Chemosphere 117 (2014) 486–493

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Chemosphere

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Technical Note

Effects of different remediation treatments on crude oil contaminatedsaline soil

http://dx.doi.org/10.1016/j.chemosphere.2014.08.0700045-6535/� 2014 Elsevier Ltd. All rights reserved.

⇑ Corresponding author. Tel.: +86 24 83970220; fax: +86 24 83970394.E-mail address: zengdh@iae.ac.cn (D.-H. Zeng).

Yong-chao Gao a,b, Shu-hai Guo c, Jia-ning Wang b, Dan Li b, Hui Wang d, De-Hui Zeng a,⇑a State Key Laboratory of Forest and Soil Ecology, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110164, Chinab Provincial Key Laboratory of Applied Microbiology, Institute of Biology, Shandong Academy of Sciences, 19 Keyuan Road, Jinan 250014, Chinac Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, Chinad School of Resources and Environment, University of Jinan, Jinan 250022, China

h i g h l i g h t s

� Different remediation treatments on crude oil contaminated saline soil were studied.� Soil physicochemical and bacterial properties varied among treatments.� Combined treatments were more effective than single treatments in remediation.� c-Proteobacteria, b-Proteobacteria, and Actinobacteria were the pioneer oil-degraders.� Firmicutes were dominant in decomposing the recalcitrant components of crude oil.

a r t i c l e i n f o

Article history:Received 4 May 2014Received in revised form 14 August 2014Accepted 19 August 2014

Handling Editor: O. Hao

Keywords:RemediationBacterial communityCrude oil contaminationDenaturing gradient gel electrophoresis(DGGE)Saline soil

a b s t r a c t

Remediation of the petroleum contaminated soil is essential to maintain the sustainable development ofsoil ecosystem. Bioremediation using microorganisms and plants is a promising method for thedegradation of crude oil contaminants. The effects of different remediation treatments, including nitro-gen addition, Suaeda salsa planting, and arbuscular mycorrhiza (AM) fungi inoculation individually orcombined, on crude oil contaminated saline soil were assessed using a microcosm experiment. Theresults showed that different remediation treatments significantly affected the physicochemical proper-ties, oil contaminant degradation and bacterial community structure of the oil contaminated saline soil.Nitrogen addition stimulated the degradation of total petroleum hydrocarbon significantly at the initial30 d of remediation. Coupling of different remediation techniques was more effective in degrading crudeoil contaminants. Applications of nitrogen, AM fungi and their combination enhanced the phytoremedi-ation efficiency of S. salsa significantly. The main bacterial community composition in the crude oil con-taminated saline soil shifted with the remediation processes. c-Proteobacteria, b-Proteobacteria, andActinobacteria were the pioneer oil-degraders at the initial stage, and Firmicutes were considered tobe able to degrade the recalcitrant components at the later stage.

� 2014 Elsevier Ltd. All rights reserved.

1. Introduction

Oil hydrocarbons are one of the most prevalent soil contami-nants in the world (Abioye, 2011). It has been estimated that thenatural crude-oil seepage amounts to 0.6 Mt per year, with a rangeof uncertainty of 0.2–2 Mt per year (Kvenvolden and Cooper,2003). Hydrocarbon components have been included in the familyof carcinogens and neurotoxic organic pollutants (Das andChandran, 2011). Remediation of the petroleum contaminated soil

is essential to maintain the sustainable development of local eco-system. Technologies commonly used for the soil remediationinclude natural attenuation, land farming, biopiling or composting,slurry bioreactor, bioventing, soil vapor extraction, thermaldesorption, incineration, soil washing, and land filling (US EPA,2004). However, these technologies are usually expensive andcan lead to incomplete decomposition of contaminants (Das andChandran, 2011).

