Chronic effects of different fertilization regimes on nirS-type denitrifier communities across the black soil region of Northeast China

Pedosphere 30(1): 73–86, 2020 doi:10.1016/S1002-0160(19)60840-4 ISSN 1002-0160/CN 32-1315/P c 2020 Soil Science Society of China ⃝ Published by Elsevier B.V. and Science Press

Chronic effects of different fertilization regimes on nirS-type denitrifier communities across the black soil region of Northeast China Xiaojing HU1 , Junjie LIU1 , Dan WEI2,5 , Ping ZHU3 , Xi’an CUI4 , Baoku ZHOU2 , Xueli CHEN2 , Jian JIN1 , Xiaobing LIU1 and Guanghua WANG1,∗ 1 Key

Laboratory of Mollisols Agroecology, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Harbin 150081 (China) 2 Institute of Soil and Fertilizer and Environment Resources, Heilongjiang Academy of Agricultural Sciences, Harbin 150086 (China) 3 Institute of Agricultural Resource and Environment, Jilin Academy of Agricultural Sciences, Changchun 130033 (China) 4 Heihe Branch of Heilongjiang Academy of Agricultural Sciences, Heihe 164300 (China) 5 Institute of Plant Nutrition and Resources, Beijing Academy of Agricultureand Forestry Sciences, Beijing 100097 (China) (Received April 8, 2019; revised June 12, 2019)

ABSTRACT Denitrification is one of the major processes causing nitrogen loss from arable soils. This study aimed to investigate the responses of nirS-type denitrifier communities to different chronic fertilization regimes across the black soil region of Northeast China. Soil samples were collected from sites located in the north (NB), middle (MB), and south (SB) of the black soil region of Northeast China, each with four chronic fertilization regimes: no fertilizer (NoF), chemical fertilizer (CF), manure (M), and chemical fertilizer plus manure (CFM). Methods of quantitative polymerase chain reaction (qPCR) and Illumina MiSeq sequencing were applied to assess the abundance and composition of denitrifier communities by targeting the nirS gene. The results showed that the M and CFM regimes significantly increased the abundances of nirS-type denitrifiers compared with NoF at the three locations. The majority of nirS sequences were grouped as unclassified denitrifiers, and the different fertilizers induced little variation in the relative abundance of known nirS-type denitrifier taxa. Over 90% of the sequences were shared among the four fertilization regimes at each location, but none of the abundant operational taxonomic units (OTUs) were shared among the three locations. Principal coordinate analysis (PCoA) revealed that the communities of nirS-type denitrifier were separated into three groups that corresponded with their locations. Although similar fertilization regimes did not induce consistent changes in the nirS-type denitrifier communities, soil pH and NO− 3 -N content simultaneously and significantly influenced the structure of nirS-type denitrifier communities at the three locations. Our results highlight that geographical separation rather than chronic fertilization was the dominant factor determining the nirS-type denitrifier community structures, and similar chronic fertilization regimes did not induce consistent shifts of nirS-type denitrifier communities in the black soils. Key Words: denitrification, denitrifier diversity, denitrifying gene, geographical separation, Illumina MiSeq sequencing, manure, Mollisols, nirS gene, quantitative polymerase chain reaction Citation: Hu X J, Liu J J, Wei D, Zhu P, Cui X A, Zhou B K, Chen X L, Jin J, Liu X B, Wang G H. 2020. Chronic effects of different fertilization regimes on nirS-type denitrifier communities across the black soil region of Northeast China. Pedosphere. 30(1): 73–86.

INTRODUCTION Denitrification is a series of reduction processes in which soluble nitrate (NO− 3 ) is ultimately reduced to dinitrogen (N2 ) under oxygen-limited conditions (Barnard et al., 2005). This process has been widely studied in soils because it causes nitrogen (N) losses in croplands via emission of nitrogenous gases, such as nitric oxide (NO), nitrous oxide (N2 O), and N2 (Hofstra and Bouwman, 2005). Among these, N2 O is a notorious greenhouse gas in depleting ozone and has a war∗ Corresponding

author. E-mail: [email protected].

ming potential approximately 300 times higher than carbon dioxide (CO2 ) (Hallin et al., 2018). Anthropogenic N2 O emissions mainly originate from farmlands due to the increase in application of N-based fertilizers, from either mineral compounds or organic manure (Ruser et al., 2006; Krause et al., 2017). To elucidate the influences of different chronic fertilization regimes on denitrification in agricultural soils is a matter of great importance to maintain sustainable agricultural development. Although some specific fungi contribute to the de-

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nitrification process in soils (Kobayashi et al., 1996), denitrification process was mainly mediated by nitrate reductases of bacteria. There are two types of bacterial nitrate reductases, which are structurally different but functionally equivalent: one contains copper encoded by the nirK gene, the other contains cytochrome cd1 encoded by the nirS gene (Zumft, 1997). The two genes are not closely congruent within different strains of the same species (Coyne et al., 1989; Jones et al., 2008). The phylogeny of the nirS gene is largely congruent with that of the 16S rRNA gene at the family or genus level (Heylen et al., 2006); however, both genes were found suitable for research on the abundance and diversity of denitrifiers in environmental samples (Li et al., 2013; Peralta et al., 2013). Amendment of inorganic or organic fertilizers influences not only soil physiochemical properties, but also soil denitrifying bacteria (Sun et al., 2015; Hou et al., 2018). Some studies have found that the response of nirS-type denitrifier community to different fertilization regimes varied greatly (Maeda et al., 2010; Tang et al., 2016). Sun et al. (2015) revealed that application of urea-N had a minor influence on the abundance of nirS-type denitrifier in a chronically fertilized Calcic Kastanozem soil. However, urea-N significantly increased the gene copies of nirS, but had a weak effect on the community composition of nirS denitrifiers in a red soil with double-cropped rice (Chen et al., 2010). Contrarily, Yang et al. (2017) revealed that nirS gene abundances decreased with the increase of N fertilizer dosage, and different N fertilization rates significantly influenced the nirS-type denitrifier community structures in a sandy clay loam soil. These inconsistent results may be due to the differences in soil properties or types. In addition, organic amendments usually enhance microbial activity and biomass (Liu et al., 2009; Francioli et al., 2016); however, limited studies have been conducted to address the responses of nirS-type denitrifier communities to organic fertilization (Tatti et al., 2012; Wang et al., 2013). Furthermore, most studies on the research of nirS-type denitrifier communities relied on traditional molecular biological methods which are of low resolution, such as denaturing gradient gel electrophoresis (DGGE) and terminal restriction fragment length polymorphism (T-RFLP) (Wolsing and Priem´e, 2004; Veraart et al., 2017). Recently, using high throughput Illumina MiSeq sequencing technique, Tao et al. (2018) investigated the nirS-type denitrifier communities in a chronic fertilization field in the Xinjiang Uyghur autonomous area of Northwest China, and found that soil organic matter (OM) obviously enhanced nirS-type denitrifier abundance and

