The oilfield soil was contaminated for years by large quantities of aged oil sludge generated in the petroleum industry. In this study, physicochemical properties, contents of main pollutants, and fungal diversity of the aged oil sludge-contaminated soil were analyzed. Results revealed that aged oil sludge significantly changed physical and chemical properties of the receiving soil and increased the contents of main pollutants (petroleum hydrocarbons and heavy metals) in soil. Meanwhile, the internal transcribed spacer (ITS) sequencing by Illumina Miseq platform at each taxonomic level demonstrated that the toxicological effect of oil pollutants obviously influenced the fungal diversity and community structure in soil. Moreover, it was found that the presence of three genera (
Oil sludge is one of the most significant hazardous solid wastes generated in oil industry in China [
In previous studies, much attention has been paid to the proper disposal and sufficient treatment of the stacking oil sludge [
In recent decades, within the various biological techniques, high-throughput sequencing technology with better capacity for detecting rare species [
This is the first study that took fungi as the typical indicators of pollution to evaluate the microbial variations in soil caused by AOS. In this study, an AOS site of 4 years on soil was selected as the point source pollution of sampling, in which the fungal diversity and community structure in soil were explored with the method of high-throughput sequencing technique. This study is aimed at evaluating the influence from AOS on physicochemical properties, fungal community structure, and diversity in soil, as well as screening dominant or core oil-resistant fungal genera for potential use in soil bioremediation. The results and related findings would aid in thorough understanding of microorganism structure in oil-contaminated soil and provide new point of view to soil bioremediation.
The samples of aged oil sludge were obtained from Gudao oil factory, the largest output plant of crude oil in Shengli oilfield. Gudao lies in semiarid warm temperate monsoon climate zone at latitudes 37°47
An AOS spot around an oil well drilled 4 years ago with the approximate diameter of 40 cm was selected. Two soil samples at the horizontal center of AOS spot were collected from 0 cm and 20 cm vertically below the surface of soil, respectively (labeled as S1 and S2). Then, another soil sample obtained from the surface soil and 120 m away from the AOS center without oily sludge surroundings was chosen as blank (labeled as S3, uncontaminated soil sample) (Figure
Sampling sites.
The pH was tested in deionized water at a soil/water solution ratio of 1 : 2.5 using a pH meter (Mettler-Toledo Instruments, Shanghai, China) [
Contents of heavy metals (copper, zinc, and chromium) were determined by atomic absorption spectrophotometer (AAS7000, SHIMADZU, Japan), with pretreatment of digesting by nitric acid, hydrofluoric acid, and hydrogen peroxide system (5 : 2 : 1 by volume), respectively, in microwave digestion instrument [
Genomic DNA of the three soil samples were isolated and extracted using the soil DNA kit (Omega Bio-tek, Norcross, GA, USA) following the manufacturer’s protocols. The DNA extracts were stored at −20°C for the PCR amplification (95°C for 5 min, followed by 27 cycles at 95°C for 30 s, 55°C for 30 s, and 72°C for 45 s and a final extension at 72°C for 5 min) which was performed in an ABI GeneAmp 9700 (USA). The fungal rDNA-ITS region was amplified using universal primers ITS1F (5
Amplicons were extracted from 2% agarose gels and purified using the AxyPrep DNA Gel Extraction Kit (Axygen Biosciences, Union City, CA, USA) according to the manufacturer’s instructions and quantified using QuantiFluor: trademark: -ST (Promega, USA). Purified amplicons were pooled in equimolar and paired-end sequenced (2 × 250) on an Illumina Miseq platform according to the standard protocols.
Raw data must be processed to remove the low-quality data [
The Shannon-Weaver diversity index (
All the determinations were performed at least in triplicate. Statistical significance was determined at the confidence levels of 0.05.
As a result of its high viscosity, aged oil sludge can be fixed in soil pores or adsorbed onto the surface of soil mineral constituents, causing reduction of water retention capacity and hydraulic conductivity of the soil [
Physicochemical properties of aged oil sludge-contaminated soil.
Sample | pH | Salinity (%) | MCa (%) | TOCb (%) | HMsc (mg∙kg−1) | TPHsd (mg∙kg−1) | ||
---|---|---|---|---|---|---|---|---|
Cu | Zn | Cr | ||||||
S1 | 8.44 | 0.27 | 21.05 | 0.41 | 76.60 | 131.63 | 74.55 | 15.2 |
S2 | 8.56 | 0.36 | 22.55 | 0.35 | 47.93 | 93.81 | 111.46 | 13.6 |
S3 | 8.11 | 1.45 | 13.95 | 0.22 | 12.20 | 15.68 | 34.07 | <5 |
aMC: moisture content; bTOC: total organic carbon; cHMs: heavy metals; dTPHs: total petroleum hydrocarbons.
Along with the emission of oil sludge to the receiving soil, the contents of TPHs and HMs were intensively increased. The concentrations of Cu, Zn, and Cr in S1 were approximately the same with those in S2, while 6.3, 8.4, and 2.2 times of those in S3, respectively (Table
By amplifying the ITS region of fungi, Illumina high-throughput sequencing which adopted a sequencing-by-synthesis approach [
Sequence information and fungal diversity indexes of samples.
