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A high-throughput sequencing study of bacterial communities in an autohydrogenotrophic denitrifying bio-ceramsite reactor
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A high-throughput sequencing study of bacterial communities in an autohydrogenotrophic denitrifying bio-ceramsite reactor Dan Chen a , Hongyu Wang a,∗ , Bin Ji a , Kai Yang a , Li Wei b,∗ , Yu Jiang a a b
School of Civil Engineering, Wuhan University, Wuhan 430072, China State Key Lab of Urban Water Resources and Environment, Harbin Institute of Technology, Harbin 150090, China
a r t i c l e
i n f o
Article history: Received 15 April 2015 Received in revised form 4 July 2015 Accepted 9 July 2015 Available online xxx Keywords: High-throughput sequencing Autohydrogenotrophic Bio-ceramsite Phyla Heatmap
a b s t r a c t For the first time, high-throughput sequencing was employed to investigate the microbial communities of the biofilm in an autohydrogenotrophic denitrifying bio-ceramsite reactor. 30,418 and 39,178 bacterial 16S rRNA gene sequences were obtained from biofilm Samples C1 and C2 in the reactor under HRT 16 h, pH 7.0 and HRT 48 h, pH 9.0 conditions. Results showed that the mainly reported autohydrogenotrophic denitrifying phyla Proteobacteria, Firmicutes and classes Gammaproteobacteria, Alphaproteobacteria, Bacilli were all detected in the reactor, and their high relative abundances demonstrated they played key roles in the autohydrogenotrophic denitrification process, suggesting that this bio-ceramsite reactor presented better denitrification performance. The heatmap analysis illustrated that the largest genus in Sample C1 was Acinetobacter, while Planomicrobium was the largest genus in Sample C2. In addition, the reported hydrogenotrophic denitrifying genera Ochrobactrum, Paracoccus, Pseudomonas, Hydrogenophaga, and Thauera were always observed in the reactor, suggesting that this bio-ceramsite reactor exhibited autohydrogenotrophic denitrifying capacity to convert nitrate to nitrogen gas. This work might add some new insights into microbial communities in autohydrogenotrophic denitrification process. © 2015 Elsevier Ltd. All rights reserved.
1. Introduction
The autohydrogenotrophic denitrification reactions are as follows:
Since nitrate pollution in drinking water often causes many serious problems in human health such as gastric cancer and Methemoglobinemia, the World Health Organization stipulates that nitrate concentration in drinking water is 11.30 mg/L [1]. Many chemical and biological methods are carried out to remove nitrate from drinking water [2–4]. Commonly, heterotrophic and autotrophic denitrification technologies are the main biological process for nitrate removal from drinking water. Although heterotrophic denitrification is effective [5], this treatment process always causes excessive biomass and organic carbon in the effluent because this process often needs external carbon source to achieve persistent efficiency. Autohydrogenotrophic denitrification refers to an autotrophic process, in which microorganisms use hydrogen as electron donor, nitrate as electron acceptor, and inorganic carbon for assimilation.
NO3 − + H2 → NO2 − + H2 O
∗ Corresponding authors. E-mail addresses: [email protected] (H. Wang), [email protected] (L. Wei).
−
(1) −
(2)
NO3 − + 2.5H2 → 0.5N2 + H2 O + OH−
(3)
NO2 + 1.5H2 → 0.5N2 + H2 O + OH Overall reaction:
Hydrogenotrophic denitrification attracts many researchers’ interests and has been developed as an alternative treatment method to heterotrophic method for nitrate removal in recent years [6–8], because this process is cost-effective, lower biomass, and without organic carbon in the treated water [9,10]. Currently, various kinds of systems such as membrane reactors [6,11], bio-electrochemical systems [12], fluidized-bed reactors [13] and fixed-bed reactors [14] have been studied for hydrogenotrophic denitrification treatment process. Li et al. [15] investigated hydrogenotrophic denitrification for nitrate removal from municipal wastewater using a lab-scale membrane diffusion packed-bed bioreactor, and achieved relatively high denitrifiaction rate. Lee et al. [5] used a lab-scale packed bed reactor (PBR) to investigate hydrogenotrophic denitrification performance, and optimized the hydrogenotrophic process. In the study of Vasiliadou et al. [16], the
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Please cite this article in press as: D. Chen, et al., A high-throughput sequencing study of bacterial communities in an autohydrogenotrophic denitrifying bio-ceramsite reactor, Process Biochem (2015), http://dx.doi.org/10.1016/j.procbio.2015.07.006
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Table 1 Reactor operation.
Fig. 1. Schematic of the bio-ceramsite reactor.
