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A comprehensive microbial insight into two-stage anaerobicdigestion of food waste-recycling wastewater

Seung Gu Shin a, Gyuseong Han a, Juntaek Lim a, Changsoo Lee b, Seokhwan Hwang a,*aSchool of Environmental Science and Engineering, Pohang University of Science and Technology, Pohang, Gyeongbuk 790-784,

South KoreabDivision of Environmental and Water Resources Engineering, School of Civil and Environmental Engineering, Nanyang Technological

University, 50 Nanyang Avenue, Singapore 639798, Singapore

a r t i c l e i n f o

Article history:

Received 10 April 2010

Received in revised form

14 June 2010

Accepted 8 July 2010

Available online 16 July 2010

Keywords:

Anaerobic digestion

Denaturing gradient gel electropho-

resis

Food waste-recycling wastewater

Non-metric multidimensional

scaling

Two-stage process

* Corresponding author. Tel.: þ82 54 279 228E-mail address: shwang@postech.ac.kr (S

0043-1354/$ e see front matter ª 2010 Elsevdoi:10.1016/j.watres.2010.07.019

a b s t r a c t

Microbial community structures were assessed in a two-stage anaerobic digestion system

treating food waste-recycling wastewater. The reactors were operated for 390 d at 10

different hydraulic retention times (HRTs) ranging from 25 to 4 d. Stable operation was

achieved with the overall chemical oxygen demand (COD) removal efficiency of 73.0e85.9%

at organic loading rate of up to 35.6 g COD/L$d. Performance of the acidogenic reactors,

however, changed significantly during operation. This change coincided with transition of

the bacterial community from one dominated by Aeriscardovia- and Lactobacillus amylovo-

rus-related species to one dominated by Lactobacillus acetotolerans- and Lactobacillus kefiri-

like organisms. In methanogenic reactors, the microbial community structures also

changed at this stage along with the shift from Methanoculleus- to Methanosarcina-like

organisms. This trend was confirmed by the non-metric multidimensional scaling joint

plot of microbial shifts along with performance parameters. These results indicated that

the overall process performance was relatively stable compared to the dynamic changes in

the microbial structures and the acidogenic performance.

ª 2010 Elsevier Ltd. All rights reserved.

1. Introduction Anaerobic digestion is an effective method of treating

Food waste constitutes one of the largest components of the

gross waste disposed in Korea (NIER, 2007). Korean food waste

is mostly collected separately from other wastes and recycled

as animal feed or compost. This recycling generates concen-

trated food waste-recycling wastewater (FRW) which causes

serious environmental concerns due to its quantity (3.3

million tons generated in 2008) and quality (up to 150 g

chemical oxygen demand (COD)/L) (Kim et al., 2010). Tradi-

tionally, most FRW has been discharged into the ocean, but

this adversely affects the ocean environment, so an alterna-

tive method of treating FRW is required.

2; fax: þ82 54 279 8299.. Hwang).ier Ltd. All rights reserve

different organic pollutants; it has the additional benefit of

generating combustible biogas which can be used to produce

energy. Previous reports have demonstrated that foodwastes

are desirable substrates for anaerobic digesters (Wang et al.,

2002; Heo et al., 2004; Zhang et al., 2007). In principle, FRW is

a diluted form of food waste and thus it is likely to be

manageable by anaerobic digestion (Kim et al., 2010).

Recently, methane production potential from FRW has been

successfully demonstrated in batch experiments (Lee et al.,

2009b; Behera et al., 2010). However, the application of

anaerobic processes for the treatment of FRW has not yet

been established in continuous-flow digesters; this type of

d.

Table 1 e Characteristics of the FRW.

Parameter Value (average � standarddeviation)

pH 3.68 � 0.23

COD (g/L) 136.8 � 12.1

Soluble COD (g/L) 86.5 � 4.7

TS (g/L) 79.5 � 8.7

VS (g/L) 63.4 � 8.3

VSS (g/L) 31.3 � 5.5

Carbohydrate (g/L) 17.5 � 4.9

Protein (g/L) 21.7 � 2.4

Lipid (g/L) 17.7 � 5.0

Total Kjeldahl nitrogen (g/L) 4.09 � 0.40

Total ammonia nitrogena (g/L) 0.62 � 0.07

NO2� (g/L) NDb

NO3� (g/L) ND

PO43- (g/L) 1.64 � 0.08

SO42- (g/L) 0.29 � 0.01

Acetate (g/L) 5.04 � 0.82

Propionate (g/L) 0.40 � 0.18

Butyrate (g/L) 0.19 � 0.08

Valerate (g/L) 0.06 � 0.02

Caproate (g/L) 0.05 � 0.02

Ethanol (g/L) 5.92 � 1.10

a The sum of N concentrations of free NH3 and NH4þ.

b Not detected.

wat e r r e s e a r c h 4 4 ( 2 0 1 0 ) 4 8 3 8e4 8 4 9 4839

operation is dominant among field-scale digesters today

(Weiland, 2009).

