links between ammonia oxidizer community structure, abundance
TRANSCRIPT
Links between ammonia oxidizer community structure, abundance and nitrification 1
potential in acidic soils 2
3
Huaiying Yao1, Yangmei Gao
1, Graeme W Nicol
2, Colin D Campbell
3, James I Prosser
2, 4
Limei Zhang4, Wenyan Han
5, Brajesh K Singh
2,3,6* 5
6
1 Key Laboratory of Environment Remediation and Ecological Health, Ministry of Education, 7
Zhejiang University, Hangzhou, 310029, China. 8
2 Institute of Biological and Environmental Sciences, University of Aberdeen, Aberdeen 9
AB24 3UU, UK 10
3 Soils Group, Macaulay Land Use Research Institute, Craigiebuckler, Aberdeen AB15 8QH, 11
UK 12
4 Research Centre for Eco-environmental Sciences, Chinese Academy of Sciences, Beijing 13
100085, China 14
5 Tea Research Institute, Chinese Academy of Agricultural Sciences, Hangzhou 310008, 15
China 16
6. Hawkesbury Institute for the Environment, University of Western Sydney, Penrith South, 17
DC, NSW 1797, Australia 18
19
20
* Corresponding author: Brajesh K Singh 21
Email: [email protected] 22
Copyright © 2011, American Society for Microbiology and/or the Listed Authors/Institutions. All Rights Reserved.Appl. Environ. Microbiol. doi:10.1128/AEM.00136-11 AEM Accepts, published online ahead of print on 13 May 2011
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Abstract 23
24
Ammonia oxidation is the first and rate-limiting step of nitrification and is performed by 25
both ammonia oxidising archaea (AOA) and bacteria (AOB). However, the environmental 26
drivers controlling the abundance, composition and activity of AOA and AOB communities 27
are not well characterised and the relative importance of these two groups in soil nitrification 28
is still debated. Chinese tea orchard soils provide an excellent system for investigating the 29
long-term effects of low pH and nitrogen fertilization strategies. AOA and AOB abundance 30
and community composition were therefore investigated in tea soils and adjacent pine forest 31
soils, using quantitative polymerase chain reaction (qPCR), terminal-restriction fragment 32
length polymorphism (T-RFLP) and sequence analysis of respective ammonia 33
monooxygenase (amoA) genes. There was a strong evidence that soil pH was an important 34
factor controlling AOB, but not AOA abundance and the ratio of AOA to AOB amoA gene 35
abundance increased with decreasing soil pH in the tea orchard soils. In contrast, T-RFLP 36
analysis suggested that soil pH was a key explanatory variable for both AOA and AOB 37
community structure but a significant relationship between community abundance and 38
nitrification potential was only observed for AOA. High potential nitrification rates indicated 39
that nitrification was mainly driven by AOA in these acidic soils. Dominant AOA amoA 40
sequences in the highly acidic tea soils were all placed within a specific clade and one AOA 41
genotype appears to be well-adapted to growth in highly acidic soils. Specific AOA and AOB 42
populations dominated in soils at particular pH values and N content, suggesting adaptation 43
to specific niches. 44
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45
Key words: ammonia-oxidizing archaea; ammonia-oxidizing bacteria; nitrification, niche 46
differentiation; acidic soils, environmental variables 47
48
Introduction 49
Nitrification, the oxidation of ammonia to nitrate, is a critical step in the nitrogen cycle and 50
has significant agricultural and environmental consequences for the availability of nitrogen as 51
a plant nutrient, nitrate leaching to groundwater and the release of greenhouse gases into the 52
atmosphere. The rate-limiting step of nitrification, the conversion of ammonia to nitrite, can 53
be performed by both ammonia-oxidizing archaea (AOA), within the proposed 54
Thaumarchaeota (7, 42), and ammonia-oxidizing bacteria (AOB). Both groups have been 55
detected in a wide range of soil ecosystems (5, 10, 15, 29, 33). The potential for archaeal 56
ammonia oxidation has been confirmed in laboratory enrichments and in isolates (13, 23, 28). 57
In most soils, archaeal amoA genes are more abundant than those of bacteria, indicating that 58
archaea could have a greater role in soil ammonia oxidation than AOB (10, 29, 36). Bacterial 59
amoA genes are more abundant in some agricultural soils receiving additional nitrogen 60
amendments (15, 26), whereas archaeal amoA genes are more abundant in soils where 61
nitrification is fuelled by mineralised organic nitrogen (34, 44). 62
The high affinity for total ammonium of Nitrosopumilus maritimus, the only cultivated 63
