Qualitative and quantitative assessment of microbial community in batch anaerobic digestion of secondary sludge

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    Available online 24 July 2010

    Keywords:

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    16S rRNA gene concentration. The microbial community structures showed continuous shifts within four

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    reaction is performed by the archaeal group that produces meth-ane using the acidogenic products. Complete mineralization of or-ganic materials is dependent on the concerted activity of theseinteracting microbial populations. Therefore, a comprehensiveunderstanding of the microbial behavior is a basic requirementfor fundamental improvement of anaerobic digestion process(Karakashev et al., 2005).

    of microbial communities in transitional states. This communitytransition, particularly during start-up, is notable because a suc-cessful start-up is crucial for long-term digester stability and ef-ciency (Leclerc et al., 2001; Lee et al., 2009b).

    Therefore, this study aimed to investigate microbial communityshifts during a batch anaerobiosis of secondary sludge. A batch pro-cess is a well-established way to study the transitional state (Leeet al., 2008). The shifts of microbial populations were interpretedin relation to changes in physicochemical proles to elucidatethe anaerobic sludge digestion. For our purpose, denaturing gradi-ent gel electrophoresis (DGGE) was conducted to identify major

    * Corresponding author.

    Bioresource Technology 101 (2010) 94619470

    Contents lists availab

    T

    elsE-mail address: shwang@postech.ac.kr (S. Hwang).ates a large volume of excess sludge. The processing and disposal ofwaste sludge, mainly secondary sludge, is a major issue in waste-water management because about half of the total operating costis dedicated to sludge treatment. Accordingly, application of acost-effective sludge process has been a subject of interest to engi-neers. Anaerobic digestion has long been used to treat sewagesludge because it has a low operational cost and produces biogas(Kobayashi et al., 2008). Anaerobic digestion of organic materialsinvolves a series of reactions: hydrolysis, acidogenesis, and metha-nogenesis. The rst two reactions are mediated by bacterial popu-lations which produce hydrogen and organic acids, and the last

    the anaerobic digestion of decaying sludge cells, however, boththe substrate and the performing microorganisms (i.e., theanaerobic microbial consortia) are prokaryotic cells, making theanalysis of the active microbial community technically demanding.Recent development of molecular techniques has provided valu-able tools to interpret complicated microbial communities. Thisenabled researchers to link microbial community structure to pro-cess performance. Although a few studies have recently reportedon the steady-state microbial compositions in the anaerobic diges-tion of sludge (Chouari et al., 2005; Kobayashi et al., 2008; Rivireet al., 2009), information is lacking in the literature on the behaviorAnaerobic digestionDenaturing gradient gel electrophoresisNon-metric multidimensional scalingReal-time PCRSecondary sludge

    1. Introduction

    A conventional municipal wastew0960-8524/$ - see front matter 2010 Elsevier Ltd. Adoi:10.1016/j.biortech.2010.07.081bacterial phyla and three archaeal orders. Several bacterial species, such as Fusibacter-related, Clostrid-ium-like, and Syntrophus-like organisms, appeared to be responsible for acidogenesis or syntrophic aciddegradation. Both hydrogenotrophic and aceticlastic methanogens appear to have been involved in themethanogenesis with the acidogenic products. The quantitative structure of the methanogenic popula-tions varied continuously, with the growth of Methanomicrobiales and Methanosarcinales in series, toresult in a Methanomicrobiales-dominant population. The ordination of microbial community structuresdemonstrated that the quantitative methanogenic structure converged to the seed inoculum while thebacterial and archaeal DGGE band patterns diverged. These results provide an insight into the microbialbehavior in the transitional phase (e.g., a start-up period) of anaerobic sludge digestion.

    2010 Elsevier Ltd. All rights reserved.

    eatment process gener-

    Secondary sludge is the excess biomass generated through thebiological wastewater treatment process. Therefore, the sludgeparticles are in principle concentrated aerobic microbial cells. InReceived 12 May 2010Received in revised form 19 July 2010Accepted 19 July 2010

    real-time PCR for an anaerobic batch digester treating secondary sludge. The batch process was success-fully operated with an organic removal efciency of 35% associated with a 91% decrease in the bacterialQualitative and quantitative assessmentanaerobic digestion of secondary sludge

    Seung Gu Shin a, Seungyong Lee a, Changsoo Lee b, Ka School of Environmental Science and Engineering, Pohang University of Science and TebDivision of Environmental and Water Resources Engineering, School of Civil and EnvirAvenue, Singapore 639798, Singapore

    a r t i c l e i n f o

    Article history:

    a b s t r a c t

    Microbial community shif

    Bioresource

    journal homepage: www.ll rights reserved.microbial community in batch

    nghyun Hwang a, Seokhwan Hwang a,*

    logy, Pohang, Gyeongbuk 790-784, South Koreantal Engineering, Nanyang Technological University, 50 Nanyang

    ere determined by denaturing gradient gel electrophoresis (DGGE) and

    le at ScienceDirect

    echnology

    evier .com/locate /bior tech

  • bacterial and archaeal species throughout the batch process. Thequantitative dynamics of bacterial and methanogenic populationswere further analyzed with real-time PCR. Ordination of the micro-bial community structures was performed with non-metric multi-dimensional scaling (NMS) for more in-depth discussion.

