Appl Microbiol Biotechnol DOI 10.1007/s00253-015-6461-0
ENVIRONMENTAL BIOTECHNOLOGY
Denitrification potential under different fertilization regimes is closely coupled with changes in the denitrifying community in a black soil Chang Yin & Fenliang Fan & Alin Song & Peiyuan Cui & Tingqiang Li & Yongchao Liang
Received: 23 December 2014 / Revised: 2 February 2015 / Accepted: 4 February 2015 # Springer-Verlag Berlin Heidelberg 2015
Abstract Preferable inorganic fertilization over the last decades has led to fertility degradation of black soil in Northeast China. However, how fertilization regimes impact denitrification and its related bacterial community in this soil type is still unclear. Here, taking advantage of a suit of molecular ecological tools in combination of assaying the potential denitrification (DP), we explored the variation of activity, community structure, and abundance of nirS and nirK denitrifiers under four different fertilization regimes, namely no fertilization control (N0M0), organic pig manure (N0M1), inorganic fertilization (N1M0), and combination of inorganic fertilizer and pig manure (N1M1). The results indicated that organic fertilization increased DP, but inorganic fertilization had no impacts. The increase of DP was mirrored by the shift of nirS denitrifiers’ community structure but not by that of nirK denitrifiers’. Furthermore, the change of DP coincided with the variation of abundances of both denitrifiers. Shifts of community structure and abundance of nirS and nirK denitrifiers were correlated with the change of soil pH, total nitrogen (TN), organic matter (OM), C:P, total phosphorus (TP), and available phosphorus (Olsen P). Our results suggest that the change of DP under these four fertilization regimes was closely
Electronic supplementary material The online version of this article (doi:10.1007/s00253-015-6461-0) contains supplementary material, which is available to authorized users. C. Yin : F. Fan : A. Song : P. Cui : Y. Liang Key Laboratory of Plant Nutrition and Fertilizer, Ministry of Agriculture, Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China T. Li : Y. Liang (*) Ministry of Education Key Laboratory of Environment Remediation and Ecological Health, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China e-mail: [email protected]
related to the shift of denitrifying bacteria communities resulting from the variation of properties in the black soil tested. Keywords Black soil . nirS . nirK . Phosphorus . Niche differentiation
Introduction Denitrification is the process of stepwise reduction of nitrate and/or nitrite, through nitric oxide (NO), nitrous oxide (N2O), and finally dinitrogen (N2). Denitrification in soils is one of the major pathways for loss of N from the farm system, and as it escapes utilization by the crop, it reduces the overall efficiency of N-fertilizer use and lowers farm profitability (Hofstra and Bouwman 2005; Philippot et al. 2007). Denitrification is also the leading source of anthropogenic N2O and NO emissions, with the former having 310× the greenhouse gas warming capacity as CO2 (Lashof and Ahuja 1990) and being also an important ozone-depleting substance (Ravishankara et al. 2009). As such, research on denitrification is of immense economic and ecological importance. Significant amount of denitrification can occur in arable soils where N-based fertilizers, either organic manure or synthetic chemical compounds, are used to sustain the soil fertility and plant productivity (Hofstra and Bouwman 2005). However, the addition of these fertilizers does not impact denitrification in a constant way between different soil types (Philippot et al. 2007). This highlights the necessity of understanding the microbial mechanisms underpinning this process. The ability to denitrify is widespread in phylogenetically unrelated microorganisms (Zumft 1997). As such, molecular approaches targeted toward shared functional genes, i.e., those encoding for enzymes responsible for each step of the
Appl Microbiol Biotechnol