Bioremediation using microorganisms and plants to detoxify orremove pollutants owing to their diverse metabolic capabilities isan evolving method for the removal and degradation of many envi-ronmental pollutants including the products of petroleum industry

Y.-c. Gao et al. / Chemosphere 117 (2014) 486–493 487

(Singh et al., 2009). Microorganisms play key roles in biotransfor-mation of complex contaminant mixtures during soil bioremedia-tion processes (Gómez et al., 2007; Gadd, 2010). There are twomain approaches to oil spill bioremediation: Bioaugmentation(addition of oil-degrading bacteria) and biostimulation (stimulat-ing the growth of indigenous oil degraders by the addition of nutri-ents or other growth-promoting co-substrates) (Das and Chandran,2011). Meanwhile, studies have shown that plants have the abilityto detoxify some xenobiotics in soil by direct uptake of the con-taminants, followed by subsequent transformation, transport andproduct accumulation (Macek et al., 2008). Phytoremediation, withthe associated role of rhizospheric microorganisms, is an importanttool in bioremediation processes (Khan et al., 2013). However, soilbioremediation is susceptible to environmental factors (Venosaand Zhu, 2003). As for crude oil contaminated soil, soil structureand physicochemical and biological characteristics, e.g., soilorganic matter content, bulk density, porosity, permeability, soilrespiration and material transfer process, can be altered by thehigh hydrophobicity of hydrocarbons (Liang et al., 2012). Further-more, saline and hypersaline environments are frequently accom-panied with crude oil contamination as a result of industrialactivities (Oren et al., 1992). Soil salinization has great inhibitoryeffects on the biodegradation of petroleum hydrocarbons (Milleet al., 1991). Therefore, plant-mycorrhiza bioremediation is aresearch hotspot as mycorrhiza can improve plant growth, resistvarious stresses, and enhance degradation and transfer of organicpollutants (Alarcon et al., 2008; Tang et al., 2009). The combinationof two or more remediation techniques is necessary to improve thebioavailability and bioremediation efficiency considering the harshcontaminated environment.

The Shengli Oilfield, located in the Yellow River Delta region, isthe second-largest oilfield in China. The crude oil contaminationdue to oil well blowouts, leaks and spills from underground tank,pipelines and illegal disposals greatly threatens the ecosystem ofthe delta region (Wang et al., 2011a). Moreover, the Yellow RiverDelta is a newly born wetland, and the land–ocean interaction isvery active (Wang et al., 2011a). Secondary salinization of surfacesoil due to excess evaporation from soil has led to land degrada-tion, which affects 60% of total land area in the region (Fanget al., 2005). The soil salt content of this region ranges from 6 to30 g kg�1 (Wang et al., 2009). Multiple environmental stressesincrease the bioremediation difficulty of the oil contaminated soil.Furthermore, information about the effects of different bioremedi-ation treatments on crude oil contaminated saline soil is lacking.

In this study, we evaluated the effects of different remediationtreatments, including nitrogen addition, Suaeda salsa planting,and arbuscular mycorrhiza (AM) fungi inoculation individually orcombined, on the crude oil contaminated saline soil. The objectivesof this study were to investigate: (1) the effects of different reme-diation treatments on soil physicochemical properties; (2) the deg-radation rate of total petroleum hydrocarbon (TPH) and thetemporal changes of crude oil fractions; and (3) the alterations ofsoil bacterial biodiversity and community structure, and the mainbacterial groups participating in remediation.

2. Materials and methods

2.1. Soil used for experiment

Uncontaminated saline soil was collected from the Shengli Oil-field in China. The soil was air dried and ground to 0.85 mm(20 meshes) before using. Crude oil was then added to a portionof the uncontaminated saline soil with a dosage of 2% of soil mass.The physicochemical properties of the uncontaminated saline soil(U1) and soil mixed with crude oil (U2) are shown in Table 1.

2.2. Experimental design

A pot experiment was carried out to study the effect of differentremediation treatments on the crude oil contaminated saline soil.Six treatments were designed: (1) CK, control; (2) S, seepweed (S.salsa) bioremediation; (3) N, nitrogen addition; (4) N + S, nitrogenaddition and S. salsa combined bioremediation; (5) M + S, AM andS. salsa combined bioremediation, adding 1% (relative to soil mass)of commercially available AM fungi inocula (AMYkor, GmbH,Bitterfeld-Wolfen, Germany) before planting S. salsa; (6) M + N + S,AM, nitrogen addition and S. salsa combined bioremediation, adding1% AM fungi inocula of the soil mass before planting S. salsa. In treat-ments 3, 4 and 6, urea was added with a dosage of 1‰ of the soilmass to the crude oil contaminated soil, and then mixed with the soilthoroughly. Each treatment was replicated four times.

