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微生物学通报 May 20, 2015, 42(5): 826−834
Microbiology China © 2015 by Institute of Microbiology, CAS
tongbao@im.ac.cn DOI: 10.13344/j.microbiol.china.140880
Foundation item: National Natural Science Foundation of China (No. 41306150); Promotive Research Fund for
Excellent Young and Middle-Aged Scientists of Shandong Province (No. BS2012HZ011); Project of
Shandong Province Higher Educational Science and Technology Program (No. J10LC09); Open
Funding Project of Key Laboratory of Marine Biogenetic Resources, SOA (No. HY201205)
*Corresponding author: Tel: 86-538-8249697; Fax: 86-538-8242217
: LI Han: lihan@sdau.edu.cn; GAO Zheng: gaozheng@sdau.edu.cn
Received: November 06, 2014; Accepted: January 26, 2015; Published online (www.cnki.net): March 03, 2015
研究报告
New findings in effect of different crude oil concentrations on
bacterioplankton communities
WEI Guang-Shan SUN Jing LI Jing LI Han* GAO Zheng*
(State Key Laboratory of Crop Biology, College of Life Sciences, Shandong Agricultural University,
Tai’an, Shandong 271018, China)
Abstract: [Objective] To investigate the effect of crude oil concentrations on bacterial community
structures and diversity, and attempt to elucidate the mechanism of this effect. [Methods] Seawater
was sampled near a marine drilling platform and was treated with five different crude oil
concentrations (0 to 10 g/L) for a week in the laboratory. Then the bacterial communities were
detected using terminal restriction fragment length polymorphism (TRFLP) method. [Results] Some
new findings were exhibited, such as the bacterial diversity did not simply decrease with the increase
of oil concentrations, but decreased at first, then increased and decreased again. Bacterial
communities of treatments with 0.1 g/L (M0.1) and 0.5 g/L (M0.5) crude oil, treatments with 2.5 g/L
(M2.5) and 10 g/L (M10) crude oil were similar, respectively, and bacterial communities in the oil
added groups (M0.1, M0.5, M2.5, M10) were significantly different from the control (M0).
Classification results of the dominant terminal restriction fragments (TRFs) in the oil treatments
mainly attached to Proteobacteria, Firmicutes and Bacteroidetes. Based on the relative ratios of TRFs
in different treatments, the 52 TRFs could be divided into six types (I to VI): low (I)/middle (II)/high
(III)/broad (IV)/narrow (V) concentrations of crude oil adapted bacteria and crude oil sensitive
bacteria (VI). Furthermore, “Carbon & Energy sources-Toxicities” hypothesis was proposed to
explain effects of oil pollution on bacterioplankton. [Conclusion] Impacts of crude oil pollutions on
the marine bacterioplankton are closely related to the concentration of oil and the original bacterial
communities in the seawater, these bacteria could be classified upon their adaptability to the crude
oil. And the “Carbon & Energy sources-Toxicities” hypothesis could explain effects of oil pollution
on bacterioplankton very well.