reductive pathway, are preferable and allow for both characterization and quantitative determination of function that is polyphyletically dispersed in a community (Braker et al. 1998; Throbäck et al. 2004). Of the range of functional gene markers, nitrite reductase (nir) and nitrous oxide reductase (nos) are two of the most widely used (Enwall et al. 2005; Dambreville et al. 2006; Hallin et al. 2009; Chen et al. 2010; Morales et al. 2010; Petersen et al. 2012). Nitrite reductase (NIR enzyme) catalyzes the conversion of nitrate to nitrite and is used as indication of the overall biological potential for denitrificaion (Morales et al. 2010). There are two structurally different but functionally equivalent nitrite reductases, and these are distributed among different nitrite-reducing bacteria. Copper-containing NIR is encoded by the nirK gene, and the cytochrome cd1 NIR is encoded by nirS gene (Zumft 1997). Together, the characterization of these nir genes can provide biological insights into total potential denitrification (Morales et al. 2010). Previous studies demonstrated that the variation of denitrification potential (DP) under different fertilization regimes was generally underlain by the shift in the community of denitrifying bacteria as a result of changes in the soil physicochemical properties (Enwall et al. 2005; Dambreville et al. 2006; Philippot et al. 2007; Hallin et al. 2009; Chen et al. 2010; Yin et al. 2012). A wide range of studies have found that the driving factors are associated with alteration of soil pH, moisture, organic carbon and soil nitrogen content, and soil physical properties (Dambreville et al. 2006; Philippot et al. 2007; Hallin et al. 2009; Chen et al. 2010; Enwall et al. 2010). In contrast, the role of soil phosphorus (P) has rarely been evaluated, despite that its availability had been demonstrated to greatly impact soil microorganisms (He et al. 2008) and the stability and functioning of soil ecosystems (Wakelin et al. 2014). The northeast area of China is an important grain production region, which contributes to up to 14 % of grain production of China (Xu et al. 2010). The major soil type in the region is Bblack soil^ (Mollisol); a full description of the soil groups characteristics, and its significance to crop production in northeast China, is given in Xu et al. (2010). Over the past 50 years, extensive agricultural intensification has been implemented in this region by high inputs of chemical fertilizers which, in turn, are resulting in serious degradation of soil quality and environmental health (Zhao et al. 2006). The nutrient-based alteration and associated interruption (decoupling) of nutrient cycles and associated microbiota were not surprisingly reflected in significant shifts in the soil N-cycling and wider communities (Tang et al. 2010; Yu et al. 2010; Fan et al. 2011; Yin et al. 2012). However, in black soils, the microbial community associated with denitrification and nutrient additions remains largely unstudied (Tang et al. 2010; Yin et al. 2012). Therefore, in this study, we applied a suit of molecular ecological tools to characterize the important denitrifier groups both quantitatively and qualitatively (community structure). The influences of organic and inorganic fertilizer
addition were examined and the data analyzed through multivariate analysis, to explore the impacts of ongoing nutrient enrichment on the microbial ecology in black soils.
Material and methods Field site and soil sampling The experimental site and soils were similar to those described in a previous study (Yin et al. 2012), with the exception that the samples were collected 1 year earlier (August, 2008). The experimental plots were established in 1980 in Gongzhuling (43° 30′ N; 124° 48′ E), which has an annual average temperature of 4–5 °C and mean annual precipitation of 595 mm. Available soil physicochemical data prior to the experiment being conducted are given in Table 1. Maize has been planted in the experimental plots since the establishment of the experimental site. Four treatments were investigated in this study in a two-way crossed design: using +/− addition of pig manure fertilizer (M0 or M1) and +/− addition of mineral fertilizer (N0 or N1). To respective treatments, composted pig manure was applied at 1300 kg hm−2 year−1. For plots receiving chemical fertilizers, a combination of urea (165 kg N hm−2 year−1), triple superphosphate (82.5 kg hm−2 year−1 P2O5), and potassium sulphate (82.5 kg hm−2 year−1) were applied. Samples of soil were collected from three replicate plots (n=3) of each