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changed the community structure. However, in the black soil region, the most important crop-producing areas of China, the variation in nirS-type denitrifier communities is currently unknown. The black soils (Mollisols) of Asia are mainly distributed in China, particularly in Northeast China. As one of the four largest black soil regions in the world, black soils in China are of inherently high fertility and productivity (Xing et al., 2005; Liu et al., 2012). The black soil region in Northeast China has been cultivated for more than 100 years (Zhang et al., 2011). However, extensive cultivation and chronically poor management has caused decline in soil quality and in turn ecological problems in this region (Chen et al., 2017). In particular, excess chemical fertilizer addition has led to soil acidification, decreased soil microbial biodiversity, and altered microbial communities (Zhou et al., 2015). However, in this region, little research has been focused on the soil denitrification process, in which the nirS gene mediates one of the key steps in soil N cycles. Recently, Cui et al. (2016) used quantitative polymerase chain reaction (qPCR) methodology in their research on a black soil of China and reported that manure fertilization significantly increased the abundance of the nirS gene, while chemical fertilizer had little effect. However, the study was only conducted at a single location, which did not help to fully understand the changes of nirS gene at multiple locations of the black soil region. Our previous investigations in this region revealed that different chronic fertilization regimes significantly altered the bacterial and fungal communities, but similar regimes did not induce consistent changes in microbial communities between locations (Hu et al., 2017, 2018). However, we do not know how functional microbe communities, such as nirS-type denitrifiers, response to chronic fertilization regimes across the black soil region. In this study, using the same soil samples as reported previously (Hu et al., 2017, 2018), the effects of four fertilization regimes on the abundances, diversity, and community structure of nirS-type denitrifiers at three locations across the black soil region of Northeast China were investigated with qPCR and Illumina MiSeq sequencing methods. Based on our previous findings (Hu et al., 2017, 2018), we hypothesized that similar fertilization regimes would have inconsistent effects on nirS-type denitrifier communities between the black soil locations (H1) and geographical separation would be a more dominant factor affecting nirS-type denitrifier communities than fertilization (H2). Our results will provide insight into how chronic fertilization regimes affect nirS-type denitrifier communities across the black soil region.

EFFECT OF FERTILIZERS ON DENITRIFIERS IN SOIL

MATERIALS AND METHODS Experimental design and soil sampling and analyses The three chronic fertilization stations are located in Gongzhuling (43◦ 31′ N, 124◦ 48′ E), Mingzhuxiang (45◦ 50′ N, 126◦ 51′ E), and Heihe (50◦ 15′ N, 127◦ 27′ E), which were marked as SB, MB, and NB as they were in the southern, middle, and northern areas of the black soil region, respectively. At SB, mean annual precipitation is 530 mm and mean annual temperature 4.5 ◦ C. Maize monoculture had been practiced since 1979. The experiment adopted a randomized block design with three replicates. Each fertilization plot included 7 rows of 70 cm width and 18 m length. The mean annual precipitation at MB is 533 mm and the mean annual temperature 3.5 ◦ C. The cropland at MB had been used for soybean-maize-wheat rotation since 1980. The fertilization plots were randomly arranged with three replicates, and each replicate included 8 rows of 70 cm width and 6 m length. The mean annual precipitation at NB is 450 mm and mean annual temperature −1.5 ◦ C. The fields at NB had been subjected to wheat-soybean rotation since 1979. Each fertilization plot covered 220 m2 with three replicates. Notably, the crop cultivated at both MB and NB was soybean in the sampling year of 2014. For each location, soil samples were collected from the three replicate plots of the four fertilization regimes of no fertilizer (NoF), chemical fertilizer (CF), manure (M), and chemical fertilizer plus manure (CFM). It should be noted that the amounts of fertilizers applied were calculated based on the local soil characteristics and nutrient contents before the experiments were set up. Thus, the type and quantity of fertilizers used were slightly different between the three locations, but the long-term strategies of no fertilization, single applications of inorganic or organic fertilizers, and combined application of inorganic and organic fertilizers are suitable for the purpose of this study. Five individual soil cores from the bulk soils were randomly collected from the top 0–20 cm soil in each fertilization plot and thoroughly mixed as one sample. Soil pH, total carbon (TC), total N (TN), total phosphorus (TP), total potassium (TK), ammonium-N (NH+ 4− N), nitrate-N (NO3 -N), available P (AP), available K (AK), and soil moisture were measured. The highest soil pH, ca. 7.0, was at SB and lowest at NB. The M and CFM regimes significantly increased soil TC and TN contents at the three locations. Soil P and K contents increased along with the addition of fertilizers at each location. Manure addition significantly increased soil moisture at SB, but no significant effect was ob-

