yin2017

Chemosphere 171 (2017) 118e125
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Chemosphere
journal homepage: www.elsevier.com/locate/chemosphere
Effects of multiple antibiotics exposure on denitrification process in
the Yangtze Estuary sediments
Guoyu Yin a, b, Lijun Hou c, *, Min Liu a, b, Yanling Zheng a, b, Xiaofei Li a, b, Xianbiao Lin a, b,
Juan Gao c, Xiaofen Jiang c, Rong Wang c, Chendi Yu c
a
b
c
Key Laboratory of Geographic Information Science (Ministry of Education), East China Normal University, Shanghai, 200241, China
School of Geographic Sciences, East China Normal University, Shanghai, 200241, China
State Key Laboratory of Estuarine and Coastal Research, East China Normal University, Shanghai, 200062, China
h i g h l i g h t s
Multiple antibiotics exposure has synergistic inhibition on denitrification rates.
Different species of antibiotics have different effect on N2O release.
Combined effects of antibiotics lead to stimulation on N2O release.
Multiple antibiotics exposure inhibits the abundances of nirS and nosZ genes.
Different inhibition on nirS and nosZ may explain the variations of N2O release.
a r t i c l e i n f o
a b s t r a c t
Article history:
Received 10 September 2016
Received in revised form
31 October 2016
Accepted 14 December 2016
Available online 18 December 2016
Denitrification is a dominant reactive nitrogen removal pathway in most estuarine and coastal ecosystems,
and plays a significant role in regulating N2O release. Although multiple antibiotics residues are widely
detected in aquatic environment, combined effects of antibiotics on denitrification remain indistinct. In this
work, 5 classes of antibiotics (sulfonamides, chloramphenicols, tetracyclines, macrolides, and fluoroquinolones) were selected to conduct orthogonal experiments in order to explore their combined effects
on denitrification. 15N-based denitrification and N2O release rates were determined in the orthogonal
experiments, while denitrifying functional genes were examined to illustrate the microbial mechanism of
the combined antibiotics effect. Denitrification rates were inhibited by antibiotics treatments, and synergistic inhibition effect was observed for multiple antibiotics exposure. Different classes of antibiotics had
different influence on N2O release rates, but multiple antibiotics exposure mostly led to stimulatory effect.
Abundances of denitrifying functional genes were inhibited by multiple antibiotics exposure due to the
antimicrobial properties, and different inhibition on denitrifiers may be the major mechanism for the
variations of N2O release rates. Combined effects of antibiotics on denitrification may lead to nitrate
retention and N2O release in estuarine and coastal ecosystems, and consequently cause cascading environmental problems, such as greenhouse effects and hyper-eutrophication.
© 2016 Elsevier Ltd. All rights reserved.
Handling Editor: Jian-Ying Hu
Keywords:
Denitrification
N2O
Antibiotics
Multiple exposure
Yangtze Estuary
1. Introduction
The loading of reactive nitrogen (mainly nitrate) has increased
significantly in the past few decades, as a result of human activities
(Cui et al., 2013; Galloway et al., 2008; Liu et al., 2013; Yin et al.,
2014a). A huge quantity of this reactive nitrogen, however, has
* Corresponding author.
E-mail address: [email protected] (L. Hou).
http://dx.doi.org/10.1016/j.chemosphere.2016.12.068
0045-6535/© 2016 Elsevier Ltd. All rights reserved.
been transported into estuarine and coastal areas, consequently
leading to various environmental problems in these aquatic ecosystems (Burgin and Hamilton, 2007; Chen et al., 2016; Hou et al.,
2015; Seitzinger, 2008; Zheng et al., 2016). As the dominant microbial nitrogen removal pathway in most estuarine and coastal
ecosystems, denitrification has received much attention (Fernandes
et al., 2012; Gomez-Velez et al., 2015; Hou et al., 2014; Yin et al.,
2014a). Denitrification can mitigate eutrophication by eliminating
reactive nitrogen from aquatic ecosystems permanently in the form
of nitrogen gas (Deng et al., 2015; Devol, 2015; Hou et al., 2012; Yin
G. Yin et al. / Chemosphere 171 (2017) 118e125
et al., 2014a). Denitrification is also intimately related to N2O generation and consumption, as N2O is an intermediate product of
denitrification process (Dong et al., 2011; Hou et al., 2014; Yin et al.,
2016). The radiative forcing potential of N2O is approximately 4
times of CH4 and 200 times of CO2, thus it is considered to be a
major greenhouse gas affecting ozone depletion in atmospheric
environment (Ravishankara et al., 2009; Reay et al., 2012). Since
denitrification plays an important role in regulating eutrophication
and the release of greenhouse gas, an understanding of anthropogenic influence on denitrification process is of great importance
(Conley et al., 2009; Hou et al., 2014; Yin et al., 2014a).
