Next Article in Journal
Abiotic Stress in Cotton: Insights into Plant Responses and Biotechnological Solutions
Previous Article in Journal
Coupling Coordination and Spatial–Temporal Evolution of the Water–Land–Ecology System in the North China Plain
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Agriculture
Volume 14
Issue 9
10.3390/agriculture14091637
agriculture-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Response of Bacterial Community Structure and Function in Rhizosphere Soil on the Photosynthesis of Selected Plant Types C3 and C4 under Bis(2,4,6-tribromophenoxy) Ethane Exposure

by
Yixuan Chen
1,
Sen Wang
1,*,
Yuru Li
1,
Wanyu Liu
1,2 and
Zhenchuan Niu
3
1
Shaanxi Key Laboratory of Earth Surface System and Environmental Carrying Capacity, College of Urban and Environmental Science, Northwest University, Xi’an 710127, China
2
Interdisciplinary Research Center of Earth Science Frontier, Beijing Normal University, Beijing 100875, China
3
Institute of Global Environmental Change, Xi’an Jiaotong University, Xi’an 710049, China
*
Author to whom correspondence should be addressed.
Agriculture 2024, 14(9), 1637; https://doi.org/10.3390/agriculture14091637
Submission received: 30 July 2024 / Revised: 13 September 2024 / Accepted: 16 September 2024 / Published: 18 September 2024
(This article belongs to the Topic Plant-Soil Interactions, 2nd Volume)
Browse Figures
Versions Notes

Abstract

:
This study investigated the response of a bacterial community’s structure and function in the rhizosphere soil of C3 and C4 plants under bis(2,4,6-tribromophenoxy) ethane (BTBPE) exposure. The bacterial community composition was determined using 16S rRNA sequencing, while FAPROTAX and PICRUSt 2 were employed for functional predictions. Results showed significant differences between C3 and C4 plants in terms of bacterial community structure. C3 plants exhibited higher abundances of Proteobacteria, Bacteroidetes at the phylum level and Sphingomicrobium at the genus level, compared to C4 plants. Conversely, C4 plants had higher abundances of Actinobacteria and Patescibacteria at the phylum level and Nocardioides at the genus level. LEfSe and function prediction analyses revealed that the rhizosphere soil bacteria in C3 plants exhibited significantly higher enrichment in nitrogen fixation functions (p < 0.05), whereas C4 plants showed a significantly higher relative abundance of bacteria and functions related to organic pollutant degradation (p < 0.05). These findings suggest that the rhizosphere soil bacteria of C3 plants exhibit a stronger response to BTBPE exposure in nitrogen metabolism-related processes, while C4 plants possess superior biodegradation ability compared to C3 plants.

1. Introduction

Brominated flame retardants (BFRs) are widely used in various industries such as plastics, furniture, building materials, textiles, and electronics due to their superior flame-retardant properties [1]. However, the toxicity and environmental persistence of traditional BFRs have led to their prohibition by several countries [2]. The mixture of penta-and octa-PBDE, consisting of tetra- through hepta-BDEs, has been designated as persistent organic pollutants (POPs) under the 2009 Stockholm Convention, with deca-BDE also listed as a POP since 2017 [3,4]. Consequently, novel brominated flame retardants (NBFRs) like decabromodiphenylethane (DBDPE) and bis(2,4,6-tribromophenoxy) ethane (BTBPE) have emerged as substitutes for traditional BFRs [5,6]. However, recent research has raised concerns about the release of NBFRs into the environment during production and use, resulting in environmental pollution [7]. The accumulation and toxicity of the NBFRs have become significant issues [4] with detection reported in the atmosphere [8], water [9], soil [10], dust [11], and humans [12]. In the soil of Guiyu farmland in China, BTBPE concentrations (0.43–15 ng g−1) [12] were lower than those in Australian manufacturing soils (not detected (nd)–63.8 ng g−1 dry weight (dw)) [13]. In estuarine sediment samples, BTBPE (nd–0.62 ng g−1 dw) was detected in 96% of cases [14]; it was found in at least 90% of human serum samples and concentrations ranging from nd to 229 ng g−1 lipid weight (lw) [4]. Zheng et al. reported BTBPE in the hair of people in e-waste workplaces in urban and rural areas in Southern China (nd–1.69 ng g−1), with occupational e-waste recycling workers showing higher concentrations (0.15–29.2 ng g−1 dw) than non-occupational exposed residents (nd–2.55 ng g−1 dw) [15]. BTBPE is also present in the general population of breast milk in China, Norway, Canada and Pakistan, with concentrations ranging from nd to 2.56 ng g−1 lw, nd to 0.99 ng g−1 lw, nd to 0.99 ng g−1 lw and 0.2 to 8 ng g−1 lw [16,17,18,19,20]. Researchers have found that BTBPE exposure in vivo or outside the body can harm health, is thyrotoxic to humans and can also cause intestinal and liver damage [4,21,22]. Consequently, attention should be given to the potential health risks of BTBPE, with the assessment of health risk exposure emphasizing dust absorption through the skin as the primary route of ingestion of flame retardants into the human body [23].
Soil, a crucial component for maintaining the Earth’s ecological balance [24], serves as a reservoir for a significant accumulation of POPs [25]. Consequently, the presence of POPs in soil stands out as a formidable environmental challenge. Microorganisms play a vital role in soils by facilitating the decomposition of plant debris and organic pollutant, thus guiding the majority of Earth’s biogeochemical cycles [26,27]. The root exudates from plants can modify the physicochemical properties of rhizosphere soils, influencing the composition and abundance of rhizosphere microorganisms [28]. Rhizosphere microorganisms are particularly noteworthy for their ability to enhance cellular metabolism and degrade organic pollutants [29,30]. Examples include ryegrass and sunflower altering the soil bacterial structure, thereby promoting the degradation of polycyclic aromatic hydrocarbons (PAHs) in the soil [31,32]. The rhizosphere effect of a mangrove forest significantly influences the degradation of di-2-ethylhexyl phthalate (DEHP) [33]. Moreover, microorganisms demonstrate the capability to convert BFRs into low-brominated BFRs, hydroxylated BFRs, or methylated BFRs [34,35,36]. P. ostreatus can degrade 99% of bisphenol A (BPA) at an initial concentration of 10 mg L−1 in 7 days, Trametes versicolor can degrade 67% of decabromodiphenyl ether (BDE-209), and DBDPE could be degraded to hydroxyl by P. ostreatus through hydroxylation and oxidation [37,38,39,40].
Different plant species exhibit specific variations in the activity and species composition of rhizosphere microorganisms [41,42]. Based on the initial products and characteristics of carbon metabolism in the CO2 assimilation process, plants are classified as C3 or C4. C3 plants produce 3-phosphoglycerate (PGA) as their initial product, while C4 plants produce malic acid or aspartic acid. Common C3 plants in nature include Triticum aestivum L., Oryza sativa L., Glycine max (L.) Merr., Medicago sativa L., etc. In contrast, examples of C4 plants are Zea mays L., Setaria italica (L.) Beauv., Amaranthus tricolor L., Setaria viridis (L.) Beauv., etc. Distinct differences in rhizosphere microorganisms between C3 and C4 plants can be attributed to various in photosynthesis and root exudates [43,44]. For example, studies have found that C4 plants exhibit higher levels of amino acids and organic acids in their root exudates, while C3 plants have higher carbohydrate content [45,46]. Studies have shown that Medicago sativa L. and Amaranthus tricolor L. possess bioremediation capacities, while Lolium perenne L. and Setaria italica (L.) Beauv. can mitigate the effects of pollutants on soil [47,48]. Additionally, Glycine max (L.) Merr., and Zea mays L. influence soil function by altering the rhizosphere microorganism community structure [49]. In this study, soil pot experiments were conducted with BTBPE as the research object, and C3 plants (Triticum aestivum L. (TA), Glycine max (L.) Merr. (GM), Medicago sativa L. (MS) and Lolium perenne L. (LP)) and C4 plants (Setaria italica (L.) Beauv. (SI), Zea mays L. (ZM) and Amaranthus tricolor L. (AT)) were chosen as model plants. The primary aim of this study was to analyze the response of a rhizosphere soil bacterial community structure of C3 and C4 plants under BTBPE exposure using 16S rRNA sequencing technology. Additionally, Functional Annotation of Procaryotic Taxa (FAPROTAX) and Phylogenetic Investigation of Communities by Reconstruction of Unobserved States 2 (PICRUSt 2) were employed to predict the functional response of the rhizosphere soil bacterial community of C3 and C4 plants under BTBPE exposure. This study compared the changes and differences of rhizosphere bacterial community and function of C3 and C4 plants under BTBPE exposure. This exploration of soil microbial community structure and function prediction holds significant implications for the plant-microbial remediation of soil contaminated with BTBPE.

2. Materials and Methods

2.1. Chemicals

BTBPE (HPLC, 99.7% purity) was purchased from J&K Scientific company, Hong Kong, China. Tetrahydrofuran, acetone and toluene were chromatographically pure.

2.2. Pot Experiment

Loessial soil (calcic cambisol, WRB), free of BTBPE, was collected from deep soil in Chang’an district of Xi’an city, China (34°8′41″ N, 108°52′28″ E). Its basic physicochemical properties were as follows: pH 7.75, 7.58 g·kg−1 organic carbon, 0.68 g·kg−1 total nitrogen content, 4.95 mg·kg−1 available phosphorus, and 172 mg·kg−1 available potassium. A total of 2 mg of BTBPE was dissolved in a mixed solvent (tetrahydrofuran/acetone/toluene, 3:2:5) with a total volume of 120 mL [50] after 50 min of ultrasound treatment, and the pollution solution was prepared. The BTBPE pollutant was artificially added to the soil and thoroughly mixed. The mixture was placed in a fume hood for 48 h and then allowed to equilibrate in a room for a month. The concentration of BTBPE-contaminated soil was 100 ng g−1 dw.
Seeds of the C3 plant, namely Setaria italica (L.) Beauv. (SI), Zea mays L. (ZM) and Amaranthus tricolor L. (AT), as well as C4 plant, including Triticum aestivum L. (TA), Glycine max (L.) Merr. (GM), Medicago sativa L. (MS) and Lolium perenne L. (LP) were obtained from the Chinese Academy of Agricultural Sciences. Seeds of uniform size, full and shiny, were selected, soaked in 3% (V/V) hydrogen peroxide (H2O2) for 20 min, cleaned with distilled water, and placed on moist filter paper. H2O2 increases the germination rate of seeds [51,52]. The seeds were then incubated in a dark incubator (PGX-450D, Saifu instruments, Ningbo, China) at 25 °C for 24 h.
The experiment was conducted in an intelligent light culture chamber from November 2019 to January 2020. Each pot was filled with 800 g BTBPE-contaminated soil, with an additional 0.5 cm layer of uncontaminated soil on the surface.
Fertilizer (N 28 mg kg−1, P 32 mg kg−1, K 30 mg kg−1) was added every two weeks in the form of a solution. Seeds with consistent germination after dark cultivation were selected for planting. Based on seed germination rates, biomass variations, pot size, actual agricultural practices, and studies, we chose different numbers of seeds for each plant [53]. The initial numbers of seeds for SI, ZM, AT, TA, GM, MS and LP were 30, 10, 40, 20, 15, 40 and 40, respectively. Ten days after germination, seedlings were thinned to 20, 5, 20, 12, 6, 18 and 24, respectively, to achieve an approximately equivalent amount of plant biomass per pot. The pot experiment was conducted in an intelligent illumination incubator for 72 d. Lighting conditions are 14 h of daylight at 25 °C with an illuminance of 18,000 lux; followed by 10 h of darkness at 20 °C with no illumination. The pots were randomly positioned and changed daily. The experiment was divided into the experimental group and control group. The experimental group had different plants in BTBPE-contaminated soil. The control group had uncontaminated soil without plants (CK) (only the same solvent was added) and BTBPE-contaminated soil without plants (CK1), each with three replicates. After 72 d, rhizosphere soil samples were collected and stored at −20 °C.

