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Microbial community structure and dynamics intwo-stage vs single-stage thermophilic anaerobicdigestion of mixed swine slurry and market bio-waste
Giuseppe Merlino a, Aurora Rizzi a, Andrea Schievano b, Alberto Tenca b, Barbara Scaglia b,Roberto Oberti b, Fabrizio Adani b, Daniele Daffonchio a,*aDepartment of Food Environmental and Nutritional Sciences (DEFENS), University of Milan, Celoria 2, 20133 Milan, ItalybDepartment of Agricultural and Environmental Science (DiSAA), University of Milan, Celoria 2, 20133 Milan, Italy
a r t i c l e i n f o
Article history:
Received 5 August 2012
Received in revised form
27 November 2012
Accepted 4 January 2013
Available online 18 January 2013
Keywords:
Bacterial and archaeal
anaerobic consortia
Bio-hydrogen
Bio-methane
PCR-DGGE
Real-time PCR
* Corresponding author. Tel.: þ39 0250319117E-mail address: daniele.daffonchio@unim
0043-1354/$ e see front matter ª 2013 Elsevhttp://dx.doi.org/10.1016/j.watres.2013.01.007
a b s t r a c t
The microbial community of a thermophilic two-stage process was monitored during two-
months operation and compared to a conventional single-stage process. Qualitative and
quantitative microbial dynamics were analysed by Denaturing Gradient Gel Electro-
phoresis (DGGE) and real-time PCR techniques, respectively. The bacterial community was
dominated by heat-shock resistant, spore-forming clostridia in the two-stage process,
whereas a more diverse and dynamic community (Firmicutes, Bacteroidetes, Synergistes) was
observed in the single-stage process. A significant evolution of bacterial community
occurred over time in the acidogenic phase of the two-phase process with the selection of
few dominant species associated to stable hydrogen production. The archaeal community,
dominated by the acetoclastic Methanosarcinales in both methanogen reactors, showed
a significant diversity change in the single-stage process after a period of adaptation to the
feeding conditions, compared to a constant stability in the methanogenic reactor of the
two-stage process. The more diverse and dynamic bacterial and archaeal community of
single-stage process compared to the two-stage process accounted for the best degradation
activity, and consequently the best performance, in this reactor. The microbiological per-
spective proved a useful tool for a better understanding and comparison of anaerobic
digestion processes.
ª 2013 Elsevier Ltd. All rights reserved.
1. Introduction a revived and increased interest as an environmentally-
Anaerobic digestion (AD) process is an effective way to treat
organic waste producing energy in the form of biogas of high
calorific value (methane and hydrogen) (Angenent et al., 2004).
This technology has been successfully used to produce
methane since several decades, and recently its use has raised
; fax: þ39 0250319238.i.it (D. Daffonchio).ier Ltd. All rights reserved
friendly alternative to fossil fuel-derived energy.
AD is a complex biological process operated by different
functional groups of microorganisms that convert organic
matter to methane through three major steps (hydrolysis/
acidogenesis, acetogenesis and methanogenesis). AD is
commonly run in single-stage process, however recently
.
wat e r r e s e a r c h 4 7 ( 2 0 1 3 ) 1 9 8 3e1 9 9 51984
a two-stage design that splits the overall process in two
phases, operated in two reactors in series with production of
hydrogen and methane separately, has been established
(Demirel et al., 2010). In the first-stage reactor, bacteria fer-
ment organic compounds, generally carbohydrates, directly
to hydrogen, carbon dioxide, organic acids and alcohols
(Valdez-Vazquez and Poggi-Varaldo, 2009).
In the second-stage reactor, methanogens convert the re-
sidual energy contained in the high-volatile fatty acids (VFAs)
effluent to bio-methane.
Early studies of bio-hydrogen production were focused on
pure cultures of Clostridia and Enterobacteria fermenting simple
soluble substrates, like starch, glucose or sucrose. However,
pure carbohydrates are very expensive and the use of pure
culture system is problematic as they are prone to con-
tamination. In following studies, mixed cultures fermenting
low cost solid organic waste were proved to be effective, easily
maintained and controlled. In general, the choice of sub-
strates for bio-hydrogen production is based on some major
criteria such as availability, cost, biodegradability and
carbohydrate-content because of the high bio-hydrogen pro-
ducing potential. The use of combined wastewaters has led to
a new path for bio-hydrogen production (Guo et al., 2010). In
particular, co-digestion of nitrogen-rich livestock manure
mixed with carbohydrate-rich materials, has been considered
for bio-hydrogen production (Guo et al., 2010).