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served at MB and NB. The fertilizer values of different fertilization regimes and the results of soil properties were described in our previously published papers (Hu et al., 2017, 2018). Soil DNA extraction and qPCR Total DNA of each sample was extracted using a FastDNAr SPIN kit for soil (MP Biomedicals, USA) according to the manufacturer’s instructions, and the quantity and purity of extracted DNA were examined using a NanoDrop 2000 spectrophotometer (Thermo Scientific, USA). Abundances of nirS-type denitrifiers were determined using a LightCyclerr 480 (Roche Applied Science, Switzerland). The qPCR reaction system contained 10 µL of SYBR Premix Ex TaqTM (Takara, China), 7.0 µL of sterilized MilliQ water, 1.0 µL soil DNA template, and 1.0 µL of 20 µmol L−1 forward primer cd3aF (5′ -GTSAACGTSAAGGARACSGG-3′ ) and reverse primer R3cd (5′ -GASTTCGGRTGSGTCTTGA-3′ ) to a final volume of 20 µL (Throb¨ack et al., 2004). The standard curves for qPCR were generated through amplification of a fragment containing the nirS gene previously cloned into a plasmid (pMD18-T). The qPCR was started with the initial denaturation for 60 s at 95 ◦ C, followed by 40 cycles of 15 s at 95 ◦ C and 60 s at 60 ◦ C, and final elongation for 10 min at 50 ◦ C. The nirS gene copies were calculated based on corresponding standard curves. Sequencing and bioinformatic analyses of the nirS gene The soil DNA extracted from each sample was used as template and amplified with nirS gene primers cd3aF/R3cd in triplicate (Throb¨ack et al., 2004). Briefly, a unique barcode sequence for each sample was added into the forward and reverse primers. The PCR product of each sample was purified with an AxyPrep DNA Eel extraction kit (Axygen, USA), combined in equal amounts, and paired-end sequenced on an Illumina MiSeq platform at Majorbio BioPharm Technology Co., Ltd. (Shanghai, China). The raw sequences of nirS gene obtained were uploaded to the NCBI database with the accession No. SRP143569. The obtained raw data of nirS gene were analyzed using QIIME 1.91 software (Caporaso et al., 2010). Adaptors, primers, barcodes, and low-quality sequences were removed, and the remaining sequences were translated into amino acid sequences through the FunGene Pipeline (Fish et al., 2013). The sequences that failed to translate into nirS proteins were removed, and the remaining high-quality sequences were clustered into operational taxonomic units (OTUs) at a 97% similarity by UPARSE (Edgar, 2013; Hou et

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al., 2018). Representative sequences were annotated using the FunGene Pipeline database. A random subset of 8 591 sequences per sample based on minimum sequences was selected for comparison of α- and βdiversity of nirS-type denitrifier communities among samples. Statistical analysis The differences in soil properties, nirS-type denitrifier abundances, and α-diversity among the fertilization regimes were examined using one-way analysis of variance (ANOVA), and the Pearson’s correlation between the nirS-type denitrifier abundances, denitrifier taxa, and soil properties were assessed using SPSS version 22.0 software. The OTUs richness and Shannon diversity index were calculated using the alpha diversity.py function of QIIME to represent αdiversity. Principal coordinate analysis (PCoA) (Gower, 1966) and unweighted pair group method with arithmetic mean (UPGMA) (Kuczynski et al., 2012) based on Bray-Curtis distance matrix were employed to analyze the β-diversity of nirS-type denitrifier communities by using R software (version 3.2.5) (R Development Core Team, 2010) using the ape and vegan libraries. Venn diagrams for shared OTU analysis among the four fertilization regimes were plotted using MOTHUR software (Schloss et al., 2009). With the Mantel test, the significance of soil properties in affecting the nirS-type denitrifier communities was analyzed, and the soil properties with significant influence on communities (P < 0.05) were selected for canonical correlation analysis (CCA) in R software using the vegan library. Volcano plots were used to identify significantly depleted and enriched OTUs between locations, which was analyzed in R software using the ggplot2 library. RESULTS Abundances of nirS gene and its link to soil properties The abundances of the nirS gene at SB, MB, and NB were in the range of (11.4–13.5) × 107 , (11.7–16.5) × 107 , and (10.9–16.3) × 107 copies per gram of dry soil, respectively (Fig. 1). Between the three locations, no difference in nirS gene abundance was observed in the NoF regime (P = 0.391), but the different fertilization regimes significantly changed the number of nirS gene copies. The M and CFM regimes significantly and consistently increased (P < 0.05) the nirS gene abundance compared with the NoF and CF regimes at the three locations, while the abundances between M and CFM were not significantly different. Compared

with the NoF regime, the CF regime increased the nirS gene abundance at MB (P < 0.05), but this increase was not observed at SB and NB. Pearson’s correlation analysis indicated that the nirS gene copies were negatively correlated with soil pH at SB (r = −0.669, P = 0.017), while the opposite trend was found at NB (r = 0.883, P < 0.001) (Table I). In addition to − soil pH, soil TC, TN, TP, NH+ 4 -N, NO3 -N, AP, AK, and moisture were significantly and positively correlated with the nirS gene abundance at each location. Specifically, the abundances of nirS gene were significantly and positively correlated with soil TN, TP, and AP at all the three locations (Table I).

Fig. 1 Copy numbers of nirS gene in the four different treatments of the chronic fertilization experiments conducted at the south (SB), middle (MB), and north (NB) locations across the black soil (Mollisol) region in Northeast China. The bars are standard errors (n = 3). Different letters above the bars indicate significant differences (P < 0.05) between treatments for a same black soil location. NoF = no fertilizer; CF = chemical fertilizer; M = manure; CFM = chemical fertilizer plus manure. TABLE I Pearson’s correlations between copy numbers of nirS gene and soil properties at the south (SB), middle (MB), and north (NB) locations across the black soil (Mollisol) region in Northeast China where the chronic fertilization experiments were conducted Soil propertiesa)

SB r

MB P

r

NB P

r

P

pH −0.669* 0.017 −0.219 0.494 0.883** < 0.001 TC 0.872** < 0.001 0.414 0.181 0.812** 0.001 TN 0.779** 0.003 0.687* 0.014 0.946** < 0.001 TP 0.795** 0.002 0.828** 0.001 0.675* 0.016 TK 0.379 0.225 0.485 0.110 0.078 0.809 NH+ 0.026 0.935 0.585* 0.046 −0.055 0.864 4 -N NO− 0.411 0.185 0.380 0.222 0.780** 0.003 3 -N AP 0.868** < 0.001 0.888** < 0.001 0.577* 0.050 AK −0.211 0.511 0.899** < 0.001 0.922** < 0.001 Moisture 0.831** 0.001 0.371 0.235 0.487 0.109 * and **Significant at P < 0.05 and P < 0.01, respectively. = total carbon; TN = total nitrogen; TP = total phosphorus; TK = total potassium; AP = available phosphorus; AK = available potassium. a) TC