Filter paper was placed at the bottom of the pot (with a size of13 cm high � 15 cm in diameter) to cover the drainage hole, and1500 g crude oil contaminated saline soil was added. For S. salsaplanting, 0.5 g of seed were sown evenly to the soil in each potand covered with 2–3 cm of soil on the top (1500 g soil added intotal for each pot). Water was then added to maintain 60–80% ofsoil water-holding capacity. All of the experiment pots were placedin a greenhouse at 25 �C. Seven days after seeds germinated, 20healthy seedlings were preserved in each pot for further phyto-remediation. Soil samples were taken after 0, 30, 60 and 90 d witha hole-puncher (10 cm long and 1.5 cm in diameter). Three soilsamples were collected and mixed to form a composite for eachpot at each sampling time. The holes were filled with the surround-ing soil in the pot immediately after sampling. Then the soilsamples were divided into two subsamples: one was used to studythe variations of soil physicochemical properties and crude oil frac-tions and the other was stored at �20 �C for denaturing gradientgel electrophoresis (DGGE) analysis. The dynamics of bacterialcommunity of all treatments before and after remediation (90 d)were analyzed. Furthermore, the bacterial community of thetreatment with best performance was monitored in the whole pro-cess to find out the main functional bacteria participating in theremediation at different stages.

2.3. Soil property, crude oil fraction and soil microbial biomassanalyses

The soil samples used for the test of electrical conductivity (EC)and pH were air-dried, passed through a 2-mm sieve, and mea-sured according to Gao et al. (2013). The soil water content wasmeasured according to Alef and Nannipieri (1995). TPH wasextracted and measured according to Chaîneau et al. (2005). Thedry extract was suspended in 10 mL of hexane by sonication(5 min, 40 kHz). Methods of separation and measurement for crudeoil fractions (saturates, aromatics, resins, and asphaltenes) in theextract were in accordance with Oudot et al. (1998). Soil total Kjel-dahl nitrogen (TKN) concentration was analyzed by the Kjeldahlmethod with a continuous-flow analyzer (AutoAnalyzer III, Bran +Luebbe GmbH, Germany).

2.4. PCR-DGGE analysis

Total genomic DNA was extracted from the soil samples usingthe E.Z.N.A. Soil DNA Kit (Omega Biotek, USA) according to themanufacturer’s instructions. The variable V3 region of 16S rRNAwas amplified by PCR using a pair of universal primers, 338F 50-ACTCCTACGGGAGGCAGCAG-30 and 534R 50-ATTACCGCGGCTGCTGG-30, to which a GC clamp (CGCCCGCCGCGCGCGGCGGGCGGGGCGGGGGCACGGGGGG) was attached at the 50-terminus (Muyzeret al., 1993). The PCR mixture consisted of 5 lL of DNA template,2 lL of 338F/534R (10 lM) primers each, 25 lL of Tiangen 2 � Taq

Table 1Physicochemical properties of the experimental soils.

Soil samples EC (mS cm�1) TPH (g kg�1) TKN (g kg�1) pH Water content (%)

U1 4.73 1.4 0.37 8.14 22.3U2 4.47 12.6 0.44 8.30 20.7

U1: uncontaminated saline soil; U2: soil mixed with crude oil. EC, electrical conductivity; TPH, total petroleum hydrocarbon; TKN, total Kjeldahlnitrogen.

