Environ Earth Sci (2015) 73:5085–5094 DOI 10.1007/s12665-015-4021-7
THEMATIC ISSUE
Spatial distribution and diversity of microbial community in large-scale constructed wetland of the Liao River Conservation Area Erquan Zhi • Yonghui Song • Liang Duan Huibin Yu • Jianfeng Peng
•
Received: 16 September 2014 / Accepted: 3 January 2015 / Published online: 13 January 2015 Ó Springer-Verlag Berlin Heidelberg 2015
Abstract Microbial communities play a key role in wetland water purification and nitrogen cycling. The spatial distribution and diversity of total bacteria in large-scale constructed wetland were investigated by polymerase chain reaction-denaturing gradient gel electrophoresis. The abundance of nitrogen related functional bacteria were measured by real-time PCR using specific primers. The results showed that the diversity of total bacterial community decreased from the inlet zone (Shannon–Wiener index, H0 = 3.471) to the outlet zone (H0 = 2.566), so did the species richness and evenness. The dominant bacteria of the wetland were Proteobacteria, Acidobacteria and Bacilli. The abundance of amoA gene was higher than those of another two functional genes. There was significant correlation between the abundance of amoA gene and pH (r = 0.852), DO (r = -0.595), NH4? (r = 0.595) and NO3- (r = 0.726) concentrations. The abundance of nosZ gene correlated with the DOC concentration (r = -0.614). The ratio of amoA/Nitrospira showed significant correlation with NH4? concentration (r = 0.641), while the ratios of amoA/nosZ (r = -0.801) and Nitrospia/nosZ (r = -0.610) could reflect the NO2- concentrations. Therefore, the three ratios of nitrogen related functional genes may
E. Zhi Y. Song (&) L. Duan (&) H. Yu J. Peng State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China e-mail:
[email protected] L. Duan e-mail:
[email protected] E. Zhi Y. Song L. Duan H. Yu J. Peng Department of Urban Water Environmental Research, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
serve as new biological indicators for wetland condition assessment. Keywords Constructed wetland Total bacteria Nitrifier Denitrifier Biological indicators
Introduction Wetlands have been widely studied and subsequently identified as highly efficient ecosystems, with respect to nutrient control (Chon et al. 2011). Constructed wetland has also been studied to efficiently control organics, nutrients and heavy metals of either agricultural discharged water or wastewater treatment plants’ effluents. The tributary estuarine wetland is a unique ecosystem that plays a significant buffering role in the transport of nitrogen from agricultural and other terrestrial-anthropogenic sources into the mainstream (Feng et al. 2014). It is not only related to biodiversity but also connect to water quality improvement. Although the wetland function relies on the properties of hydrology, vegetation and soil, microbial communities are particularly important to biogeochemical processes in wetlands. The microbial composition and abundance in the wetland environment are critical to nutrient cycling for maintaining healthy ecological functions (Sims et al. 2012a; Ahn et al. 2007). In tributary estuarine sediments, microbial driven processes may lead to a transformation and net removal of nitrogen from the environment (Quan et al. 2010). Thus, it is crucial to understand the associations between the microbial community composition and the environmental parameters affecting these ecosystems. Increased anthropogenic nitrogen loads have led to a strong deterioration of water quality worldwide, causing hypoxia, excessive growth of plants and algae, biodiversity
123
5086
loss and fish-kills. Biological nitrogen removal through nitrification and denitrification is one of the most important functions of wetlands. During last decade, modern molecular-based techniques have been successfully used to study microbial community structure and diversity of wetlands. Denaturing gradient gel electrophoresis (DGGE) has been applied to study the spatial variations of denitrifying community structure in a treatment wetland and the results have indicated that DGGE was a viable tool to study microbial diversity in environmental samples (Kjellin et al. 2007). Real-time PCR has also been successfully used to quantify the seasonal population changes of ammoniaoxidizing organisms in a constructed wetland (Sims et al. 2012a). However, most of the researches focused on either denitrifying genes (Chon et al. 2011; Ligi et al. 2013b) or ammonia-oxidizing organisms (Dong and Reddy 2012; Sims et al. 2012b). Previous researches have rarely taken both nitrifier and denitrifier into account as an integrate process of nitrogen removal. Little has been known about the distribution patterns and abundance of nitrogen transformation functional genes, and their indication effect of wetland ecosystem has not been evaluated. Our goal in this study was to: (1) investigate the bacterial community structure and biodiversity in large-scale constructed wetland; (2) quantify the abundance of total bacteria, AOB, NOB and denitrifers; (3) evaluate whether the nitrogen transformation functional gene abundance and their ratio could be used for wetland condition assessment.