treatment. Five cores to a depth of 20 cm were taken for each replicate; then, the samples were pooled and thoroughly mixed to produce one composite sample; a total of 12 samples were collected. After collection, the soil samples were transported to laboratory in a frozen state, about 200 g soil was stored at −80 °C for further molecular analysis, and the rest was stored at 4 °C (until required) for assay of DP and soil physicochemical properties. Soil pH was measured in a 1:5 soil to H2O slurry mixture. Soil moisture was determined gravimetrically by drying the soil at 105 °C for 24 h. Total soil nitrogen (TN) was measured by Kjeldahl nitrogen method. Soil organic matter (OM) was measured using dichromate oxidation. For determination of soil total phosphorus (TP), molybdenum antimony blue colorimetry was used after HClO4-H2SO4 digestion. Soil available phosphorus (Olsen P) was also determined by molybdenum antimony blue colorimetry after extraction by 0.5 M NaHCO3. The measured properties are presented in Table 1. Denitrification potential (DP) DP was measured for each sample according to the method of Enwall et al. (2005) with minor modification. Briefly, stored soil equivalent to 5 g dry mass of soil per sample was sealed in a 100 ml serum bottle containing 5 ml of buffer solution (10 mM glucose and 10 mM KNO3). Denitrifying conditions were induced by flushing the headspace with pure nitrogen
Appl Microbiol Biotechnol Table 1
Physicochemical properties and denitrification potential (DP) in soil following addition of inorganic and organic fertilizers
Chemical Fertilizer levela
Manure pH fertilizer levelb
Moisture (%) TNc (%)
Olsen Pd (mg kg−1)
TPc (g kg−1)
OMc (g kg−1)
C:N
C:P
N0
M0 M1 M0 M1
17.83 (0.01) 16.68 (0.01) 15.81 (0.01) 16. 99 (0.01)
6.82 (0.18) 188.66 (1.81) 11.01 (0.47) 208.82 (15.27) 27.0
0.48 (0.03) 1.05 (0.14) 0.46 (0.01) 1.69 (0.15) 0.14
23.18 (0.03) 36.26 (0.10) 25.78 (0.27) 38.63 (0.18) 28.10
16.14 (0.11) 17.73 (1.53) 16.54 (0.69) 16.14 (0.31)
48.86 (2.95) 35.83 (5.44) 55.77 (1.76) 23.17 (2.05)
N1 Before experiment
7.94 (0.01) 7.70 (0.01) 7.86 (0.01) 7.52 (0.01) 7.8
0.144 (0.001) 0.207 (0.02) 0.156 (0.006) 0.240 (0.003)
The value was average (n=3), and values in the parentheses are standard errors a
N0 = No inorganic fertilizer; N1 = Inorganic fertilizer
b
No organic manure; M1 = Organic manure
c
Total nitrogen; TP = Total phosphorus; OM = Organic matter
d
Olsen P = Biocarbonate extractable, reactive P
gas (99.9 %) for 10 min. After the bottles were balanced to atmospheric pressure, the 10 ml headspace gas was substituted with an equal volume of pure acetylene (99.9 %). The bottles were incubated on orbital shaker at 25 °C for 8 h, and gas samples collected at 2, 4, and 8 h. Nitrous oxide in gas samples was then analyzed on a gas chromatograph (Agilent 7890A) as described elsewhere by Cui et al. (2013).
DNA extraction and T-RFLP analysis Total DNA was extracted from 500 mg of each soil sample using Fast DNA SPIN Kit for soil and FastPrep-24 machine (Qbiogene, Canada) according to the manufacturer’s instruction. For terminal-restriction fragment length polymorphism (T-RFLP) analysis, the nirS and nirK fragments were amplified using primers cd3aF/R3cd (Throbäck et al. 2004) and nirK1F /nirK5R (Braker et al. 1998), respectively. The cd3aF and nirK5R were labeled with the FAM fluorophore. Each 25 μl PCR contained 2.5 μl of 10× TaKaRa PCR rTaq buffer, 200 μM of dNTP mixture, 0.4 μM of each primer, 2.5 U rTaq polymerase, and 400 ng μl−1 BSA (TaKaRa, Dalian, China). Thermal cycling conditions have been described elsewhere (Bremer et al. 2007; Throbäck et al. 2004). Three PCRs for each sample were performed independently and subsequently pooled to minimize PCR artifacts. Products of the targeted size were gel-purified using Tiangene gel extraction kit (Tiangene, Beijing, China). The purified products were digested for 6 h according to the instructions provided by the manufacturer (New England Biolabs, USA) in separate reactions with 10 U of the restriction endonuclease HhaI for nirS gene and HaeIII for nirK gene. The terminal restriction fragments (T-RFs) were capillary-separated and intensity values measured using an ABI 3730 sequencer (Applied Biosystems, CA) against internal standard (mapmarker 1000; ABI) spiked in each sample.
