Literature DB >> 31568679

Effects of applying inorganic fertilizer and organic manure for 35 years on the structure and diversity of ammonia-oxidizing archaea communities in a Chinese Mollisols field.

Jianli Ding1,2, Mingchao Ma2, Xin Jiang2, Yao Liu3, Junzheng Zhang4, Linna Suo1, Lei Wang1, Dan Wei1, Jun Li2.   

Abstract

In this study, we investigated the physicochemical properties of soil, n class="Chemical">and the diversity n class="Chemical">and structure of the soil an class="Chemical">ammonia-oxidizing archaea (AOA) community, when subjected to fertilizer treatments for over 35 years. We collected soil samples from a black soil fertilization trial in northeast China. Four treatments were tested: no fertilization (CK); manure (M); npan>n> class="Chemical">nitrogen (N), phosphorus (P), and potassium (K) chemical fertilizer (NPK); and N, P, and K plus M (MNPK). We employed 454 high-throughput pyrosequencing to measure the response of the soil AOA community to the long-term fertilization. The fertilization treatments had different impacts on the shifts in the soil properties and AOA community. The utilization of manure alleviated soil acidification and enhanced the soybean yield. The soil AOA abundance was increased greatly by inorganic and organic fertilizers. In addition, the community Chao1 and ACE were highest in the MNPK treatment. In terms of the AOA community composition, Thaumarchaeota and Crenarchaeota were the main AOA phyla in all samples. Compared with CK and M, the abundances of Thaumarchaeota were remarkably lower in the MNPK and NPK treatments. There were distinct shifts in the compositions of the AOA operational taxonomic units (OTUs) under different fertilization management practices. OTU51 was the dominant OTU in all treatments, except for NPK. OTU79 and OTU11 were relatively abundant OTUs in NPK. Only Nitrososphaera AOA were tracked from the black soil. Redundancy analysis indicated that the soil pH and soil available P were the two main factors that affected the AOA community structure. The abundances of AOA were positively correlated with the total N and available P concentrations, and negatively correlated with the soil pH.
© 2019 The Authors. MicrobiologyOpen published by John Wiley & Sons Ltd.

Entities:  

Keywords:  amoA gene; black soil; long-term fertilization; pyrosequencing; qPCR

Mesh:

Substances:

Year:  2019        PMID: 31568679      PMCID: PMC6957403          DOI: 10.1002/mbo3.942

Source DB:  PubMed          Journal:  Microbiologyopen        ISSN: 2045-8827            Impact factor:   3.139


INTRODUCTION

Black soil, also known as Mollisols, is a unique soil with excellent characteristics and high fertility, which is well n class="Chemical">suited to plant growth. Black soil is found in four main areas throughout the world, one of which is located in northeast China. This area covers approximately 1.03 million square kilometers, and it produces about 225–250 billion kilograms of commercial grain each year. It is China's largest commercial grain production base. However, long‐term continuous cropping and unreasonable farming practices (such as long‐term excessive and unreasonable fertilizer application) have led to the degradation of the black soil farmland (Zhou et al., 2016) and have affected the various microorganisms related to the an class="Chemical">nitrogen (N) cycle process in black soil (Yin et al., 2015). n class="Chemical">Ammonia oxidization is a key step in the soil N cycle and is the primary and limiting stage in nitrification (Kowalchuk & Stephen, 2001). In recent decades, many studies have suggested that ammonia‐oxidizing bacteria (AOB) are the dominating participants in ammonia oxidation. However, this view changed after the identification of ammonia‐oxidizing archaea (AOA) (Gao, Chang, et al., 2018c; Leininger et al., 2006; Li, Chapman, Nicol, & Yao, 2018). Thus, research into the roles of AOA and AOB in the ammonia oxidization process has intensified (Hou, Cao, Song, & Zhou, 2013; Wang, Wang, Feng, Zhai, & Zhu, 2011). A common method for determining the abundance and diversity of AOA and AOB in soil samples involves the extraction of DNA. Ammonia monooxygenase is the key enzyme that catalyzes the first reaction in ammonia oxidization. The amoA gene encodes the alpha subunit of ammonia monooxygenase (Kowalchuk & Stephen, 2001). Thus, the amoA gene has been employed widely as a molecular biomarker to measure the AOA and AOB composition and diversity (Junier et al., 2010). In ocen class="Chemical">an, lake, and soil environments, the amoA gene copy numbers from AOA are tens or even thousands of times greater than those from AOB (Li, Weng, Huang, Su, & Yang, 2015). Studies have shown that AOA prefer areas with low an class="Chemical">ammonium concentrations, whereas AOB prefer areas with high n class="Chemical">ammonium concentrations (Gao, Liu, Li, Chen, & Liang, 2018a; Ouyang, Norton, & Stark, 2017). When AOA and AOB coexist in most agricultural soils, they differ in terms of their responses to environmental disturbances (i.e., niche specialization) and resource utilization (i.e., niche differentiation) (Gao, Chang, et al., 2018c; Ouyang, Norton, Stark, Reeve, & Habteselassie, 2016). AOA are suitable for a wider range of aerobic conditions according to some studies (Chen, Zhu, Xia, Shen, & He, 2008; Li et al., 2015). Indeed, the abundances of AOB are lower than those of AOA in many acidic soils (Zhang, Wang, Li, He, & Zhang, 2015a). Researchers have speculated that in some environments, such as acidic soils, the contribution of AOB to nitrification may be less than that of AOA (Lehtovirta‐Morley et al., 2014; Wang et al., 2015). Hence, it is very important to study the AOA community structure in soil that has undergone long‐term fertilizer treatment to further understand the nitrification process and its mechanism. Previous studies have n class="Chemical">suggested that the main differenpan>ces in AOA in terms of their abundance, activity, and community structures can be explained by the soil physicochemical properties and agricultural management strategies (Ciccolini, Bonari, Ercoli, & Pellegrino, 2016; Sun, an class="Chemical">Guo, Wang, & Chu, 2015; Wang et al., 2015). Long‐term fertilization in different soils affects the composition and abundance of AOA, such as in paddy soil (Gao, Cao, et al., 2018b; Gu et al., 2017). He et al. (2018) and Zhang, Wanpan>n>g, et al. (2015a), Zhapan class="Chemical">nn>g, Chen, Dai, Sun, and Wen (2015b) showed that the long‐term application of biochar could alter the composition and affect the abundance of n class="Chemical">ammonia oxidizers, especially in acid soils. The long‐term application of N fertilizer also dramatically increases the abundance of AOA in the soil according to the analysis of the amoA gene (Beeckman, Motte, & Beeckman, 2018; Ouyang, Evans, Friesen, & Tiemann, 2018). Under continuous maize cultivation for 23 years, Xue et al. (2016) showed that the fertilization regime can cause changes in the structure and composition of the archaea community in an experimental black soil, where chemical fertilizer had the greatest effect on the AOA composition, whereas the application of chemical fertilizer plus manure neutralized the changes in the community induced by the chemical fertilizer. Compared with an acidic red soil, black soil was acidified due to the long‐term application of chemical fertilizer (Zhou et al., 2015), and it had higher organic matter (OM) and ammonia nitrogen contents. These differences in the substrates for AOA are very important. In this study, we investigated the changes in the structure and diversity of AOA under long‐term treatment (more than 35 years), where four fertilizer treatments were tested: no fertilization (CK), manure (M), chemical fertilizer (NPK), and NPK plus M (MNPK). The soil AOA structure, diversity, and abundance were determined using marked sequencing and quantitative PCR (qPCR) of the archaeal amoA genes. Correlations among black soil properties and the AOA structure and diversity were analyzed.