    2. Methods

    2.1. Experimental set-up

    An anaerobic complete-stirred tank reactor, with a working vol-ume of 6 L, was operated in the batch mode. Waste activatedsludge (WAS) and anaerobic sludge (AS) were collected from a lo-cal municipal wastewater treatment plant and used as substrateand seed inoculum (1%, v/v), respectively. The volatile solids (VS)concentrations of the substrate and the seed inoculum were 10.6and 17.4 g/L, respectively. The substrate had high salinity (8.2 gNaCl/L) due to intermittent seawater inputs into the local waste-water stream (Lee et al., 2009a). Temperature was maintained at

    denaturation at 94 C for 10 min; 20 cycles of denaturation at94 C for 30 s, annealing at 65 to 55 C (reducing the temperatureby 0.5 C per cycle) for 30 s, and extension at 72 C for 1 min; 15additional cycles of 94 C for 30 s, 55 C for 30 s, and 72 C for1 min; nal extension at 72 C for 7 min. DGGE was performedwith a DCode system (Bio-Rad, Hercules, CA). The PCR productwas loaded onto an 8% (w/v) acrylamide gel containing a 4060%denaturant gradient, where 100% was dened as 7 M urea with40% (v/v) formamide. Electrophoresis was run at 150 V for 7 h in1 TAE buffer. After staining with ethidium bromide, visible bandswere excised and eluted with distilled water. The eluted solutionwas further amplied with PCR using the corresponding primerswithout the GC-clamp. The PCR products were puried from a 1%agarose gel and cloned into the pGEM-T Easy vector (Promega,Madison, WI). The cloned 16S rRNA gene fragments were se-quenced and the results were compared with the reference se-quences in the GenBank database using the BLAST program.Sequence alignment and phylogenetic analysis were performedusing the DNAMAN software (version 5.2.2, Lynnon Biosoft, Que-

    2 lL of 10 reaction solution, and 2 lL of template DNA. The

    AGCGCGTASBGGGGWCCGCTCGCACTGCAATGCAGTTAGGCATYTCTGAGWG

    9462 S.G. Shin et al. / Bioresource Technology 101 (2010) 9461947035 C and pH was adjusted to no less than 7.0 with 6 N NaOH.The surface of the bioreactor was sealed in order to protect it fromlight.

    2.2. Extraction of DNA

    DNA was extracted using an automated nucleic acid extractor(Magtration System 6GC, Precision System Science, Chiba, Japan).Possible PCR inhibitors and DNA from cell debris were minimizedby removing residual medium twice after centrifugation. The puri-ed DNA was eluted with TrisHCl buffer (pH 8.0) and stored at20 C until use. All DNAs were extracted and analyzed induplicate.

    2.3. PCRDGGE and band afliation

    Bacterial and archaeal 16S rRNA genes were amplied by PCRwith the domain-level universal primers (Table 1) (Lee et al.,2008; Shin et al., 2008). The 50-ends of BAC338F and ARC787F wereadded with 40-bp GC-clamps, 50-CGCCCGCCGCGCGCGGCGGGCGGGGCGGGGGCACGGGGGG-30 and 50-CGCCCGCCGCGCCCCGCGCCCGTCCCGCCGCCCCCGCCCG-30, respectively, to stabilize the meltingbehavior of the PCR products (Muyzer et al., 1993). A touch-downPCR was conducted according to the following protocol: initial

    Table 1Characteristics of the oligonucleotides used in this study.

    Target group Namea Sequence

    Bacteria F: BAC338F ACTCCTACGGGT: BAC516F TGCCAGCAGCR: BAC805R GACTACCAGG

    Archaea F: ARC787F ATTAGATACCCT: ARC915F AGGAATTGGCR: ARC1059R GCCATGCACC

    Methanobacteriales F: MBT857F CGWAGGGAAT: MBT929F AGCACCACAAR: MBT1196R TACCGTCGTCC

    Methanococcales F: MCC495F TAAGGGCTGGT: MCC686F TAGCGGTGRAR: MCC832R CACCTAGTYCG

    Methanomicrobiales F: MMB282F ATCGRTACGGT: MMB749F TYCGACAGTGR: MMB832R CACCTAACGCR