2.3. Soil DNA Extraction, Bacterial 16S rRNA Gene Amplification, Sequencing and Bioinformatic Analysis

The 16S rRNA sequencing protocol was referred to Ge et al.’s method [47]. Before sequencing, sample quality was assessed, and all samples passed the quality test, classified as Class A, indicating correct PCR product band size for sequencing analysis. The experiment comprised four main steps: 1. DNA Extraction: Genomic DNA was extracted and confirmed by 1% agarose gel electrophoresis. 2. PCR Amplification: The 16S V3-V4 was amplified using the following primers: forward primer 338F (5′-ACTCCTACGGGAGGCAGCAG-3′) and reverse primer 806R (5′-GGACTACNNGGGTATCTAAT-3′). The PCR was carried out on an ABI 9700 PCR instrument (Applied Biosystems, Waltham, MA, USA) using 25 μL reaction volumes, containing 12.5 μL 2×Taq PCR MasterMix (Vazyme Biotech Co., Ltd., Nanjing, China), 3 μL BSA (2 ng μL−1), 1 μL forward primer (5 μM), 1 μL reverse primer (5 μM), 2 μL template DNA and 5.5 μL ddH2O. The PCR conditions were as follows: initial denaturation at 95 °C for 5 min; 28 cycles of denaturation at 95 °C for 45 s; annealing at 55 °C for 50 s; and elongation at 72 °C for 45 s with a final extension at 72 °C for 10 min [54]. PCR products were detected by 1% agarose gel electrophoresis and purified by Agencourt AMPure XP (Beckman Coulter, Inc., Brea, CA, USA) nucleic acid purification kit. 3. Library Construction: Miseq libraries were constructed. 4. Miseq sequencing: Sequencing was performed using Illumina Miseq (Illumina, Beijing, China). Raw sequencing date were processed by Beijing Auwegene Tech, Ltd. (Beijing, China). Raw data were filtered and spliced using PEAR (v 0.9.6) software [55]. Sequences with ambiguous base-calls (N) were removed, and the parts of the reads with low quality score (≤20) were trimmed. During splicing, the minimum overlap was set to 10 bp, with a p-value of 0.0001. After splicing, Vsearch [56] (v 2.7.1) software was employed to remove chimeric sequences using the Denovo method. Qualified sequences were denoised into amplicon sequence variants (ASVs) using Unoise3 [57] algorithm in Usearch (v 10.0.240) software. Then, high-quality sequences were clustered at 100% similarity using the Quantitative Insights into Microbial Ecology (QIIME 2, v 2024.5). Taxonomic assignment was performed using Greengene database (http://greengenes.lbl.gov, accessed on 29 August 2024).

2.4. Function Prediction

Function prediction of bacterial communities in soil was carried out using FAPROTAX, and PICRUSt 2. ASVs taxa were then compared with the FAPROTAX function annotation database (http://www.loucalab.com/archive/FAPROTAX/, accessed on 30 August 2024) to derive functional predictions for the corresponding bacteria [58]. FAPROTAX integrates functions for over 4600 species, encompassing more than 7600 functional annotations, primarily predicting elemental cycle processes such as carbon, nitrogen and sulfur. Functional groups in FAPROTAX predictions might be nested, reflecting associations of an ASV taxon with multiple functions.
The PICRUSt 2 function forecast method was mainly based on Langille et al.’s work with improvements [59]. PICRUSt 2 is a second-generation building on PICRUSt’s functional forecast. It employs evolutionary models to predict metagenomics from 16S data and reference genome databases, enriching 16S data in the KEGG database (https://www.genome.jp/kegg/, accessed on 30 August 2024) to obtain the corresponding KEGG function pathways and complete functional predictions.

2.5. Statistical Analysis

The α-diversity index Chao 1 was used to analyze microbial richness, and Phylogenetic Diversity (PD)_whole_tree, and Shannon and Simpson indices were used to analyze microbial diversity. Partial Least Squares Discriminant Analysis (PLS-DA) and non-metric multidimensional scaling (NMDS) were used for β-diversity analysis. All statistical analyses were performed using SPSS 25. One-way analysis of similarities (ANOSIM) was used to test the differences between the C3 and C4 treatment groups, showing significantly greater differences between groups than within groups (p < 0.05). Significance analysis was conducted using Analysis of Molecular Variance (AMOVA), Wilcoxon rank-sum test and Kruskal–Wallis test, with significance set at p < 0.05 [60]. The Linear Discriminant Analysis Effect Size (LEfSe) method was conducted to analyze differences in the composition of rhizosphere soil bacteria under C3 and C4 plant treatments. Kruskal–Wallis was used to detect species with significant differences in abundance between different groups. Wilcoxon rank-sum test was used to analyze the differences between groups. The Linear Discriminant Analysis (LDA) was then used to evaluate the influence of species with significant differences [61]. Functional predictions were made using PICRUSt 2 and FAPROTAX, with results analyzed by STAMP [62]. Data compilation was performed using Microsoft Excel (v 16.88), and graphs were generated using Origin 2024.

3. Results and Discussion

3.1. Species Richness and Diversity Index of Bacteria in Rhizosphere Soil of C3 and C4 Plants

3.1.1. ASV Distribution of Rhizosphere Soil Bacteria

Following sequencing, the data were utilized to generate ASVs (Amplicon Sequence Variants) by QIIME 2. A total of 3469 ASVs were generated, with 3437 remaining after leveling. Table S1 showed the number of ASVs of bacteria in rhizosphere soil of different treatments. The analysis of bacterial ASVs in the rhizosphere soil of different plant species (Table 1) revealed a significant increase in the number of ASVs in rhizosphere soil bacteria after planted Amaranthus tricolor L. (AT) compared to unplanted BTBPE-contaminated soil (p < 0.05). By analyzing the ASV distribution of rhizosphere soil bacteria under C3 and C4 plant treatments (Figure S1), the results showed that the total number of ASVs in the BTBPE-contaminated soil without plant control group, C3 plant treatment group and C4 plant treatment group was 661. The number of unique ASVs in BTBPE-contaminated soil without plant control group, C3 plant treatment group and C4 plant treatment group was 518, 752 and 485, respectively. The order of ASVs under different treatments was as follows: C3 > C4 > CK1. This suggested that planting plants significantly elevated the number of ASVs of soil bacteria, with a more pronounced change in ASVs for the C3 plant compared to the C4 plant. Plant root exudates significantly influence the abundance and composition of rhizosphere microbial communities [63]. The exudates from C3 and C4 plants differ in content and composition, including vitamins and amino acids, leading to distinct changes in ASV profiles between the two plant types [64].

3.1.2. α-Diversity of Rhizosphere Soil Bacteria

The α-diversity index of soil bacteria in the rhizosphere of C3 and C4 plants was analyzed (Table 1, Figure 1 and Figure S2). Regarding richness, both the Chao1 and Observed_species indices followed a similar pattern, with C3 plants exhibiting higher richness compared to C4 plants (C3 > C4). In terms of phylogenetic diversity, the Phylogenetic Diversity (PD)_whole_tree index indicated that C4 plants had greater phylogenetic diversity than C3 plants (C4 > C3). For community diversity, the Shannon index ranked C3 plants higher than C4 plants (C3 > C4). There was no significant difference in microbial diversity, community diversity and ecosystem stability among C4 and C3 plants, and CK1 (p > 0.05). While both C3 and C4 plants influenced bacterial richness and diversity in the rhizosphere soil, no significant difference was found between C3 and C4 plants.

3.1.3. β-Diversity of Rhizosphere Soil Bacteria

The non-metric multidimensional scaling (NMDS) analysis of rhizosphere soil bacteria of different plant species is presented in Figure 2a. The distance between samples in the NMDS plot indicated the dissimilarity in soil bacterial community structure: the greater the distance, the more pronounced the difference. Planting altered the soil rhizosphere bacterial community structure. Notably, the response of TA to BTBPE-contaminated soil bacterial community structure was significantly different from that of other plants. Similar distances were observed between the rhizosphere soil samples of MS and LP, and GM and AT, indicating similar soil bacterial community structures among these pairs. Figure 2b showed the NMDS analysis of rhizosphere soil bacteria for C3 and C4 plants, demonstrating that C3 and C4 plants had a significant impact on the microbial communities in the contaminated soils. Partial Least Squares Discriminant Analysis (PLS-DA) was conducted on different rhizosphere soil samples to evaluate the impact of BTBPE on bacterial community dynamics. Clear differences in bacterial community structure were observed between planted and unplanted soil, as well as between BTBPE-contaminated and uncontaminated soil. The results of PLS-DA analysis showed that the rhizosphere soil bacteria of BTBPE-contaminated soil without plant control group, C3 plant treatment group and C4 plant treatment group could be completely separated (Figure 2c), indicating that C3 and C4 plants changed the community structure of soil bacteria, and there was a big difference in the community structure of rhizosphere soil bacteria between C3 and C4 plants. For different plants, the bacterial community structure of AT rhizosphere soil was different from that of other plants (Figure 2c). Both C3 (SI, ZM, AT) and C4 (TA, GM, MS, LP) plants induced changes in the soil bacteria community structure, with differences between the rhizosphere soil of the C3 and C4 plants (Figure 2d). This divergence may be attributed to variations in the composition of plant root exudates. Previous studies have reported that the root exudates of C4 plants have higher levels of amino acids and organic acids, while C3 plants exhibited higher levels of carbohydrates [45]. Rhizosphere soil bacteria from C3 plants demonstrated a more dispersed distribution, concentrating on principal component 2. In contrast, rhizosphere soil bacteria of C4 plants exhibited a closer distribution on principal component 2, with substantial distances between sample groups and a stratified distribution. Overall, the degree of aggregation of rhizosphere soil bacteria in the C3 plant treatment group was higher than that in C4 plants, indicating a less distinct difference in the community structure of rhizosphere soil bacteria among different C3 plants and a more pronounced difference among different C4 plants.