Keywords: Crude oil pollution, TRFLP, Bacterioplankton, Community structures, Hypothesis
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不同石油浓度对浮游细菌群落影响的新发现
位光山
孙静
李静
李菡
*
高峥
*
(山东农业大学生命科学学院 作物生物学国家重点实验室 山东 泰安 271018)
摘 要: 【目的】研究不同浓度石油污染对海水中浮游细菌群落结构及多样性的影响，并尝试
阐述造成这种影响的机理。【方法】将采集自海上钻井平台附近的表层海水样品，在实验室条
件下用不同浓度的石油(0−10 g/L)处理 1周后，用末端限制性片段长度多态性(TRFLP)方法检测
其细菌群落结构及多样性变化情况。【结果】得到了一些与以往研究结果不同的新发现，如细
菌多样性不是简单地随石油浓度的升高而降低，而是呈现先降低再升高最后又降低的趋势。
0.1 g/L 石油处理组(M0.1)与0.5 g/L 处理组(M0.5)、2.5 g/L 石油处理组(M2.5)和10 g/L 处理组
(M10)的细菌群落结构更相似，且添加石油处理组(M0.1、M0.5、M2.5、M10)与未添加石油的对
照组(M0)间细菌群落结构相差较大。与石油降解相关的细菌主要集中于变形菌门(Proteobacteria)、
厚壁菌门(Firmicutes)和拟杆菌门(Bacteroidetes)。基于 TRFs 在不同处理组的相对比例，可将实
验得到的 52 个TRFs 划分为 6种类型：低浓度(I)、中浓度(II)、高浓度(III)、广浓度(IV)、窄浓
度(V)石油适应型和石油敏感型(VI)细菌。另外，首次提出“碳(能)源-毒素”假说来解释石油污染
对浮游细菌群落的影响。【结论】石油污染对浮游细菌群落的影响与石油的浓度和海水中原有
的历史细菌群落密切相关，可以按照浮游细菌对石油的适应性对其进行分类，并且“碳(能)源-
毒素”假说能较好地解释石油污染对浮游细菌群落的影响。
关键词: 石油污染，TRFLP，浮游细菌，群落结构，假说
1 Introduction
Crude oil as a complex mixture of hydrocarbons
and other organic compounds is classified into four
fractions: aliphatics, aromatics, resins and
asphaltenes[1]. Meanwhile, it includes some heavy
metal constituents, most notably mixture of vanadium
and nickel[2-3]. So crude oil released into seawater
affects marine organisms in many ways, but it is
gradually removed by the action of oil-degrading
microorganisms, especially bacteria[2].
With the development of microbial molecular
methods, culture-independent methods, such as
TRFLP, DGGE (denaturing gradient gel
electrophoresis), 16S rRNA gene clone library and
high-throughput sequencing, showed great advantages
in monitoring dynamics and diversity of microbial
communities. Due to the high throughputs, high
reproducibility and robustness, quantitative in species
ratios and web-based RDP database[4-5], TRFLP
method has been widely used in recent microbial
diversity and dynamics researches[6-7]. Depending on
culture and/or culture-independent methods, a large
number of studies have examined the effects of crude
oil or its partial components on microbial
communities in different environmental samples.
MacNaughton et al. found that the structure and
diversity of the dominant bacterial community
changed substantially and oil treatment encouraged
the growth of gram-negative microorganisms within
the Alphaproteobacteria and Bacteroidetes during
bioremediation of an experimental oil spill[8].
Proteobacteria, Firmicutes, Actinobacteria and
Bacteroidetes were demonstrated to be the adapted
microbiota during the degradation of Tunisian
zarzatine oil, and a clear decrease in bacterial diversity
happened according to the incubation time in
seawater[9]. The polycyclic aromatic hydrocarbons
(PAHs) as major components of crude oil were found
to reduce the microbial diversity both with the
exposure time and the PAH concentration in the
mangrove sediment[10].
However, the studies in relationships between
crude oil concentration gradients and bacterioplankton
communities are very limited. Systematic and general
theories or hypotheses to explain the effects of crude
oil pollution on bacterial communities are rarely
828 微生物学通报 Microbiol. China 2015, Vol.42, No.5
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proposed. In this study, we reported the effects of
different crude oil concentrations on the
bacterioplankton communities in the Yellow River
estuary. Based on the data, “Carbon & Energy
sources-Toxicities” hypothesis was proposed.
2 Materials and Methods
2.1 Sampling site and physiochemical parameters
The Yellow River estuary is situated on the
confluence among the Yellow River, Bohai Bay and
Laizhou Bay of China, and the Shengli Oil Field is
located here. Therefore, it is threatened by crude oil
pollution, for instance, the ConocoPhillips oil leak in
Bohai Bay happened in 2011. Surface seawater was
sampled beside an oil field in the Yellow River estuary
(119°18′29.0″E, 37°43′49.5″N). When sampled, the in
situ water temperature was 14.1 °C, pH was 8.10,
salinity was 26.67‰, and the dissolved oxygen was
7.50 mg/L. Total nitrogen of the sample was 4.50 mg/L,
total phosphorus was 0.079 mg/L and the chemical
oxygen demand (COD) was 53.60 mg/L. The crude oil
from Shengli Oil Field was collected in a sterile flask.