    Methanosarcinales F: MSL812F GTAAACGATRT: MSL860F AGGGAAGCCGR: MSL1159R GGTCCCCACAa F, T and R indicate forward primer, TaqMan probe and reverse primer, respectively.b Culture collection numbers are in parentheses.two-step amplication protocol was as follows: initial denatur-ation for 10 min at 94 C followed by 45 cycles of 10 s at 94 Cand combined annealing and extension for 30 s at 60 C (63 Cfor the Methanomicrobiales-set). The standard curves for real-time

    Representative strainsb

    GCAG Escherichia coli K12 (DSM 1607)GGTAATACTCTAATCCTAGTCC Methanomicrobium mobile BP (DSM 1539)GGAGCACTCT Methanosarcina barkeri MS (DSM 800)GTTAAGT Methanobacterium formicicum M.o.H. (DSM 863)GTGGACCTTAGT Methanococcus voltae (DSM 1537)YGTTGATCCRAGTTTAGTGGG M. mobile BP (DSM 1539)RACGAAAGCTGHGTTTACGC TAGGT M. barkeri MS (DSM 800)AGCGARCCTACCbec, Canada). The phylogenetic trees were constructed using theneighbor-joining method. The nucleotide sequences reported inthis study have been deposited under GenBank Accession Nos.GQ233042GQ233104.

    2.4. Real-time PCR

    The six primer and probe sets targeting the domains Bacteriaand Archaea, and the methanogenic orders Methanobacteriales,Methanococcales, Methanomicrobiales, and Methanosarcinaleswere used in this study (Table 1) (Yu et al., 2005b). The four ordersets should cover most methanogens in anaerobic digesters (Yuet al., 2005b). Real-time PCR was performed using a LightCycler1.2 instrument (Roche Diagnostics, Mannheim, Germany). The20 lL real-time PCR mixture was prepared using the LightCyclerFastStart DNA Master Hybridization Probes kit (Roche Diagnos-tics): 9.6 lL of PCR-grade water, 2.4 lL of MgCl2 stock solution (-nal concentration 4 mM), 1 lL of each primer (nal concentration500 nM), 2 lL of the TaqMan probe (nal concentration 200 nM),

  • ame ionization detector, was used to quantify C2C6 volatile fatty

    pionate and iso-valerate concentrations peaked at 314 mg/L at day11.9 and 208 mg/L at day 9.9, respectively. Due to the thermody-namic disadvantage of propionate degradation, propionate is oftenthe last organic acid that persists in an anaerobic digester(Batstone, 2002; Lee et al., 2008). Propionate was virtually theonly VFA remaining after day 15.9; propionate was almost com-pletely degraded (>98%) at day 19.9 when methane productionceased.

    3.2. Bacterial and archaeal community shifts

    PCRDGGE targeting on bacterial and archaeal 16S rRNA geneswas performed to investigate the microbial community shifts inthis process. The DGGE proles showed continuous changes in bac-terial and archaeal community structures during the incubationtime (Fig. 2). The partial 16S rRNA gene fragments obtained from36 bacterial (B136) and 27 archaeal (A127) bands were se-quenced and the afliations were determined by comparison withthe GenBank database (Table 2).

    B26 was one of the dominant bands during the initial incuba-tion period when the VS and protein concentrations rapidly de-creased with the elevation of the TVFA level (Fig. 1). B26 and B27were most closely related to a clone isolated from an oil reservoir,which has putative afliation within the genus Fusibacter (Table 2).The members of the genus Fusibacter were reported to be thiosul-fate-reducers which utilize carbohydrates to produce acetate,butyrate, CO2, and H2 (Basso et al., 2009). B30 was not clearly ob-served at day 0 but visualized after 2.4 days of incubation (Fig. 2A).

    Time (days)0 5 10 15 20 25

    Fig. 1. Changes in chemical proles along with methane production. COD, chemicaloxygen demand; VS, volatile solids; TVFA, total volatile fatty acid.

    chnacids (VFAs) and ethanol. Another identical gas chromatograph,equipped with an HP-5 capillary column (Agilent) and a thermalconductivity detector, was used to analyze the composition ofthe biogas.

    3. Results

    3.1. Reactor performance

    The batch reactor was operated for 25.0 days. Fig. 1 shows theoverall process performance of the anaerobic bioreactor. Methaneproduction started at day 1.2 without a distinct lag period(Fig. 1A). At day 8.9, the methane production rate increased sharplyfrom 46 to 106 mL CH4/L days. The cumulative methane produc-tion reached 1.15 L/L at day 19.9 when biogas production ceased.The corresponding methane yield coefcient was 0.30 L CH4 pro-duced/g VS removed or 0.22 L CH4 produced/g COD removed.

