Article pubs.acs.org/est
Pyrosequencing Reveals the Key Microorganisms Involved in Sludge Alkaline Fermentation for Efficient Short-Chain Fatty Acids Production Xiong Zheng, Yinglong Su, Xiang Li, Naidong Xiao, Dongbo Wang, and Yinguang Chen* State Key Laboratory of Pollution Control and Resource Reuse, School of Environmental Science and Engineering, Tongji University, 1239 Siping Road, Shanghai 200092, China S Supporting Information *
ABSTRACT: Short-chain fatty acids (SCFAs) have been regarded as the excellent carbon source of wastewater biological nutrient removal, and sludge alkaline (pH 10) fermentation has been reported to achieve highly efficient SCFAs production. In this study, the underlying mechanisms for the improved SCFAs production at pH 10 were investigated by using 454 pyrosequencing and fluorescent in situ hybridization (FISH) to analyze the microbial community structures in sludge fermentation reactors. It was found that sludge fermentation at pH 10 increased the abundances of Pseudomonas sp. and Alcaligenes sp., which were able to excrete extracellular proteases and depolymerases, and thus enhanced the hydrolysis of insoluble sludge protein and polyhydroxyalkanoates (PHA). Meanwhile, the abundance of acid-producing bacteria (such as Clostridium sp.) in the reactor of pH 10 was also higher than that of uncontrolled pH, which benefited the acidification of soluble organic substrates. Further study indicated that sludge fermentation at pH 10 significantly decreased the number of methanogenic archaea, resulting in lower SCFAs consumption and lower methane production. Therefore, anaerobic sludge fermentation under alkaline conditions increased the abundances of bacteria involved in sludge hydrolysis and acidification, and decreased the abundance of methanogenic archaea, which favored the competition of bacteria over methanogens and resulted in the efficient production of SCFAs.
■
phosphorus.6 Hence, the SCFAs production from anaerobic sludge fermentation might solve this problem. Both laboratory and pilot scale studies showed that WAS could be highly degraded and converted to large amounts of SCFAs under alkaline conditions (especially pH 10).7,8 It is well-known that hydrolysis is a rate-limiting step of anaerobic sludge fermentation, and the competition between bacteria involved in sludge hydrolysis and acidification and methanogenic archaea responsible for SCFAs consumption determines the main final product of sludge fermentation being SCFAs or methane. However, to date, the microbes and their competition in sludge hydrolysis, acidification, and methanogenesis at pH 10 have not yet been fully investigated. Recently, to avoid the isolation and cultivation of microorganisms, culture-independent genomic-based approaches, such as a clone library and fluorescent in situ hybridization (FISH), have been widely used to explore the diversity of bacteria or archaea in anaerobic sludge fermentation under pH uncontrolled conditions.9−11 For example, to study the diversity of microorganisms in an anaerobic sludge digester, two clone libraries were constructed which contained, respectively, 579
INTRODUCTION Activated sludge process is the most widely used method for treating wastewater (especially municipal wastewater) in the world. However, large amounts of waste activated sludge (WAS) are produced in this process.1 It is therefore necessary to find an efficient way to treat this WAS. Since WAS has a high content of organic matter, it can be reused to generate useful products, such as short-chain fatty acids (SCFAs)2 or methane,3 by anaerobic fermentation. Microorganisms play important roles in anaerobic sludge fermentation, because it is a complex process involving large amounts of bacterial and archaeal populations to carry out sludge hydrolysis, acidification, and methanogenesis. However, most microbial studies on anaerobic sludge fermentation were related to methane production at pH 7 or uncontrolled pH. For example, Actinobacteria and Firmicutes were observed to be the major bacterial phyla, and Methanosaeta sp. was the most abundant archaeal population in a full scale anaerobic sludge digester.4 Similarly, some researchers reported that the core group of bacteria in anaerobic sludge digesters consisted of Chlorof lexi, Betaproteobacteria, Bacteroidetes, and Synergistetes, whereas the archaeal community was mainly affiliated to Methanosarcinales, Methanomicrobiales, and Arc I phylogenetic groups.5 SCFAs have been regarded as the excellent carbon source of wastewater biological nutrient removal, and their shortage in wastewater can lead to poor removal of nitrogen and © 2013 American Chemical Society
Received: Revised: Accepted: Published: 4262
January 15, 2013 March 22, 2013 April 1, 2013 April 1, 2013 dx.doi.org/10.1021/es400210v | Environ. Sci. Technol. 2013, 47, 4262−4268
Environmental Science & Technology
Article