488 Y.-c. Gao et al. / Chemosphere 117 (2014) 486–493

PCR Master Mix, and 16 lL ddH2O comprising a total volume of50 lL (Tiangen Biotech, Beijing). A modified touch-down PCR pro-cedure was used for cycling amplification in a Veriti PCR thermalcycler (Applied Biosystems, USA). Touch-down amplification wasperformed with an initial step of 10 min at 94 �C, followed by10 cycles of denaturation for 1 min at 94 �C, annealing for 1 minwith temperatures decreasing from 60 �C at 0.5 �C per cycle, andprimer extension for 1.5 min at 72 �C. This step was similarly fol-lowed by 25 cycles of denaturation for 1 min at 94 �C, annealingfor 1 min at 55 �C, and primer extension for 1.5 min at 72 �C,followed by a final extension at 72 �C for 10 min. DGGE analysiswas performed with 8% (w/v) polyacrylamide gels (ratio of acryl-amide to bis-acrylamide 37.5:1) in 1 � TAE buffer (40 mM Tris–acetate, 1 mM Na-EDTA, pH 8.0) with a gradient ranging from 40to 60% (where 100% denaturant was defined as 7 M urea and 40%formamide) at a constant voltage of 65 V and 60 �C for 16 h (Bio-Rad Dcode System, USA). Gels were silver stained according toNing et al. (2009). Finally, the DGGE gels were scanned using GelDoc 2000 gel image analysis system (Bio-Red, USA) and analyzedby Quantity One image analysis software (version 4.1; Bio-RadLaboratories, Hercules, CA, USA). Prominent DGGE bands wereexcised with a sterile razor blade, re-suspended in 50 lL sterilizedddH2O, stored at 4 �C overnight, re-amplified, cloned in the pGEM-T Easy vector (Promega, Madison, WI), and sequenced by using anABI Prism Big Dye terminator cycle sequencing reaction kit, version3.1 (Perkin-Elmer Applied Biosystems, Foster City, CA, USA), and anABI 3700 DNA sequencer (Perkin-Elmer Applied Biosystems, FosterCity, CA, USA) following the manufacturer’s instructions. Thesequences were edited and assembled using the BioEdit software,and inspected for the presence of ambiguous base assignments.

2.5. Biodiversity and phylogenetic analyses

We used Shannon index (H’), Pielou’s evenness index (E) andrichness (detected bands) to assess the bacterial diversity duringthe remediation of the oil-contaminated saline soil. The H’ valuewas calculated as follows:

H0 ¼ �XS

i¼1

Pi lg Pi

where Pi is the relative peak area intensity of a DGGE band, calcu-lated from ni/N, ni is the peak area of the band, N is the sum of allpeak areas in the densitometry curve, and S is the total number ofdistinct bands in a lane (Kirk et al., 2005). The E value was calcu-lated from each standardized band by using number and height ofpeaks in each band profile as representatives of the number and rel-ative abundance of different phylotypes in each line. The formulafor E value was calculated as follows:

E ¼ H0

Hmax

where Hmax = lg S (Thavamani et al., 2012).16S rRNA gene sequences were blasted against the GenBank

database (www.ncbi.nlm.nih.gov/BLAST). All sequences with simi-larities greater than 97% were included in a phylogenetic analysis(Xing et al., 2010). All sequences used for phylogenetic analysis

have been deposited in the GenBank nucleotide sequence databaseunder accession numbers from KJ179808 to KJ179831. The phylo-genetic trees were constructed by the neighbor-joining methodwith the Molecular Evolutionary Genetics Analysis software(Tamura et al., 2007).

2.6. Statistical analyses

The differences of soil EC, TPH, TKN and water content of oil-contaminated saline soil in different remediation treatments andsampling time were analyzed using one-way ANOVA analysisand repeated measures variance analysis. Dendrogram analysis ofthe DGGE fingerprints was constructed based on the Dice similaritycoefficient using unweighted pair group method clustering withthe Quantity One software.

3. Results

3.1. Physicochemical properties of the remediation soils

EC is the most commonly used index for soil salinity assess-ment. The EC of the original soils used for the experiment was over4 mS cm�1 (Table 1), showing that the soils were saline. Therepeated measures ANOVA analysis showed that EC, TPH degrada-tion rate and TKN had significant differences at different remedia-tion time and treatments. Furthermore, there existed significantinteractive effects of time and treatment on EC, TPH degradationrate and TKN (Table 2). EC had no significant difference amongthe different treatments during the initial 30 d of remediation.The soil EC in the treatments of S, N + S, M + S and M + N + Sreduced significantly with the extension of remediation time. Thetreatment of M + N + S was best in reducing soil salinization. Nitro-gen addition alone had no obvious contribution to the alleviationof soil salinization. TPH degradation rate had significant differencesamong different treatments during remediation (Table 2). Nitrogenaddition (the treatments of N, N + S and M + N + S) significantlystimulated the degradation of TPH at the initial 30 d. The TPH deg-radation efficiency of treatment M + N + S was more effective thanothers. However, nitrogen addition alone had little effect on theTPH degradation in the subsequent 60 d. The soil water contentschanged significantly over the remediation process and they hadno difference among treatments at each sampling time. No interac-tive effects of remediation time and treatments on the watercontent were observed.