Anaerobic digestion is amulti-stage biochemical process in

which complex organic materials undergo hydrolysis, acido-

genesis, acetogenesis, and methanogenesis in series. These

reactions are mediated by many species of microorganisms,

which are broadly classified into acidogenic bacteria and

methanogenic archaea (Chouari et al., 2005). These two groups

are present in a mixed anaerobic culture but they differ in

their nutritional and pH requirements, growth kinetics, and

their ability to tolerate environmental stresses (Demirer and

Chen, 2005). Therefore, phase separation into two digesters

has been claimed to enhance the overall process rate due to

the maintenance of favorable environments for, in series,

acidogens and methanogens (Yang et al., 2003). With the

proper enrichment of microbial communities, the two-stage

anaerobic process has been demonstrated to perform effi-

ciently (Liu et al., 2002; Stamatelatou et al., 2003; Yang et al.,

2003; Bouallagui et al., 2004).

Characterization of microbial community structure in

anaerobic digesters has attracted interest from engineers

because understanding of microbial behavior is essential to

improving the digestion process (Fernandez et al., 1999; Lee

et al., 2008). Recent advances in molecular techniques have

provided useful tools to analyze anaerobic communities in

different digester configurations (Leclerc et al., 2004;

Akarsubasi et al., 2005; Lee et al., 2009a; Riviere et al., 2009).

However, relatively little information is available on moni-

toring both acidogenic and methanogenic communities in

a two-stage system (Liu et al., 2002; Ueno et al., 2007). Moni-

toring microbial community structures in a two-stage anaer-

obic process can provide valuable information that can be

used to optimize conditions in series reactors to favor efficient

breakdown of wastes.

The purpose of this study was to assess the microbial

community structures through the molecular detection of

bacterial and archaeal species in a two-stage anaerobic

digestion for the treatment of FRW. The two-stage process

was operated at 10 different hydraulic retention times (HRTs)

ranging from 25 to 4 d. Themicrobial populationwas analyzed

using denaturing gradient gel electrophoresis (DGGE) of

bacterial and archaeal 16S rRNA genes. Community structures

were ordinated for further interpretation using non-metric

multidimensional scaling (NMS).

2. Material and methods

2.1. Preparation of substrate

FRW was collected from a food waste-recycling plant in

Kwangyang, South Korea. The FRWwas periodically collected,

mixed thoroughly, filtered through an 850-mm sieve, and

distributed in 20-L plastic bottles. The individual bottles were

stored at �20 �C until thawed and kept at 4 �C for use as

a feedstock. The pH of the FRWwas low (average value of 3.68;

Table 1), probably due to partial fermentation of residues

during food waste collection, processing, and storage (Heo

et al., 2004; Kim et al., 2008). The FRW was rich in

carbohydrate, protein, and lipid, the sum of which accounted

for 87.3e99.5% of volatile solids (VS).

2.2. Reactor setup and operations

Two identical sets of two-stage anaerobic digesters (D1, D2)

were operated in this study. Each set consisted of one acido-

genic reactor (working volume of 1 L, DA1 and DA2) and one

methanogenic reactor (working volume of 5 L, DM1 and DM2) in

series (D1, DA1eDM1, and D2, DA2eDM2). The reactors were

operated as a continuous stirred tank reactor (CSTR) at 35 �Cwithout pH control. At start-up, the four reactors were filled

with an anaerobic sludge (14.5 g VS/L) from a full-scale mes-

ophilic anaerobic digester receiving 95% v/v municipal

wastewater and 5% v/v foodwaste. Each set received substrate

stream semi-continuously through a peristaltic pump equip-

ped with a programmable mechanical timer. A steady state

was assumed when both the effluent COD concentration and

the methane production rate were constant (�5%) during

more than half of the HRT and over at least 7 d. HRT of the

two-stage digesters was decreased: 25, 15, 10, 8, 6.5, 5, and 4 d

for D1 (runs 1, 4, 6, 7, 8, 9, 10); 20, 17.5, and 12.5 d for D2 (runs 2,

3, 5) (Table 2).

2.3. Analytical methods

Samples were collected from all reactors 2e3 times per week.

Biogas production from DA (DA1 and DA2) was negligible; the

biogas production from DM (DM1 and DM2) was recorded daily

using an automated gas metering system (Korean patent

application number 10-2005-0025013), and analyzed using

a gas chromatograph (6890 plus, Agilent, Palo Alto, CA)

equipped with an HP-5 capillary column and a thermal

Table 2 e Operational and performance characteristics of the two-stage anaerobic digesters.

Run 1 2 3 4 5 6 7 8 9 10

Digester D1 D2 D2 D1 D2 D1 D1 D1 D1 D1

Operational days 0e166 0e166 166e229 166e229 229e278 229e272 272e304 304e332 332e356 356e390

HRT (d)

DA 4.2 3.3 2.9 2.5 2.1 1.7 1.3 1.1 0.8 0.7

DM 20.8 16.7 14.6 12.5 10.4 8.3 6.7 5.4 4.2 3.3

Total 25.0 20.0 17.5 15.0 12.5 10.0 8.0 6.5 5.0 4.0

OLRa (g COD/L$d) 5.7 7.2 8.2 9.5 10.5 13.1 16.4 20.2 26.2 35.6

MPb (L/L substrate) 42.2 � 2.5 43.6 � 2.0 44.3 � 1.2 39.5 � 1.6 40.5 � 1.7 36.2 � 1.8 34.4 � 1.5 32.4 � 1.5 30.7 � 1.8 27.1 � 2.2