AOA (31), suggests that they may dominate ammonia oxidation in oligotrophic environments 64
such as the open ocean. In soil ecosystems, nitrifiers and nitrification rates vary with 65
vegetation type, location and environmental conditions (16,49). Soil pH is known to have a 66
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considerable effect on the activity and diversity of soil ammonia oxidisers (12, 33) and it has 67
been suggested that the absence of nitrification activity in some highly acidic soils is the 68
result of AOB sensitivity to low pH (11, 12), although growth and activity of some AOB at 69
low pH may be possible through urease activity and aggregate formation (2, 8, 12). Specific 70
AOA and AOB phylotypes have been found to be associated with soil pH across a pH 71
gradient of 4.3 to 7.5, with an increase in the ratio of amoA transcript:gene abundance with 72
decreasing and increasing pH for AOA and AOB communities, respectively (33). N fertilizer 73
can also affect the activity and abundance of ammonia-oxidizers (15, 19, 39, 49). However, 74
the mechanisms controlling activity of a particular group of soil ammonia oxidizers or the 75
potential for niche differentiation are not clear. 76
Tea (Camellia sinensis) orchard soils provide an excellent environment to examine the 77
relative contribution of AOA and AOB in nitrification processes and niche adaptation by 78
different genotypes within AOA and AOB lineages. Tea is an important economic crop and is 79
planted widely on acid red soils in the tropical and subtropical zones in China. High levels of 80
nitrogen fertilizer are applied, altering N cycling and microbial community structure (45, 54). 81
Soils under tea plantations are often acidic, with pH values ranging from 3.5 to 5.5, but, 82
despite the potential sensitivity of AOB to low pH, nitrification rates and nitrate 83
concentrations are high (9, 35, 51,53). Soil type and vegetation have potentially additional 84
effects on microbial community composition (27), and it is therefore pertinent to compare tea 85
soils with other vegetated systems on the same soil type. 86
The aim of this research was to determine how AOA and AOB community composition 87
and abundance vary in response to soil pH and N input, to assess the relative contributions of 88
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AOA and AOB to soil nitrification, and to determine drivers of ammonia oxidizer community 89
composition and activity. We hypothesized that AOA are responsible for most of the 90
nitrification in acidic soils; that soil pH and N fertilizer input influence both ammonia 91
oxidizer structure and nitrification potential, and that different AOA and AOB phylotypes 92
occupy distinct pH ranges (i.e. niche differentiation). To achieve this, AOA and AOB 93
community structure, abundance and associated potential nitrification rates were determined 94
in tea soils and in adjacent pine plantations. 95
96
Materials and methods 97
Study sites and soil sampling 98
Soil samples for the study were collected from two sites. The first is located in the West 99
Lake district of Hangzhou (30o11' N/120
o05'E), Zhejiang Province in China, where selected 100
tea soils represent a wide range of orchard age, fertilizer (urea) and lime applications. Since 101
the N application rate is high in Hangzhou area, samples were also obtained from a second 102
site, with two low N application tea orchard soils in Taihu county, Auhui Province in China 103
(30o33' N/116
o20'E). Adjacent pine forest soils at each site were sampled to evaluate and 104
compare the effect of vegetation on ammonia oxidizing communities. The two sites are 105
characterized by a subtropical wet monsoon climate with mean annual rainfall of 1400 - 1500 106
mm. All soils were Ultisols with kaolinite, chlorite, Fe and Al oxides as the dominant clay 107
minerals. The soils were developed on quaternary red earth. Triplicate samples were collected 108
from three sampling plots randomly chosen within each tea orchard or pine forest. Six 109
random soils cores (5 cm diameter × 15 cm length) was taken from each sample and mixed. 110
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Field moist soils were sieved to <2 mm and visible pieces of plant material and soil animals 111
were removed before use. Subsamples of each replicate were stored at -80°C prior to DNA 112
extraction. The land use history and some physicochemical properties of the soils are 113
presented in Table 1. 114
115