3.2. Effects of different remediation treatments on crude oil fractions

The composition of the oil significantly varied in different treat-ments after 90 d of remediation (Fig. 1). Saturates and aromatics intotal accounted for about 65% of the oil at the initial stage of theexperiment. After 90 d, the TPH degradation rate increased at dif-ferent degrees under different treatments (Table 2). The treatmentsof M + S and M + N + S significantly improved the degradation ratecompared with the control. Comparing the data of TPH degradationrate and the proportion of the four crude oil fractions, saturatesand aromatics were the most easily degradable fractions of the

Tabl

e2

Repe

ated

mea

sure

san

alys

isof

vari

ance

for

EC,T

PHde

grad

atio

nra

te,T

KN

and

wat

erco

nten

tof

oil-

cont

amin

ated

salin

eso

ildu

ring

rem

edia

tion

.

Trea

tmen

tEC

(mS

cm�

1)

TPH

degr

adat

ion

rate

(%)

TKN

(gkg�

1)

Wat

erco

nte

nt

(%)

30d

60d

90d

30d

60d

90d

30d

60d

90d

30d

60d

90d

CK

4.4

(0.1

)a4.

3(0

.1)c

4.2

(0.1

)c24

.2(2

.1)c

40.3

(4.3

)b44

.0(1

.3)b

0.36

(0.1

)a0.

30(0

.0)a

0.26

(0.1

)a21

.8(0

.6)a

20.4

(0.7

)a14

.8(1

.0)a

S4.

3(0

.0)a

4.0

(0.1

)bc

3.4

(0.1

)b29

.4(1

.6)c

43.8

(1.1

)ab

48.5

(3.0

)ab

0.41

(0.0

)a0.

43(0

.0)b

0.42

(0.0

)b19

.9(0

.5)a

18.8

(0.8

)a15

.8(0

.9)a

N4.

6(0

.1)a

4.3

(0.1

)c4.

0(0

.1)c

39.1

(4.9

)b44

.3(3

.3)a

b47

.0(2

.9)a

b0.

75(0

.1)b

0.74

(0.1

)c0.

69(0

.2)c

19.9

(1.0

)a20

.9(0

.8)a

16.0

(1.8

)aN

+S

4.5

(0.1

)a3.

6(0

.1)b

3.4

(0.1

)b47

.9(3

.2)a

45.5

(5.4

)ab

53.9

(1.5

)ab

0.89

(0.0

)c0.

78(0

.0)c

0.66

(0.1

)c22

.2(0

.3)a

20.3

(1.2

)a16

.9(0

.7)a

M+

S4.

5(0

.1)a

3.7

(0.1

)b3.

1(0

.2)b

45.6

(1.2

)a46

.9(2

.0)a

b54

.1(1

.2)a

0.36

(0.1

)a0.

39(0

.0)a

b0.

42(0

.2)b

19.6

(0.4

)a19

.8(0

.2)a

17.9

(0.3

)aM

+N

+S

4.6

(0.1

)a3.

2(0

.2)a

2.5

(0.1

)a52

.9(0

.1)a

53.1

(5.2

)a59

.9(2

.6)a

0.77

(0.1

)b0.