Hydrogen is an important energy transfer intermediate in
AD. In the acidogenic phase of a two-phase system, the key
issue is to enable the accumulation of hydrogen, typically
consumed very quickly by microorganisms. Three microbial
groups are key players in hydrogen turnover: H2-producing
fermenting bacteria (HPB), H2-consuming methanogens and
H2-consuming acetogens. In order to facilitate HPB, while
preventing H2-consuming microorganisms, pretreatments
and biokinetic control of parameters, such as, pH and hy-
draulic retention time (HRT) are used. Heat-treatment of the
inoculum, selecting for spore-forming bacteria, decreases
methanogen content. Maintaining a low in-reactor pH and
a high dilution rate prevent the growth of methanogens and
possibly other H2-consuming microorganisms (Valdez-
Vazquez and Poggi-Varaldo, 2009). However, the knowledge
on microbial community structure and dynamics in the
two-stage processes is still limited. Studies focusedmainly on
the microbial qualitative diversity (Jo et al., 2007; Xing et al.,
2008; Luo et al., 2011b) but not on the qualitative and quanti-
tative dynamics of the key functional microbial groups
occurring in the two-stages AD processes. As the microor-
ganisms with their biochemical reactions are the key players
of the process, investigating the complexity of the microbial
community and its dynamics is a prerequisite to understand
the AD process, control it and improving its efficiency.
The aim of this study was to characterize and compare,
qualitatively and quantitatively, the bacterial and archaeal
community of a two-stages and a conventional single-stage
processes, both fed with the same mixture of swine manure
and fruit and vegetable market wastes. In a previous study we
compared the energetic and chemical performances of
a two-stages and a single-stage AD processes run in lab-scale
thermophilic intermittent-continuous stirred tank reactors
(I-CSTR) (Schievano et al., 2012). We found comparable overall
energy recovery for the two processes, though some organic
matter was left undegraded in two-stage process indicating
partial inefficiency. Here we report the results of a study on
the structure and dynamics of microbial communities in the
two processes assessed by PCR-Denaturing Gradient Gel
Electrophoresis (DGGE). We complemented the study of the
microbial communities dynamics by evaluating the temporal
quantitative changes of themajor functional microbial groups
involved in the two processes by quantitative Real-Time PCR.
Our aim was to give a contribution to the knowledge of
microbiological aspects of two types of reactor processes
investigating, together with previous analytical data, micro-
bial signatures associated to the performance of two
processes.
2. Materials and methods
2.1. Bioreactor set up and operation
Three previously described (Schievano et al., 2012) anaerobic
completely stirred tank reactor (CSTR) were operated and
used as source of biomass samples. The two-stage process
consisted of a hydrogen-producing reactor (R1) with 2.3 l
working volume and a methane-producing reactor (R2) with
14.7 l working volume. The single-stage process was a reactor
with 14.7 l working volume (R3). R1 was inoculated with heat-
shocked (100 �C for 2 h) anaerobic seeding sludge from a full-
scale biogas plant treating household source-separated bio-
waste and agro-industrial by-products. The same sludge,
without heat-shock, was used as inoculum for both R2 and R3.
The feeding substrate, a mixture (4:1 w/w ratio) of swine
manure and fruits and vegetables market waste (a chemical
characterization presented in Schievano et al. (2012)) was
supplied intermittently to R1 and R2 by peristaltic pumps. The
operational hydraulic retention time (HRT) was 3, 22 and 25
days in R1, R2 and R3, respectively. Temperature was main-
tained at 55 � 2 �C, pH was measured in continuous and not
actively controlled. Qualitative and quantitative biogas anal-
ysis were performed automatically in each reactor by gas
flow-meters (Schievano et al., 2012). The two-stage hydrogen-
methane and the single-stage methane AD processes were
monitored for 2 and 1 month, respectively.