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Taxonomic distribution of nirS-type denitrifiers

classes, and a similar phenomenon was observed in the main nirS-type denitrifier genera such as Bradyrhizobium and Rhodanobacter (Table II). Interestingly, irrespective of fertilization regimes, the relative abundance of Alphaproteobacteria was at the lowest level at SB but at the highest level at NB, while the opposite trend was observed for Gammaproteobacteria (Table II). Affiliated within the above two denitrifier classes, the genera Bradyrhizobium and Rhodanobacter also presented a similar trend in the three locations (Table II). At the OTU level, the shared OTUs among the four fertilization regimes at each location are illustrated individually by Venn diagrams (Fig. 2a–c). The majority of OTUs were shared among the four regimes, with the sequences of shared OTUs accounting for 92%, 97%,

A total of 958 248 high-quality sequences were acquired from 36 soil samples with 8 591–17 577 sequences per sample (mean = 13 309). Based on the sequences, Proteobacteria was detected as the sole known phylum of nirS-type denitrifier with the relative abundances ranging 2.4%–33.7%, and the unclassified nirStype denitrifier ranging 66.3%–97.6%. All the classifiable nirS-type denitrifiers are shown in Table II, which showed that at SB and MB, chronic fertilization had little influence on the main nirS-type denitrifier classes such as Alphaproteobacteria and Gammaproteobacteria compared with the NoF regime. As for NB, only the M regime significantly increased the relative abundance of the abovementioned two nirS-type denitrifier TABLE II

Relative abundances of nirS-type denitrifiers at the phylum, class, order, family, and genus levels in the four different treatmentsa) of the chronic fertilization experiments conducted at the south (SB), middle (MB), and north (NB) locations across the black soil (Mollisol) region in Northeast China Taxon

SB NoF

MB CF

M

CFM

NoF

NB CF

M

CFM

NoF

CF

M

CFM

20.00ab 12.40ab 9.90b

7.37b

3.76b 17.10a

8.57b

2.79a 0.92a 10.00a

0.36b 0.14b 8.25a

2.83a 0.21b 5.21a

3.89b 1.21b 0.49b

2.39b 10.80a 0.43b 2.43a 0.06b 0.96a

5.09b 1.20b 0.31b

10.00a 0.03ab 2.79a 0.00a 0.00a 0.41a

8.25a 0.01b 0.36b 0.00a 0.00a 0.06a

5.21a 0.00b 2.83a 0.00a 0.00a 0.06a

0.49ab 0.10ab 3.88b 0.01a 0.00a 0.10a

0.06b 0.92a 0.02b 0.17ab 2.39b 10.80a 0.00a 0.00a 0.00a 0.01a 0.09a 0.92a

0.26b 0.26a 5.08b 0.00a 0.02a 0.28a

0.00a 0.02a 10.00a 0.00a 2.79a 0.03ab

0.00a 0.03a 8.25a 0.00a 0.36b 0.01b

0.00a 0.01a 5.21a 0.00a 2.83a 0.00b

0.00a 0.01a 0.49ab 0.01a 3.88b 0.10ab

0.00a 0.01a 0.00a 0.01a 0.06b 0.92a 0.00a 0.00a 2.39b 10.80a 0.02b 0.17ab

0.02a 0.04a 0.26b 0.00a 5.08b 0.26a

10.00a 0.02a 0.03a 2.79a 0.00a 0.02a 0.00b 0.00a 0.00a 0.00a

8.25a 0.03a 0.00a 0.36b 0.00a 0.02a 0.01b 0.00a 0.00a 0.00a

5.21a 0.01a 0.00a 2.83a 0.00a 0.01a 0.00b 0.00a 0.00a 0.00a

0.49ab 0.01a 0.03ab 3.88b 0.00a 0.00a 0.00a 0.01a 0.00a 0.00a

0.06b 0.92a 0.00a 0.01a 0.01b 0.06ab 2.39b 10.80a 0.00a 0.01a 0.00a 0.00a 0.00a 0.00a 0.00a 0.00a 0.00a 0.00a 0.00a 0.02a

0.26b 0.04a 0.10a 5.08b 0.02a 0.00a 0.00a 0.00a 0.00a 0.00a

% Phylum 17.54b) ac) 22.50a 26.50a 26.70a 22.30a Protobacteria Class Alphaproteobacteria 0.31a 0.19a 0.14a 0.17a 1.52ab Betaproteobacteria 1.08a 3.77a 1.06a 4.04a 0.60ab Gammaproteobacteria 6.25a 6.96a 11.30a 8.30a 8.85a Order Xanthomonadales 6.25a 6.96a 11.30a 8.28a 8.85a Rhodocyclales 0.21a 0.03b 0.00b 0.00b 0.09a Rhizobiales 0.00a 0.00a 0.00a 0.00a 1.52ab Rhodospirillales 0.03a 0.04a 0.03a 0.04a 0.00a Pseudomonadales 0.00a 0.00a 0.00a 0.01a 0.00a Burkholderiales 0.03a 0.05a 0.00a 0.03a 0.19a Family Pseudomonadaceae 0.00a 0.00a 0.00a 0.01a 0.00a Oxalobacteraceae 0.00a 0.00a 0.00a 0.00a 0.10a Xanthomonadaceae 6.25a 6.96a 11.30a 8.28a 8.85a Rhodospirillaceae 0.03a 0.04a 0.03a 0.04a 0.00a Bradyrhizobiaceae 0.00a 0.00a 0.00a 0.00a 1.52ab Rhodocyclaceae 0.21a 0.03b 0.00b 0.00b 0.09a Genus Rhodanobacter 6.25a 6.96a 11.30a 8.28a 8.85a Herbaspirillum 0.00a 0.00a 0.00a 0.00a 0.10a Dechloromonas 0.10a 0.00a 0.00a 0.00a 0.00a Bradyrhizobium 0.00a 0.00a 0.00a 0.00a 1.52ab Pseudomonas 0.00a 0.00a 0.00a 0.01a 0.00a Rubrivivax 0.03a 0.05a 0.00a 0.02a 0.04a Azospira 0.00a 0.00a 0.00a 0.00a 0.07a Azospirillum 0.00a 0.01a 0.00a 0.00a 0.00a Aromatoleum 0.01a 0.03a 0.00a 0.00a 0.00a Azoarcus 0.06a 0.00b 0.00b 0.00b 0.02a a) NoF