Cloning and sequencing Based on the T-RFLP analysis, the clone libraries of nirS for N0M1 and of nirK for N1M1 treatment were constructed, respectively. The same primer systems as mentioned previously were used but with the exception that no fluorescence label was attached. The amplification condition (amplification cocktail ingredient and thermal cycling) was identical as above. After gel purification, the purified product was ligated into pMD19-T vector (TaKaRa, Dalian, China), overnight clones selected by blue-white screening and confirmed by PCR testing. Plasmids were purified from selected strains and sequenced from universal primers (M13) on an ABI 3730 instrument (Applied Biosystems, CA). Sequences were submitted to GeneBank under the accession numbers: KM852685–KM852738 for the nirS genes and KM852622–KM852684 for the nirK genes. Real-time PCR The size of the denitrifier community was measured by realtime PCR (qPCR) of both nirS and nirK genes. Standard curves for each targeted gene were obtained using serial dilution of pMD19 plasmids containing cloned nirS and nirK gene fragments, generating a dilution series ranging from 10−1 to 10−7. The real-time qPCR assays were performed on an iCycle system (Bio-Rad, USA), using SYBR green I chemistry (BioRad, USA) with three technical replicates for each sample. For quantification of nirK gene, the primer pair nirK876/nirK1040 was used, and the thermal cycling conditions were the same as described previously (Henry et al. 2004); for nirS gene, the primers and the thermal cycling protocol as described by Liu et al. (2010) were used. PCRs were conducted in 20 μl volumes, containing 10 μl of 2× SuperMix (Bio-Rad, USA), 2 μl 20-fold diluted extracted DNA, 0.4 μl each primer (10 mM),
Appl Microbiol Biotechnol
and 7.2 μl sterilized Millipore water. The amplification specificity was analyzed by melting curve analysis and also agarose gel electrophoresis. A serial dilution of soil DNA was also subject to qPCR to detect any inhibitory effects; the minimum inhibition was achieved when the 1:20 dilution was used. The amplification R2 was >0.990, and amplification efficiency was 93.8 % for nirS and 87.4 % for nirK, respectively.
With the exception of tree assembly (MEGA 5), all statistical analyses were performed in R (R Team C 2012), with the multivariate analysis (RDA and Mantel test) using the Bvegan^ package (Oksanen et al. 2007).
Results Soil properties under different fertilization regimes
Statistical analysis Two-way ANOVA was used to compare the effect of inorganic and organic fertilization on the soil properties, DP, and the abundance of nirS and nirK denitrifiers. Prior to the analysis, the homogeneity of variance was checked by Bartlett’s test, and the normality of data examined using quantile-quantile plots; data were log-transformed if needed. For T-RFLP analysis, the size and relative abundance of TRFs were assigned in PeakScanner version 1.0 (Applied Biosystems, Inc), while peaks with length of
ENVIRONMENTAL BIOTECHNOLOGY
Denitrification potential under different fertilization regimes is closely coupled with changes in the denitrifying community in a black soil Chang Yin & Fenliang Fan & Alin Song & Peiyuan Cui & Tingqiang Li & Yongchao Liang
Received: 23 December 2014 / Revised: 2 February 2015 / Accepted: 4 February 2015 # Springer-Verlag Berlin Heidelberg 2015
Abstract Preferable inorganic fertilization over the last decades has led to fertility degradation of black soil in Northeast China. However, how fertilization regimes impact denitrification and its related bacterial community in this soil type is still unclear. Here, taking advantage of a suit of molecular ecological tools in combination of assaying the potential denitrification (DP), we explored the variation of activity, community structure, and abundance of nirS and nirK denitrifiers under four different fertilization regimes, namely no fertilization control (N0M0), organic pig manure (N0M1), inorganic fertilization (N1M0), and combination of inorganic fertilizer and pig manure (N1M1). The results indicated that organic fertilization increased DP, but inorganic fertilization had no impacts. The increase of DP was mirrored by the shift of nirS denitrifiers’ community structure but not by that of nirK denitrifiers’. Furthermore, the change of DP coincided with the variation of abundances of both denitrifiers. Shifts of community structure and abundance of nirS and nirK denitrifiers were correlated with the change of soil pH, total nitrogen (TN), organic matter (OM), C:P, total phosphorus (TP), and available phosphorus (Olsen P). Our results suggest that the change of DP under these four fertilization regimes was closely
Electronic supplementary material The online version of this article (doi:10.1007/s00253-015-6461-0) contains supplementary material, which is available to authorized users. C. Yin : F. Fan : A. Song : P. Cui : Y. Liang Key Laboratory of Plant Nutrition and Fertilizer, Ministry of Agriculture, Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China T. Li : Y. Liang (*) Ministry of Education Key Laboratory of Environment Remediation and Ecological Health, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China e-mail: [email protected]