DNA Extraction and Quantification of Total Bacteria and Archaea. For each set, DNA was extracted from sludge of three replicate reactors using the FastDNA Kit (BIO 101, Vista, CA) according to the manufacture’s instruction, and then pooled together. In real-time PCR assays, the universal primers 341F (5′-CCTACGGGAGGCAGCAG-3′) and 534R (5′ATTACCGCGGCTGCTGG-3′) were used for the quantification of total bacteria,15 whereas the primers Arch344F (5′ACGGGGYGCAGCAGGCGCGA-3′) and Arch915R (5′GTGCTCCCCCGCCAATTCCT-3′) were adopted for total archaea.16 PCR reactions were performed via a StepOne RealTime PCR System (Applied Biosystems, Foster City, USA) in a total volume of 20 μL containing 1 × SYBR Green PCR Master Mix (Invitrogen), 0.5 μM each primer, and 1 μL of template DNA. According to the literature,17 the amplification program consisted of an initial denaturation at 95 °C for 5 min, followed by 30 cycles of denaturing at 95 °C for 30 s, annealing at 55 °C for 30 s, and extension at 72 °C for 30 s, followed by a final extension at 72 °C for 5 min. All PCR assays were performed using three replicates per sample, and contained the control reactions without template DNA. The copy number of total bacteria (or archaea) per g TSS was calculated using a standard curve generated by using 10-fold serial dilutions of linearized plasmids containing the gene fragment of bacteria (or archaea) as a template. PCR Amplification, Product Purification, and Pyrosequencing. In order to conduct the pyrosequencing, three independent PCR reactions were carried out. The primers for Bacteria were 341F and 1073R,18 whereas those for Archaea were Arch344F and Arch915R. To achieve the sample multiplexing during pyrosequencing, barcodes were incorporated between the 454 adaptor and forward primer. PCR reactions were performed in a total volume of 20 μL containing 1 × Ex Taq reaction buffer (TaKaRa, Japan), 0.25 mM dNTPs, 5 μM each primer, 1.5 mM MgCl2, 2 U Ex Taq polymerase, and 0.5 μL of template DNA. It was reported in the literature that the PCR amplification program contained an initial denaturation at 95 °C for 5 min, followed by 25 cycles of denaturing at 95 °C for 30 s, annealing at 55 °C for 30 s, and extension at 72 °C for 30 s, followed by a final extension at 72 °C for 5 min.15,19 The PCR products of three independent reactions were pooled together, purified with the QIAquick PCR Purification Kit (Qiagen, Valencia, CA), and quantified using a NanoDrop spectrophotometer (NanoDrop Technologies, Wilmington, DE). Before pyrosequencing, the PCR products of different samples were normalized in equimolar amounts in the final mixture, which was used to construct the PCR amplicon libraries according to the manufacture’s instruction (454 Life Sciences). Pyrosequencing was carried out on a Roche 454 GS FLX+ Titanium platform, and the raw sequences have been deposited in the NCBI Short Read Archive (SRA) database under the accession numbers SRA058043 for bacterial sequences and SRA058572 for archaeal sequences. Processing of Pyrosequencing Data. Raw sequences from pyrosequencing were sorted based on the specific barcodes of sludge samples using the Pipeline Initial Process tool at the Ribosomal Database Project (RDP). The adapters, barcodes, and primers in all raw sequences were trimmed,20 and the sequences containing ambiguous nucleotides or shorter than 350 bp in length were removed.21 The remaining sequences were checked for the potential chimeras using Chimera Slayer, grouped into OTUs using the 97% and 95%
and 246 almost full-length 16S rRNA gene sequences of bacteria and archaea, and it was found that Bacteroidetes, Grampositives, and Proteobacteria were the main bacteria, whereas the archaea belonged to Euryarchaeota and Crenarchaeota.9 However, constructing 16S rRNA gene clone libraries is a time-consuming and low-throughput method, which might underestimate the diversity of microorganisms. Therefore, in recent years, high-throughput sequencing technologies such as 454 pyrosequencing have been developed to fully explore the microbial diversity in the environment, such as conventional sludge digesters12 or biogas plants.13,14 In this study, two sets of anaerobic sludge fermentation reactors were respectively operated under the conditions of pH 10 and uncontrolled pH over 100 days, and the mechanisms of the improved SCFAs production under the pH 10 condition were investigated by analyzing the key microorganisms involved in sludge hydrolysis, acidification, and methanogenesis. By using 454 pyrosequencing, the functional populations of bacteria and archaea under conditions of pH 10 and uncontrolled pH were investigated, and the results were further validated by FISH analysis. Meanwhile, the real-time PCR assays were used to quantify the numbers of total bacteria and archaea in order to explore the competition between bacteria and methanogenic archaea in the fermentation reactors of pH 10 and uncontrolled pH. To the best of our knowledge, this is the first report concerning the key microorganisms involved in sludge hydrolysis, acidification, and methanogenesis under alkaline conditions.