MATERIALS AND METHODS

Soil sampling

The soil samples were collected from the trial site, located in Harbin, Heilongjiang Province, China (n class="Chemical">N 45°40′, E 126°35′), which is affiliated with Heilongjiang Academy of Sciences. This region has a mean annual temperature of 3.5°C and annual precipitation of 575 mm, with a typical monsoon climate. The site had a total area of 7,000 m2 and 96 plots (32 treatments with triplicates of each treatment). Plots were randomly arranged, and cement plates were inserted between the plots. The tillage practices comprised shallow plowing combined with subsoiling and an class="Disease">rotary tillage combined with subsoiling. The study site had been subjected to n class="Species">wheat–maizesoybean crop rotation since 1980, and the samples were collected in the 35th year of use (soybean was planted in this year). The experimental site was flat, and the soil properties were homogeneous. The basic soil physicochemical properties (1980) were as follows: OM 26.7 g/kg, total N (TN) 1.47 g/kg, total phosphorus (TP) 1.07 g/kg, available N 151.1 mg/kg, available phosphorus (AP) 51.0 mg/kg, available potassium (AK) 200 mg/kg, and pH 7.22 (Ding et al., 2016). Further details of this long‐term field experiment were reported by Wei et al. (2008). Four fertilization experimental treatments were tested comprising no fertilization (CK); manure (M); N (urea used as N), P, and K chemical fertilizer (NPK); and N, P, and K plus M (MNPK). The doses of chemical fertilizers were 150 kg N/ha, 75 kg P2O5/ha, and 75 kg K2O/ha for the wheat and maize plots, and 75 kg N/ha, 150 kg P2O5/ha, and 75 kg K2O/ha for the soybean plots. The dose of horse manure as an organic amendment was approximately 18,600 kg manure/ha. The nutrient contents of the horse manure determined as averages in a calendar year were 0.56%, 0.63%, and 0.89% for N, P2O5, and K2O, respectively. When the soybean was harvested in September 2014, we selected three plots from each of the four fertilization treatments (total of 12 plots) to collect soil samples. We collected soil from a depth of 5–25 cm at 10 points (plow layer) and mixed them together to obtain a soil sample for the plot. Samples were stored in n class="Chemical">an icebox and returned to the laboratory for examination. Each sample was separated into two parts, where one was stored at –80℃ for biological analysis and the other was employed for physical and chemical analyses. The soil an class="Chemical">nitrate nitrogen (NN) and n class="Chemical">ammonium nitrogen (AN) contents were measured using the fresh soil samples. Other soil properties were analyzed after drying the samples at room temperature and passing through a 2.0‐mm mesh.

Soil properties and soybean yield

The soil pH, n class="Chemical">NN, n class="Chemical">AN, AP, AK, OM, and TN were determined using the methods described by Ding et al. (2017). Briefly, the soil pH was measured with a pH meter using a 1:1 sample:water extract. Inorganic N (NN and AN) was determined by flow injection analysis. Soil TN was measured with the micro‐Kjeldahl method. Soil AP was analyzed using the Mo‐Sb colorimetric method. The soil AK was determined by flame photometry. Soil OM was measured using the K2an class="Species">Cr2O7‐capacitance method. The n class="Species">soybean yield was estimated after harvesting soybeans from 10 m2 of the central area of the plot. After threshing and drying, the dry weight was determined for the soybeans harvested from the sampling area in order to calculate the soybean yield per plot.