= no fertilizer; CF = chemical fertilizer; M = manure; CFM = chemical fertilizer plus manure. are means of three replicates. c) Different letters in a row for each location indicate significant differences at P < 0.05. b) Values

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Fig. 2 Venn diagrams showing the numbers of unique and shared operational taxonomic units (OTUs) (a, b, and c) and the relative abundances of dominant OTUs (> 0.5%) (d, e, and f) in the four treatments of the chronic fertilization experiments conducted at the south (SB) (a and d), middle (MB) (b and e), and north (NB) (c and f) locations of the black soil (Mollisol) region in Northeast China. The values in parentheses in a, b, and c are percentages of the OTUs sequences in the whole sequences. The percentages, 80%, 89%, and 82%, in d, e, and f, respectively, are the proportions of dominant OTUs sequences to the whole sequences of nirS-type denitrifier at the corresponding location. The color scales in d, e, and f represented the numerical magnitude with log2 transformation. NoF = no fertilizer; CF = chemical fertilizer; M = manure; CFM = chemical fertilizer plus manure.

and 96% of total sequences at SB, MB, and NB, respectively. Meanwhile, although chronic fertilization had little influence on the main nirS-type denitrifiers at phylum and genus levels, none of the identical abundant OTUs were detected simultaneously at all the three locations (Fig. 2d–f), which indicated that nirS sequences presented distinct distribution patterns in this region. Diversity of nirS-type denitrifiers Different chronic fertilization regimes significantly influenced the α-diversity of nirS-type denitrifiers at the three locations; however, similar fertilization regimes did not induce the same changes in α-diversity between the three locations (Table III). All fertilization regimes had no obvious effects on the OTU richness at

TABLE III Alpha-diversity indexes, i.e., operational taxonomic unit (OTU) richness and Shannon diversity, of nirS-type denitrifiers in the four treatmentsa) of the chronic fertilization experiments conducted at the south (SB), middle (MB), and north (NB) locations of the black soil (Mollisol) region in Northeast China Treat- SB MB NB ment OTU Shannon OTU Shannon OTU Shannon richness diversity richness diversity richness diversity NoF CF M CFM

257ab) 244a 260a 257a

3.01b 3.32ab 3.61a 3.65a

162a 133b 125b 112b

3.68a 2.97b 3.39a 2.63b

195b 138c 234a 206b

3.74a 3.03b 3.80a 3.03b

a) NoF = no fertilizer; CF = chemical fertilizer; M = manure; CFM = chemical fertilizer plus manure. b) Different letters indicate significant differences between treatments at P < 0.05.

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SB, while the M and CFM regimes significantly increased the Shannon diversity at this location. At MB and NB, the CF regime concurrently reduced the OTU richness and Shannon diversity as compared with NoF; the M regime decreased the diversity at MB, but increased the diversity at NB. In addition, between the three locations, significant differences in OTU richness (P < 0.001) and Shannon diversity (P = 0.01) were observed in the NoF regime. The PCoA showed the relationships among the nirS-type denitrifier communities of all the samples, in which the first and the second axis together explained 70.4% variation of the community structures (Fig. 3). The total communities of nirS-type denitrifier were separated into three groups along the PCoA 1 axis based on their sampling locations, regardless of the different fertilization regimes (Fig. 3). This phenomenon was also verified by the UPGMA (Fig. 4), in which the nirS-type denitrifier communities of MB and NB were clustered close to each other while both were far away from that of SB. Furthermore, we calculated the numbers of significantly depleted and enriched OTUs between locations using volcano plots, which showed that the significantly altered OTUs were less between MB

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and NB (50%) than between SB and NB (60%) and between MB and SB (52%) (Fig. 5). In addition, the three subplots of PCoA for individual locations further revealed that the different chronic fertilization regimes altered the community structures of nirS-type denitrifier to some extent, whilst similar fertilizations did not induce consistent changes between the three locations (Fig. 3). For example, nirS-type denitrifier communities in the NoF and CF regimes were clustered together, away from those in the M and CFM regimes at SB, while the CF and CFM regimes formed a group that was away from the NoF and M regimes at MB and NB. Links of nirS-type denitrifier community with soil properties Pearson’s correlation analysis revealed that the relative abundance of the main nirS-type denitrifier phyla and genera had significant relationships with some soil properties (Table IV). For all the samples, the relative abundances of the class Alphaproteobacteria and the genus Bradyrhizobium were negatively correlated with soil pH, whereas those of other taxa were all positively correlated with some soil properties. No consis-

Fig. 3 Principal coordinates analysis (PCoA) of the nirS-type denitrifier communities based on operational taxonomic units (OTUs) from 36 soil samples collected from the four treatments of the chronic fertilization experiments conducted at the south (SB), middle (MB), and north (NB) locations of the black soil (Mollisol) region in Northeast China. NoF = no fertilizer; CF = chemical fertilizer; M = manure; CFM = chemical fertilizer plus manure.

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Fig. 4 Hierarchical cluster analysis of the nirS-type denitrifier communities based on operational taxonomic units (OTUs) from 36 soil samples collected from the four treatments of the chronic fertilization experiments conducted at the south (SB), middle (MB), and north (NB) locations of the black soil (Mollisol) region in Northeast China. NoF = no fertilizer; CF = chemical fertilizer; M = manure; CFM = chemical fertilizer plus manure.

