Front. Environ. Sci. Eng. DOI 10.1007/s11783-014-0635-3

RESEARCH ARTICLE

Abundance and distribution of ammonia-oxidizing archaea in Tibetan and Yunnan plateau agricultural soils of China Kun DING, Xianghua WEN (✉), Liang CHEN, Daishi HUANG, Fan FEI, Yuyang LI Environmental Simulation and Pollution Control State Key Joint Laboratory, School of Environment, Tsinghua University, Beijing 100084, China

© Higher Education Press and Springer-Verlag Berlin Heidelberg 2014

Abstract As low oxygen and high ultraviolet (UV) exposure might significantly affect the microbial existence in plateau, it could lead to a specialized microbial community. To determine the abundance and distribution of ammonia-oxidizing archaea (AOA) in agricultural soil of plateau, seven soil samples were collected respectively from farmlands in Tibet and Yunnan cultivating the wheat, highland-barley, and colza, which are located at altitudes of 3200–3800 m above sea level. Quantitative PCR (q-PCR) and clone library targeting on amoA gene were used to quantify the abundances of AOA and ammonia-oxidizing bacteria (AOB), and characterize the community structures of AOA in the samples. The number of AOA cells (9.34
107–2.32
108 g–1 soil) was 3.86–21.84 times greater than that of AOB cells (6.91
106–1.24
108 g–1 soil) in most of the samples, except a soil sample cultivating highlandbarley with an AOA/AOB ratio of 0.90. Based Kendall’s correlation coefficient, no remarkable correlation between AOA abundance and the environmental factor was observed. Additionally, the diversities of AOA community were affected by total nitrogen and organic matter concentration in soils, suggesting that AOA was probably sensitive to several environmental factors, and could adjust its community structure to adapt to the environmental variation while maintaining its abundance. Keywords ammonia-oxidizing archaea, ammonia-oxidizing bacteria, quantitative PCR, clone library, plateau

1

Introduction

Generally, nitrification includes two steps: oxidation of – ammonia (NHþ 4 ) to nitrite (NO2 ) executed by ammoniaoxidizing bacteria (AOB) and nitrite (NO2– ) to nitrate Received August 13, 2013; accepted December 9, 2013 E-mail: [email protected]

(NO3– ) executed by nitrite-oxidizing bacteria (NOB). Ammonia oxidation is often the rate-limiting step of the whole nitrification process in a wide variety of environments [1]. For a long time, AOB have been considered the – key to oxidization of ammonia (NHþ 4 ) to nitrite (NO2 ) [2]. Recently, some archaea, e.g. the crenarchaeal groups I.1a and I.1b, was suggested to potentially have the capability of performing chemoautotrophic nitrification based on several meta-genome analyses [3]. The first critical evidence for autotrophic archaeal ammonia oxidation was reported by Könneke et al. [4]. They isolated an ammonia-oxidizing archaeon named Nitrosopumilus maritimus from an aquarium. Subsequently, some other ammonia-oxidizing archaea (AOA) were isolated or enriched from hot spring [5], marine sediments [6], sand of an eelgrass zone [7], and soil [8]. Molecular ecological studies demonstrated that AOA were often found to be markedly abundant in various natural environments, such as soil [9], estuarine sediments [10], and seawater [11]. Moreover, AOA were also detected in several engineered environments, such as drinking water treatment facilities [12], and wastewater treatment plants [13,14]. A number of studies have shown that archaeal amoA genes outnumbered bacterial ones in many natural environments. In marine, the archaeal amoA abundance was 1–2 orders of magnitude higher than the bacterial one [15]. In 12 pristine and agricultural soils of three climatic zones, amoA gene copies of archaea were up to 3000-fold more abundant than those of bacteria [9]. In some European industrial wastewater treatment plants (WWTPs), archaea carrying amoA gene were detected in high abundance, e.g., up to 10000-fold than bacteria [16]. Opposite to these evidences of abundance of AOA, several recent studies reported the predominance of AOB in sediments [10]. The environment factors, such as temperature, pH, depth, and salinity, might have effect on the abundance and distribution of AOA and AOB [10,11,17]. In addition, altitude was also considered as an influential factor shifting the quantitative ratio of AOA/AOB [18].