DNA extraction and qPCR analysis

We extracted the soil total community DNA (TC DNA) with a Power Soil DNA Isolation Kit (MOBIO Laboratories Inc., Carlsbad, CA, USA) according to the manufacturer's instructions, except the additional incubation step at 65℃ was increased by 10 min (Fierer et al., 2012). In order to obtain the whole community DNA for the subsequent analyses, each soil sample was extracted to obtain six replicates and these replicates were then mixed. The DNA quality and concentration (A260/A280) were estimated using a NanoDrop ND‐1000 UV‐Vis Spectrophotometer (Thermo Scientific, Rockwood, TN, USA). Each TC DNA sample was stored at –80°C until further analyses. The primers comprising Arch‐amoAF (5′‐STAATGGTCTGGCTTAGACG‐3′) and Arch‐amoAR (5′‐GCGGCCATCCATCTGTATGT‐3′) were used for amplifying the archaeal amoA genpan>e (Gn class="Chemical">an et al., 2016). The plasmids were prepared as described by Ding et al. (2016). Quantitative analysis of the archaeal amoA gene was conducted with an ABI 7,500 Real‐Time PCR Detection System (Applied Biosystems, Waltham, MA, USA). The reaction mixture (20 μL) comprised 2 × FastFire qPCR PreMix (FastFire qPCR PreMix, Tiangen Biotech, China), 1 × ROX Reference Dye, 1 ml of 1/10 diluted DNA, and 10 nM of each primer. The optimum amplification conditions were as follows: initial denaturation at 95℃ for 60 s, 40 cycles of denaturation at 95℃ for 5 s and annealing at 60℃ for 32 s, and melting curve analysis. A plasmid containing the archaeal amoA gene was 10‐fold serially diluted to generate the standard curve.

454 high‐throughput pyrosequencing and bioinformatics analyses

We performed 454 high‐throughput pyrosequencing as described by Zhn class="Chemical">ang, Chenpan>, et al. (2015b). The primers were the same as those used for qPCR. Briefly, the AOA amoA genpan>es with barcoded primers were amplified in triplicate with n class="Chemical">an ABI 9,700 thermocycler (ABI, Foster City, CA, USA). The PCR amplification cycle comprised the following: 120 s at 95℃, followed by 35 cycles of denaturation at 95℃ for 30 s, annealing at 55℃ for 30 s, and extension at 72℃ for 30 s, with a final elongation step for 300 s at 72℃. The mixture of triplicate PCR products was verified by 1% agarose gel electrophoresis and then purified using an AxyPrep DNA Gel Extraction Kit (Axygen, Union City, CA, USA). Finally, the purified PCR products were used to generate the amplicon libraries. The DNA library was sequenced with a Roche GS‐FLX Titanium Sequencer (Roche Diagnostics Corporation, Branford, CT, USA). The pyrosequencing data were deposited in the NCBI Short Reads Archive Database (SRA accession: PRJNA512072). The pyrosequencing data were n class="Chemical">analyzed with the QIIME pipeline versionpan> 1.8.0 (Caporaso et al., 2010). We excn class="Chemical">luded low‐quality reads in an initial quality filtering step. First, the reads with ambian class="Chemical">guous bases > 0 and average sequence quality < 25 were removed. The lowest sample number after rarefaction was 11,517. The average length of the valid sequences used for alignment was 418 bp. Chimeric sequences were then identified using UCHIME (Edgar, 2010). Operational taxonomic units (OTUs) were defined by clustering at 97% similarity. The rarefaction and diversity indices were calculated after clustering the OTUs. The OTUs were taxonomically classified based on the Fungene reference database (Release 7.3 http://fungene.cme.msu.edu/) (Wanpan>n>g, Garrity, Tiedje, & Cole, 2007), ann>d the confidence level was set at 80%. The α‐diversity of AOA was calculated using mothur (Schan class="Disease">loss, Gevers, & Westcott, 2011) (1.31.2, http://www.mothur.org/) and with the following four parameters: Shannon and Simpson diversity indices, and Chao1 and the abundance‐based coverage estimator (ACE) as an class="Disease">richness indices. Phylogenetic trees were constructed using MEGA 6.0 with the neighbor‐joining method.

Statistical analysis

Significn class="Chemical">ant differenpan>ces inpan> the abunpan>dpan> class="Chemical">ances of AOA were detected by an class="Chemical">ANOVA. The relationships between the soil properties and the relative abundances anpan>pan>>d diversity indices for AOA were tested based on Pearson's correlation coefficients (Ramirez, Craine, & Fierer, 2012). Data ann>alyses were conducted with SPSS version 19.0 (IBM Inc., USA). Interactions between the AOA community and environmental factors were detected using CANOCO 5.0 (Microcomputer Power, Ithaca, NY) for redundancy analysis.