COD removal (%) 84.0 � 0.9 85.9 � 1.0 84.0 � 1.3 81.1 � 1.6 80.9 � 1.6 75.5 � 2.3 78.2 � 1.2 77.8 � 1.2 75.8 � 2.5 73.0 � 1.9

a Organic loading rate; calculation based on the total (DA þ DM) reactor volume.

b Methane production.

wat e r r e s e a r c h 4 4 ( 2 0 1 0 ) 4 8 3 8e4 8 4 94840

conductivity detector. Volatile fatty acids (VFAs, C2eC6) and

ethanol were measured using an identical gas chromatograph

equipped with an Innowax capillary column and a flame

ionization detector. COD, total solids (TS), VS, and volatile

suspended solids (VSS) were determined according to the

procedures in Standard Methods (APHA, 2005). The carbohy-

drate concentration was measured using the phenolesulfuric

acidmethod (Dubois et al., 1956). Total Kjeldahl nitrogen, total

ammonia nitrogen, and protein concentrations were deter-

mined using the Kjeldahl method (APHA, 2005). Lipid

concentrations were measured using gravimetry after

extraction of lipids by solvent (chloroform: methanol 1:2 v/v)

(Bligh and Dyer, 1959). Nitrite, nitrate, phosphate, and sulfate

ion concentrations were measured using an ion chromato-

graph (790 Personal IC, Metrohm, Herisau, Switzerland)

equipped with a Metrosep A Supp 5 column.

2.4. Microbial community analysis

2.4.1. Nucleic acid extractionImmediately after sampling, 0.2 mL samples were centrifuged

twice and the supernatant was removed each time to mini-

mize concentrations of possible PCR inhibitors and DNA from

cell debris. The concentrated samples were stored frozen at

�20 �C before DNA extraction (Wells et al., 2009). Total DNA

was extracted from steady state samples using an automated

nucleic acid extractor (Magtration System 6 GC, Precision

System Science, Chiba, Japan). The purified DNA was eluted

with nuclease-free water and stored at �20 �C until use. All

extractions were carried out in duplicate.

2.4.2. DGGE and phylogenetic analysisBacterial and archaeal community structures were investi-

gated using DGGE, targeting the 16S rRNA gene. Conventional

PCR was performed with domain-level universal primers:

BAC338F (50-ACTCCTACGGGAGGCAG-30) and BAC805R (50-GACTACCAGGGTATCTAATCC-30) (Lee et al., 2008) for bacteria;

ARC787F (50-ATTAGATACCCSBGTAGTCC-30) and ARC1059R

(50-GCCATGCACCWCCTCT-30) for archaea. The 50 ends of the

forward primers were capped with 40-bp GC-clamps, 50-CGCCCGCCGCGCGCGGCGGGCGGGGCGGGGGCACGGGGGG-30

for bacteria and 50-CGCCCGCCGCGCCCCGCGCCCGTCCCGC-CGCCCCCGCCCG-30 for archaea, to stabilize the melting

behavior of the PCR products (Muyzer et al., 1993). The PCR

mixture of 50 mL was prepared using the SolGent Taq DNA

Polymerase kit (Solgent, Daejon, South Korea): 5 mL of

10� reaction solution, 2 mL of each primer (final concentration

400 nM), 1 mL of dNTP mixture (final concentration 200 mM

each), 0.25 mL of Taq polymerase, 5 mL of template DNA, and

34.75 mL of PCR-grade water. A touch-down PCR was con-

ducted according to the following protocol: (1) initial dena-

turation at 94 �C for 10 min; (2) 20 cycles of denaturation at

94 �C for 30 s, annealing at 65e55 �C (reducing the temperature

by 0.5 �C per cycle) for 30 s, and extension at 72 �C for 1min; (3)

an additional 15 cycles of 94 �C for 30 s, 55 �C for 30 s, and 72 �Cfor 1 min; (4) final extension at 72 �C for 30 min. DGGE was

performed using a DCode system (Bio-Rad, Hercules, CA).

Duplicate DNA samples were used as template, and the

mixture (1:1, v/v) of the duplicate PCR products was loaded

onto an 8% (w/v) acrylamide gel containing a 30e60% dena-

turant gradient, where 100%was defined as 7 M urea with 40%

(v/v) formamide. Electrophoresis was run at 150 V for 7 h in

1 � TAE buffer. After staining with ethidium bromide, visible

bandswere excised and elutedwith distilledwater. The eluted

solution was further PCR-amplified using the corresponding

primers without GC-clamps. The PCR products were purified

from 1% agarose gel and cloned into the pGEM-T Easy vector

(Promega, Madison, WI). The cloned 16S rRNA gene fragments

were sequenced and the results were compared with refer-

ence sequences in the GenBank database using the BLAST

program (http://blast.ncbi.nlm.nih.gov/). Hierarchical classi-

fication of the 16S rRNA gene sequences was also assisted by

“Classifier” from the Ribosomal Database Project (Cole et al.,

2009). Neighbor-joining trees were constructed for

phylogenetic analysis using MEGA 4 software (Tamura et al.,

2007). The nucleotide sequences reported in this study

have been deposited under GenBank accession numbers

HM066947eHM066994.