3.2. Species Composition of Bacteria in Rhizosphere Soil of C3 and C4 Plants

3.2.1. Taxonomic Composition of Bacterial Community in Rhizosphere Soil of C3 and C4 Plants

Statistical analysis of soil bacteria at various taxonomic levels in different treatment groups revealed differences in the bacterial community composition (Table S2). Table 2 demonstrated the number of newly emerging bacteria at different taxonomic levels in different plant treatment groups compared to the BTBPE-contaminated soil without plants (CK1). Each experimental group exhibited new bacterial populations. Among the plant species, ryegrass (LP) had the highest number of soil microorganisms across all taxonomic levels, indicating that the bacterial community composition in rhizosphere soil of ryegrass was the most responsive to BTBPE exposure.

3.2.2. Composition Characteristics of Bacterial Phylum in Rhizosphere Soil of C3 and C4 Plants

The top five bacteria phyla in the rhizosphere soil of both C3 and C4 plants were Proteobacteria, Actinobacteria, Bacteroidetes, Patescibacteria and Verrucomicrobia (Figure 3a). Actinobacteria, Proteobacteria, Patescibacteria and Bacteroidetes together accounted for over 90% of the total bacterial population. These findings align with the results of Zhang et al., who reported similar bacterial dominance (Proteobacteria, Acidobacteria, Bacteroidetes and Actinobacteria) in soils contaminated with pollutants such as cadmium (Cd) and 3-(3.5-dichlorophenyl)-N-isopropyl-2.4-dioxo-imidazolidine-l-carboxamide (iprodione) [65]. Compared to the control group of BTBPE-contaminated soil without plants (CK1), planting plants increased the richness of certain bacterial groups. Specifically, the relative abundances of Proteobacteria and Verrucomicrobia under plant treatments were significantly higher than those in the CK1 (p < 0.05), while the relative abundances of Patescibacteria and Chloroflexota were also elevated compared to CK1. Similarly, Sivaram et al. found that planting C3 and C4 plants in PAH-contaminated soil altered the rhizosphere bacterial community structure, increasing the richness of soil bacterial community and expanding the bacterial phyla from 4 to 21 [66].
A comprehensive analysis of bacterial phylum composition in rhizosphere soil under C3 and C4 plant treatments revealed distinctive differences (Figure 3b). C3 plants exhibited higher relative abundances of Proteobacteria, Bacteroidetes, Verrucomicrobia and Cyanobacteria compared to C4 plants. While C3 plants demonstrated lower relative abundances of Actinobacteria, Patescibacteria, Chloroflexota, Acidobacteriota and Gemmatimonadetes compared to C4 plants. Notably, Proteobacteria dominated in the rhizosphere soil bacteria of both C3 and C4 plants, comprising 42% and 35% of the relative abundance, respectively. Actinobacteria accounted for 31% and 33%, while Bacteroidetes constituted 11% and 9%. These dominant phyla (Proteobacteria and Actinobacteria), known for containing plant growth-promoting rhizobacteria (PGPR), such as Alphaproteobacteria and Actinobacteria, are crucial for plant health [67,68]. Additionally, Proteobacteria and Bacteroidetes have demonstrated efficacy in degrading diesel fuel in soil [69,70]. Under persistent organic pollutant stress, Bacteroidetes is induced. For instance, studies have revealed that during the joint degradation of BDE-209 by plant-rhizosphere microorganisms, the proportion of Proteobacteria in sediments increases [71]. In the remediation of co-contaminated soil with heavy metals and organic pollutants using Medicago sativa L (MS), there was an observed increase in the relative abundance of Bacteroidetes in rhizosphere soil bacteria [65]. Additionally, Proteobacteria, Actinobacteria and Bacteroidetes have demonstrated effectiveness in the biodegradation of hydrocarbons in previous research [72]. According to Ye et al., Proteobacteria played a significant role in the nitrogen cycle [73]. It was found that the proportion of 14C respiration in C3 plants was higher than that in C4 plants, and respiration was positively correlated with the nitrogen content of rhizosphere [74]. Based on the above analysis, C3 plants are inferred to enhance nitrogen recycling in the soil more effectively, while C4 plants display stronger biodegradation capabilities.

3.2.3. Composition Characteristics of Bacterial Genus in Rhizosphere Soil of C3 and C4 Plants

At the genus level, most microbial taxa were detected (94–96%), but some were not identified (Figure 3c,d). A total of 594 bacterial genera were identified in the rhizosphere soil of C3 and C4 plants. Figure 3c showed the distribution of the 20 major bacterial genera, each with relative abundances exceeding 1%. The top 10 genera identified were Nocardioides, Sphingomicrobium, Chryseotalea, Glycomyces, Pseudarthrobacter, Lysobacter, UBA5946, Promicromonospora, Kribbella and Lentzea. Among the three treatments (CK1, C3 and C4), 125 bacterial genera exhibited significant differences, with 38 genera showing particularly notable distinctions, including Sphingomicrobium, Devosia, Pseudaminobacter, Sinorhizobium, Pseudarthrobacter, etc. (p < 0.01). Comparative analysis with CK1 revealed the appearance of 195 new genera in the rhizosphere soil bacteria of C3 plants and 157 new genera in C4 plants, with 89 bacterial genera disappearing under C3 and C4 plant treatments. Notably, C3 and C4 plant treatments increased the relative abundance of organic pollutant-degrading bacteria, such as Lysobacter, Glycomycetes and Nocardioides, which were the top three in relative abundance of bacteria under all plant treatments except SI. Moreover, its relative abundance in rhizosphere soil bacteria of LP (7%) and TA (7%) was higher than that of other plants, and it had a certain degradation ability of exogenous organic pollutants [75,76].
At the genus level, the rhizosphere soil of C3 plants exhibited a higher abundance of Glycomyces, Sphingopyxis, Pseudarthrobacter, Devosia, Daejeonella, Massilia, Methylotenera and Allosphingosinicella compared to C4 plants. In contrast, the abundance of Nocardioides, UBA5946, Promicromonospora, Lentzea, Kribbella, Actinosynnema, Streptomyces, Tabrizicola, Pedobacter, Pseudomonas and Limnobacter was lower in C3 plants than in C4 plants. It was also found that the relative abundance of Sphingopyxis in BTBPE-contaminated rhizosphere soil increased by 0.68–2.20% after planting [76]. Regarding the distribution of organic pollutant-degrading bacteria in the rhizosphere soil of C3 and C4 plants, the proportion of these bacteria in C4 plants was generally higher than in C3 plants, except for Stenotrophomonas. The relative abundance of organic pollutant-degrading bacteria, such as Nocardioides, Streptomyces and Pseudomonas, was 1.04, 1.52, and 3.77 times higher, respectively, in the rhizosphere soil of C4 plants compared to C3 plants. These results suggested that C4 plants possess significant potential for BTBPE degradation compared to C3 plants.
This finding was consistent with previous research by Sivaram et al., which indicated a higher relative abundance of PAH-degrading bacteria in the rhizosphere soil of C4 plants, highlighting their superior capacity for PAH degradation compared to C3 plants [66]. Also, Pseudomonas have been found to degrade benzene, toluene, ethylbenzene and xylene (BTEX) compounds [77].

3.3. Analysis of Differences in Bacterial Species Composition in Rhizosphere Soil of C3 and C4 Plants

The LDA Effect Size (LEfSe) method [78] was employed to analyze differences in the composition of rhizosphere soil bacteria under C3 and C4 plant treatments (Figure S3 and Figure 4). The length of the bar chart represents the influence of significantly different species (Figure S3). In total, 71 taxa exhibited significant differences in the rhizosphere soil bacteria of C3 plants (p < 0.05), while 36 taxa showed significant differences in the rhizosphere soil bacteria of C4 plants (p < 0.05).
In the rhizosphere soil of C3 plants, significant differences were observed at various taxonomic levels (p < 0.05), including 2 at the phylum level, 2 at the class level, 11 at the order level, 15 at the family level, 20 at the genus level and 21 at the class level. The most significant differences were found in the phylum Proteobacteria (p < 0.05). Compared to the BTBPE-contaminated soil without the plant control group, the most substantial differences in the rhizosphere soil bacteria under C3 plant treatment were observed in Proteobacteria (p < 0.05), with significant differences in Verrucomicrobia (p < 0.05). Among the Proteobacteria, the bacteria in the rhizosphere soil of C3 plants were the most different in Alphaproteobacteri, including Rhizobiales, Caulobacterales and Sphingomonadales. LEfSe analysis underscored the significant enrichment of Sphingomicrobium (p < 0.05), Rhizobium, and Mesorhizobium (p < 0.05) in the rhizosphere soil of C3 plants, suggesting a strong association with nitrogen fixation in the nitrogen cycle. Additionally, the study identified leguminous plants (GM and MS) in C3 plants, containing a substantial number of nitrogen-fixing bacteria such as Rhizobiales [79]. This finding was reinforced by a notable LDA score, surpassing three, indicating enhanced nitrogen cycle-related processes induced by C3 plants.
In the rhizosphere soil of C4 plants, significant differences were observed at various taxonomic levels (p < 0.05), including seven at the order level, seven at the family level, ten at the genus level, and twelve at the species level. The most significant differences were found in the species Lysobacter (p < 0.05). Within Proteobacteria, the most notable differences occurred in Gammaproteobacteria, along with significant differences in Rhodobacteraceae, Burkholderiaceae, Rhodocyclaceae and Pedosphaerales (p < 0.05). Notably, Burkholderiaceae-related bacteria were associated with the degradation of organic pollutants such as benzene and polychlorinated biphenyls (PCBs) [80,81,82]. In addition to Proteobacteria, there were also significant differences in Chloroflexia among different C4 plant species (p < 0.05).
Figure 4 presented the evolutionary branch diagram of bacteria in the rhizosphere soil of C3 and C4 plants based on LEfSe analysis. Comparative analysis revealed that the most substantial differences in rhizosphere soil bacteria under C3 and C4 plant treatments were in Proteobacteria. Notably, C3 plants exhibited pronounced differences in Alphaproteobacteria, while C4 plants displayed significant distinction in Gammaproteobacteria (p < 0.05). Pseudomonadaceae (Gammaproteobacteria) (p < 0.05) has been shown to play an important role in the degradation of PAHs [72,83]; for instance, Pseudomonas aeruginos has demonstrated the ability to remove 89.6% of naphthalene and 77.2% of anthracene within 15 days [84]. LEfSe analysis results showed that C3 plant rhizosphere soil bacteria were significantly enriched with nitrogen-fixing bacteria such as Sphingosinomonas, Rhizobium and Mesorhizobium, promoting the nitrogen cycling process of BTBPE-contaminated soil. Conversely, C4 plant rhizosphere soil bacteria were significantly enriched in Burkholderiaceae, which was related to organic pollutant degradation.