kinetics of hydrogenotrophic denitrification process was studied and the kinetic parameters were discussed. Culture-based and culture-independent methods are the first technologies for analyses of bacterial communities in drinking water treatment process and these classical microbiological methods often achieve unrepresentative results [17]. Recently, clone library [18], microarray [19,20], fluorescent in situ hybridization [21], and real time polymerase chain reaction [22,23] are often employed to evaluate the bacterial communities in activated sludge and biofilms in water treatment process. However, high-throughput sequencing is a more powerful method than the above-mentioned methods for evaluation of microbial communities [24–26] in denitrification process, due to that denitrification process always exhibits extraordinary diversity of microorganisms and high-throughput sequencing method can accomplish this evaluation preferably. The high-throughput analytical approach pyrosequencing was developed by Roche 454 FLX Titanium platform (Roche, Basel, Switzerland), which uses massively parallel sequencing-bysynthesis method [27] in order to produce larger amounts of DNA reads. This method has been widely applied to evaluate microbial communities in many types of environmental samples such as soil [28], marine water [29], wastewater treatment plant influent [30], and human distal intestine [31]. However, relatively few studies have investigated the microbial communities on biofilm samples especially for hydrogenotrophic denitrification process using highthroughput analytical method. Kwon and coworkers [10,25,32] investigated the microbial communities in activated sludge system and membrane filtration system for water treatment process using high-throughput method and the results represented the bacterial diversity and community structure commendably. The aim of the present work was to investigate the denitrification performance and analyze the bacterial communities through 454-pyrosequencing, in order to discuss and reveal the relationship between bacterial community structure and nitrate removal performance in the autohydrogenotrophic denitrifying bio-ceramsite reactor. This work would add some new insights into the evaluation of bacterial communities in autohydrogenotrophic denitrification process. 2. Materials and methods 2.1. Reactor operation A schematic diagram of the autohydrogenotrophic denitrifying bio-ceramisite reactor used in this work is shown in Fig. 1,
Stages
HRT (h)
pH
Stage 1 (day 1–100) Stage 2 (day 101–200) Stage 3 (day 201–300) Stage 4 (day 301–400)
5 16 24 48
6.0 7.0 8.0 9.0
which was studied in our previous work [33]. The compositions of synthetic influent water and start-up of the bio-ceramsite reactor followed our previous work [33]. Synthetic wastewater contained NaNO3 , KH2 PO4 , NaHCO3 , piped water, and trace elements contained ZnCl2 , CoCl2 , MnSO4 , FeSO4 , CaCl2 , etc. Start-up of the bio-ceramsite reactor was initiated by seeding with anaerobic activated sludge which covered the ceramsite. Hydrogen and sodium bicarbonate (inorganic carbon source) were introduced to the reactor. When denitrification rate reached 80% and a compacted biofilm formed on the surface of the ceramsite after 3 weeks, the domestication phase was accomplished. Then the bio-ceramsite reactor was continuously and steadily operated for 400 days. As shown in Table 1, the operation of the reactor was divided into four stages in terms of pH and hydraulic retention time (HRT) because HRT and pH played important roles in the autohydrogenotrophic denitrification process according to our previous study [33] and many other researches [34,35]. The pH of synthetic wastewater was adjusted by adding HCl or NaOH solutions, and HRT was adjusted by regulating influent flow. The nitrate loading, C/N (carbon to nitrate ratio) and temperature were maintained at 30 mg NO3 − -N/L, 1.0 and 25 ◦ C during the whole operation. 2.2. Analysis methods Total nitrogen (TN), ammonium nitrogen (NH4 + -N), nitrate nitrogen (NO3 − -N), and nitrite nitrogen (NO2 − -N) were determined according to Standard Methods for the Examination of Water and Wastewater [36]. Nitrogen gas (N2 ) and nitrous oxide (N2 O) were measured by an Agilent HP4890D gas chromatography. The pH was measured by a pH meter (PHS-3C, Kexiao Instrument, China). The water temperature was measured by a thermometer (TM827, Zhugongda Instrument, China). 2.3. Microbial community analysis 2.3.1. DNA extraction, PCR amplification and pyrosequencing The biofilm Samples C1 and C2 were collected from the surfaces on the bottom, middle, and upside of the ceramsite in the reactor from Stage 2 and Stage 4 during the steady operation period on day 150 and day 350 under HRT 16 h, pH 7.0 and HRT 48 h, pH 9.0 conditions, respectively. Bacterial genomic DNA was extracted using the PowerSoil DNA extraction kit (MO BIO Laboratories, Inc., Carlsbad, CA) following the manufacturer’s instruction. The PCR amplification (Supplementary Materials) used the universal bacteria primers 8F and 533R, which were targeting the V1 and V3 hypervariable regions [26]. The primers was modified by adding a 10-nucleotide barcode (C1: 5 -AGTACTACTA-3 ; C2: 5 -CTCGAGTCTC-3 ) and corresponding pyrosequencing adaptors. The final sequences of the primers were 8F (5 -AGAGTTTGATCCTGGCTCAG-3 ), 533R (5 TTACCGCGGCTGCTGGCAC-3 ). Then the pyrosequencing procedure was according to our previous approach [37]. 2.3.2. Sequence analysis The sequence analysis followed the method (Supplementary Materials) described in our previous study [37]. Operational taxonomic unit (OTU), rarefaction curves and the diversity indices
Please cite this article in press as: D. Chen, et al., A high-throughput sequencing study of bacterial communities in an autohydrogenotrophic denitrifying bio-ceramsite reactor, Process Biochem (2015), http://dx.doi.org/10.1016/j.procbio.2015.07.006
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Table 2 Community richness and diversity indices of Samples C1 and C2. Sample
No. of sequences
Coverage
Ace
Chao
Shannon
Simpson
C1 C2
30,418 39,178
0.995382 0.995451
468 779
482 674
2.178326 2.519675
0.326332 0.269457
Fig. 2. Denitrification efficiency from Stage 1 to Stage 4.
(Ace and Chao 1) were determined by Mothur ver. 1.17.0, and the taxonomy-based analysis used RDP-II Classifier of the Ribosomal Database Project (RDP) and the National Center for Biotechnology Information (NCBI) BLAST. 3. Results and discussion 3.1. NO3 − -N and TN removal of the bio-ceramsite reactor As shown in Fig. 2, the average NO3 − -N and TN removal efficiencies increased from 61.21% to 91.36% and 57.61% to 87.87% from Stage 1 to Stage 2. The highest average NO3 − -N removal efficiency 97.41% and TN removal efficiency 93.93% were achieved at Stage 3 under HRT 24 h and pH 8.0 conditions. However, the NO3 − -N and TN removal efficiencies decreased to 80.31% and 76.21% at Stage 4. The highest average producing N2 27.63 mg/L was observed at Stage 3 when the initial nitrate loading was 29.58 mg/L. Moreover, the concentrations of NO2 − -N and N2 O were always maintained below 0.94 mg/L and 1.03 mg/L during the whole experiments, meaning
that nitrate (29.58 mg/L) was almost completely converted to nitrogen gas (27.63 mg/L) in the denitrification process in the reactor. The lowest nitrate removal performance was observed at Stage 1 due to the very short HRT 5 h and acidic environment. As reported by Wang et al., the nitrate removal efficiency decreased if HRT was too short in the hydrogen dependent denitrification bioreactor [34] because microorganisms did not grow well for degradation of nitrate. On the other hand, hydrogenotrophic denitrification process was easily influenced by pH and many researchers reported that the optimal pH value was 7.5–8.0 [35,38] for this process. In the present study in Stage 1, low pH value 6.0 inhibited the denitrification process due to the reason that the reactivity of hydrogenotrophic denitrifying bacteria was affected by the decomposition of carbonate ions under this environment [39]. For Stage 2, the nitrate removal rate reached above 90% at HRT 16 h and pH 7.0 condition, suggesting that HRT 16 h was appropriate for the system to achieve complete denitrification under neutral environment. This result was in accordance with the research of Ghafari et al. [40], which reported that the suitable HRT was 13.5–30 h for nitrate removal in hydrogenotrophic denitrification process. The best nitrate removal efficiency was observed at Stage 3 due to the reason that pH 8.0 was most suitable for the hydrogenotrophic denitrifying bio-ceramisite reactor to reduce nitrate under HRT 24 h condition. This result was in accordance with the study of Wang et al. [34], which demonstrated that a fiber-based biofilm reactor achieved excellent denitrification efficiency when pH was neutral and alkalescent for nitrate removal. For Stage 4, an obvious decrease of nitrate removal rate was observed due to that high pH 9.0 was harmful to the dominant hydrogenotrophic denitrifying bacteria [34] in the reactor, which was similar with the result of Rezania et al. [41]. 3.2. Bacterial diversity analysis A total of 30,418 and 39,178 bacterial 16S rRNA gene sequences were obtained from Samples C1 and C2, and then used for bacterial community analyses (Table 2). Rarefaction analyses based on OTUs at 3%, 5% and 10% dissimilarity were shown in Fig. 3a, which indicated that the recovered sequences commendably represented the diversity of the bacterial communities in the two samples because the rarefaction curves were approaching plateaus with 99.54% and
Fig. 3. Diversity of bacterial communities in the bio-ceramsite reactor. (a) Rarefaction curves, and (b) rank-abundance curves based on bacterial OTUs at a dissimilarity level of 3%.
Please cite this article in press as: D. Chen, et al., A high-throughput sequencing study of bacterial communities in an autohydrogenotrophic denitrifying bio-ceramsite reactor, Process Biochem (2015), http://dx.doi.org/10.1016/j.procbio.2015.07.006
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Fig. 4. Taxonomic classification of bacterial 16S rRNA gene reads retrieved from C1 and C2 at phylum level (a) and class level (b) using RDP classifier with a confidence threshold of 80%.
99.55% coverage under 3% dissimilarity for C1 and C2, respectively. It can be seen from Fig. 3a that the species richness of C2 was higher than that of C1. In addition, the values of Ace, Chao, Shannon, and Simpson (Table 2) also demonstrated that the bacterial diversity of C2 was higher than that of C1. Moreover, the rank-abundance curves (Fig. 3b) demonstrated that the two samples contained relatively low proportions of highly abundant bacteria because the curves represented a majority of the reads belonged to rare organisms [42]. Sample C1 was collected from Stage 2 under HRT 16 h and pH 7.0 conditions, while Sample C2 was collected from Stage 4 under HRT 48 h and pH 9.0 conditions. The higher community richness and bacterial diversity of C2 compared to C1 might be due to that more bacterial species preferred alkaline environment in the bioceramsite reactor. On the other hand, long HRT might be beneficial for steady survival of more bacterial species. However, the nitrate removal rate of C1 was higher than that of C2, due to the reason that the dominant autohydrogenotrophic denitrifying bacteria for effective nitrate removal preferred pH 7.0 condition in the bioreactor. Furthermore, this was the first work to evaluate the microbial communities in autohydrogenotrophic denitrifying bio-ceramsite reactor through 454-pyrosequencing analysis. The large numbers of bacterial 16S rRNA gene sequences, and diversity indices such as community richness indices (Chao and Ace) and community diversity indices (Shannon Simpson) and Coverage were very useful for analyzing the microbial communities in this reactor, which demonstrated that 454-pyrosequencing would be an available approach to evaluate the microbial communities of biofilm samples in autohydrogenotrophic denitrification process. 3.3. Bacterial community structure and nitrate removal performance It can be seen from Fig. 4a that the total of identified phyla for Samples C1 and C2 were 20. Sample C1 was mainly composed of Proteobacteria (70.46%), Firmicutes (24.61%), Planctomycetes (1.84%), and Actinobacteria (1.58%). Sample C2 was mainly represented by Firmicutes (75.03%), Proteobacteria (15.39%), Actinobacteria (4.02%), and Planctomycetes (3.06%). Although the major phyla among the two samples were uniform, their relative abundances were different. As shown in Fig. 4b, the total of identified classes for Samples C1 and C2 were 40. The dominant classes in Sample C1 were Gammaproteobacteria (64.57%), Bacilli (15.80%), Clostridia (8.78%), and Alphaproteobacteria (5.53%). Sample C2 was mainly represented by Bacilli (50.53%), Clostridia (24.43%), Alphaproteobacteria (9.97%), and Gammaproteobacteria (4.01%). The four dominant
classes had obviously different abundances among the two samples. In addition, classes Betaproteobacteria, Flavobacteria, and Sphingobacteria were also detected in the two samples. According to many researches, phylum Proteobacteria (main classes contained Alphaproteobacteria, Betaproteobacteria, and Gammaproteobacteria) was one of the most abundant groups in freshwater [25,43]. Karanasiosa et al. [9] reported that most of the hydrogenotrophic denitrifying microorganisms would belong to phylum Proteobacteria. Szekeres et al. [44] studied the bacterial population in a hydrogen dependent denitrification bioreactor, and reported phylum Proteobacteria (contained species Ochrobactrum anthropi, Pseudomonas stutzeri, Paracoccus panthotrophus, and Paracoccus denitrificans) played a vital role in the hydrogenotrophic denitrification process. Wang et al. [34] demonstrated that phylum Firmicutes played important role in denitrification process in a fiber-based biofilm reactor for nitrate removal from groundwater. Huang et al. [43] utilized T-RFLP and 16S rRNA gene clone library to investigate bacterioplankton communities, and reported that Betaproteobacteria and Gammaproteobacteria were the dominant classes. Chen et al. [45] reported that the dominant class was Alphaproteobacteria in biofilms formed on MF membrane with isolation and cloning experiments. Verbaendert et al. [46] detected that a large number of denitrifying bacteria were belonged to class Bacilli. In addition, some bacterial communities from hydrogenotrophic denitrifying biofilms had been identified as the class Flavobacteria [47] and Sphingobacteria [48]. In the study of Park et al. [47], the major populations were Proteobacteria and Flavobacteria in the hydrogenotrophic denitrification biofilm-electrode reactor. Sahu et al. [48] reported that hydrogenotrophic denitrifying class Sphingobacteria participated in the nitrate removal process in a membrane biofilm reactor. In the present study, the mainly reported autohydrogenotrophic denitrifying phyla such as Proteobacteria, Firmicutes and classes such as Gammaproteobacteria, Alphaproteobacteria, Bacilli were all detected in the autohydrogenotrophic denitrifying bio-ceramsite reactor. The high relative abundances demonstrated these phyla and classes played key roles in the autohydrogenotrophic denitrification process, meaning that this bio-ceramsite reactor exhibited excellent nitrate removal performance. It also demonstrated that the microorganisms in this reactor had the ability to use H2 as electron donor and use nitrate as electron acceptor for nitrate removal. The denitrification rate of Sample C1 was higher than that of Sample C2 because the relative abundances of the dominant phylum Proteobacteria and the dominant class Gammaproteobacteria in Sample C1 were higher than of Sample C2 in the bioreactor, suggesting that phylum Proteobacteria and class Gammaproteobacteria exhibited excellent denitrification capacity to convert nitrate to nitrogen gas
Please cite this article in press as: D. Chen, et al., A high-throughput sequencing study of bacterial communities in an autohydrogenotrophic denitrifying bio-ceramsite reactor, Process Biochem (2015), http://dx.doi.org/10.1016/j.procbio.2015.07.006
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Fig. 5. Relative abundance of each taxonomic genus in Samples C1 and C2. Heat map illustrates the abundance of the top 100 genera in each sample, and scale bar shows the variation ranges of the normalized abundance of the genera.
under neutral environment in the reactor. It was also indicated that dominant phylum Proteobacteria and class Gammaproteobacteria preferred neutral environment for higher denitrification efficiency rather than alkaline environment. However, some unreported autohydrogenotrophic denitrifying bacterial groups such as phyla Planctomycetes, Actinobacteria and class Clostridia also showed high relative abundances in Sample C2 under long HRT and alkaline environment. They also played roles in autohydrogenotrophic denitrification process, and their ecological functions in this bioceramsite reactor remained unclear and needed doing further researches. The similarities of microbial community structures in the two biofilm samples were discussed at genus level by hierarchically clustered heatmap analysis (Fig. 5). The largest genus in Sample C1 was Acinetobacter (58.84%), while Planomicrobium (48.97%) was the dominant genus in Sample C2. Some researchers reported that Acinetobacter was the dominated genus in hydrogen-oxidizing microbial cultures [10,49]. Vasiliadou et al. [10] investigated the hydrogenotrophic denitrification in a batch reactor and demonstrated Acinetobacter exhibited the ability to use hydrogen as
electron donor for nitrate removal. Liessens et al. [49] isolated Acinetobacter from the hydrogenotrophic reactor for the denitrification treatment and proved Acinetobacter played a vital role in the hydrogenotrophic denitrification process. In this study, Sample C1 attained higher NO3 − -N and TN removal efficiency than that of Sample C2 because of the leading role of genus Acinetobacter in Sample C1, meaning that genus Acinetobacter was the key contributors to convert nitrate to nitrogen gas in this autohydrogenotrophic denitrifying bioceramsite reactor under appropriate conditions. In Sample C2, genus Planomicrobium was mainly responsible for the denitrifiaction process. According to many reports, genera Ochrobactrum, Paracoccus [10,48], Pseudomonas [49,50], Hydrogenophaga [51] and Thauera [26] were always observed in hydrogen dependent denitrification reactors. Liessens et al. [49] demonstrated that Pseudomonas played a key role in the hydrogenotrophic denitrification process in a hydrogenotrophic reactor. Zhang et al. [51] reported that Hydrogenophaga played an important role in autohydrogenotrophic denitrification in a hollow fiber membrane biofilm reactor for nitrate removal from drinking water. These reported
Please cite this article in press as: D. Chen, et al., A high-throughput sequencing study of bacterial communities in an autohydrogenotrophic denitrifying bio-ceramsite reactor, Process Biochem (2015), http://dx.doi.org/10.1016/j.procbio.2015.07.006
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genera Ochrobactrum, Paracoccus, Pseudomonas, Hydrogenophaga and Thauera, were all detected in our hydrogenotrophic bioceramsite reactor and participated in the hydrogenotrophic denitrification process, suggesting that this bio-ceramsite reactor exhibited autohydrogenotrophic denitrifying capacity. However, the high abundance of Planomicrobium in Sample C2 might be related to the alkaline environment. Planomicrobium might be a valuable and worth investigating genus for hydrogenotrophic denitrification process. The autohydrogenotrophic denitrification process always involved limited bacterial community compositions, due to the fact that the hydrogenotrophic denitrifying environment was highly selective [9]. The bacteria in this hydrogenotrophic denitrifying system must have the ability to use nitrate as electron acceptor and use H2 as electron donor, and grow with inorganic carbon under anaerobic conditions in order to realize hydrogen dependent denitrification. Furthermore, the main interactions between microorganisms in the reactor were competition and synergy. Competition refers to the process that various microorganisms competed for nitrate source, inorganic carbon source, and electron donor hydrogen gas for self-growth and degrading nitrate. In addition, synergy refers to microorganisms’ mutual use of each other. For instance, some nitrate reducing bacteria convert nitrate into nitrite, then nitrite can be used by nitrite reducing bacteria for electron acceptor to convert nitrite to nitrogen gas. 4. Conclusions The hydrogenotrophic denitrifying bio-ceramsite reactor exhibited excellent nitrate removal performance, and the highest NO3 − -N and TN removal efficiencies reached 97.41% and 93.93%. Pyrosequencing analysis of the biofilm samples showed high bacterial diversity, and many effective hydrogen dependent denitrifying phyla, classes and genera were detected in the bio-ceramsite reactor. Phylum Proteobacteria, class Gammaproteobacteria, and genus Acinetobacter were the dominant contributors for effective nitrate removal performance in this bio-ceramsite reactor under HRT 16 h and pH 7.0 conditions. The hydrogenotrophic denitrification process involved limited bacterial community compositions, due to that the hydrogenotrophic denitrifying environment was highly selective. Acknowledgements This work was financially supported by the National Natural Science Foundation of China (NSFC) (51378400) and the National Science and Technology Pillar Program (2014BAL04B04). Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at doi:10.1016/j.procbio.2015.07.006 References [1] WHO, Nitrate and nitrite in drinking-water: Background document for development of WHO Guidelines for Drinking-water Quality, 2003. [2] S. Aslan, A. Turkman, Nitrate and pesticides removal from contaminated water using biodenitrification reactor, Process Biochem. 41 (2006) 882–886. [3] S¸. Aslan, Combined removal of pesticides and nitrates in drinking waters using biodenitrification and sand filter system, Process Biochem. 40 (2005) 417–424. [4] C. Della Rocca, V. Belgiorno, S. Meric¸, An heterotrophic/autotrophic denitrification (HAD) approach for nitrate removal from drinking water, Process Biochem. 41 (2006) 1022–1028. [5] J.W. Lee, K.H. Lee, K.Y. Park, S.K. Maeng, Hydrogenotrophic denitrification in a packed bed reactor: effects of hydrogen-to-water flow rate ratio, Bioresour. Technol. 101 (2010) 3940–3946.
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A high-throughput sequencing study of bacterial communities in an autohydrogenotrophic denitrifying bio-ceramsite reactor Dan Chen a , Hongyu Wang a,∗ , Bin Ji a , Kai Yang a , Li Wei b,∗ , Yu Jiang a a b
School of Civil Engineering, Wuhan University, Wuhan 430072, China State Key Lab of Urban Water Resources and Environment, Harbin Institute of Technology, Harbin 150090, China
a r t i c l e
i n f o
Article history: Received 15 April 2015 Received in revised form 4 July 2015 Accepted 9 July 2015 Available online xxx Keywords: High-throughput sequencing Autohydrogenotrophic Bio-ceramsite Phyla Heatmap
a b s t r a c t For the first time, high-throughput sequencing was employed to investigate the microbial communities of the biofilm in an autohydrogenotrophic denitrifying bio-ceramsite reactor. 30,418 and 39,178 bacterial 16S rRNA gene sequences were obtained from biofilm Samples C1 and C2 in the reactor under HRT 16 h, pH 7.0 and HRT 48 h, pH 9.0 conditions. Results showed that the mainly reported autohydrogenotrophic denitrifying phyla Proteobacteria, Firmicutes and classes Gammaproteobacteria, Alphaproteobacteria, Bacilli were all detected in the reactor, and their high relative abundances demonstrated they played key roles in the autohydrogenotrophic denitrification process, suggesting that this bio-ceramsite reactor presented better denitrification performance. The heatmap analysis illustrated that the largest genus in Sample C1 was Acinetobacter, while Planomicrobium was the largest genus in Sample C2. In addition, the reported hydrogenotrophic denitrifying genera Ochrobactrum, Paracoccus, Pseudomonas, Hydrogenophaga, and Thauera were always observed in the reactor, suggesting that this bio-ceramsite reactor exhibited autohydrogenotrophic denitrifying capacity to convert nitrate to nitrogen gas. This work might add some new insights into microbial communities in autohydrogenotrophic denitrification process. © 2015 Elsevier Ltd. All rights reserved.
1. Introduction
The autohydrogenotrophic denitrification reactions are as follows:
Since nitrate pollution in drinking water often causes many serious problems in human health such as gastric cancer and Methemoglobinemia, the World Health Organization stipulates that nitrate concentration in drinking water is 11.30 mg/L [1]. Many chemical and biological methods are carried out to remove nitrate from drinking water [2–4]. Commonly, heterotrophic and autotrophic denitrification technologies are the main biological process for nitrate removal from drinking water. Although heterotrophic denitrification is effective [5], this treatment process always causes excessive biomass and organic carbon in the effluent because this process often needs external carbon source to achieve persistent efficiency. Autohydrogenotrophic denitrification refers to an autotrophic process, in which microorganisms use hydrogen as electron donor, nitrate as electron acceptor, and inorganic carbon for assimilation.
NO3 − + H2 → NO2 − + H2 O
∗ Corresponding authors. E-mail addresses: [email protected] (H. Wang), [email protected] (L. Wei).
−
(1) −
(2)
NO3 − + 2.5H2 → 0.5N2 + H2 O + OH−
(3)
NO2 + 1.5H2 → 0.5N2 + H2 O + OH Overall reaction:
Hydrogenotrophic denitrification attracts many researchers’ interests and has been developed as an alternative treatment method to heterotrophic method for nitrate removal in recent years [6–8], because this process is cost-effective, lower biomass, and without organic carbon in the treated water [9,10]. Currently, various kinds of systems such as membrane reactors [6,11], bio-electrochemical systems [12], fluidized-bed reactors [13] and fixed-bed reactors [14] have been studied for hydrogenotrophic denitrification treatment process. Li et al. [15] investigated hydrogenotrophic denitrification for nitrate removal from municipal wastewater using a lab-scale membrane diffusion packed-bed bioreactor, and achieved relatively high denitrifiaction rate. Lee et al. [5] used a lab-scale packed bed reactor (PBR) to investigate hydrogenotrophic denitrification performance, and optimized the hydrogenotrophic process. In the study of Vasiliadou et al. [16], the
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Table 1 Reactor operation.
Fig. 1. Schematic of the bio-ceramsite reactor.
kinetics of hydrogenotrophic denitrification process was studied and the kinetic parameters were discussed. Culture-based and culture-independent methods are the first technologies for analyses of bacterial communities in drinking water treatment process and these classical microbiological methods often achieve unrepresentative results [17]. Recently, clone library [18], microarray [19,20], fluorescent in situ hybridization [21], and real time polymerase chain reaction [22,23] are often employed to evaluate the bacterial communities in activated sludge and biofilms in water treatment process. However, high-throughput sequencing is a more powerful method than the above-mentioned methods for evaluation of microbial communities [24–26] in denitrification process, due to that denitrification process always exhibits extraordinary diversity of microorganisms and high-throughput sequencing method can accomplish this evaluation preferably. The high-throughput analytical approach pyrosequencing was developed by Roche 454 FLX Titanium platform (Roche, Basel, Switzerland), which uses massively parallel sequencing-bysynthesis method [27] in order to produce larger amounts of DNA reads. This method has been widely applied to evaluate microbial communities in many types of environmental samples such as soil [28], marine water [29], wastewater treatment plant influent [30], and human distal intestine [31]. However, relatively few studies have investigated the microbial communities on biofilm samples especially for hydrogenotrophic denitrification process using highthroughput analytical method. Kwon and coworkers [10,25,32] investigated the microbial communities in activated sludge system and membrane filtration system for water treatment process using high-throughput method and the results represented the bacterial diversity and community structure commendably. The aim of the present work was to investigate the denitrification performance and analyze the bacterial communities through 454-pyrosequencing, in order to discuss and reveal the relationship between bacterial community structure and nitrate removal performance in the autohydrogenotrophic denitrifying bio-ceramsite reactor. This work would add some new insights into the evaluation of bacterial communities in autohydrogenotrophic denitrification process. 2. Materials and methods 2.1. Reactor operation A schematic diagram of the autohydrogenotrophic denitrifying bio-ceramisite reactor used in this work is shown in Fig. 1,
Stages
HRT (h)
pH
Stage 1 (day 1–100) Stage 2 (day 101–200) Stage 3 (day 201–300) Stage 4 (day 301–400)
5 16 24 48
6.0 7.0 8.0 9.0
which was studied in our previous work [33]. The compositions of synthetic influent water and start-up of the bio-ceramsite reactor followed our previous work [33]. Synthetic wastewater contained NaNO3 , KH2 PO4 , NaHCO3 , piped water, and trace elements contained ZnCl2 , CoCl2 , MnSO4 , FeSO4 , CaCl2 , etc. Start-up of the bio-ceramsite reactor was initiated by seeding with anaerobic activated sludge which covered the ceramsite. Hydrogen and sodium bicarbonate (inorganic carbon source) were introduced to the reactor. When denitrification rate reached 80% and a compacted biofilm formed on the surface of the ceramsite after 3 weeks, the domestication phase was accomplished. Then the bio-ceramsite reactor was continuously and steadily operated for 400 days. As shown in Table 1, the operation of the reactor was divided into four stages in terms of pH and hydraulic retention time (HRT) because HRT and pH played important roles in the autohydrogenotrophic denitrification process according to our previous study [33] and many other researches [34,35]. The pH of synthetic wastewater was adjusted by adding HCl or NaOH solutions, and HRT was adjusted by regulating influent flow. The nitrate loading, C/N (carbon to nitrate ratio) and temperature were maintained at 30 mg NO3 − -N/L, 1.0 and 25 ◦ C during the whole operation. 2.2. Analysis methods Total nitrogen (TN), ammonium nitrogen (NH4 + -N), nitrate nitrogen (NO3 − -N), and nitrite nitrogen (NO2 − -N) were determined according to Standard Methods for the Examination of Water and Wastewater [36]. Nitrogen gas (N2 ) and nitrous oxide (N2 O) were measured by an Agilent HP4890D gas chromatography. The pH was measured by a pH meter (PHS-3C, Kexiao Instrument, China). The water temperature was measured by a thermometer (TM827, Zhugongda Instrument, China). 2.3. Microbial community analysis 2.3.1. DNA extraction, PCR amplification and pyrosequencing The biofilm Samples C1 and C2 were collected from the surfaces on the bottom, middle, and upside of the ceramsite in the reactor from Stage 2 and Stage 4 during the steady operation period on day 150 and day 350 under HRT 16 h, pH 7.0 and HRT 48 h, pH 9.0 conditions, respectively. Bacterial genomic DNA was extracted using the PowerSoil DNA extraction kit (MO BIO Laboratories, Inc., Carlsbad, CA) following the manufacturer’s instruction. The PCR amplification (Supplementary Materials) used the universal bacteria primers 8F and 533R, which were targeting the V1 and V3 hypervariable regions [26]. The primers was modified by adding a 10-nucleotide barcode (C1: 5 -AGTACTACTA-3 ; C2: 5 -CTCGAGTCTC-3 ) and corresponding pyrosequencing adaptors. The final sequences of the primers were 8F (5 -AGAGTTTGATCCTGGCTCAG-3 ), 533R (5 TTACCGCGGCTGCTGGCAC-3 ). Then the pyrosequencing procedure was according to our previous approach [37]. 2.3.2. Sequence analysis The sequence analysis followed the method (Supplementary Materials) described in our previous study [37]. Operational taxonomic unit (OTU), rarefaction curves and the diversity indices
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Table 2 Community richness and diversity indices of Samples C1 and C2. Sample
No. of sequences
Coverage
Ace
Chao
Shannon
Simpson
C1 C2
30,418 39,178
0.995382 0.995451
468 779
482 674
2.178326 2.519675
0.326332 0.269457
Fig. 2. Denitrification efficiency from Stage 1 to Stage 4.
(Ace and Chao 1) were determined by Mothur ver. 1.17.0, and the taxonomy-based analysis used RDP-II Classifier of the Ribosomal Database Project (RDP) and the National Center for Biotechnology Information (NCBI) BLAST. 3. Results and discussion 3.1. NO3 − -N and TN removal of the bio-ceramsite reactor As shown in Fig. 2, the average NO3 − -N and TN removal efficiencies increased from 61.21% to 91.36% and 57.61% to 87.87% from Stage 1 to Stage 2. The highest average NO3 − -N removal efficiency 97.41% and TN removal efficiency 93.93% were achieved at Stage 3 under HRT 24 h and pH 8.0 conditions. However, the NO3 − -N and TN removal efficiencies decreased to 80.31% and 76.21% at Stage 4. The highest average producing N2 27.63 mg/L was observed at Stage 3 when the initial nitrate loading was 29.58 mg/L. Moreover, the concentrations of NO2 − -N and N2 O were always maintained below 0.94 mg/L and 1.03 mg/L during the whole experiments, meaning
that nitrate (29.58 mg/L) was almost completely converted to nitrogen gas (27.63 mg/L) in the denitrification process in the reactor. The lowest nitrate removal performance was observed at Stage 1 due to the very short HRT 5 h and acidic environment. As reported by Wang et al., the nitrate removal efficiency decreased if HRT was too short in the hydrogen dependent denitrification bioreactor [34] because microorganisms did not grow well for degradation of nitrate. On the other hand, hydrogenotrophic denitrification process was easily influenced by pH and many researchers reported that the optimal pH value was 7.5–8.0 [35,38] for this process. In the present study in Stage 1, low pH value 6.0 inhibited the denitrification process due to the reason that the reactivity of hydrogenotrophic denitrifying bacteria was affected by the decomposition of carbonate ions under this environment [39]. For Stage 2, the nitrate removal rate reached above 90% at HRT 16 h and pH 7.0 condition, suggesting that HRT 16 h was appropriate for the system to achieve complete denitrification under neutral environment. This result was in accordance with the research of Ghafari et al. [40], which reported that the suitable HRT was 13.5–30 h for nitrate removal in hydrogenotrophic denitrification process. The best nitrate removal efficiency was observed at Stage 3 due to the reason that pH 8.0 was most suitable for the hydrogenotrophic denitrifying bio-ceramisite reactor to reduce nitrate under HRT 24 h condition. This result was in accordance with the study of Wang et al. [34], which demonstrated that a fiber-based biofilm reactor achieved excellent denitrification efficiency when pH was neutral and alkalescent for nitrate removal. For Stage 4, an obvious decrease of nitrate removal rate was observed due to that high pH 9.0 was harmful to the dominant hydrogenotrophic denitrifying bacteria [34] in the reactor, which was similar with the result of Rezania et al. [41]. 3.2. Bacterial diversity analysis A total of 30,418 and 39,178 bacterial 16S rRNA gene sequences were obtained from Samples C1 and C2, and then used for bacterial community analyses (Table 2). Rarefaction analyses based on OTUs at 3%, 5% and 10% dissimilarity were shown in Fig. 3a, which indicated that the recovered sequences commendably represented the diversity of the bacterial communities in the two samples because the rarefaction curves were approaching plateaus with 99.54% and
Fig. 3. Diversity of bacterial communities in the bio-ceramsite reactor. (a) Rarefaction curves, and (b) rank-abundance curves based on bacterial OTUs at a dissimilarity level of 3%.
