Responses of bacterial communities in wheat rhizospheres in different soils to di-n-butyl and di(2-ethylhexyl)phthalate contamination

Geoderma 362 (2020) 114126

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Responses of bacterial communities in wheat rhizospheres in different soils to di-n-butyl and di(2-ethylhexyl)phthalate contamination

T

Minling Gaoa, Ze Zhangb, Youming Dongb, Zhengguo Songa, , Huaxin Daic ⁎

a

Department of Civil and Environmental Engineering, Shantou University, No 243 Daxue Road, Shantou, Guangdong Province, 515063, China School of Environmental Science and Engineering, Tianjin Polytechnic University, No. 399 Binshui West Road, Xiqing District, Tianjin 300387, China c Key Laboratory of Eco-environment and Tobacco Leaf Quality, Zhengzhou Tobacco Research Institute of China National Tobacco Corporation, Zhengzhou 450001, China b

ARTICLE INFO

ABSTRACT

Handling Editor: Dr Naoise Nunan

Di-n-butyl phthalate (DBP) and di(2-ethylhexyl)phthalate (DEHP) are commonly used as plasticizers to enhance the flexibility of plastic products. They are universal pollutants and well-known endocrine disruptors, and their effects on rhizosphere organisms have aroused great concern. In the present study, the effects of DBP and DEHP contamination on bacterial community structure and functions in wheat rhizospheres in fluvo-aquic, cinnamon, and brown soils were investigated using Illumina HiSeq 2500 sequencing. Operational taxonomic unit richness and bacterial diversity were decreased in DEHP-contaminated fluvo-aquic and brown soils, but not in DEHPcontaminated cinnamon and DBP-polluted soils. The relative abundance of some families was positively associated with soil pH, total nitrogen content (TN), and soil organic matter (SOM), and negatively correlated with DBP/DEHP concentration. The relative abundances of families that can extremely effectively degrade DBP/ DEHP were enhanced by DBP/DEHP pollution, whereas the relative abundances of some genera that are beneficial to soil health were reduced in the DBP/DEHP-polluted soils. Soil pH, TN, and SOM were crucial in determining the fate and effect of PAEs in the soil ecosystems. In conclusion, DBP/DEHP pollution alters the rhizosphere bacterial community structure and affects microbial metabolic behavior and functional diversity during wheat growth.

Keywords: Di-n-butyl phthalate Di(2-ethylhexyl)phthalate Bacterial community Rhizosphere soil Wheat

1. Introduction Phthalic acid esters (PAEs) are used as plasticizers to improve the flexibility and workability of polymeric materials, which are handled in large quantities globally. Because PAEs do not chemically bind to these products, they can migrate into the ecosystem or wastewater during their processing and after disposal, and they particularly leak from plastic products (Meng et al., 2015; Sarkar et al., 2013). Di-n-butyl phthalate (DBP) is an important PAE that can easily escape to the environment from plastics. Di(2-ethylhexyl)phthalate (DEHP) is the most commonly used phthalate plasticizer because of its low cost and high performance, with some plastics containing up to 40% of this compound (Net et al., 2015). These phthalates are widely detected in agricultural soils (Dankova et al., 2013; Zhao et al., 2015). Zorníková et al. (2011) reported high levels of DBP and DEHP (0.3 and 10.3 mg kg−1 dw, respectively) in agricultural soils in the Czech Republic. The concentrations of DBP and DEHP in Danish agricultural soils ranged from 0.3 to 453 μg kg−1 and 12 to 1900 μg kg−1, respectively (Vikelsøe et al., 2002). Kong et al. (2012) found that the

⁎

concentrations of six priority PAEs ranged from 0.05 to 10.4 mg g−1 in suburban farmland, vegetable, orchard, and wasteland soils of Tianjin (China). The concentrations of six major PAEs in plastic-mulched crop lands were 74–208% higher than those in non-mulched farmlands in China (Wang et al., 2013). The concentrations of DBP and DEHP found in Chinese-grown vegetables and Chinese soils generally exceed USA and European food security standards and their respective environmental risk limits of 0.7 and 1.0 mg kg−1 (Steinmetz et al., 2016). The rhizosphere microbiome is the community of microbes adhering to and inhabiting the soil surrounding plant roots. They are crucial for both above- and below-ground ecosystem functioning, as well as plant growth and development. The diversity of this microbial community influences microbial function in the rhizosphere soil. Numerous studies have reported that organic pollutants have strong adverse effects on endogenous microbial communities (Chao and Hsu, 2004; Chao and Cheng, 2007). Using PCR-denaturing gradient gel electrophoresis, Zhang et al. (2015) found that DBP dramatically altered the abundance, structure, and composition of the rhizosphere microbiome at concentrations higher than 50 mg L−1. Bacillus was identified as the

Corresponding author. E-mail address: [email protected] (Z. Song).

https://doi.org/10.1016/j.geoderma.2019.114126 Received 30 April 2019; Received in revised form 2 December 2019; Accepted 4 December 2019 0016-7061/ © 2019 Elsevier B.V. All rights reserved.

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dominant species in DBP-polluted cucumber rhizospheric soil. Based on terminal restriction fragment length polymorphism analysis, Kong et al. (2018) found that soil alpha diversity and bacterial community structure were significantly changed under DBP stress, whereas no significant effect on vegetable (Brassica napus)-associated bacteria was observed by using quantitative PCR and Illumina HiSeq sequencing. Although several studies have revealed that bacterial communities and their structure change in PAE-contaminated soils, there is limited information on the potential negative effects of DBP and DEHP on the structural and functional diversity of microbial communities in rhizosphere soils of wheat, one of the most important grain crops globally. Therefore, in this study, we constructed a soil-wheat ecosystem with DBP and DEHP pollution gradients. The aims of the study were: 1) to investigate the effects of DBP/DEHP on bacterial communities in the rhizosphere soil using 16S rDNA HiSeq high-throughput sequencing, and 2) to reveal the relationships between PAE stress and microbial community components, structure, and diversity.