Fig. 5 Volcano plots of the nirS-type denitrifier communities showing the significantly depleted and enriched operational taxonomic units (OTUs) between the three locations of the chronic fertilization experiments conducted at the south (SB), middle (MB), and north (NB) locations of the black soil (Mollisol) region in Northeast China. The numbers in the left hand corners of each plot are percentages of OTUs which were significantly depleted at the first location (i.e., MB, NB, and SB in the left, middle, and right plots, respectively) compared with the corresponding OTUs at the second location (i.e., SB, MB, and NB in the left, middle, and right plots, respectively). The numbers in the right hand corners of each plot are percentages of OTUs which were significantly enriched at the first location compared with the corresponding OTUs at the second location.

tent negative or positive relationships between nirStype denitrifier taxa and soil properties were observed at the three locations (Table IV). For example, soil pH was significantly and positively correlated with all the

detected nirS-type denitrifier taxa at NB, while some nirS-type denitrifier taxa had significant negative relationships with soil pH at SB and MB. At the OTU level, we analyzed the relationships between soil pro-

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TABLE IV Pearson’s correlation coefficients (r) between soil properties (pH, total carbon (TC), total nitrogen (TN), total phosphorus (TP), total − potassium (TK), NH+ 4 -N, NO3 -N, available phosphorus (AP), available potassium (AK), and moisture) and relative abundances of dominant nirS-type denitrifiers at the phylum and genus levels at the south (SB), middle (MB), and north (NB) locations of the black soil (Mollisol) region in Northeast China where the chronic fertilization experiments were conducted Taxon

pH

TC

TN

TP

TK

NH+ 4 -N

SB 0.310 0.553 −0.601* −0.045 0.628* 0.565 −0.048 0.151 −0.050 0.151 – – MB Proteobacteria 0.022 −0.461 −0.586* −0.666* −0.381 −0.288 Alphaproteobacteria −0.683* −0.609* 0.014 −0.272 0.098 0.559 Betaproteobacteria −0.416 −0.315 −0.166 −0.721** 0.002 0.043 Gammaproteobacteria 0.080 −0.174 −0.396 −0.191 0.038 −0.178 Rhodanobacter 0.080 −0.174 −0.396 −0.191 0.038 −0.178 Bradyrhizobium −0.683* −0.909* 0.014 −0.272 0.098 0.559 NB Proteobacteria 0.767** 0.185 0.531 0.022 −0.226 −0.375 Alphaproteobacteria 0.760** 0.190 0.567 0.017 −0.131 −0.320 Betaproteobacteria 0.702* 0.138 0.436 −0.021 −0.341 −0.526 Gammaproteobacteria 0.643* 0.037 0.299 −0.173 −0.348 −0.454 Rhodanobacter 0.605* −0.012 0.250 −0.225 −0.340 −0.479 Bradyrhizobium 0.759** 0.190 0.567 0.017 −0.131 −0.319 All samples Proteobacteria 0.622** 0.009 0.295 0.256 −0.197 0.379* Alphaproteobacteria −0.562** 0.212 0.164 −0.094 0.049 −0.284 Betaproteobacteria 0.333* 0.244 0.461** 0.371* 0.093 0.489** Gammaproteobacteria 0.462** −0.286 −0.089 0.024 0.018 0.232 Rhodanobacter 0.462** −0.288 −0.091 0.022 0.018 0.232 Bradyrhizobium −0.582** 0.205 0.152 0.101 0.062 −0.293 Proteobacteria Alphaproteobacteria Betaproteobacteria Gammaproteobacteria Rhodanobacter Bradyrhizobium

−0.620* 0.384 −0.339 −0.338 −0.336 –a)

0.512 −0.422 −0.045 0.484 0.483 –

0.621* −0.392 0.238 0.437 0.435 –

0.623* −0.460 0.191 0.432 0.430 –

NO− 3 -N

AP

AK

Moisture

0.460 −0.247 0.358 0.140 0.139 –

0.572 −0.444 0.040 0.488 0.486 –

−0.003 −0.135 0.350 −0.211 −0.210 –

0.478 −0.250 −0.263 0.633* 0.632* –

−0.736** 0.334 −0.348 −0.764** −0.764** 0.334

−0.772** −0.133 −0.740** −0.338 −0.338 −0.133

−0.595* 0.066 −0.375 −0.187 −0.187 0.066

−0.154 −0.461 −0.206 0.106 0.106 −0.461

0.090 0.102 0.035 −0.111 −0.171 0.102

−0.158 −0.117 −0.231 −0.374 −0.424 −0.117

0.639* 0.658* 0.528 0.461 0.413 0.658*

−0.062 −0.110 0.153 −0.329 −0.370 −0.109

0.341* 0.192 −0.144 −0.286 0.466** 0.031 0.083 0.276 0.082 0.275 −0.150 −0.282

−0.091 0.070 −0.186 0.167 0.168 0.085

0.562** −0.685** 0.003 0.751** 0.752** −0.687**

* and **Significant at P < 0.05 and P < 0.01, respectively. a) No detection.

perties and the dominant OTUs (relative abundance > 0.5%) at each location, and significant correlations were selected and are presented by networks in Fig. 6a– c. The relationships of the dominating OTUs with soil properties were inconsistent between the three locations. For example, none of the OTUs had a significant relationship with soil NH+ 4 -N but most OTUs had a significant relationship with soil moisture at SB, while opposite trends were observed at MB and NB. The relationship between soil properties and community structure of nirS-type denitrifiers were examined by Mantel test analyses (Table V). Overall, all the detected soil properties significantly influenced the total nirS-type denitrifier communities, with soil pH being the most influential factor. Soil TP content exerted the strongest influence on the nirS-type denitrifier communities at SB, followed by soil pH, TC, TN, NO− 3N, AP, and moisture. As for MB, soil pH and NH+ -N 4 and NO− 3 -N contents significantly impacted the nirStype denitrifier communities, with soil pH being the most important factor. At NB, except the TP content,

all the detected soil properties had significant correlations with the nirS-type denitrifier communities, with soil pH again being the key predictor. Specially, soil pH and NO− 3 -N simultaneously and significantly influenced the community structures of nirS-type denitrifier at the three locations. Moreover, the positive or negative relationships between soil properties and nirS-type denitrifier communities in similar fertilization regimes varied among the three locations (Fig. 6d). For example, soil pH had a positive correlation with nirS-type denitrifier community in the CF regime at SB, but an opposite trend was detected at MB and NB. DISCUSSION Effects of chronic fertilization on the abundance of nirS-type denitrifiers The abundance of nirS-type denitrifiers are generally influenced by many soil properties, such as N nutrients, soil OC, and soil pH (Kandeler et al., 2006; B´arta et al., 2010; Hamonts et al., 2013). In this study,