2.2. DNA extraction
Reactor samples were centrifuged (10,000 � g, 30 min, 4 �C),the resulting pellet washed twice with sterile water and cen-
trifuged again in the same conditions. Variable volumes
(2e3 ml) were used for centrifugation to obtain a final pellet of
100mg. The pellets were stored at�20 �C until DNA extraction
performed using the PowerSoil DNA Isolation kit (MoBio Lab-
oratories, Inc., Milan, Italy) according to the manufacturer’s
instructions. All DNA were extracted in duplicate.
2.3. PCR-DGGE analysis
Bacterial and archaeal 16S rRNA gene were amplified by PCR
using the primer sets GC-357-F/907-R and GC-ARC787-F/
ARC1059-R, respectively (Sass et al., 2001; Hwang et al., 2008).
wat e r r e s e a r c h 4 7 ( 2 0 1 3 ) 1 9 8 3e1 9 9 5 1985
PCR reactions and thermal programs were performed as pre-
viously described (Merlino et al., 2012). PCR products (approx.
300 ng) were loaded onto 7% (w/v) polyacrylamide gels
(0.75 mm) containing a denaturant gradient of 30e70% or
40e60% for Bacteria and Archaea, respectively (100% denatur-
ant contained 7 M urea and 40% formamide). Electrophoresis
was run in 1 � TAE buffer using a D-Code electrophoresis
system (BioRad) at 90 V and 60 �C for 17 h. Gels were stained
with SYBR(R) Green I Nucleic A (Invitrogen) and documented
with the GelDoc 2000 apparatus (BioRad) by using the Di-
versity Database software (BioRad). Relevant DNA bands were
excised from the gels and eluted in 50 ml of TriseHCl 10 mM.
Five microliters of DNA was PCR reamplified and the obtained
sequences (Macrogen, Seoul, Korea) were compared against
the NCBI genomic database with the BLAST search alignment
tool. Sequence alignment and phylogenetic trees were carried
out using theMEGA software, version 5.0 (Tamura et al., 2011).
The trees were constructed using the Maximum Likelihood
algorithm and the Tamura Nei parameter correction and were
bootstrapped 2000 times.
DGGE gel profiles were analysed using the Quantity One
software (Biorad). Lane background was subtracted by the
“rolling disk” tool. Bands were detected automatically and
matched manually. DGGE-based molecular parameters,
namely dynamycs (Dy), richness (Rr) and community organi-
zation (Co), were calculated as previously described (Marzorati
et al., 2008). Briefly, Dy was calculated from the similarity
matrix (100 e similarity%); Rr was the total number of bands
multiplied by the percentage of denaturing gradient used; Co
was the percentage of Gini coefficient, a value describing the
degree of evenness within a community by measuring the
normalized area between a given Lorenz curve and the perfect
evenness line. The Co parameter informs on the functional
organization of the microbial community describing the spe-
cies abundance distribution within a microbial community in
terms of degrees of evenness (0e100). Low Co values represent
a highly even community, whereas high Co values are char-
acteristic of uneven communities. Average Co (Co 45e60)
values correspond to balanced community, characterized by
most functional stability and resilience. The Co coefficient
Table 1 e Real time PCR primer sets used in this study.
Target group Name Sequence
Bacteria Bac357-F CCTACGGGAGGCAGCAG
Bac907-R CCGTCAATTCCTTTGAGTTT
Hydrogen-producing
bacteria (HPB)
hydF1 GCCGACCTKACMATMATGGA
hydH ATRCARCCRCCSGGRCAGGCCAT
Acetogens fhs1 GTWTGGGCWAARGGYGGMGAA
FTHFS-r GTATTGDGTYTTRGCCATACA
Sulphate-reducing
bacteria (SRB)
Drs1þ-F ACSCACTGGAAGCACGGCGG
Dsr-R GTGGMRCCGTGCAKRTTGG
Archaea Arch 931-F AGGAATTGGCGGGGGAGCA
ArchM1100-R BGGGTCTCGCTCGTTRC
Methanosarcinales Msl812-F GTAAACGATRYTCGCTAGGT
Msl1159-R GGTCCCCACAGWGTACC
was calculated based on the Gini value, Dy was determined by
the moving window analysis (Marzorati et al., 2008).