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Some study has observed the correlation between ammonium levels in the effluent and the abundance of AOA amoA genes in WWTPs [14]. Focusing on agricultural soil, AOB are probably to be the key players of nitrification in agricultural soils featured with relatively high ammonia concentrations [19], while AOA presented competitive advantages in soil nitrification at low concentrations of ammonia [20]. In other studies, AOA was observed responding to ammonia amendment in an agricultural soil [20], and also combined with AOB responding to organic fertilizer amendment [21]. Though some studies on AOA in natural and engineered environments have been done and published, which indicates the increasing concern on AOA, there has been barely research on the distributions and community structures of AOA in plateau agricultural soils. Contrasting to the plain (a fertile region which is located at altitudes of less than 200 m above sea level), the plateau, an area of highland which is located at altitudes of over 3000 m above sea level, is well known for its special environmental conditions, such as low atmospheric pressure, low oxygen content in air, strong ultraviolet (UV) exposure, and special life style (e.g., people need to eat food with more calorie to resist alpine hypoxia and keep health especially in the Tibetan plateau compared to the plain area), which might significantly affect microbial existence and lead to a specialized microbial community. The plateau in western china, especially the Tibetan plateau and Yunnan plateau which located at altitudes of over 3000 m above the sea level, is considered an amplifier of global climate change [22]. The increasing air temperature, one critical indicator of global warming, might have a complicated effect on the vegetation cover in plateau and the microbes in top soils [23,24]. However, the abundance and community structure of AOA in the agricultural soils of the plateau area have not been studied. In this study, cloning library and quantitative PCR (q-PCR) were used to determine the diversity and distribution of AOA in the typical agricultural soils of the plateau regions, and ultimately to identify the factors which have tangible impacts the abundance and community structure of AOA in those soils.

2

Material and methods

2.1

Sample collection

In July 2010, seven soil samples (respectively tagged as Tibet-DL2#, Tibet-DL3#, Tibet-DZ3#, Tibet-DZ4#, TibetDZ5#, Yunnan-NPH4#, Yunnan-NPH5#) were collected from the farmlands cultivating wheat, highland barley, and colza soil in Tibet and Yunnan, which located at altitudes of 3200–3900 m above sea level (Table 1). Ten subsamples (each of 10 g) from the topsoil were pooled and sieved (2.0 mm mesh size) as one sample after removal of large stones,

plant roots and other impurities, and three samples were obtained and analyzed for each site. The sieved samples were stored in a – 18°C thermostatic refrigerated container, and transported to the laboratory. The samples were store at – 80°C prior to the chemical analysis and DNA extraction. 2.2

Chemical analysis

In this study, all the chemical analyses were performed in triplicate. Soil total nitrogen (TN) was determined by the semi-micro Kjeldahl method. Soil pH was determined by a multi-parameter measuring instrument (Thermo Scientific Orion 520M-01, USA) with a soil to water ratio of 1:10. Soil organic carbon was determined by using the K2Cr2O7 oxidation method. Soil inorganic nitrogen, including Ammonia-N, Nitrite-N and Nitrate-N, was extracted 1 mol$L–1 KCl solution. The concentrations of ammonia and nitrite in the soil extraction were measured by using colorimetric methods, and nitrate was measured by using UV spectrometric method. 2.3

DNA extraction

DNA extraction from 0.5 g of each soil sample was performed by using the FastDNA® SPIN Kit for Soil (MP Biomedicals, USA) following the manufacturer’s protocol. The amount and purity of DNA were determined by using a NanoDrop® Spectrophotometer ND-1000 (Thermo Fisher Scientific, USA) based on the absorbency of A260 and the ratio of A260/A280 respectively. 2.4

PCR amplification of archaeal amoA gene

Archaea amoA gene fragments were amplified from the soil total DNA using the primer pairs of Arch-amoAF (5′STAATGGTCTGGCTTAGACG-3′)/Arch-amoAR (5′GCGGCCATCCATCTGTATGT-3′) [25] with Takara EX Taq DNA polymerase (Takara, Dalian, China). The total volume of PCR mixture was 25 μL containing 2.5 μL 10
EX Taq buffer, 2.5 μL deoxynucleotide triphosphate (dNTP) mix (2.5 mmol$L–1 for each kind of dNTP), 1 U of Ex Taq DNA polymerase(5 U$μL–1), 25 pmol of each primer, and 10–20 ng template DNA. Thermal cycling of PCR mixture was carried out by a Pre-denaturation step at 94°C for 5 min followed by 40 cycles of denaturing (94°C, 40 s), annealing (53°C, 60 s) and elongation (72°C, 60 s). After electrophoresis, PCR products were visualized on a 1% agarose gel stained with Gold View I to confirm the products’ size, and purified with a QIAquick® Gel Extraction Kit (QIAGEN Sciences, USA) as described in the QIAquick® Spin Handbook. 2.5