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Fig. 6 Relationships between dominant operational taxonomic units (OTUs) (relative abundance > 0.5%) and soil properties (a, b, and c) and canonical correspondence analysis (CCA) of nirS-type denitrifier communities associated with soil properties (d) in the four treatments of the chronic fertilization experiments conducted at the south (SB, a and d), middle (MB, b and d), and north (NB, c and d) locations of the black soil (Mollisol) region in Northeast China. The red and blue lines in a, b, and c indicate negative and positive, respectively, correlations between OTUs and soil properties. TC = total carbon; TN = total nitrogen; TP = total phosphorus; TK = total potassium; AP = available phosphorus; AK = available potassium; NoF = no fertilizer; CF = chemical fertilizer; M = manure; CFM = chemical fertilizer plus manure.

soil pH had a totally opposite relationship with nirStype denitrifier abundances between SB and NB (Table I); however, chronic organic fertilization significantly increased soil TN at all the locations, which in turn led to increases in nirS-type denitrifier abundance (Fig. 1). This phenomenon might indicate that soil TN had a stronger impact on nirS-type denitrifier abundance than soil pH did in the black soils, although some reports stated that nirS-type denitrifiers ˇ were most sensitive to soil pH variation (Cuhel et al., 2010; Yin et al., 2015). Unlike soil N, soil mineral P could not be increased through biological fixation or atmospheric deposition (Tang et al., 2016), and P fertilizer was a principal P source for crop production.

Meanwhile, microbial growth was also limited by the presence of P element due to its requirement for protein synthesis (Vanbogelen et al., 1996), and high soil P content significantly increased nirS-type denitrifier abundances at the three locations (Table I). Effects of chronic fertilization on community composition of nirS-type denitrifiers The majority of nirS sequences in the black soils were classified as unclassified denitrifiers or environmental clones, with only the phylum Proteobacteria detected (Table II). Indeed, the nirS-type denitrifiers were mostly found belonging to Alphaproteobacteria, Betaproteobacteria, and Gammaproteobacteria (Hey-

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len et al., 2006; Zhou et al., 2016). Alphaproteobacteria generally had a negative relationship with soil pH (Kim et al., 2014), which explains the higher relative abundance of this denitrifier at NB than at SB (Table II), since soil pH was higher at SB than at NB. In contrast, some denitrifiers affiliated with Gammaproteobacteria prefer to grow in moderately alkaline conditions (Boltyanskaya et al., 2007; Shapovalova et al., 2008), which might explain the extremely low abundance of Gammaproteobacteria in the acidic soil at NB (Table II). Unlike wastewater, sediment, or paddy soils, which contained high abundances of Rhodocyclales and Burkholderiales with the nirS gene (Chen et al., 2010; Zeng et al., 2016; Zhou et al., 2016), Rhodanobacter and Bradyrhizobium were found to be the most abundant genera in black agricultural soils of this study (Table II). Particularly, as a noteworthy symbiotic N-fixer, Bradyrhizobium, which frequently colonizes soils when leguminous plants are cultivated (Pereira e Silva et al., 2013), was more abundant at MB and NB with soybean cultivation. Some species of this genus carried nirS and nirK genes and had the ability to mediate denitrification under low-oxygen conditions (S´anchez and Minamisawa, 2018). In addition, chronic fertilization had little influence on the relative abundances of nirS-type denitrifiers at the three locations. The reason might be that increases in soil nutrients under fertilization additions were insufficient to change the abundances of these denitrifying taxa (Yin et al., 2015). As for the low-level classifications, significant differences in OTUs with high relative abundances were observed (Fig. 2d– f), and there was a great discrepancy in the influences of soil properties on these OTUs (Fig. 6a–c), supporting our hypothesis (H1). These results suggest that

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community composition of nirS-type denitrifiers was distinctly different between locations. Although chronic fertilization had little impacts on the nirS-type denitrifiers at the genus or higher taxonomic levels (Table IV), this effect was obvious at the OTUs level (Fig. 2d– f). Unfortunately, most of the OTUs were aligned into the unclassified species due to limited databases, and it is necessary to further isolate the nirS-type denitrifiers to better understand the structures and functions of these microorganisms. Effects of chronic fertilization on α- and β-diversity of nirS-type denitrifiers Distribution of soil nirS-type denitrifier communities varied noticeably between sampling locations (Fig. 3), which supported our hypothesis (H2) that geographical separation would be the dominant factor determining the nirS-type denitrifier communities in the black soil region. We speculated that discrepancies in the underlying soil properties between the three locations might explain the structure differences in the nirS-type denitrifier communities (Braker et al., 2015), despite the soils originating from the same soil type in this study. That is, as nirS-type denitrifiers are sensitive to environment disturbances (Dang et al., 2009; Azziz et al., 2017), nirS-type denitrifier community structure in the black soils was obviously impacted by all the soil properties detected in this study (Table V). At individual locations, different chronic fertilization regimes had obvious influences on the diversity and structure of nirS-type denitrifier community; however, the influences of similar fertilization regimes were not consistent between the three locations (Fig. 3). Although a previous study reported little variation

TABLE V Correlation coefficients (r) between soil properties and community structures of nirS-type denitrifiers based on Mantel test at the south (SB), middle (MB), and north (NB) locations of the black soil (Mollisol) region in Northeast China where the chronic fertilization experiments were conducted Soil propertiesa) pH TC TN TP TK NH+ 4 -N NO3 -N AP AK Moisture

SB

MB

NB

All samples

r

P value

r

P value

r

P value

r

P value

0.844** 0.815** 0.805** 0.875** 0.085 −0.055 0.539** 0.834** 0.036 0.486**

0.001 0.001 0.001 0.001 0.195 0.608 0.001 0.001 0.369 0.004

0.874** 0.020 0.095 0.099 −0.077 0.717** 0.214* 0.121 0.118 −0.128

0.001 0.337 0.155 0.139 0.815 0.001 0.048 0.118 0.139 1.000

0.552** 0.520** 0.459** 0.103 0.247* 0.550** 0.237* 0.409** 0.442** 0.034

0.001 0.001 0.002 0.226 0.036 0.001 0.048 0.008 0.003 0.354

0.694** 0.482** 0.335** 0.294** 0.092** 0.147** 0.124** 0.219** 0.418** 0.516**

0.001 0.001 0.001 0.001 0.006 0.001 0.001 0.001 0.001 0.001

* and **Significant at P < 0.05 and P < 0.01, respectively. a) TC = total carbon; TN = total nitrogen; TP = total phosphorus; TK = total potassium; AP = available phosphorus; AK = available potassium.