2.4. Real-time PCR analysis
Quantitative PCR assays were performed using primer set
reported in Table 1. Considering that in anaerobic reactor
most Archaea are methanogens (Yu et al., 2005), an archaeal
PCR real time assay was used to estimate quantitatively
methanogens. PCR SYBR green reactions were prepared by
using the “Brilliant SYBR Green QPCR Master Mix” kit (Stra-
tagene) in 96-well plates on the I-Cycler (Biorad). The reaction
mix (25 ml) contained: 1 � Brilliant SYBR Green (2.5 mMMgCl2),
0.12 mM of each primers, and approx. 100 ng of extracted DNA.
In the case of primer set Msl812-F/Msl1159-R extra MgCl2 was
added to a final concentration of 4.0 mM. One real time assay
was carried out per extracted DNA. The thermal cycling pro-
gram consisted of 10 min at 95 �C, followed by 40 cycles of 30 s
at 95 �C, 1 min at X �C (X ¼ 58 �C for Bac357-F/Bac907-R, 49 �Cfor hyd-F1/hyd-R1, 55 �C for fhs1-F/THFS-R, 59 �C for Drs1þ-F/
Dsr-R, 64 �C for Arch 931-F/ArchM1100-R, 60 �C for Msl812-F/
Msl1159-R) and 1min at 72 �C. Finally, amelting curve analysis
was performed for verifying the specificity of PCR products.
The program was as follows: denaturation of 1 min at 95 �C,cooling of 1 min at 55 �C and then 95 �C again, at a rate of
þ0.5 �C per cycle. Cycle threshold (Ct) values were calculated
using the Biorad real-time software (version 3.0a) according to
the manufacturer’s instructions. Standard curves were gen-
erated by tenfold diluting the standard plasmids to obtain
a series of concentrations ranging from 10 to 108 copies of
plasmid DNA. The standard plasmids were constructed as
previously described (Merlino et al., 2012) by cloning frag-
ments obtained from PCR amplification of genomic DNA from
the bacterium Asaia for bacteria) or from total DNA (for
archaea) from an anaerobic batch digester (Table 1). Conver-
sion of 16S rRNA gene copy numbers to cell number was done
considering the average 16S rRNA gene copy numbers of
bacteria (4/cell) and methanogens (2.5 copies/cell) reported in
the Ribosomal RNA Database (rrnDB, Lee et al., 2009). In the
case of real-time PCR targeting functional genes, it was
Targetgene
Ampliconsize (bp)
Closest relative ofstandard fragment
(% similarity)
Reference
16S
rRNA
550-585 Asaia sp. AM404260
(100%)
Favia et al.,
2007
hydA 700 Uncultured bacterium
EU828435 (75%)
Xing et al.,
2008
GG fhs 250 Clostridium beijerinckii
CP000721 (76%)
Xu et al.,
2009
dsrA 221 Desulfobacterium
autotrophicum
CP001087 (98%)
Kondo et al.,
2004
16S
rRNA
169 Methanobrevibacter
sp. DQ402034 (98%)
Einen et al.,
2008
16S
rRNA
354 Methanosarcina mazeii
LM5 DQ987528 (98%)
Yu et al.,
2005
wat e r r e s e a r c h 4 7 ( 2 0 1 3 ) 1 9 8 3e1 9 9 51986
assumed that copy number was equivalent to cell number
based on the premise that the majority of known bacteria in
the database have a single copy of the functional genes con-
sidered (Kondo et al., 2004; Xu et al., 2009).