■
MATERIALS AND METHODS Source and Characteristics of WAS. The WAS used in this study was obtained from the secondary sedimentation tank of a municipal wastewater treatment plant (WWTP) in Shanghai, China, and this WWTP was operated with a traditional biological nutrient removal process. Before anaerobic fermentation, the sludge was concentrated by settling at 4 °C for 24 h, and its main characteristics after settlement were as follows: pH 6.9 ± 0.1, TSS (total suspended solids) 12680 ± 870 mg/L, VSS (volatile suspended solids) 9470 ± 710 mg/L, total protein 9130 ± 490 mg chemical oxygen demand (COD)/L, total carbohydrate 1310 ± 82 mg COD/L, total polyhydroxyalkanoates (PHA) 735 ± 52 mg COD/L, and total lipid 180 ± 10 mg COD/L. Operation of Semi-Continuous Fermentation Reactors. Two sets of semi-continuous fermentation reactors with three replicate reactors in each set were anaerobically operated at 21 ± 1 °C, and each reactor had a working volume of 5 L. During the entire fermentation process, the fermentation pH of one set was maintained at pH 10.0 ± 0.2 by adding 2 M sodium hydroxide (NaOH), while the other was used as the control (uncontrolled pH). After the addition of sludge, these fermentation reactors were flushed with nitrogen gas to remove oxygen, sealed, and mechanically stirred at a speed of 80 rpm. According to our previous publication, 625 mL of fermentation mixture was wasted every day from each reactor, followed by adding 625 mL of fresh sludge, which resulted in the sludge retention time (SRT) of 8 days.7 The concentrations of SCFAs and methane in these reactors were measured during the fermentation period, and were observed to reach relatively stable levels after 30 days of operation. For the analysis of functional bacterial and archaeal populations in fermentation reactors, sludge samples were collected before replacing fermentation mixture by fresh sludge on day 100. 4263
dx.doi.org/10.1021/es400210v | Environ. Sci. Technol. 2013, 47, 4262−4268
Environmental Science & Technology
Article
Figure 1. SCFAs accumulation (A) and methane production (B) in the fermentation reactors of pH 10 and uncontrolled pH during the fermentation period of 100 d. The SCFAs consisted of acetic, propionic, iso-butyric, n-butyric, iso-valeric, and n-valeric acids. Error bars represent standard deviations of triplicate measurements.
Table 1. Summary of Pyrosequencing Data for the Fermentation Reactors of pH 10 and Uncontrolled pH bacterial community number of sequences total length of sequences (bp) average length of sequences (bp) operational taxonomic units (OTUs)a ACE richness estimatora chao1 richness estimatora a
archaeal community
pH 10
uncontrolled pH
pH 10
uncontrolled pH
24 622 14 725 958 598 1159 3748−4315 2446−3184
28 685 15 782 675 550 6102 32572−34638 17110−19449
25 498 13 833 551 542 432 812−996 627−875
23 477 12 757 309 543 612 1259−1503 946−1276
It was defined by the 97% identity threshold (i.e., 3% dissimilarity level).