Materials and methods Study area Liaohe River is located at the northeast of China (Fig. 1a). It is one of the seven largest rivers in the country. To consolidate the pollution control achievements of the Liao River mainstream and to achieve long-term goal of sustainable development, Liaoning Provincial Government designated the mainstream of Liao River as conservation area, which is the first conservation area for the management and protection of river in China. Currently, tributaries are the main pollutants source of the Liao River mainstream. Therefore, the constructed wetland in the tributary estuary was built to purify the tributary water and relieve the pollution load of mainstream. Wanquan River lies at the northern part of Shenyang City, capital city of Liaoning Province. It is a typical tributary river of Liao River, which is polluted by the industrial and agricultural wastewater from the large city. The constructed wetland has been built in 2009 and run for nearly 3 years. The total area of constructed wetland (N42°80 18.1700 – 42°80 48.6000 , E123°280 57.1300 –123°300 48.3600 ) is about 1.67 km2 (Fig. 1b) and the water storage capacity is about
123
Environ Earth Sci (2015) 73:5085–5094
2.5 9 106 m3. The hydraulic retention time (HRT) is 5–7 days. Sample collection and DNA extraction Twelve representative sample sites (black squares in Fig. 1b) were selected and labeled with 1–12 from upstream to downstream. Sites 1–3 represented the inlet part of Wanquan River. Sites 4 and 5 were two little ponds in the wetland. Sites 6, 7 and 9 were the center of wetland. Site 8 was a brooklet named Yangchang River. Sites 10–12 represented the outlet zone of wetland. As we know, the water environment is one of the most important factors which influence the spatial distribution and diversity of microbial community (Sims et al. 2012a; Ligi et al. 2013b). Thus, the samples were collected in April, 2012, the most polluted period with lowest water level of the year. Surface water samples (0–20 cm) were collected in clean glass bottles (10 % of nitric acid and Milli-Q rinsed) and kept on ice until back in laboratory (\6 h). Dissolved organic carbon (DOC) was measured using a TOC analyzer (Analytik jena multi N/C 3100 TOC, Germany). NH4? and NO3- were measured using the colorimetric method. Sediment samples (0–10 cm) were collected into sterile 50 mL centrifuge tubes and stored at -20 °C until further processing. Total genomic DNA was extracted from all samples using a QIAampÒ DNA Stool Mini Kit (Qiagen, Germany), following the manufacturer’s instructions. DNA quality was detected through agarose gel electrophoresis (1 %) which was stained with SYBRÒ Safe DNA Gel Stain (Invitrogen, USA). No additional purification procedure was required for any of the samples. PCR amplification The PCR was carried out in 50 lL using a DNA thermocycler (Eppendorf, Germany). The PCR mixture contained 25 lL of Go TaqÒ Green Master Mix (29, Promega, WI, USA), 0.5 lM of each primer, and 30 ng of template DNA. A two-step nested PCR procedure described in previous paper was adopted (Muyzer et al. 1993). The thermal profile used for the 27f/1492r was: 2 min at 95 °C; 30 cycles of 30 s at 95 °C, 30 s at 53 °C, and 2 min at 72 °C; and a final extension for 10 min at 72 °C. The thermal profile used for the 357f-GC/518r was: 2 min at 95 °C; 35 cycles of 30 s at 95 °C, 30 s at 55 °C, 1 min at 72 °C; and a final extension for 10 min at 72 °C. DGGE Denaturing gradient gel electrophoresis was performed using a D-Code apparatus (BioRad, Hercules, CA, USA).
Environ Earth Sci (2015) 73:5085–5094
5087
Fig. 1 The locations of Liao River conservation area and Wanquan River
The equal amounts of PCR amplicons were loaded onto 8 % (w/v) of polyacrylamide gels (37.5:1, acrylamide: bisacrylamide) in 1 9 TAE buffer using a specific denaturing gradient ranging from 40 to 60 % denaturant [100 % denaturant contains 7.0 M urea, 40 % (v/v) formamide in 1 9 TAE]. Electrophoresis was performed at 60 °C, 65 V for 16 h. Then, the gel was stained with 1 9 SYBRÒ Gold Nucleic Acid Gel Stain (Invitrogen, USA) solution for 50 min. Gels were visualized on a UV transilluminator. Quantity One 4.6.2 software (Bio-Rad) was used for band pattern analysis. Lanes and bands were applied to the image of the gel by the software, with additional manual fine tuning of the band designations. Dendrograms relating band pattern similarities were automatically calculated with the Dice coefficient, without band weighting (consideration of band density) by both the complete linkage and unweighted pair group method with arithmetic mean (UPGMA) algorithms in the Quantity One software (Stamper et al. 2003). The Shannon–Wiener index (H0 ) was used to evaluate the structural diversity of microbial communities in different samples (Duan et al. 2009, 2013). H0 was given by: H0 ¼
S X
Pi =lnPi
where H0 was the Shannon biodiversity index, Pi was the ratio of one specific group of bacteria to the total microorganisms, and S was the total number of microbial species in the samples. Additionally, species richness and equitability index were calculated by the following equation (Duan et al. 2009; Stamper et al. 2003): Species richnessðd Þ : d ¼ ðS 1Þ=logN Equitability indexðEÞ : E ¼ H 0 =logS where S was the number of species, N was number of individuals, H0 was Shannon–Wiener index of diversity. DNA sequencing and phylogenetic analysis The specific DGGE bands were manually excised and amplified for nucleotide sequence analysis (Yujing, Inc., Shanghai, China). The sequences were compared with those deposited in the GeneBank (NCBI) database (http:// www.ncbi.nlm.nih.gov/BLAST/). To determine the phylogenetic affiliation, similarity searches were performed using the BLAST program. For phylogenetic analysis, alignments were performed using CLUSTALW (Thompson et al. 1994). A phylogenetic
i
123
5088
Environ Earth Sci (2015) 73:5085–5094
tree was then constructed by the neighbor-joining method using the MEGA version 5.1.
Table 2 Water quality parameters of the wetland Sample
T
pH
Quantitative PCR
1
17.0
11.80
2
17.5
9.00
3
17.8
4 5
Real-time quantitative PCR was carried out using an ABI StepOnePlus 7500 Real-time PCR systems (ABI, CA, USA). Total bacteria, AOB (amoA), nitrospira-like NOB and denitrifying bacteria (nosZ) were estimated. Primers used in qPCR were previously described (Table 1). Each reaction was performed in a 20 lL volume containing 5 ng sample DNA, 4 lmol of each primer and 10 lL UltraSYBR Mixture (29, CWbio, China). PCR cycling conditions were as follows: 10 min at 95 °C; 45 cycles of 15 s at 95 °C, and 1 min at 60 °C. All PCR runs included control reactions without template. Standard curves for qPCR were generated via serial decimal dilutions (101–1012) of plasmid DNA containing specific target gene inserts. Primer specificity and the absence of primer dimers were confirmed via melt curve analysis (data not shown). The gene copy numbers were calculated by comparison of threshold cycles obtained in each PCR run with those of known standard DNA concentrations. The threshold cycle (CT) of each PCR was determined automatically by detecting the cycle at which the fluorescence exceeded the calculated threshold.
DOC
NH4?
NO3-
NO2-
1.31
47.01
10.61
0.747
0.0182
2.53
38.23
9.19
0.614
0.0486
10.43
7.54
33.57
8.77
0.480
0.0532
20.4
9.09
9.05
30.38
3.97
0.400
0.0076
18.9
9.53
8.46
41.99
2.25
0.267
0.0106
6
17.8
9.39
13.34
41.92
6.82
0.534
0.0547
7
18.4
9.32
14.20
34.07
6.82
0.400
0.0243
8
18.7
8.81
7.04
35.79
3.20
0.534
0.0289
9
18.4
9.32
9.55
24.72
2.31
0.400
0.0395
10
20.7
9.34
13.31
13.11
2.37
0.374
0.0197
11 12
20.1 18.6
8.79 8.41
8.81 7.14
33.8 22.88
5.93 5.51
0.507 0.507
0.0577 0.0182
DO
Results and discussion
values exceeding 2.00 mg/L in all the sample sites, of which the highest value reached 10.61 mg/L in the tributary, thus leading to highest pH value and lowest DO concentration. The pollutant was mainly from domestic wastewater and agricultural non-point sources. NH4? was purified by the wetland and the concentration in the outlet zone reduced to 5.51 mg/L. The highest NO3- concentration (0.747 mg/L) was also observed at site 1, and then decreased to 0.507 mg/L after passed through the wetland. NO2- concentration was low in the wetland. Therefore, the wetland could significantly purify the tributary water.
Water quality improvement by the wetland
Microbial community characterization
The water quality parameters of the wetland are shown in Table 2. The temperature was 18.7 ± 1.2 °C. The pH value was 9.44 ± 0.89, and presented gradual decline trend along the wetland. The DO concentration was 8.82 ± 3.96 mg/L, which showed rising trend. The DOC concentration in inlet part of Wanquan River (site 1) showed the highest value (47.01 mg/L). After water flowed through the wetland, DOC concentration decreased to 22.88 mg/L. The NH4? concentrations were very high with
The PCR-DGGE was used to compare the composition of the microbial community at different samples sites. The DGGE fingerprint patterns of the total bacterial community are shown in Fig. 2a. DGGE profiles on the total bacterial level showed more than 20 bands in each samples, indicating the presence of more species. Some bands such as band 1 and band 2 existed in almost all the lanes. A space evolution of microbial community was observed in the wetland. The communities in the inlet part of Wanquan
Table 1 The primers used in PCR amplification Target Total bacteria Nitrospira spp. nos Z gene amoA gene
123
Primer
Sequence (50 -30 )
References Park et al. 2010 and Kim et al. 2011
1055F
ATGGCTGTCGTCAGCT
1392R
ACGGGCGGTGTGTAC
NSR 1113F
CCTGCTTTCAGTTGCTACCG
NSR 1264R
GTTTGCAGCGCTTTGTACCG
nosZ-2F
CGCRACGGCAASAAGGTSMSSGT
nosZ-2R
CAKRTGCAKSGCRTGGCAGAA
amoA-1F
GGGGTTTCTACTGGTGGT
amoA-2R
CCCCTCKGSAAAGCCTTCTTC
Harms et al. 2002 Chen and Zhu 2011 and To¨we et al. 2010 Jin et al. 2011
Environ Earth Sci (2015) 73:5085–5094
5089
Fig. 2 DGGE fingerprint patterns (a), cluster analysis of total bacterial community dynamics (b) and phylogenetic tree (c)
River (sites 1–3) were significantly different from the outlet zone of the wetland (sites 10–12). This may be due to the influence of polluted water on the microbial composition. Specifically, bands 8, 10–13, 15, 17, 19, 20, 22 and 24 were clearly observed in lanes 1–3, 5, 7, 8. Bands 16, 18, 20, and 21 had higher intensity in lane 11. The biodiversity of the total bacterial community is an important indicator of the ecosystem. Species richness (number of different species) and species evenness (relative abundance among species) are two facets of biodiversity (Purvis and Hector 2000). Based on the number and intensity of bands in each lane, diversity statistics of total
bacterial community were calculated (Table 3). The value of Shannon–Wiener index (H0 ) increased along the Wanquan River (sites 1–3), which indicated the increased diversity of microbial community. The highest H0 value in the wetland appeared in site 3 (3.471). The H0 values for site 4 and site 5 were less than those in the inlet part of Wanquan River. The diversity of bacteria community was relatively high in the center of the wetland. In the outlet zone of the wetland, the H0 showed the lowest value (2.566) in all the samples. The species richness (d) and equitability index (E) exhibited a similar pattern with Shannon–Wiener index. These revealed that the diversity of total bacterial
123
5090
Environ Earth Sci (2015) 73:5085–5094
Fig. 2 continued
Table 3 The species richness, equitability index and diversity of microbial communities of the twelve samples
Sample
H0
d
E
1
3.330
6.208
2.255
2
3.398
6.568
2.258
3
3.471
6.920
2.286
4
3.244
5.719
2.266
5
3.261
5.801
2.254
6
3.329
6.200
2.277
7
3.407
6.221
2.284
8
3.386
6.278
2.270
9
3.414
6.453
2.268
10 11
3.100 3.052
5.096 4.884
2.246 2.241
12
2.566
3.078
2.239
community was decreased through the wetland, as well as the species richness and the species evenness. Additionally, the similarity in microbial diversity among samples is shown in Fig. 2b. In the inlet part of Wanquan River, lane 2 and lane 3 showed some 60 % of similarity lane 5 and lane 8 showed the highest similarity (more than 70 %). Lane 6 and lane 7 were similar in microbial diversity with 70 % of similarity. Lane 9 and lane 10 had more than 60 % of similarity.
123
The majority of the bands (designated 1 until 24 in Fig. 2a) were sequenced. The bands were excised and amplified for nucleotide sequence analysis. Some bands failed to provide useful sequence data because of the DGGE-specific limitation such as the detection of heteroduplex molecules (when two similar but different strands joint together) or when one species has more than one rDNA sequence producing band (Duan et al. 2009). Table 4 listed per DGGE band and the corresponding closest match from the NCBI database. The similarity of each band ranged from 95 to 100 %. The phylogenetics of the dominant DGGE bands is shown in Fig. 2c. The dominant bacterial phylotypes of the wetland was Proteobacteria (14 bands), which contained subdivisions of Alphaproteobacteria (4 bands), Betaproteobacteria (9 bands) and Gammaproteobacteria (1 band). This result was coincidence with the microbial community structure in soil and sediment of a created riverine wetland reported in previous study (Ligi et al. 2013a). Proteobacteria has been proved to play a key role in bio-degradation of carbohydrates and other organic compounds (Kragelund et al. 2008). Furthermore, another two bacterial phylotypes of Acidobacteria (4 bands) and Bacilli (6 bands) were obtained. Previous studies showed that Acidobacteria widely distributed in fresh water, streams and aquatic
Environ Earth Sci (2015) 73:5085–5094
5091
Table 4 DGGE band identification of total bacteria associated with Fig. 2a Band
16S rDNA gene
Acc. No.
Closest class
Similarity (%)a
1
Herminiimonas sp. enrichment culture clone CN
KF422141.1
Betaproteobacteria
98
2
Uncultured Caulobacteraceae bacterium clone CNY_03313
JQ402839.1
Alphaproteobacteria
98
3
Uncultured bacterium clone 12C16d-2-55
HG327348.1
Acidobacteria
99
4
Uncultured bacterium clone SSOTU10
HM346681.1
Bacilli
99
5
Staphylococcus epidermidis strain QTR-54
KC849421.1
Bacilli
100
6
Uncultured bacterium clone SIP4-RT-31.
FR774685.1
Acidobacteria
96
7
Uncultured bacterium clone B-44
JQ978892.1
Bacilli
97
8
Uncultured bacterium clone B1001R002_I07
AB659735.1
Alphaproteobacteria
98
9
Uncultured beta proteobacterium clone SA1B1
FJ916633.1
Betaproteobacteria
99
10
Uncultured bacterium clone LWS-T4819
EU546335.1
Alphaproteobacteria
97
11 12
Uncultured beta proteobacterium clone A2 Aeribacillus pallidus strain HS/OUAT/18/2013
KF411665.1 KF258896.1
Betaproteobacteria Bacilli
99 100
13
Uncultured soil bacterium clone CWT CU01_E02
DQ128434.1
Acidobacteria
95
14
Lysobacter sp. KTce-2
JQ349049.1
Gammaproteobacteria
99
15
Acidovorax sp. JHL-9
KC197036.1
Betaproteobacteria
99
16
Uncultured bacterium clone N1_053
JX406190.1
Betaproteobacteria
99
17
Uncultured Acidobacteria bacterium clone N3CHKT5
HQ132336.1
Acidobacteria
18
Sulfate-reducing bacterium enrichment culture clone 1-0-A3
KF220591.1
Bacilli
19
Unidentified bacterium clone Qui4P1-88
AJ518560.1
Betaproteobacteria
99 100 99
20
Uncultured bacterium clone EMIRGE_OTU_s7t4e_2246
JX224734.1
Bacilli
99
21
Uncultured bacterium clone JW07
JN868754.1
Betaproteobacteria
98
22
Bacterium enrichment culture clone 124
KF286253.1
Betaproteobacteria
100
23
Uncultured alpha proteobacterium clone Aug-VN117
JQ795327.1
Alphaproteobacteria
100
24
Uncultured bacterium clone SM49
KC961301.1
Betaproteobacteria
99
a
Percentages represented similarities between the DGGE band sequence and the closest match sequences in GeneBank
sediments (Zimmermann et al. 2012; Rowe et al. 2007; Barns et al. 1999). Zimmermann et al. (2012) revealed that Acidobacteria in freshwater ponds were mainly cocci preferring aerobic niches with an elevated ratio of the organic matter to the total Fe. Hartman et al. (Hartman et al. 2008) found that wetland restoration strongly influenced the normalized ratio of Proteobacteria to Acidobacteria and this ratio could be used as an indicator of wetland soil trophic status. Abundance of total bacteria, nitrifiers and denitrifiers Real-time PCR assays were employed to estimate the abundance of total bacteria, nitrifiers and denitrifiers in the sediment samples taken from the wetland. The dynamic changes of different gene copies are shown in Fig. 3. The population of total bacteria ranged from 4.11 9 102 to 4.12 9 105 copies mg-1 sediments. These numbers were always higher than those obtained for any of the functional genes. The highest abundance of total bacteria appeared at site 3, in accordance with the biodiversity index (i.e., H0 , d and E) deduced from the DGGE profiles. The outlet zone of wetland showed the least abundance of total bacteria.
Nitrification is carried out in two sequential steps via two distinct groups of bacteria: ammonia-oxidizing bacteria (AOB) and nitrite oxidizing bacteria (NOB). It is known that all AOB carry amoA gnens. The amoA gene encodes a-submit of the enzyme ammonia monoxygenase (AMO), which is associated with the N cycling and can oxidize NH3 to the intermediate NH2OH (Dong and Reddy 2012). The amoA concentration ranged from 67.05 to 8.03 9 103 copies mg-1 sediments, slightly higher than some natural wetlands in US in winter (Sims et al. 2012b). It occupied 0.15–19.33 % of total bacterial abundance. The change of AOB community may result from selection of bacteria adapted to particular nutrient status (Dong and Reddy 2012). The variation pattern of amoA abundance was similar to the NH4? concentration in the wetland. The highest abundance of amoA gene appeared in the Wanquan River (site 1), which indicated that high ammonium concentration was beneficial for AOB growth (Sims et al. 2012b). NOB is responsible for the second step of the nitrification process. Nitrospira spp. is believed to be the dominant NOB in wastewater (Garnier and Cebron 2005). The Nitrospira-like NOB copy number ranged from 9.36 to 61.00 copies mg-1
123
5092
Environ Earth Sci (2015) 73:5085–5094
Gene abundance and its potential application in assessing wetland condition
Fig. 3 Abundance of total bacteria 16S rDNA gene and nitrogen related functional bacterial communities (i.e., NOB, AOB and denitrifying bacteria)
sediments, which occupied 0.01 to 2.28 % of the total bacterial. It showed higher concentration in the latter part of wetland. The relative abundance of Nitrospira spp. showed some association with nitrite oxidation (Shore et al. 2012). NOB could be inhibited in some degree for its weaker affinity with oxygen than AOB in oxygenlimited condition (Liu et al. 2012). In this study, NOB had the lowest average gene copy number, which is attributed to the insufficient oxygen in the sediments. Microbial denitrification is a respiratory process in which nitrate (NO3-) is reduced to dinitrogen gas (N2). For nitrogen removal in wetlands, sediments have been shown to be important environments for denitrification (Kjellin et al. 2007). Lower DO in sediment can create a better anaerobic environment, which is benefit for the denitrifer’s bioactivity. The last step of the denitrification is catalyzed by the nitrous oxide reductase, which is encoded by the nosZ gene presenting in the periplasm (Horn et al. 2006; Stres et al. 2004). The nosZ gene ranged from 23.70 to 537.40 copies mg-1 sediments, which occupied 0.07–7.80 % of the total bacteria. The abundance of nosZ was higher in the latter part of wetland, which indicated relatively higher denitrification activities in these areas.
123
The most common and effective way to assess the health or biological condition of wetlands is to measure the biological community conditions first and in concert with physical and chemical assessment (Sims et al. 2012b). More importantly, engineering concepts that account for wetland can help to clarify the relationship between specific activity and the specific abundance of nitrogen related functional genes Nitrospira, amoA, nosZ. The ratios of these functional genes were calculated as biological indicators of ecosystem integrity. Pearson’s correlation coefficients were calculated between variables (Table 5). The copy number of amoA gene showed significant correlation with pH (r = 0.852) and the concentrations of DO (r = -0.595), NH4? (r = 0.595) and NO3- (r = 0.726). The results indicated that the abundance of AOB increased with pH values. Sims et al. (Sims et al. 2012b) found that the ammonium concentration was a major factor influencing AOB population in wetlands; higher ammonia loading facilitated the amoA abundance and diversity. But higher ammonia concentration could deplete oxygen concentration of water body, thus amoA gene negatively correlated with DO (Luo et al. 2014). Soil nitrification potential was positively correlated with the amoA abundance of natural wetland. Previous study demonstrated that the bacterial amoA gene copy numbers had a strong positive relationship with potential nitrification rate of the lake sediment (Hou et al. 2013). nosZ gene abundance was significantly correlated with the DOC concentration (r = -0.614). The availability of easily degradable organic carbon was a limiting factor for denitrifiers in wetland sediments (Ingersoll and Baker 1998). The ratio of amoA/Nitrospira showed significant correlation with NH4? concentrations (r = 0.641). The values of amoA/nosZ (r = -0.801) and Nitrospia/nosZ (r = -0.610) were significantly correlated with NO2- concentrations. Hence, the three ratios of nitrogen-related functional genes were a promising indicator of ‘‘wetland health’’ to infer the wetland condition.
Conclusions The constructed wetland greatly improved the water quality of tributary of Liao River, especially for DOC and ammonia reduction. The total bacterial community in the inlet part of wetland showed higher diversity, species richness and species evenness than those of the outlet zone. The dominant bacteria of the wetland were Proteobacteria, Acidobacteria and Bacilli. High ammonium load in the tributary water facilitated the abundance of amoA, and the population of Nitrospira was less than that of amoA. There
Environ Earth Sci (2015) 73:5085–5094
5093
Table 5 Pearson correlation coefficients (r) between the abundance of nitrogen functional genes and two ratios and the water quality parameters (n = 12)
T
Nitrospira
amoA
-0.074
-0.535
pH
0.006
DO
0.346
0.852** -0.595*
nosZ
amoA/Nitrospira 0.442
0.046
-0.314
0.246
0.485
0.199
0.203
-0.292
-0.407
-0.128
0.510
-0.614*
-0.498
NH4?
-0.125
0.595*
-0.417
-0.845**
NO3-
0.166
0.726**
-0.234
NO2-
0.074
0.080
0.193
Nitrospia/nosZ
0.129
DOC
-0.153
amoA/nosZ
-0.127
0.087
0.308
-0.020
0.393
-0.396
0.072
0.334
-0.273
-0.801**
-0.610*
* Correlation is significant at the 0.05 level (2-tailed) ** Correlation is significant at the 0.01 level (2-tailed)
was a strong correlation between the abundance of amoA and pH (r = 0.852), DO (r = -0.595), NH4? (r = 0.595) and NO3- (r = 0.726) concentrations. nosZ significantly correlated with DOC concentration in wetland. The ratio of amoA/Nitrospira could reflect the variation of NH4? concentrations (r = 0.641), while the values of amoA/nosZ (r = -0.801) and Nitrospia/nosZ (r = -0.610) were related to NO2- concentrations in wetland. Hence, these three ratios might serve as biological indicators for wetland condition assessment. Acknowledgments We thank Mr. Shuai Wang, Miss. Rui Geng and Mr. Pengcheng Yang for their assistance of this research. This work was financially supported by the National Major Scientific and Technological Program for Water Pollution Control and Management of China (2012ZX07202-004-03, 2012ZX07202-005).
References Ahn C, Gillevet PM, Sikaroodi M (2007) Molecular characterization of microbial communities in treatment microcosm wetlands as influenced by macrophytes and phosphorus loading. Ecol Indic 7(4):852–863 Barns SM, Takala SL, Kuske CR (1999) Wide distribution and diversity of members of the bacterial kingdom acidobacterium in the environment. Appl Environ Microb 65(4):1731–1737 Chen YG, Zhu XY (2011) Reduction of N(2)O and NO generation in anaerobic-aerobic (low dissolved oxygen) biological wastewater treatment process by using sludge alkaline fermentation liquid. Environ Sci Technol 45(6):2137–2143 Chon K, Chang J-S, Lee E, Lee J, Ryu J, Cho J (2011) Abundance of denitrifying genes coding for nitrate (narG), nitrite (nirS), and nitrous oxide (nosZ) reductases in estuarine versus wastewater effluent-fed constructed wetlands. Ecol Eng 37(1):64–69 Dong X, Reddy GB (2012) Ammonia-oxidizing bacterial community and nitrification rates in constructed wetlands treating swine wastewater. Ecol Eng 40:189–197 Duan L, Moreno-Andrade I, C-l Huang, Xia S, Hermanowicz SW (2009) Effects of short solids retention time on microbial community in a membrane bioreactor. Biores Technol 100(14): 3489–3496
Duan L, Song Y, Xia S, Hermanowicz SW (2013) Characterization of nitrifying microbial community in a submerged membrane bioreactor at short solids retention times. Biores Technol 149:200–207 Feng X, Peng J, Song Y, Duan L, Gao H (2014) Design of tributary estuary wetland in Liaohe Conservation Area. J Environ Eng Technol 4(1):13–17 Garnier J, Cebron A (2005) Nitrobacter and Nitrospira genera as representatives of nitrite-oxidizing bacteria: detection, quantification and growth along the lower Seine River (France). Water Res 39(20):4979–4992 Harms G, Layton AC, Dionisi HM, Gregory IR, Garrett VM, Hawkins SA, Robinson KG, Sayler GS (2002) Real-Time PCR quantification of nitrifying bacteria in a municipal wastewater treatment plant. Environ Sci Technol 37(2):343–351 Hartman WH, Richardson CJ, Vilgalys R, Bruland GL (2008) Environmental and anthropogenic controls over bacterial communities in wetland soils. Proc Natl Acad Sci USA 105(46): 17842–17847 Horn MA, Drake HL, Schramm A (2006) Nitrous oxide reductase genes (nosZ) of denitrifying microbial populations in soil and the earthworm gut are phylogenetically similar. Appl Environ Microb 72(2):1019–1026 Hou J, Song C, Cao X, Zhou Y (2013) Shifts between ammoniaoxidizing bacteria and archaea in relation to nitrification potential across trophic gradients in two large Chinese lakes (Lake Taihu and Lake Chaohu). Water Res 47(7):2285–2296 Ingersoll TL, Baker LA (1998) Nitrate removal in wetland microcosms. Water Res 32(3):677–684 Jin T, Zhang T, Ye L, Lee OO, Wong YH, Qian PY (2011) Diversity and quantity of ammonia-oxidizing Archaea and Bacteria in sediment of the Pearl River Estuary, China. Appl Microbiol Biotechnol 90(3):1137–1145 Kim YM, Cho HU, Lee DS, Park D, Park JM (2011) Influence of operational parameters on nitrogen removal efficiency and microbial communities in a full-scale activated sludge process. Water Res 45(17):5785–5795 Kjellin J, Hallin S, Worman A (2007) Spatial variations in denitrification activity in wetland sediments explained by hydrology and denitrifying community structure. Water Res 41(20): 4710–4720 Kragelund C, Levantesi C, Borger A, Thelen K, Eikelboom D, Tandoi V, Kong Y, Krooneman J, Larsen P, Thomsen TR (2008) Identity, abundance and ecophysiology of filamentous bacteria belonging to the Bacteroidetes present in activated sludge plants. Microbiology 154(3):886–894
123
5094 Ligi T, Oopkaup K, Truu M, Preem J-K, No˜lvak H, Mitsch WJ, ¨ , Truu J (2013a) Characterization of bacterial Mander U communities in soil and sediment of a created riverine wetland complex using high-throughput 16S rRNA amplicon sequencing. Ecol Eng. doi:10.1016/j.ecoleng.2013.09.007 ¨ Ligi T, Truu M, Truu J, No˜lvak H, Kaasik A, Mitsch WJ, Mander U (2013b) Effects of soil chemical characteristics and water regime on denitrification genes (nirS, nirK, and nosZ) abundances in a created riverine wetland complex. Ecol Eng. doi:10.1016/j. ecoleng.2013.07.015 Liu T, Li D, Zeng H, Li X, Zeng T, Chang X, Ya Cai, Zhang J (2012) Biodiversity and quantification of functional bacteria in completely autotrophic nitrogen-removal over nitrite (CANON) process. Biores Technol 118:399–406 Luo Z, Qiu Z, Wei Q, Du L, Zhao Y, Yan C (2014) Dynamics of ammonia-oxidizing archaea and bacteria in relation to nitrification along simulated dissolved ozygen gradient in sediment water interface of the Jiulong river estuarine wetland, China. Environ Earth Sci 72(7):1725–1734 Muyzer G, De Waal EC, Uitterlinden AG (1993) Profiling of complex microbial populations by denaturing gradient gel electrophoresis analysis of polymerase chain reaction-amplified genes coding for 16S rRNA. Appl Environ Microb 59(3):695–700 Park H, Rosenthal A, Jezek R, Ramalingam K, Fillos J, Chandran K (2010) Impact of inocula and growth mode on the molecular microbial ecology of anaerobic ammonia oxidation (anammox) bioreactor communities. Water Res 44(17):5005–5013 Purvis A, Hector A (2000) Getting the measure of biodiversity. Nature 405(6783):212–219 Quan X, Wang Y, Xiong W, He M, Yang Z, Lin C (2010) Description of microbial community structure of sediments from the Daliao River water system and its estuary (NE China) by application of fluorescence in situ hybridization. Environ Earth Sci 61(8): 1725–1734 Rowe OF, Sa´nchez-Espan˜a J, Hallberg KB, Johnson DB (2007) Microbial communities and geochemical dynamics in an
123
Environ Earth Sci (2015) 73:5085–5094 extremely acidic, metal-rich stream at an abandoned sulfide mine (Huelva, Spain) underpinned by two functional primary production systems. Environ Microbiol 9(7):1761–1771 Shore JL, M’Coy WS, Gunsch CK, Deshusses MA (2012) Application of a moving bed biofilm reactor for tertiary ammonia treatment in high temperature industrial wastewater. Biores Technol 112:51–60 Sims A, Gajaraj S, Hu Z (2012a) Seasonal population changes of ammonia-oxidizing organisms and their relationship to water quality in a constructed wetland. Ecol Eng 40:100–107 Sims A, Horton J, Gajaraj S, McIntosh S, Miles RJ, Mueller R, Reed R, Hu ZQ (2012b) Temporal and spatial distributions of ammonia-oxidizing archaea and bacteria and their ratio as an indicator of oligotrophic conditions in natural wetlands. Water Res 46(13):4121–4129 Stamper DM, Walch M, Jacobs RN (2003) Bacterial population changes in a membrane bioreactor for graywater treatment monitored by denaturing gradient gel electrophoretic analysis of 16S rRNA gene fragments. Appl Environ Microb 69(2):852–860 Stres B, Mahne I, Avgusˇtin G, Tiedje JM (2004) Nitrous oxide reductase (nosZ) gene fragments differ between native and cultivated Michigan soils. Appl Environ Microb 70(1):301–309 Thompson JD, Higgins DG, Gibson TJ (1994) CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice. Nucleic Acids Res 22(22): 4673–4680 To¨we S, Kleineidam K, Schloter M (2010) Differences in amplification efficiency of standard curves in quantitative real-time PCR assays and consequences for gene quantification in environmental samples. J Microbiol Meth 82(3):338–341 Zimmermann J, Portillo MC, Serrano L, Ludwig W, Gonzalez JM (2012) Acidobacteria in Freshwater Ponds at Donana National Park, Spain. Microb Ecol 63(4):844–855