Cloning and sequencing

Purified PCR products were linked to pGEM-T easy

Kun DING et al. Ammonia-oxidizing archaea abundance and diveristy in plateau agricultural soils

Vectors (Promega, USA) and cloned into competent Escherichia coli DH5α cells (Tiangen, China) according to the manufacturer’s protocol. The blue-white screen was used to check clones with inserts. White colonies were incubated overnight at 37°C in the fresh liquid LuriaBertani (LB) medium. Primer pairs T7/SP6 were utilized to select the positive clones with the correct size of 635 bp. Subsequently, the sequences amplified from the positive clones were sent to a commercial company (Sinogenomax, China) for sequencing. The archaeal amoA gene fragments of clones representing close phylogeny types with ≥97% similarity were classified as the same operational taxonomic unit (OTU). Several representative amoA gene fragments were picked out from each OTU to generate a neighbor-joining phylogenetic tree in the software ClustalX 1.8 and Mega 4.0 using Jukes-Cantor with 1000 replicates to produce bootstrap values. 2.6

Fluorescent quantitative PCR targeting amoA gene

Archaeal and bacterial amoA gene in soil samples were quantified by Real-time PCR with SYBR Green I on an iCycler iQ5 thermocycler (Bio-Rad, USA) using primer pairs of Arch-amoAF/Arch-amoAR [25] and amoA1F(5′G G G G T T T C TA C T G G T G G T- 3 ′ ) / a m o A 2 R ( 5 ′ CCCCTCKGSAAAGCCTTCTTC-3′) [26] respectively. All Real-time PCR mixtures in triplicate consisted of 12.5 μL 2
SYBR® Premix Ex TaqTM (Takara, Dalian, China), 25 pmol of each primer, and 1 μL template (10–20 ng) or 10-fold diluted of constructed DNA plasmid for standard curves in a final volume of 25 μL. Thermal cycling conditions were as follows: an initial denaturation step at 95°C for 1 min, followed by 40 cycles of 94°C for 40 s, 53°C for 1 min and 72°C for 1 min. The Fluorescent intensity was measured at 72°C. Analysis of Melt curve was determined at the end of Real-time PCR protocol to identify the specificity of the PCR products. The positive clones from Cloning and Sequencing were selected to extract constructed DNA plasmids with a QIAGEN® Plasmid Mini Kit (QIAGEN Sciences, USA) for standardization of archaeal or bacterial amoA gene templates which was determined by a NanoDrop® Spectrophotometer ND-1000 (Thermo Fisher Scientific, USA). Amplification efficiency of archaeal and bacterial amoA gene for standard curves were 99.1% and 101.4% respectively. Correlation coefficients were 0.995 for AOA, and 0.994 for AOB. 2.7

Statistical analysis

The analysis of Kendall’s correlation was conducted using the software SPSS 13.0. Shannon’s diversity index, Gini coefficient and Pareto-Lorenz curves were calculated or drawn to characterize the community structures of AOA.

2.8

3

Nucleotide sequence accession numbers

The archaeal amoA gene sequences obtained from this study were submitted to GenBank, and have been assigned the following accession numbers: JF748119-JF748386.