    The VS and COD concentrations gradually decreased until 35.3%and 34.8% of the initial amounts were removed, respectively(Fig. 1A). The VS removal rate was the highest during the earlystage of the batch reaction; 40% of the total VS reduction (i.e.,14% of the initial VS concentration) was achieved by day 2.4. How-ever, the COD removal in this period was notably lower (i.e., 25% ofthe total COD reduction) than the VS removal, although the overallremoval efciencies of VS and COD were similar. The proteinreduction efciency was 48.7% throughout the reaction (Fig. 1A).The decrease of protein concentration was 59% of that of VS con-centration, suggesting that protein decomposition was a signicantcatabolic pathway in this process.

    The total VFA (TVFA) concentration rapidly increased up to1.2 g/L, which then decreased continuously until day 19.9 withthe production of methane (Fig. 1B). Acetate, propionate, and iso-valerate were the most abundant acidogenic products in this pro-PCR analysis were constructed as previously described (Lee et al.,2009b) with the representative strains listed in Table 1.

    2.5. Ordination

    Ordination allows analysis of high-dimensional spaces by plot-ting the strongest structure into reduced dimensions (Falk et al.,2009). NMS is one of the most generally effective ordination meth-ods for ecological community data because it avoids distributionalassumptions commonly associated with other ordination tech-niques (McCune and Grace, 2002). In this study, NMS ordinationwas performed based on the Sorensen distance measure in thePC-ORD software (MjM Software Design, Gleneden Beach, OR).The presence or absence of each DGGE band was scored 1 or 0,respectively, to generate distance matrices for bacterial and archa-eal community structures. Another matrix employing methano-genic group abundance was generated for ordination ofmethanogenic communities in a quantitative aspect. Each mainmatrix was processed for ordination such that the stress (

  • chn9464 S.G. Shin et al. / Bioresource Teacetate, propionate, CO2, and H2 (Takii et al., 2007). The band inten-sity of B23 increased during the early batch period and remaineddistinct until the end of reaction (Fig. 2A). B23 was closely relatedto Clostridium aminobutyricum with 97% sequence similarity(Table 2). C. aminobutyricum is a spore-forming anaerobe whichferments amino acids to form acetate, butyrate, and ammonia(Balows et al., 1992). B33 was also closely (99%) associated witha Clostridium species, C. sticklandii (Table 2). C. sticklandii anaerobi-cally utilizes pairs of amino acids by Stickland reaction andproduces acetate, butyrate, and ammonia (Balows et al., 1992).

    Band B36, observed throughout the reaction (Fig. 2A), had 100%sequence similarity with Lactobacillus delbrueckii subsp. bulgaricus(Table 2). Although most Lactobacillus species can grow on variouscarbohydrates, L. delbrueckii subsp. bulgaricus is reported to utilizemainly lactose to form lactate (Balows et al., 1992). The closestneighbor of B24 was an environmental clone which was afliatedwithin the genus Syntrophus (Table 2). Members of the genus Syn-trophus are anaerobes which utilize butyrate, benzoate, or otheracids through syntrophism with H2 and/or formate utilizers suchas methanogens (Jackson et al., 1999). Putative roles of the other29 bacterial bands were relatively unclear. Bands B2829 andB3435 were not detected at day 0 and evolved thereafter(Fig. 2A). By contrast, band intensities of B19, B1220, B25, andB3132 gradually decreased throughout the reaction. It is note-worthy that some of these bands were closely related to bacteriaor clones with marine origin due to the high salinity (8.2 g NaCl/L) and the putative seawater input into the local wastewater treat-ment plant (Lee et al., 2009a).

    Fig. 2. DGGE proles of (A) bacterial and (B) archaeal 16S rRNA gene fragments. Numbersludge; AS, anaerobic sludge.ology 101 (2010) 94619470The archael DGGE proles showed continuous shifts in archaealcommunity structure during the batch period (Fig. 2B). Overall, thearchaeal band patterns were less complicated than the bacterial re-sults due to the relatively low diversity of the domain Archaea inmost microbial complexes (Curtis and Sloan, 2004). A26 was thedominant band after the onset of methane production (Fig. 1A).Eight bands including A26 were closely related to Methanoplanuspetrolearius (Table 2). Eleven other bands (A34, A6, A810, A14,A18, A20, A22, and A24) were also closely related to four hydro-genotrophic methanogens (Table 2). Among these bands, A18,A20, A22, and A24 were observed during the incubation period(Fig. 3B).