2.3. Exposure experiment DBP and DEHP stock solutions of 1000 mg L–1 were prepared in methanol. Soil samples weighing 1.5 kg were artificially contaminated with 150, 300, or 600 mg kg−1 DBP or DEHP. After methanol volatilization, the soil samples were mixed gradually with 13.5 kg of uncontaminated soils to obtain theoretical experimental concentrations of 10 mg kg−1 (DBP10, DEHP10), 20 mg kg−1 (DBP20, DEHP20), and 40 mg kg−1 (DBP40, DEHP40). Then, 5.0 kg of each soil sample was transferred into a polypropylene pot (length × width × height = 18 cm × 16 cm × 22 cm). The rhizobox used in this study was designed according to He et al. (2005). Subsequently, the soil moisture content was adjusted to 60% of the maximum water-holding capacity, using deionized water. For each soil type, a non-treated control group was included, and the 21 treatments were conducted in triplicate. The pots were transferred to a greenhouse (temperature = 20 °C ± 5 °C, relative humidity = 43%) located at the Agro-Environmental Protection Institute (Tianjin, China) and left to stand for 5 days. The specific concentrations of DBP (DEHP) were 7.64 (8.12), 15.94 (15.99), and 30.33 (30.58) mg kg−1 in the fluvo-aquic soil, 8.12 (8.05), 15.61 (15.28), and 29.72 (29.83) mg kg−1 in the brown soil, and 8.29 (8.12), 15.46 (15.69), and 29.88 (29.74) mg kg−1 in the cinnamon soil, respectively, after standing for 5 days. They were extracted and determined according to Gao et al. (2019). Then, the soils were fertilized with a water solution containing 4.29 g urea and 2.195 g KH2PO4 per pot. Jinqiang 8 wheat seeds were provided by the Agro-Environmental Protection Institute, Ministry of Agriculture (Tianjin, China). The seeds were surface-sterilized by immersion in 2.5% sodium hypochlorite for 30 min, and residual sodium hypochlorite was removed by three washes with sterile water. Subsequently, 22 wheat seeds were sown in each pot and cultured in the greenhouse at 25 °C ± 5 °C. In the seedling and jointing stages, 50 mL of water was supplied daily, and in the booting stage, 100 mL of water was supplied daily. Before the booting stage, 2.15 g urea and 1.10 g KH2PO4 were added. The rhizosphere soils were collected after the ripening stage (89 days). Wheat plants were gently removed and the rhizosphere soils were collected by gently shaking the roots to dislodge small clumps of soil adhering to the roots. Soil samples were immediately stored at −80 °C until analyses.

2. Materials and methods 2.1. Soil samples Three types of soil (0–20 cm layer) were collected in the Henan (fluvo-aquic soil with a sandy loam texture, N35°07′00.73″ and E113°42′36.65″), Shanxi (cinnamon soil with a loam texture, N37°58′ and E113°06′), and Shandong (brown soil with a loam texture, N36°12′46.27″ and E116°51′4.57″) provinces of China. They belong to Cambisols, Lixisols, and Lixisols, respectively, according to the World Reference Base for Soil Resource (IUSS Working Group WRB, 2015). No residual DBP and DEHP were detected in the soil samples. The soil samples were naturally air-dried, ground, and passed through a 10mesh sieve. The soil chemical characteristics were analyzed according to previously reported methodologies (Lu, 1999). Briefly, pH was determined with a pH electrode (FE28, Mettler Toledo, Shanghai, China), total nitrogen (TN) was digested with H2SO4 and measured by Kjeldahl digestion, available nitrogen (AN) was diffused by NaOH-hydrolyzation and measured using neutralization titration. Total phosphorus (TP) and total potassium (TK) were extracted with NaOH and analyzed by molybdenum-antimony-D-iso-ascorbic-acid colorimetry and atomic absorption spectrophotometry (Zeenet 700, Analytik-Jena AG, Jena, Germany), respectively. Available phosphorus (AP) was extracted with NaHCO3 and measured by molybdenum-antimony-D-iso-ascorbic-acid colorimetry, available potassium (AK) was extracted with ammonium acetate and analyzed by atomic absorption spectrophotometry (Zeenet 700), and soil organic matter (SOM) was measured by K2Cr2O7 oxidation–reduction colorimetry. Detailed characteristics of the soils before the start of the experiment and after wheat ripening are presented in Table 1 and Table S1, respectively.