■
RESULTS AND DISCUSSION SCFAs Accumulation and Methane Production in the Semi-Continuous Fermentation Reactors of pH 10 and Uncontrolled pH. Figure 1 demonstrates the variations of the concentrations of SCFAs and methane in the fermentation reactors of pH 10 and uncontrolled pH during the fermentation period of 100 days. It can be found that the average concentration of SCFAs in the reactor of pH 10 was 1443 ± 45 mg COD/L, whereas that of uncontrolled pH was only 212 ± 10 mg COD/L (Figure 1A). On the other hand, the methane production in the fermentation reactor of pH 10 was observed to be 540 bp remained after raw sequence processing and denoising. Previous studies usually collected >16 000 effective sequences for each sample to analyze their microbial communities.12,20 Figure 2 shows that when the sequencing depth of each sludge sample was >10 000, the Shannon diversities under the fermentation conditions of pH 10 and uncontrolled pH were not obviously increased, indicating that the library size of >23 000 effective sequences in this study was satisfied to fully characterize the bacterial and archaeal communities in these sludge fermentation reactors. To estimate the phylogenetic diversities of bacterial and archaeal communities in the fermentation reactors of pH 10 and uncontrolled pH, the trimmed sequences were grouped into OTUs using the 97% identity threshold. Table 1 demonstrates that the bacterial sequences from the reactor of uncontrolled pH were identified to be 6102 OTUs, which was similar to 5926 OTUs of conventional anaerobic digester reported in the literature.12 However, the number of bacterial OTUs under the pH 10 condition was 1159, indicating that controlling the fermentation pH at pH 10 reduced the bacterial diversity, which was confirmed by the rarefaction curves (SI Figure S1). All species richness estimators such as ACE and Chao1 indices at pH 10 were also lower than those at uncontrolled pH (Table 1). Similar results were observed regarding the archaeal communities in the fermentation reactors of pH 10 and uncontrolled pH. Previous publication documented that the bacterial (or archaeal) PCR amplicons from sludge fermentation reactors were grouped into only 238−514 (or 8−26) OTUs according to the clone library method.5 It can be found that compared with the traditional clone library, 454 pyrosequencing revealed much more bacterial 4265
dx.doi.org/10.1021/es400210v | Environ. Sci. Technol. 2013, 47, 4262−4268
Environmental Science & Technology
Article
10.29 Thus, the higher abundance of Pseudomonas sp. in the fermentation reactor of pH 10 obviously benefited the hydrolysis of particulate protein in WAS. On the other hand, depending on the extracellular depolymerases such as PHB depolymerase and PHV depolymerase, the insoluble PHA could be hydrolyzed into water-soluble monomeric compositions (3-hydroxybutyrate and 3-hydroxyvalerate),30 which were easily converted to SCFAs by acid-producing bacteria.31 Previous publication reported that the extracellular PHB depolymerase and PHV depolymerase were mainly from the genera of Alcaligenes and Pseudomonas, such as Alcaligenes faecalis,32 Pseudomonas lemoignei,33 and Pseudomonas stutzeri.34 Figure 5 shows that the ratio of soluble PHA to total PHA in the reactor of pH 10 was also higher than that in the control, indicating that the hydrolysis of insoluble PHA in sludge were significantly improved under the pH 10 condition. The enhanced hydrolysis efficiency of sludge PHA under alkaline conditions was due to the higher abundances of Alcaligenes sp. and Pseudomonas sp. Meanwhile, Clostridium sp. was usually reported to carry out the acidification process,35 and FISH analysis validated that the abundance of this bacterium in the reactor of pH 10 was more than 2 times of that of uncontrolled pH, which also benefited the SCFAs production from anaerobic sludge fermentation. Effect of Alkaline pH on Methanogenic Archaea Involved in Sludge Fermentation. It is well-known that the produced SCFAs in the sludge acidification process will be consumed in the subsequent methanogenesis stage. Thus, the previous publication reported that methanogens degraded large amounts of SCFAs and converted to methane in the sludge fermentation reactor of uncontrolled pH.36 It can be seen from Figure 1B that the methane production was largely inhibited, when sludge fermentation was carried out under the pH 10 condition. However, to date, the reasons for the low methane production from sludge alkaline fermentation have not yet been fully studied. The literature usually pointed out that most methanogens grew over a relative narrow pH range between 6 and 8.37 Only a few methanogenic archaea were capable of growing under acidic38 or alkaline conditions.39 However, Table 1 demonstrates that the archaeal OTUs involved in the reactors of pH 10 and uncontrolled pH were 532 and 612, respectively, indicating that the archaeal populations in sludge fermentation reactors showed highly diverse under the conditions of pH 10 and uncontrolled pH. Figure 6 further illustrates the genus level distributions of archaeal populations in these sludge fermentation reactors. In the reactor of uncontrolled pH, the genera of Methanosaeta, Methanobacterium, and Methanobrevibacter accounted for 30.1%, 22.6%, and 20.2% of total archaeal sequences, respectively. However, the archaeal sequences from the reactor of pH 10 was mainly related to Methanosaeta sp. (55.9%) and Methanospirillum sp. (35.9%), while the relative abundances of Methanobacterium sp. and Methanobrevibacter sp. were decreased to 2.7% and 2.8%, respectively. It was reported in the literature that cell surface structures of methanogens were diverse, and could be roughly divided into pseudomurein, surface layer, methanochondroitin, and sheath.40 Compared with Methanobacterium sp. and Methanobrevibacter sp., the genera of Methanosaeta and Methanospirillum had a proteinaceous sheath outside of their individual cell envelope layers.40 This sheath exhibited a very low porosity, and thus was an unusually stable layer that could resist dissociation by conventional treatments,40,41 which might be one reason for