    The band intensity of A27 increased considerably during theincubation period (Fig. 2B). A27 was closely related to Methanosar-cina mazei with 98% sequence similarity (Table 2). Bands A12 andA1517 also corresponded to an aceticlastic methanogen, Methan-osaeta concilii (Table 2). A12 and A13 were observed during the ini-tial phase but disappeared after day 2.4 (Fig. 2B). These bands weremostly closely related to a clone which was isolated from a meth-anogenic consortium (Table 2). They were branched within the or-der Thermoplasmatales, a group of non-methanogenicthermophilic acidophiles, with their metabolic roles in this systemremaining unclear.

    Neighbor-joining trees were constructed to characterize theafliation of the bacterial and archaeal band sequences to the data-base sequences (Fig. 3). The bacterial sequences were branchedwithin four phyla, Proteobacteria, Bacteroidetes, Firmicutes, andActinobacteria (Fig. 3A). In the archaeal neighbor-joining tree, 25

    s at the top designate the incubation time in days of each lane. WAS, waste activated

  • AY682382 98

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    m p

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    clon

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    B36 Lactobacillus delbrueckii subsp. bulgar

    chnA12, 1517 Methanosaeta conciliiA3, 22 Methanocalculus pumilusA4 Methanoculleus sp. ZC-2A5, 7, 11, 19, 21, 23, 2526 Methanoplanus petroleariusA6, 8, 10, 20, 24 Methanogenium marinumTable 2Phylogenetic afliation of the 16S rRNA gene sequences from DGGE bands.

    Band(s) Nearest sequence

    B1 Yeosuana aromativoransB2, 4, 1516 Denitromonas aromaticusB3 Aequorivita antarcticaB5, 1213 Uncultured DeltaproteobacteriumB6 Flavobacterium sp. 90dB7, 22 Uncultured bacterium 128O51B89 Uncultured DeltaproteobacteriumB10 Hyphomonas adhaerensB11 Uncultured GammaproteobacteriuB14 Uncultured bacterium JH10_C65B17 Dechloromonas denitricansB18 Uncultured bacterium UA01B19 Uncultured bacterium FS396_454B20 Uncultured bacterium boneC15BB21 Uncultured bacterium 43_BS5_8B23 Clostridium aminobutyricumB24 Syntrophus sp. B3B25 Pelobacter masseliensisB2627 Fusibacter sp. enrichment cultureB28 Uncultured bacterium BSA1B-15B29 Uncultured Bacteriodetes bacteriuB30 Dethiosulfatibacter aminovoransB3132 Uncultured bacterium A-L-2B33 Clostridium sticklandiiB34 Uncultured bacterium clone CLA-B35 Uncultured Actinobacteria bacteri

    S.G. Shin et al. / Bioresource Teout of 27 bands (92%) were assigned to methanogenic orders; 19bands (70%) within Methanomicrobiales and six bands (22%) with-in Methanosarcinales (Fig. 3B). No member of Methanobacterialesor Methanococcales was identied.

    3.3. Quantitative population dynamics

    Quantitative changes in the 16S rRNA gene concentrations werealso determined by real-time PCR (Fig. 4). The concentration pro-les showed signicant temporal variations in bacterial, archaeal,and the order-level methanogenic populations with respect to per-formance data. The bacterial 16S rRNA gene concentration initiallyincreased from 7.0 109 to 9.8 109 copies/mL (39% increase) be-tween days 0 and 2.4, then it decreased continuously down to6.6 108 copies/mL (93% decrease from day 2.4 or 91% decreasefrom day 0) until the end of reaction. The archaeal 16S rRNA genelevel increased sharply in the early phase: from 3.5 106 to3.4 107 copies/mL (15-fold increase) on day 7.9. After day 7.9,the archaeal gene concentration did not change signicantly,remaining above 3 107 copies/mL. Accordingly, the relativeabundance of archaea to bacteria increased continuously from0.1% to 9.9% throughout the reaction period. The bacteria to ar-chaea ratios of the WAS and the AS were 0.1% and 2.9%,respectively.

    The three hydrogen-utilizing methanogenic groups, Methano-microbiales, Methanobacteriales, and Methanococcales, behaveddifferently in terms of their abundance (Fig. 4). The 16S rRNA geneconcentration of Methanomicrobiales increased sharply during theearly period. This trend coincides with the elevation of VFA con-centrations. The concentration increased up to 7.4 107 copies/mL (25-fold increase) on day 7.9. Similarly to the archaeal result,the Methanomicrobiales gene concentration did not change signif-

    A9, 14, 18 Methanocorpusculum bavaricumA1213 Uncultured Euryarchaeote SMS-sludgeA27 Methanosarcina mazeiAB049763 96AY771732 99