Nowadays, up to 200,000 tons of antibiotics are used annually
around the world (Shi et al., 2014), due to the huge demand of
medical care, aquaculture, farming, and veterinary drug usage
(Looft et al., 2012; Yang et al., 2011; Zhang et al., 2015; Zhou et al.,
2013). Consistent antibiotics input leads to wide distribution and
occurrence of antibiotics residues in aquatic ecosystems
lez et al., 2015; Yan et al.,
(Kümmerer, 2009a; Moreno-Gonza
2013a), and antibiotics residues may disturb natural microbial
processes because of the antibacterial properties (Kümmerer,
2009b; Novo et al., 2013; Yan et al., 2013a). The effects of antibiotics on nitrate reduction processes have become an emerging topic
(Brandt et al., 2015; DeVries and Zhang, 2016; Roose-Amsaleg and
Laverman, 2015), and several recent studies have been operated to
investigate the antibiotics influence on denitrification process
(DeVries et al., 2015; Hou et al., 2014; Yan et al., 2013b; Yin et al.,
2016). However, these studies are mostly carried out with single
antibiotic exposure. Actually, multiple antibiotics occurrence is
widely detected in aquatic ecosystems (Chen and Zhou, 2014; Looft
et al., 2012; Yan et al., 2013a; Zhao et al., 2015). Combined effects of
multiple antibiotics exposure may disturb N2O release and nitrate
reduction in denitrification process, thus leading to various environmental problems, such as greenhouse effect and eutrophication
(Canfield et al., 2010; Deegan et al., 2012; Ravishankara et al., 2009;
Reay et al., 2012). Therefore, study of combined effects of antibiotics
on denitrification is required to give a further understanding of
reactive nitrogen and antibiotics pollution control (DeVries and
Zhang, 2016; Roose-Amsaleg and Laverman, 2015).
The Yangtze Estuary, one of the most heavily populated and
industrialized estuarine and coastal regions in China (Deng et al.,
2015), was selected as the study area. Consistent inputs of industrial and domestic sewage lead to sustained antibiotics residues and
hyper-eutrophication in this area (Chen et al., 2016; Yan et al.,
2013a). The most widely detected antibiotics residues in the
Yangtze Estuary are sulfonamides, chloramphenicols, tetracyclines,
macrolides, and fluoroquinolones (Chen and Zhou, 2014; Yan et al.,
2013a; Zhang et al., 2015; Zhao et al., 2015), thus sulfamethazine
(SMT), thiamphenicol (TAP), oxytetracycline (OTC), erythromycin
(ERY), and norfloxacin (NOR) were selected to represent the five
classes of these antibiotics, respectively. In this work, orthogonal
experiments were employed to illustrate the combined effects of
antibiotics on denitrification and N2O release rates, and abundances of denitrifying functional genes were also detected to
investigate the microbial mechanisms of multiple antibiotics
exposure at genic level. This work provides more realistic data for
the understanding of denitrification process responding to multiple
antibiotics exposure in aquatics ecosystems, which may help to
control the pollution of both reactive nitrogen and antibiotics.
2. Materials and methods
2.1. Sampling and pretreatment
Box corers were used to collect surface sediments (0e5 cm)
from the intertidal zone of the Yangtze Estuary in December 2015
119
(Fig. S1, Supporting Information). The sediment samples were
transported to the laboratory within 2 h. A pre-incubation was
conducted to eliminate ambient antibiotics in the sediment samples in order to resemble a pristine status. Briefly, the sediment
corers were pre-incubated at room temperature (25 C) in a recirculating glass container which was filled with artificial seawater
having near in situ nutrient levels and salinity (Yin et al., 2016). The
pre-incubation experiment lasted for about 2 months. After the
pre-incubation, the sediments were extracted and the antibiotics
concentrations were examined to confirm that no antibiotics residuals were left (Shi et al., 2014; Yan et al., 2013a). Subsequently,
the sediment samples were used for the slurry experiments and
functional gene abundance measurements.