2.4.3. OrdinationOrdination offers a view into high-dimensional spaces by plot-

ting the strongest structure into reduceddimensions (Falk et al.,

2009).NMSis themostgenerally effectiveordinationmethod for

ecological community data because NMS avoids distributional

assumptions commonly associated with other ordination

techniques (McCune and Grace, 2002). In this study, NMS ordi-

nation based on the Sorensen distancemeasurewas performed

in PC-ORD software (MjM Software Design, Gleneden Beach,

wat e r r e s e a r c h 4 4 ( 2 0 1 0 ) 4 8 3 8e4 8 4 9 4841

OR).ThepresenceorabsenceofeachDGGEbandwasscored1or

0, respectively, to generate three main matrices with rows

DAþDM,DA, andDM. Eachmainmatrixwasprocessed such that

the stress (<10) and the instability (<10�4) criteriaweremet.The

probability of a similar stress obtained by chance was deter-

mined for 40 real and 50 randomized Monte Carlo runs (Morris

et al., 2010). To evaluate the correlation between process

parameters and ordination axes in the joint plots, second

matrices were generated for joint plotting with pH, methane

production, COD and carbohydrate removal efficiency, and

concentrations of acetate, propionate, and ethanol.

3. Results

3.1. Reactor performance

Fig. 1 shows the temporal process performance of the two-

stage anaerobic digesters. Overall, stable operation of the

anaerobic system was achieved with constant production of

methane (Fig. 1a). D1 was operated for 390 d at 7 different

HRTs; D2 was operated for 278 d at 3 different HRTs (Table 2).

The performance of the anaerobic digesters was estimated at

steady states (Table 2). The concentrations of C4eC6 VFAs

were low (<0.2 g/L) in all digesters, the sum of which

accounted for < 10% of the total VFA (TVFA).

Two acidogenic reactors (DA) were operated at HRTs of

4.2e0.7 d (organic loading rate (OLR) of 34.3e213.9 g COD/L$d).

The pH in DA remained low (<4.5) after the start-up period of

15 d (Fig. 1b). The pH in DA at steady state was between 4.2 and

4.4 in runs 1e4 (at acidogenic HRTs of 4.2e2.5 d) and below 4.0

in runs 5e10 (2.1e0.7 d). Concomitant to the relatively high pH

values, a high rate of acidogenesis (i.e., net acetate

production > 13.4 g/L) was achieved in runs 1e4 (Fig. 1d). The

amount of carbohydrate degradation in DA was equivalent to

68e96% of acetate production in these runs. In contrast, net

acetate production in DA was<1.2 g/L in runs 5e10, whichwas

significantly lower (<9%) than that in runs 1e4. In all runs, net

propionate and ethanol productions in DA were estimated to

be <0.8 g/L and <2.0 g/L, respectively (Fig. 1e, f); ethanol

production was higher than TVFA production only in run 10.

The performance of the methanogenic reactors (DM) was

relatively stable throughout the experiment. Methane

production rate increased with respect to the increase in the

OLR (Fig. 1a). However, methane production per unit volume

of substrate decreased in general as HRT decreased (Table 2).

In DM, pH was maintained between 7.6 and 8.1 (Fig. 1b), which

is in the range favorable for methanogens (Speece, 1996). The

COD removal in DM was stable with efficiencies of 71.0e82.3%

(Fig. 1c). Estimated overall COD reduction efficiencies through

the two-stage system were 73.0e85.9% (Table 2). The meth-

anogenic effluent contained relatively low levels of acetate,

propionate, and ethanol (Fig. 1d, e, f). However, the propionate

concentration increased with decreasing HRT, up to

3.7 � 0.3 g/L in run 10. The methanogenic effluent also con-

tained 1.65e2.58 g/L of total ammonia nitrogen and

0.05e0.09 g/L of phosphate, indicating that nutrients (N, P)

were not limiting in this system. The sulfate concentration in

DM was measured to be 0.01e0.03 g/L.

3.2. Microbial community analysis

DGGE and subsequent phylogenetic analysis were conducted

to characterize the microbial community structures in the

two-stage anaerobic digesters. Both bacterial and archaeal

PCRs were performed with DNA samples collected when DA

andDMwere at steady state. Archaeal PCR ofDA samples failed

to produce amplification products, indicating the absence of

archaea in DA due to the suppression of methanogen growth

at low pH (Liu et al., 2002). Archaeal PCR of DM and bacterial

PCR of DA and DM samples successfully amplified 16S rRNA

gene fragments and DGGE band patterns were obtained

(Fig. 2). Phylogenetic affiliations of the 16S rRNA gene

sequences from DGGE bands were determined by comparing

against the GenBank database. Neighbor-joining trees

showing the phylogenetic identities of the 16S rRNA gene

fragments were also constructed (Figs. 3 and 4).

A total of 36bandswereexcisedandanalyzed frombacterial

DGGEs (Fig. 2a, b). Overall, bacterial band patterns in the seed

sludge, DA, and DM were distinct. The phylogenetic affiliations

of DA bacterial community converged within two phyla, Acti-

nobacteria and Firmicutes, and also within two genera, Aer-

iscardovia and Lactobacillus (Fig. 3), although the species

composition of the bacterial community shifted clearly

between runs 1 and 2e4, between runs 2e4 and 5e9, and

between runs 5e9 and 10 (Fig. 2a). B7 was one of the dominant

bands of DA in runs 1e4 (Fig. 2a). B7 was most closely (91%)