and unclassified bacteria (24.2%), while under the pH 10 condition the sequences closely related to Pseudomonas sp., Alcaligenes sp., and Clostridium sp. accounted for 61.6%, 10.3%, and 8.9% of total bacterial sequences, respectively. Furthermore, FISH analysis validated that the abundances of Pseudomonas sp., Alcaligenes sp., and Clostridium in the reactor of pH 10 accounted for 67%, 12%, and 8% of the total biomass, respectively, whereas the corresponding data were 31%, 4%, and 3% in the reactor of uncontrolled pH (SI Figure S2). Realtime PCR assays indicated that the average numbers of total bacteria in the reactors of uncontrolled pH and pH 10 were 8.7 × 109 and 5.4 × 109 copies/g TSS, respectively, which had no significant difference. Therefore, the genera of Pseudomonas, Alcaligenes, and Clostridium were found to be the key functional microorganisms in the reactor of pH 10. It was reported in the literature that the hydrolysis of complex organic substances in sludge was the rate-limiting step in anaerobic sludge fermentation processes (Figure 4).26 The
Figure 4. Hydrolysis of solid-state sludge protein and PHA to watersoluble compositions.
main organic substances of WAS were particulate protein, carbohydrate, and PHA. As the hydrolysis of carbohydrate was easier than that of protein or PHA,27 the hydrolysis of protein and PHA should be enhanced in order to produce more soluble organic matter. Figure 5 shows that the ratio of soluble protein
Figure 5. Ratios of soluble protein to total protein and soluble PHA to total PHA under the conditions of the control and pH 10. Error bars represents standard deviations of triplicate measurements.
to total protein in the reactor of pH 10 was much higher than that in the control, indicating that sludge fermentation at pH 10 significantly improved the hydrolysis of particulate protein. Previous literature pointed out that Pseudomonas sp. could greatly produce and secrete proteases such as alkaline protease and elastase,28 and these extracellular proteases were the most important enzymes to carry out the hydrolysis of sludge protein. Further studies observed that the activities of proteases were prominent under alkaline conditions, especially at pH 4266
dx.doi.org/10.1021/es400210v | Environ. Sci. Technol. 2013, 47, 4262−4268
Environmental Science & Technology
Article
Figure 6. Genus level distributions of archaeal populations in the fermentation reactors of pH 10 (A) and uncontrolled pH (B).
■
the predominance of Methanosaeta sp. and Methanospirillum sp. under the pH 10 condition. Previous publication has reported that Methanosaeta sp. is the obligate acetoclastic methanogenic archaea.37 Thus, the higher level of acetic acid could benefit the growth of this methanogen, which was consistent with more Methanosaeta sp. involved in the reactor of pH 10 than in the control reactor (SI Figure S3). The genera of Methanobacterium and Methanobrevibacter were the obligate hydrogenotrophic methanogens, which preferred to use H2/CO2, but not acetic acid,42 which might be the reason for the significant decrease of Methanobacterium sp. and Methanobrevibacter sp. in the reactor of pH 10. The average numbers of total archaea in the reactors of pH 10 and uncontrolled pH were 6.8 × 105 and 3.5 × 107 copies/g TSS, respectively, indicating that controlling the fermentation pH at pH 10 significantly decreased the number of total methanogenic archaea, which was the main reason for the low methane production in sludge alkaline fermentation. As seen from this study, anaerobic sludge fermentation at pH 10 achieved highly efficient production of SCFAs compared with conventional sludge digestion, and the higher accumulation of SCFAs was due to the enhancement of sludge hydrolysis/acidification and the inhibition of methanogenesis. Further investigations found that sludge fermentation under the pH 10 condition did not change the numbers of total bacteria in the reactors, but significantly increased the abundances of the genera of Pseudomonas and Alcaligenes. These key microorganisms were able to excrete the extracellular proteases and depolymerases, which enhanced the hydrolysis of sludge protein and PHA under the alkaline condition. Meanwhile, sludge fermentation at pH 10 increased the abundance of acidproducing bacteria such as Clostridium sp., which benefited the subsequent acidification process. Furthermore, the phylogenetic analysis revealed that the archaeal populations were highly diverse in the reactor of pH 10, which has never been reported in previous publications. However, compared with the control, the number of total archaea in the reactor of pH 10 was significantly decreased, which was responsible for the low methane production in sludge alkaline fermentation. Therefore, the increased key bacteria involved in sludge hydrolysis/ acidification and the decreased methanogenic archaea were the main reasons for the higher production of SCFAs under the pH 10 condition.