2.4. Soil microbial DNA extraction, PCR amplification, and library construction Microbial DNA of soil samples was extracted using a FastDNA SPIN Kit for Soil (MP Biomedicals, CA, USA). DNA concentration and purity were monitored by agarose gel electrophoresis. DNA was diluted to 1 ng/μL in sterile water. The hypervariable V4 region of the 16S rRNA gene was amplified by PCR with the universal primers 515F (GTGCCAGCMGCCGCGGTAA) and 806R (GGACTACHVGGGTWTCTAAT), which detected nearly all bacterial taxa in the soil samples based on in-silico analysis. The primers used for sequencing were composed of a proper Illumina adapter, pad linker, and the gene-specific primer, and a 6-nt barcode unique to each sample was attached to the reverse primer. Detailed information regarding barcoding for each sample is provided in Table S1. All PCRs were carried out in 30-μL reactions containing 15 μL of Phusion® High-Fidelity PCR Master Mix (New England Biolabs), 0.2 μM of forward and reverse primers, and 10 ng template DNA. Thermal

2.2. Reagents DBP (≥99% purity) and DEHP (≥99% purity) were purchased from J&K China Chemical Ltd. (Beijing, China). Methanol and H2O2 (HPLC grade) were purchased from Jinke Chemical Reagent Company (Tianjin, China). Other chemicals (analytical purity) were acquired from Fengchuan Chemical Reagent Company (Tianjin, China). Table 1 Chemical properties of soil samples. Soil samples

pH

SOM(g kg−1)

TN(g kg−1)

TP(g kg−1)

TK(g kg−1)

AN(mg kg−1)

AP(mg kg−1)

AK(mg kg−1)

fluvo-aquic soil cinnamon soil brown soil

8.02 7.92 6.04

7.52 15.0 7.34

0.53 0.73 0.43

0.60 1.03 0.34

22.0 24.3 25.3

51.6 49.5 38.0

7.70 40.6 32.3

78.5 250 48.5

SOM, soil organic matter; TN, total nitrogen; TP, total phosphorus; TK, total potassium; AN, available nitrogen; AP, available phosphorus; AK, available potassium. 2

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cycles consisted of initial denaturation at 98 °C for 1 min, 30 cycles of denaturation at 98 °C for 10 s, annealing at 50 °C for 30 s, and elongation at 72 °C for 30 s, and finally, 72 °C for 5 min. PCR products were mixed with the same volume of 1× loading buffer containing SYBR green and electrophoresed on 2% agarose gels. Samples with a major, bright band at 300 bp were selected for further analyses. PCR products were mixed in equidensity ratios and then purified using a gel extraction kit (Qiagen, Hilden, Germany). Sequencing libraries were generated using a TruSeq® DNA PCR-Free Sample Preparation Kit (Illumina, San Diego, CA, USA) following the manufacturer’s recommendations, and index codes were added. Library quality was assessed on a Qubit 2.0 fluorometer (Thermo Scientific) and a Bioanalyzer 2100 (Agilent). Finally, the library was sequenced on an Illumina HiSeq 2500 platform (Illumina) at Novogene Bioinformatics Technology Co., Ltd. (Tianjin, China), and 250-bp paired-end reads were generated.

decreased with an increase in DBP concentration. Under DEHP stress, they showed an opposite trend. TN and TK contents were higher than those in the control when PAEs were added at 40 mg kg−1. In cinnamon soil, AN content showed a trend opposite to that observed in fluvoaquic soil. Although AK content declined dramatically upon DBP and DEHP addition, it was still higher under DEHP stress than in the control. In brown soil, changes in AN, AP, and AK contents were similar to those in fluvo-aquic soil. TP content in 10 and 20 mg kg−1 DEHP-treated soil was lower than that in the control. pH was the highest in fluvo-aquic soil, followed by cinnamon soil and brown soil. SOM content was significantly higher in cinnamon soil than in fluvo-aquic and brown soils. AN, AP, and TN contents in fluvoaquic soil were significantly higher than those in cinnamon and brown soils, and TP and TK contents were the highest in cinnamon soil and similar in fluvo-aquic and brown soils. 3.2. General sequencing data features

2.5. Data analysis

In total, 5,554,489 raw reads were obtained by Illumina HiSeq sequencing of the 63 soil samples, and 5,024,311 sequences were maintained after discarding short and low-quality reads, singletons, replicates, and chimeras (Table S3). Effective sequences ranged from 65,626 to 80,055 in fluvo-aquic soil samples, from 57,253 to 88,424 in cinnamon soil samples, and from 53,387 to 79,911 in brown soil samples.

After discarding the adaptor and primer sequences, paired-end reads were assigned to samples based on their unique barcodes (Table S1). Then, barcodes and primer sequences were trimmed, and the resulting reads were approximately 250 bp. Paired-end reads from the original DNA fragments were merged using FLASH (v. 1.2.7), and the splicing sequences obtained were called raw tags. Raw tags were quality-filtered using Quantitative Insights Into Microbial Ecology (QIIME, v. 1.7.0). The tags were compared with a reference database (Gold database) using the UCHIME algorithm to detect chimera sequences, which were removed. Thus, effective tags were obtained. Subsequently, sequence analysis was performed using the UPARSE algorithm (v. 7.0.1001 http://drive5.com/usearch/manual/singletons.html) to generate an operational taxonomic unit (OTU) table and select representative sequences. Briefly, UPARSE was used to dereplicate sequences and obtain representative sequences, and singletons were removed. The retained sequences were assigned OTUs at 97% similarity, and chimeras were filtered out. For each OTU, a representative sequence was selected for taxonomic annotation based on the RDP classifier (v. 2.2) algorithm using the SILVA database (v. 128). To study phylogenetic relationships among the OTUs and to identify dominant species in different samples (groups), multiple sequence alignments were conducted using MUSCLE (v. 3.8.31). OTU abundance was normalized using a standard of sequence numbers corresponding to the sample with the least sequences (the number of sequences used for subsampling was 43,737). Alpha and beta diversities were analyzed based on the normalized data. Alpha diversity indices, including Shannon, Simpson, and Evenness, and richness indices, including ACE and Chao1, were calculated with QIIME (v. 1.7.0), and data were visualized with R (v. 2.15.3). Beta diversity using weighted UniFrac was calculated with QIIME. Principal coordinate analysis (PCoA) based on UniFrac distance matrices was performed to identify and visualize principal coordinates. PCoA data were displayed using the WGCNA, stat, and ggplot2 packages in R (v. 2.15.3). Unweighted Pair-group Method with Arithmetic Means (UPGMA) Clustering was conducted in QIIME using weighted UniFrac. Correlations between alpha diversities and environmental factors were determined using Spearman’s test. Statistically significant differences between treatments were identified by one-way ANOVA (version 18.0, IBM, New York, USA). P < 0.05 was considered significant.