2.2. Orthogonal experimental design
The L16 (45) orthogonal experiment was applied to study the
effects of multiple antibiotics exposure on denitrification rates. Five
antibiotics (SMT, TAP, OTC, ERY, and NOR) were designated as five
influence factors to represent the most widespread antibiotics
residues in the study area (Chen and Zhou, 2014; Shi et al., 2014;
Yan et al., 2013a). Four concentration levels were applied for each
antibiotic, which were specifically assigned as 0, minimum concentration detected, average concentration detected, and
maximum concentration detected in both estuarine water and
sediments of the study area (Chen and Zhou, 2014; Yan et al., 2013a;
Zhao et al., 2015). Detailed information on antibiotics concentrations and assignments in the orthogonal experimental design is
exhibited in Table S1 (Supporting Information). Range analysis was
conducted to make a brief description of different antibiotics influence. K value and Rj value were defined in the range analysis as
two parameters. K value is referred to as the average value of each
result at the same antibiotic concentration. Rj value is referred to as
subtracting the minimum K value from the maximum K value in
each antibiotic group. A large Rj value means a great influence of
the antibiotic (Shen et al., 2016). Analysis of variance was also done
to examine the significance of antibiotics influence (Yang et al.,
2014).
2.3. Slurry experiments
The surface sediment samples were homogenized with artificial
seawater having near in situ salinity at a ratio of 1:7 (Hou et al.,
2014). The slurries were purged with helium and stirred vigorously for 15 min (Hou et al., 2013). The mixed slurries were filled
into respective 12 mL gas-tight vials (Exetainer, Labco, High
Wycombe, UK), and then the vials were sealed with butyl-rubber
septa and screw caps. A 24-h pre-incubation was operated to
eliminate the background nitrate/nitrite (Hou et al., 2014). After the
pre-incubation, the vials were spiked with 15NO
3 (final concentration ca. 100 mmol L1, final % 15N ca. 90e99%) (Hou et al., 2012).
Meanwhile, solutions of selected antibiotics were injected into the
respective vials following the orthogonal experimental design. An
initial group was designated for each trial and preserved with
250 ml 50% ZnCl2 solution (Yin et al., 2016), and 8 replicates were
prepared for each group. The slurries were incubated for 8 h at
room temperature on a shaker table (200 rpm) (Hou et al., 2012).
After the incubation, replicates of all the groups were preserved
with ZnCl2 as described for the initial groups. Half of the replicates
in each group were used to analyze the dissolved nitrogen gases
(29N2 and 30N2) generated during the incubations by membrane
inlet mass spectrometry (HPR-40, Hiden Analytical, UK), with a
detection limit of 0.1 mmol L1 for N2 (Yin et al., 2014b). The denitrification rates were calculated according to the following equation (Hou et al., 2014):
120
G. Yin et al. / Chemosphere 171 (2017) 118e125
RD ¼ N30 2 ð1 Fn Þ Fn1 þ 2 N30
where RD (mmol 15N kg1 h1) represents the total 15NO
3 -based
rates of denitrification; N30 (mmol 30N2 kg1 h1) represents the
measured generation rates of 30N2 derived from 15NO
3 during the
incubation; Fn (%) represents the fraction of 15N in total NO
3 . The
remaining replicates were used to measure dissolved N2O using gas
chromatography with a detection limit of 0.001 mmol L1 (Shimadzu GC-14B, Shimadzu Co., Kyoto, Japan) (Yin et al., 2016). N2O
release rates were calculated using headspace equilibrium technique (Hinshaw and Dahlgren, 2013) with the following equation
(Hou et al., 2014):
RN ¼ Tf Ti V H1
where RN (mmol kg1 h1) means the N2O release rates; Ti and Tf
(mmol mL1) mean the measured contents of dissolved N2O in the
initial and final samples, respectively; H (h) means the incubation
time; V (mL) is the volume of the gas-tight vials.
2.4. Molecular microbial analysis
The incubated sediment slurries were collected to analyze
functional gene abundances of denitrifiers. The nirS gene encoding
for nitrite reductase and the nosZ gene encoding for nitrous oxide
reductase were quantified to illustrate the combined effects of
antibiotics on the denitrifying microbes (Black et al., 2016; Kandeler
et al., 2006). The total DNA extraction in the sediment samples were
conducted using Powersoil™ DNA Isolation Kits (MO BIO, USA),
according to the instructions of manufacturer. The abundances of
nirS and nosZ genes in the extracted DNA were determined via realtime quantitative PCR assays. The nirS gene (nitrite reductase)
fragments in the extracted DNA were amplified with primers R3cd
(50 -GAS TTC GGR TGS GTC TTG A- 30 ) and cd3aF (50 -GTS AAC GTS
€ck et al., 2004).