    5 AM040101 9192AF228796 88FJ416130 97

    5 AJ289747 9899AF082790 99

    KB3B-20 AB247876 97AY568817 95AJ318917 97AB456223 93

    00bp_1036B DQ909703 90AY548995 98FJ825571 97X76161 97AJ133796 97AY187308 98

    e 22-7A EU517558 99AB175369 95

    G-5-1-3-L EU626571 93AB218661 97AB154497 95M26494 99DQ068728 97

    QEDN11DD05 FJ661111 95icus FJ915705 100

    X16932 9899AB008853 99100DQ787476 99AY196681 9798DQ177344 97Accession No. % Similarity

    ology 101 (2010) 94619470 9465icantly after day 7.9, remaining above 6 107 copies/mL. By con-trast, no distinct growth of Methanobacteriales was observed.Methanococcales was not detected in any DNA samples in thisstudy. The 16S rRNA gene level of Methanosarcinales, the only ace-ticlastic order among methanogens, increased from 2.2 106 to1.0 107 copies/mL (4.6-fold increase) between days 4.8 and15.9. During this period, the acetate concentration gradually de-creased to zero (Fig. 1B). The Methanosarcinales level increasedsteeply between days 9.9 and 11.9, corresponding to the periodwhen the methane production rate increased sharply (Fig. 1A).The sum of the three methanogenic orders accounted for 64% to135% of archaea; it was less than 100% when non-methanogenicarchaeal DGGE bands (A1213) were present.

    The relative abundance of the methanogenic populations wasvisualized in Fig. 5. The substrate and the seed contained9.3 106 and 1.7 108 copies/mL of methanogenic 16S rRNA genewith Methanosarcinales and Methanomicrobiales as the majorpopulation, respectively. The aceticlastic Methanosarcinales wasthe most abundant population at day 0 (mixture of the substrate,99% v/v, and the seed) but supplanted by hydrogenotrophic meth-anogens with the rapid growth of Methanomicrobiales (Figs. 4 and5). The 16S rRNA gene ratio of Methanomicrobiales revealed itsmaximum of 94.3% at day 9.9 and remained greater than 88%thereafter (Fig. 5). On the other hand, Methanosarcinales main-tained a relatively small population (411%) after day 4.8.

    3.4. Ordination

    Changes in microbial community structures were also visual-ized by NMS ordination (Fig. 6). Fig. 6A and B shows the continuousshifts of bacterial and archaeal DGGE band patterns, respectively,while Fig. 6C shows the ordination of the methanogenic group

    AF042197 9798-6 AB479397 99100

    AY196685 98

  • chn9466 S.G. Shin et al. / Bioresource Teabundance quantitatively assessed by real-time PCR. The resultsmet the general criteria for good NMS performance, with the stressvalue below 10 and the instability lower than 104 (McCune andGrace, 2002).

    Fig. 3. Neighbor-joining tree illustrating the phylogenetic identities of the 16S rRNA genclasses within the phylum Proteobacteria.ology 101 (2010) 94619470The bacterial DGGE band patterns were assigned as a one-dimensional solution by the NMS analysis with the sole axis 1Aexplaining 94% of the variability in band structures (Fig. 6A). Onthe NMS map, the bacterial community structure was placed near

    e sequences from (A) bacterial and (B) archaeal DGGE bands. a, b, c, and d designate

  • chnS.G. Shin et al. / Bioresource Tethe substrate at day 0 and shifted continuously towards, in general,the opposite direction of the seed. As a result, the end-point bacte-rial community at day 25.0 evolved to a point distinct from boththe substrate and the seed. The archaeal DGGE band patterns areillustrated on a two-dimensional NMS plot (Fig. 6B). The archaealpattern at day 0 was between, although not close to, the substrateand the seed points. The archaeal band patterns gradually migratedto the cluster including points at days 7.925.0, which was alsodistinct from the archaeal community of the substrate or the seed.Shifts in the quantitative methanogenic population proles areshown in Fig. 6C. The methanogenic real-time PCR prole at day0 was placed near the substrate and continuously migrated intoa cluster (days 7.925.0) near the seed prole.

    4. Discussion

    Secondary sludge is the excess biomass generated from the acti-vated sludge process. The organic materials in the sludge consistmainly of prokaryotic cells, mostly aerobic bacteria. In this batchprocess, changes in the substrate were monitored primarily by

    Fig. 3 (contology 101 (2010) 94619470 9467measuring crude organic materials such as VS and COD. The VSreduction efciency in this study (35.3%) was comparable to previ-ous reports with mesophilic continuous operation, where 1436%of VS was reduced with hydraulic retention times of 845 days(Bolzonella et al., 2005; Park et al., 2004). Alternatively, the bacte-rial 16S rRNA gene level determined by real-time PCR presumablyrepresents the quantity of the intact bacterial cells in the digester.The change in the bacterial rRNA gene concentration results fromthe combination of the decay of aerobic cells (substrate) andthe growth and decay of anaerobic bacteria (acidogens). There-fore, the 91% decrease in the bacterial 16S rRNA gene concentrationduring the batch process implies that more than 90% of the initialbacterial cells were decomposed. The decrease in bacterial DNAconcentration corresponds to the decrease of band intensities ofB19, B1220, B25, and B3132, implying that the bacteria relatedto these bands decayed. The relatively low organic removal ef-ciency (35%), compared to the decrease in the bacterial DNA con-centration (91%), is likely to be due to the low biodegradabilityof sludge solids by conventional anaerobic processes (Park et al.,2004; Siegrist et al., 2002).