related to Aeriscardovia aeriphila, a Gram-positive, non-spore-

forming bacteria which utilizes various carbohydrates to form

acids at pH�4.2 (Simpson et al., 2004). Phylogenetic analysis in

theRibosomalDatabaseProject has classifiedB7 into the genus

Aeriscardoviawith 97%confidence, although this bandwas also

closely (up to 90%) related to Bifidobacterium spp. The band

intensity of B11 was also dominant in DA in runs 2e4. B11

showed 99% sequence similarity with Lactobacillus amylovorus,

a fermentative bacteria which produces lactic acid and small

amounts of acetic acid from sugars (Nakamura, 1981). B13 and

B15 were closely (99e100%) matched with Lactobacillus kefiri,

a heterofermentative microorganism which produces lactic

and other acids simultaneously (Marshall et al., 1984). B12

and B17 were closely related to Lactobacillus acetotolerans and

Lactobacillus suntoryeus with sequence similarity of 99% and

97%, respectively. These two species are homofermentative,

producing lactic acid as the sole fermentative product (Entani

et al., 1986; Cachat and Priest, 2005).

The bacterial community in DM included members affili-

ated within four different phyla, Firmicutes, Proteobacteria,

Spirochaetes, and Bacteroidetes, and one unaffiliated band

(B20) (Fig. 3); thus it was more diverse than the community in

DA. No band obtained from DM was related primarily to a 16S

rRNA gene sequence from an isolated microorganism.

Instead, most of the bands (B20e23, 26e36) were closely

(>97%) related to environmental clones derived from natural

and engineered environments.

The archaeal community structures in the seed sludge and

DM were visualized in Fig. 2c. The archaeal bands in DM were

affiliated within three orders, Methanomicrobiales, Meth-

anosarcinales, and Thermoplasmatales (Fig. 4). Bands similar

toMethanocorpusculumbavaricum (A1e3)were only found in the

Fig. 1 e Experimental results during the operational periods: (a) methane production rate (MPR), (b) pH, (c) COD, (d) acetate, (e)

propionate, and (f) ethanol. DA1 (6), DA2 (:), DM1 (B), and DM2 (C).

wat e r r e s e a r c h 4 4 ( 2 0 1 0 ) 4 8 3 8e4 8 4 94842

seedsludge; bandsA4e8were identifiedonly in runs1e4.A4e5

and A7 were most closely (>98%) related to Methanoculleus

bourgensis and Methanoculleus submarinus, respectively (Fig. 4).

These methanogens utilize hydrogen or formate to produce

methane (Balows et al., 1992; Mikucki et al., 2003). A6 and A8

were closely related to archaeal clones isolated from a pig

manure storage pit (Snell-Castro et al., 2005) and a closed

municipal solidwaste landfill (Huang et al., 2003), respectively;

Fig. 2 e DGGE band patterns of the 16S rRNA gene fragments: (a) bacterial profiles in DA, (b) bacterial profiles in DM, and

(c) archaealprofiles inDM.Each lane isequivalent toeitherseedsludge (seed ) oronesteadystate (indicatedbythe runnumbers).

wat e r r e s e a r c h 4 4 ( 2 0 1 0 ) 4 8 3 8e4 8 4 9 4843

they were affiliated within the order Thermoplasmatales

(Fig. 4). A9e12 showed high (>98%) sequence similarity with

the acetate-utilizingmethanogenMethanosarcina mazei; theM.

mazei-like sequence was retrieved from all experimental runs.

3.3. Ordination

NMS was used to visualize the patterns in microbial

community structure across the sample set (Fig. 5). The NMS

analysis was performed on three individual community

matrices (i.e., DA þ DM, DA, and DM). DM generated a 1-dimen-

sional resultant matrix with two distinct values: one in runs

1e4 and the other in runs 5e10 (figure not shown). Thereby,

NMS analysis on DM bands confirmed the existence of two

distinct microbial community structures, whereas a joint plot

could not be drawn.

Both NMS plots in Fig. 5 met the stress (<10) and the

instability (<10�4) criteria. The Monte Carlo test resulted in

p-values of 0.0196 for DA þ DM and 0.0392 for DA. Microbial

structures in DA and DM reactors (Fig. 5a) were clearly sepa-

rated; they were located at opposite ends of Axis 1A, which

explained 72.0% of the variability in community structures.

Community structures in each digester were also separated

along Axis 2A, which explained 21.8% of the variance.

Parameters such as pH, COD and carbohydrate reduction

efficiency, and acetate and ethanol concentrations were

highly (>0.77) correlated with Axis 1A, whereas these

parameters were less correlated with Axis 2A (<0.63).

The patterns in microbial structure in DA were illustrated

in an NMS joint plot with performance data (Fig. 5b). The

communities could be assigned to four groups corresponding

to runs 1, 2e4, 5e9, and 10. The community shift along Axis 1B

explained 63.8% of the variability in the DGGE band patterns,

and the shift along Axis 2B accounted for 29.8%. Parameters

such as pH, carbohydrate reduction efficiency, and acetate

and propionate concentrations were highly (>0.73) correlated

with longer HRT along ordination Axis 1B (Morris et al., 2010).

In contrast, ethanol concentration was slightly more corre-

lated with the sample in run 10 (at HRT 4.0 d) along Axis 2B

(0.56) than along Axis 2A (0.34).