3. Results
3.1. Operation performance of anaerobic bioreactors
The two-stage process was monitored over a period of two
months including the start-up period (days 0e9), a steady
Fig. 1 e Hydrogen/methane productions in R1 (A), R2 (B) and R3 (
start-up period and a 17-long days period after the steady state
state period (days 9e43) described in Schievano et al. (2012),
and a further 17-days long period where some imbalances
occurred (Fig. 1A and B), whereas the single-stage process was
monitored only along the steady state period (Fig. 1C). As
previously reported (Schievano et al., 2012), at the steady state
hydrogen production rate was of 1.5 Ndm3 H2/L d (45% [v/v]
content in biogas) in the acidogenic reactors (R1), whereas
methane production rates of 0.53 and 0.54 Ndm3 CH4/L d were
registered for the methanogenic reactors of the two- (R2) and
single-stage (R3) processes, respectively (68% and 54% [v/v]
content in biogas). In R1 methane was detected between day
40 and day 50 with percentages of 1e5% of total biogas. A
C) during the observed operational period. In R1 and R2 the
are indicated by shading.
wat e r r e s e a r c h 4 7 ( 2 0 1 3 ) 1 9 8 3e1 9 9 5 1987
serious biogas production failure occurred from days 49e51
both in R1 and R2, and was attributed to electric energy
shortage that determined a stop of the thermal control and
a drop of the reactor temperatures.
In R1 the major acidogenic byproducts were hexanoic acid,
acetate, butyrate and propionate. Total VFAs concentration
was approx. 3900 mg acetate/L and acetate accumulated at
more than 2500 mg/L. In R2 the concentration of acetate
decreased and remained at low level (<500 mg/L) indicating
a consuming activity by acetotrophic methanogens. Butyrate
was completely degraded suggesting the presence of active
syntrophic bacteria. After the steady-state, on day 59, an ini-
tial accumulation of VFA (1045 mg acetate/L), and con-
sequently a partial inhibition of the process, occurred
(1890 mg acetate/L at day 66). In R3 the total VFAs were
detected at concentrations about approx. ten times lower than
R2 (763e1056 mg acetate/L) with acetate as the major product
and both butyrate and propionate under the limit of detection.
3.2. Microbial community characterization of two-stageanaerobic process
3.2.1. Hydrogenogenic acidogenic processThe PCR-DGGE of Bacteria is showed in Fig. 2A and the phy-
logenetic positions of the identified sequences are indicated in
Fig. 3 (sequences affiliation in Table S1 of supplemental ma-
terial). Most bands were not closely related to known species.
All bands were assigned to the phylum of Firmicutes; nine fell
into the Clostridiales order and two into the Thermoanaer-
obacterales order. Band H1, strictly related to an uncultured
Fig. 2 e Bacterial (A, B, C) and archaeal (A0, B0, C0) DGGE profiles
extracted from samples obtained from R1 (A, A0), R2 (B, B0) andreactor (days), lane F indicate the DGGE profile of the feeding so
species from an hydrogen fermenter (Lee et al., 2010b), was
detected throughout the entire time-course of the process
and, according to its intensity, appeared as a predominant
microorganism. Several other bands (H2-H8), mainly detected
from day 9 to day 15, were also closely related (99e100%
similarity) to uncultured bacteria detected by the same au-
thors (Lee et al., 2010b). Bands H1, and H5-H8 were assigned to
the Ruminococcaceae family, and showed 94% similarity to
Clostridium sp. BS-1, a sludge isolate fermenting D-galactitol to
H2, acetate, butyrate and hexanoic acid (Jeon et al., 2010), and
93% similarity to Clostridium sp. strain Z6, isolated from paper
mill wastewater, and Clostridium sporosphaeroides, capable to
produce hydrogen (and acetate) from glutamate. Bands H2
and H3, assigned to unclassified Lachnospiraceae, were closely
related to an uncultured bacterium from an hydrogen digester
(Lee et al., 2010a) and, more distantly, to uncultured Clostri-
dium clones involved in the cellulosic and lignocellulosic
waste digestion (Shiratori et al., 2006). Bands H9 and H10,
showing a high intensity mostly after 36 day of operation,
grouped into the Clostridiaceae cluster I and fullymatchedwith
many uncultured bacteria associated to faeces and anaerobic
reactors. Band H7 matched (99.4%) with Clostridium cellulosi,
a thermophilic cellulolytic bacterium frequently detected in
H2-producing systems. Band H4, detected at days 11e15,
strictly matched (99.7%) with an uncultured Thermoanaer-
obacterium from a hydrogen reactor treating food waste
(Wang, 2008) and was also related (99.1%) to Thermoanaer-
obacterium thermosaccharolyticum, a thermophilic saccharolytic
microorganism involved in production of large hydrogen
amount (Ueno et al., 2001).
of the 16S rRNA gene PCR products amplified from DNA
R3 (C, C0). Lanes are labelled with the sampled time of the
urce. Dots and numbers indicate the bands sequenced.