■
AUTHOR INFORMATION
Corresponding Author
*Phone: +86 21 65981263; fax: +86 21 65986313; e-mail:
[email protected]. Notes
The authors declare no competing financial interest.
■
ACKNOWLEDGMENTS This work was financially supported by the National Hi-Tech Research and Development Program of China (863 Program) (2011AA060903) and the National Natural Science Foundation of China (51278354 and 51178324).
■
REFERENCES
(1) Appels, L.; Baeyens, J.; Degreve, J.; Dewil, R. Principles and potential of the anaerobic digestion of waste-activated sludge. Prog. Energy Combust. Sci. 2008, 34, 755−781. (2) Feng, L.; Chen, Y.; Zheng, X. Enhancement of waste activated sludge protein conversion and volatile fatty acids accumulation during waste activated sludge anaerobic fermentation by carbohydrate substrate addition: The effect of pH. Environ. Sci. Technol. 2009, 43, 4373−4380. (3) Zhang, D.; Chen, Y.; Zhao, Y.; Zhu, X. New sludge pretreatment method to improve methane production in waste activated sludge digestion. Environ. Sci. Technol. 2010, 44, 4802−4808. (4) Ariesyady, H. D.; Ito, T.; Okabe, S. Functional bacterial and archaeal community structures of major trophic groups in a full-scale anaerobic sludge digester. Water Res. 2007, 41, 1554−1568. (5) Riviere, D.; Desvignes, V.; Pelletier, E.; Chaussonnerie, S.; Guermazi, S.; Weissenbach, J.; Li, T.; Camacho, P.; Sghir, A. Towards the definition of a core of microorganisms involved in anaerobic digestion of sludge. ISME J. 2009, 3, 700−714. (6) Tong, J.; Chen, Y. Enhanced biological phosphorus removal driven by short-chain fatty acids produced from waste activated sludge alkaline fermentation. Environ. Sci. Technol. 2007, 41, 7126−7130. (7) Yuan, H.; Chen, Y.; Zhang, H.; Jiang, S.; Zhou, Q.; Gu, G. Improved bioproduction of short-chain fatty acids (SCFAs) from excess sludge under alkaline conditions. Environ. Sci. Technol. 2006, 40, 2025−2029. (8) Li, X.; Chen, H.; Hu, L.; Yu, L.; Chen, Y.; Gu, G. Pilot-scale waste activated sludge alkaline fermentation, fermentation liquid separation, and application of fermentation liquid to improve biological nutrient removal. Environ. Sci. Technol. 2011, 45, 1834−1839. (9) Chouari, R.; Le Paslier, D.; Daegelen, P.; Ginestet, P.; Weissenbach, J.; Sghir, A. Novel predominant archaeal and bacterial groups revealed by molecular analysis of an anaerobic sludge digester. Environ. Microbiol. 2005, 7, 1104−1115. (10) Hori, T.; Haruta, S.; Ueno, Y.; Ishii, M.; Igarashi, Y. Dynamic transition of a methanogenic population in response to the concentration of volatile fatty acids in a thermophilic anaerobic digester. Appl. Environ. Microbiol. 2006, 72, 1623−1630. (11) Zhang, P.; Chen, Y.; Zhou, Q.; Zheng, X.; Zhu, X.; Zhao, Y. Understanding short-chain fatty acids accumulation enhanced in waste
ASSOCIATED CONTENT
* Supporting Information S
This file contains Table S1 and Figures S1−S3. This material is available free of charge via the Internet at http://pubs.acs.org. 4267
dx.doi.org/10.1021/es400210v | Environ. Sci. Technol. 2013, 47, 4262−4268
Environmental Science & Technology
Article