3

Results

3.1

Soil chemical properties

The alkalinity of the two samples NPH4# and NPH5# from Napa Lake district in Yunnan were 9.13 and 9.14, markedly higher than that of other samples, though all the samples were alkalescent (Table1). Generally, the soil samples collected from the same farming area possess similar chemical properties including pH, TN and organic matter (Table 1), indicating that the soil chemical properties are mainly affected by the altitude or the geographic position rather than the vegetation cover in the soil. The concentration of Ammonia-N in soils ranged from 0.80 to 9.27 mg$kg–1, which is similar to the previous reported values for the soils with relatively high ammonia [19]. The concentration ratios of soil inorganic nitrogen including ammonia-N, nitrite-N and nitrate-N to TN were extremely low, and the content of organic carbon had significantly positive correlation with the total nitrogen (P < 0.05; Table 2), demonstrating that most of nitrogen in soil existed in the form of organic nitrogen. Interestingly, the concentration of Ammonia-N in soils had positive correlation with that of Nitrate-N. 3.2

AOA and AOB abundance

The AOA and AOB abundance in the samples represented by the amoA gene copy number per gram soil are shown on Fig. 1(a). The Archaeal amoA gene copy number in samples ranged from 9.34
107 to 2.32
108 g–1 soil, closing to that in low altitude ( < 5400 m a.s.l.) soils in Mount Everest (5.17
107 to 3.79
108 g–1 soil) with the pH value of 8.6–9.0 [18]. However, it outnumbered those in some acid or neutral soils, e.g., an upland red soil in China (8.42
106 to 9.56
107 g–1 soil) [27] with the pH value of 3.7 – 5.8, and soils in Scotland (2.1
106 to 9.9
106 g–1 soil) with the pH value of 4.5–7.5 [17]. Bacterial amoA gene copy number varied from 1.73
107 to 3.09
108 g–1 soil, and was considerably higher than those found in previous studies, e.g., an agricultural topsoil (0–20 cm depth) in German (2.5
106 g–1 soil) with neutral pH [28], and low altitude ( < 5400 m a.s.l.) soils in Mount Everest (6.97
105 to 1.59
107 g–1 soil) [18]. Assuming each genome of AOB and AOA contains 2.5 and 1.0 amoA gene copy [3], as shown on Fig. 1(b), the number of AOA cell (9.34
107 to 2.32
108 g–1 soil) was 3.86–21.84 times greater than that of AOB cell (6.91

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Table 1 Soil geographical and chemical characteristics of samples in the plateau soil code

vegetation cover

DL2#

pH

highland 8.010.04 barley

organic carbon /(g$kg–1)

total nitrogen (TN)/(g$kg–1)

ammonia-N /(mg$kg–1)

nitrite-N /(mg$kg–1)

nitrate-N altitude/m /(mg$kg–1)

30.920.66

2.200.00

2.170.02

0.390.01

2.270.00

3873

alongitude

latitude

E 90°44′30″ N 29°50′50″

DL3#

wheat

8.790.03

33.850.78

2.180.18

9.270.49

0.190.00

1132

3681

E 90°56′31″ N 29°40′08″

DZ3#

wheat

7.150.03

23.580.76

1.490.02

4.430.09

0.060.01

21.30.4

3707

E 91°24′33″ N 29°40′46″

highland 7.640.03 barley

23.522.57

1.630.03

3.210.03

0.060.00

19.90.5

3714

E 91°22′21″ N 29°40′03″

7.710.03

24.501.51

1.530.03

1.260.02

0.030.01

0.200.15

3715

E 91°22′21″ N 29°40′03″

highland 9.130.01 barley

29.511.39

1.860.13

0.800.04

0.030.02

0.500.25

3253

E 99°37′23″ N 27°53′00″

27.901.77

1.750.20

1.010.03

0.100.01

N/A

3253

E 99°37′23″ N 27°53′00″

DZ4#a) DZ5#a)

colza a)

NPH4#

NPH5#a)

colza

9.140.01

Notes: a) The resolution of Global Positioning System (GPS) Locator used in this study was 1″ (& 30.8 m), and the distances, from DZ4# site to DZ5# site and from NPH4# site to NPH5#, were shorter than 30.8 m


10 6 to 1.24
108 g–1 soil) in most of the samples, except DL2# which had a quantitative AOA/AOB ratio of 0.90, indicating that archaea was predominant among ammoniaoxidizing prokaryotes. The AOA/AOB ratio found in this study was similar to the finding in a marine related study [15]. In contrast to a previous research [18], it was observed that no significant positive or negative correlation between the abundance of AOA or AOB and other properties of the soil samples in this study. However, there was an obvious positive correlation between AOB abundance and the concentration of nitrite in soil samples (Table 2). These results imply that the soil properties might have relatively

complex effects on AOA and AOB abundance, rather than putative linear correlation among them. 3.3