Soil chemical analysis and potential nitrification rate 116
Soil pH was measured using a glass electrode (soil:water, 1:2.5). Total organic C was 117
determined by dichromate oxidation and total nitrogen was determined by Kjeldahl digestion 118
and quantified using a continuous flow analyzer (Skalar, Delft, The Netherlands). Inorganic N 119
(NH4+-N and NO3
--N) was extracted with 2M KCl by shaking (1 h, 200 rpm) and filtering 120
through a 0.45-µm polysulfone membrane, before colorimetric determination using a 121
continuous flow analyzer. Nitrification potential was determined according to the shaken 122
slurry method of Hart et al. (22). Fifteen gram soil from each sample was pre-incubated at 123
room temperature for one week and then mixed with 100 ml of 1.5 mM ammonium sulfate. 124
After incubation for 2, 4, 22 and 24 h, 10-ml slurry samples were centrifuged and the 125
supernatant filtered through a 0.45-µm membrane. NO3-
content in the supernatant was 126
immediately analyzed, as described above for KCl-extracted NO3--N. NO3
- concentration 127
increased linearly and nitrification potential (NO3--N h
-1) was calculated from the rate of 128
increase in NO3- concentration over time in the slurry using linear regression. The method of 129
Hart et al. (22) involves adjustment of the slurry pH to 7.2 and potentially changes the 130
activity of indigenous communities, selected in soils of different pH. Potential nitrification 131
rates were therefore also measured at natural soil pH, without adjustment of pH. 132
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133
DNA extraction and quantitative PCR 134
DNA was extracted from approximately 500-mg soil samples using the FastDNA SPIN 135
kit for soil (Bio101, Vista, CA), as per the manufacturer’s instructions. Archaeal and 136
bacterial amoA abundance were determined by qPCR using an ABI 7500 Thermocycler 137
(Applied Biosystems, Foster City , CA) as described by Chen et al. (10). Bacterial amoA 138
genes were quantified using primers amoA-1F and amoA-2R (37). For crenarchaeal amoA, 139
qPCR was performed with primers CrenamoA23f and CrenamoA616r (33). DNA 140
concentration was determined by NanoDrop and each reaction was performed in a 25-µl 141
volume containing ~5 ng of DNA, 0.2 mg ml-1
BSA, 0.2 µM of each primer, 0.5 µl ROX 142
reference dye (50X), and 12.5 µl of SYBR Premix EX Taq (Takara Shuzo, Shiga, Japan). 143
Product specificity was confirmed by melt curve analysis (67-95°C) and visualization by 144
agarose gel electrophoresis. A known copy number of linearized plasmid of amoA gene clone 145
was used as a standard for AOA or AOB qPCR (10). For all assays, amplification efficiency 146
was 91-95% and r2 values were 0.97-0.99. 147
148
Terminal-restriction fragment length polymorphism (T-RFLP) 149
AOA T-RFLP profiles were obtained from two sets of FAM-labelled primers. For, the first 150
set of T-RFLP data, we used CrenamoA23f and CrenamoA616r (33) primers for PCR. The 151
second set of T-RFLP data for AOA was obtained from PCR-amplification using the amo111f 152
and amo643r (6). The first set of primers in combination with restriction enzyme (HpyCH4V) 153
used has comparatively low discriminatory ability for some phylotypes, while the second set 154
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of primers provides better discrimination between some phylotypes, although primer 111f 155
does exhibit more than one mismatch to a large proportion of currently known AOA amoA 156
sequences. For AOB analysis, the bacterial amoA partial gene fragment was PCR-amplified 157
using labelled primers amoA-1F and amoA-2R. The labelled PCR amplicons were checked 158
by agarose gel electrophoresis and purified using an UltraClean DNA purification kit (MoBio 159
labs, CA). The first AOA samples were digested with restriction enzyme HpyCH4V, and the 160
second AOA products were restricted using RsaI as this enzyme has been reported before to 161
provide better T-RFLP profiles (1). AOB PCR products were restricted with MspI (47). After 162
digestion, 2 µl of each sample was mixed with 0.3 µl of LIZ-labelled internal size standard 163
and 12 µl of formamide. Fragment size analysis was carried out with an ABI PRISM 3030xl 164
genetic analyzer (Applied Biosystems, Warrington, UK) (40). Fragment analysis of T-RFLP 165
data was performed between 35 and 640 bp. All T-RFs (terminal restriction fragments) with 166
fluorescence units <50 units and peaks with heights that were less than 2% of the total peak 167
height were excluded from further analysis to avoid potential noise before calculating relative 168