3.4. Functional Prediction of Bacterial Community in Rhizosphere Soil of C3 and C4 Plants

3.4.1. FAPROTAX Function Prediction

The relative abundance of the FAPROTAX function prediction of the bacterial community in rhizosphere soil of different plants (Figure S4) revealed the most significant function enrichment in chemoheterotrophy, aerobic chemoheterotrophy and aromatic compound degradation. Chemoheterotrophy and aerobic chemoheterotrophy were also the most prevalent functions, constituting 47–50% of the total functional groups. This is consistent with findings by Liang et al., indicating that chemoheterotrophic and oxidative heterotrophic functions are predominant among soil bacteria in different land use types [85]. FAPROTAX functional difference analysis highlighted nine significantly different functions (p < 0.05) enriched in the rhizosphere soil bacteria of C3 and C4 plants (Figure 5). C3 plants exhibited significantly higher enrichment in nitrate fixation, manganese oxidation, dark oxidation of sulfur compounds and chemoheterotrophy, compared to C4 plants (p < 0.05), while C4 plants showed significantly higher enrichment in knallgas bacteria, aliphatic non-methane hydrocarbon degradation, hydrocarbon degradation, dark hydrogen oxidation and predatory or exoparasitic (p < 0.05).
In terms of carbon cycle functions (Figure S5), differences in the enrichment of chemoheterotrophy, aerobic chemoheterotrophy, methanol oxidation, methanotrophy and plastic degradation function were observed under different plant treatments, with relative abundances ranging from 20% to 24%. C3 plants exhibited significantly higher enrichment in chemoheterotrophy function compared to C4 plants (Figure 5, p < 0.05). Mengle pointed out a large difference in root morphology between C3 and C4 plants, leading to higher plant-derived carbon content in C3 plants soils [86,87]. Notably, compared to C3 plants, C4 plants exhibited significantly higher enrichment in aliphatic non-methane hydrocarbon degradation and hydrocarbon degradation functions, both associated with organic pollutant degradation (Figure 5, p < 0.05). This finding aligns with the LEfSe analysis, which demonstrated a significant enrichment of organic pollutant-degrading bacteria, such as Rhodobacteraceae, Burkholderiaceae and Rhodocyclaceae, in the rhizosphere soil of C4 plant.
Regarding the nitrogen cycle functions (Figure S6), compared with CK1, the abundance of bacteria involved in ureolysis increased, while those associated with nitrite and nitrate denitrification functions decreased. Soybean (GM) had higher relative abundances in denitrification, nitrous oxide denitrification. Notably, C3 plants demonstrated significantly higher enrichment in nitrogen fixation compared to C4 plants (Figure 5, p < 0.05). These findings were consistent with the earlier LEfSe analysis, indicating significant enrichment of nitrogen-fixing bacteria, such as Rhizobium, Mesorhizobium and Sphingomicrobium in the rhizosphere soil of C3 plants. Additionally, bacteria such as Pseudomonas, Bacillus and Steroidobacter associated with denitrification demonstrated higher relative abundances in the rhizosphere soil bacteria of C3 plants compared to C4 plants. This suggested that C3 plants contribute to enhanced nitrogen fixation and denitrification in the nitrogen cycle. Muneer et al. found that the N-sink intensity of Leymus chinensis (LC, C3 plant) was greater than that of Cleistogenes squarrosa (CS, C4 plant), but Cleistogenes squarrosa showed greater potential for nutrient transfer [88]. In summary, FAPROTAX functional predictions revealed that the enrichment of rhizosphere soil bacteria was induced in carbon-cycle-and nitrogen-cycle-related functions after planting plants under BTBPE exposure. In addition, the rhizosphere soil bacteria in C3 plants enriched significantly higher levels of the nitrogen fixation function, while C4 plants enriched significantly higher organic pollutant degradation functions (p < 0.05), consistent with the LEfSe analysis results.

3.4.2. PICRUSt 2 Function Prediction

PICRUSt 2 functional prediction of rhizosphere soil bacteria under different plant treatments revealed that at the KEGG level 1 functional layer, metabolism function exhibited the highest relative abundance, followed by genetic information processing. At the KEGG level 2 (Figure S7), the top three functions of relative abundance in metabolic functions were carbohydrate metabolism, amino acid metabolism, and metabolism of cofactors and vitamins. Carbohydrate metabolism and amino acid metabolism play a crucial role in the carbon and nitrogen cycle, respectively [89,90]. Additionally, cofactors are the main components of proteases involved in various catalytic conversion reactions and promoting metabolic processes [91]. Moreover, under BTBPE exposure, rhizosphere soil bacteria were also enriched in the metabolism of terpenoids and polyketides, xenobiotics biodegradation and metabolism, lipid metabolism and metabolism of other amino acids, with their relative abundance exceeding 5% of the functional prediction results. The metabolism of terpenoids and polyketides and the lipid metabolism are markers of exogenous oxidative stress [92]. A total of 176 functional groups were predicted at the KEGG level 3, with Figure S8 displaying functional groups with a relative abundance of more than 1%. Functional prediction results showed that rhizosphere soil bacteria had the highest relative abundance in carbohydrate metabolism (about 13%) and amino acid metabolism (about 13%), followed by a metabolism of cofactors and vitamins (about 11%), metabolism of terpenoids and polyketides (9–10%) and metabolism of other amino acids (about 8%). Wu et al. also identified amino acid metabolism, carbohydrate metabolism and membrane transport as the three major metabolic functions of microorganisms in heavy metal and PBDE-contaminated soils [93]. In carbohydrate metabolism, bacteria were mainly enriched in the TCA cycle, pentose phosphate pathway, pyruvate metabolism, butanoate metabolism, propanoate metabolism and glycolysis/gluconeogenesis, making up about 7% of the total functional groups. These pathways are key biological processes in sugar metabolism and significantly impact other soil bacteria metabolic activities. In the metabolism of terpenoids and polyketides, bacteria were mainly enriched in the biosynthesis of ansamycins, biosynthesis of vancomycin group antibiotics, Geraniol degradation and terpenoid backbone biosynthesis, also comprising about 7% of the total functional groups.
The functional analysis of soil bacteria in the rhizosphere of C3 plants and C4 plants, as predicted by PICRUSt 2, identified three significantly distinct functions enriched at KEGG level 2 (Figure 6, p < 0.05). Rhizosphere soil bacteria from C3 plants exhibited significantly higher membrane transport and drug resistance: antimicrobial functions than those from C4 plants (p < 0.05). Notably, rhizosphere soil bacteria from C4 plants surpassed those from C3 plants in the metabolism of terpenoids and polyketides (p < 0.05), indicating a more pronounced response of C4 plants to BTBPE stress. Terpenoids and polyketones, vital components of secondary metabolites, are known to confer stress resistance under adverse conditions [94]. Cui et al. suggested that in order to protect the metabolic balance of plants, phenolic compounds, terpenoids and alkaloids in plants would increase under abiotic stress [95]. Combined with the genus composition of rhizosphere soil bacteria in C3 and C4 plants, it was evident that the relative abundance of bacteria capable of degrading organic pollutants in the rhizosphere soil of C4 plants was 1.04–3.77 times higher than that in C3 plants. This highlights the superior degradation potential of C4 plants for BTBPE. The changes in root exudates impact the functionality and metabolic limitations of microorganisms, especially concerning variations in amino acids and organic acids [96]. Studies have indicated the detection of low-molecular-weight organic acids (LMWOAs) in the rhizosphere soil of both C4 and C3 plants contaminated with PAHs, with citric acid exhibiting the highest concentration. Citric acid demonstrated a significant impact on PAH degradation, and the degradation potential of LMWOAs in C4 plants exceeded that in C3 plants [97]. Studies have also proven that the degradation efficiency of PAHs (naphthalene, acenaphthene and fluorene) in C4 (Zea mays L., Sorghum sudanense (Piper) Stapf and Chrysopogon zizanioides (L.) Roberty) plants was better than that in C3 (Vigna unguiculata (L.) Walp., Helianthus annuus L. and Austrodanthonia caespitosa) plants [98]. The results of PICRUSt 2 functional difference analysis showed that C4 plants exhibited significantly higher functions related to metabolism than those from C3 plants (p < 0.05). Combining the results of LEfSe analysis, FAPROTAX and PICRUSt 2 function predictions, it was indicated that C4 plants had a great degradation potential for BTBPE.

4. Conclusions

This study investigated the responses of bacterial community structure and function in the rhizosphere soil of C3 and C4 plants to BTBPE exposure. The presence of C3 and C4 plants changed the bacterial richness, community diversity and composition in BTBPE-contaminated soil. C3 and C4 plants had significant differences on bacterial community structure, with C4 plants showing more pronounced differences among species. The microbial communities in the rhizosphere soil exhibited distinct characteristics under C3 and C4 plant treatments. At the phylum level, Proteobacteria dominated the bacterial communities for both plant types. C3 plant rhizosphere soil had higher abundances of Proteobacteria, Bacteroidetes, Verrucomicrobia and Cyanobacteria, while C4 plants’ rhizosphere soil had higher abundances of Actinobacteria, Patescibacteria, Chloroflexota, Acidobacteriota and Gemmatimonadetes. At the genus level, key bacteria involved in organic pollutant degradation included Nocardioides, Streptomyces, Pseudomonas, Stenotrophomonas and Sphingopyxis. Sphingomicrobium was most abundant in C3 plants’ rhizosphere soil, while Nocardioides dominated in C4 plant’s rhizosphere soil. LEfSe analysis showed that the key bacteria in the rhizosphere soil of C3 plants were associated with nitrogen fixation, promoting nitrogen-cycle-related processes in BTBPE-contaminated soil. In contrast, the key bacterial communities in C4 plants’ rhizosphere soil were organic pollutant-degrading bacteria, significantly enriched in Burkholderia, indicating a strong potential for BTBPE degradation. FAPROTAX and PICRUSt 2 function prediction analysis further indicated that the relative abundance of bacteria associated with nitrogen metabolism-related functions were significantly higher in rhizosphere soil of C3 plants, while the relative abundance of bacteria associated with organic pollutant degradation potential functions were significantly higher in the rhizosphere soil of C4 plants. In conclusion, this study establishes that C3 and C4 plants induce varying degrees of impacts in the composition and function of soil rhizosphere microbial communities after BTBPE exposure. These findings provide a theoretical foundation for further investigations into plant–microbial remediation strategies for BTBPE-contaminated soil.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/agriculture14091637/s1, Table S1: Sequencing results and the number of ASVs in rhizosphere soil of different treatments, Table S2: Bacterial species richness and diversity indices in rhizosphere soil of different treatments, Figure S1: ASV distribution of bacteria in rhizosphere soil of C3 and C4 plants, Figure S2: α-diversity of soil bacteria in the rhizosphere of different treatments, Figure S3: LDA distribution of C3 and C4 plant rhizosphere soil bacteria based on LEfSe analysis, Figure S4: FAPROTAX function prediction of bacterial community in rhizosphere soil of different treatments, Figure S5: Distribution of related functions of carbon cycle in rhizosphere soil of different treatments, Figure S6: Distribution of related functions of nitrogen cycle in rhizosphere soil of different treatments, Figure S7: Functional prediction of PICRUSt 2 bacterial communities in rhizosphere soil of different treatments (KEGG level 2), Figure S8: Functional prediction of PICRUSt 2 bacterial communities in rhizosphere soil of different treatments (KEGG level 3).