3.3. PAE contamination negatively affects rhizospheric alpha diversity Rarefaction analyses demonstrated that the number of OTUs per sample tended to reach a plateau after 40,000 sequences at 97% similarity (Fig. S1). The alpha diversity differed significantly between the three control soil samples (Table 2). The high Good’s coverage estimator (≥99%) indicated that bacterial OTUs were well captured in each soil sample. The OTUs in the 21 treatments ranged from 1027 to 1972, and the highest richness was observed in DBP40-treated cinnamon soil, whereas DEHP10-treated brown soil displayed considerably lower richness. The Chao1 values for all treatments ranged between 1077 and 2239. Cinnamon soil had the highest bacterial OTU number and richness. DBP-treated soils had higher bacterial OTU numbers and richness than DEHP-treated soils. Shannon index values ranged from 4.08 to 7.94. Cinnamon soil displayed the highest bacterial diversity, followed by fluvo-aquic and brown soils. Bacterial diversity in the cinnamon soil was not significantly influenced by DBP and DEHP (P > 0.05). The Shannon index value was not obviously affected by DBP (P > 0.05), whereas DEHP significantly decreased Shannon diversity in fluvo-aquic and brown soil samples (P < 0.05). Thus, the numbers of OTUs and Chao1 and Shannon indices significantly differed among the soil types. DPB had no obvious effect when compared to the control. Conversely, DEHP induced a significant decrease in richness in all three soils. 3.4. Effect of PAEs on rhizospheric microbial community and structure The dominant phyla in the three soil samples are presented in Fig. 1. Proteobacteria were the most abundant in fluvo-aquic soil samples, accounting for 51.92% (DBP10) to 74.87% (DEHP40) of total bacteria (Fig. 1a), followed by Bacteroidetes (8.84–25.12%, average: 19.85%), Firmicutes (2.61–11.91%, average: 4.31%), Actinobacteria (3.60–7.56%, average: 4.83%), Gemmatimonadetes (1.78–3.16%, average: 2.52%), and Acidobacteria (1.97–3.20%, average: 2.48%). In fluvo-aquic soil, the relative abundance of Proteobacteria increased, whereas that of Bacteroidetes decreased upon DEHP treatment when compared to the control treatment. The relative abundance of Thaumarchaeota was significantly decreased in DBP- and DEHP-treated soils (P < 0.05). Similar to the findings for fluvo-aquic soil, Proteobacteria was the most abundant phylum in cinnamon soil (Fig. 1b). Bacteroidetes and

3. Results 3.1. Soil chemical properties after PAE addition The chemical properties of the soils after wheat ripening are shown in Table S1. In fluvo-aquic soil, AN, AP, and AK contents increased significantly at 10 mg kg−1 DBP compared to the control, and 3

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Table 2 Bacterial community diversity indices in rhizosphere soils. Soil type

Treaments

alpha diversity indices OTUs

Hshannon

Chao1

Goods_coverage

Fluvo-aquic soil

CK DBP10 DBP20 DBP40 DEHP10 DEHP20 DEHP40

1577 1568 1484 1564 1392 1433 1282

± ± ± ± ± ± ±

42a 95a 145ab 47a 106bc 12ab 35c

6.94 6.89 6.29 6.76 5.97 6.15 5.83

± ± ± ± ± ± ±

0.19a 0.15a 0.45b 0.17a 0.25bc 0.17bc 0.21c

1588 1587 1506 1588 1411 1458 1293

± ± ± ± ± ± ±

51a 106a 154ab 46a 99bc 17ab 28c

0.998 0.998 0.998 0.998 0.998 0.998 0.998

Cinnamon soil

CK DBP10 DBP20 DBP40 DEHP10 DEHP20 DEHP40

1805 1860 1722 1972 1766 1720 1715

± ± ± ± ± ± ±

114ab 77ab 187ab 77a 57ab 249ab 54b

7.37 7.87 7.47 7.94 7.25 7.24 7.61

± ± ± ± ± ± ±

0.38ab 0.05ab 0.59ab 0.10a 0.50b 0.41b 0.14ab

2000 2065 1977 2239 2094 2003 1960

± ± ± ± ± ± ±

125a 97a 99a 183a 199a 399a 1a

0.992 0.992 0.992 0.991 0.990 0.991 0.992

Brown soil

CK DBP10 DBP20 DBP40 DEHP10 DEHP20 DEHP40

1387 1343 1250 1462 1027 1241 1056

± ± ± ± ± ± ±

83ab 92bc 23c 92a 60d 112c 93d

6.25 5.83 5.56 6.56 4.08 6.26 4.58

± ± ± ± ± ± ±

0.50ab 0.17bc 0.18c 0.37a 0.06e 0.14ab 0.64d

1439 1377 1284 1504 1077 1254 1095

± ± ± ± ± ± ±

70ab 106bc 34 cd 99a 60e 114d 90e

0.996 0.996 0.997 0.996 0.996 0.998 0.996

Data are the mean (n = 3) ± S.D. Different letters indicated statistically significant differences (P < 0.05) based on Duncan tests.