71(0

.1)c

0.59

(0.1

)c24

.8(0

.9)a

19.7

(0.4

)a16

.8(0

.4)a

Pva

lues

Tim

e(T

)***

***

**

**

Trea

tmen

t(M

)***

**

***

ns

T�

M***

**

***

ns

CK

,con

trol

;S,

S.sa

lsa

bior

emed

iati

on;

N,n

itro

gen

addi

tion

;N

+S,

nit

roge

nad

diti

onan

dS.

sals

aco

mbi

ned

bior

emed

iati

on;

M+

S,A

Man

dS.

sals

aco

mbi

ned

bior

emed

iati

on;

M+

N+

S,A

M,n

itro

gen

addi

tion

and

S.sa

lsa

com

bin

edbi

orem

edia

tion

.Val

ues

repo

rted

are

mea

ns

(n=

4)an

dst

anda

rder

rors

inth

ebr

acke

ts.T

he

diff

eren

tlo

wer

case

lett

ers

inea

chco

lum

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tesi

gnifi

can

tdi

ffer

ence

sin

the

diff

eren

ttr

eatm

ents

atsa

me

sam

plin

gti

me.

ns,

Not

sign

ifica

nt.

**

P<

0.01

.***

P<

0.00

1.

Y.-c. Gao et al. / Chemosphere 117 (2014) 486–493 489

oil. By contrast, asphaltenes and resins were hardly degraded in allof the treatments.

3.3. Soil bacterial biodiversity in different remediation treatments

Soil bacterial community diversity indices were analyzed usingthe DGGE data (Table 3). The H’ index increased immediately afterthe addition of crude oil contaminants in the saline soil (U2). Ninetydays later, the H’ index in treatment of N + S was the highest amongall the treatments. The H’ and richness indices of the combinedtreatments (N + S, M + S and M + N + S) were all higher than thetreatments individually. The combined treatments led to thedecrease of the E index, while the treatments individually had noeffect on the E index. The long-term monitoring of the treatmentM + N + S showed that the bacterial community diversity variedgradually during the remediation process. The H’ index of the wholebacterial community increased, while the E index decreasedaccordingly.

3.4. Phylogenetic analysis

The DGGE profile showed that the richness and composition ofthe bacterial populations had significant differences among differ-ent treatments and remediation periods (Fig. 2). The number of dis-tinct DNA bands ranged from 7 in the pristine saline soil to 21 in thesoil after 90 d of remediation. The main sequences of the DGGEbands fell into corresponding operational taxonomic units (OTUs)based on a threshold of 97% similarity (Kocherginskaya et al.,2001). The phylogenetic distributions of the OTUs were divided intothe following three groups (Fig. 3): Proteobacteria (c-Proteobacte-ria, b-Proteobacteria, a-Proteobacteria), Actinobacteria, and Firmi-cutes. Some OTUs could not be classified and were designated as‘‘unclassified’’. The bacterial populations were sparse in the pristinesaline soil without crude oil contamination (Fig. 2, U1). With theaddition of crude oil to the soil, the bacterial species increasedimmediately (Fig. 2, U2). b-Proteobacteria (bands 11, 14) was anew class evoked by oil contamination. The main bacterial popula-tions changed slightly after 90 d (see the DGGE patterns of U2 andCK in Fig. 2). The treatments of planting seepweed or nitrogen addi-tion did not alter the bacterial community structure significantly.The richness of the bacterial populations was improved signifi-cantly in the combined treatments (N + S, M + S, and M + N + S).Comparing the DGGE profile and the phylogenetic tree (Figs. 2and 3), the groups of b-Proteobacteria (bands 11, 14), c-Proteobac-teria (bands 4, 5, 12, 13) and Actinobacteria (bands 3, 17) were thepioneer degraders participating in the TPH biodegradation at theearly stage, while the groups of b-Proteobacteria (bands 9, 16), c-Proteobacteria (bands 1, 2), Actinobacteria (bands 10, 24) andFirmicutes (bands 22, 23) were the dominant groups participatingin the TPH biodegradation at the later stage. Among which, b-Prote-obacteria (band 16) was the bacteria emerging around the roots ofthe seepweed. The groups of a-Proteobacteria (bands 7, 20) andActinobacteria (band 18) were the indigenous phyla that cannotdegrade the TPH.