4. Discussion

Acetate is often regarded as the most important (equivalent

to >70% of methane production) intermediate in anaerobic

digestion (Speece, 1996). Acetate can be directly utilized by the

aceticlastic methanogens such as Methanosarcina spp. There-

fore, conversion of organic materials into acetate in the first

stage of the two-stage reactors provides favorable substrate

for the methanogenic consortia in the second stage (Yang

et al., 2003). In this study, high (>13.4 g/L) production of

acetate was observed only in runs 1e4 (Fig. 1d). The difference

in the acidogenic efficiency in DA between runs 1e4 and runs

5e10 can be attributed to changes in operational factors such

as HRT. HRT is among the most crucial parameters that

determine the efficiency of an acidogenic reactor (Hwang and

Hansen, 1997; Yang et al., 2003). Reduction in HRT imposes

selective pressure on slow-growing microorganisms, which

may result in the microbial community shifts (Demirel and

Yenig, 2002). Accordingly, bacterial community structure

changed from species related to A. aeriphila and L. amylovorus,

acidogens that are capable of producing acetate, in runs 1e4

into species related to homofermentative Lactobacillus spp. in

runs 5e10 (Figs. 2a and 3). Although lactate production was

not determined in this report, the strong intensity of Lactoba-

cillus-like bands suggested that lactate may have been

involved in the degradation of the FRW. In DA, pH was not

externally controlled but was dependent upon the type and

proportion of fermentation products. The pH values in runs

1e4 were between 4.2 and 4.4; the pH values in runs 5e9 were

between 3.4 and 3.5 (Fig. 1b). Similarly, in a three-stage

anaerobic digestion of Korean food waste, the major acido-

genic product was acetate at pH 4.5e5.5 and lactate at pH

B5B7B6

Aeriscardovia aeriphila (AY174107)Bifidobacterium bifidum (U25952)

Bifidobacterium minimum (M58741)Streptomyces albus (AJ621602)

Chloroflexus aurantiacus (D38365)Thermaerobacter marianensis (AB011495)

Pseudomonas aeruginosa (X06684)Burkholderia cepacia (U96927)

Caulobacter vibrioides (AJ009957)Rhodobacter capsulatus (D16428)

B30B32

clone D23 (AM500730)Desulfovibrio cuneatus (X99501)Desulfovibrio desulfuricans (M34113)

Geobacter metallireducens (L07834)Desulforhopalus sp.lsv20 (AF099057)Desulforhopalus vacuolatus (L42613)

B3Syntrophobacter wolinii (X70905)

Myxococcus fulvus (DQ768117)Desulfobulbus propionicus (AY548789)

Syntrophus buswellii (X85131)Smithella propionica (AF126282)

Spirochaeta aurantia (AY599019)Treponema pallidum (M88726)

Treponema maltophilum (X87140)B22

clone BS12 (EU358687)B1

clone A543 (EU283591)B20

clone QEDS3CA02 (CU921669)Flammeovirga aprica (D12655)

B23clone QEEB1DF04 (CU918196)

B21Dysgonomonas gadei (Y18530)

Bacteroides fragilis (CR626927)Bacteroides nordii (AY608697)

Persicobacter diffluens (AB260929)Flavobacterium aquatile (AM230485)

B2clone 035g04.g (EU837886)

B26clone A35 D28_L_B_D03 (EF559197)

Pedobacter heparinus (AJ438172)Sphingobacterium spiritivorum (EF090267)

99

99

99

99

99

99

a

93

99

99

95

78

73

72

9899

99

99

96

98

74

99

99

73

96

98

88

0.05

Bacteroidetes

Actinobacteria

Firmicutes

Proteobacteria

Spirochaetes

Chloroflexi

unidentified

Fig. 3b

Fig. 3 e Neighbor-joining tree illustrating the phylogenetic identities of the bacterial 16S rRNA gene fragments obtained

from DGGE bands excised from seed sludge (:), DA (B), and DM (C). Numbers at nodes are bootstrap values derived from

100 analyses. Firmicutes are presented in a separate tree (b).

wat e r r e s e a r c h 4 4 ( 2 0 1 0 ) 4 8 3 8e4 8 4 94844

3.3e3.4 (Kim et al., 2008). Ethanol is one of the important

intermediates of anaerobic digestion. Ethanol production in

the first stage of the series reactors efficiently delivers energy

to the anaerobic consortia in the second stage (Pipyn and

Verstraete, 1981). In DA, ethanol production of 1.3e1.9 g/L,

equivalent to only 1.9e2.7% of the influent COD concentration,

was observed in runs 1e4 and 10; in runs 5e9, ethanol

production was negligible. Therefore, ethanol appears to have

played a limited role in conveying organic material between

DA and DM.

The COD removal efficiencies in this process (73.0%e85.9%;

Table 2) are comparable to previous studies in which organic

removal efficiencies of two-stage CSTRs ranged from 65 to 85%

(Demirel and Yenig, 2002). This high overall performance can

be attributed to the relatively stable performance of DM

throughout the operational period (Fig. 1c, Table 2). The diver-

sity of anaerobicmicroorganisms inDMwas higher than that in

DA; 14 bacterial and 5 archaeal operational taxonomic units

were identified from DM. Relatives of the bacterial bands from

DM include different trophic groups such as sulfate-reducing

Desulfovibrio spp. (B30, B32; Fig. 3a), carbohydrate-utilizing

Dysgonomonas gadei (B21, B23), syntrophic Syntrophomonaswolfei

(B35; Fig. 3b), sugar- and peptide-utilizing Sporanaerobacter ace-

tigenes (B28, B29), and cellulolytic Clostridium phytofermentans

(B34) (Hofstad et al., 2000; Hernandez-Eugenio et al., 2002;