Author Contributions

Conceptualization, Y.C., S.W. and Y.L.; collecting Samples: S.W. and Y.L.; data curation: Y.C., S.W., Y.L., W.L. and Z.N.; methodology: Y.C., S.W., Y.L., W.L. and Z.N.; formal analysis: Y.C., S.W., Y.L., W.L. and Z.N.; writing-original draft preparation, Y.C., S.W., Y.L., W.L. and Z.N.; writing-review and editing, Y.C., S.W., Y.L., W.L. and Z.N.; supervision, S.W.; funding acquisition, S.W. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Shaanxi Province Youth Science and Technology New Star Plan of China (2016KJXX-83) and the National Natural Science Foundation of China (41975160, 41303073).

Institutional Review Board Statement

Not applicable.

Data Availability Statement

The data presented in this study are openly available in NCBI, reference number PRJNA1158447.

Conflicts of 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.

References

  1. Kalachova, K.; Hradkova, P.; Lankova, D.; Hajslova, J.; Pulkrabova, J. Occurrence of brominated flame retardants in household and car dust from the Czech Republic. Sci. Total Environ. 2012, 441, 182–193. [Google Scholar] [CrossRef] [PubMed]
  2. Jiao, S.; Hou, X.; Zhao, G.; Feng, Y.; Zhang, S.; Zhang, H.; Liu, J.; Jiang, G. Migration of polycyclic aromatic hydrocarbons in the rhizosphere micro-interface of soil-ryegrass (Lolium perenne L.) system. Sci. Total Environ. 2023, 903, 166299. [Google Scholar] [CrossRef] [PubMed]
  3. Tian, M.; Chen, S.; Wang, J.; Zheng, X.; Luo, X.; Mai, B. Brominated flame retardants in the atmosphere of e-waste and rural sites in southern China: Seasonal variation, temperature dependence, and gas-particle partitioning. Environ. Sci. Technol. 2011, 45, 8819–8825. [Google Scholar] [CrossRef] [PubMed]
  4. Zhao, X.; Chen, T.; Yang, B.; Wang, D.; Sun, W.; Wang, Y.; Yang, X.; Wen, S.; Li, J.; Shi, Z. Serum levels of novel brominated flame retardants (NBFRs) in residents of a major BFR-producing region: Occurrence, impact factors and the relationship to thyroid and liver function. Ecotoxicol. Environ. Saf. 2021, 208, 111467. [Google Scholar] [CrossRef]
  5. McGrath, T.J.; Ball, A.S.; Clarke, B.O. Critical review of soil contamination by polybrominated diphenyl ethers (PBDEs) and novel brominated flame retardants (NBFRs); concentrations, sources and congener profiles. Environ. Pollut. 2017, 230, 741–757. [Google Scholar] [CrossRef]
  6. Covaci, A.; Harrad, S.; Abdallah, M.A.-E.; Ali, N.; Law, R.J.; Herzke, D.; de Wit, C.A. Novel brominated flame retardants: A review of their analysis, environmental fate and behaviour. Environ. Int. 2011, 37, 532–556. [Google Scholar] [CrossRef]
  7. Xiong, P.; Yan, X.; Zhu, Q.; Qu, G.; Shi, J.; Liao, C.; Jiang, G. A review of environmental occurrence, fate, and toxicity of novel brominated flame retardants. Environ. Sci. Technol. 2019, 53, 13551–13569. [Google Scholar] [CrossRef]
  8. Zhang, W.; Wang, P.; Zhu, Y.; Yang, R.; Li, Y.; Wang, D.; Matsiko, J.; Han, X.; Zhao, J.; Zhang, Q.; et al. Brominated flame retardants in atmospheric fine particles in the Beijing-Tianjin-Hebei region, China: Spatial and temporal distribution and human exposure assessment. Ecotoxicol. Environ. Saf. 2019, 171, 181–189. [Google Scholar] [CrossRef]
  9. Nyholm, J.R.; Grabic, R.; Arp, H.P.H.; Moskeland, T.; Andersson, P.L. Environmental occurrence of emerging and legacy brominated flame retardants near suspected sources in Norway. Sci. Total Environ. 2013, 443, 307–314. [Google Scholar] [CrossRef]
  10. Shi, T.; Chen, S.; Luo, X.; Zhang, X.; Tang, C.; Luo, Y.; Ma, Y.; Wu, J.; Peng, X.; Mai, B. Occurrence of brominated flame retardants other than polybrominated diphenyl ethers in environmental and biota samples from southern China. Chemosphere 2009, 74, 910–916. [Google Scholar] [CrossRef]
  11. Ali, N.; Harrad, S.; Goosey, E.; Neels, H.; Covaci, A. “Novel” brominated flame retardants in Belgian and UK indoor dust: Implications for human exposure. Chemosphere 2011, 83, 1360–1365. [Google Scholar] [CrossRef] [PubMed]
  12. Xu, P.; Tao, B.; Zhou, Z.; Fan, S.; Zhang, T.; Liu, A.; Dong, S.; Yuan, J.; Li, H.; Chen, J.; et al. Occurrence, composition, source, and regional distribution of halogenated flame retardants and polybrominated dibenzo-p-dioxin/dibenzofuran in thesoils of Guiyu, China. Environ. Pollut. 2017, 228, 61–71. [Google Scholar] [CrossRef] [PubMed]
  13. McGrath, T.J.; Morrison, P.D.; Ball, A.S.; Clarke, B.O. Detection of novel brominated flame retardants (NBFRs) in the urban soils of Melbourne, Australia. Emerg. Contam. 2017, 3, 23–31. [Google Scholar] [CrossRef]
  14. Xie, J.; Sun, Y.; Cheng, Y.; Chen, Y.; Chen, L.; Xie, C.; Dai, S.; Luo, X.; Zhang, L.; Mai, B. Halogenated flame retardants in surface sediments from fourteen estuaries, South China. Mar. Pollut. Bull. 2021, 164, 112099. [Google Scholar] [CrossRef]
  15. Zheng, J.; Luo, X.; Yuan, J.; Wang, J.; Wang, Y.; Chen, S.; Mai, B.; Yang, Z. Levels and sources of brominated flame retardants in human hair from urban, e-waste, and rural areas in South China. Environ. Pollut. 2011, 159, 3706–3713. [Google Scholar] [CrossRef] [PubMed]
  16. Bu, Q.; Wu, D.; Xia, J.; Wu, M.; Liu, X.; Cao, Z.; Yu, G. Polybrominated diphenyl ethers and novel brominated flame retardants in indoor dust of different microenvironments in Beijing, China. Environ. Int. 2019, 122, 159–167. [Google Scholar] [CrossRef]
  17. Chen, T.; Yu, D.; Yang, L.; Sui, S.; Lv, S.; Bai, Y.; Sun, W.; Wang, Y.; Chen, L.; Sun, Z.; et al. Thyroid function and decabromodiphenyl ethane (DBDPE) exposure in Chinese adults from a DBDPE manufacturing area. Environ. Int. 2019, 133, 105179. [Google Scholar] [CrossRef]
  18. Fromme, H.; Becher, G.; Hilger, B.; Völkel, W. Brominated flame retardants-Exposure and risk assessment for the general population. Int. J. Hyg. Environ. Health 2016, 219, 1–23. [Google Scholar] [CrossRef]
  19. Zhou, S.N.; Buchar, A.; Siddique, S.; Takser, L.; Abdelouahab, N.; Zhu, J. Measurements of selected brominated flame retardants in nursing women: Implications for human exposure. Environ. Sci. Technol. 2014, 48, 8873–8880. [Google Scholar] [CrossRef]
  20. Ali, N.; Shahzad, K.; Rashid, M.I.; Shen, H.; Ismail, I.M.I.; Eqani, S.A.M.A.S. Currently used organophosphate and brominated flame retardants in the environment of China and other developing countries (2000–2016). Environ. Sci. Pollut. Res. 2017, 24, 18721–18741. [Google Scholar] [CrossRef]
  21. Zhang, Q.; Wang, Z.; Xiao, Q.; Ge, J.; Wang, X.; Jiang, W.; Yuan, Y.; Zhuang, Y.; Meng, Q.; Jiang, J.; et al. The effects and mechanisms of the new brominated flame retardant BTBPE on thyroid toxicity. Food Chem. Toxicol. 2023, 180, 114027. [Google Scholar] [CrossRef] [PubMed]
  22. Cui, Y.; Xiao, Q.; Wang, Z.; Zhang, Q.; Liu, Y.; Hao, W.; Jiang, J.; Meng, Q.; Wei, X. 1,2-bis(2,4,6-tribromophenoxy) ethane, a novel brominated flame retardant, disrupts intestinal barrier function via the IRX3/NOS2 axis in rat small intestine. J. Hazard. Mater. 2024, 461, 132597. [Google Scholar] [CrossRef] [PubMed]
  23. Yadav, I.C.; Devi, N.L.; Singh, V.K.; Li, J.; Zhang, G. Measurement of legacy and emerging flame retardants in indoor dust from a rural village (Kopawa) in Nepal: Implication for source apportionment and health risk assessment. Ecotoxicol. Environ. Saf. 2019, 168, 304–314. [Google Scholar] [CrossRef]
  24. Doran, J.W.; Zeiss, M.R. Soil health and sustainability: Managing the biotic component of soil quality. Appl. Soil Ecol. 2000, 15, 3–11. [Google Scholar] [CrossRef]
  25. An, Q.; Yang, L.; Yang, S.; Wang, Y.; Shi, L.; Aamir, M.; Liu, W. Legacy and novel brominated flame retardants in agricultural soils of eastern China (2011–2021): Concentration level, temporal trend, and health risk assessment. J. Hazard. Mater. 2023, 446, 130631. [Google Scholar] [CrossRef]
  26. Zhou, J.; Deng, Y.; Shen, L.; Wen, C.; Yan, Q.; Ning, D.; Qin, Y.; Xue, K.; Wu, L.; He, Z.; et al. Temperature mediates continental-scale diversity of microbes in forest soils. Nat. Commun. 2016, 7, 12083. [Google Scholar] [CrossRef]
  27. Liu, J.; He, X.; Lin, X.; Chen, W.; Zhou, Q.; Shu, W.; Huang, L. Ecological effects of combined pollution associated with e-waste recycling on the composition and diversity of soil microbial communities. Environ. Sci. Technol. 2015, 49, 6438–6447. [Google Scholar] [CrossRef]
  28. Liu, F.; Mo, X.; Kong, W.; Song, Y. Soil bacterial diversity, structure, and function of Suaeda salsa in rhizosphere and non-rhizosphere soils in various habitats in the Yellow River Delta, China. Sci. Total Environ. 2020, 740, 140144. [Google Scholar] [CrossRef] [PubMed]