3.6. Relationship between microbial community structure and environmental parameters

Gemmatimonadetes had similar relative abundances in PAEs-treated and non-treated cinnamon soil samples. The relative abundance of Proteobacteria was decreased upon DBP treatment. The relative abundance of Firmicutes in DBP20 (6.84%) was higher than that in other DBP and DEHP treatments (1.51–3.92%). Compared with the control, the proportions of Proteobacteria and Firmicutes were increased in brown soil under DBP stress, whereas the proportions of Proteobacteria and Bacteroidetes were clearly decreased in the DEHP10 and DEHP40 groups (P < 0.05). The proportion of Firmicutes was significantly higher in DEHP10- and DEHP40-contaminated soil than in the control (P < 0.05).

PCoA based on OTU composition showed that the samples from each site clustered tightly and the sites were clearly differentiated (Fig. 2a). In total, 50.49% and 17.09% of the variation in the bacterial communities could be explained by the first and second principal coordinates, respectively. Based on the clustering of the samples, fluvoaquic and cinnamon soils had a more similar community composition, whereas that of brown soil was more different. The PCoA results were confirmed by weighted UniFrac distance clustering analysis at the phylum level (Fig. S2). The results showed that the fluvo-aquic and cinnamon soil groups were clustered, and were clearly separated from the brown soil group. This observation suggested that soil type was more important in determining the innate rhizosphere microbiome structure than DBP or DEHP in the current study. Bacterial communities in fluvo-aquic soil treated with DBP and DEHP were clearly separated from those in the control soil, and bacterial communities of fluvo-aquic soil treated with DBP were separated from those treated with DEHP (Fig. 2b). In cinnamon soil, bacterial community composition was not altered by DBP and DEHP treatments (Fig. 2c). Finally, bacterial communities in brown soil under DBP and DEHP treatments were grouped together and were not clearly separated from those in control soil (Fig. 2d).

3.5. Effect of PAEs on the relative abundance of different genera The relative abundances of the 35 most abundant genera in the soils are shown in Fig. 3. At the genus level, the relative abundances of Candidatus Nitrososphaera, Pontibacter, and Brevundimonas were significantly decreased upon DBP and DEHP treatments when compared with the control in fluvo-aquic soil. Additionally, the relative abundances of Bacteroides, Halobacillus, and Massilia were significantly higher in the DBP10 group than in other groups. The relative abundances of Streptomyces, Nocardioides, and Methylobacillus were significantly higher in the DEHP40 group than in other groups. In the cinnamon soil, the relative abundance of RB 41 was increased, but decreased with an increase in DBP concentration, when compared to the control. DEHP10 and DEHP20 triggered an increase in Nitrosospira, whereas DEHP40 induced a decrease in Nitrosospira. The relative abundances of Gemmatirosa and Sphingomonas were significantly increased in DEHP40-treated cinnamon soil when compared to the control (P < 0.05). In brown soil, the relative abundances of Glutamicibacter, Paenibacillus, and Cohnella were significantly decreased in DBP- and DEHP-treated soils when compared to the control (P < 0.05). Specifically, the relative abundances of Tumebacillus and Intrasporangium were significantly enhanced in DBP20 and DEHP20, respectively, compared with the control and other groups (P < 0.05). DBP40 significantly increased the relative abundances of Rhodanobacter, unidentified_Gemmatimonadaceae, Gemmationas, and Bryobacter in brown soil.

3.7. Direct and indirect impacts of PAE contamination on the bacterial community The relative contributions of environmental variables in rhizosphere soil after wheat ripening (Table S1) on bacterial community were determined using canonical correspondence analysis (CCA) and CCAbased variation partitioning analysis (VPA) (Fig. 4a). Soil pH, TN, SOM, and PAE concentration had the greatest impact on the microbial community in the three soil samples (P < 0.05), as illustrated by the longer arrows for these variables in the CCA plot. CCA-based VPA showed that soil properties and PAE concentration explained 40.77% and 2.29%, respectively, of the variation in the rhizosphere soil bacterial community. Their interaction explained 21.92% of the variation, leaving 35.02% of the variation unexplained (Fig. 4b). 4

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PCoA PC1 vs PC2

1

0.5

PC2 (17.09%)

Relative abundance

0.2

Others Deinococcus-Thermus Nitrospirae Verrucomicrobia Gemmatimonadetes Acidobacteria Thaumarchaeota Actinobacteria Firmicutes Bacteroidetes Proteobacteria

0.75

FCK FDBP10 FDBP20 FDBP40 FDEHP10 FDEHP20 FDEHP40 CCK CDBP10 CDBP20 CDBP40 CDEHP10 CDEHP20 CDEHP40 BCK BDBP10 BDBP20 BDBP40 BDEHP10 BDEHP20 BDEHP40

0.0

-0.2

0.25 -0.2

0.0

0.2

0.4

PC1 (50.49%)

0

b

brown soil)

0

0

0

EH

P4

P2 EH

D

D

D

EH

P1

40 BP D

D

BP

20

10 BP D

C

K

(a) PCoA of the bacterial communities in rhizosphere soils. (F, fluvo-aquic soil; C, cinnamon soil; B, PCoA PC1 vs PC2

0.2

1 0.1

Relative abundance

0.5

PC2 (25.45%)

Others Thaumarchaeota Nitrospirae Planctomycetes Verrucomicrobia Actinobacteria Acidobacteria Gemmatimonadetes Firmicutes Bacteroidetes Proteobacteria

0.75

CK DBP10 DBP20 DBP40 DEHP10 DEHP20 DEHP40

0.0

-0.1

-0.2

-0.3 -0.4

0.25

-0.2

0.0

0.2

PC1 (37.06%)