related to the shift of denitrifying bacteria communities resulting from the variation of properties in the black soil tested. Keywords Black soil . nirS . nirK . Phosphorus . Niche differentiation
Introduction Denitrification is the process of stepwise reduction of nitrate and/or nitrite, through nitric oxide (NO), nitrous oxide (N2O), and finally dinitrogen (N2). Denitrification in soils is one of the major pathways for loss of N from the farm system, and as it escapes utilization by the crop, it reduces the overall efficiency of N-fertilizer use and lowers farm profitability (Hofstra and Bouwman 2005; Philippot et al. 2007). Denitrification is also the leading source of anthropogenic N2O and NO emissions, with the former having 310× the greenhouse gas warming capacity as CO2 (Lashof and Ahuja 1990) and being also an important ozone-depleting substance (Ravishankara et al. 2009). As such, research on denitrification is of immense economic and ecological importance. Significant amount of denitrification can occur in arable soils where N-based fertilizers, either organic manure or synthetic chemical compounds, are used to sustain the soil fertility and plant productivity (Hofstra and Bouwman 2005). However, the addition of these fertilizers does not impact denitrification in a constant way between different soil types (Philippot et al. 2007). This highlights the necessity of understanding the microbial mechanisms underpinning this process. The ability to denitrify is widespread in phylogenetically unrelated microorganisms (Zumft 1997). As such, molecular approaches targeted toward shared functional genes, i.e., those encoding for enzymes responsible for each step of the
Appl Microbiol Biotechnol
reductive pathway, are preferable and allow for both characterization and quantitative determination of function that is polyphyletically dispersed in a community (Braker et al. 1998; Throbäck et al. 2004). Of the range of functional gene markers, nitrite reductase (nir) and nitrous oxide reductase (nos) are two of the most widely used (Enwall et al. 2005; Dambreville et al. 2006; Hallin et al. 2009; Chen et al. 2010; Morales et al. 2010; Petersen et al. 2012). Nitrite reductase (NIR enzyme) catalyzes the conversion of nitrate to nitrite and is used as indication of the overall biological potential for denitrificaion (Morales et al. 2010). There are two structurally different but functionally equivalent nitrite reductases, and these are distributed among different nitrite-reducing bacteria. Copper-containing NIR is encoded by the nirK gene, and the cytochrome cd1 NIR is encoded by nirS gene (Zumft 1997). Together, the characterization of these nir genes can provide biological insights into total potential denitrification (Morales et al. 2010). Previous studies demonstrated that the variation of denitrification potential (DP) under different fertilization regimes was generally underlain by the shift in the community of denitrifying bacteria as a result of changes in the soil physicochemical properties (Enwall et al. 2005; Dambreville et al. 2006; Philippot et al. 2007; Hallin et al. 2009; Chen et al. 2010; Yin et al. 2012). A wide range of studies have found that the driving factors are associated with alteration of soil pH, moisture, organic carbon and soil nitrogen content, and soil physical properties (Dambreville et al. 2006; Philippot et al. 2007; Hallin et al. 2009; Chen et al. 2010; Enwall et al. 2010). In contrast, the role of soil phosphorus (P) has rarely been evaluated, despite that its availability had been demonstrated to greatly impact soil microorganisms (He et al. 2008) and the stability and functioning of soil ecosystems (Wakelin et al. 2014). The northeast area of China is an important grain production region, which contributes to up to 14 % of grain production of China (Xu et al. 2010). The major soil type in the region is Bblack soil^ (Mollisol); a full description of the soil groups characteristics, and its significance to crop production in northeast China, is given in Xu et al. (2010). Over the past 50 years, extensive agricultural intensification has been implemented in this region by high inputs of chemical fertilizers which, in turn, are resulting in serious degradation of soil quality and environmental health (Zhao et al. 2006). The nutrient-based alteration and associated interruption (decoupling) of nutrient cycles and associated microbiota were not surprisingly reflected in significant shifts in the soil N-cycling and wider communities (Tang et al. 2010; Yu et al. 2010; Fan et al. 2011; Yin et al. 2012). However, in black soils, the microbial community associated with denitrification and nutrient additions remains largely unstudied (Tang et al. 2010; Yin et al. 2012). Therefore, in this study, we applied a suit of molecular ecological tools to characterize the important denitrifier groups both quantitatively and qualitatively (community structure). The influences of organic and inorganic fertilizer
addition were examined and the data analyzed through multivariate analysis, to explore the impacts of ongoing nutrient enrichment on the microbial ecology in black soils.