  29. Zhang, X.; Song, J.; Yan, W.; Li, T.; Li, R.; Wang, J.; Wang, X.; Zhou, Q. Regulation of rhizospheric microbial network to enhance plant growth and resist pollutants: Unignorable weak electric field. Sci. Total Environ. 2023, 855, 158888. [Google Scholar] [CrossRef]
  30. Arthur, E.; Rice, P.; Rice, P.; Anderson, T.; Baladi, S.; Henderson, K.; Coats, J. Phytoremediation—An overview. Crit. Rev. Plant Sci. 2005, 24, 109–122. [Google Scholar] [CrossRef]
  31. Tejeda-Agredano, M.C.; Gallego, S.; Vila, J.; Grifoll, M.; Ortega-Calvo, J.J.; Cantos, M. Influence of the sunflower rhizosphere on the biodegradation of PAHs in soil. Soil Biol. Biochem. 2013, 57, 830–840. [Google Scholar] [CrossRef]
  32. Guo, M.; Gong, Z.; Miao, R.; Rookes, J.; Cahill, D.; Zhuang, J. Microbial mechanisms controlling the rhizosphere effect of ryegrass on degradation of polycyclic aromatic hydrocarbons in an aged-contaminated agricultural soil. Soil Biol. Biochem. 2017, 113, 130–142. [Google Scholar] [CrossRef]
  33. Chen, Y.; Zhen, Z.; Li, G.; Li, H.; Wei, T.; Huang, F.; Li, T.; Yang, C.; Ren, L.; Liang, Y.; et al. Di-2-ethylhexyl phthalate (DEHP) degradation and microbial community change in mangrove rhizosphere gradients. Sci. Total Environ. 2023, 871, 162022. [Google Scholar] [CrossRef]
  34. Dong, J.; Li, G.; Gao, J.; Zhang, H.; Bi, S.; Liu, S.; Liao, C.; Jiang, G. Catalytic degradation of brominated flame retardants in the environment: New techniques and research highlights. Sci. Total Environ. 2022, 848, 157695. [Google Scholar] [CrossRef]
  35. Ma, S.; Yu, Y.; Yang, Y.; Li, G.; An, T. A new advance in the potential exposure to “old” and “new” halogenated flame retardants in the atmospheric environments and biota: From occurrence to transformation products and metabolites. Crit. Rev. Environ. Sci. Technol. 2020, 50, 1935–1983. [Google Scholar] [CrossRef]
  36. Wang, G.; Xu, X.; Li, Y. Distribution, transformation and biological effects of polybrominated diphenyl ethers and their derivatives in soil: A review. Res. Environ. Sci. 2021, 34, 755–765. [Google Scholar]
  37. Li, W.; Wang, S.; Chen, Y.; Liu, L.; Hou, S.; You, H. Integration of transcriptomic and proteomic reveals the toxicological molecular mechanisms of decabromodiphenyl ethane (DBDPE) on Pleurotus ostreatus. Environ. Pollut. 2022, 314, 120263. [Google Scholar] [CrossRef] [PubMed]
  38. Wang, S.; Li, W.; Liu, L.; Qi, H.; You, H. Biodegradation of decabromodiphenyl ethane (DBDPE) by white-rot fungus Pleurotus ostreatus: Characteristics, mechanisms, and toxicological response. J. Hazard. Mater. 2022, 424, 127716. [Google Scholar] [CrossRef]
  39. Vilaplana, M.; Rodríguez-Rodríguez, C.; Barón, E.; Gorga, M.; Sarrà, M.; Caminal, G.; Eljarrat, E.; Barceló, D. Biodegradation of polybrominated diphenyl ethers in liquid media and sewage sludge by trametes versicolor. Int. J. Environ. Res. 2015, 9, 273–280. [Google Scholar]
  40. de Freitas, E.N.; Bubna, G.A.; Brugnari, T.; Kato, C.G.; Nolli, M.; Rauen, T.G.; de Peralta Muniz Moreira, R.F.; Peralta, R.A.; Bracht, A.; de Souza, C.G.M.; et al. Removal of bisphenol a by laccases from Pleurotus ostreatus and Pleurotus pulmonarius and evaluation of ecotoxicity of degradation products. Chem. Eng. J. 2017, 330, 1361–1369. [Google Scholar] [CrossRef]
  41. Innes, L.; Hobbs, P.J.; Bardgett, R.D. The impacts of individual plant species on rhizosphere microbial communities in soils of different fertility. Biol. Fertil. Soils 2004, 40, 7–13. [Google Scholar] [CrossRef]
  42. Kowalchuk, G.A.; Hol, W.H.G.; Van Veen, J.A. Rhizosphere fungal communities are influenced by Senecio jacobaea pyrrolizidine alkaloid content and composition. Soil Biol. Biochem. 2006, 38, 2852–2859. [Google Scholar] [CrossRef]
  43. Batten, K.M.; Scow, K.M.; Davies, K.F.; Harrison, S.P. Two invasive plants alter soil microbial community composition in serpentine grasslands. Biol. Invasions 2006, 8, 217–230. [Google Scholar] [CrossRef]
  44. Allen, E.B.; Allen, M.F.; Helm, D.J.; Trappe, J.M.; Molina, R.; Rincon, E. Patterns and regulation of mycorrhizal plant and fungal diversity. Plant Soil 1995, 170, 47–62. [Google Scholar] [CrossRef]
  45. Vranova, V.; Rejsek, K.; Skene, K.R.; Janous, D.; Formanek, P. Methods of collection of plant root exudates in relation to plant metabolism and purpose: A review. J. Plant Nutr. Soil Sci. 2013, 176, 175–199. [Google Scholar] [CrossRef]
  46. O’Leary, M.H. Carbon isotope fractionation in plants. Phytochemistry 1981, 20, 553–567. [Google Scholar] [CrossRef]
  47. Ge, Y.; Shen, C.; Wang, Y.; Sun, Y.; Schimel, J.; Gargra-Torresday, J.; Holden, P. Carbonaceous nanomaterials have higher effects on soybean rhizosphere prokaryotic communities during the reproductive growth phase than during vegetative growth. Environ. Sci. Technol. 2018, 52, 6636–6646. [Google Scholar] [CrossRef]
  48. Li, H.; Zhang, Y.; Yang, S.; Yang, S.; Wang, Z.; Feng, X.; Liu, H.; Jiang, Y. Variations in soil bacterial taxonomic profiles and putative functions in response to straw incorporation combined with N fertilization during the maize growing season. Agric. Ecosyst. Environ. 2019, 283, 106578. [Google Scholar] [CrossRef]
  49. D’Orazio, V.; Ghanem, A.; Senesi, N. Phytoremediation of pyrene contaminated soils by different plant species. CLEAN–Soil Air Water 2013, 41, 377–382. [Google Scholar] [CrossRef]
  50. Li, H.N.; Huang, H.L.; Lü, L.L.; Guo, B.; Wen, B.; Ke, X. Plant uptake and translocation of DBDPE in soil and the micro-mechanisms. Acta Scientiae Circumstantiae 2020, 40, 1848–1857. [Google Scholar]
  51. Barba-Espin, G.; Diaz-Vivancos, P.; Clemente-Moreno, M.J.; Albacete, A.; Faize, L.; Faize, M.; HernÁNdez, J.A. Interaction between hydrogen peroxide and plant hormones during germination and the early growth of pea seedlings. Plant Cell Environ. 2010, 33, 981–994. [Google Scholar] [CrossRef] [PubMed]
  52. Sekmen, C.A.H.; Yalcinkaya, T.; Akyol, T.Y.; Gokce, A.; Turkan, I. Pretreatment of seeds with hydrogen peroxide improves deep-sowing tolerance of wheat seedlings. Plant Physiol. Biochem. 2021, 167, 321–336. [Google Scholar] [CrossRef] [PubMed]
  53. Shi, W.; Qin, M.; Chen, F.; Xia, B. Supragingival Microbial Profiles of Permanent and Deciduous Teeth in Children with Mixed Dentition. PLoS ONE 2016, 11, 0146938. [Google Scholar] [CrossRef] [PubMed]
  54. Zhao, D.; Sun, M.; Xue, Y.; Yang, Q.; Liu, B.; Jia, B.; Zhang, Z. Spatial variations of plant species diversity in urban soil seed banks in Beijing, China: Implications for plant regeneration and succession. Urban For. Urban Green. 2023, 86, 128012. [Google Scholar] [CrossRef]
  55. Zhang, J.; Kobert, K.; Flouri, T.; Stamatakis, A. PEAR: A fast and accurate Illumina Paired-End reAd mergeR. Bioinformatics 2014, 30, 614–620. [Google Scholar] [CrossRef]
  56. Rognes, T.; Flouri, T.; Nichols, B.; Quince, C.; Mahé, F. VSEARCH: A versatile open source tool for metagenomics. Peer J. 2016, 4, e2584. [Google Scholar] [CrossRef]
  57. Edgar, R.C. UNOISE2: Improved error-correction for Illumina 16S and ITS amplicon sequencing. BioRxiv 2016, 15, 081257. [Google Scholar]
  58. Louca, S.; Parfrey, L.W.; Doebeli, M. Decoupling function and taxonomy in the global ocean microbiome. Science 2016, 353, 1272–1277. [Google Scholar] [CrossRef]
  59. Langille, M.G.; Zaneveld, J.; Caporaso, J.G.; McDonald, D.; Knights, D.; Reyes, J.A.; Clemente, J.C.; Burkepile, D.E.; Vega Thurber, R.L.; Knight, R.; et al. Predictive functional profiling of microbial communities using 16S rRNA marker gene sequences. Nat. Biotechnol. 2013, 31, 814–821. [Google Scholar] [CrossRef]
  60. Chen, H.; Feng, Y.; Yang, X.; Yang, B.; Sarkar, B.; Bolan, N.; Meng, J.; Wu, F.; Wong, J.W.C.; Chen, W.; et al. Assessing simultaneous immobilization of lead and improvement of phosphorus availability through application of phosphorus-rich biochar in a contaminated soil: A pot experiment. Chemosphere 2022, 296, 133891. [Google Scholar] [CrossRef]
  61. Segata, N.; Izard, J.; Waldron, L.; Gevers, D.; Miropolsky, L.; Garrett, W.S.; Huttenhower, C. Metagenomic biomarker discovery and explanation. Genome Biol. 2011, 12, R60. [Google Scholar] [CrossRef] [PubMed]
  62. Parks, D.H.; Tyson, G.W.; Hugenholtz, P.; Beiko, R.G. STAMP: Statistical analysis of taxonomic and functional profiles. Bioinformatics 2014, 30, 3123–3124. [Google Scholar] [CrossRef]
  63. Jia, T.; Wang, Y.; Chai, B. Bacterial community characteristics and enzyme activities in bothriochloa ischaemum litter over progressive phytoremediation years in a copper lailings dam. Front. Microbiol. 2020, 11, 565806. [Google Scholar] [CrossRef]
  64. Rovira, A.D. Plant root excretions in relation to the rhizosphere effect. Plant Soil 1956, 348, 178–194. [Google Scholar] [CrossRef]