(b) PCoA based on weighted UniFrac distances in fluvo-aquic soils 0

D

D

EH

P4

0

P2 0 EH

P1 0 D EH

40 D BP

D BP

20

10

0.1

1

Others Planctomycetes Verrucomicrobia Chloroflexi Saccharibacteria Acidobacteria Gemmatimonadetes Actinobacteria Bacteroidetes Proteobacteria Firmicutes

Relative abundance

0.75

0.5

PC2 (12.86%)

c

D BP

C K

PCoA PC1 vs PC2

CK DBP10 DBP20 DBP40 DEHP10 DEHP20 DEHP40

0.0

-0.1

0.25

-0.2

-0.1

0.0

0.1

PC1 (48.76%) 0

0

(c) PCoA based on weighted UniFrac distances in cinnamon soils

P4 EH

PCoA PC1 vs PC2

D

D

EH

P2

0 D

EH

P1

0 BP 4 D

0 BP 2 D

10 BP D

C

K

0

Fig. 1. Relative abundances of microbial community composition at phylum level in rhizospheres soil. (a, fluvo-aquic soil; b, cinnamon soil; c, brown soil).

0.1

PC2 (9.8%)

3.8. Relationship between microbial structure and environmental parameters Mantel’s test was used to examine associations between environmental factors and bacterial community structure in the soils. AN, TP, AK, and AP were significantly associated with the fluvo-aquic soil bacterial communities, whereas TK and TN were significantly associated with the bacterial communities in cinnamon soil (P < 0.05, Table 3). AN was the most strongly correlated with fluvo-aquic soil bacterial community (r = 0.347, P = 0.008), whereas TK showed a significant positive correlation with bacterial community structure in cinnamon soil (r = 0.354, P = 0.0017).

CK DBP10 DBP20 DBP40 DEHP10 DEHP20 DEHP40

0.0

-0.1

-0.2

-0.2

0.0

0.2

PC1 (73.57%)

(d) PCoA based on weighted UniFrac distances in brown soils (caption on next page) 5

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neutral and alkaline soils, indicating that soil acidity is crucial in determining the fate and effect of PAEs in soil ecosystems. DBP/DEHP treatments triggered responses of specific bacterial groups in the three soils. All soils contained taxa that are commonly found in soil rhizospheres and that have various effects on plant health, including beneficial and pathogenic interactions (Berendsen et al., 2012). Some bacterial phyla were recovered from soils regardless of DBP/DEHP treatment, with Proteobacteria and Bacteroidetes being the dominant phyla in fluvo-aquic and cinnamon soils. The most dominant phyla in brown soil were Firmicutes and Proteobacteria. Although none of these phyla were obviously correlated with soil pH, the relative abundances of certain taxa did vary depending on pH. For example, Firmicutes were relatively more enriched in soils with lower pH, whereas Bacteroidetes were more abundant in soils with higher pH. Some genera within the phyla Gemmatimonadetes (e.g., Gemmatimonas and unidentified_Gemmatimonadaceae) and Acidobacteria (e.g., Bryobacter) were more abundant in soils with lower pH, whereas taxa from Thaumarchaeota (e.g., Candidatus Nitrososphaera) favored soils with pH 7.0–8.0. Further, relative abundances of Acidobacteria and Gemmatimonadetes were higher in soils with higher SOM content. This may be explained by the higher capacity of Actinobacteria to decompose moderately labile forms of soil organic carbon and the fast growth of Proteobacteria when readily decomposable carbon substrates are present (Trivedi et al., 2013). The relative abundances of certain genera were altered by DBP/ DEHP contamination. The relative abundances of Lysobacter (phylum Proteobacteria) and Streptomyces (phylum Actinobacteria) increased with increasing DBP/DEHP concentration in fluvo-aquic soil. These bacteria have been also detected in vegetable rhizosphere soil (Kong et al., 2018). Our results indicated that high soil concentrations of DBP/DEHP might promote the growth of DBP-degrading bacteria, while inhibiting the growth of others. This is consistent with reports by Cao et al. (2017) and Kong et al. (2018). In addition, the relative abundances of Methylobacillus (phylum Proteobacteria) and Nocardioides (family Nocardioidaceae) were significantly higher under DEHP40 treatment than under the other treatments (P < 0.05), and Methylobacillus has been

Fig. 2. PCoA of the bacterial communities in wheat rhizospheres in different soils. (a) PCoA of the bacterial communities in rhizosphere soils. (F, fluvo-aquic soil; C, cinnamon soil; B, brown soil). (b) PCoA based on weighted UniFrac distances in fluvo-aquic soils. (c) PCoA based on weighted UniFrac distances in cinnamon soils. (d) PCoA based on weighted UniFrac distances in brown soils.