Warnick et al., 2002). This bacterial diversity appears to have

B10Lactobacillus amylovorus (AY944408)

B8B9B11

Lactobacillus suntoryeus (AY445815)Lactobacillus crispatus (AF257097)

B17B14

B12Lactobacillus acetotolerans (AB303841)

Lactobacillus delbrueckii (CR954253)B15

Lactobacillus kefiri (AY363303)B13B18

clone C12 (EU873789)B16

Lactobacillus pontis (AJ422032)Lactobacillus reuteri (X76328)

B19Lactobacillus panis (NR 026310)

Streptococcus pyogenes (AB002521)Bacillus subtilis (AJ276351)Desulfotomaculum thermobenzoicum (AJ276351)

Syntrophomonas wolfei (DQ666175)B35

clone 134_BE1_15 (FJ825457)B24

B25clone d18 (AB241589)

clone 318-173-HRB1 (FJ669011)Desulfitibacter alkalitolerans (AY538171)

Clostridium butyricum (AJ458420)Clostridium novyi (AB041866)Desulfotomaculum nigrificans (X62176)

Clostridium sticklandii (M26494)B28B29

Sporanaerobacter acetigenes (AF358114)B31

clone 30BF17 (AB330617)B33

clone B-85 (AY676486)B27

clone S5 (EU551089)Acetivibrio cellulolyticus (L35516)

B36clone SB27 (AB494287)

Ruminococcus flavefaciens (L76603)B34

clone 054F04.b (EU837948)Clostridium phytofermentans (AF020431)

Anaerosporobacter mobilis (AY534872)Clostridium celerecrescens (X71848)

Hespellia stercorisuis (AF445264)Ruminococcus gauvreauii (EF529620)B4

clone 24 (FJ534970)

84

b

7290

93

90

99

98

92

91

98

90

98

9999

7594

86

98

99

99

9999

98

99

99

99

77

98

0.02

Lactobacillales

Clostridiales

Bacillales

Fig. 3 e (continued).

wat e r r e s e a r c h 4 4 ( 2 0 1 0 ) 4 8 3 8e4 8 4 9 4845

resulted in themore versatile utilization of organicmaterials in

DM with lower levels of COD and VFAs. One exception to this

trend was the elevated propionate concentration in DM

compared to that in DA in runs 5e10 (Fig. 1e). Propionate is one

of the important intermediates of the anaerobic metabolism

and comprises 6e35% of the carbon balance (Scholten and

Conrad, 2000). The existence of the DGGE band (B35) poten-

tially related to the genus Desulfotomaculum, some members of

which are able to oxidize propionate (McInerney et al., 2008),

implies that propionate metabolism may have occurred in DM.

The slow-growing nature of propionate-utilizing microorgan-

isms (Gavala et al., 2003) can be responsible for the accumula-

tion of propionate at shorter HRTs. Although some bands (B30,

B32) were closely related to sulfate-reducing bacteria (Fig. 3a),

sulfate reduction in this system (0.26e0.27 g/L) accounted for

only 0.2% of the total electron flow calculated as described

previously (Isa et al., 1986).

ThearchaealDGGEresults suggested thatMethanoculleus- and

Methanosarcina-like organisms were likely to be mainly respon-

sible for the hydrogenotrophic and aceticlasticmethanogenesis,

respectively (Figs. 2c and 4). The stable methanogenic perfor-

mance in DM implies the maintenance of well-established

methanogenic consortia throughout the reaction period.

However, the archaeal community structure showed a dynamic

shift between runs 1e4 and runs 5e10 (Figs. 2c and 5a), coinci-

dental with the change of the acidogenic performance in DA.

The putative hydrogenotrophic methanogens related to Meth-

anoculleus appear to have participated in syntrophic fatty acid

mineralization by removing acetogenic products in runs 1e4

(Batstone, 2002; de Bok et al., 2004). The lack of DGGE bands

Methanomicrobiales

Methanosarcinales

Thermoplasmatales

HalobacterialesArchaeoglobales

Methanobacteriales

Methanococcales

Methanopyrales

A1A3A2

Methanocorpusculum bavaricum (AY196676)Methanocorpusculum parvum (M59147)

Methanospirillum hungatei (AY196683)A4

A5Methanoculleus bourgensis (AB065298)

A7Methanoculleus marisnigri (M59134)Methanoculleus submarinus (NR 028856)

Methanomicrobium mobile (M59142)Methanogenium cariaci (M59130)

Methanoplanus petrolearius (U76631)Methanofollis tationis (AF095272)

A9A11

A10A12

Methanosarcina acetivorans (M59137)Methanosarcina mazei (FJ155845)Methanosarcina thermophila (M59140)

Methanosarcina barkeri (AJ012094)Methanolobus tindarius (M59135)

Methanococcoides methylutens (M59127)Methanosaeta concilii (M59146)

Methanosaeta thermophila (AB071701)Methanosaeta harundinacea (AY817738)

Haloferax volcanii (AY425724)Archaeoglobus fulgidus (AE000782)

Methanobacterium formicicum (AF169245)Methanosphaera stadtmanae (CP000102)

Methanobrevibacter ruminantium (AY196666)Methanothermobacter thermautotrophicus (AY196660)