T-RF abundance (40). 169
170
Cloning and sequencing 171
DNA samples with different dominant T-RFs (terminal restriction fragments) were used for 172
cloning and sequencing analysis of AOA amoA sequences to assign phylogenetic affiliation to 173
specific T-RFs. To investigate potential niche specialization over broader pH ranges, DNA 174
extracted from each sample was pooled into three groups with soil pH in the ranges 3.5 - 4.4, 175
4.4 - 5.0, 5.0 - 6.8. In total, three AOA amoA clone libraries and one AOB amoA clone library 176
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were constructed. Clones were generated using a TOPO TA cloning kit (Invitrogen, Carlsbad, 177
CA) according to manufacturer’s instructions. A total of 120 AOA clones and 80 AOB clones 178
were sequenced using vector specific primers T3 and T7. AOA or AOB sequences (37 and 38 179
OTUs for AOA and AOB, respectively) were first used to construct a neighbor-joining tree 180
using Mega software (39). One representative from each OTU (<2% nucleotide dissimilarity) 181
was then used to construct the phylogenetic tree. Translated amoA gene sequences from this 182
study were aligned with reference sequences using ClustalW implemented in BioEdit (21). 183
Maximum likelihood and distance analyses were calculated using the Jones, Taylor and 184
Thornton (JTT) substitution model with site variation (invariable sites and four variable 185
gamma rates) using PHYML (20) and PHYLIP (16), and parsimony analysis calculated using 186
PHYLIP. All the sequences have been deposited in the Genbank database with accession 187
numbers GU396237-GU396254, FN869058-FN869114. 188
189
Statistical analysis 190
All ANOVA, regression and multivariate analyses were conducted using GenStat 12th
191
Edition (VSN International, Oxford, UK). Mean values and least significant differences at the 192
95% level were calculated by a one way ANOVA. The T-RFLP data were also analyzed using 193
canonical variate analysis. 194
195
Results 196
Soil pH and potential nitrification rate 197
Soil pH values ranged from 3.58 to 6.29 with highly significant differences between 198
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different soils (Table 1). The 50-year-old year tea orchards had the lowest pH, which may be 199
due to a combination of high N fertilizer application (usually in the form of urea) and 200
acidification by nitrification, plant growth and acidic phytochemical inputs. Lime application 201
caused a significant increase in soil pH, especially in the soils with low organic matter. 202
Potential nitrification rate was positively correlated with total nitrogen (r2=0.71, p<0.001), 203
organic C (r2=0.67, p<0.001) and N fertilizer application (r
2=0.27, p<0.001) and negatively 204
correlated with soil pH (r2=0.28, p<0.001). Measurement of potential nitrification without 205
adjusting pH produced similar results and trends, but process rates were reduced to 206
approximately 60-90% (Suppl. Table 1). 207
208
Quantitative PCR determination of amoA gene abundance 209
Abundances of putative AOA and AOB were assessed by quantifying their respective 210
amoA genes (Table 1). Archaeal amoA gene abundance ranged from 5.5 x 104 to 2.4 x 10
7 g
-1 211
soil and was lower in the pine soils than the tea orchard soils. Soil potential nitrification rate 212
increased with AOA gene abundance in all samples (p<0.001) and in the tea orchard soils 213
only (p=0.014), but there was no significant correlation between AOA abundance and soil pH 214
(p=0.071) (Suppl. Table 2). Bacterial amoA abundance was lower than that of archaea in all 215
soils. In one pine (Taihu) and two highly acidic tea orchard soils, bacterial amoA abundance 216
was below the detection limit (2.0 x 104 g
-1 soil). AOB abundance decreased significantly 217
with decreasing pH (p<0.001) but did not correlate with nitrification potential (p=0.255). 218
Interestingly, there was a sharp increase in the ratio of archaeal:bacterial amoA abundance 219
below pH 4 (Figure 1). 220
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221
T-RFLP analysis of AOA and AOB communities 222
T-RFLP data using CrenamoA23f and CrenamoA616r in combination with HpyCH4V 223
enzyme produced a total of 14 T-RFs in all samples and were used for all multivariate 224
statistical analysis. PCA analysis of the T-RFLP data showed that the scores of the first 225
component were significantly (p=0.001) correlated with soil pH. Canonical variate analysis, 226
using all 14 T-RFs, showed a significant difference between different lime treatments, but no 227
significant difference between N fertilizer applications (Figure 2). AOA T-RF166 had highest 228
relative abundance (on average 49%) in the tested soils and may include several sequence 229
types, as indicated by cloning and sequencing data (see below). AOA T-RF79 and T-RF205 230
had similar dominance (10-15%) in all soil samples within the pH range 5.4 - 5.8, irrespective 231
of site and land use type. T-RFLP profiles obtained from primer set Amo111f and amo643r in 232
combination with the RsaI enzyme produced 20 T-RFs in all the samples. T-RF 101 was the 233
major T-RF and had highest relative abundance (>50%) in the highly acidic tea soils with pH 234
lower than 4.4. Because the second set of primers has low specificity (occasionally 235
amplifying non-AOA sequences), they were used only for confirmation and identification of 236
T-RFs obtained using the first primer set and T-RFs originating from this set of primers were 237
hereafter identified by restriction enzyme used (RsaI) followed by T-RF size in base pair. 238
A total of 9 AOB T-RFs were obtained from soils and AOB T-RFs 60, 156, 256 had high 239
relative abundances of 43%, 33% and 13%, respectively. PCA of the T-RFLP data showed 240
that the scores of the first component were significantly (p=0.003) correlated with soil pH. 241
Canonical variate analysis showed a significant difference between limed and unlimed soils, 242
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but no significant difference between the low and high lime treatments (Figure 3). There was 243
also a significant difference between the highly fertilized soils (900 kg N ha-1
y-1
) and other 244
less fertilized samples (Figure 3). 245
246
Analysis of AOA and AOB amoA sequences 247
All major AOA and AOB amoA T-RFs were characterized by cloning and sequencing. 248
Finally, 14 representative AOA sequences and 11 AOB sequences were selected for detailed 249
analysis and the construction of phylogenetic trees. AOA were also classified using two sets 250
of T-RFLP data and exactly the same 14 representative AOA sequences were obtained (Table 251
2). The size of T-RF in Table 2 was determined by computation analysis and was close to that 252
determined experimentally. 253
Clones of AOA T-RF 166 (Rsa473) were quite different from the other T-RF166 clones 254
(Rsa101,187, 203,293, 554) in the phylogenetic tree (Figure 4). All sequences belonging to 255
AOA T-RF49 and T-RF79 fell within the soil/sediment cluster. However, the clones of AOA 256
T-RFs 217, 205 were distributed into 2 and 3 subclusters, respectively. Most AOA T-RF217 257
clones belonged to T-RF217 (Rsa244) and fell within the soil/sediment cluster (Table 2). 258
According to the nomenclature of Avrahami and colleagues (3, 4), 78 AOB clones were 259
related to the genus Nitrosospira and 2 clones of T-RF264 belonged to Nitrosomonas (Suppl. 260
Figure 1), indicating a predominance of Nitrosospira over Nitrosomonas in soils. 261
262
Environmental niches for different phylotypes within each ammonia oxidizing community 263
Relationships between specific sequence types and environmental factors were 264
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investigated to assess potential niche adaptation. The relative abundance of AOA T-RF166 265
was negatively correlated with soil pH (r2=-0.28, p<0.001), but 4 samples (including pine 266
forest and tea orchard) from the Taihu site had high relative abundance at pH 5.5-6.0 (Fig. 5). 267
T-RFLP analysis with a second set of primers with enzyme RsaI and sequencing data suggest 268
that T-RF166 represents several phylotypes, and T-RF166 (Rsa101) was found only in the 269
highly acidic soils (pH<4.4), while T-RF166 (Rsa473) dominated only in soils with pH >5.0 270
(Table 2). An NCBI data search for sequences obtained for T-RF166 (Rsa101) suggests that 271
all related sequences (accession numbers FJ517358-517359, FJ517362-517367, FJ174702, 272
EF207215) (24, 55) were obtained from highly acidic environments (pH 3.7-4.3) irrespective 273
of land use type. 274
AOA T-RF79 had a wide pH range and its relative abundance was not correlated with soil 275
pH (Suppl. Figure 2). However, the relative abundances of AOA T-RF49, T-RF205 and 276
T-RF217 were positively correlated with soil pH and these T-RFs were generally found only 277
in soils with pH >4.4 (Suppl. Figure 2). Sequencing data indicated that T-RF217 (Rsa244) 278
was only present in the clone library of pH 5.0-6.8 and had high similarity (99%) with 279