  65. Zhang, M.; Wang, J.; Bai, S.H.; Zhang, Y.; Teng, Y.; Xu, Z. Assisted phytoremediation of a co-contaminated soil with biochar amendment: Contaminant removals and bacterial community properties. Geoderma 2019, 348, 115–123. [Google Scholar] [CrossRef]
  66. Sivaram, A.K.; Subashchandrabose, S.R.; Logeshwaran, P.; Lockington, R.; Naidu, R.; Megharaj, M. Rhizodegradation of PAHs differentially altered by C3 and C4 plants. Sci. Rep. 2020, 10, 16109. [Google Scholar] [CrossRef] [PubMed]
  67. Spain, A.M.; Krumholz, L.R.; Elshahed, M.S. Abundance, composition, diversity and novelty of soil Proteobacteria. ISME J. 2009, 3, 992–1000. [Google Scholar] [CrossRef]
  68. Maryam, Z.S.; Fatemeh, M.; Mehdi, H.; Sajjad, S. Salinity stress endurance of the plants with the aid of bacterial genes. Front. Genet. 2023, 14, 1049608. [Google Scholar]
  69. Ehiosun, K.I.; Godin, S.; Urios, L.; Lobinski, R.; Grimaud, R. Degradation of long-chain alkanes through biofilm formation by bacteria isolated from oil-polluted soil. Int. Biodeterior. Biodegrad. 2022, 175, 105508. [Google Scholar] [CrossRef]
  70. Bai, Y.; Liang, H.; Wang, L.; Tang, T.; Li, Y.; Cheng, L.; Gao, D. Bioremediation of diesel-contaminated soil by fungal solid-state fermentation. Bull. Environ. Contam. Toxicol. 2024, 112, 13. [Google Scholar] [CrossRef]
  71. Zhao, L.; Jiang, J.; Chen, C.; Zhan, S.; Yang, J.; Yang, S. Efficiency and mechanism of the phytoremediation of decabromodiphenyl ether-contaminated sediments by aquatic macrophyte Scirpus validus. Environ. Sci. Pollut. Res. 2017, 24, 12949–12962. [Google Scholar] [CrossRef] [PubMed]
  72. Wang, H.; Kuang, S.; Lang, Q.; Wang, L. Bacterial community structure of aged oil sludge contaminated soil revealed by illumina high-throughput sequencing in East China. World J. Microbiol. Biotechnol. 2021, 37, 183. [Google Scholar] [CrossRef] [PubMed]
  73. Ye, R.; Thomas, S.M. Microbial nitrogen cycles: Physiology, genomics and applications. Curr. Opin. Microbiol. 2001, 4, 307–312. [Google Scholar] [CrossRef] [PubMed]
  74. Warembourg, F.; Roumet, C.; Lafont, F. Differences in rhizosphere carbon-partitioning among plant species of different families. Plant Soil 2003, 256, 347–357. [Google Scholar] [CrossRef]
  75. Xu, Y.; Ge, Y.; Lou, Y.; Meng, J.; Shi, L.; Xia, F. Assembly strategies of the wheat root-associated microbiome in soils contaminated with phenanthrene and copper. J. Hazard. Mater. 2021, 412, 125340. [Google Scholar] [CrossRef]
  76. Story, S.P.; Kline, E.L.; Hughes, T.A.; Riley, M.B.; Hayasaka, S.S. Degradation of aromatic hydrocarbons by Sphingomonas paucimobilis strain EPA505. Arch. Environ. Contam. Toxicol. 2004, 47, 168–176. [Google Scholar] [CrossRef]
  77. Du, S.; Yu, M.; Liu, F.; Xiao, L.; Zhang, H.; Tao, J.; Gu, W.; Gu, J.; Chen, C. Effect of facility management regimes on soil bacterial diversity and community structure. Chin. J. Eco-Agric. 2017, 25, 1615–1625. [Google Scholar]
  78. Gupta, P.K.; Gandhi, M. Bioremediation of organic pollutants in soil–water system: A review. BioTech 2023, 12, 36. [Google Scholar] [CrossRef]
  79. Kuypers, M.M.M.; Marchant, H.K.; Kartal, B. The microbial nitrogen-cycling network. Nat. Rev. Microbiol. 2018, 16, 263–276. [Google Scholar] [CrossRef] [PubMed]
  80. Zhang, L.; Liu, W.; Liu, S.; Zhang, P.; Ye, C.; Liang, H. Revegetation of a barren rare earth mine using native plant species in reciprocal plantation: Effect of phytoremediation on soil microbiological communities. Environ. Sci. Pollut. Res. 2020, 27, 2107–2119. [Google Scholar] [CrossRef]
  81. Sun, H.; Chen, Q.; Qu, C.; Tian, Y.; Song, J.; Liu, Z.; Guo, J. Occurrence of OCPs & PCBs and their effects on multitrophic biological communities in riparian groundwater of the Beiluo River, China. Ecotoxicol. Environ. Saf. 2023, 253, 114713. [Google Scholar]
  82. van der Zaan, B.M.; Saia, F.T.; Stams, A.J.; Plugge, C.M.; de Vos, W.M.; Smidt, H.; Langenhoff, A.A.; Gerritse, J. Anaerobic benzene degradation under denitrifying conditions: Peptococcaceae as dominant benzene degraders and evidence for a syntrophic process. Environ. Microbiol. 2012, 14, 1171–1181. [Google Scholar] [CrossRef]
  83. He, L.; Hong, Q.; Li, S. Characterization of a phenanthrene-degrading strain and cloning of degradation-related gene. Chin. J. Appplied Environ. Biol. 2009, 2009, 682–685. [Google Scholar] [CrossRef]
  84. Yang, X.; Zhang, W.; Li, S.; Zhang, M.; Liu, G.; Chen, T.; Hu, P.; Wu, X.; Tai, X.; Chen, W. Study on isolation, identification and physiological characteristics of PAHs-degrading bacteria. Huanjing Kexue Xuebao Acta Sci. Circumstantiae 2012, 32, 1033–1040. [Google Scholar]
  85. Liang, S.; Deng, J.; Jiang, Y.; Wu, S.; Zhou, Y.; Zhu, W.X. Functional distribution of bacterial community under different land use patterns based on FaProTax function prediction. Pol. J. Environ. Stud. 2020, 29, 1245–1261. [Google Scholar] [CrossRef]
  86. Qiao, Y.; Miao, S.; Han, X.; Yue, S.; Tang, C. Improving soil nutrient availability increases carbon rhizodeposition under maize and soybean in Mollisols. Sci. Total Environ. 2017, 603, 416–424. [Google Scholar] [CrossRef]
  87. Mengel, K. Responses of various crop species and cultivars to fertilizer application. Plant Soil 1983, 72, 305–319. [Google Scholar] [CrossRef]
  88. Muneer, M.A.; Chen, X.; Munir, M.Z.; Nisa, Z.-U.; Saddique, M.A.B.; Mehmood, S.; Su, D.; Zheng, C.; Ji, B. Interplant transfer of nitrogen between C3 and C4 plants through common mycorrhizal networks under different nitrogen availability. J. Plant Ecol. 2023, 16, 2. [Google Scholar] [CrossRef]
  89. Hildebrandt, T.M.; Nunes Nesi, A.; Araújo, W.L.; Braun, H.-P. Amino acid catabolism in plants. Mol. Plant 2015, 8, 1563–1579. [Google Scholar] [CrossRef]
  90. Zhang, Z.; Mao, C.; Shi, Z.; Kou, X. The amino acid metabolic and carbohydrate metabolic pathway play important roles during salt-stress response in tomato. Front. Plant Sci. 2017, 8, 1231. [Google Scholar] [CrossRef]
  91. Rucker, R.B.; Steinberg, F.M.; Chowanadisai, W. Organic: Biochemical mechanisms and regulation of vitamins and vitamin-like cofactors. Encycl. Hum. Nutr. (Fourth Ed.) 2023, 2, 215–249. [Google Scholar]
  92. Naya, L.; Ladrera, R.; Ramos, J.; González, E.M.; Arrese-Igor, C.; Minchin, F.R.; Becana, M. The response of carbon metabolism and antioxidant defenses of alfalfa nodules to drought stress and to the subsequent recovery of plants. Plant Physiol. 2007, 144, 1104–1114. [Google Scholar] [CrossRef] [PubMed]
  93. Wu, Z.; Gao, G.; Wang, Y. Effects of soil properties, heavy metals, and PBDEs on microbial community of e-waste contaminated soil. Ecotoxicol. Environ. Saf. 2019, 180, 705–714. [Google Scholar] [CrossRef] [PubMed]
  94. Haghighi, Z.; Karimi, N.; Modarresi, M.; Mollayi, S. Enhancement of compatible solute and secondary metabolites production in Plantago ovata Forsk. by salinity stress. J. Med. Plants Res. 2012, 6, 3495–3500. [Google Scholar]
  95. Cui, G.; Zhang, Y.; Zhang, W.; Lang, D.; Zhang, X.; Li, Z.; Zhang, X. Response of carbon and nitrogen metabolism and secondary metabolites to drought stress and salt stress in plants. J. Plant Biol. 2019, 62, 387–399. [Google Scholar] [CrossRef]
  96. Gong, X.; Feng, Y.; Dang, K.; Jiang, Y.; Qi, H.; Feng, B. Linkages of microbial community structure and root exudates: Evidence from microbial nitrogen limitation in soils of crop families. Sci. Total Environ. 2023, 881, 163536. [Google Scholar] [CrossRef]
  97. Sivaram, A.K.; Logeshwaran, P.; Lockington, R.; Naidu, R.; Megharaj, M. The impact of low molecular weight organic acids from plants with C3 and C4 photosystems on the rhizoremediation of polycyclic aromatic hydrocarbons contaminated soil. Environ. Technol. Innov. 2020, 19, 100957. [Google Scholar] [CrossRef]
  98. Sivaram, A.K.; Logeshwaran, P.; Subashchandrabose, S.R.; Lockington, R.; Naidu, R.; Megharaj, M. Comparison of plants with C3 and C4 carbon fixation pathways for remediation of polycyclic aromatic hydrocarbon contaminated soils. Sci. Rep. 2018, 8, 2100. [Google Scholar] [CrossRef]
Agriculture 14 01637 g001
Figure 1. α-diversity of soil bacteria in the rhizosphere of different treatments. (a) Chao 1. (b) observed_species. (c) Phylogenetic Diversity (PD)_whole_tree. (d) Shannon. Different letters in the same column indicate significant difference (p < 0.05) (CK1, BTBPE-contaminated soil without plant; SI, Setaria italica (L.) Beauv.; ZM, Zea mays L.; AT, Amaranthus tricolor L.; TA, Triticum aestivum L.; GM, Glycine max (L.) Merr.; MS, Medicago sativa L.; LP, Lolium perenne L.).