RESULTS

Compared with the CK treatment, the AP, Tn class="Chemical">N, and NN contents all increased uniformly in the fertilization treatments (Table 1). The OM concentrations in M and MNPK were higher than CK. The pH was lowest in the NPK treatment. The soil AP contents differed significantly in the four treatments, for example, 103.1 and 94.59 mg/kg in MNPK and NPK, respectively. Furthermore, fertilization improved an class="Species">soybean production, where the n class="Species">soybean production with MNPK (2,421.73 kg/ha) was greater than that under NPK (2,283.67 kg/ha) (Figure 1). Soybeans can fix N biologically, but inorganic N fertilization decreased biological N fixation by soybeans (Ding et al., 2016). Thus, the yield was highest with M, followed by MNPK and then NPK.
Table 1

General physicochemical properties of soils (mean ± standard deviation*) for each treatment

VariableCKMMNPKNPK
AP(mg/kg)2.89 ± (0.90)a 13.86 ± (0.98)a 103.1 ± (20.48)b 94.59 ± (7.01)b
AK(mg/kg)157.17 ± (29.27)a 190.2 ± (1.48)a 171.78 ± (9.30)a 166.88 ± (15.02)a
NN(mg/kg)2.36 ± (1.02)a 4.44a ± (0.62)b 6.84 ± (0.63)c 4.72 ± (1.12)bc
AN(mg/kg)34.85 ± (0.57)a 37.47 ± (6.41)a 41.27 ± (4.82)a 35.80 ± (7.46)a
OM(g/kg)24.46 ± (0.25)a 27.67 ± (0.12)c 25.65 ± (0.31)b 24.92 ± (0.32)a
TN(g/kg)1.18 ± (0.02)a 1.23 ± (0.06)ab 1.36 ± (0.11)ab 1.42 ± (0.08)b
pH(1:1 H2O)6.48 ± (0.06)c 6.59 ± (0.05)c 5.88 ± (0.16)b 5.53 ± (0.03)a

Abbreviations: AP, available phosphorus; AK, available potassium; NN, nitrate nitrogen; AN, ammonium nitrogen; OM, organic matter; TN, total nitrogen; CK, no fertilizer; M, manure only; NPK, inorganic fertilizer; MNPK, inorganic fertilizer with manure.

Values followed by different letters are significantly different (p < .05) according to Tukey's multiple comparison test.

Figure 1

Soybean yield with each treatment. CK, no fertilizer; M, manure only; NPK, inorganic fertilizer; MNPK, inorganic fertilizer with manure

General physicochemical properties of soils (men class="Chemical">an ± stpan> class="Chemical">andard deviation*) for each treatment Abbreviations: AP, available n class="Chemical">an class="Chemical">phosphoruspan>>; AK, available pan class="Chemical">nn> class="Chemical">potassium; NN, pan> class="Chemical">nitrate nitrogen; AN, ammonium nitrogen; OM, organic matter; TN, total nitrogen; CK, no fertilizer; M, manure only; NPK, inorganic fertilizer; MNPK, inorganic fertilizer with manure. Van class="Chemical">lues followed by differenpan>t letters are signpan>ificpan> class="Chemical">antly different (p < .05) according to Tukey's multiple comparison test. an class="Species">Soybeanpan>pan>> yield with each treatment. CK, no fertilizer; M, manure only; NPK, inorganic fertilizer; MNPK, inorganic fertilizer with manure

Copy numbers of amoA gene

The long‐term fertilization regimes affected the sizes of the AOA communities based on the AOA amoA gene copy numbers. The amoA gene copy numbers in the treatments rn class="Chemical">anged from 2.36 × 105 to 3.43 × 106 genpan>e copies per ng Dn class="Chemical">NA (Figure 2). The amoA gene copy numbers did not differ significantly in CK and M (p < .05), but they were lower in MNPK than NPK (p < .05). Moreover, Pearson's correlation coefficients between the soil properties and AOA amoA gene copy numbers (Table 3) showed that the AOA amoA gene copy numbers were positively correlated with the soil TN (r = 0.691, p < .05) and AP concentrations (r = 0.799, p < .01), but negatively correlated with the soil pH (r = –0.792, p < .01).
Figure 2

AOA amoA gene copy numbers detected by qPCR in soil samples from different fertilization treatments. CK, no fertilizer; M, manure only; NPK, inorganic fertilizer; MNPK, inorganic fertilizer with manure

Table 3

Pearson's correlation coefficients between diversity indices, AOA sequence copy numbers, and soil properties

 APAKNNANpHOMTN
ACE0.580* −0.020.765** 0.319−0.2820.1170.321
Chao10.510.0390.730** 0.247−0.2470.1580.31
Shannon0.650* 0.0720.868** 0.411−0.3930.3040.496
Simpson−0.667* −0.071−0.846** −0.3840.471−0.301−0.548
AOA gene copy numbers0.799** −0.3280.4990.211−0.792** −0.3450.691*

Abbreviations: AP, available phosphorus; AK, available potassium; NN, nitrate nitrogen; AN, ammonium nitrogen; OM, organic matter; TN, total nitrogen.

Correlation is significant at p < .05.

Correlation is significant at p < .01.

