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Article

Potential Changes in Soil Microbial Composition under 1,2-Dichlorobenzene Contamination

by
Wen-Ting Huang
and
Yo-Jin Shiau
*
Department of Bioenvironmental Systems Engineering, National Taiwan University, Taipei 10617, Taiwan
*
Author to whom correspondence should be addressed.
Sustainability 2023, 15(2), 1432; https://doi.org/10.3390/su15021432
Submission received: 6 December 2022 / Revised: 4 January 2023 / Accepted: 9 January 2023 / Published: 12 January 2023
(This article belongs to the Section Hazards and Sustainability)
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Abstract

:
Chlorine-containing organic compounds are important industrial solvents but are severely toxic to humans and the environment. Because of their stability and dense non-aqueous phase, they barely biodegrade when released into soil and groundwater systems and may significantly impact the soil environment. One bioremediation approach, biostimulation, adds rate-limiting nutrients to the soil to promote biodegradation processes, but the link remains unclear between stimulated microbial communities and nutrient inputs in anaerobic environments. This study evaluated changes to soil microbial communities in 1,2-dichlorobenzene (1,2-DCB)-contaminated soil under diverse carbon (C) and nutrient conditions. The experiments used anaerobic microcosms that were amended with various C and nutrient sources, and the analysis employed real-time PCR and next-generation sequencing. The results reveal that methanogens may have high resistance to 1,2-DCB in oligotrophic conditions. However, bacteria such as Pseudomonas, Sphingomonas, and some uncultured genera in the Xanthomonadaceae, Pseudomonadaceae, and Bacillales families can resist high 1,2-DCB concentrations when N and P sources are available. These results indicate that external N and P sources are important for stabilizing soil microbial communities and their processes in contaminant sites.

Graphical Abstract

1. Introduction

Chlorine-containing organic compounds, such as 1,2-dichlorobenzene (1,2-DCB), are widely used in dye manufacturing and as industrial solvents for toluene diisocyanate because of their high affinity for lipids [1,2]. They can be used as intermediate products, cleaners for mechanical parts, and solvents for pesticides. However, chlorine-containing organic substances are usually carcinogenic and pose exposure and pollution risks to humans, soil, and groundwater [3,4]. For example, chlorpyrifos is a chlorine-containing organic compound that causes neurological diseases in young and old people [5,6]. Paclobutrazol, a chlorine-containing organic compound widely used as a plant growth regulator in agriculture [7], may cause a serious ecosystem imbalance [8]. Similarly, 1,2-DCB has been shown to effectively bind liver and kidney proteins and cause centrolobular necrosis [9].
Because of the stability of chlorine-containing organic compounds, they are barely degraded or decomposed naturally in the environment. Thus, they are typically remediated with amended strong chemical oxidants or reductants. In the current development stage of contaminant removal techniques, the chemical reduction or oxidation of chlorine-containing organic compounds is the most widely used remediation technique. In situ chemical oxidation introduces oxidants into the environment and produces oxidative free radicals to degrade contaminants [10]. For example, a heat-activated persulfate chemical oxidation process has been developed to effectively degrade dichlorodiphenyltrichloroethane (DDT) [11]. Similarly, an iron-carbon catalyst with persulfate activation sites has been developed to accelerate the degradation of phenol [12,13].
In recent years, bioremediation has emerged as an alternative remediation method for chlorine-containing organic compounds, as it is cost-effective and environmentally friendly [14]. Two major approaches, bioaugmentation and biostimulation, are considered to offer the best bioremediation for waste degradation [15]. The bioaugmentation method adds external microbial strains that have the ability to degrade the toxic contaminates [16]. Studies show that chlorpyrifos can be effectively degraded by amended fungal strains, such as Byssochlamys spectabilis, Aspergillus fumigates, and Aspergillus terreus TF1 [5,17], as well as by bacterial strains, such as Pseudomonas putida T7, Pseudomonas aeruginosa M2, and Klebsiella pneumoniae M6 [5]. Similarly, Dehalocococcoides sp. is also found capable of degrading chlorinated ethylenes [18]. Diaphorobacter sp. strain JS3051, another dechlorinating bacteria, can effectively utilize 2,3-dichloronitrobenzene, 3-chloronitrobenzene, and 3-bromonitrobenzene as carbon sources [19,20]. Pseudomonas and Arthrobacter are also found to be effective atrazine-degrading bacterial genera [21]. However, bioaugmentation is usually not the best approach for bioremediation, as it does not permit the evaluation of the collaborative metabolic functions of diverse microbial communities in real contaminant sites [8].
By contrast, the biostimulation remediation technique adds rate-limiting nutrients, such as phosphorus, nitrogen, and electron donors, to contaminated sites to stimulate the existing microbial communities that are capable of degrading toxins [15,22,23]. For example, studies have shown the potential of using bioremediation for chlorine-containing organic degradation using mixed cultures in anaerobic reductive dechlorination and have successfully degraded hexachlorobenzene compounds [24]. Similarly, research indicates that dioxygenase may play an important role in degrading chlorine-containing organics under aerobic conditions, as the enzyme first oxidizes chlorobenzene by introducing oxygen molecules into its aromatic structures for subsequent decyclization [25]. Other studies show that chlorocycloalkanes can be degraded through the synergistic action of methanogens, sulfate-reducing bacteria, and dechlorination bacteria under anaerobic environmental conditions [26]. In addition, Yuan et al. [27] observed that gamma-hexachlorocyclohexane degradation rates were positively correlated to methane emissions during a seven-day microcosm experiment.
Most previous studies have been conducted in laboratory environments with pure cultured microbes to determine the maximum biodegradation potential for chlorine-containing organic compounds, and the majority of related mesocosm studies have focused on the biodegradation of such organisms under aerobic soil environments [28,29,30,31,32,33]. Because many chlorine-containing organic pollutants are dense non-aqueous phase liquids (DNAPLs), however, they usually sink to deep soil layers or groundwater and must be biodegraded under anaerobic conditions in contaminant sites, yet few studies have examined the potential effects of these pollutants on the microbial communities in the soil or their potential for biodegradation under anaerobic conditions. Indeed, using 13C isotopes as tracers, a recent study has shown that the biodegradation of 1,4-DCB is controlled by anaerobic reductive dechlorination [34]. Thus, learning about microbial community compositions in anaerobic environments contaminated with chlorine-containing organic compounds will benefit future bioremediation projects at contamination sites.
Next-generation sequencing (NGS), a parallel sequencing technology commonly used in environmental microbiological studies [35], offers high-throughput data and can recover DNA sequences directly from environmental samples without the vector-based cloning required by conventional methods [36,37]. Thus, it can process complex environmental samples that the conventional Sanger DNA sequencing method cannot [35]. Another common method of detecting the populations of specific types of microorganisms is real-time polymerase chain reaction (PCR), known as quantitative PCR (qPCR) [38]. The technique detects the fluorescent signal in real time during DNA amplification and calculates the absolute quantity of the target DNA by comparison with the signals of standard samples [39,40]. When using NGS, studies have uncovered that microorganisms belonging to Desulfovibrio sp. may degrade 1,2,3-trichloropropane (TCP) under anaerobic environments [41].
This study used NGS and qPCR to identify changes to the soil microbial composition over time in 1,2-DCB-contaminated microcosms with amended carbon and/or nutrient sources (i.e., N and P) to deepen our understanding of which microbial communities may better tolerate 1,2-DCB under anaerobic conditions.

2. Materials and Methods

2.1. Site Description and Microcosm Preparation

As its reference, this study selected a site in Tao-Yuan City, Taiwan, that the Taiwan Environmental Protection Administration (TWEPA) had declared a soil- and groundwater-contaminated site in February 2004. The major pollutants at the site were 1,2-DCB and 1,4-DCB, with concentrations of approximately 5000 ppm at soil depths of 7–9 m. The composition of soil particles was 87% sand and 13% silt and clay.
For the microcosm study, pot soil and standard silica sand were mixed with the above-mentioned particle composition. Soil microbes were extracted from sediment from the contaminant site and added to the microcosms. The microbial extraction followed the recommendations of previous studies, with some modifications [42,43]. Briefly, the field-collected sediments were added to 0.85% NaCl at a 1:9 soil:solution ratio, exposed to ultrasonic shock for 30 min, and then centrifuged at 4000 rcf for 10 min to collect the supernatant. After the microbial provenance solution was prepared, around 1 kg of mixed bulk soil was placed in a 500 mL wide-mouth serum bottle, and 50 mL of provenance solution was added in an anaerobic operation table. The bottle was then sealed and pre-incubated at 25 °C for 15 days.

2.2. Anaerobic Microcosm Experiments

After the bulk soil had been pre-incubated for 15 days, a total of 28 microcosm bottles were prepared. First, the pre-incubated soil was homogenized in an anaerobic operation table. For each microcosm, 10 g of soil was weighed out, placed into a 30 mL serum bottle, and sealed with a serum stopper and aluminum cap. The 28 bottles (i.e., 28 microcosms) were randomly separated into seven groups, each with four microcosms, and 1,2-DCB was added to six of the seven groups at a concentration of 5000 mg/kg of soil. The last group (designated as G) did not receive 1,2-DCB.
The first group of samples (designated A) underwent no treatment. The second and fifth groups of samples (B group and E group, respectively) were treated with 0.3 mL of 99.9% carbon dioxide (CO2) to obtain a CO2 concentration in the headspace of around 10,000 ppm. The third and sixth groups of microcosms (C group and F group, respectively) were treated with 0.3 mL of 99.9% methane (CH4) to produce a CH4 concentration of around 10,000 ppm in the bottle. The fourth group (D group) and the E and F groups were each treated with around 1 mL of 10 mM NH4NO3 and 10 mM K2HPO4. The seventh group (G group) did not undergo treatment with any C, N, or P sources. The soil of the samples was analyzed for the initial condition at day 0, and the soil chemical and microbial experiments were conducted on days 7, 14, 42, and 63 after incubation.

2.3. Soil Chemical and Microbial Experiments

On days 7, 14, 42, and 63 after incubation, a microcosm from each group was randomly selected and subjected to chemical and microbial experiments. For each treatment, 0.5 g of soil was weighed out from each microcosm to extract the genomic DNA using a DNA extraction kit (PowerSoil DNA isolation kit, Qiagen, Hilden, Düsseldorf, Germany). The extraction steps were carried out according to the manufacturer’s instructions, with one modification: the “bead solution” in the kits was replaced with the same quantity of a mixed solution of phenol:chloroform:isoamyl alcohol.
The extracted DNA was amplified for the 16S rRNA amplicons with a universal primer pair (515F/806R) and reagent kit (Taq DNA polymerase 2× Master Mix RED, Ampliqon, Denmark). The 16S rRNA amplicons were sequenced on the Illumina MiSeq platform (Nextera XT DNA Library Preparation Kit, Illumina, San Diego, CA, USA). The extracted genomic DNA was analyzed for 16S rRNA and bphA gene copies with a reagent kit (GoTaq qPCR Master Mix, Promega Co., Madison, WI, USA) using a real-time PCR detection system (CFX Connect, Bio-Rad Laboratories Inc., Hercules, CA, USA). Soil anion concentrations were extracted using a hot water extraction method [44,45] and analyzed by ion chromatography (Eco IC, Metrohm AG, Herisau, Switzerland).

2.4. Data Analysis and Statistical Analysis

The sequence data were assembled and calculated for the operational taxonomic units (OTUs) using Mothur version 1.47 [46] and the RDP V18 database. The 50 most dominant OTUs were selected to calculate the phylogenetic trees using MEGA X [47], and the trees were then finalized using EvolView version 3 [48]. One-way ANOVA and Tukey’s honestly significant difference analysis were performed using JMP 11.0 (SAS Inc., Cary, NC, USA). A redundancy analysis (RDA) was performed using RStudio 1.3. to analyze the relationship between soil chemical properties and representative OTUs. The 16S rRNA gene sequences obtained from MiSeq sequencing have been deposited in the NCBI under accession number PRJNA916587.

3. Results

The results of soil anion concentrations show that the addition of CO2 increased the mineralization of soil sulfate and chloride concentrations after 63 days of incubation (Figure 1, A, B, and C). In addition, the sulfate and chloride concentrations greatly increased, while the nitrate and phosphate were consumed by microbial communities with amended N and P nutrients after incubation in the D group. The phosphate concentration was highest in the E group (i.e., soil amended with CO2, N, and P).
Using real-time PCR, we measured the results of the total amount of microorganisms in each group, which significantly decreased after being amended with 1,2-DCB and then increased over time (Figure 2). No difference in microbial population was observed among treatments (i.e., groups) amended with 1,2-DCB after incubation, but all the treatments resulted in significantly lower populations than in the reference treatment (i.e., group G).
Similarly, the dechlorinated bphA functional gene copies in the microcosms first decreased after amendment with 1,2-DCB and then recovered throughout the incubation periods (Figure 3). In addition, the number of bphA copies was found to be higher in the B, D, and E groups.
In this study, approximately 77,283 sequences were obtained from each soil sample, with the G + C content at 57%. The results of NGS show that Proteobacteria, Actinobacteria, and Acidobacteria were the dominant phyla in the soil in the early stage of the incubation experiment (Figure 4, Table S1). After the microcosms were amended with 1,2-DCB and other inorganic C sources, the Euryarchaeota phylum increased in the A, B, and C groups over time. Meanwhile, in the microcosms amended with 1,2-DCB and inorganic C and N sources (i.e., groups D, E, and F), both the Euryarchaeota and Proteobacteria increased over time. In addition, Actinobacteria increased in relative abundance in groups A, C, D, E, and F. However, Acidobacteria decreased in abundance after incubation in all treatments.
The results showing the 50 dominant representative OTUs in this study mostly correlated to genera that had not yet been classified and were widely observed in the microcosms of all treatments (Figure 5). OTU-1, which was distinctly correlated to Methanobacterium sp., appeared to be the dominant OTU. OTU-3 and OTU-30 (which were distinctly correlated to Sphingomonas sp.), OTU-8 and OTU-15 (which were distinctly correlated to Pseudomonas sp.), and OTU-6 (which was distinctly correlated to Anaeromyxobacter) also showed high relative abundances in the microcosms after 63 days of incubation. It is worth noting that OTU-2, which belongs to the order Myxococcales, was the second-most abundant OTU.
By combining the soil chemical and microbial data in this study for RDA, we found that OTU-1 and OTU-2 had a positive relationship with the chloride ion in the environment, while OTU-3 and OTU-7 had a positive relationship with other soil anions, such as NO3−, PO43−, and SO42− (Figure 6).

4. Discussion

This study measured changes in microbial communities in soils that were contaminated with 1,2-DCB under microcosm conditions. The resulting anion concentrations imply that microorganisms may decompose 1,2-DCB in environments enriched by CO2 and/or nutrients (i.e., N and P), as in groups B, D, and E. Thus, some heterotrophic and autotrophic microbes may have the ability to survive the adverse environments associated with 1,2-DCB. Nevertheless, the 16S rRNA copy results imply that, overall, soil microbial populations were significantly reduced by the addition of 1,2-DCB, possibly due to its toxicity. However, the similar numbers of 16S rRNA copies among all the treatments after 63 days of incubation imply that some microorganisms may possess functional traits to resist the toxicity of 1,2-DCB environments, even though they may not be able to decompose the contaminant [49]. In addition, because the pot soil for the incubation experiment also contained organic carbon for heterotrophic microorganisms, it may have provided carbon sources for microbial growth, thus suggesting no correlation between the overall microbial populations and the degradation of contaminants.
The results of the bphA gene copies also support the above-mentioned assumption, as the groups amended with CO2 and/or nutrients (i.e., N and P) had more bphA copies. In group B specifically, the bphA copies increased by more than 2500 times in the late stage of incubation compared to the original soil. Because the increased bphA copies correlate with the increased chloride concentration, we speculate that CO2 potentially facilitates the biodegradation of 1,2-DCB. In addition, the low number of bphA copies in the A and C groups suggests that the majority of microorganisms in the soils may tolerate but not decompose 1,2-DCB, or that some environmental niches that are not affected by 1,2-DCB were formed in the incubated soils [50,51].
The dominant phylum after incubation was Euryarchaeota, which is one of the phyla responsible for methanogenesis. Three types of methanogens that use CO2, methanol, or acetate as C sources exist in nature [52]. Because the major methanogens found in the treatments are distinctly correlated to Methanobacterium sp., which are mostly hydrogenotrophic methanogens [53], the amended CO2 concentrations may facilitate their growth. Previous studies have shown that methanogens can decompose chlorine-containing organic compounds, such as hexachlorocyclohexane [27] and pentachlorophenol [54], in addition to generating CH4. Thus, we suspect that the dominance of Euryarchaeota may be due to the adaptability of this phylum in a chlorine-containing environment. This result may also explain the higher chloride concentration observed in the B group after 63 days of incubation.
The Actinobacteria phylum also increased in relative abundance by the end of the incubation period in some groups. A previous study found that many species of this phylum have high resistance to chlorine-containing antibiotics [55], and other studies have shown that this phylum can live in environments with high Cl− concentrations and can be used for antibiotic production [56,57]. Thus, we suspect that the Actinobacteria observed in the microcosms may confirm their high resistance to chlorine-containing environments.
Acidobacteria contain mostly chemoorganotrophic and aerobic microbes in the environment [58], and microbes in this phylum are important to carbohydrate decomposition in nature [58,59]. However, previous studies indicate that Acidobacteria have low growth rates and grow better in oligotrophic environments than in eutrophic ones [58,60,61]. Our finding of decreased Acidobacteria may be attributed to the ecological role of K-strategists. Furthermore, the result may imply that 1,2-DCB is not the C source for Acidobacteria.
The Proteobacteria phylum, by contrast, embraces a wide variety of microorganisms that are either lithotrophic or organotrophic, aerobic or anaerobic [62]. Bacteria belonging to the Proteobacteria are mostly important in regulating natural element cycles, such as C, N, S, and P [62]. Recent studies also show that some Proteobacteria species are capable of degrading chlorine compounds in anaerobic environments [63,64]. Some microorganisms have also been shown to participate in an intra-aerobic pathway that derives oxygen from inorganic oxo-compounds [64,65,66]. If we consider the chloride concentration as an indicator that is positively correlated to 1,2-DCB degradation in the present study, the higher chloride but lower nitrate and phosphate concentrations imply that some Proteobacteria microorganisms may engage in intra-aerobic processes in degrading 1,2-DCB during incubation. This observation also implies that nitrate and phosphorus may be important inorganic nutrients for future biostimulation projects.
This study’s data on the most prevalent OTUs show that—in addition to Methanobacterium—Pseudomonas, Nocardioides, and unclassified genera belonging to the Xanthomonadaceae family were also prominent in some microcosms. Studies have shown that some methanogens can biodegrade chlorine-containing compounds [67] or engage in synergistic interactions with other dechlorinating microbial communities [68]. Because we observed the highest number of bphA gene copies, the greatest decrease in chloride concentration, and the greatest abundance of Methanobacterium in the B group, we suspect that dechlorinating processes involving Methanobacterium likely occurred in this treatment. Notably, the bphA-to-16S rRNA ratios were less than 0.1%, which does not equal the magnitude of Methanobacterium’s abundance (i.e., more than 80% in the B group). Methanobacterium may not necessarily contribute to yielding the highest number of bphA copies.
Furthermore, greater numbers of Pseudomonas, Sphingomonas, Nocardioides, Anaeromyxobacter, and unclassified genera of the Xanthomonadaceae family were found in the treatments amended with N and P concentrations. Studies indicate that many species in these genera can degrade chlorine-containing organic substances [69,70,71], and other studies show that these genera are important in nitrate reduction [72,73,74]. Thus, we suspect that the high relative abundance of these three OTUs may correlate with the presence of 1,2-DCB in the microcosms amended with nitrate.
An increasing number of studies have found that microorganisms such as anaerobic fermentative bacteria, denitrifying bacteria, and hydrogen-producing acetogenic bacteria have positive correlations between their abundance and the dichlorobenzene concentration in the environment [27,32]. Furthermore, a comparative analysis of 27 Myxococcus genomes identified carotenoid genes in all three Myxococcus suborders, indicating that Myxococcales can regulate the B12-dependent pathway of carotenoid production through light [75]. Another study shows the synergistic effect of zero-valent magnesium and vitamin B12 in degrading chlorine-containing organic matter in pure anhydrous ethanol [76]. Thus, the high abundance of unclassified OTUs distinctly correlates to the Myxococcales order, and the positive relationship of this order with the Cl− concentration in this study implies that some species may also be able to degrade chlorine-containing organic substances, meriting further investigation.

5. Conclusions

This study investigated changes in microbial composition in 1,2-DCB-contaminated soils under diverse environmental conditions. Our analyses determined that the overall microbial population fell by more than 90% under high 1,2-DCB concentrations. In addition, the OTU that was distinctly correlated with Methanobacterium sp. was the most dominant OTU in 1,2-DCB-contaminated soils under oligotrophic conditions. Furthermore, Pseudomonas, Sphingomonas, and some uncultured genera in the Xanthomonadaceae, Pseudomonadaceae, and Bacillales families can tolerate 1,2-DCB concentrations in N- and P-enriched anaerobic environments. These results indicate that external N sources are important for stabilizing soil microbial communities and their processes at contaminant sites.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/su15021432/s1, Table S1: Relative abundance of soil microbial community at phylum level in microcosms amended with 1,2-DCB (A); 1,2-DCB and CO2 (B); 1,2-DCB and CH4 (C); 1,2-DCB, N, and P (D); 1,2-DCB, CO2, N, and P (E); 1,2-DCB, CH4, N, and P (F); and no chemical amendment (G); Table S2: Relative abundance of soil microbial community at class level in microcosms amended with 1,2-DCB (A); 1,2-DCB and CO2 (B); 1,2-DCB and CH4 (C); 1,2-DCB, N, and P (D); 1,2-DCB, CO2, N, and P (E); 1,2-DCB, CH4, N, and P (F); and no chemical amended (G); Table S3: Relative abundance of soil microbial community at order level in microcosms amended with 1,2-DCB (A); 1,2-DCB and CO2 (B); 1,2-DCB and CH4 (C); 1,2-DCB, N, and P (D); 1,2-DCB, CO2, N, and P (E); 1,2-DCB, CH4, N, and P (F); and no chemical amendment (G); Table S4: Relative abundance of soil microbial community at family level in microcosms amended with 1,2-DCB (A); 1,2-DCB and CO2 (B); 1,2-DCB and CH4 (C); 1,2-DCB, N, and P (D); 1,2-DCB, CO2, N, and P (E); 1,2-DCB, CH4, N, and P; (F) and no chemical amendment (G); Table S5: Relative abundance of soil microbial community at genus level in microcosms amended with 1,2-DCB (A); 1,2-DCB and CO2 (B); 1,2-DCB and CH4 (C); 1,2-DCB, N, and P (D); 1,2-DCB, CO2, N, and P (E); 1,2-DCB, CH4, N, and P (F); and no chemical amendment (G).

Author Contributions

Conceptualization, Y.-J.S.; methodology, Y.-J.S.; formal analysis, W.-T.H.; investigation, W.-T.H.; resources, Y.-J.S.; data curation, Y.-J.S.; writing—original draft preparation, W.-T.H.; writing—review and editing, Y.-J.S.; supervision, Y.-J.S.; funding acquisition, Y.-J.S. All authors have read and agreed to the published version of the manuscript.

Funding

This study was funded by the National Science and Technology Council, Taiwan (110-2313-B-002-033-MY3), the Environmental Protection Administration, Taiwan (Taiwan EPA), under the grant number 110GA0008001004 and National Taiwan University (111L8953). The views or opinions expressed in this article are those of the writers and should not be construed as opinions of the Taiwan EPA. Mention of trade names, vendor names, or commercial products does not constitute endorsement or recommendation by the Taiwan EPA.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Data available on request from the authors.

Acknowledgments

The authors thank Justin Pelofsky of Third Draft Editing and the anonymous for the English language editing.

Conflicts of Interest

The authors declare no conflict of interest.

Abbreviations

1,2-DCB1,2-dichlorobenzene
1,4-DCB1,4-dichlorobenzene
γ-HCHgamma-hexachlorocyclohexane
DNAPLdense non-aqueous phase liquids
NGSnext-generation sequencing
CO2carbon dioxide
CH4methane
rRNAribosomal ribonucleic acid
PCRpolymerase chain reaction
OTUoperational taxonomic units
bphAbiphenyl dioxygenase subunit alpha
RDAredundant analysis
DDTdichlorodiphenyltrichloroethane

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Figure 1. The ratios of nitrate, sulfate, phosphate, and chloride concentrations before and after incubation. Red (i.e., greater than 1) indicates that the concentration increased after incubation, while blue (i.e., less than 1) indicates that the concentration decreased after incubation.
Figure 1. The ratios of nitrate, sulfate, phosphate, and chloride concentrations before and after incubation. Red (i.e., greater than 1) indicates that the concentration increased after incubation, while blue (i.e., less than 1) indicates that the concentration decreased after incubation.
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Figure 2. Changes in 16S rRNA copies in the microcosms amended with 1,2-DCB (A); 1,2-DCB and CO2 (B); 1,2-DCB and CH4 (C); 1,2-DCB, N, and P (D); 1,2-DCB, CO2, N, and P (E); 1,2-DCB, CH4, N, and P (F); and no chemical amendment (G).
Figure 2. Changes in 16S rRNA copies in the microcosms amended with 1,2-DCB (A); 1,2-DCB and CO2 (B); 1,2-DCB and CH4 (C); 1,2-DCB, N, and P (D); 1,2-DCB, CO2, N, and P (E); 1,2-DCB, CH4, N, and P (F); and no chemical amendment (G).
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Figure 3. Changes to bphA gene copies in the microcosms amended with 1,2-DCB (A); 1,2-DCB and CO2 (B); 1,2-DCB and CH4 (C); 1,2-DCB, N, and P (D); 1,2-DCB, CO2, N, and P (E); 1,2-DCB, CH4, N, and P (F); and no chemical amendment (G).
Figure 3. Changes to bphA gene copies in the microcosms amended with 1,2-DCB (A); 1,2-DCB and CO2 (B); 1,2-DCB and CH4 (C); 1,2-DCB, N, and P (D); 1,2-DCB, CO2, N, and P (E); 1,2-DCB, CH4, N, and P (F); and no chemical amendment (G).
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Figure 4. Relative abundance of soil microbial community at phylum level in microcosms amended with 1,2-DCB (A); 1,2-DCB and CO2 (B); 1,2-DCB and CH4 (C); 1,2-DCB, N, and P (D); 1,2-DCB, CO2, N, and P (E); 1,2-DCB, CH4, N, and P (F); and no chemical amendment (G).
Figure 4. Relative abundance of soil microbial community at phylum level in microcosms amended with 1,2-DCB (A); 1,2-DCB and CO2 (B); 1,2-DCB and CH4 (C); 1,2-DCB, N, and P (D); 1,2-DCB, CO2, N, and P (E); 1,2-DCB, CH4, N, and P (F); and no chemical amendment (G).
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Figure 5. Relative abundance of the 50 most prevalent OTUs in the initial condition and in microcosms amended with 1,2-DCB (A); 1,2-DCB and CO2 (B); 1,2-DCB and CH4 (C); 1,2-DCB, N, and P (D); 1,2-DCB, CO2, N, and P (E); 1,2-DCB, CH4, N, and P (F); and no chemical amendment (G). (Note: the OTU numbers represent the ranking of richness.)
Figure 5. Relative abundance of the 50 most prevalent OTUs in the initial condition and in microcosms amended with 1,2-DCB (A); 1,2-DCB and CO2 (B); 1,2-DCB and CH4 (C); 1,2-DCB, N, and P (D); 1,2-DCB, CO2, N, and P (E); 1,2-DCB, CH4, N, and P (F); and no chemical amendment (G). (Note: the OTU numbers represent the ranking of richness.)
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Figure 6. RDA of the soil chemical properties and the first 10 OTUs in the microcosms treated with 1,2-DCB after 63 days of incubation.
Figure 6. RDA of the soil chemical properties and the first 10 OTUs in the microcosms treated with 1,2-DCB after 63 days of incubation.
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Huang, W.-T.; Shiau, Y.-J. Potential Changes in Soil Microbial Composition under 1,2-Dichlorobenzene Contamination. Sustainability 2023, 15, 1432. https://doi.org/10.3390/su15021432

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Huang W-T, Shiau Y-J. Potential Changes in Soil Microbial Composition under 1,2-Dichlorobenzene Contamination. Sustainability. 2023; 15(2):1432. https://doi.org/10.3390/su15021432

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Huang, Wen-Ting, and Yo-Jin Shiau. 2023. "Potential Changes in Soil Microbial Composition under 1,2-Dichlorobenzene Contamination" Sustainability 15, no. 2: 1432. https://doi.org/10.3390/su15021432

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