sequences deposited in NCBI (accession number EF207213, EU315714, FJ853234, 280
FJ601563) (24, 41, 56) which were also isolated from environments with pH>5.0. AOA 281
T-RF205 had high relative abundance in soils with low potential nitrification rate, and was 282
generally absent from soils with nitrification potential >0.5 mg NO3--N g
-1 h
-1 (Figure 6). 283
AOB T-RF 156 had a wide pH range (pH>4) and its relative abundance was positively 284
correlated with soil pH (Suppl. Figure 3). The average AOB T-RF256 relative abundance was 285
less than that for T-RF156. The peak had a wide pH range (pH>3.8) and relative abundance 286
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was negatively correlated with soil pH (Suppl. Figure 3). 287
The relative abundances of several T-RFs were significantly (p<0.05) correlated with N 288
fertilizer application. For example, the relative abundances of AOA T-RF49 decreased and 289
AOA T-RF166 increased, respectively, with increasing fertilizer input (Suppl. Figure 4). AOB 290
T-RF256 was not detected in soil with low fertilizer input, and the relative abundance of AOB 291
T-RF156 was negatively correlated with fertilizer input (Suppl. Figure 5). 292
293
Discussion 294
Abundance and activity of ammonia oxidizers 295
Archaeal and bacterial amoA abundances were much higher in the tea orchards than in 296
adjacent pine soils and correlated with potential nitrification rates. This may be explained by 297
the fact that the tea orchards have been fertilized over long periods while the pine forest soils 298
have never received any fertilizer treatment. Nitrogen input may therefore influence 299
abundance, but only two pine sites were investigated. Previous studies (15) showed that N 300
fertilizer application stimulates soil nitrification and ammonia oxidizer abundance. Moreover, 301
the differences in litter quality and quantity may account for differences in the nitrification 302
rate and ammonia-oxidizer abundance, since vegetation type was considered an important 303
factor in determining the activity and abundance of nitrifiers (39, 50, 52). 304
AOB abundance decreased significantly with decreasing pH, indicating that pH was an 305
important factor controlling AOB abundance in the soil and consistency with other reports of 306
higher AOB abundance in neutral or slightly alkaline conditions (33, 39). However, no 307
significant correlation was observed between AOA abundance and pH in this study. AOA 308
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were present over a wider pH range with some populations adapted to highly acidic soils. 309
AOA were generally more abundant than AOB and the ratio of AOA:AOB amoA gene 310
abundance increased with decreasing soil pH. This suggests that AOA were the dominant 311
ammonia oxidisers in acid soils (33). The trends in specific gene abundance may reflect 312
different preferences of archaeal and bacterial ammonia oxidizers for available ammonia 313
concentration or other differences in physiology and metabolism. Available ammonia 314
concentration decreases with decreasing pH due to ionization of ammonium and this is 315
believed to the major reason for reduced activity of ammonia oxidation at low pH (12). 316
Although effects of pH and ammonia concentration were not distinguished in this study, 317
pH-associated differences may have resulted from other differences in physiology and 318
metabolism. Measurement of potential nitrification with natural pH produced similar trends, 319
but lower rates compared to the neutral pH. The results suggest that AOA may perform 320
nitrification at low pH as well as at neutral pH. 321
322
AOA and AOB community structure 323
Ammonia-oxidizing archaeal and bacterial community composition determined by 324
T-RFLP analysis varied with liming and correlated with soil pH, suggesting that soil pH is a 325
key factor controlling the community composition. Nicol et al (33) also found effects of soil 326
pH on AOA and AOB communities. Nitrogen fertilizer is also believed to influence AOA and 327
AOB community composition (14, 24, 30, 32, 47, 48). In this study, AOB community 328
composition was influenced by high input of N fertilizer (900 kg N ha-1
y-1
). AOB amoA 329
genes were not detected in the highest N application treatments (1500 kg N ha-1
y-1
) but 330
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fertilizer treatment did not affect AOA T-RFLP patterns. Consequently, data suggest that the 331
effect of N fertilizer on ammonia oxidizer community composition was smaller than the soil 332