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Fig. 4. Taxonomic classification of bacterial 16S rRNA gene reads retrieved from C1 and C2 at phylum level (a) and class level (b) using RDP classifier with a confidence threshold of 80%.
99.55% coverage under 3% dissimilarity for C1 and C2, respectively. It can be seen from Fig. 3a that the species richness of C2 was higher than that of C1. In addition, the values of Ace, Chao, Shannon, and Simpson (Table 2) also demonstrated that the bacterial diversity of C2 was higher than that of C1. Moreover, the rank-abundance curves (Fig. 3b) demonstrated that the two samples contained relatively low proportions of highly abundant bacteria because the curves represented a majority of the reads belonged to rare organisms [42]. Sample C1 was collected from Stage 2 under HRT 16 h and pH 7.0 conditions, while Sample C2 was collected from Stage 4 under HRT 48 h and pH 9.0 conditions. The higher community richness and bacterial diversity of C2 compared to C1 might be due to that more bacterial species preferred alkaline environment in the bioceramsite reactor. On the other hand, long HRT might be beneficial for steady survival of more bacterial species. However, the nitrate removal rate of C1 was higher than that of C2, due to the reason that the dominant autohydrogenotrophic denitrifying bacteria for effective nitrate removal preferred pH 7.0 condition in the bioreactor. Furthermore, this was the first work to evaluate the microbial communities in autohydrogenotrophic denitrifying bio-ceramsite reactor through 454-pyrosequencing analysis. The large numbers of bacterial 16S rRNA gene sequences, and diversity indices such as community richness indices (Chao and Ace) and community diversity indices (Shannon Simpson) and Coverage were very useful for analyzing the microbial communities in this reactor, which demonstrated that 454-pyrosequencing would be an available approach to evaluate the microbial communities of biofilm samples in autohydrogenotrophic denitrification process. 3.3. Bacterial community structure and nitrate removal performance It can be seen from Fig. 4a that the total of identified phyla for Samples C1 and C2 were 20. Sample C1 was mainly composed of Proteobacteria (70.46%), Firmicutes (24.61%), Planctomycetes (1.84%), and Actinobacteria (1.58%). Sample C2 was mainly represented by Firmicutes (75.03%), Proteobacteria (15.39%), Actinobacteria (4.02%), and Planctomycetes (3.06%). Although the major phyla among the two samples were uniform, their relative abundances were different. As shown in Fig. 4b, the total of identified classes for Samples C1 and C2 were 40. The dominant classes in Sample C1 were Gammaproteobacteria (64.57%), Bacilli (15.80%), Clostridia (8.78%), and Alphaproteobacteria (5.53%). Sample C2 was mainly represented by Bacilli (50.53%), Clostridia (24.43%), Alphaproteobacteria (9.97%), and Gammaproteobacteria (4.01%). The four dominant
classes had obviously different abundances among the two samples. In addition, classes Betaproteobacteria, Flavobacteria, and Sphingobacteria were also detected in the two samples. According to many researches, phylum Proteobacteria (main classes contained Alphaproteobacteria, Betaproteobacteria, and Gammaproteobacteria) was one of the most abundant groups in freshwater [25,43]. Karanasiosa et al. [9] reported that most of the hydrogenotrophic denitrifying microorganisms would belong to phylum Proteobacteria. Szekeres et al. [44] studied the bacterial population in a hydrogen dependent denitrification bioreactor, and reported phylum Proteobacteria (contained species Ochrobactrum anthropi, Pseudomonas stutzeri, Paracoccus panthotrophus, and Paracoccus denitrificans) played a vital role in the hydrogenotrophic denitrification process. Wang et al. [34] demonstrated that phylum Firmicutes played important role in denitrification process in a fiber-based biofilm reactor for nitrate removal from groundwater. Huang et al. [43] utilized T-RFLP and 16S rRNA gene clone library to investigate bacterioplankton communities, and reported that Betaproteobacteria and Gammaproteobacteria were the dominant classes. Chen et al. [45] reported that the dominant class was Alphaproteobacteria in biofilms formed on MF membrane with isolation and cloning experiments. Verbaendert et al. [46] detected that a large number of denitrifying bacteria were belonged to class Bacilli. In addition, some bacterial communities from hydrogenotrophic denitrifying biofilms had been identified as the class Flavobacteria [47] and Sphingobacteria [48]. In the study of Park et al. [47], the major populations were Proteobacteria and Flavobacteria in the hydrogenotrophic denitrification biofilm-electrode reactor. Sahu et al. [48] reported that hydrogenotrophic denitrifying class Sphingobacteria participated in the nitrate removal process in a membrane biofilm reactor. In the present study, the mainly reported autohydrogenotrophic denitrifying phyla such as Proteobacteria, Firmicutes and classes such as Gammaproteobacteria, Alphaproteobacteria, Bacilli were all detected in the autohydrogenotrophic denitrifying bio-ceramsite reactor. The high relative abundances demonstrated these phyla and classes played key roles in the autohydrogenotrophic denitrification process, meaning that this bio-ceramsite reactor exhibited excellent nitrate removal performance. It also demonstrated that the microorganisms in this reactor had the ability to use H2 as electron donor and use nitrate as electron acceptor for nitrate removal. The denitrification rate of Sample C1 was higher than that of Sample C2 because the relative abundances of the dominant phylum Proteobacteria and the dominant class Gammaproteobacteria in Sample C1 were higher than of Sample C2 in the bioreactor, suggesting that phylum Proteobacteria and class Gammaproteobacteria exhibited excellent denitrification capacity to convert nitrate to nitrogen gas
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Fig. 5. Relative abundance of each taxonomic genus in Samples C1 and C2. Heat map illustrates the abundance of the top 100 genera in each sample, and scale bar shows the variation ranges of the normalized abundance of the genera.
