was supported by the Academy of 509

Finland [290315], The Kuopio Naturalists’ Society, Federation of European Microbiologist Society, 510

Saastamoinen Foundation., and project P25369 of the Austrian Science Fund (FWF).

511 512 513

Competing Interests Statement:

514

The authors declare that the research was conducted in the absence of any commercial or financial 515

relationships that could be construed as a potential competing or conflicting interest.

516 517

Author contributions:

518

H.S., R.A., P.M., C.S. and C.B., designed the project. R.A., H.S., C.B., R.L., J.R., H.B. and M.M., 519

collected the soil samples and measured N2O fluxes in the field and participated measurements of 520

soil properties. H.S., R.L., H.B., M.M. and C.B., measured gross-nitrification rates and did the 521

microcosm experiment. H.S., J.R., R.L. and A.B., extracted and purified nucleic acids of the 522

samples, amplified DNA with PCR, and prepared the samples for sequencing. H.S., A.B., R.A. and 523

C.S. did bioinformatics and interpreted the results. H.S., wrote the manuscript and all authors 524

discussed and revised the manuscript.

525 526

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527 528 529

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