activated sludge alkaline fermentation: Kinetics and microbiology. Environ. Sci. Technol. 2010, 44, 9343−9348. (12) Nelson, M. C.; Morrison, M.; Yu, Z. T. A meta-analysis of the microbial diversity observed in anaerobic digesters. Bioresour. Technol. 2011, 102, 3730−3739. (13) Schluter, A.; Bekel, T.; Diaz, N. N.; Dondrup, M.; Eichenlaub, R.; Gartemann, K. H.; Krahn, I.; Krause, L.; Kromeke, H.; Kruse, O.; Mussgnug, J. H.; Neuweger, H.; Niehaus, K.; Puhler, A.; Runte, K. J.; Szczepanowski, R.; Tauch, A.; Tilker, A.; Viehover, P.; Goesmann, A. The metagenome of a biogas-producing microbial community of a production-scale biogas plant fermenter analysed by the 454pyrosequencing technology. J. Biotechnol. 2008, 136, 77−90. (14) Krober, M.; Bekel, T.; Diaz, N. N.; Goesmann, A.; Jaenicke, S.; Krause, L.; Miller, D.; Runte, K. J.; Viehover, P.; Puhler, A.; Schluter, A. Phylogenetic characterization of a biogas plant microbial community integrating clone library 16S-rDNA sequences and metagenome sequence data obtained by 454-pyrosequencing. J. Biotechnol. 2009, 142, 38−49. (15) Muyzer, G.; de Waal, E. C.; Uitterlinden, A. G. Profiling of complex microbial populations by denaturing gradient gel electrophoresis analysis of polymerase chain reaction-amplified genes coding for 16S rRNA. Appl. Environ. Microbiol. 1993, 59, 695−700. (16) Raskin, L.; Stromley, J. M.; Rittmann, B. E.; Stahl, D. A. Groupspecific 16S rRNA hybridization probes to describe natural communities of methanogens. Appl. Environ. Microbiol. 1994, 60, 1232−1240. (17) Moore, T. A.; Xing, Y.; Lazenby, B.; Lynch, M. D. J.; Schiff, S.; Robertson, W. D.; Timlin, R.; Lanza, S.; Ryan, M. C.; Aravena, R.; Fortin, D.; Clark, I. D.; Neufeld, J. D. Prevalence of anaerobic ammonium-oxidizing bacteria in contaminated groundwater. Environ. Sci. Technol. 2011, 45, 7217−7225. (18) Uroz, S.; Oger, P.; Morin, E.; Frey-Klett, P. Distinct ectomycorrhizospheres share similar bacterial communities as revealed by pyrosequencing-based analysis of 16S rRNA genes. Appl. Environ. Microbiol. 2012, 78, 3020−3024. (19) Liu, R.; Li, D.; Gao, Y.; Zhang, Y.; Wu, S.; Ding, R.; Hesham, A. E. L.; Yang, M. Microbial diversity in the anaerobic tank of a full-scale produced water treatment plant. Process Biochem. 2010, 45, 744−751. (20) Zhang, T.; Shao, M.; Ye, L. 454 pyrosequencing reveals bacterial diversity of activated sludge from 14 sewage treatment plants. ISME J. 2012, 6, 1137−1147. (21) Claesson, M. J.; O’Sullivan, O.; Wang, Q.; Nikkila, J.; Marchesi, J. R.; Smidt, H.; de Vos, W. M.; Ross, R. P.; O’Toole, P. W. Comparative analysis of pyrosequencing and a phylogenetic microarray for exploring microbial community structures in the human distal intestine. PLoS One 2009, 4, e6669. (22) Sogin, M. L.; Morrison, H. G.; Huber, J. A.; Mark Welch, D.; Huse, S. M.; Neal, P. R.; Arrieta, J. M.; Herndl, G. J. Microbial diversity in the deep sea and the underexplored ″rare biosphere″. Proc. Natl. Acad. Sci. U. S. A. 2006, 103, 12115−12120. (23) Zheng, X.; Chen, Y.; Wu, R. Long-term effects of titanium dioxide nanoparticles on nitrogen and phosphorus removal from wastewater and bacterial community shift in activated sludge. Environ. Sci. Technol. 2011, 45, 7284−7290. (24) Jiang, Y.; Chen, Y.; Zheng, X. Efficient polyhydroxyalkanoates production from a waste-activated sludge alkaline fermentation liquid by activated sludge submitted to the aerobic feeding and discharge process. Environ. Sci. Technol. 2009, 43, 7734−7741. (25) APHA. Standard Methods for the Examination of Water and Wastewater, 20th ed.; American Public Health Association: Washington, DC, 1998. (26) Vavilin, V. A.; Rytov, S. V.; Lokshina, L. Y. A description of hydrolysis kinetics in anaerobic degradation of particulate organic matter. Bioresour. Technol. 1996, 56, 229−237. (27) Yang, Q.; Luo, K.; Li, X.; Wang, D.; Zheng, W.; Zeng, G.; Liu, J. Enhanced efficiency of biological excess sludge hydrolysis under anaerobic digestion by additional enzymes. Bioresour. Technol. 2010, 101, 2924−2930.