Community structure of AOA

Referring to the results of clone library and operational taxonomic unit (OTU) classification rules, totally 268 sequences of archaeal amoA gene found in the seven soil samples were categorized into 20 OTUs with the coverage of 87.5%–100.0%. As shown on Fig. 2, the representative sequences selected from each OTU combined with related sequences derived from National Center of Biotechnology Information (NCBI) database were used to construct the

Table 2 Kendall’s correlation coefficient among the AOA/AOB abundance, the distribution of AOA and the properties of soil samples (n = 7) abundance abundance ratio of of AOA of AOB AOA/AOB abundance of AOB

0.048

ratio of AOA/AOB

0.238

– 0.714*

pH

– 0.333

– 0.143

pH

TN

ammonia-N nitrite-N

nitrate-N

organic C

altitude

diversity index

Pareto coefficient

– 0.143

TN

– 0.429

0.143

– 0.429

0.333

ammonia

0.333

0.524

– 0.238

– 0.429

– 0.143

nitrite

– 0.250

0.651*

– 0.651*

0.050

0.551

0.350

nitrate

0.143

0.333

– 0.238

– 0.429

0.048

0.810*

0.250

organic matter

– 0.333

0.238

– 0.524

0.429

0.714*

– 0.048

0.350

0.143

altitude

0.390

0.390

– 0.098

– 0.390

0.000

0.098

0.103

0.000

– 0.098

diversity index

0.333

– 0.238

0.524

– 0.429

– 0.905**

0.238

– 0.451

0.048

– 0.810*

– 0.098

Pareto coefficient

– 0.098

0.390

– 0.488

0.488

0.683*

0.000

0.513

– 0.195

0.683*

0.150

– 0.781*

Gini coefficient

– 0.333

0.238

– 0.524

0.429

0.905**

– 0.238

0.451

– 0.048

0.810*

0.098

– 1.000**

0.781*

Notes: * Correlation between two parameters is significant at the level of 0.05 (two-tailed); ** Correlation between two parameters is significant at the level of 0.01 (two-tailed)

Kun DING et al. Ammonia-oxidizing archaea abundance and diveristy in plateau agricultural soils

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Fig. 1 (a) Abundance of archaeal and bacterial amoA gene in Tibetan and Yunnan plateau agricultural soils and (b) abundance of AOA and AOB in Tibetan and Yunnan plateau agricultural soils (the left y-axis represents the abundances of AOA and AOB, and the right y-axis represents the ratio of AOA and AOB abundance)

phylogenetic tree of archaeal amoA gene. All the archaeal amoA gene sequences fell into the soil/sediment lineage that consisted of the sequences obtained from soil and sediment environments and grouped into three different clades (Fig. 2), and Clade 3 was excluded in the monophyletic lineage formed by Clade 1 and Clade 2, showing a similar topology analogous to the result of a previous research on AOA in soils of Mount Everest [18]. In other words, this result indicates that the soil samples collected from different areas in Tibet or other plateau areas of China probably have a similar topology of phylogenetic tree of archaeal amoA gene The sequences of archaeal amoA gene in Clade 1 were grouped into 6 OTUs out of all the 20 OTUs, among which OTU 1 and OTU 9 were dominant with proportions of 55.0%–90.0% in the samples (Fig. 3), suggesting that Clade 1 accounted for the majority of overall AOA sequences and were present in all soils at modest varying proportions. Though there were 12 OTUs in Clade 2, the proportions of these OTUs were much lower than those observed in Clade1, showing that the sequences from Clade 2 had high diversities but low abundances. In addition, Clade 3 consisting of OTU 2 and OTU 3 represented the minority of the sequences. In addition, no sample with all the 20 OTUs has been detected, suggesting that the species of AOA in soil environments were so various that it was rarely to find all species of AOA in single soil sample. The archaeal amoA genes in the plateau agricultural soil showed higher diversity than that in other soils reported by some researchers [27], though the Shannon’s diversity indices of samples were different from each other (Fig. 4). Corresponding to the soil chemical properties, the microbial community diversity indices of samples collected from the same farming area were more similar. For example, the Shannon’s diversity indices obtained from DZ3# and