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in the diversity of nirS-type denitrifiers under urea fertilization in the paddy soils (Chen et al., 2010), we found that the same chemical fertilizers significantly reduced the Shannon diversity of nirS-type denitrifiers and shifted their community structures under soybean cultivation (at MB and NB). However, although soil pH had a significantly negative relationship with the diversity of nirS-type denitrifier (r = −0.771, P = 0.003) at SB, the neutral soil there alleviated the influence of chemical fertilizers, leading to little variation in diversity and structure of nirS-type denitrifier community (Hou et al., 2018). Conversely, organic fertilizers significantly increased the diversity of nirStype denitrifier communities (Hou et al., 2018; Tao et al., 2018), and induced a great change in the communities at this location. In addition, soil TC, TN, NH+ 4 -N, and NO− -N contents have been reported as indirect 3 or direct metabolic substrates for denitrifiers (Yang et al., 2017), and had significant influences on denitrifier community structure (Table V). Nevertheless, in this study we mainly focused on the changes of nirS-type denitrifier communities, which occupied different ecological niches to nirK-type denitrifiers (B´arta et al., 2010; Jones and Hallin, 2010), and further research to examine the shifts of nirK-type denitrifier communities under chronic fertilization regimes in the black soils might be necessary. CONCLUSIONS This study provided a number of new insights into the nirS-type denitrifier communities in agricultural black soils of Northeast China. Chronic application of manure or chemical fertilizer plus manure significantly increased the nirS-type denitrifier abundances at the three locations, while had little influence on the relative abundances of known denitrifier taxa. The abundant OTUs in the four fertilization regimes were totally different between the three locations, and the relationship between abundant OTUs and soil properties presented obvious discrepancies between the locations. Across the black soil region, geographical separation exerted a stronger influence on the structure of nirStype denitrifier communities than chronic fertilization, and similar fertilization regimes did not consistently change the nirS-type denitrifier communities between the three locations. Understanding these influences on the nirS-type denitrifier communities may help us for improvement of N management in agriculture soils. ACKNOWLEDGEMENT This work was supported by the Strategic Priori-

ty Research Program of Chinese Academy of Sciences (No. XDB15010103), the National Key Research and Development Program of China (No. 2017YFD0200604), the National Natural Science Foundation of China (No. 41771284), and the Chinese Biodiversity Monitoring and Research Network (Sino BON). REFERENCES Azziz G, Monza J, Etchebehere C, Irisarri P. 2017. NirS- and nirK-type denitrifier communities are differentially affected by soil type, rice cultivar and water management. Eur J Soil Biol. 78: 20–28. Barnard R, Leadley P W, Hungate B A. 2005. Global change, nitrification, and denitrification: A review. Glob Biogeochem Cycles. 19: GB1007. ˇ B´ arta J, Melichov´ a T, Vanˇ ek D, Picek T, Santr˚ uˇ ckov´ a H. 2010. Effect of pH and dissolved organic matter on the abundance of nirK and nirS denitrifiers in spruce forest soil. Biogeochemistry. 101: 123–132. Boltyanskaya Y V, Kevbrin V V, Lysenko A M, Kolganova T V, Tourova T P, Osipov G A, Zhilina T N. 2007. Halomonas mongoliensis sp. nov. and Halomonas kenyensis sp. nov., new haloalkaliphilic denitrifiers capable of N2 O reduction, isolated from soda lakes. Microbiology. 76: 739–747. Braker G, Matthies D, Hannig M, Brandt F B, Brenzinger K, Gr¨ ongr¨ oft A. 2015. Impact of land use management and soil properties on denitrifier communities of Namibian savannas. Microb Ecol. 70: 981–992. Caporaso J G, Kuczynski J, Stombaugh J, Bittinger K, Bushman F D, Costello E K, Fierer N, Pe˜ na A G, Goodrich J K, Gordon J I, Huttley G A, Kelley S T, Knights D, Koenig J E, Ley R E, Lozupone C A, McDonald D, Muegge B D, Pirrung M, Reeder J, Sevinsky J R, Turnbaugh P J, Walters W A, Widmann J, Yatsunenko T, Zaneveld J, Knight R. 2010. QIIME allows analysis of high-throughput community sequencing data. Nat Methods. 7: 335–336. Chen Z, Luo X Q, Hu R G, Wu M N, Wu J S, Wei W X. 2010. Impact of long-term fertilization on the composition of denitrifier communities based on nitrite reductase analyses in a paddy soil. Microb Ecol. 60: 850–861. Chen Z M, Xu Y H, Fan J L, Yu H Y, Ding W X. 2017. Soil autotrophic and heterotrophic respiration in response to different N fertilization and environmental conditions from a cropland in Northeast China. Soil Biol Biochem. 110: 103– 115. Coyne M S, Arunakumari A, Averill B A, Tiedje J M. 1989. Immunological identification and distribution of dissimilatory heme cd1 and nonheme copper nitrite reductases in denitrifying bacteria. Appl Environ Microbiol. 55: 2924–2931. ˇ ˇ Cuhel J, Simek M, Laughlin R J, Bru D, Ch` eneby D, Watson C J, Philippot L. 2010. Insights into the effect of soil pH on N2 O and N2 emissions and denitrifier community size and activity. Appl Environ Microbiol. 76: 1870–1878. Cui P Y, Fan F L, Yin C, Song A L, Huang P R, Tang Y J, Zhu P, Peng C, Li T Q, Wakelin S A, Liang Y C. 2016. Longterm organic and inorganic fertilization alters temperature sensitivity of potential N2 O emissions and associated microbes. Soil Biol Biochem. 93: 131–141. Dang H Y, Wang C Y, Li J, Li T G, Tian F, Jin W, Ding Y S, Zhang Z N. 2009. Diversity and distribution of sediment nirS-encoding bacterial assemblages in response to environmental gradients in the eutrophied Jiaozhou Bay, China. Mi-

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