    inued)

  • Axis 1B

    Axi

    sWAS

    00.4

    1.0

    chnTime (days)0 5 10 15 20 25

    16S

    rRN

    A ge

    ne (c

    opie

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    1e+5

    1e+6

    1e+7

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    1e+9

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    1e+11BacteriaArchaeaMethanomicrobialesMethanosarcinalesMethanobacteriales

    Fig. 4. Quantitative changes in bacterial, archaeal, and methanogenic 16S rRNAgene concentrations determined by real-time PCR.

    9468 S.G. Shin et al. / Bioresource TeProtein is one of the major constituents (i.e., approximately halfof the dry weight) of a prokaryotic cell (Madigan and Martinko,2006). In anaerobic digesters, a specialized group of microorgan-isms, e.g. proteolytic clostridia, is responsible for protein catabo-lism. The maintenance of well-functioning proteolytic consortia,therefore, is important for the efcient operation of anaerobicsludge digestion. As revealed by DGGE analysis, two Clostridium-like bacteria (B23, B33) may have been mainly responsible forthe protein catabolism in this system. During this batch reaction,the protein removal efciency (48.7%) was higher than the proteindegradation ratio of 39% in a previous study (Bougrier et al., 2007).The higher protein reduction efciency could be attributed to abetter availability of the particulate proteins to the enzymatic ma-trix (Angelidaki and Sanders, 2004) and/or the existence of moreversatile proteolytic anaerobes in this digester.

    The batch anaerobic digestion in this study can be roughly di-vided into an early hydrolytic/acidogenic phase and a later metha-nogenic phase; macromolecules were degraded into simpler acids,e.g. acetate, in the former while the acidogenic products were re-duced to biogas in the latter. Among the bacterial species detected,the Fusibacter-related (B2627), the D. aminovorans-related (B30),the Clostridium-like (B23, B30), and the Lactobacillus-like (B36)organisms appear to have been involved in the production of VFAs.The VS removal by day 2.4 (40% of the total) was remarkably high-er than the COD removal (25% of the total), although both param-eters commonly describe the overall organic concentration ofwaste or wastewater (Angelidaki and Sanders, 2004). The relativelylow boiling point of intermediate acids (e.g., 118.1 C for acetate),which encourages evaporation of these molecules at 105 C in sol-

    Fig. 5. Relative abundance of the three methanogenic orders based on the 16S rRNAgene concentrations. 2B

    2.4

    4.87.9

    9.9 11.9

    13.9

    15.9

    19.925.0AS

    Axi

    s 1A

    WAS0

    0.41.0

    2.4

    4.8

    7.99.9 11.9 13.9 15.9 19.9 25.0

    AS

    B

    A

    ology 101 (2010) 94619470ids measuring procedures (APHA, 2005), could be responsible forthe gap between the VS and COD removal efciencies in the earlierphase.

    Acetate is often regarded as the major (70%) methanogenic pre-cursor (Speece, 1996) and can be utilized directly by methanogens.Accordingly, the acetate-utilizing Methanosarcinales has been re-ported to be the dominant methanogenic group in previous studies(Kobayashi et al., 2008; Yu et al., 2005a). Methanosarcinales wasthe most abundant methanogenic group, however, only at day 0in this system (Figs. 4 and 5). At this point, M. conilii-like archaeon(A1517) was the only aceticlastic methanogen visualized in theDGGE prole. M. concilii can only utilize acetate for growth and iswidely distributed in nature due to its high afnity to acetate(Smith and Ingram-Smith, 2007). The 16S rRNA gene concentrationof Methanosarcinales increased after day 4.8 when the highest ace-tate concentration was observed (Fig. 1B). The Methanosarcinaleslevel increased steeply between days 9.9 and 11.9, coincident withthe appearance of M. mazei-like band (B27; Fig. 2B). M. mazei is anacetate-utilizing methanogen which can also convert other organ-ics to methane (Garrity, 2005). Methanosarcina spp. have highergrowth rate than Methanosaeta spp. (Lee et al., 2009b); therefore,

    Axis 1C

    Axi

    s 2C

    WAS

    0

    0.41.02.4

    4.8

    7.9

    9.9

    11.913.9

    15.919.9

    25.0

    AS

    C

    Fig. 6. Non-metric multidimensional scaling ordination plot for (A) bacterial and(B) archaeal DGGE band patterns and (C) quantitative methanogenic prolesdetermined by real-time PCR. Each community prole on the plot is labeled witheither a number indicating the incubation time (days) or its identity. WAS, wasteactivated sludge; AS, anaerobic sludge.