AAG GAR ACS GG- 30 ) (Michotey et al., 2000; Throba
The nosZ gene (nitrous oxide reductase) fragments were amplified
with primers nosZ2R (50 -CAK RTG CAK SGC RTG GCA GAA- 30 ) and
nosZ2F (50 -CGC RAC GGC AAS AAG GTS MSS GT- 30 ) (Jones et al.,
2013). The gene copy numbers of nirS and nosZ were quantified
in quadruplicate using the SYBR green qPCR method with an ABI
7500 Sequence Detection System (Applied Biosystems, Canada).
The qPCR systems contained 12.5 mL of Maxima SYBR Green/Rox
qPCR Master Mix (Fermentas, Lithuania), 1 mL of template DNA, 1 mL
of each primer (10 mmol L1, Sangon, China), and 10.5 mL of sterile
ddH2O. The qPCR reactions were performed with the thermal
cycling conditions of 2 min at 50 C, 10 min at 95 C, followed by 40
cycles of 30 s at 95 C, 1 min at 57 C for nirS, 60 C for nosZ, and
1 min at 72 C. Serial dilution of a known amount of plasmid DNA
containing the target fragment was conducted to build the standard
curves. Real-time qPCR consistency was confirmed by strong linear
relationships of the standard curves between the log10 values of
gene copy numbers and the threshold cycle (CT) (R2 ¼ 0.9953 for
nirS, and R2 ¼ 0.9976 for nosZ). Three negative controls with no
template DNA were prepared for all experiments in order to
exclude possible contamination. The abundances of nirS and nosZ
genes were calculated on the basis of the constructed standard
curve, and then converted and expressed as copies g1 dry
sediment.
2.5. Statistical analysis
An analysis of variance (ANOVA) was conducted in this study.
Statistical analyses were performed at the 95% confidence level
(alpha ¼ 0.05) to determine whether the changes in the measured
data were statistically significant. The Statistical Package of Social
Sciences (SPSS, version-22.0) was used to perform all statistical
analyses.
3. Results
3.1. Denitrification rates
Rates of denitrification ranged from 6.87 to 12.32 mmol 15N kg1
h in the 16 trials of the orthogonal experiment (Table 1). Due to
the addition of antibiotics, the denitrification rates decreased by
44.2%. The maximum denitrification rate was observed in trial 1,
which was a blank group without antibiotics addition, while the
minimum rate was found in trial 4. Based on the range analysis
(Table 2), TAP had greater inhibition on denitrification rates than
the other antibiotics (Rj ¼ 1.682), whereas ERY had the smallest
inhibition effect (Rj ¼ 0.940). Denitrification rates were inhibited
significantly by all the 5 antibiotics (one-way ANOVA, p < 0.05)
(Table 3), however, they were observed to be slightly stimulated by
the minimum concentration of ERY (0.05 ng L1) (Fig. 1).
1
Table 1
Results of the L16 (45) orthogonal experiment. RD represents the total 15NO
3 -based denitrification rates; RN represents the N2O release rates; nirS gene and nosZ gene represent
the abundances of nirS gene and nosZ gene.
Trials
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
SMT
(ng L1)
TAP
(ng L1)
OTC
(ng L1)
NOR
(ng L1)
ERY
(ng L1)
RD
(mmol
0
0
0
0
0.53
0.53
0.53
0.53
47.6
47.6
47.6
47.6
89.1
89.1
89.1
89.1
0
0.91
62.9
110
0
0.91
62.9
110
0
0.91
62.9
110
0
0.91
62.9
110
0
5.13
11.6
22.5
5.13
0
22.5
11.6
11.6
22.5
0
5.13
22.5
11.6
5.13
0
0
0.2
2.6
14.2
2.6
14.2
0
0.2
14.2
2.6
0.2
0
0.2
0
14.2
2.6
0
0.05
9.68
45.4
45.4
9.68
0.05
0
0.05
0
45.4
9.68
9.68
45.4
0
0.05
12.32 ± 0.2
10.18 ± 1.0
8.66 ± 0.9
6.87 ± 0.2
9.13 ± 0.5
8.42 ± 0.6
8.77 ± 1.1
8.79 ± 0.6
8.94 ± 0.9
7.61 ± 0.2
8.80 ± 0.6
7.58 ± 0.5
8.53 ± 0.6
8.32 ± 0.7
8.16 ± 0.2
8.95 ± 0.1
15
N kg1 h1)
RN
(mmol kg1 h1)
0.070
0.063
0.081
0.111
0.069
0.061
0.165
0.118
0.125
0.168
0.201
0.202
0.269
0.334
0.187
0.287
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
0.02
0.02
0.05
0.05
0.04
0.02
0.06
0.02
0.05
0.03
0.03
0.03
0.08
0.05
0.02
0.04
nirS gene
(108 copies g1)
2.86
2.23
2.57
1.62
2.19
2.35
2.24
2.12
2.14
1.91
2.21
2.09
1.82
2.29
2.02
1.87
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
0.3
0.2
0.2
0.2
0.1
0.4
0.1
0.2
0.2
0.3
0.2
0.3
0.1
0.1
0.4
0.2
nosZ gene
(107 copies g1)
8.82
7.71
7.60
6.20
7.65
6.97
6.69
6.63
6.27
6.51
6.38
5.75
5.83
6.18
6.26
6.04
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
±
0.2
0.3
0.3
0.3
0.5
0.6
0.3
0.2
0.2
0.3
0.2
0.2
0.2
0.4
0.2
0.2
G. Yin et al. / Chemosphere 171 (2017) 118e125
121
Table 2
The basic range analysis data of the L16 (45) orthogonal experiment. RD represents
the total 15NO
3 -based denitrification rates; RN represents the N2O release rates; nirS
gene and nosZ gene represent the abundances of nirS gene and nosZ gene. K1, K2, K3,
and K4 represent the average value of each result at the same antibiotic
concentration.
Result
K value
SMT
TAP
OTC
NOR
ERY
RD
K1
K2
K3
K4
Rj
K1
K2
K3
K4
Rj
K1
K2
K3
K4
Rj
K1
K2
K3
K4
Rj
9.508
8.778
8.232
8.490
1.276
0.081
0.103
0.174
0.269
0.188
2.320
2.225
2.088
2.000
0.320
7.582
6.985
6.228
6.078
1.504
9.730
8.632
8.598
8.048
1.682
0.133
0.156
0.158
0.180
0.046
2.252
2.195
2.260
1.925
0.327
7.142
6.842
6.732
6.155
0.987
9.622
8.762
8.678
7.945
1.677
0.155
0.130
0.164
0.178
0.048
2.322
2.132
2.280
1.897
0.425
7.052
6.842
6.670
6.307
0.745
9.248
9.075
8.588
8.098
1.150
0.193
0.163
0.151
0.121
0.072
2.370
2.095
2.135
2.032
0.338
6.860
6.638
6.950
6.425
0.525
9.220
9.230
8.298
8.280
0.940
0.136
0.160
0.153
0.179
0.043
2.228
2.120
2.208
2.078
0.150
7.055
6.678
6.538
6.602
0.517
RN
nirS gene
nosZ gene
Fig. 1. Relationship between denitrification rates (RD) and concentrations of different
antibiotics. min, ave, and max in the horizontal axis stand for minimum concentration
detected, average concentration detected, and maximum concentration detected of
each antibiotic, respectively.
down the N2O release rates by 37.3%. TAP, OTC, and ERY accelerated
the N2O release rates slightly (Fig. 2), but the stimulation was not
significant (one-way ANOVA, p > 0.05).
3.2. N2O production
N2O release rates ranged from 0.06 to 0.33 mmol kg1 h1 in the
orthogonal experiment trials (Table 1). Compared to the blank
group (trial 1), the release rates of N2O were stimulated in most
trials (except for trials 2, 5, and 6). Range analysis showed that SMT
(Rj ¼ 0.188) and NOR (Rj ¼ 0.072) had a greater influence on N2O
release rates than TAP, OTC, and ERY (Table 2). N2O release rates
were accelerated significantly by SMT (one-way ANOVA, p < 0.05),
and the minimum concentration of SMT (0.53 ng L1) led to a 27.2%
increase of the N2O release rates (Table 3). On the contrary, NOR
inhibited N2O release rates significantly (one-way ANOVA,
p < 0.05), and the maximum concentration of NOR (14.2 ng L1) cut
3.3. Q-PCR of denitrifying functional genes
Abundances of denitrifying functional genes in the incubated
sediments of the orthogonal experiment were quantified. The
abundances of nirS and nosZ genes ranged from 1.62 108 to
2.86 108 copies g1 and from 5.75 107 to 8.82 107 copies g1
in the 16 trials, respectively (Table 1). Compared to the blank group
(trial 1), the abundances of nirS and nosZ genes in the other trials
were all inhibited by the addition of antibiotics. Range analysis
indicated that OTC (Rj ¼ 0.425) and SMT (Rj ¼ 1.504) had the
greatest inhibition effect on the abundances of nirS genes and nosZ
genes, respectively (Table 2). On the other hand, ERY had the
Table 3
The analysis of variance (ANOVA) data of the L16 (45) orthogonal experiment. RD
represents the total 15NO
3 -based denitrification rates; RN represents the N2O release
rates; nirS gene and nosZ gene represent the abundances of nirS gene and nosZ gene.
SUM ¼ sum of square; df ¼ degree of freedom; MS ¼ mean of square; p < 0.05 means
changes in the measured data were statistically significant at the 95% confidence
level.
Result
Antibiotic
SUM
df
MS
F value
p value
RD
SMT
TAP
OTC
NOR
ERY
SMT
TAP
OTC
NOR
ERY
SMT
TAP
OTC
NOR
ERY
SMT
TAP
OTC
NOR
ERY
14.559
23.855
22.635
12.884
13.730
0.344
0.017
0.020
0.042
0.015
0.948
1.186
1.785
1.037
0.240
23.037
6.043
1.564
5.273
7.411
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
4.853
7.952
7.545
4.295
4.577
0.115
0.006
0.007
0.014
0.005
0.316
0.395
0.595
0.346
0.080
7.679
2.014
0.521
1.758
2.470
3.497
5.730
5.437
3.095
3.298
38.006
1.927
2.180
4.650
1.684
5.736
7.179
10.799
6.278
1.455
22.023
5.777
7.085
1.495
2.085
0.022
0.002
0.003
0.036
0.028
0.000
0.138
0.103
0.006
0.183
0.002
0.000
0.000
0.001
0.239
0.000
0.002
0.028
0.228
0.104
RN
nirS gene
nosZ gene
Fig. 2. Relationship between N2O release rates (RN) and concentrations of different
antibiotics. min, ave, and max in the horizontal axis stand for minimum concentration
detected, average concentration detected, and maximum concentration detected of
each antibiotic, respectively.
122
G. Yin et al. / Chemosphere 171 (2017) 118e125
Fig. 3. Relationship between abundances of nirS gene and concentrations of different
antibiotics. min, ave, and max in the horizontal axis stand for minimum concentration
detected, average concentration detected, and maximum concentration detected of
each antibiotic, respectively.
smallest influence on the abundances of both nirS and nosZ genes
(Rj ¼ 0.150 and 0.517, respectively). SMT, TAP, and OTC inhibited
both nirS and nosZ genes significantly (one-way ANOVA, p < 0.05),
and NOR only had significant inhibition on nirS genes (Table 3).
Though a slight inhibition effect was observed for ERY on both nirS
and nosZ genes (Fig. 3 and Fig. 4), the inhibition was not significant
(one-way ANOVA, p > 0.05).
4. Discussion
4.1. Antibiotics influence on denitrification rates
The denitrification rates were inhibited significantly by all the 5
antibiotics used in this study, as the metabolism of denitrifying
bacteria can be inhibited by antibiotics (Conkle and White, 2012;
Yan et al., 2013a). According to our previous study, denitrification
rates were reduced approximately 30% by 500 ng L1 SMT and
1000 ng L1 TAP, respectively (Hou et al., 2014; Yin et al., 2016). In
this study, the total concentrations of antibiotics were no more than
300 ng L1 in all the 16 trials. However, denitrification rates were
cut down by up to 44.2% in the orthogonal experiment, implying
that multiple antibiotics exposure may lead to greater inhibition
effect on denitrification rates. The inhibition of single SMT exposure
on denitrification rates has an upper limit (Hou et al., 2014), as
denitrifying bacteria may harbor sulfonamide resistance genes
(Hou et al., 2014; Kotzerke et al., 2008). The inhibition effect of
average SMT concentration (47.6 ng L1) and maximum SMT concentration (89.1 ng L1) on denitrification rates resembled each
other (Table 2), as they both reached the upper limit. However,
multiple antibiotics exposure may decrease the overall antibiotics
resistance of the denitrifying bacteria community (Chait et al.,
2007). The resistance to a single antibiotic may remove the suppression effect among the antibiotics, which could explain the
greater inhibition effect of multiple antibiotics exposure (Ding and
He, 2010). Synergistic effects of both OTC and ERY on aquatic microorganisms have been reported (Christensen et al., 2006), and the
synergy and additivity among different antibiotics on denitrifying
bacteria could be another reason of the greater inhibition effect.
Range analysis showed that TAP had the greatest inhibition effect
on denitrification rates among the 5 antibiotics. As the average and
maximum concentrations of TAP detected in the study area were
generally higher than the other antibiotics, the greatest inhibition
effect may be caused by dosage effect (Basarab et al., 2015). On the
contrary, the concentrations of OTC were much lower than TAP, but
the inhibition effect was nearly at the same level (Rj ¼ 1.682 for TAP,
Rj ¼ 1.677 for OTC). The distribution coefficient (Kd value) of OTC
was much larger than that of TAP, which indicated that OTC was
more likely to be combined with sediment (Chen et al., 2015; Xu
et al., 2009). OTC and TAP both inhibit the protein synthesis and
the related enzyme activities (Evaggelopoulou and Samanidou,
2013). The higher combination with sediment makes OTC more
exposed to the denitrifying bacteria community, which may lead to
a higher inhibition efficiency of OTC than TAP. Antibacterial properties of ERY can be suppressed by the presence of chloramphenicols (Chakraborty et al., 2014), thus ERY had the smallest inhibition
effect on denitrification rates. However, the antagonism between
ERY and TAP did not mitigate the total synergistic effect of multiple
antibiotics exposure. The minimum concentration of ERY
(0.05 ng L1) slightly stimulated the denitrification rates, which
may be caused by the hormesis effect of ultra-low dose antibiotics
exposure (Calabrese and Baldwin, 2003; Deng et al., 2012). Relationship of ultra-low dose stimulation and high-dose inhibition has
been demonstrated to be highly generalizable for several classes of
antibiotics (Deng et al., 2012). However, it is not easy to be observed
under environmental concentrations of antibiotics, as the multiple
exposure of antibiotics mostly leads to concentrations far beyond
the ultra-low dose in estuarine and coastal regions (Chen and Zhou,
2014; Yan et al., 2013a). Stimulatory effect of sulfonamides on
denitrification under ultra-low dose exposure has also been reported recently (DeVries et al., 2015). Combined effects of multiple
antibiotics exposure lead to greater inhibition on denitrification
rates, which may cause the retention of excessive reactive nitrogen,
and further contribute to hyper-eutrophication in estuarine and
coastal ecosystems.
4.2. Antibiotics influence on N2O release
Fig. 4. Relationship between abundances of nosZ gene and concentrations of different
antibiotics. min, ave, and max in the horizontal axis stand for minimum concentration
detected, average concentration detected, and maximum concentration detected of
each antibiotic, respectively.
N2O release rates were significantly stimulated by SMT and
inhibited by NOR, while no significant influence was observed for
TAP, OTC, and ERY. Although different influence of antibiotics on
N2O release rates was detected, the combination of multiple
G. Yin et al. / Chemosphere 171 (2017) 118e125
antibiotics resulted in stimulatory effect in the orthogonal experiment trials. The stimulation of SMT was much greater than the
inhibition of NOR, thus only in trials 2, 5, and 6 the N2O release rates
were lower than the blank group (trial 1), where the concentrations
of SMT were quite low. SMT single exposure has also been reported
to stimulate N2O release rates, which can be explained by the
different inhibition effect between N2O generation and N2O
reduction to N2 (Hou et al., 2014). The stimulation was not affected
by multiple antibiotics exposure, as SMT inhibits the synthesis of
folic acid, which is a quite different antibacterial mechanism from
other classes of antibiotics (Hou et al., 2014). NOR may also have
different inhibition on N2O generation and N2O reduction to N2
procedures, but the effect is opposite to SMT. NOR inhibits DNA
replication in microorganisms (Cheng et al., 2013), the disparate
antibacterial mechanism may lead to a stronger inhibition on N2O
generation than N2O reduction to N2, and eventually cause the
inhibition on N2O release rates. Single exposure of TAP has been
recently reported to stimulate N2O release rates (Yin et al., 2016),
but no significant influence of TAP on N2O release rates was found
in this study. TAP and ERY both inhibit the protein synthesis and the
related enzyme activities of denitrifying bacteria (Evaggelopoulou
and Samanidou, 2013). The antagonism between TAP and ERY
may be the main factor causing no significant influence of both TAP
and ERY on N2O release rates (Chakraborty et al., 2014). Though
different classes of antibiotics have different influence on N2O
release rates, the multiple antibiotics exposure mostly leads to
stimulatory effect. Multiple antibiotics residues can be a fatal factor
of increasing N2O release in estuarine and coastal ecosystems,
which may contribute to ozone depletion and greenhouse effects in
the atmosphere (Ravishankara et al., 2009; Reay et al., 2012).
4.3. Microbial mechanisms of antibiotics influence
Nitrite reduction and N2O reduction to N2 are key steps involved
in denitrification process (Pan et al., 2013), thus the abundances of
nirS and nosZ genes were quantified to investigate the microbial
mechanisms of multiple antibiotics exposure in this work.
Compared to the blank group (trial 1), the abundances of nirS and
nosZ genes were all inhibited by antibiotics treatments in the other
orthogonal experiment trials, due to the antimicrobial properties of
antibiotics (Conkle and White, 2012; Yan et al., 2013a). OTC had the
greatest inhibition effect on nirS genes according to the range
analysis, demonstrating that OTC has a higher inhibition efficiency
on denitrification than other antibiotics used in this study. OTC has
a higher tendency to combine with sediment (Chen et al., 2015; Xu
et al., 2009), which may lead to a greater inhibition on nitrite
reductase, and eventually cause a higher inhibition efficiency on
denitrification rates. OTC also inhibited nosZ genes significantly,
and the inhibition effect may resemble that on nirS genes, which
may explain why OTC had no significant influence on N2O release
rates. Range analysis showed that SMT had the greatest influence
on nosZ genes, and inhibited the abundances of nosZ genes significantly. The greatest inhibition effect on nosZ genes may be the
main factor leading to the N2O accumulation during the incubation,
as the N2O reduction to N2 step was inhibited by SMT. Similar
mechanism has been reported in single SMT exposure assays,
where N2O release rates were also stimulated by SMT treatment
(Hou et al., 2014). NOR inhibited nirS genes significantly, but had no
significant influence on nosZ genes. That means that N2O generation was inhibited significantly by NOR, while no significant influence was observed on the N2O reduction to N2 step. Therefore, N2O
release rates were significantly inhibited by NOR. NOR has also
been reported to inhibit N2O generation in sewage treatment plant
123
(Costanzo et al., 2005). Antibacterial properties of ERY were suppressed by the presence of TAP (Chakraborty et al., 2014), thus ERY
had no significant influence on both nirS genes and nosZ genes.
Single TAP exposure has been reported to stimulate N2O release
rates due to the different inhibition on denitrifying functional genes
(Yin et al., 2016), but both TAP and ERY had no significant influence
on N2O release rates in this study. The antagonistic effect between
TAP and ERY may disturb their inhibition effects on nirS genes and
nosZ genes, which could be the major mechanism causing no significant influence on N2O release rates. Multiple antibiotics exposure leads to various effects on denitrifying functional genes, and
subsequently affects denitrification rates and N2O release rates
dissimilarly.
5. Conclusions
This work demonstrates that multiple antibiotics exposure is
intimately related to denitrification rates and associated N2O
release rates in estuarine and coastal sediments. Denitrification
rates are inhibited by antibiotics treatments, and multiple antibiotics exposure leads to a synergistic inhibition effect. OTC has the
highest inhibition efficiency on denitrification rates, and hormesis
effect of ultra-low dose ERY exposure may be detected. N2O release
rates are stimulated by SMT and inhibited by NOR, and multiple
antibiotics exposure mostly leads to stimulatory effect. Antibiotics
exposure inhibits the growth of denitrifying bacteria due to the
antimicrobial properties, and different inhibition on denitrifying
functional genes may be the major mechanism for the variations of
N2O release rates. The interaction among different classes of antibiotics may create shifts of inhibition on denitrifying functional
genes, and lead to different effects compared with single antibiotic
exposure. The combined effects of antibiotics may cause reactive
nitrogen retention and enhanced N2O release, thus contributing to
environmental problems in estuarine and coastal regions.
Acknowledgements
This work was funded by National Natural Science Foundations
of China (Nos. 41071135, 41130525, 41271114, 41322002 and
41501524), National key research and development program
(2016YFA0600904), and China Postdoctoral Science Foundation
(2015M571522). The State Key Laboratory of Estuarine and Coastal
Research and the Program for New Century Excellent Talents in
University (NCET) also supported this study.
Appendix A. Supplementary data
Supplementary data related to this article can be found at http://
dx.doi.org/10.1016/j.chemosphere.2016.12.068.
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