Sample bottles were stored in ice box and were
transported back to laboratory immediately.
2.2 Samples management in laboratory
Sampled seawater was mixed sufficiently and
was equally transferred into fifteen 250 mL sterile
flasks (100 mL in each flask). Different concentrations
of sterilized crude oil were added into the flasks, final
oil concentrations in each treatment were 0, 0.1, 0.5,
2.5 and 10 g/L, respectively, and triplicate for each
treatment. Shaking (170 r/min) and sealing cultured at
30 °C for a week. Then triplicates seawater of same oil
concentration were mixed together, filtered by 0.22 μm
millipore filters and stored at −80 °C until the DNA
extraction.
2.3 DNA extraction and TRFLP analysis
The DNA extraction followed the manufacturer’s
protocol of E.N.Z.A.TM Water DNA Kit (Omega,
USA). The DNA extracts were examined by
electrophoresis in a 1% (W/V) agarose gel. The
TRFLP analysis followed previous procedures,
27F-FAM and 1492R primer sets were used, and
approximate 1 500 bpʼs 16S rRNA gene products were
obtained for analysis[7]. The purified PCR products
(10 μL) were digested with two different restriction
enzymes, Hae III and Msp I (TaKaRa, Japan),
respectively.
2.4 Statistical analysis
A TRF (terminal restriction fragment)
represented an OTU (operational taxonomic unit) and
the relative abundance was calculated by the TRFs’
relative peak area. Sizes of TRFs between 60 and
700 bp were adopted in further analysis and TRFs
with relative abundance <1% were excluded. Based on
the effective TRFs, the non-metric multidimensional
scaling (NMDS) and diversity indices were conducted
using the PAST software[11], Bray-Curtis coefficient
was adopted to visualize the dissimilarity among
bacterial community. Diversity indices, Margalef,
Shannon, Pielou and Simpson index, denoted the
richness, diversity, evenness and dominance,
respectively. The PAT+ online program of MiCA 3
was used to confirm the phyla of dominant TRFs[12].
3 Results
3.1 Change of bacterioplankton diversity with
the concentrations of crude oil
Different restriction endonuclease, Hae III and
Msp I, were used to digest the 16S rRNA gene
fragments, separately. Interestingly, the bacterial
richness did not simply decrease with the increase of
crude oil concentrations. Both the two digestion
exhibited consistent trends, the bacterial richness
decreased at first (from 0 to 0.5 g/L) and then
increased (0.5 to 2.5 g/L) and decreased again (2.5 to
10 g/L) with the increase of crude oil concentrations
(Figure 1). The bacterial richness in 0.5 g/L crude oil
was lower than that in 2.5 g/L, and was comparable
with that in 10 g/L treatment (Figure 1). Because of
the better polymorphism of Msp I digesting results
(Figure 1), further analysis in the study mainly based
on the data from Msp I digestion. The Shannon,
Margalef and Simpson indices also showed that the
bacterial diversity decreased from M0 to M0.5, and
then increased in M2.5, and decreased again in M10
(Table 1).
3.2 Bacterioplankton community structures
among different treatments
Through Msp I digestion, a total of 52 different
effective TRFs were obtained. Control without crude
oil (M0) was detected the most TRFs (22 TRFs),
followed by M0.1 (21 TRFs), M2.5 (20 TRFs), M0.5
(16 TRFs) and M10 (16 TRFs). The bacterial communities
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Figure 1 Changing trends of bacterial richness with crude
oil concentrations
图1 细菌丰富度随石油浓度变化趋势
Note: Msp I and Hae III are different restriction endonuclease.
注：Msp I 和Hae III 代表两种不同的限制性核酸内切酶.