DZ4#, with the values of 0.743 and 0.936, were lower than those obtained from other samples. There were significant negative relationship between the Shannon’s diversity index and the Gini coefficient with the value of “ – 1.000” (P < 0.01, Table 2). Moreover, the Gini coefficients obtained from NPH4# and NPH5#, with the values of 0.878 and 0.868, were very similar compared to those obtained from other samples. As shown in Table 2, soil chemical properties, especially high TN and organic matter, had negative effect on the diversities of AOA community, and increased the uneveness level of species distribution in AOA community. The soil samples collected from the same farming area possess similar TN and organic matter. In summary, the results indicate that diversities of AOA provide clues about the characteristic of geographical distribution of AOA. Similar to the previously studies related to AOB and methanotrophic bacteria [29,30], Pareto-Lorenz (PL) evenness curves (Fig. 5) were drawn based on the classification data of species OTUs in the samples and used to analyze the species distributions of AOA communities. The PL curves of all the samples were far away from the ideal curve (straight line), meaning that the distributions of AOA communities in all the samples were unequal, especially those in DL2# and DL3# with the Gini coefficients of 0.912 and 0.896 respectively (Figs. 4 and 5). As observed on Fig. 5, the top 20% of OTUs corresponded with at least 80% of the cumulative sequences of the OTUs in all the samples, suggesting that the uneven species distributions of AOA communities follow the Pareto principle (also known as the 80/20 rule).

4

Discussion

In this study, we focused on the abundance and distribution

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Fig. 2 Neighbor-joining phylogentic tree of archaeal amoA gene sequences (635 bp) obtained from the agricultural soils, on the Tibetan and Yunnan Plateau. Clones in this study are shown in bold with the soil code (DL2#, DL3#, DZ3#, DZ4#, DZ5#, NPH4# and NPH5#), followed by clone code in some soil sample, the following accession number in GenBank, and then by the number of OTU

of ammonia-oxidizing archaea in agricultural soil of plateau in China. As seen on Figs. 2 and 3, ammoniaoxidizing archaea was superior in terms of abundance

among ammonia-oxidizing prokaryotes in the tested soil samples, and the soil chemical properties have influence on the community structure of AOA (Table 2).

Kun DING et al. Ammonia-oxidizing archaea abundance and diveristy in plateau agricultural soils

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Fig. 3 Histograms of OTU cumulative percentages related to archaeal amoA gene in the seven soil samples. The relative percentage is the ratio of the number of sequences in a given OTU of a given sample to the sum of the number of sequences in that sample

Fig. 4 Histograms of diversity index and Gini coefficient of AOA community in the seven soil samples. The left y-axis represents the Shannon index of AOA community, and the right yaxis represents the Gini coefficient of AOA community

However, the question which is the dominant nitrifier in the nitrification process of the agricultural soils has not

been answered yet in this study. Noticeably, higher abundance does not necessarily imply stronger capacity. Mussmann et al. found that archaea carrying amoA gene were detected in high abundance, while not all amoAcarrying archaea were capable of carrying out autotrophic ammonia oxidation [16]. Actually, AOA might have a potential mixotrophic metabolic pathway, based on the genomes analyses of N. maritimus SCM1 and “Ca. Cenarchaeum sysbiosum” which were successfully isolated or enriched from nature environments [3]. Moreover, Nitrososphaera viennensis EN76, isolated from soil, has 12 times greater growth yields with the addition of pyruvate (mixotrophic) than with the addition of only ammonia (purely autotrophic conditions) [8]. Additionally, some studies reported the possible reason that higher abundance of AOA was determined while AOB was underestimated was that DNA extraction from AOB micro-colonies was difficult [31], and AOA were more susceptible to the lysis than AOB [32]. Thus, all these data indicate that it is difficult to judge the contribution of AOA to ammonia oxidation with the result of higher AOA abundance.