Material and methods Field site and soil sampling The experimental site and soils were similar to those described in a previous study (Yin et al. 2012), with the exception that the samples were collected 1 year earlier (August, 2008). The experimental plots were established in 1980 in Gongzhuling (43° 30′ N; 124° 48′ E), which has an annual average temperature of 4–5 °C and mean annual precipitation of 595 mm. Available soil physicochemical data prior to the experiment being conducted are given in Table 1. Maize has been planted in the experimental plots since the establishment of the experimental site. Four treatments were investigated in this study in a two-way crossed design: using +/− addition of pig manure fertilizer (M0 or M1) and +/− addition of mineral fertilizer (N0 or N1). To respective treatments, composted pig manure was applied at 1300 kg hm−2 year−1. For plots receiving chemical fertilizers, a combination of urea (165 kg N hm−2 year−1), triple superphosphate (82.5 kg hm−2 year−1 P2O5), and potassium sulphate (82.5 kg hm−2 year−1) were applied. Samples of soil were collected from three replicate plots (n=3) of each treatment. Five cores to a depth of 20 cm were taken for each replicate; then, the samples were pooled and thoroughly mixed to produce one composite sample; a total of 12 samples were collected. After collection, the soil samples were transported to laboratory in a frozen state, about 200 g soil was stored at −80 °C for further molecular analysis, and the rest was stored at 4 °C (until required) for assay of DP and soil physicochemical properties. Soil pH was measured in a 1:5 soil to H2O slurry mixture. Soil moisture was determined gravimetrically by drying the soil at 105 °C for 24 h. Total soil nitrogen (TN) was measured by Kjeldahl nitrogen method. Soil organic matter (OM) was measured using dichromate oxidation. For determination of soil total phosphorus (TP), molybdenum antimony blue colorimetry was used after HClO4-H2SO4 digestion. Soil available phosphorus (Olsen P) was also determined by molybdenum antimony blue colorimetry after extraction by 0.5 M NaHCO3. The measured properties are presented in Table 1. Denitrification potential (DP) DP was measured for each sample according to the method of Enwall et al. (2005) with minor modification. Briefly, stored soil equivalent to 5 g dry mass of soil per sample was sealed in a 100 ml serum bottle containing 5 ml of buffer solution (10 mM glucose and 10 mM KNO3). Denitrifying conditions were induced by flushing the headspace with pure nitrogen
Appl Microbiol Biotechnol Table 1
Physicochemical properties and denitrification potential (DP) in soil following addition of inorganic and organic fertilizers
Chemical Fertilizer levela
Manure pH fertilizer levelb
Moisture (%) TNc (%)
Olsen Pd (mg kg−1)
TPc (g kg−1)
OMc (g kg−1)
C:N
C:P
N0
M0 M1 M0 M1
17.83 (0.01) 16.68 (0.01) 15.81 (0.01) 16. 99 (0.01)
6.82 (0.18) 188.66 (1.81) 11.01 (0.47) 208.82 (15.27) 27.0
0.48 (0.03) 1.05 (0.14) 0.46 (0.01) 1.69 (0.15) 0.14
23.18 (0.03) 36.26 (0.10) 25.78 (0.27) 38.63 (0.18) 28.10
16.14 (0.11) 17.73 (1.53) 16.54 (0.69) 16.14 (0.31)
48.86 (2.95) 35.83 (5.44) 55.77 (1.76) 23.17 (2.05)
N1 Before experiment
7.94 (0.01) 7.70 (0.01) 7.86 (0.01) 7.52 (0.01) 7.8
0.144 (0.001) 0.207 (0.02) 0.156 (0.006) 0.240 (0.003)
The value was average (n=3), and values in the parentheses are standard errors a
N0 = No inorganic fertilizer; N1 = Inorganic fertilizer
b
No organic manure; M1 = Organic manure
c
Total nitrogen; TP = Total phosphorus; OM = Organic matter
d
Olsen P = Biocarbonate extractable, reactive P
gas (99.9 %) for 10 min. After the bottles were balanced to atmospheric pressure, the 10 ml headspace gas was substituted with an equal volume of pure acetylene (99.9 %). The bottles were incubated on orbital shaker at 25 °C for 8 h, and gas samples collected at 2, 4, and 8 h. Nitrous oxide in gas samples was then analyzed on a gas chromatograph (Agilent 7890A) as described elsewhere by Cui et al. (2013).