Table 1 Diversity indices of different treatments
表1 不同浓度石油处理组多样性指数
Groups Margalef Shannon Pielou Simpson
M0 4.56 2.70 0.87 0.089
M0.1 4.34 2.49 0.82 0.117
M0.5 3.47 2.38 0.84 0.114
M2.5 4.13 2.65 0.88 0.081
M10 3.26 2.38 0.86 0.123
Note: “M” refers to digestion results of Msp I, and the followed
number denotes concentrations of crude oil.
注：M0−M10：限制性核酸内切酶 Msp I酶切后不同浓度梯
度的实验组.
changed largely both in the TRFʼs sizes and their
relative ratios among different experimental groups
(Figure 2). The 435 bp TRF (22.82%) was the most
dominated one in group M0, followed by 295 bp
(12.85%), 485 bp (8.96%), 489 bp (7.23%), 487 bp
(6.38%) and 545 bp (5.02%), however, most of the
dominant bacteria were replaced by some low
abundance bacteria in M0 when crude oil was added
(Figure 2). In the oil added groups (M0.1 to M10),
there were 11 different dominant TRFs which covered
approximately 70% in each group. The most
predominant TRF became 425 bp both in group M0.1
and M0.5 (24.22% in M0.1 and 20.57% in M0.5),
followed by 151 bp (20.22% in M0.1 and 17.82% in
M0.5). Nevertheless, a 435 bp TRF turned into the
most dominated TRF in higher concentrations of crude
oil groups (16.95% in M2.5 and 29.21% in M10), the
second dominant TRF was 485 bp (13.69%) in M2.5,
while 433 bp (9.83%) in M10. These TRFs, 425 bp,
435 bp and 485 bp, existed in all oil-contained groups
(M0.1 to M10) and were abundant (Figure 2).
Through the MiCA 3 online program, the dominant
TRFs (relative ratio > 5%) in the oil treated groups
mainly were Proteobacteria, Firmicutes, Bacteroidetes
and maybe in phyla of Verrucomicrobia,
Actinobacteria and Cyanobacteria.
To clarify the dissimilarity of the bacterial
communities among different groups, NMDS plot was
conducted (Figure 3). In the plot, the community
structure of group M2.5 and M10 were closer, and
group M0.1 and M0.5 was more similar, while the
bacterial communities of group M0 was very different
from them (Figure 3). These results indicated that the
bacterial communities changed largely after crude oil
was added, and some similar bacterial species existed
in different degrees of oil polluted environments.
Figure 2 The distributions of bacterioplankton TRFs in
different experimental groups
图2 不同实验组中浮游细菌 TRFs 的分布状况
Note: Each color is on behalf of a specific TRF. M0–M10
represents different treatments.
注：不同的颜色代表不同片段长度的 TRFs；M0−M10 代表
不同的实验处理组.
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3.3 Six types: the selective effects of crude oil
on the bacterioplankton
In this study, selective effects of crude oil
concentrations on bacterioplankton were discovered.
Based on the relative ratio of a certain TRF among
different groups, the 52 different TRFs can be
divided into six types (I to VI, Figure 4). And the
characteristics of the six types were as follows
(Figure 4):
Type I: low concentrations of crude oil adapted
bacteria. After the oil pollution happened, relative
ratios of bacteria were higher in low concentrations of
oil than those in other concentrations, that is, type I
was more adaptive in low concentrations crude oil
seawater.
Type II: middle concentrations of crude oil
adapted bacteria. Bacterial relative proportions were
higher in moderate concentrations of oil than those in
other concentrations.
Type III: high concentrations of crude oil adapted
bacteria. Bacteria relative ratios were higher in high
concentrations of crude oil than those in other
concentrations.
Type IV: broad concentrations of crude oil
adapted bacteria. Their relative ratios were stable in
broad concentrations ranges of crude oil. Type IV
could exist in various degrees of oil pollutions with a
relative stable ratio.
Figure 3 NMDS plot of different experimental groups
图3 不同实验组的非参数多维尺度分析(NMDS)
Note: M0−M10: Experimental groups treated with different
concentrations of crude oil.
注：M0−M10：不同石油浓度处理的实验组.