Sample ID | Reads | 0.97 (the similarity threshold of OTUs) | |||||
---|---|---|---|---|---|---|---|
OTUs | Ace | Chao1 | Coverage | Shannon-Weaver | Simpson | ||
S1 | 31,118 | 475 | 476 | 478 | 0.999734 | 4.36 | 0.0467 |
S2 | 31,938 | 557 | 558 | 558 | 0.999812 | 4.61 | 0.0355 |
S3 | 33,275 | 565 | 567 | 566 | 0.999730 | 4.44 | 0.0414 |
The rarefaction analysis was used to verify whether the volume or the depth of sampling was sufficient to capture the existing OTUs [
Rarefaction curves based on the 18s rRNA gene sequencing.
OTU venn analysis in different samples.
The fungal community compositions of the three soil samples reflected similar diversities but different abundances. Figure
Histogram of fungal community structure at phylum level.
Further analysis was carried out to analyze the fungal community composition in family levels. In general, 91.83% of the total sequences were assigned and there were 28 identified families with the relative abundance of above 1%. As shown in Table
The fungal community structures and diversities at family level.
OTU ID | S1 | S2 | S3 |
---|---|---|---|
Cephalothecaceae | 16.76% | 12.63% | 0.00% |
Aspergillaceae | 10.76% | 2.80% | 11.32% |
Unclassified | 9.61% | 7.63% | 7.28% |
Mortierellaceae | 5.58% | 12.74% | 13.46% |
Thelephoraceae | 5.36% | 2.18% | 0.58% |
Nectriaceae | 4.22% | 5.08% | 5.24% |
Cordycipitaceae | 4.06% | 3.09% | 1.43% |
Hypocreaceae | 3.52% | 1.11% | 4.22% |
Trichocomaceae | 2.72% | 2.36% | 3.17% |
Pleosporaceae | 2.46% | 5.44% | 0.19% |
Lasiosphaeriaceae | 2.39% | 6.26% | 5.50% |
Hypocreales_norank | 2.27% | 3.01% | 3.85% |
Pseudeurotiaceae | 2.15% | 0.91% | 2.03% |
Didymellaceae | 1.91% | 1.42% | 0.80% |
Chaetomiaceae | 1.67% | 2.97% | 3.62% |
Venturiaceae | 1.60% | 0.40% | 0.08% |
Stachybotriaceae | 1.48% | 0.33% | 1.47% |
Sporormiaceae | 1.28% | 0.35% | 1.09% |
Atheliaceae | 1.21% | 0.37% | 0.10% |
Sebacinaceae | 1.17% | 0.26% | 0.16% |
Botryosphaeriaceae | 1.15% | 3.09% | 4.46% |
Helotiales_norank | 1.12% | 0.92% | 0.55% |
Hyaloscyphaceae | 0.86% | 2.09% | 2.01% |
Cystofilobasidiaceae | 0.82% | 1.49% | 1.38% |
Herpotrichiellaceae | 0.57% | 0.59% | 1.15% |
Polyporales_norank | 0.47% | 1.04% | 0.94% |
Clavicipitaceae | 0.42% | 1.21% | 0.72% |
Phaeosphaeriaceae | 0.34% | 1.74% | 0.06% |
Meruliaceae | 0.00% | 0.00% | 9.33% |
The relative fungal abundance at genus level was also analyzed. Totally, 39 genera with the abundance of above 1% were classified in the samples. It was observed that the growth of most identified genera was limited, with the possible reason that AOS discharged TPHs into the receiving soil. TPHs comprised hydrogen and carbon, but lack of nitrogen, sulfur, and phosphorus essential for microbial growth [
Relative abundance of the three (a) limited genera and (b) oil-resistant genera in samples.
The analysis of multiple samples shown as cluster tree (Figure
Multiple sample cluster tree.
In the present study, combined with the results of the high-throughput sequencing, further study should be carried out in the future to explore more microorganisms like bacteria and archaea with powerful features of oil resistance before strict screening, culturing, and domesticating of the dominant fungi genera.
This is the first study that evaluated the significant effects on physicochemical properties and fungal diversities of soil caused by AOS contamination. The results revealed that longtime oil exposure made the receiving soil arid, saline-alkali, and unsuitable for agriculture. The contents of both TPHs and HMs in the contaminated soils were apparently increased compared with noncontaminated soil. High-throughput sequencing results by Miseq platform showed significant changes in fungi community compositions and diversities. It was observed that oily circumstance could limit the growth of most genera and meanwhile promote the growth of certain oil-resistant fungi like
International transcribed spacer
Petroleum hydrocarbons
Heavy metals
Aged oil sludge
Total petroleum hydrocarbons
Operational taxonomic unit
Ribosomal database project
Total organic carbon
Polycyclic aromatic hydrocarbons
Lignin-modifying enzymes
Moisture content.
The data used to support the findings of this study are available from the corresponding author upon request.
The authors declare that they have no conflicts of interest.
This work was financially supported by the National Natural Science Foundation of China (No. 41673112, No. 41541025) and Open Research Fund Program of Shandong Provincial Key Laboratory of Eco-Environmental Science for Yellow River Delta, Binzhou, Shandong (2015KFJJ01).