AOA amoA gene copy numbers detected by qPCR in soil samples from different fertilization treatments. CK, no fertilizer; M, manure onpan>ly; n class="Chemical">NPK, inorganic fertilizer; MNPK, inorganic fertilizer with manure

AOA community diversity

The community characteristics were determined by 454 high‐throughput pyrosequencing based on the AOA amoA gene. The coverage, diversity, n class="Chemical">and n class="Chemical">an class="Disease">richness indices obtained for the AOA amoA gene are shown in Table 2. The coverage exceeded 99% in all of the treatments, ann>d 153 OTUs were detected. The order of abundann>ce in the treatments for the detected OTUs was as follows: MNPK > NPK > M > CK, which was consistent with the diversity of the sequences based on the community diversity indices and n class="Disease">richness indices. Moreover, the community Chao1 and ACE indices were higher in MNPK (133.33 and 136.0, respectively) than those in the NPK treatment (115.0 and 115.33, respectively). Furthermore, the community Shannon index value was higher in MNPK (2.73) compared with the NPK treatment (2.55). There were clear significant differences (p < .05) between the fertilizer regimes (Table 2). In addition, the relationships between the α‐diversity and the soil properties are shown in Table 3. The Simpson index values were negatively correlated with the soil NN (r = –0.846, p < .01) and AP (r = –0.667, p < .05). The Shannon, ACE, and Chao1 indices were positively correlated with NN.
Table 2

Diversity indices, coverage, and OTUs (mean ± standard deviation*) in soils with each treatment

VariableCKMMNPKNPK
ACE98.67 ± (4.62)a 111 ± (6.93)ab 136.0 ± (3.61)c 115.33 ± (6.93)b
Chao198.33 ± (7.57)a 112.33 ± (9.87)a 133.33 ± (4.16)b 115.0 ± (6.0)ab
Shannon2.28 ± (0.11)a 2.52 ± (0.01)b 2.73 ± (0.01)c 2.55 ± (0.02)b
Simpson0.25 ± (0.03)b 0.2 ± (0.0)a 0.16 ± (0.0)a 0.18 ± (0.0)a
Coverage0.99900.99860.99870.9986
OTU92 ± (3)a 99 ± (3)ab 115 ± (3)c 106 ± (4)b

Abbreviations: CK, no fertilizer; M, manure only; NPK, inorganic fertilizer; MNPK, inorganic fertilizer with manure.

Values followed by different letters are significantly different (p < 0.05) according to Tukey's multiple comparisons test.

Diversity indices, coverage, n class="Chemical">and OTUs (mepan> class="Chemical">an ± standard deviation*) in soils with each treatment Abbreviations: CK, no fertilizer; M, mn class="Chemical">anure onpan>ly; pan> class="Chemical">NPK, inorganic fertilizer; MNPK, inorganic fertilizer with manure. Van class="Chemical">lues followed by differenpan>t letters are signpan>ificpan> class="Chemical">antly different (p < 0.05) according to Tukey's multiple comparisons test. Pearson's correlation coefficients between diversity indices, AOA sequence copy numbers, n class="Chemical">and soil properties Abbreviations: AP, available n class="Chemical">an class="Chemical">phosphoruspan>>; AK, available pan class="Chemical">nn> class="Chemical">potassium; NN, pan> class="Chemical">nitrate nitrogen; AN, ammonium nitrogen; OM, organic matter; TN, total nitrogen. Correlation is significn class="Chemical">ant at p < .05. Correlation is significn class="Chemical">ant at p < .01.

AOA composition and phylogenetic analysis

According to the shared and unique OTUs, the AOA communities in the four fertilizer regimes were compared using the Ven class="Chemical">nn diagrams. In total, 153 AOA‐related OTUs were detected in CK, M, MNPK, and NPK (Figure 3). The number of shared OTUs was 98 (64.0% of the total). The distributions of the main OTUs in each treatment are shown in Figure 4a. The OTUs were selected based on their relative abundances (1%) in the four fertilizer regimes. The total number of selected OTUs was greater than 90% of the total OTUs, and thus, they reflected the overall distribution. Clear shifts in the AOA community compositions under different fertilization treatments were detected by analyzing the distributions of the OTUs as follows. In CK and M, OTU51 and OTU121 were the dominant OTUs. In MNPK, OTU121, OTU51, and OTU7 were relatively abundant OTUs. In NPK, the main OTUs were OTU121, OTU7, OTU79, and OTU11. Thaumarchaeota and Crenarchaeota were the dominant AOA phyla (Figure 4b). The main AOA amoA OTUs in the different fertilization treatments were assembled in a phylogenetic tree (Figure 5), and only Nitrososphaera AOA were tracked from the black soil. The main AOA amoA OTUs were assigned to two clusters, where OTU79 and OTU45 were distributed in cluster 2, and the other 23 OTUs in cluster 1. The two clusters were closely related. The abundances of Thaumarchaeota were far lower in MNPK and NPK compared with those in CK and M. Furthermore, the relationships between the main AOA amoA OTUs and the soil properties are shown in Table 4. Eleven OTUs were negatively correlated with the soil pH, and 10 OTUs were positively correlated with the soil pH. In addition, 10 OTUs were negatively correlated with the soil AP and 12 OTUs were positively correlated with the soil AP.
Figure 3

Venn diagram of AOA amoA genes based on the OTUs in different fertilization treatments. CK, no fertilizer; M, manure only; NPK, inorganic fertilizer; MNPK, inorganic fertilizer with manure

Figure 4

Relative abundances based on the AOA community compositions in soils under different fertilization treatments at the OTU level (a) and main phylum level (b). CK, no fertilizer; M, manure only; NPK, inorganic fertilizer; MNPK, inorganic fertilizer with manure

Figure 5

Neighbor‐joining phylogenetic tree obtained based on AOA amoA gene fragment sequences from black soil. OTUs were selected based on their relative abundances > 1%