4. Discussion

4.1. Effect of nitrogen addition on promoting the degradation of crudeoil

Oil pollution could lead to significant changes in soil chemicalproperties, such as TPH, TOC, C/N and C/P ratios (Wang et al.,2010). Nitrogen is the most commonly limiting factor to biologicaldegradation of hydrocarbon in soils (Mohn and Stewart, 2000).Nitrogen addition could stimulate the microbial activity, and

Fig. 1. Proportion of four crude oil fractions after 90 d of incubation under different treatments (%). CK, control; S, S. salsa bioremediation; N, nitrogen addition; N + S, nitrogenaddition and S. salsa combined bioremediation; M + S, AM and S. salsa combined bioremediation; M + N + S, AM, nitrogen addition and S. salsa combined bioremediation.

Table 3The bacterial biodiversity of the oil-contaminated saline soil under different remediation treatments.

Diversity index U1 U2 90 d 60 d 30 d

CK S N N + S M + S M + N + S M + N + S M + N + S

Shannon index (H’) 2.3 2.61 2.82 2.62 2.75 3.09 2.84 2.90 2.62 2.76Evenness index (E) 0.99 0.98 0.98 0.98 0.98 0.95 0.97 0.97 0.98 0.99Richness index (detected bands) 10 14 17 14 16 25 18 19 14 16

U1, uncontaminated saline soil; U2, oil-contaminated saline soil; CK, control; S, S. salsa bioremediation; N, nitrogen addition; N + S, nitrogen addition and S. salsa combinedbioremediation; M + S, AM and S. salsa combined bioremediation; M + N + S, AM, nitrogen addition and S. salsa combined bioremediation.

490 Y.-c. Gao et al. / Chemosphere 117 (2014) 486–493

increase the degradation rate of hydrocarbon (Braddock et al.,1997; Xu and Obbard, 2003). In our study, the addition of nitrogenstimulated the degradation of TPH significantly at the initial 30 d ofremediation (Table 2). However, the stimulating effect did not con-tinue in the following 60 d. The low bioavailability of contaminantand the accumulation of recalcitrant compounds could inhibit themicrobial biodegradation ability (Margesin and Schinner, 1999).Significant additive effects on the TPH degradation rates wereobserved in treatments N + S and M + N + S at the initial 30 d ofremediation compared with the treatment of N addition alone.Nitrogen addition promoted the growth of plants, which may leadto greater transpirational water loss, allow more air to enter thesoil and thus increase soil oxidization (Lin and Mendelssohn,1998).

4.2. Effects of planting seepweed on the remediation of crude oilcontaminated saline soil

Phytoremediation is an emerging technology which uses variousplants to extract, contain, degrade, and/or immobilize contami-nants (Wang et al., 2011b). Plants support hydrocarbon-degradingmicrobes that assist in phytoremediation in the root zone throughtheir ‘rhizosphere effects’ (Nie et al., 2009). In the present study,phytoremediation merely had a contribution to the reduction of soilsalinity, but no significant effect on TPH degradation (Table 2). Theefficiency of phytoremediation depends mostly on the establish-ment of robust plant–microbe interactions (Wenzel, 2009; Nieet al., 2011). Roots offer perfect attachment sites for microorgan-isms and supply nutrients in the form of exudates, which couldenhance the microbial activity and thus the biodegradation oforganic contaminants (Sijm et al., 2000; Xie et al., 2012). Combined

remediation of planting seepweed with nitrogen addition and/orAM fungus inoculation not only alleviated soil salinization, but alsosignificantly reduced the TPH concentrations.

4.3. Effect of AM on the remediation of crude oil contaminated salinesoil

AM fungi can enhance plant growth by improving mineralnutrition, or increasing resistance or tolerance to biotic and abi-otic stresses (Turnau and Haselwandter, 2002; Khan, 2006). Inthe present study, the treatments of M + S and M + N + Senhanced the degradation of TPH significantly and obviously pro-longed the validity of remediation compared with the other treat-ments. Mycorrhizal fungal mycelia and surrounding soil providedsuitable habitats for diverse community composition of microor-ganisms, which increased the availability of high-energymetabolic substrates and surfaces for colonization (Sen, 2003).The soil salinity was also reduced significantly in the treatmentsof S, N + S, M + S and M + N + S. The dilution effects of plantgrowth and AM fungi colonization were inferred to be an impor-tant reason in alleviating the soil salinity (Giri et al., 2007; Latefand He, 2011).

4.4. Functional oil-degraders during remediation process

The degradation of complex pollutants such as petroleumrequires a combination of different bacteria as a community, whichcan degrade a broader spectrum of hydrocarbons than any singlebacterial species alone (Pelz et al., 1999; Röling et al., 2002). Sev-eral studies showed that the bacterial community was always

Fig. 2. DGGE of 16S rRNA amplification fragments and corresponding bands isolated for sequencing. PCR fragments were separated on a DGGE using a denaturant gradient of40–60%. U1, uncontaminated saline soil; U2, oil-contaminated saline soil; CK, control; S, S. salsa bioremediation; N, nitrogen addition; N + S, nitrogen addition and S. salsacombined bioremediation; M + S, AM and S. salsa combined bioremediation; M + N + S, AM, nitrogen addition and S. salsa combined bioremediation.

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changed dynamically (Zucchi et al., 2003; Vinas et al., 2005; Yuet al., 2011). In our study, the increase of certain bacterialpopulations responsible for the TPH degradation led to the shiftof bacterial community according to the variation of microbialcommunity richness, evenness and the phylogenetic tree. Previousstudies showed that specific bacterial phylotypes were associatedwith different phases of polycyclic aromatic hydrocarbon (PAH)degradation in PAH contaminated soil (Vinas et al., 2005). At theearly stages of biodegradation, the a-Proteobacteria were the dom-inant group in all treatments. At the later stages, c-Proteobacteria,a-Proteobacteria, and the Cytophaga-Flexibacter-Bacteroides werethe dominant groups in the non-nutrient treatments, whilec-Proteobacteria, b-Proteobacteria, and a-Proteobacteria were thedominant groups in the nutrient treatments. The microcosmexperiment on the succession of bacterial community with thedegradation of crude oil contaminants using saline soil sampledfrom the Yellow River Delta, China showed that, c-Proteobacteriawere the dominant bacteria responsible for the biodegradation ofTPH at the initial stage. Subsequently, the bacteria belonging toa-Proteobacteria became the dominant oil-degraders to degrade

the remaining recalcitrant constituents of the heavy crude oil (Yuet al., 2011). Acinetobacteria has the ability to utilize n-alkanesof chain length C10–C40 as a sole source of carbon (Throne-Holstet al., 2007). In the present study, c-Proteobacteria, b-Proteobacte-ria, and Actinobacteria were found to be the pioneer oil-degradersat the early stage. With the proceeding of remediation,c-Proteobacteria, b-Proteobacteria, and Actinobacteria were stillthe dominant groups in the soils, and Firmicutes were consideredto play a key role for the decomposition of the remaining crudeoil constituents.

In conclusion, different remediation treatments had differenteffects on saline soil physicochemical properties, oil contaminantdegradation and bacterial community structure. Coupling of differ-ent remediation techniques was more effective in degrading crudeoil contaminants. Nitrogen addition, AM fungi inoculation or theircombination significantly enhanced the remediation efficiency ofseepweed. Soil bacterial community shifted with the remediationprocesses. c-Proteobacteria, b-Proteobacteria, and Actinobacteriawere the pioneer oil-degraders, while Firmicutes were inferred tobe able to degrade the recalcitrant components.

Fig. 3. Phylogenetic tree of the16S rRNA amplification fragments separated by DGGE gel. The reference sequences used are shown with their species names and GenBankaccession numbers. The scale bar corresponds to 0.02 substitutions per nucleotide position.

492 Y.-c. Gao et al. / Chemosphere 117 (2014) 486–493

Acknowledgments

We thank Gui-Yan Ai and Jing-Shi Li for their help inlaboratory analyses. This work was funded by the NationalHigh Technology Research and Development Program (‘‘863’’Program) of China (2013AA06A210), the Natural Science Foun-

dation of Shandong Province (No. ZR2011DQ002), the NationalNatural Science Foundation of China (31270586) and the OpenFund of the Laboratory of Marine Spill Oil Identification andDamage Assessment Technology, North China Sea Environmen-tal Monitoring Center, Oceanic Administration of China (No.201213).

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