Figure 4 The characteristics of six types (I to VI) in different concentrations of crude oil
图4 不同石油浓度实验组中“6 种类型”(I−VI)的分布特征
Note: M0−M10: Experimental groups treated with different concentrations of crude oil; Vertical coordinate: The relative ratios of
TRFs; Different lines: Different bacterial TRFs; Gray shades: The dominant concentration region of a certain type; I to VI in the
shadow mean six different types.
注：M0−M10：不同处理组；纵坐标：细菌 TRFs 的相对比例；不同颜色的线条：不同的细菌 TRFs；灰色阴影：某种类型的
优势浓度区间；I−VI：6种不同类型.
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Type V: narrow range concentrations of crude oil
(light, midrange or heavy) adapted bacteria. They
thrived in certain narrow range concentrations of
crude oil, and this type included some sub-types.
Type VI: crude oil sensitive bacteria. They
dominated in the environment without crude oil
pollution, and these bacteria disappeared or existed in
a state of very low abundance after oil pollution
happened.
In the present study, the type I had higher
proportions in the 0.1 g/L and 0.5 g/L crude oil
concentrations than those in other concentrations
(Figure 4A). Relative ratios of the type II were higher
in 0.5 g/L and 2.5 g/L crude oil concentrations than
those in other groups (Figure 4B). The type III was more
dominant in higher concentrations crude oil (2.5 g/L and
10 g/L) (Figure 4C). The type IV were relative
abundant and stable in all concentrations (Figure 4D).
The type V were those narrow range crude oil
concentration adapted bacteria which could be
detected only in a narrow range of crude oil
concentration, so this group included 0.1 g/L crude oil
adapted bacteria (V-0.1), 2.5 g/L adapted bacteria
(V-2.5) and 10 g/L adapted bacteria (V-10) (Figure
4E). And the type VI were found only in original
environment and disappeared after crude oil pollution
happened (Figure 4F). The type VI owned the most
TRFs (13 TRFs), and the fact indicated that a large
number of bacteria were not related to crude oil
degradation in the sampling site. In the bacteria
related to oil degradation, the type I and type III had
the most TRFs (10 TRFs, respectively), followed by
the sub-type V-0.1 (8 TRFs), V-10 (4 TRFs), sub-type
V-2.5 (3 TRFs), type II (3 TRFs), and type IV (1 TRF).
These results showed that bacteria adapted the low
concentrations (<0.5 g/L) and high concentrations
(>2.5 g/L) of crude oil exhibited the highest diversity,
the broad crude oil concentrations adapted bacteria
were very rare. In addition, some bacteria could be
only found in a narrow range of concentrations crude
oil, especially in low concentrations.
4 Discussion
4.1 The bacterioplankton related to crude oil
degradation
Hydrocarbon-degrading microorganisms usually
exist in very low abundance in marine environments[13].
Pollution by petroleum hydrocarbons, however, may
stimulate the growth of such organisms and cause
changes in the structure of microbial communities in
the contaminated area[14]. In our study, a consistent
trend was found that most bacterioplankton related
to crude oil degradation existed in a state of low
abundance in the original seawater (M0) and became
thriving after oil was added. Meanwhile, the
dominant TRFs (relative ratio >5%) related to crude
oil degradation were mainly affiliated to
Proteobacteria, Firmicutes and Bacteroidetes in our
study and this result was in accordance with the
previous result[9].
4.2 “Carbon & Energy sources-Toxicities”
hypothesis (“CE-T” hypothesis)
Previously, Röling and colleagues found that
bacterial diversity following addition of oil can be
dramatically reduced, and the result was owing to
strong selection for hydrocarbon-degrading species[15].
In our study, we found that bacterial diversity did not
simply reduce, but related to the concentrations of
crude oil. And the bacterioplankton could be divided
into six types following the crude oil concentrations.
About the comprehensive influences of crude oil on
bacterioplankton, although many studies have
examined the effect of crude oil pollution on bacterial
communities[9,16-17], theories or hypotheses to explain
the effects are still absent. In order to explain
comprehensive influences of crude oil on
bacterioplankton, based on our data and previous
studies, “Carbon & Energy sources-Toxicities”
hypothesis is proposed. The core ideas of the
hypothesis are as follows: crude oil is a two-sided
mixture due to the “increasing effect” on bacterial
abundance from “Carbon & Energy sources”
(hydrocarbons and other nutrients) and “decreasing
effect” from “Toxicities” (such as PAHs, heavy metals
etc.). Different concentrations of crude oil had
different selective effects on bacteria that led to six
types, and due to the two-sided selective effects of
crude oil, different types owned different high
efficient “carbon & energy sources” utilization
concentrations regions and different “toxicities”
tolerance concentrations regions.
4.3 “CE-T” hypothesis explains crude oil
pollution related microorganisms’ phenomena
Because of the “Carbon & Energy
832 微生物学通报 Microbiol. China 2015, Vol.42, No.5
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sources-Toxicities” effects, six types maybe have
different ranges of efficient “carbon & energy
sources” utilization concentration regions and
different regions of “toxicities” tolerance
concentrations. The intersection of two regions
determine whether a bacterium existing or dominant
in a oil polluted environment. In this research, the
intersection of type I concentrates in low
concentrations (0.1 g/L to 0.5 g/L crude oil), and the
“Toxicities” tolerance region might be the limiting
factor. The intersection of type II is mainly in range of
middle concentrations (0.5 g/L to 2.5 g/L). “Toxicities”
tolerance regions of type III and the type IV were very
broad (0.1 g/L to 10 g/L), but the high efficient “carbon
& energy sources” utilization concentrations regions
were different, the type III distributed mainly in high
concentrations (2.5 g/L to 10 g/L), while the type IV had
broad utilization region range from 0.1 g/L to 10 g/L.
The intersection for the type V concentrated in a
narrow range, so they could only thrive in some
specific concentration. The type VI could not
metabolize crude oil and be sensitive to toxicities, thus
they disappeared (under the detection line) when
crude oil pollution happened in seawater. After
clarifying the characteristics of the six types, it is easy
to understand the changing of bacterial diversity in our
study. Through the Figure 4, the richness of six types
was as follows: VI (13 TRFs)>I=III (10 TRFs)>V-0.1
(8 TRFs)>V-10 (4 TRFs)>II=V-2.5 (3 TRFs)>IV (1
TRFs). In the original seawater, some
bacterioplankton related to crude oil degradation
existed in a state of very low abundance. Without
pollution and relatively stable environment led to high
bacterial diversity be detected in M0 (mainly VI).
When crude oil was added, “increasing effect” from
“carbon & energy sources” and “decreasing effect”
from “toxicities” began to work. In the concentration
of 0.1 g/L, “toxicities” decreased some “crude oil
sensitive bacteria” (VI) and insufficient “carbon &
energy sources” could not support “middle and high
crude oil concentrations adapted bacteria” (II and III);
“increasing effect” mostly acted on the type I and
V-0.1, but due to the richness of six types in the
original seawater, “decreasing effect” was slightly
stronger and “comprehensive effect” was decreasing
of bacterial diversity (Table 2). Similarly, when the
concentration was up to 0.5 g/L, more “toxicities”
continuingly decreased the V-0.1, although “carbon &
energy sources” increased the II, due to the ratio of the
II was lower than the V-0.1, and “comprehensive
effect” was further decreasing (Table 2). In the 2.5 g/L
crude oil group, “carbon & energy sources” were
relatively sufficient, and “toxicities” were in the
tolerant range of bacteria (mainly II, III and V-2.5),
thus the bacterial diversity increased again. With the
concentrations reaching to 10 g/L, “Carbon & Energy
sources” were more sufficient, but the toxicities were
increasing continually which would make the diversity
or richness of the II and V-2.5 decrease, and bacterial
diversity decreased in 10 g/L group again (Table 2).