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Fig. 5 Pareto-Lorenz curves based on the analysis of the clone libraries related to archaeal amoA gene on the seven soil samples. The red short dash-dot line at the 0.2x axis is drawn to evaluate the range of the Pareto values

Interestingly, we found that there was an obvious positive correlation between AOB abundance and the concentration of nitrite-N in soil samples. Generally, nitrite is the direct product of ammonia oxidation, and AOB seems to be a more positive ammonia oxidizer in the agricultural soil of plateau. However, excess nitrite is toxic to AOA and AOB. The tolerance of AOB to nitrite toxicity ( < 15 mmol$L–1) is much higher than that of AOA (& 40 μmol$L–1) in soil solutions [33]. Assuming the soil water content of 25% in this study, nitrite concentrations in the soil solutions could be estimated from the data in Table1. It is clear that the low-level nitrite concentrations ranging from 0.00971 to 0.112 μmol$L–1 was barely harmful to the growths of both AOA and AOB compared to those previous reports described above. In addition, several recent studies found that in soil featured with relatively high ammonia concentrations, AOB might play a more important role key in nitrification [19]. These previous studies reported that bacterial amoA gene patterns but not archaeal ones correspond to nitrification activity as indicated by the rising nitrate concentrations. Since the samples were directly collected from agricultural soils in plateau without control experiments, the dynamic variation of the AOA abundance and the soil mineral nitrogen could not be measured in situ. Soil pH is potentially a major determinant of evolution, distribution of ammonia oxidizers responsible for soil nitrification. In this study, we found that archaeal amoA gene abundance in the agricultural soils of plateau which were alkalescent outnumbered those in some acid or neutral soils. Generally, it is agreed that ammonia could be the direct substrate to ammonia monooxygenase (AMO) rather than ammonium. Thus, pH combined with ammonia

concentration would impact on ammonia oxidation executed by ammonia oxidizers in soil via the theoretically predicted pathway NH3 + H+ ⇄ NHþ 4 (pKa = 9.25). More and more studies have shown that AOA could play a predominant role in ammonia oxidation under acidic conditions in accordance with low ammonia concentrations [17,28], based on the observation of a higher affinity of AOA to ammonia [4,6,8]. Assuming the soil water content of 25% in this study, the ammonia concentrations based on the ionization equilibrium in soil water were from 35.6 to 918 μmol$L–1, considerably higher than the substrate threshold of N. maritimus isolated from an aquarium [4], indicating AOA in the plateau agricultural soils could resist in the environment of high ammonia concentration with relative higher abundance in this study. Compared to the species distributions of AOA communities in this study, it was observed that AOB in soils/ biologic reactors and bacteria in WWTPs also have similar species distribution based on the denaturing gradient gel electrophoresis (DGGE) patterns [29,30] and T-RFs patterns [34], implying that the unevenness of microbial community might exist in ammonia oxidizer, even in the entire microbes. However, it should be noticed that preferential amplification could induce in the bias when applying molecular biologic tools based on conventional PCR [35]. Therefore, prior to formal experiment, extra care, such as selection of broad-spectrum primers and optimization of PCR amplification should be taken when using the PCR method. Recently, some studies found that soil pH was the key factor measured that significantly influenced community structure of AOA [17]. Intriguingly, in this study we found that TN and organic carbon had negative effect on the diversities of AOA community, though the properties do not affect the abundance of AOA (Table 2). The result indicates that TN and organic matter could be chosen as effective selection pressure to control the community structure of AOA. On the other hand, the AOA community might be sensitive to several environmental factors, and be able to adjust the community structure to adapt to the variation of factors while maintaining the abundance of AOA. Notably, the argument concerning whether AOB is more sensitive to environmental factors than AOA has not been solved [18]. Due to the harsh plateau environment, the sampling in plateau is much more difficult than that in plain, thus, seven samples were successfully collected from agricultural soils. To comprehensively identify the relationships among the abundance and distribution of AOA, and the soil chemistry properties, more sampling combined with further research is needed.

5

Conclusions

In this study, the analysis of AOA and AOB abundance in

Kun DING et al. Ammonia-oxidizing archaea abundance and diveristy in plateau agricultural soils

plateau agricultural soils indicated that the archaea was predominant in ammonia oxidizer and probably played a key role in the nitrification process. There was no significant positive or negative correlation between the abundance of AOA or AOB and the properties of soil samples. However, the diversities of AOA community were affected by the contents of total nitrogen and organic carbon. Acknowledgements This study was supported by the National Natural Science Foundation of China (Grant No. 51078207), and Research Fund for the Doctoral Program of High Education of China (No. 20090002770003). We wish to thank the staff of Research Platform for Modern Environmental Biologic Technology of School of Environment in Tsinghua University.

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