4. Discussion Microbes in terrestrial environments play pivotal roles in nutrient cycling, and in agricultural systems, they influence soil characteristics and crop growth (Li et al., 2017; Kotoky et al., 2018). In general, higher soil microbe diversity leads to lower plant disease pressure and higher yield. However, soil microbial diversity is substantially affected by xenobiotic pollutants, including heavy metals and organic pollutants. To understand the influences of PAE contamination on a wheat-soil ecosystem, we investigated the effects of DBP/DEHP on indigenous microorganism diversity and structure. In this study, the soil chemical properties were altered after wheat ripening. Soil nutrient parameters, including SOM, AN, AP, TN, and TP, are vital to soil quality and indispensable to wheat growth. The above parameters, which decreased or increased under DBP/DEHP stress, were mainly affected by wheat growth; however, they may also have been affected by the physicochemical characteristics and concentration of DBP/DEHP. We found that DEHP strongly decreased OTU richness and alpha diversity of the indigenous microbial communities in fluvo-aquic and brown soils in a dose-dependent manner. This is in agreement with findings of a previous study on the effect of dimethyl phthalate on soil microbial communities (Wang et al., 2015). In the current study, DBP stress induced less severe effects on OTU richness and alpha diversity. Kong et al. (2018) found that OTUs and alpha diversity of soils declined with increasing DBP concentration. However, the OTUs and alpha diversity significantly differed among the three soils before any treatment. Additionally, brown soil had lower bacterial richness and diversity than the other two soil types. It is that brown soil has a lower pH. Consistent with our findings, Zhu et al. (2018) found that bacterial richness and diversity were lower in DEHP-polluted acidic soils than in

Fig. 3. Heatmap of the top 35 most abundant genera in each sample. F, fluvo-aquic soil; C, cinnamon soil; B, brown soil. The bacterial phylogenetic tree (left) was constructed using the neighbor-joining method. 6

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a

CCA Plot 2 TP

CCA2 (17.41%)

0

pH

TN

TK

AK

SOM

PAEs

AN AP

-2

-4

-1

0

1

cinnamon soil. Sphingomonas has been detected in acidic soil (Zhu et al., 2018) and has the ability to degrade PAEs (Liang et al., 2008). Bacteria in the genus Sphingomonadaceae, including Sphingomonas, are known to degrade aromatic compounds, and Ramlibacter harbors protocatechuic acid catabolic genes (Hickey et al., 2012). The reductions in Glutamicibacter (phylum Actinobacteria), Paenibacillus (phylum Firmicutes), and Cohnella (phylum Firmicutes) in PAE-treated brown soil suggested that DBP/DEHP exposure might negatively affect soil carbon metabolism, because these phylotypes are known to decompose organic matter (Zhu et al., 2018). Notably, Tumebacillus (order Bacillales, class Bacilli, phylum Firmicutes) was significantly increased in DBP20-treated brown soil, indicating that it is highly sensitive to medium concentrations of DBP or its metabolites (Feng et al., 2017). Du et al. (2017) isolated a Tumebacillus strain that could grow heterotrophically on complex carbon substrates from wastewater. In our study, Bacillus (phylum Gemmatimonadetes) was detected in PAE-treated brown soil. It is possible that Bacillus can use DBP/DEHP as carbon source. On the other hand, Bacillus is ubiquitous in nature, and the most common species of this genus can promote plant growth by simulating nutrient uptake by and supplying growth-promoting substances to the roots (Lucy et al., 2004). PAE-degrading strains have also been isolated from this genus (Cheng et al., 2018; Feng et al., 2017). We speculate that Bacillus may protect wheat plants by degrading DBP/DEHP. Soil characteristics, such as pH and nutrients affect microbial communities (Hu et al. 2013; Landa et al. 2013; Liu et al., 2010). Soil pH is an important determinant of the microbial community composition (Hu et al. 2013; Xu, et al., 2017). SOM provides a carbon source for microbes (Landa et al. 2013), and other nutrients may influence the biomass, activity, and composition of microbial communities (Liu et al., 2010). In the present study, microbial diversity was lower in acidic soil and higher in alkaline soil, and the relative abundances of some important phyla varied along the pH gradient. We consider that the differences in soil bacterial communities were mainly a result of soil types; the three soils were collected in different regions with different soil characteristics. Moreover, CCA indicated that soil pH had the strongest influence on the functional diversity of soil microbial communities, followed by TN and SOM. Wu et al. (2017) found that pH not only affected microbial diversity of soils polluted by polycyclic aromatic hydrocarbon, but also shaped bacterial community composition. Xu et al. (2017) have also demonstrated that different soil types have diverse bacterial communities. Liu et al. (2010) found that soil N availability is a major factor affecting the functional diversity of soil microbial communities in Hulunbeir, Inner Mongolia, northern China. In addition, PAEs may marginally affect microbial communities, which may result in different changes in same bacterial communities. Some significant differences in bacterial communities under different PAE stresses and concentrations were observed in our study, possibly resulting from the negative effect of PAEs on soil nutrients. Likewise, Kong et al. (2018) found that DBP contamination caused adverse effects on soil quality, including TN, TP, and total carbon content, which in turn significantly affected the rhizosphere bacterial communities. The mechanism of action of PAEs on soil microbial communities requires further investigation.

FCK FDBP10 FDBP20 FDBP40 FDEHP10 FDEHP20 FDEHP40 CCK CDBP10 CDBP20 CDBP40 CDEHP10 CDEHP20 CDEHP40 BCK BDBP10 BDBP20 BDBP40 BDEHP10 BDEHP20 BDEHP40

2

CCA1 (54.79%)

Fig. 4. CCA of the correlations between rhizosphere soil bacterial communities and environmental variables (a) and CCA-based VPA of bacterial communities explained by soil properties (b). F, fluvo-aquic soil; C, cinnamon soil; B, brown soil. Table 3 Mantel analysis of the relationships between rhizosphere soil bacterial community structure and environmental variables. Environmental factors

pH SOM AN AP AK TN TP TK PAEs

Fluvo-aquic soil

Cinnamon soil

Brown soil

r

P

r

P

r

P

0.106 0.132 0.347 0.224 0.274 0.072 0.314 0.110 0.094

0.175 0.189 0.008 0.034 0.006 0.670 0.012 0.877 0.103

0.004 0.026 0.054 0.015 0.026 0.274 0.196 0.354 0.084

0.440 0.573 0.291 0.513 0.351 0.019 0.092 0.017 0.216

0.030 0.041 0.017 0.043 0.083 0.058 0.043 0.008 0.057

0.337 0.262 0.345 0.229 0.127 0.727 0.294 0.495 0.701

SOM, soil organic matter; AN, available nitrogen; AP, available phosphorus; AK, available potassium; TN, total nitrogen; TP, total phosphorus; TK, total potassium.