“CE-T” hypothesis not only can explain results in
this research, but also provide a way to understand
some phenomena related to crude oil pollution in
previous papers. Nayar et al. demonstrated that the
density of bacteria increased upon the addition of
crude oil at a concentration of about 0.001 g/L[18].
Based on “CE-T” hypothesis, at the concentration of
0.001 g/L, the “toxicities” might not be adequate to
decrease the diversity of bacteria in the original
environment, but the “carbon & energy sources” could
increase part of low abundance bacteria (mainly type I)
related to hydrocarbons metabolizing. Thus, the
comprehensive effect was increase of bacterial density.
Furthermore, some researchers have referred that
DMC (defined mixed culture) could enhanced the
capabilities of crude oil degradation[19-20]. But
systematic theories or hypothesis were rarely proposed
Table 2 Effects of “CE-T” hypothesis in different
treatments
表2 “碳(能)源-毒素”假说在各处理组中的作用效应
Concentrations
石油浓度(g/L)
Increase
增加效应 Decrease
减少效应
Comprehensive
综合效应
0.1 (I&V–0.1)↑(VI&II&III)↓ ↓
0.5 (II)↑ (V-0.1)↓ ↓
2.5 (II&III&V–
2.5)↑ (I)↓ ↑
10.0 (III)↑ (II&V–2.5)↓ ↓
Note: ↑: “Increasing effect” of crude oil makes some types
being detected; ↓: “Decreasing effect” of crude oil makes some
types becoming under the detection line; I−VI: The six types (I
to VI).
注：↑：石油对某些类型细菌的“促进效应”，使其在生境中
相对比例增加；↓：石油对某些类型细菌的“抑制效应”，使其
在生境中相对比例降低；I–VI：所划分的 6种不同类型细菌.
WEI Guang-Shan et al. New findings in effect of different crude oil… 833
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to explain the fact. Through the “CE-T” hypothesis,
different types of bacteria with different “carbon &
energy sources” utilization abilities and “toxicities”
tolerance abilities should be contained in the DMC. It
would allow different types of bacteria to play critical
roles in different degrading stages. Therefore, DMC
could enhance biodegrading capabilities of oil. In
addition, some phenomena in other related studies
could also be given good explanations through the
“CE-T” hypothesis[8,21-22].
4.4 Comparison of the “CE-T” hypothesis and
the “intermediate disturbance hypothesis”
The conception of “intermediate disturbance
hypothesis” (IDH) was presented by Connell[23], and
the IDH demonstrated that diversity of competing
species is, or should be expected to be, maximized at
intermediate frequencies and/or intensities of
disturbance or environmental change[24]. The IDH was
a very universal hypothesis in ecology in the past
years, and ecologists had tested the hypothesis for a
variety of taxa in a number of different
environments[25-27]. However, in a recent review paper,
Fox argued that the IDH has been refuted on both
empirical and theoretical grounds, and so should be
abandoned[24]. The “CE-T” hypothesis is different
from the IDH mainly in two aspects. On one hand, the
concerned periods and aims are different. The IDH
aims to predict the diversity-disturbance relationship
in a long-time community succession, while the
“CE-T” hypothesis focuses on the short-time effects of
oil pollutions on the microorganism community. We
aim to explain not to predict the behaviors of bacteria
after oil spills accidents happening. On the other hand,
the disturbance factor is special in our study. Crude oil
not only has disturbance effect on bacteria from PAHs
etc., but also has promoting effect on bacteria’s
growth due to carbon sources etc. The “CE-T”
hypothesis gives a good perspective on explaining the
effects of crude oil accidents on microorganism
community. Although it is difficult to predict the oil
pollution and bacteria diversity relationship, it points
out the possibility and universality of the six types in
all water columns, and the prediction will become
available after deducing the proportions of six types
through our experiments. Finally, does the bacterial
communities in other environments (soil, freshwater
etc.) responding to crude oil pollution exhibit similar
changing trend with our results? Are the six types
really common in a large scale of environments? And
as a hypothesis, different environments and larger
scales samples need to be studied to confirm the
“CE-T” hypothesis in the future.
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