(28) Guzzo, J.; Pages, J. M.; Duong, F.; Lazdunski, A.; Murgier, M. Pseudomonas aeruginosa alkaline protease: Evidence for secretion genes and study of secretion mechanism. J. Bacteriol. 1991, 173, 5290−5297. (29) Whiteley, C. G.; Heron, P.; Pletschke, B.; Rose, P. D.; Tshivhunge, S.; Van Jaarsveld, F. P.; Whittington-Jones, K. The enzymology of sludge solubilisation utilising sulphate reducing systems: Properties of proteases and phosphatases. Enzyme Microb. Technol. 2002, 31, 419−424. (30) Jendrossek, D. Microbial degradation of polyesters: A review on extracellular poly(hydroxyalkanoic acid) depolymerases. Polym. Degrad. Stab. 1998, 59, 317−325. (31) Reischwitz, A.; Stoppok, E.; Buchholz, K. Anaerobic degradation of poly-3-hyroxylbutyrate and poly-3-hydroxybutyrate-co-3-hydroxyvalerate. Biodegradation 1997, 8, 313−319. (32) Saito, T.; Suzuki, K.; Yamamoto, J.; Fukui, T.; Miwa, K.; Tomita, K.; Nakanishi, S.; Odani, S.; Suzuki, J.; Ishikawa, K. Cloning, nucleotide sequence, and expression in Escherichia coli of the gene for poly(3-hydroxybutyrate) depolymerase from Alcaligenes faecalis. J. Bacteriol. 1989, 171, 184−189. (33) Schober, U.; Thiel, C.; Jendrossek, D. Poly(3-hydroxyvalerate) depolymerase of Pseudomonas lemoignei. Appl. Environ. Microbiol. 2000, 66, 1385−1392. (34) Ohura, T.; Kasuya, K.; Doi, Y. Cloning and characterization of the polyhydroxybutyrate depolymerase gene of Pseudomonas stutzeri and analysis of the function of substrate-binding domains. Appl. Environ. Microbiol. 1999, 65, 189−197. (35) Temudo, M. F.; Muyzer, G.; Kleerebezem, R.; van Loosdrecht, M. C. M. Diversity of microbial communities in open mixed culture fermentations: Impact of the pH and carbon source. Appl. Microbiol. Biotechnol. 2008, 80, 1121−1130. (36) Chen, Y.; Jiang, S.; Yuan, H.; Zhou, Q.; Gu, G. Hydrolysis and acidification of waste activated sludge at different pHs. Water Res. 2007, 41, 683−689. (37) Garcia, J. L.; Patel, B. K. C.; Ollivier, B. Taxonomic, phylogenetic, and ecological diversity of methanogenic Archaea. Anaerobe 2000, 6, 205−226. (38) Brauer, S. L.; Cadillo-Quiroz, H.; Yashiro, E.; Yavitt, J. B.; Zinder, S. H. Isolation of a novel acidiphilic methanogen from an acidic peat bog. Nature 2006, 442, 192−194. (39) Zhilina, T. N.; Zavarzin, G. A. Alkaliphilic anaerobic community at pH 10. Curr. Microbiol. 1994, 29, 109−112. (40) Albers, S. V.; Meyer, B. H. The archaeal cell envelope. Nat. Rev. Microbiol. 2011, 9, 414−426. (41) Beveridge, T. J.; Stewart, M.; Doyle, R. J.; Sprott, G. D. Unusual stability of the Methanospirillum hungatei sheath. J. Bacteriol. 1985, 162, 728−737. (42) Leclerc, M.; Delgenes, J. P.; Godon, J. J. Diversity of the archaeal community in 44 anaerobic digesters as determined by single strand conformation polymorphism analysis and 16S rDNA sequencing. Environ. Microbiol. 2004, 6, 809−819.
4268
dx.doi.org/10.1021/es400210v | Environ. Sci. Technol. 2013, 47, 4262−4268