Table 4

Pearson's correlation coefficients between soil properties and main AOA amoA OTUs

 pHOMTNNNANAPAK
OTU7−0.944** −0.3410.842** 0.3930.0290.797** −0.117
OTU11−0.975** −0.3550.892** 0.4490.0570.844** −0.128
OTU140.973** 0.38−0.871** −0.473−0.038−0.841** 0.22
OTU180.920** 0.214−0.829** −0.584* −0.105−0.900** 0.068
OTU220.953** 0.446−0.827** −0.429−0.118−0.841** 0.155
OTU280.964** 0.405−0.850** −0.462−0.034−0.845** 0.166
OTU35−0.816** −0.0680.755** 0.770** 0.2640.951** −0.044
OTU39−0.897** −0.2590.792** 0.733** 0.2820.961** −0.173
OTU420.965** 0.5−0.776** −0.541−0.149−0.915** 0.314
OTU45−0.864** −0.3660.790** 0.183−0.0810.640* −0.136
OTU510.947** 0.209−0.875** −0.630* −0.189−0.946** 0.061
OTU53−0.754** −0.0110.697* 0.790** 0.2910.894** 0.011
OTU60−0.861** −0.2230.848** 0.597* 0.1880.919** −0.111
OTU610.960** 0.284−0.886** −0.588* −0.107−0.935** 0.052
OTU680.4240.624* −0.30.4680.454−0.0760.337
OTU710.918** 0.676* −0.693* −0.38−0.012−0.833** 0.354
OTU79−0.923** −0.3680.846** 0.288−0.020.747** −0.132
OTU800.985** 0.352−0.884** −0.535−0.095−0.910** 0.167
OTU92−0.553−0.20.4070.657* 0.3860.793** −0.097
OTU1020.972** 0.355−0.885** −0.565−0.171−0.920** 0.139
OTU115−0.767** −0.1860.686* 0.787** 0.3420.911** −0.053
OTU121−0.938** −0.2340.848** 0.680* 0.2050.973** −0.083
OTU122−0.695* −0.3440.5370.644* 0.3980.836** −0.221

Abbreviations: AP, available phosphorus; AK, available potassium; NN, nitrate nitrogen; AN, ammonium nitrogen; OM, organic matter; TN, total nitrogen.

Correlation is significant at p < .05.

Correlation is significant at p < .01.

Ven class="Chemical">nn diagram of AOA amoA genpan>es based onpan> the OTUs inpan> differenpan>t fertilizationpan> treatmenpan>ts. CK, no fertilizer; M, mpan> class="Chemical">anure only; NPK, inorganic fertilizer; MNPK, inorganic fertilizer with manure Relative abundn class="Chemical">ances based onpan> the AOA communpan>ity compositionpan>s inpan> soils unpan>der differenpan>t fertilizationpan> treatmenpan>ts at the OTU level (a) pan> class="Chemical">and main phylum level (b). CK, no fertilizer; M, manure only; NPK, inorganic fertilizer; MNPK, inorganic fertilizer with manure n class="Chemical">Neighbor‐joinpan>inpan>g phylogenpan>etic tree obtainpan>ed based onpan> AOA amoA genpan>e fragmenpan>t sequenpan>ces from black soil. OTUs were selected based onpan> their relative abunpan>dpan> class="Chemical">ances > 1% Pearson's correlation coefficients between soil properties n class="Chemical">and mainpan> AOA amoA OTUs Abbreviations: AP, available n class="Chemical">an class="Chemical">phosphoruspan>>; AK, available pan class="Chemical">nn> class="Chemical">potassium; NN, pan> class="Chemical">nitrate nitrogen; AN, ammonium nitrogen; OM, organic matter; TN, total nitrogen. Correlation is significn class="Chemical">ant at p < .05. Correlation is significn class="Chemical">ant at p < .01.

Correlations between selected soil properties and AOA taxa

According to redundancy pan> class="Chemical">analysis (Figure 6), all of the selected soil properties explained 97.0% of the variation in the AOA community composition among the samples. Axis 1 and axis 2 obtained by redundancy analysis explained 96.43% of the total variance, where axis 1 explained 86.0% and axis 2 explained 10.43%. The main contributor to the shifts in the AOA community was the soil pH (F = 38.6, p = .002), which explained 79.4% of the variation. The remaining soil properties affected the AOA community composition in the following order: AP > an class="Chemical">AN > TN > AK > OM. Furthermore, the plots for CK, M, MNPK, and NPK grouped well and they were separated from the NPK plot.
Figure 6

Redundancy analysis of the AOA community structure and relationships with soil factors. AP, available phosphorus; AK, available potassium; NN, nitrate nitrogen; AN, ammonium nitrogen; OM, organic matter; TN, total nitrogen; CK, no fertilizer; M, manure only; NPK, inorganic fertilizer; MNPK, inorganic fertilizer with manure

Redundancy pan> class="Chemical">analysis of the AOA community structure and relationships with soil factors. AP, available an class="Chemical">phosphorus; AK, available n class="Chemical">potassium; NN, nitrate nitrogen; AN, ammonium nitrogen; OM, organic matter; TN, total nitrogen; CK, no fertilizer; M, manure only; NPK, inorganic fertilizer; MNPK, inorganic fertilizer with manure

DISCUSSION

Alleviation of soil acidification

The 35‐year application of inorgn class="Chemical">anic fertilizer increased the acidificationpan> of the soil, but organic manure effectively alleviated the soil acidification, probably because it contained organic acids, an class="Chemical">carbonates, and n class="Chemical">bicarbonates (Ding et al., 2017). Furthermore, there were large amounts of carboxyl and phenolic hydroxyl groups in the organic acids, which may relieve the soil acidity and enhance the soil pH value (Ding et al., 2016).