  • the anaerobic environment and the protection from light.

    lum and the shifts in bacterial populations were within the range

    chnthe rapid increase of Methanosarcinales may have mainly resultedfrom the rapid growth ofM. mazei-like methanogen in this system.The community shift from M. concilii to M. mazei, associated withthe rapid consumption of acetate, was important for the overallreaction efciency because the accumulation of intermediate acidsduring a start-up period often leads to system failure (Batstone,2002). It is notable that the seed sludge contained no visible bandcorresponding to M. mazei, implying that the M. concilii-like archa-eon was the dominant aceticlastic methanogen due to the low ace-tate environment of the stable full-scale anaerobic digester(Demirel and Scherer, 2008; Yu et al., 2005a).

    Hydrogenotrophic methanogenesis is one of the major metha-nogenic pathways in anaerobic digesters (Ahring, 2003). Due tothe thermodynamic limitations of the hydrogen-mediated metab-olism, low hydrogen partial pressure must be maintained for syn-trophic consortia to utilize various intermediates (Batstone et al.,2002). Therefore, efcient removal of hydrogen by hydrogen-utiliz-ing microorganisms is required for acidogenesis and/or acetogene-sis to occur. In this study, hydrogen-utilizing Methanomicrobialesincreased steeply during the early reaction period (Fig. 4); thischange coincided with the increase in band intensity of A26, theM. petrolearius-like band (Fig. 2B). M. petrolearius is a mesophilicmethanogen utilizing H2 and CO2, formate, and 2-propanol in thepresence of acetate (Garrity, 2005). The strong band intensity ofA26 and the acetate-containing environment suggested that theM. petrolearius-like species was in part responsible for themethanogenesis through Syntrophism with hydrogen- or formate-producing bacteria (e.g., the Syntrophus-like bacterium corre-sponding to B24). M. petrolearius was reported to favor halophilicconditions (up to 5% NaCl) (Ollivier et al., 1997), which could havebeen a selective pressure in favor of this species due to the highsalinity (8.2 g NaCl/L) of the substrate. Among other archaealbands, A18, A20, A22, and A24 were observed during the incuba-tion period (Fig. 2B), suggesting that the Methanocorpusculumbavaricum-like, the Methanogenium marinum-like, and the Methan-ocalculus pumilus-like organisms are also involved in methane pro-duction through hydrogen (Garrity, 2005).

    The methanogenic populations in this study shifted from aMethanosarcinales-dominant one to a Methanomicrobiales-domi-nant one (Fig. 5). Similar changes have been attributed to shiftsin VFA-utilizing pathway associated with the growth of differentmethanogenic populations (Lee et al., 2009b). It is noteworthy thatsome previous studies have reported the dominance of aceticlasticmethanogens in the anaerobic digestion of sludge (Karakashevet al., 2005; Kobayashi et al., 2008; Yu et al., 2005a). However,many other reports have demonstrated the prevalence of thehydrogenotrophic pathway in anaerobic processes with differentsubstrates (Demirel and Scherer, 2008; Karakashev et al., 2005;Song et al., 2010); the key factor determining the major pathwaycould be the existence of high levels of inhibitory ions, which ingeneral have more severe effects on aceticlastic methanogens.The rapid growth of the A26-corresponding archaeon (Fig. 2B), re-lated to halophilic M. petrolearius, was likely to be responsible forthe outgrowth of Methanomicrobiales in this system.

    The microbial community structures, as determined by DGGE,showed continuous shifts within four bacterial phyla and twoarchaeal orders. No archaeal DGGE band related to Methanobacte-riales was identied by DGGE, although this group was success-fully quantied with real-time PCR. The relatively low abundanceof this group (

  • sources. This work was also supported by the Korea ResearchFoundation Grant funded by the Korean Government (MOEHRD).The authors are grateful to Dr. Byeongchul Park and Dr. Jaai Kimfor their contribution to this work and we also thank Bi Wen Zhoufor valuable discussions.

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    Qualitative and quantitative assessment of microbial community in batch anaerobic digestion of secondary sludgeIntroductionMethodsExperimental set-upExtraction of DNAPCRDGGE and band affiliationReal-time PCROrdinationAnalytical methods

    ResultsReactor performanceBacterial and archaeal community shiftsQuantitative population dynamicsOrdination

    DiscussionConclusionsAcknowledgementsReferences

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