under neutral environment in the reactor. It was also indicated that dominant phylum Proteobacteria and class Gammaproteobacteria preferred neutral environment for higher denitrification efficiency rather than alkaline environment. However, some unreported autohydrogenotrophic denitrifying bacterial groups such as phyla Planctomycetes, Actinobacteria and class Clostridia also showed high relative abundances in Sample C2 under long HRT and alkaline environment. They also played roles in autohydrogenotrophic denitrification process, and their ecological functions in this bioceramsite reactor remained unclear and needed doing further researches. The similarities of microbial community structures in the two biofilm samples were discussed at genus level by hierarchically clustered heatmap analysis (Fig. 5). The largest genus in Sample C1 was Acinetobacter (58.84%), while Planomicrobium (48.97%) was the dominant genus in Sample C2. Some researchers reported that Acinetobacter was the dominated genus in hydrogen-oxidizing microbial cultures [10,49]. Vasiliadou et al. [10] investigated the hydrogenotrophic denitrification in a batch reactor and demonstrated Acinetobacter exhibited the ability to use hydrogen as
electron donor for nitrate removal. Liessens et al. [49] isolated Acinetobacter from the hydrogenotrophic reactor for the denitrification treatment and proved Acinetobacter played a vital role in the hydrogenotrophic denitrification process. In this study, Sample C1 attained higher NO3 − -N and TN removal efficiency than that of Sample C2 because of the leading role of genus Acinetobacter in Sample C1, meaning that genus Acinetobacter was the key contributors to convert nitrate to nitrogen gas in this autohydrogenotrophic denitrifying bioceramsite reactor under appropriate conditions. In Sample C2, genus Planomicrobium was mainly responsible for the denitrifiaction process. According to many reports, genera Ochrobactrum, Paracoccus [10,48], Pseudomonas [49,50], Hydrogenophaga [51] and Thauera [26] were always observed in hydrogen dependent denitrification reactors. Liessens et al. [49] demonstrated that Pseudomonas played a key role in the hydrogenotrophic denitrification process in a hydrogenotrophic reactor. Zhang et al. [51] reported that Hydrogenophaga played an important role in autohydrogenotrophic denitrification in a hollow fiber membrane biofilm reactor for nitrate removal from drinking water. These reported
Please cite this article in press as: D. Chen, et al., A high-throughput sequencing study of bacterial communities in an autohydrogenotrophic denitrifying bio-ceramsite reactor, Process Biochem (2015), http://dx.doi.org/10.1016/j.procbio.2015.07.006
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genera Ochrobactrum, Paracoccus, Pseudomonas, Hydrogenophaga and Thauera, were all detected in our hydrogenotrophic bioceramsite reactor and participated in the hydrogenotrophic denitrification process, suggesting that this bio-ceramsite reactor exhibited autohydrogenotrophic denitrifying capacity. However, the high abundance of Planomicrobium in Sample C2 might be related to the alkaline environment. Planomicrobium might be a valuable and worth investigating genus for hydrogenotrophic denitrification process. The autohydrogenotrophic denitrification process always involved limited bacterial community compositions, due to the fact that the hydrogenotrophic denitrifying environment was highly selective [9]. The bacteria in this hydrogenotrophic denitrifying system must have the ability to use nitrate as electron acceptor and use H2 as electron donor, and grow with inorganic carbon under anaerobic conditions in order to realize hydrogen dependent denitrification. Furthermore, the main interactions between microorganisms in the reactor were competition and synergy. Competition refers to the process that various microorganisms competed for nitrate source, inorganic carbon source, and electron donor hydrogen gas for self-growth and degrading nitrate. In addition, synergy refers to microorganisms’ mutual use of each other. For instance, some nitrate reducing bacteria convert nitrate into nitrite, then nitrite can be used by nitrite reducing bacteria for electron acceptor to convert nitrite to nitrogen gas. 4. Conclusions The hydrogenotrophic denitrifying bio-ceramsite reactor exhibited excellent nitrate removal performance, and the highest NO3 − -N and TN removal efficiencies reached 97.41% and 93.93%. Pyrosequencing analysis of the biofilm samples showed high bacterial diversity, and many effective hydrogen dependent denitrifying phyla, classes and genera were detected in the bio-ceramsite reactor. Phylum Proteobacteria, class Gammaproteobacteria, and genus Acinetobacter were the dominant contributors for effective nitrate removal performance in this bio-ceramsite reactor under HRT 16 h and pH 7.0 conditions. The hydrogenotrophic denitrification process involved limited bacterial community compositions, due to that the hydrogenotrophic denitrifying environment was highly selective. Acknowledgements This work was financially supported by the National Natural Science Foundation of China (NSFC) (51378400) and the National Science and Technology Pillar Program (2014BAL04B04). Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at doi:10.1016/j.procbio.2015.07.006 References [1] WHO, Nitrate and nitrite in drinking-water: Background document for development of WHO Guidelines for Drinking-water Quality, 2003. [2] S. Aslan, A. Turkman, Nitrate and pesticides removal from contaminated water using biodenitrification reactor, Process Biochem. 41 (2006) 882–886. [3] S¸. Aslan, Combined removal of pesticides and nitrates in drinking waters using biodenitrification and sand filter system, Process Biochem. 40 (2005) 417–424. [4] C. Della Rocca, V. Belgiorno, S. Meric¸, An heterotrophic/autotrophic denitrification (HAD) approach for nitrate removal from drinking water, Process Biochem. 41 (2006) 1022–1028. [5] J.W. Lee, K.H. Lee, K.Y. Park, S.K. Maeng, Hydrogenotrophic denitrification in a packed bed reactor: effects of hydrogen-to-water flow rate ratio, Bioresour. Technol. 101 (2010) 3940–3946.
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