pH effect. Moreover, the changes in AOB community composition caused by N fertilizer 333
input may also be partly due to a decrease in soil pH through continued nitrification. 334
335
Relative importance of AOA and AOB in highly acidic soils 336
Regression analysis showed a significant positive relationship between nitrification 337
potential and archaeal, but not bacterial amoA abundance, suggesting that nitrification is 338
driven by AOA in acidic soils. AOB amoA gene abundance was below detection limits in the 339
heavily N-fertilized (1500 kg N ha-1
y-1
) and low pH tea soils, but nitrification potential and 340
AOA abundance were high. The relative role of AOA and AOB has been debated since 341
Leininger et al. (29) first reported the dominance of AOA in soil (36). Furthermore, Chen et 342
al (10) suggested that AOA are dominant in the rhizosphere in paddy soils and were 343
influenced more by exudation from rice roots. However, AOA abundance and activity did not 344
increase with N fertilizer input and AOB and not AOA contributed to nitrification in 345
grassland soils receiving high nitrogen inputs (15). Distinctions may be due to different land 346
use and environmental conditions. Evolutionary considerations suggest that archaea can grow 347
under conditions of extreme salinity, temperature and pH, and low ammonia availability (18, 348
31), which do not support growth of bacteria and eukaryotes (46). Therefore, it is possible 349
that AOA lack the competitive advantage in some grassland soils, but can adapt and flourish 350
under highly acidic soils. Low pH may explain the higher relative abundance of AOA 351
compared to AOB in tea orchards. 352
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353
Niche differentiation and potential activity of ammonia oxidizer phylotypes 354
Soil pH is clearly a major factor influencing niche separation of AOA and AOB. The 355
relative abundances of several AOA and AOB T-RFs (e.g., AOA T-RFs 49, 217(Rsa244) and 356
AOB T-RF256,) correlated with soil pH and were dominant in specific pH ranges. N fertilizer 357
input also influenced relative abundance, but this may be a secondary effect due to reduction 358
in soil pH due to increased levels of nitrification. For example, the relative abundances of 359
AOB T-RFs 60, 256 and AOB T-RF 156 increased and decreased, respectively, with 360
increasing N fertilizer input. Soil pH has previously been shown to be a major driver of AOB 361
(43) and AOA (33) community structure and that of bacteria (17), and contrasts with the 362
suggestion (25) that amoA genes may be too conserved to reflect ecological differences. 363
T-RFLP and sequence analyses suggest that T-RF166 (Rsa101), represented by amoA 364
gene sequence (GU396241), dominates highly acidic tea orchard soils with pH<4.4. These 365
soils had very high AOA:AOB amoA gene ratios (>15) and high nitrification potential. 366
Consequently, the dominant representative AOA phylotype in these highly acidic soils may 367
have high activity and play an important role in nitrification. The negative relationship 368
between the abundance of AOA T-RF205 and nitrification potential also suggest that this 369
phylotype may have low activity in Chinese soils. 370
The relative contributions of AOA and AOB to soil nitrification remain a topic of debate (36). 371
Here we have provided evidence that AOA dominate the ammonia oxidiser community in 372
acidic soils and, along with potential nitrification data, results suggest that AOA may be 373
responsible for most of the nitrification in these highly acidic environments. The study 374
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demonstrates that different ammonia oxidiser phylotypes occupy distinct pH niches, which in 375
turn provides new insight into relative dominance of AOA and AOB and niche differentiation 376
of individual phylotypes in natural environments. 377
378
Acknowledgements 379
This work was financially supported by the Royal Society of Edinburgh, and the National 380
Science Foundation of China (No. 30871600, 40771113). CDC and BS are funded by the 381
Scottish Government, Rural and Environment Research and Analysis Directorate. GWN is 382
funded by a NERC Advanced Fellowship (NE/D010195/1). Nadine Thomas, Lucinda 383
Robinson, Duncan White, Clare Cameron and Cecile Gubry-Rangin are gratefully 384
acknowledged for technical assistance and advice. 385
386
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Table 1. Land use history, chemical properties and abundance of AOA and AOB amoA genes 545
g-1
soil (dry weight) in tea and pine soils. 546