Changes in the abundance of the AOA amoA gene

Long‐term fertilization stimulated the growth of AOA in the black soil. Compared with no fertilization, the AOA amoA gene number was increased in the fertilizer treatments because of the stimulating effects of the inorgn class="Chemical">anic fertilizer n class="Chemical">and the an class="Disease">inorganic plus organic fertilizers, but particularly the former, possibly because there was a negative correlation between the abundance of AOA and the soil pH. The long‐term use of inorgann>ic fertilizer led to a decrease in the soil pH, ann>d thus, the abundance of AOA was highest with the inorganic fertilizer. The AOA amoA gene copy number was not affected by fertilization in some previous studies. Ouyang et al. (2016) reported that AOA was affected less by N fertilizer in a calcareous Millville silt loam, and Tao, Wakelin, Liang, and Chu (2017) found no significant effects of a mineral fertilizer and mineral fertilizer plus n class="Species">cattle manure on the AOA amoA copy numbers in a cultivated gray desert soil. However, archaeal amoA copies in root layer soil with high N were significantly higher than those in soils with no fertilization and low N (Song & Lin, 2014. The application of N fertilizer stimulated the growth of AOA in a yellow clay paddy soil (Yao et al., 2016). Ai et al. (2013) found that the abundance of AOA increased with the OM inputs in a long‐term field trial in a calcareous fluvoaquic soil. A previous study also showed that nitrification activity is positively correlated with the abundn class="Chemical">ance of AOA in some acidic soils (Li et al., 2018). Inpan> our study, the abundance of AOA was negatively related to the soil pH, thereby demonstrating that the distribution of AOA was influenced by the soil pH (Liu et al., 2018). The inorganic fertilizer decreased the soil pH and greatly increased the abundance of AOA. The long‐term application of inorganic fertilizer, especially N fertilizer, can increase the abundance of AOA (Carey, Dove, Beman, Hart, & Aronson, 2016; Ouyang et al., 2018). However, the abundance of AOA was inhibited by organic fertilizer when we applied organic fertilizer plus inorganic fertilizer to the black soil. Moreover, the abundance of AOA was increased by the TN and AP contents in the long‐term fertilizer treatments in black soil, where they had positive relationships. However, Chen et al. (2017) showed that the abundance of AOA in an class="Species">alpine meadows was negatively correlated with the soil TN. This difference may have been related to other factors.

Effects on AOA α‐diversity and community composition

Gao, Chn class="Chemical">ang, et al. (2018c) showed that the AOA community diversity was reduced by the applicationpan> of chemical fertilizer to a paddy soil. However, we found that fertilizationpan> for 35 years increased the AOA α‐diversity index in black soil. The soil AOA α‐diversity was greatly enpan>hanced by the application of inorganic and organic fertilizations, but especially the organic plus inorganic fertilizer, and this result was consistent with that obtained by Han et al. (2018). The AOA α‐diversity indices were significantly positively correlated with the soil NN content of the black soil. Li, Hn class="Chemical">an, He, Zhang, and Zhang (2019) found that the AOA community structure was influenced little by the application of chemical fertilizer. By contrast, we showed that the long‐term application of fertilizers to a black soil altered the AOA community structure. Clear shifts in the AOA community composition under the different fertilization strategies were detected by analyzing the distributions of the AOA OTUs. OTU51 was the dominant OTU in CK, M, and MNPK, but not in NPK. OTU79 and OTU11 were relatively abundant OTUs in NPK. In addition, redundancy analysis clearly demonstrated that the CK, M, and MNPK treatments were distinctly separate from the NPK treatment, thereby suggesting that the change in the AOA community associated with inorganic fertilizer could have been partially attributable to the greater soil mineral N content and the relatively low pH (Ouyang et al., 2017; Tao et al., 2017). We constructed a phylogenetic tree according to the AOA amoA gene fragment sequences (Figure 5), which showed that the main groups comprised n class="Chemical">Nitrososphaera AOA, n class="Chemical">and they have been detected frequently in many soil environments in previous studies (Ke, an class="Chemical">Angel, Lu, & Conrad, 2013; Prosser & Nicol, 2012; Shi et al., 2018). A previous study showed that the Nitrososphaera cluster was the richest soil AOA lineage in acidic soil and alkaline soil (Oishi et al., 2012). Several studies (Koch et al., 2015; Palatinszky et al., 2015) have shown that the Nitrososphaera cluster in farmland soils has a direct linear relationship with nitrification activity, ann>d members of this cluster have a strong genetic capacity to utilize various pan class="Chemical">nn> class="Chemical">ammonia sources. In the present study, the diverse fertilization strategies had different effects on the relative abundances of AOA at the phylum level. Thaumarchaeota and Crenarchaeota were the main AOA phyla (Figure 4b). The abundances of Thaumarchaeota were very low in MNPK and NPK compared with those in CK and M. The appearance of Thaumarchaeota as the dominant taxon in the AOA community may have led to a shift in the pan> class="Chemical">ammonia‐oxidizing capacity (Deignan, Pawlik, & Erwin, 2018). The phylum Crenarchaeota was highly abundant in the black soil. Previous studies reported that members of Crenarchaeota dominate soils with higher pH values in forests (Nicol, Campbell, Chapman, & Prosser, 2007), thereby agreeing with the results obtained in the present study.

CONCLUSION

We studied a black soil in northeast China and investigated the responpan>ses of the soil AOA community structure and diversity to long‐term fertilizer practices. The changes were primarily due to shifts in the soil pH. Compared with NPK, MNPK alleviated the acidification of the soil. Based on the diversity indices (ACE, Chao1, and Shannon), the soil AOA α‐diversity was improved more with MNPK than NPK. According to redundancy analysis and the AOA composition, an class="Disease">inorganic plus organic fertilizer may be beneficial for maintaining the stability of the original AOA community composition in the soil. Our results highlight the effects of organic manure as an amendment for use with inorganic fertilizer to facilitate the long‐term stable development of Chinese Mollisols.

CONFLICT OF INTEREST

The authors declare no potential conflict of interests.

AUTHORS CONTRIBUTION

J. D. n class="Chemical">and M. M. designpan>ed pan> class="Chemical">and executed the experiments. X. J., Y. L., and J. Z. provided technical and theoretical support. L. S. and L. W. analyzed all of the data and produced the figures. J. D. and M. M. wrote and revised the manuscript. D. W. and J. L. were responsible for the overall supervision of the study. All authors read and approved the final manuscript.

ETHICAL APPROVAL

n class="Chemical">Nonpan>e required.
  33 in total

1.  Search and clustering orders of magnitude faster than BLAST.

Authors:  Robert C Edgar
Journal:  Bioinformatics       Date:  2010-08-12       Impact factor: 6.937

2.  Niche differentiation of ammonia oxidizers and nitrite oxidizers in rice paddy soil.

Authors:  Xiubin Ke; Roey Angel; Yahai Lu; Ralf Conrad
Journal:  Environ Microbiol       Date:  2013-02-25       Impact factor: 5.491

3.  Denitrification potential under different fertilization regimes is closely coupled with changes in the denitrifying community in a black soil.

Authors:  Chang Yin; Fenliang Fan; Alin Song; Peiyuan Cui; Tingqiang Li; Yongchao Liang
Journal:  Appl Microbiol Biotechnol       Date:  2015-02-26       Impact factor: 4.813

4.  Agelas Wasting Syndrome Alters Prokaryotic Symbiont Communities of the Caribbean Brown Tube Sponge, Agelas tubulata.

Authors:  Lindsey K Deignan; Joseph R Pawlik; Patrick M Erwin
Journal:  Microb Ecol       Date:  2018-01-03       Impact factor: 4.552

5.  Ammonia manipulates the ammonia-oxidizing archaea and bacteria in the coastal sediment-water microcosms.

Authors:  Yan Zhang; Lujun Chen; Tianjiao Dai; Renhua Sun; Donghui Wen
Journal:  Appl Microbiol Biotechnol       Date:  2015-03-24       Impact factor: 4.813

6.  Diversity and community structure of ammonia oxidizers in a marsh wetland of the northeast China.

Authors:  Dawen Gao; Fengqin Liu; Lu Li; Chuhong Chen; Hong Liang
Journal:  Appl Microbiol Biotechnol       Date:  2018-07-20       Impact factor: 4.813

7.  Reducing the effects of PCR amplification and sequencing artifacts on 16S rRNA-based studies.

Authors:  Patrick D Schloss; Dirk Gevers; Sarah L Westcott
Journal:  PLoS One       Date:  2011-12-14       Impact factor: 3.240

8.  Characterisation of terrestrial acidophilic archaeal ammonia oxidisers and their inhibition and stimulation by organic compounds.

Authors:  Laura E Lehtovirta-Morley; Chaorong Ge; Jenna Ross; Huaiying Yao; Graeme W Nicol; James I Prosser
Journal:  FEMS Microbiol Ecol       Date:  2014-07-31       Impact factor: 4.194

9.  Effects of applying inorganic fertilizer and organic manure for 35 years on the structure and diversity of ammonia-oxidizing archaea communities in a Chinese Mollisols field.

Authors:  Jianli Ding; Mingchao Ma; Xin Jiang; Yao Liu; Junzheng Zhang; Linna Suo; Lei Wang; Dan Wei; Jun Li
Journal:  Microbiologyopen       Date:  2019-09-30       Impact factor: 3.139

10.  Expanded metabolic versatility of ubiquitous nitrite-oxidizing bacteria from the genus Nitrospira.

Authors:  Hanna Koch; Sebastian Lücker; Mads Albertsen; Katharina Kitzinger; Craig Herbold; Eva Spieck; Per Halkjaer Nielsen; Michael Wagner; Holger Daims
Journal:  Proc Natl Acad Sci U S A       Date:  2015-08-24       Impact factor: 11.205

View more
  2 in total

1.  Effects of applying inorganic fertilizer and organic manure for 35 years on the structure and diversity of ammonia-oxidizing archaea communities in a Chinese Mollisols field.

Authors:  Jianli Ding; Mingchao Ma; Xin Jiang; Yao Liu; Junzheng Zhang; Linna Suo; Lei Wang; Dan Wei; Jun Li
Journal:  Microbiologyopen       Date:  2019-09-30       Impact factor: 3.139

Review 2.  Recent trends in nitrogen cycle and eco-efficient nitrogen management strategies in aerobic rice system.

Authors:  Muhammad Shahbaz Farooq; Xiukang Wang; Muhammad Uzair; Hira Fatima; Sajid Fiaz; Zubaira Maqbool; Obaid Ur Rehman; Muhammad Yousuf; Muhammad Ramzan Khan
Journal:  Front Plant Sci       Date:  2022-08-25       Impact factor: 6.627

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.