Methanopyrus kandleri (AE009439)Methanococcus voltae (M59290)Methanococcus vannielii (AY196675)

Methanocaldococcus jannaschii (L77117)A6

Uncultured archaeon clone DF86 (AY816986)A8

Uncultured archaeon clone GZK61 (AJ576235)Thermogymnomonas acidicola(AB269873)Thermoplasma acidophilum (M38637)

100

100

100

100

92

100

100

8997

84

82

84

83

100

99

78

77

95

99

99 86

89

99

88

0.05

Fig. 4 e Neighbor-joining tree illustrating the phylogenetic identities of the archaeal 16S rRNA gene fragments obtained

from DGGE bands excised from seed sludge (:) and DM (C). Numbers at nodes are bootstrap values derived from 100

analyses.

wat e r r e s e a r c h 4 4 ( 2 0 1 0 ) 4 8 3 8e4 8 4 94846

related to hydrogenotrophic methanogens in runs 5e10 was

beyond anticipation because hydrogen often accounts for about

30% of the methane production in anaerobiosis (Speece, 1996)

and the influent ethanol, the degradation of which produces

hydrogen,was completely utilized inDM (Fig. 1f). This shift in the

major DGGE bandsmay be attributed to the general limitation of

the PCR-based methods with which a numerically minor but

functionally important population could be omitted in the result

(Forney et al., 2004; Shin et al., 2008). Twoarchaeal bands (A6, A8)

were also identified in DM; they are only distantly related to the

thermoacidophilic non-methanogenic archaea Thermoplasma

acidophilum or Thermogymnomonas acidicola, so their metabolic

roles remain unclear (Itoh et al., 2007). However, many of the

bands (B20e23, B26e36, A6, A8) isolated from DM were closely

(>97%) related toenvironmental clonesderived fromnatural and

engineered environments. This suggests that these yet-to-be-

cultured organisms are ubiquitous in the environment and,

potentially,havebroadmetaboliccapabilities (Huangetal., 2003).

Operational conditions of the series digesters (DA and DM)

differed only in HRT; in both digesters, mesophilic tempera-

ture (35 �C) was maintained and pH was not controlled. At the

start-up, both DA and DM were seeded with the same meso-

philic sludge. After the long-term operation in runs 1 and 2,

however, completely different structures of the microbial

communities, also distinct from the structure in the seed

sludge, have evolved in the series reactors (Fig. 5a). As a result,

the performance of the two-stage reactors was totally

different in terms of biogas production, COD removal, and the

effluent quality. Interestingly, the performance was also

different between DA in run 1 (HRT of 4.2 d) and DM in run 9

(4.2 d) or 10 (3.3 d), where theHRT ofDMwas equal to or shorter

than that of DA. Therefore, it can be deduced that the main-

tenance of well-functioning methanogenic consortia through

a systematic acclimation to a new substrate, e.g. a stepwise

increase in OLR, is important for the successful operation of

anaerobic processes (McMahon et al., 2004; Song et al., 2010).

Fig. 5 e Sample ordinations in NMS joint plots of DGGE

band patterns and performance data in (a) both DA and DM

and (b) DA reactors. The presence or absence of each band

was scored to generate the data matrices for DGGE band

patterns; pH, methane production, percent COD removal

(CODrem) and percent carbohydrate removal (CARrem), and

concentrations of acetate, propionate, and ethanol were

used to generate the data matrices for the performance.

A Sorenson distance measurement was employed for the

NMS analysis. Each point is labeled with the corresponding

run number. Proportion of variance represented by each

axis is given in parentheses.

wat e r r e s e a r c h 4 4 ( 2 0 1 0 ) 4 8 3 8e4 8 4 9 4847

5. Conclusions

Themicrobial community structures in a two-stage anaerobic

digestion for the treatment of FRW were assessed in this

study.

� Stable operation at 10 different HRTs was achieved with

estimated overall COD removal efficiencies of 73.0e85.9%

at OLR of 5.7e35.6 g COD/L$d.

� Performance of the acidogenic reactors changed signifi-

cantly during operation due to the decrease of HRT. The

acidogenic performance change coincided with bacterial

transition from Aeriscardovia- and L. amylovorus-related

species to L. acetotolerans- and L. kefiri-like organisms.

� Performance of the methanogenic reactors was relatively

stable throughout the reaction. Higher diversity of

microorganisms, composed of both bacterial and archaeal

populations, was observed in the methanogenic reactors.

Shift of distinct DGGE bands, from hydrogenotrophic

Methanoculleus- to aceticlastic Methanosarcina-like metha-

nogens, was observed coincidental to the bacterial

community shift in the acidogenic reactors.

� These trends were confirmed by the NMS joint plot of

microbial shifts along with performance parameters.

These results indicated that the overall process perfor-

mance was relatively stable compared to the dynamic

changes in the microbial structures and the acidogenic

performance.

Acknowledgements

This research was supported in part by Korea Ministry of Envi-

ronment as “Human Resource Development Project for Energy

fromWaste & Recycling”. In addition this work was financially

supported by Korea Ministry of Education, Science and Tech-

nology through the BK-21 program and by Korea Ministry of

Knowledge and Economyas “ManpowerDevelopment Program

for Energy and Resources”. The authors thank Youngback Kim

and Suhyun Kim for their contribution to the experiments.

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