DNA extraction and T-RFLP analysis Total DNA was extracted from 500 mg of each soil sample using Fast DNA SPIN Kit for soil and FastPrep-24 machine (Qbiogene, Canada) according to the manufacturer’s instruction. For terminal-restriction fragment length polymorphism (T-RFLP) analysis, the nirS and nirK fragments were amplified using primers cd3aF/R3cd (Throbäck et al. 2004) and nirK1F /nirK5R (Braker et al. 1998), respectively. The cd3aF and nirK5R were labeled with the FAM fluorophore. Each 25 μl PCR contained 2.5 μl of 10× TaKaRa PCR rTaq buffer, 200 μM of dNTP mixture, 0.4 μM of each primer, 2.5 U rTaq polymerase, and 400 ng μl−1 BSA (TaKaRa, Dalian, China). Thermal cycling conditions have been described elsewhere (Bremer et al. 2007; Throbäck et al. 2004). Three PCRs for each sample were performed independently and subsequently pooled to minimize PCR artifacts. Products of the targeted size were gel-purified using Tiangene gel extraction kit (Tiangene, Beijing, China). The purified products were digested for 6 h according to the instructions provided by the manufacturer (New England Biolabs, USA) in separate reactions with 10 U of the restriction endonuclease HhaI for nirS gene and HaeIII for nirK gene. The terminal restriction fragments (T-RFs) were capillary-separated and intensity values measured using an ABI 3730 sequencer (Applied Biosystems, CA) against internal standard (mapmarker 1000; ABI) spiked in each sample.
Cloning and sequencing Based on the T-RFLP analysis, the clone libraries of nirS for N0M1 and of nirK for N1M1 treatment were constructed, respectively. The same primer systems as mentioned previously were used but with the exception that no fluorescence label was attached. The amplification condition (amplification cocktail ingredient and thermal cycling) was identical as above. After gel purification, the purified product was ligated into pMD19-T vector (TaKaRa, Dalian, China), overnight clones selected by blue-white screening and confirmed by PCR testing. Plasmids were purified from selected strains and sequenced from universal primers (M13) on an ABI 3730 instrument (Applied Biosystems, CA). Sequences were submitted to GeneBank under the accession numbers: KM852685–KM852738 for the nirS genes and KM852622–KM852684 for the nirK genes. Real-time PCR The size of the denitrifier community was measured by realtime PCR (qPCR) of both nirS and nirK genes. Standard curves for each targeted gene were obtained using serial dilution of pMD19 plasmids containing cloned nirS and nirK gene fragments, generating a dilution series ranging from 10−1 to 10−7. The real-time qPCR assays were performed on an iCycle system (Bio-Rad, USA), using SYBR green I chemistry (BioRad, USA) with three technical replicates for each sample. For quantification of nirK gene, the primer pair nirK876/nirK1040 was used, and the thermal cycling conditions were the same as described previously (Henry et al. 2004); for nirS gene, the primers and the thermal cycling protocol as described by Liu et al. (2010) were used. PCRs were conducted in 20 μl volumes, containing 10 μl of 2× SuperMix (Bio-Rad, USA), 2 μl 20-fold diluted extracted DNA, 0.4 μl each primer (10 mM),
Appl Microbiol Biotechnol
and 7.2 μl sterilized Millipore water. The amplification specificity was analyzed by melting curve analysis and also agarose gel electrophoresis. A serial dilution of soil DNA was also subject to qPCR to detect any inhibitory effects; the minimum inhibition was achieved when the 1:20 dilution was used. The amplification R2 was >0.990, and amplification efficiency was 93.8 % for nirS and 87.4 % for nirK, respectively.
With the exception of tree assembly (MEGA 5), all statistical analyses were performed in R (R Team C 2012), with the multivariate analysis (RDA and Mantel test) using the Bvegan^ package (Oksanen et al. 2007).
Results Soil properties under different fertilization regimes
Statistical analysis Two-way ANOVA was used to compare the effect of inorganic and organic fertilization on the soil properties, DP, and the abundance of nirS and nirK denitrifiers. Prior to the analysis, the homogeneity of variance was checked by Bartlett’s test, and the normality of data examined using quantile-quantile plots; data were log-transformed if needed. For T-RFLP analysis, the size and relative abundance of TRFs were assigned in PeakScanner version 1.0 (Applied Biosystems, Inc), while peaks with length of