Figure 1. α-diversity of soil bacteria in the rhizosphere of different treatments. (a) Chao 1. (b) observed_species. (c) Phylogenetic Diversity (PD)_whole_tree. (d) Shannon. Different letters in the same column indicate significant difference (p < 0.05) (CK1, BTBPE-contaminated soil without plant; SI, Setaria italica (L.) Beauv.; ZM, Zea mays L.; AT, Amaranthus tricolor L.; TA, Triticum aestivum L.; GM, Glycine max (L.) Merr.; MS, Medicago sativa L.; LP, Lolium perenne L.).
Agriculture 14 01637 g001
Agriculture 14 01637 g002
Figure 2. Non-metric multidimensional scaling (NMDS) analysis and Partial Least Squares Discriminant Analysis (PLS-DA) of bacterial communities in rhizosphere soil of different treatments. Ellipses are used to compare the similarity of community structure composition between groups. (a) NMDS analysis of different plants. (b) NMDS analysis of C3 and C4 plants. (c) Partial Least Squares Discriminant Analysis (PLS-DA) of different plants. (d) Partial Least Squares Discriminant Analysis (PLS-DA) of C3 and C4 plants (CK1, BTBPE-contaminated soil without plant; SI, Setaria italica (L.) Beauv.; ZM, Zea mays L.; AT, Amaranthus tricolor L.; TA, Triticum aestivum L.; GM, Glycine max (L.) Merr.; MS, Medicago sativa L.; LP, Lolium perenne L.).
Figure 2. Non-metric multidimensional scaling (NMDS) analysis and Partial Least Squares Discriminant Analysis (PLS-DA) of bacterial communities in rhizosphere soil of different treatments. Ellipses are used to compare the similarity of community structure composition between groups. (a) NMDS analysis of different plants. (b) NMDS analysis of C3 and C4 plants. (c) Partial Least Squares Discriminant Analysis (PLS-DA) of different plants. (d) Partial Least Squares Discriminant Analysis (PLS-DA) of C3 and C4 plants (CK1, BTBPE-contaminated soil without plant; SI, Setaria italica (L.) Beauv.; ZM, Zea mays L.; AT, Amaranthus tricolor L.; TA, Triticum aestivum L.; GM, Glycine max (L.) Merr.; MS, Medicago sativa L.; LP, Lolium perenne L.).
Agriculture 14 01637 g002
Agriculture 14 01637 g003
Figure 3. Composition characteristics of bacterial phylum (a,b) and genus (c,d) in rhizosphere soil of different treatments (CK1 BTBPE-contaminated soil, SI Setaria italica (L.) Beauv., ZM Zea mays L., AT Amaranthus tricolor L., TA Triticum aestivum L., GM Glycine max (L.) Merr., MS Medicago sativa L., LP Lolium perenne L.).
Figure 3. Composition characteristics of bacterial phylum (a,b) and genus (c,d) in rhizosphere soil of different treatments (CK1 BTBPE-contaminated soil, SI Setaria italica (L.) Beauv., ZM Zea mays L., AT Amaranthus tricolor L., TA Triticum aestivum L., GM Glycine max (L.) Merr., MS Medicago sativa L., LP Lolium perenne L.).
Agriculture 14 01637 g003
Agriculture 14 01637 g004
Figure 4. Evolutionary branch diagram of bacteria in rhizosphere soil of C3 and C4 plants based on LEfSe analysis. The circles radiating from the center represent taxonomic levels from phylum to genus (or species). Each small circle at different taxonomic levels represents a classification at that level, with the diameter of the circle proportional to its relative abundance. The coloring principle is as follows: species with no significant difference are uniformly colored to yellow, while biomarkers of the different species are colored according to their respective groups. Red nodes represent microbial groups that are significant in the red group, and the green nodes represent the microbial groups that are significant in the green group. Other circles follow the same color meaning. The species names represented by the English letters in the figure are displayed in the right legend.
Figure 4. Evolutionary branch diagram of bacteria in rhizosphere soil of C3 and C4 plants based on LEfSe analysis. The circles radiating from the center represent taxonomic levels from phylum to genus (or species). Each small circle at different taxonomic levels represents a classification at that level, with the diameter of the circle proportional to its relative abundance. The coloring principle is as follows: species with no significant difference are uniformly colored to yellow, while biomarkers of the different species are colored according to their respective groups. Red nodes represent microbial groups that are significant in the red group, and the green nodes represent the microbial groups that are significant in the green group. Other circles follow the same color meaning. The species names represented by the English letters in the figure are displayed in the right legend.
Agriculture 14 01637 g004
Agriculture 14 01637 g005
Figure 5. Difference analysis of FAPROTAX function prediction in soil bacterial communities in rhizosphere of C3 and C4 plants.
Figure 5. Difference analysis of FAPROTAX function prediction in soil bacterial communities in rhizosphere of C3 and C4 plants.
Agriculture 14 01637 g005
Agriculture 14 01637 g006
Figure 6. Difference in functional prediction of PICRUSt 2 in soil bacterial communities in rhizosphere of C3 and C4 plants (KEGG level 2).
Figure 6. Difference in functional prediction of PICRUSt 2 in soil bacterial communities in rhizosphere of C3 and C4 plants (KEGG level 2).
Agriculture 14 01637 g006
Table 1. Bacterial species richness and diversity indices in rhizosphere soil of different treatments.
Table 1. Bacterial species richness and diversity indices in rhizosphere soil of different treatments.
SampleASVsChao1PD_Whole TreeShannonSimpson
CK649.67 ± 62.34 b657.99 ± 71.02 a51.86 ± 1.96 a7.29 ± 0.11 a0.98 ± 0.0047 a
CK1711.67 ± 223.73 a719.58 ± 229.01 a50.33 ± 7.97 a7.31 ± 0.35 a0.98 ± 0.0047 a
SI (C4)526.33 ± 24.14 ab526.09 ± 23.98 a41.05 ± 2.43 a7.08 ± 0.10 a0.97 ± 0.0000 a
ZM (C4)619.33 ± 82.40 ab620.72 ± 83.42 a44.04 ± 4.97 a7.23 ± 0.79 a0.94 ± 0.0403 a
AT (C4)742.33 ± 87.81 ab752.62 ± 88.63 a51.76 ± 1.97 a7.84 ± 0.26 a0.98 ± 0.0047 a
TA (C3)574.67 ± 114.77 ab581.04 ± 118.08 a38.73 ± 6.75 a7.25 ± 0.17 a0.98 ± 0.0047 a
GM (C3)636.67 ± 55.93 ab641.52 ± 59.08 a43.77 ± 2.69 a7.78 ± 0.15 a0.98 ± 0.0000 a
MS (C3)678.00 ± 120.22 ab684.83 ± 125.50 a49.34 ± 7.26 a7.59 ± 0.20 a0.98 ± 0.0047 a
LP (C3)692.67 ± 106.69 a698.25 ± 111.01 a49.00 ± 8.02 a7.62 ± 0.08 a0.98 ± 0.0000 a
Note: 1. CK, no BTBPE-contaminated soil without plant; CK1, BTBPE-contaminated soil without plant; SI, Setaria italica (L.) Beauv.; ZM, Zea mays L.; AT, Amaranthus tricolor L.; TA, Triticum aestivum L.; GM, Glycine max (L.) Merr.; MS, Medicago sativa L.; LP, Lolium perenne L. 2. Values are the mean ± Standard Deviation (SD) (n = 3), and different letters in the same column indicate significant difference (p < 0.05).
Table 2. Number of newly emerging bacteria at different taxonomic levels in various plant treatment groups compared to CK1.
Table 2. Number of newly emerging bacteria at different taxonomic levels in various plant treatment groups compared to CK1.
PhylumClassOrderFamilyGenusSpecies
SI (C4)0211183392
ZM (C4)12183044143
AT (C4)04173239120
TA (C3)00111965112
GM (C3)23142490130
MS (C3)16203083127
LP (C3)382335109153
Note: CK1, BTBPE-contaminated soil without plant; SI, Setaria italica (L.) Beauv.; ZM, Zea mays L.; AT, Amaranthus tricolor L.; TA, Triticum aestivum L.; GM, Glycine max (L.) Merr.; MS, Medicago sativa L.; LP, Lolium perenne L.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Chen, Y.; Wang, S.; Li, Y.; Liu, W.; Niu, Z. Response of Bacterial Community Structure and Function in Rhizosphere Soil on the Photosynthesis of Selected Plant Types C3 and C4 under Bis(2,4,6-tribromophenoxy) Ethane Exposure. Agriculture 2024, 14, 1637. https://doi.org/10.3390/agriculture14091637

AMA Style

Chen Y, Wang S, Li Y, Liu W, Niu Z. Response of Bacterial Community Structure and Function in Rhizosphere Soil on the Photosynthesis of Selected Plant Types C3 and C4 under Bis(2,4,6-tribromophenoxy) Ethane Exposure. Agriculture. 2024; 14(9):1637. https://doi.org/10.3390/agriculture14091637

Chicago/Turabian Style

Chen, Yixuan, Sen Wang, Yuru Li, Wanyu Liu, and Zhenchuan Niu. 2024. "Response of Bacterial Community Structure and Function in Rhizosphere Soil on the Photosynthesis of Selected Plant Types C3 and C4 under Bis(2,4,6-tribromophenoxy) Ethane Exposure" Agriculture 14, no. 9: 1637. https://doi.org/10.3390/agriculture14091637

APA Style

Chen, Y., Wang, S., Li, Y., Liu, W., & Niu, Z. (2024). Response of Bacterial Community Structure and Function in Rhizosphere Soil on the Photosynthesis of Selected Plant Types C3 and C4 under Bis(2,4,6-tribromophenoxy) Ethane Exposure. Agriculture, 14(9), 1637. https://doi.org/10.3390/agriculture14091637

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop