Journal Pre-proof Effect of bioaugmentation and biostimulation on hydrocarbon degradation and microbial community composition in petroleum-contaminated loessal soil
Manli Wu, Jialuo Wu, Xiaohui Zhang, Xiqiong Ye PII:
S0045-6535(19)31680-7
DOI:
https://doi.org/10.1016/j.chemosphere.2019.124456
Article Number:
124456
Reference:
CHEM 124456
To appear in:
Chemosphere
Received Date:
07 January 2019
Accepted Date:
25 July 2019
Please cite this article as: Manli Wu, Jialuo Wu, Xiaohui Zhang, Xiqiong Ye, Effect of bioaugmentation and biostimulation on hydrocarbon degradation and microbial community composition in petroleum-contaminated loessal soil, Chemosphere (2019), https://doi.org/10.1016/j. chemosphere.2019.124456
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Journal Pre-proof 1
Code number: CHEM59490
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Effect of bioaugmentation and biostimulation on hydrocarbon
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degradation
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petroleum-contaminated loessal soil
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Manli Wua,b, Jialuo Wua,b, Xiaohui Zhangc, Xiqiong Yea,b
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(a Shaanxi Key Laboratory of Environmental Engineering, Xi’an University of Architecture and
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Technology, Xi’an 710055, People’s Republic of China;
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b Key Laboratory of Northwest Water Resource, Environment and Ecology, MOE, Xi’an
and
microbial
community
composition
in
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University of Architecture and Technology, Xi’an 710055, People’s Republic of China;
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c Exploration and Development Research Institute of Changqing Oilfield Company, PetroChina,
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Xi’an 710018, People’s Republic of China)
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Abstract: This study assessed the benefits of biostimulation with nitrogen and phosphorous
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(BS) versus bioaugmentation with native petroleum degrading flora (BA) in terms of petroleum
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hydrocarbon removal and the microbial community structure shift in petroleum-polluted loessal
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soil. After 12 weeks of remediation, the TPH degradation efficiencies were 28.3% and 13.9% in
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BS and BA treated soils, respectively. Biostimulation was more effective than bioaugmentation
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for petroleum hydrocarbon degradation. Soil microbial community composition changed while
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microbial diversity decreased greatly by bioaugmentation treatment. The inoculum could
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survive, grow up quickly and become the predominant microorganisms after one week of
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inoculation. In the biostimulation treatment, microbial community composition is more
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evenness and richness than in the bioaugmented remediation. The strong positive correlations of
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the nitrogen and phosphorus with the petroleum hydrocarbon suggest the importance of
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nutrients for petroleum biodegradation processes in the contaminated loessal soil. The results 1
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indicate that the stabilization and variety of the microbial community structure are essential for
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the petroleum biodegradation performance. Further engineering is suggested to improve the
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evenness and richness of the soil microbial community since an abundance of nitrogen and
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phosphorus nutrients ensures the degraders’ activity in the petroleum polluted environment.
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Keywords: Petroleum-contaminated soil; Bioaugmentation; Biostimulation; TPH; Microbial
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community; α-diversity
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Introduction
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Petroleum pollution has become a global environmental concern. Soil contamination with
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petroleum hydrocarbons is caused by accidental leakage from reservoirs and petroleum
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refineries and spillage from transport pipelines. The presence of petroleum hydrocarbons affects
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the physical, chemical and ecological properties of soil (Ramadass et al., 2015; Petrov et al.,
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2016). Among a variety of the remediation strategies, bioremediation, based on the use of
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microorganisms to degrade contaminants, has been widely used for treating oil-contaminated
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sites and is an efficient, cost-effective and environmentally sound remediation approach.
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Bioaugmentation and biostimulation are the two main bioremediation strategies for the
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decontamination of petroleum polluted soil. Biostimulation enhances the metabolic activity of
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the indigenous microbial community through nutrients amendment. Nitrogen and phosphorus
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are the essential growth-limiting nutrients for microorganism growth. Many studies suggest that
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the supplement of nitrogen and phosphorus is important to enhance the degradation of petroleum
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in polluted soil (Leys et al., 2005; John et al., 2011; Shahi et al., 2016). Studies have indicated
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that when the C/N/P ratio is regulated to 100/5/1, 100/10/1, and 100/15/1, the bacterial activity
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in biostimulation practice is tolerant to various hydrocarbons and can utilize hydrocarbons as
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carbon sources for their growth (Shahi et al., 2016). Since different properties of contaminated
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soil has a diverse microbial community, the optimum C/N/P ratio may be different for 2
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remediation. Generally, a ratio of C/N/P of 100/10/1 is widely accepted as a standard formula
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for biostimulation strategy (Leys et al., 2005; Shahi et al., 2016).
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Bioaugmentation, the inoculation of exogenous microorganisms into soil, is the best option
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when contaminated soils have low indigenous populations of hydrocarbon degraders (Xu and
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Lu, 2010; Castiglione et al., 2016). In addition, bioaugmentation gives an appropriate result
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when the pollutants have a toxic effect on the native microorganisms (Tyagi et al., 2011; Wu et
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al., 2013). One of the advantages of bioaugmentation is that the degradation process can start
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immediately when specific microbial degraders are introduced.
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Although bioaugmentation technology has been reported to be a sufficient method to
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improve the degradation of petroleum in contaminated soil, the effects of bioaugmentation are
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case specific and controversial. Some studies indicate that bioaugmentation only enhances
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degradation efficiencies temporarily and that biostimulation represents a more ideal remediation
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strategy to achieve effective petroleum decontamination (Kauppi et al., 2011; Liu et al., 2011;
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Megharaj et al., 2011; Sayara et al., 2011; Abed et al., 2014; Yang et al., 2015; Wu et al., 2016;
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Yulia et al., 2017). However, the reason for the inefficiency of bioaugmentation treatment in
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some cases is still not apparent. There is a need to better understand the causes that lead to
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bioaugmentation failure.
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Microbial communities, as the essential component in soil ecological systems, are vital for
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the remediation of petroleum hydrocarbon and other pollutants (Yan et al., 2016; Jia et al.,
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2017). Since petroleum hydrocarbon remediation depends on soil microorganisms that have
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suitable metabolic capabilities, understanding how bioaugmentation and biostimulation
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influence the soil microbial community structure are fundamental to ensuring effective
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remediation of oil-contaminated soil.
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Molecular technologies provide a good understanding of the microbial community
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composition in remediation systems (Zhang, et al., 2018). Various studies have attempted to 3
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analyze the microbial structure that is responsible for the degradation of petroleum
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hydrocarbons. Studies documenting the remediation of petroleum contaminated soil have
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applied denaturing gel gradient electrophoresis (DGGE) (Jia et al., 2005; Pacwa-Płociniczak et
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al., 2016; Wu et al., 2016), phospholipid fatty acid (PLFA) (Bundy et al., 2004; Margesin et al.,
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2007), terminal-restriction fragment length polymorphism percentage(T-RFLP) (Grant et al.,
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2007; Liu et al., 2011; Liu et al., 2013) and high throughput sequencing (Peng et al., 2015; Bao
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et al., 2017; Wu et al., 2017a) to investigate bacterial community shifts. These
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culture-independent molecular biology techniques can provide a good understanding of the
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microbial community shift during remediation.
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This paper presents a study of the effects of bioaugmentation and biostimulation strategies
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applied to loessal soil polluted with 20,000 mg kg-1 total petroleum hydrocarbons (TPH). The
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objectives were 1) to assess the petroleum hydrocarbon degradation efficiencies of the
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bioaugmentation and biostimulation strategies, 2) to investigate the changes in the microbial
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community structures as a function of time and type of treatment using high throughput
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sequencing analysis, and 3) to evaluate the potential benefits of biostimulation with nutrients
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versus bioaugmentation with hydrocarbon degrading microorganisms. We present evidence
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regarding the superiority of the biostimulation strategy for the remediation of petroleum
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contaminated loessal soil.
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2. Materials and methods
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2.1. Soil for the bioremediation study
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A petroleum polluted soil sample was collected from an oil well in north Shaanxi
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province, China. The site has a history of oil pollution over many years. According to the
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sampling method “The Technical Specification for Soil Environmental monitoring (HJ/T 166
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-2004, China)”, eight soil samples were sampled using a sterilized shovel from the top 10-cm
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soil layer around the oil well. Then, these samples were well-mixed and homogenized into a 4
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single soil sample. The fresh samples were loaded in polyethylene bag and immediately
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transported to the laboratory by using a cooler. Table 1 summarizes selected physicochemical
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and biological characteristics of this contaminated soil (IS).
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2.2. Enrichment and identification of petroleum degrading flora from petroleum polluted soils
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Five grams of petroleum-contaminated soil was suspended in 50 mL of MBS culture
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medium. The medium contained 1% petroleum as the sole carbon and energy source. Incubation
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was cultured at 25 ℃ by shaking on an oscillating incubator (150 rpm) for 7 days, 6% of the
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cultures were then transferred into 50 mL of fresh MBS for further enriched. After five cycles of
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repeated enrichment, the petroleum hydrocarbon degrading microbial flora PMC was obtained
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by centrifugation (5000 rpm) for 15 min and suspended in PBS buffer. Identification of the
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hydrocarbon degrading flora was performed using high throughput sequencing analysis by
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Sangon Biotech Co., Ltd. China (ftp://ftp.sangon.com:21148).
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2.3. Bioremediation experiment design
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Two different remediation microcosms of BA and BS were prepared. (1) BA:
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bioaugmentation was performed by adding the PMC hydrocarbon degrading flora (described in
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2.2) into the petroleum-contaminated soil to obtain a density of 108 cfu g-1 soil as reported by
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Abalos et al. (2004). (2) BS: biostimulation with NH4NO3 and KH2PO4, which were amended to
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soil by a C/N/P ratio of 100/10/1.
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Each microcosm was prepared in triplicate with 0.8 kg of soil. The microcosms were then
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incubated at 24 °C for 12 weeks. Distilled water was amended to the soil to keep 15% soil
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moisture. The soil was stirred weekly for sufficient aeration.
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2.4. Physicochemical characteristics analysis
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The soil pH, available phosphorus (AP), total nitrogen (TN), ammonia nitrogen (NH4+-N),
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nitrate nitrogen (NO3--N), and oxidation-reduction potential (ORP) were determined according
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to the technical specifications for soil analysis (2014). Total petroleum hydrocarbons (TPH) 5
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were determined by the gravimetric method as described in Mishra et al. (2001).
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2.5. Illumina sequencing
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The initial petroleum contaminated soil (IS) and soil samples from the BA and BS
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microcosms were collected at weeks 1 and 12 for MiSeq sequencing. DNA was extracted
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according to a Power Soil DNA extraction kit (MoBio Laboratories, USA). The quality of DNA
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was determined on a 0.5 % agarose gel. For bacterial community structure analysis, primers
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341F
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(GACTGGAGTTCCTTGGCACCCGAGAATTCCAGACTACHVGGGTATCTAATCC)
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used to amplify the the V3-V4 region as reported by Qu et al. (2016). The PCR products then
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loaded on Illumina-Miseq device according to the manufacturer’s protocols. After sequencing,
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data were collected and processed by Sangon Biotech Co., Ltd (ftp://ftp.sangon.com:21148).
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Operational taxonomic unit (OTU) clustering was performed using Usearch (version 8.1.1831)
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at 97% sequence similarity threshold.
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2.6. Statistical analysis
(CCCTACACGACGCTCTTCCGATCTGCCTACGGGNGGCWGCAG)
and
805R was
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All experiments were conducted with three replications. The experimental results of the
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TPH content, soil pH, AP, TN, NH4+-N, NO3--N, and ORP are presented as the mean ±standard
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deviation (SD). To study the relationship between petroleum hydrocarbon degradation and soil
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physicochemical characteristics, the Pearson correlation coefficient was calculated using
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statistical software SPSS 25 (Statistical Package for the Social Sciences, China). A p value less
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than 0.05 was considered to be statistically significant.
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3. Results
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3.1. Analysis of petroleum-degrading flora
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The composition of petroleum-degrading flora PMC isolated from petroleum contaminated
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soil was analyzed according to the high throughput sequencing method. The petroleum
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degrading consortia were classified into two phyla and sixteen different genera. Among them, 6
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the Proteobacteria phylum was predominant and accounted for 96.3%, and the Firmicutes was
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the second dominant phylum, with a relative abundance of 3.70%. At the genus level,
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Pseudomonas, Achromobacter, Bacillus, and Azomonas were dominant and accounted for
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87.2%, 6.12%, 3.51 and 1.80%, respectively (Fig. 1).
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3.2. Effects of bioremediation on TPH degradation
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The concentration of total petroleum hydrocarbon (TPH) in the contaminated soil sample
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was 20,000 mg kg-1 soil (Table 1). After 12 weeks of remediation, TPH was 17230 and 14340
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mg kg-1 soil in the BA and BS microcosms (Fig. 2), which represented TPH removal
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efficiencies of 13.9% and 28.3%, respectively. Thus, the BS treatment was more effective than
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the BA treatment for petroleum degradation in contaminated loessal soil.
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3.3. Physicochemical properties of petroleum-polluted soil
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The ORP value of the initial oil-contaminated soil was -48 mV (Fig.3-a). The ORP values
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changed to -52~-55 mV and -40~-47 mV in the BA and BS treatments, respectively. Soil ORP
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was enhanced by biostimulation and reduced by bioaugmentation treatment.
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The initial oil-contaminated soil had pH values of 7.88 (Table 1). During the remediation,
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the pH values were approximately 7.82 and 7.76 in the BA and BS treatments, respectively
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(Fig.3-b). The soil pH value was lower in the BS treatment than in the BA treatment during the
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remediation.
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Total nitrogen (TN), ammonia nitrogen (NH4+-N), and nitrate nitrogen (NO3--N) were
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1159.7, 0.38 and 12.39 mg kg-1 in the initial contaminated soil, respectively (Table 1). In the BA
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treatment, the concentrations of TN, NH4+-N, and NO3--N were 1159.6~1170.4, 4.21~1.38, and
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12.1~18.5 mg kg-1, respectively (Fig.3-c-d, Fig.3-f). The various forms of nitrogen remained
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relatively stable during the remediation. In the BS treatment, the contents of TN, NH4+-N, and
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NO3--N respectively increased to 1650.3, 210.4 and 292.9 mg kg-1 after the amendment of
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NH4NO3 (zero weeks) for the biostimulation treatment. After 12 weeks of biostimulation 7
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treatment, the contents of TN, NH4+-N, and NO3--N decreased to 1523.1, 128.7 and 225.6 mg
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kg-1, respectively (Fig 3-c-d, Fig.3-f).
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The content of available phosphorus (AP) in the initial oil-contaminated soil was 15.9 mg
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kg-1 (Table 1). An increase in soil AP at zero weeks was observed when the bioaugmentation
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and biostimulation treatments were applied due to the addition of KH2PO4 in the BS treatment
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or inoculation of PMC flora (which suspended in PBS buffer) in the BA treatment. After one
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week of incubation, the AP concentration dropped from 175.7 to 93.5 mg kg-1 in the BS sample
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and thereafter showed a substantial decrease. The AP content decreased from 35.0 to 22.2 mg
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kg-1 and then increased in the BA treatment (Fig.3-e).
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3.4. Correlation between the petroleum hydrocarbon and soil physicochemical properties
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The correlations between the soil physicochemical properties and TPH are given in Table 2.
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In the BS treatment, the TPH content had a strong positive relationship with TN and AP and a
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correlation with pH and NH4+-N. In the BA treatment, the TPH content had a positive
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correlation with NH4+-N and AP. Correlation between the petroleum hydrocarbon degradation
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and nutrients in the BA treatment are different from BS treatment, which may be attributed to
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different nitrogen utilization ways in the bioaugmentation and biostimulation strategies.
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3.5. Evaluation of soil microbial diversity and community composition
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In this study, we collected bioaugmentation (BA) and biostimulation (BS) soil samples at
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weeks 1 and 12 for Illumina MiSeq sequencing analysis. They are hereafter referred to as BA1
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and BS1 for the first week and BA12 and BS12 for the twelfth week of remediation,
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respectively. Additionally, the initial petroleum contaminated soil (IS) was analyzed by Illumina
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MiSeq sequencing analysis.
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3.5.1. Sequencing quality control
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The initial number of sequences was 45501, 43274, 32449, 42716, and 42269 in the IS,
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BA1, BS1, BA12 and BS12 samples, respectively. After dislodging low-quality reads using 8
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Usearch software, the valid sequence number was 41369, 41031, 30489, 40858, and 40,418,
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respectively. The sequencing optimization and coverage rates were more than 90% and 98% for
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all samples, indicating that the optimization procedures were reasonable and the sequencing
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depths were adequate.
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The valid sequences were then clustered into OTUs at a threshold of 97%. The results
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indicated the OTUs number obtained in the IS (1669) and BS1 (1631) samples were the highest,
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next to the BS12 sample (1217), followed by the BA1 (1027) and the BA12 (765) samples
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(Table 3). The details of the bacterial taxonomy (phylum, class, order, family, and genus) in
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different soil samples are shown in Table 3.
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3.5.2. Soil microbial diversity
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Table 3 summarize the biodiversity index of different soil samples. The species diversity
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indices, including Chao 1, Ace, and Shannon indices, produced the highest values for the IS,
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followed by BS1 and BS12, and the lowest value for the BA12 samples among the treatments
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(Table 3), which indicated that the bacterial diversity was higher in the IS and BS treatments
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than in the BA treatment. The BA treatment greatly decreased the biodiversity of the soil
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microbial community. Compared to the BA treatment, the microbial community composition is
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stable and diverse in the BS treatment. In addition, the α-diversity decreased along with the
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remediation time compared with those of the same treatment at different remediation periods
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(BA1 vs. BA12; BS1 vs. BS12).
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3.5.3. Microbial community composition
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The 10 most abundant phyla and top 20 predominant genera in each sample and their
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relative abundances are shown in Fig. 4. In the initial contaminated soil (IS), Actinobacteria and
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Proteobacteria were the dominant phyla, with the relative abundances of 47.3% and 37.4%,
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respectively. The Firmicutes phylum was the subordinate dominant, with a relative abundance
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of 9.16% (Fig.4-a). At the genus level, Promicromonospora and Exiguobacterium were the
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dominant genera, with the relative abundances of 19.0% and 8.49%, respectively (Fig. 4-b). 9
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Compared to the IS, the microbial community compositions significantly changed in the
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BA treatment. At the phylum level, the Proteobacteria phylum was the most dominant in the
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BA1 and BA12 samples, with the relative abundance increased to 96.3% and 87.4%,
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respectively. Firmicutes (3.71% in the BA1 vs. 2.64% in the BA12) and Actinobacteria (2.46%
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in the BA1 vs. 5.46% in the BA12) decreased and became the subordinate dominant phyla
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(Fig.4-a). At the genus level, the Pseudomonas genus was predominant and accounted for 75.2%
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in the BA1 sample and 76.4% in the BA12 sample. The Achromobacter (8.81% in the BA1 vs.
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7.56% in the BA12) genus increased and became the secondary dominant genus. There was no
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discernible change in the BA12 sample compared to the BA1sample (Fig. 4-b).
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The microbial community composition changed in the BS12 sample compared to that in
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the BS1 sample. The relative abundance of the Actinobacteria (17.8% in the BS1 vs. 50.4% in
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the BS12) and Bacteroidetes phyla (0.64% in the BS1 vs. 2.16% in the BS12) increased
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substantially, while that of the Proteobacteria (35.5% in the BS1 vs. 10.1% in the BS12) and
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Firmicutes phyla (58.4% in the BS1 vs. 35.5% in the BS12) were significantly reduced with the
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remediation time. At the genus level, the relative abundances of Nocardioides (1.66% in the
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BS1 vs. 28.9% in the BS12) and Promicromonospora (6.34% in the BS1 vs. 14.8% in the BS12)
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increased, while those Bacillus (31.6% in the BS1 vs. 22.7% in the BS12) and Planococcaceae
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(6.64% in the BS1 vs. 2.07% in the BS12) were substantially reduced during the remediation.
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4. Discussion
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Strains isolated from oil contaminated soil that can effectively degrade hydrocarbons often
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include the Proteobacteria phylum and Pseudomonas genus (Bento et al., 2005; Wang et al.,
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2005; Han et al., 2009). In this study, the hydrocarbon degrading flora PMC obtained from
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petroleum contaminated loessal soil primarily consisted of the Proteobacteria phylum and
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Pseudomonas genus. These results indicate that the classification homology of petroleum
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degraders isolated from the different soil types and textures. 10
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The initial physiochemical parameters of the contaminated soil are valuable to the success
252
of remediation. It has been widely accepted that the optimum C/N/P ratio in soil for
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biostimulation strategy is 100/10/1, which is equivalent to the nutrients required for active
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bacteria (US EPA, 2002; Wu et al., 2016). Additionally, some studies suggested that the
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appropriate degrading population in soil for bioaugmentation strategy is approximately 108
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cfug-1of soil (Abaloset al., 2004; Masy et al., 2016).
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The physiochemical characteristics of petroleum-contaminated loessal soil suggested that
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the C/N/P ratio in the polluted soil was 660/10/0.14. Additionally, the initial contaminated soil
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had lower populations of TPH degraders (Table 1). Theoretically, the addition of a suitable
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amount of nitrogen and phosphorus for biostimulation or inoculation with the appropriate
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hydrocarbon degraders for bioaugmentation are both useful strategies for the bioremediation of
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the petroleum-contaminated soil.
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Studies have demonstrated that the introduction of microbial flora enriched from
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contaminated soil and inoculated back to the same soil was more effective in degrading
265
hydrocarbons than flora obtained from other soils (Wu et al., 2013). In this study, we isolated
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the indigenous petroleum hydrocarbon degrading flora PMC from contaminated soil that was
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actively under bioremediation and added it back to the same polluted soil. The results of high
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throughput sequencing revealed the main compositions of flora PMC belonged to the
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Proteobacteria phylum (96.3%) and Pseudomonas genus (87.2%) (Fig. 1). After one week of
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inoculation, the relative abundance of the Proteobacteria phylum increased from 37.4% to
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87.4% (Fig. 4-a), and that of the Pseudomonas genus increased from 2.99% to 76.4% in the BA
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treatment (Fig. 4-b). After 12 weeks of incubation, the Proteobacteria phylum and
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Pseudomonas genus were still the most dominant microorganisms in the BA12 sample. These
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results suggest that the inoculated oil-degrading flora PMC survived and grew quickly in
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contaminated soil. However, the TPH degradation efficiency was lower in the bioaugmentation
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treatment (13.9%) than that in the biostimulation treatment (28.3%). It seems that the TPH 11
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degrader population is not a prerequisite for petroleum hydrocarbon degradation.
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The contents of TN, NH4+-N NO3--N, and AP are high in the BS treatment because of the
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addition of NH4NO3 and KH2PO4 for the biostimulation treatment. The NH4+-N, NO3--N, and
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AP contents decreased rapidly after one week of remediation, which can be explained by
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microbial utilization and petroleum hydrocarbon degradation in soil under biostimulation (John
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et al., 2011; Urakawa et al., 2012; Marchand et al., 2017). In addition, the soil pH value was
283
lower and ORP was higher in the biostimulation treatment than those in the bioaugmentation
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treatment. The strong positive correlations of the nutrient contents with the petroleum
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concentration in the BA and BS treatments indicated the importance of nutrients for the
286
bioremediation processes.
287
The similarity of the microbial community compositions in BA1 and BA12 suggested that
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soil microbial community structure achieved balance rapidly in the bioaugmentation treatment
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after one week of remediation. According to Fig. 4, soil microbial community structure in the
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first week of bioaugmentation (BA1) greatly changed compared with the initial soil (IS), but
291
then remained basically unchanged in the twelfth week (BA12). Also, TPH degradation is the
292
highest in the first week during the whole remediation (shown Fig. 2). The highest TPH
293
degradation efficiencies in the first week indicated that the microbial community structure shift
294
may be associated with the petroleum hydrocarbon degradation.
295
Proteobacteria, Firmicutes and Actinobacteria were the dominant phyla across all soil
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samples. These phyla are widely distributed in petroleum-contaminated loessal soil (Liu et al.,
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2013). The relative abundance of these strains changed in different bioremediation strategies.
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In the bioaugmentation treatment, the relative abundance of the Proteobacteria phylum and
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Pseudomonas genus significantly increased, which can be attributed to the inoculation of the
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petroleum-degrading flora PMC in contaminated soil. The inoculants become the most dominant
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microorganisms in the contaminated soil, which restrained indigenous microorganism growth
302
during the remediation. 12
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In the BS treatment, the relative abundance of the Proteobacteria phylum decreased, while
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that of the Firmicutes phylum increased and became dominant compared to the IS. At the genus
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level, the relative abundances of Exiguobacterium and Promicromonosporawere reduced, while
306
those of Nocardioides and Bacillus enhanced and became dominant.
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According to the literature, the Firmicutes phylum and Bacillus genera are primary
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petroleum degraders in oil-contaminated soil (Yeh, 1985; Ortega-González et al., 2015; Yang et
309
al., 2015). The increase of the Firmicutes phylum and Bacillus genus indicate the correlativity
310
between these strains and TPH degradation in the biostimulation treatment.
311
Biodiversity is dependent on both the richness and evenness of the microbial composition.
312
The diversity indices of Chao 1 and Ace represent the richness, while Shannon and Simpson
313
indices represent the evenness of a microbial community (Sengupta and Dick, 2015).
314
The bioaugmentation treatment led to the lowest microbial biodiversity among all soil
315
samples (Table 3). Soil microbial species were relatively single and inhomogeneous in the
316
bioaugmentation treatment, which constrained their degradation capability. On the contrary, the
317
microbial community composition was more suitable and diverse in the biostimulation
318
treatment. Thus, the advantage of biostimulation was ensuring that the soil microbial community
319
was well-matched to the specific soil environment, which led to improved petroleum
320
hydrocarbon degradation.
321
Previous studies have revealed that the success of oil-contaminated bioremediation depends
322
on the presence of sufficient microorganisms with the appropriate metabolic capabilities (Krutz
323
et al., 2005; Wu et al., 2017b). Our study found that TPH degrader enrichment was not a
324
prerequisite for enhancing hydrocarbon degradation and that the balance and diversity of the
325
microbial community structure were essential for petroleum hydrocarbon remediation. We also
326
demonstrated that the evenness and richness of species were vital for contaminant remediation
327
in the polluted soil. 13
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5. Conclusion
329
Biostimulation with nitrogen and phosphorous represents a more effective remediation
330
strategy for TPH degradation than bioaugmentation with petroleum degrading flora in
331
contaminated loessal soil. In the bioaugmentation treatment, the inoculum was able to survive,
332
flourish quickly and become the most dominant microorganisms. Microbial species
333
was inhomogeneous by the bioaugmentation treatment. The soil microbial community
334
changed considerably and reached stability after one week of remediation. In the biostimulation
335
treatment, the microbial community composition was more diverse than that in the
336
bioaugmentation treatment. The balance and diversity of the microbial community structure
337
were beneficial to petroleum hydrocarbon decontamination.
338
Acknowledgments
339
This work was supported by the National Natural Science Foundation of China (No.
340
21577109), the Program for Innovative Research Team in Shaanxi (PIRT) (Grant No.
341
2013KCT-13), the Natural Science Foundation of Shaanxi Province (2015JM5163), and the Key
342
Laboratory Project of the Shaanxi Provincial Education Department (13JS048).
343
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from
Different
Wastewater
Treatment
472 473 474
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Plants.
Microb.
Ecol.
DOI:
Journal Pre-proof Fig.1. hydrocarbon degrading flora isolated from petroleum contaminated soil. Fig.2. Degradation of TPH by biostimulation and bioaugmentation in oil-contaminated soil. Errors bars indicate ±SD of triplicate samples. Different letters in the same week represent a significant difference at P<0.05. Fig.3. Changes of physicochemical properties of soil. (3-a ORP; phosphorus;
3-b pH;
3-c NH4+-N;
3-d NO3-N;
3-e Available
3-f Total nitrogen).
Fig.4. Microbial community composition in the BA and BS treatments from Illumina sequencing (4-a The most abundant bacterial phyla; 4-b The most abundant bacterial genus).
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Fig.1
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BA
19000
a
a
BS
a a
-1
TPH concentrations(mg kg )
20000 a
18000
a
a
17000
b b
16000
a
a b b
b
b
15000
b
14000
b
b
13000 12000 0
1
2
3
4
5
6
7
Time(weeks) Fig.2
8
9
10 11 12 13
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BA -30
8.6
(a)
-35 -40
8.2
-45
8.0
-50 -55
7.4
-65
7.2
-70 0
2
3
4
5
6
7
8
+
7.0
9 10 11 12
-1
200
1
2
3
4
5
6
7
8
9 10 11 12
2
3
4
5
6
7
8
9 10 11 12
2
3
4
5
6
7
8
9 10 11 12
(d)
300 240
160 120
-
180
80
120
40
60
0 0 180
1
2
3
4
5
6
7
8
0
9 10 11 12
0
1800 -1
TN (mg kg )
(e)
160 -1
0
NO3 -N (mg kg )
(c)
-1
NH4 -N (mg kg )
1
360
240
AP (mg kg )
7.8 7.6
-60
140 120 100 80
1
(f)
1700 1600 1500 1400
60 40
1300
20
1100
0
(b)
8.4
pH
ORP (mv)
BS
1200
0
1
2
3
4
5
6
7
8
9 10 11 12
1000
Time(weeks)
0
1
Time(weeks)
Fig.3
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100 Others Verrucomicrobia
Relative abundance(%)
80
Planctomycetes Gemmatimonadetes
60
Chloroflexi Candidatus Saccharibacteria
40
Bacteroidetes Acidobacteria
20
Proteobacteria Actinobacteria
0
Firmicutes
IS
BA1
BA12
BS1
BS12
100
(b)
Others Olivibacter Achromobacter Planococcaceae_incertae_sedis Fictibacillus Paenisporosarcina Paenibacillus Arthrobacter Blastococcus Altererythrobacter Pseudoxanthomonas Acinetobacter Leifsonia Mycobacterium Nocardioides Unclassified Citrobacter Exiguobacterium Bacillus Pseudomonas Promicromonospora
80
Relative abundance(%)
(a)
60 40 20 0
IS
BA1
BA12
Treatments
Fig.4
BS1
BS12
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Biostimulation is better than bioaugmentation for petroleum hydrocarbon degradation.
Bioaugmentation decrease soil microbial diversity.
Soil microbial are more diverse in the biostimulation than in the bioaugmentation.
The advantage of biostimulation is ensuring soil microbial evenness and diversity.
Journal Pre-proof Table 1 Physicochemical and microbiological properties of the petroleum-contaminated soil (mean ± standard deviation (SD), n = 3). Main characteristics
Values
TPHa(g kg-1)
19.8±0.38
Total carbon(%)
7.65 ±0.05
Organic matter(%)
0.67± 0.03
Moisture content(%)
5.40±0.11
pH
7.88± 0.11
Total nitrogen(mg kg-1)
1159.7± 95.2
Available phosphorus(mg kg-1)
171.6 ± 18.4
Ammonia nitrogen(mg kg-1)
0.38 ± 0.08
Nitrate nitrogen(mg kg-1)
12.39± 0.87
Total bacterial numbers(cells g-1)
(6.8 ± 0.3)×106
TPH degraders(MPNb g-1)
(3.30 ± 0.6)×104
aTPH:
total petroleum hydrocarbon most probably number
bMPN:
Journal Pre-proof Table 2 Correlation matrix (coefficients and significance levels) for parameters of BS and BA treatments. pH ORP N-NH4+ N-NO3TN AP Biostimulation treatment TPH 0.784* -0.303 pH 1 -0.682* ORP 1 + N-NH4 N-NO3TN AP Bioaugmentation treatment TPH -0.185 -0.29 pH 1 0.034 ORP 1 + N-NH4 N-NO3TN AP
0.786* 0.567* 0.197 1
0.036 0.311 -0.529* -0.287 1
0.806** 0.746* -0.111 0.831** 0.294 1
0.908** 0.922** -0.364 0.825** 0.157 0.915** 1
0.574* -0.745* -0.213 1
-0.329 0.709* -0.5* -0.171 1
-0.467 -0.561* -0.351 0.964** 0.098 1
0.508* -0.499 -0.787* 0.456 0.061 0.477 1
*,p> 0.05;**,p> 0.01.
TPH: total petroleum hydrocarbon; ORP: oxidation-reduction potential; nitrogen; AP: Available phosphorus.
TN: total
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Table 3 Bacterial taxonomy and diversity indices of the BA and BS treatments at the 1st and 12th weeks of remediation. Treatments
IS
BA1
BS1
BA12
BS12
1669
1027
1631
765
1217
Phylum
21
17
22
20
19
Class
42
37
49
43
46
Order
67
51
70
60
64
Family
136
100
139
115
132
Genus
353
241
380
248
322
4.38
2.00
4.10
1.62
3.25
Ace index
3327.1
2674.4
3180.4
2699.6
3009.2
Chao1 index
2534.1
1815.4
2481.2
1584.2
2088.9
0.05
0.39
0.07
0.5
0.12
sequencing analysis OTUs num
Diversity indices Shannon index
Simpson index