Soil
No
Land use
Site
NFI*
Lime*
pH
H2O
Org
C
%
TN
%
PNR*
amoA genes x 105 g
-1
soil
AOB AOA
1 Tea-3yr HZ* 900 0 5.25 1.62 0.18 0.20 8.6 58.0
2 Tea-7yr HZ 900 0 4.12 1.30 0.13 0.21 4.9 110
3 Tea-8yr HZ 900 0 4.31 3.16 0.26 0.72 9.3 200
4 Tea-10yr HZ 900 0 4.39 1.70 0.18 0.51 7.0 97.0
5 Tea-16yr HZ 900 0 4.46 4.02 0.37 0.89 14.0 140
6 Tea-20yr HZ 900 0 3.92 2.30 0.24 0.29 0.67 160
7 Tea-40yr HZ 900 0 3.99 4.62 0.45 0.90 3.1 210
8 Tea-45yr HZ 1500 0 3.88 3.84 0.40 1.09 BDL* 180
9 Tea-50yr HZ 1500 0 3.58 6.41 0.54 1.03 BDL 210
10 Tea-60yr HZ 900 0 3.81 4.17 0.37 0.73 2.0 100
11 Tea-90yr HZ 900 0 4.16 9.19 0.71 1.32 4.4 93.0
12 Tea-4yr HZ 450 0 5.01 1.38 0.15 0.22 29.0 160
13 Tea-4yr HZ 450 1000 5.39 1.35 0.14 0.33 27.0 180
14 Tea-4yr HZ 450 4000 6.29 1.35 0.13 0.41 43.0 130
15 Tea-5yr HZ 450 0 4.46 4.23 0.45 0.59 15.0 160
16 Tea-5yr HZ 450 1000 4.63 4.31 0.47 0.75 28.0 240
17 Tea-5yr HZ 450 4000 5.03 3.99 0.41 0.97 44.0 240
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18 Pine-50yr HZ 0 0 4.61 2.76 0.18 0.06 0.26 0.55
19 Tea-10yr TH* 50 0 5.54 1.18 0.13 0.16 7.1 52.0
20 Tea-39yr TH 200 0 5.51 1.46 0.13 0.40 4.2 130
21 Pine-30yr TH 0 0 5.86 1.10 0.08 0.04 BDL 12.0
LSD0.05 0.14 0.34 0.03 0.05 1.7 11.0
*NFI = N fertilizer input (kg N h-1
y-1
); Lime = lime Input (kg CaCO3 h-1
y-1
); Org C= soil organic 547
carbon; TN = total N; PNR= potential nitrification rate (mg NO3--N g
-1 h
-1); HZ=Hangzhou, 548
TH=Taihu; BDL = Below detection limit. The values in this Table are the average of the 549
measurement from triplicate soil samples. 550
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Table 2. Representative AOA amoA gene sequences and their T-RF groups. 551
552
T-RF
Code
T-RF generated from
primer (23f :616r)
(HpyCh4V enzyme)
T-RF generated from
primer (111f :643r)
(RsaI enzyme)
Accession
number
pH range Number of
clones
TRF49(Rsa203) TRF49 TRF203 FN869067 4.4-6.8 6
TRF79(Rsa108) TRF79 TRF108 GU396238 3.5-6.8 8
TRF79(Rsa291) TRF79 TRF291 GU396249 3.5-6.8 7
TRF166(Rsa101) TRF166 TRF101 GU396241 3.5-4.4 38
TRF166(Rsa187) TRF166 TRF187 FN869065 3.5-5.0 6
TRF166(Rsa203) TRF166 TRF203 GU396244 4.4-6.8 4
TRF166(Rsa293) TRF166 TRF293 GU396253 4.4-6.8 7
TRF166(Rsa473) TRF166 TRF473 FN869072 5.0-6.8 8
TRF166(Rsa554) TRF166 TRF554 FN869068 4.4-6.8 3
TRF205(Rsa79) TRF205 TRF79 GU396237 4.4-6.8 2
TRF205(Rsa101) TRF205 TRF101 GU396248 4.4-6.8 8
TRF205(Rsa187) TRF205 TRF187 FN869061 4.4-6.8 5
TRF217(Rsa203) TRF217 TRF203 FN869059 4.4-6.8 1
TRF217(Rsa244) TRF217 TRF244 FN869058 5.0-6.8 17
553
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Figure Legends 554
Fig. 1. The relationship between soil pH and the ratio of archaeal:bacterial amoA genes in tea 555
orchards. 556
( 557
Fig. 2. Plot of ordination of canonical variates (CV1 against CV2) generated by canonical 558
variate analysis of archaeal amoA T-RFLP profiles. Each circle represents 95% confidence 559
level and indicates AOA communities that are separated with statistical significance (p<0.05). 560
561
Fig. 3. Ordination plot of canonical variates (CV1 against CV2) generated by canonical 562
variate analysis of bacterial amoA T-RFLP profiles. Each circle represents 95% confidence 563
level and indicate AOB communities that are separated with statistical significance (p<0.05). 564
565
Fig. 4. Maximum likelihood (ML) phylogenetic analysis of derived amino acid sequences 566
(158 aligned positions) from cloned archaeal amoA gene sequences from tea soils. Sequences 567
from this study are presented in bold and are described as ‘clone name (accession number) 568
RsaI T-RF size (HpyCh4V T-RF size)’. Reference sequences are described as ‘clone name 569
(environment, accession number)’. Bootstrap support for major clades represent the most 570
conservative value from ML, distance and parsimony analyses (100, 1000 and 1000 replicates 571
respectively). 572
573
Fig. 5 The relationship between soil pH and the relative abundance of archaeal ammonia 574
oxidizer T-RF166. Sequencing data and T-RFLP patterns obtained from the second set of 575
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primer suggested that this T-RF consists of more than one OTU. For example, the phylotypes 576
represented by triangles comprise mainly T-RF166 (Rsa101), while phylotype represented by 577
squares comprise mainly T-RF166 (Rsa473). 578
579
Fig. 6 The relationship between nitrification potential and relative abundance of archaeal 580
ammonia oxidizer T-RF205 of ammonia-oxidizing archaea. 581
582
583
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