5. Conclusions

demonstrated to be able to degrade DBP (Kumar and Maitra, 2016). The family Nocardioidaceae may be related to DEHP degradation in neutral soils (Zhu et al., 2018). However, the relative abundances of Pontibacter (phylum Proteobacteria) and Candidatus Nitrososphaera decreased with increasing DBP/DEHP concentration in fluvo-aquic soil. Pontibacter have previously been demonstrated to be advantageous to soil health (Xu et al., 2014; Poehlein et al., 2015; Zhu et al., 2018). DBP induced obvious changes in RB 41 and Nitrosospira, and DEHP caused significant increases in Gemmatirosa and Sphingomonas in

In the present study, the responses of wheat rhizosphere microorganisms to PAEs in three types of soils were investigated in a pot experiment. We found that application of DEHP decreased OTU richness and bacterial diversity in fluvo-aquic and brown soils, whereas DBP stress had no significant effect in the three soils. The relative percentages of some bacterial families related to plant growth were decreased upon DBP/DEHP treatment. The bacterial community structure of wheat rhizosphere soils was obviously altered by DBP/ DEHP pollution, whereas the relative abundances of some genera 7

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associated with PAE degradation were increased. Additionally, the soil bacterial community was obviously influenced by the DBP/DEHP concentration, whereas changes in the rhizosphere soil bacterial community were significantly associated with soil properties. Our results suggest that DBP/DEHP contamination affects wheat rhizosphere microbial metabolism and biodiversity, although the effect of PAEs on rhizosphere microbial metabolism and biodiversity is smaller than the differences between soils, and that the effects of the pollutants are soildependent. Our findings will be helpful in understanding the degradation and transformation of organic pollution in agricultural systems.

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Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Acknowledgments This work was funded by the National Natural Science Foundation of China (Nos. 41877362 and 41671482), STU Scientific Research Foundation for Talents (No. NTF19026), and Natural Science Foundation of Henan Province of China (No. 182300410055). Appendix A. Supplementary data Supplementary data to this article can be found online at https:// doi.org/10.1016/j.geoderma.2019.114126. References Berendsen, R.L., Pieterse, C.M., Bakker, P.A., 2012. The rhizosphere microbiome and plant health. Trends Plant Sci. 17, 478–486. Cao, X.L., Diao, M.H., Zhang, B.G., Liu, H., Wang, S., Yang, M., 2017. Spatial distribution of vanadium and microbial community responses in surface soil of panzhihua mining and smelting area, china. Chemosphere 183, 9–17. Chao, W.L., Cheng, C.Y., 2007. Effect of introduced phthalate-degrading bacteria on the diversity of indigenous bacterial communities during di-(2-ethylhexyl)phthalate (DEHP) degradation in a soil microcosm. Chemosphere 67 (3), 482–488. Chao, W.L., Hsu, S.F., 2004. Response of the soil bacterial community to the addition of toluene and toluene-degrading bacteria. Soil Biol. Biochem. 36, 479–487. Cheng, J.J., Liu, Y.A., Wan, Q., Yuan, L., Yu, X.Y., 2018. Degradation of dibutyl phthalate in two contrasting agricultural soils and its long-term effects on soil microbial community. Sci. Total Environ. 640, 821–829. Dankova, R., Jarošova, A., Polakova, Š., 2013. Monitoring of phthalates in Moravian agricultural soils in 2011 and in 2012. MendelNet 563–567. Du, S.Y., Yu, M., Li, F.H., Xiao, L.L., Zhang, H.X., Tao, J., Gu, W., Gu, J.Y., Chen, Q., 2017. Effect of facility management regimes on soil bacterial diversity and community structure. Chinese J. Eco-Arg. 25 (11), 1615–1625. Feng, N.X., Yu, J., Mo, C.H., Zhao, H.M., Li, Y.W., Wu, B.X., Cai, Q.Y., Li, H., Zhou, D.M., Wong, M.H., 2017. Biodegradation of di-n-butyl phthalate (DBP) by a novel endophytic Bacillus megaterium strain YJB3. Sci. Total Environ. 616, 117–127. Gao, M.L., Xu, Y.L., Dong, Y.Y., Song, Z.G., Liu, Y., 2019. Accumulation and metabolism of di(n-butyl) phthalate (DBP) and di(2-ethylhexyl) phthalate (DEHP) in mature wheat tissues and their effects on detoxification and the antioxidant system in grain. Sci. Total Environ. 697, 133981. He, Y., Xu, J.M., Tang, C.X., Wu, Y.P., 2005. Facilitation of pentachlorophenol degradation in the rhizosphere of ryegrass (Lolium perenne L.). Soil Biol. Biochem. 37, 2017–2024. Hickey, W.J., Chen, S., Zhao, J., 2012. The phn island: a new genomic island encoding catabolism of polynuclear aromatic hydrocarbons. Front. Microbiol. 3, 125. Hu, H.W., Zhang, L.M., Dai, Y., Di, H.J., He, J.Z., 2013. pH-dependent distribution of soil ammonia oxidizers across a large geographical scale as revealed by high-throughput pyrosequencing. J. Soils Sediments 13, 1439–1449.

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