Fig. 3 e Phylogenetic tree showing the phylogenetic relationships of bacterial 16S rRNA sequences affiliated to Firmicutes
phylum with reference sequences deposited at the GenBank database. Sequences from feeding source, R1, R2 and R3 are
indicated with the capital letters F, H, T and S, respectively. Un indicates an uncultered bacterium. Numbers at nodes
represent bootstrap values. The scale bar represents a sequence divergence of 5%.
wat e r r e s e a r c h 4 7 ( 2 0 1 3 ) 1 9 8 3e1 9 9 51988
The bacterial DGGE pattern was further characterized
using parameters independent from the DGGE run, namely,
microbial richness (Rr), dynamics of change (Dy) and com-
munity organization (Co) (Fig. 4). Rr was higher in the start-up
period (Rr-indices of 30e40), thereafter Rr decreased reaching
at the end of the sampling values (6e10) corresponding to low
range-weighted richness. The Dy values, were generally kept
high, indicating the adaption of the community during the
Fig. 4 e Microbial richness (Rr), dynamics (Dy), and community organization (Co) parameters from bacterial (A, B) and
archaeal (C, D) DGGE profiles of R1 (A), R2 (C) and R3 (B, D).
wat e r r e s e a r c h 4 7 ( 2 0 1 3 ) 1 9 8 3e1 9 9 5 1989
process. Dy decreased after day 43 and was very low the last
day of sampling (rate of 8%). Variable values of Co were
observed during the start-up period, thereafter stabilizing to
values (on average approx. 40) representing a relatively mod-
erate organized community.
In order to account for the methane production recorded,
a PCR-DGGE analysis was carried out on Archaea (Fig. 2A0). Aphylogenetic tree of identified sequences is shown in Fig. 5
(sequences affiliation in Table S2 of supplemental material).
A dominant band (h2) affiliated (96.9%) to Methanosaeta was
found in the initial days of the process, but after day 36 was
replaced, at least in term of dominant intensity, by two bands
(bands h5 and h6) affiliated (98%) to Metanogenium sp.
Quantitative measurements of the bacterial abundance in
the acidogenic reactor are shown in Fig. 6. Bacteria were pre-
sent at high concentrations (108e109 bacteria per ml). Within
Bacteria, HPB represented only 0.05e1.4% of total Bacteria,
whereas acetogens were 0.6e6.2% of total Bacteria. Number of
HPB remained almost constant during the process (106 bac-
teria per ml), though a decrease was observed from day 36 to
day 50 with a ratio HPB to total Bacteria of about 0.05%. The
acetogens, with an abundance similar to that of HPB in the
first ten days of hydrogen production, thereafter increased of
one order magnitude higher than HPB. Sulfate-reducing bac-
teria (SRB) counted one order magnitude lower than HPB
(about 105 bacteria per ml). A slight increase was observed at
day 43 in correspondence of a declining trend of HPB and also
of an increase of total Bacteria. Archaea were at low titre after
heat shock treatment (104 bacteria/ml) and were of two-three
orders of magnitude lower than Bacteria. Within Archaea,
Methanosarcinales represented approx. 1% of total Archaea,
declining to 0.1% at day 64. In the influent, Methanosarcinales
were detected at low concentration too (7%).
3.2.2. Methanogenic processThe PCR-DGGE of Archaea is showed in Fig. 2B and the phylo-
genetic positions of the identified sequences are indicated in
Fig. 5 (for sequences affiliation see Table S2 of supplemental
material). The PCR-DGGE profiles showed always three
strongly intense bands (t1, t2, t3), closely related to each other
and to Methanosarcina mazeii (>98%). Bands t5 and t6, appear-
ing at day 60, were closely related (>99%) to the genus Meth-
anothermobacter which depends entirely on H2/CO2 as energy
and carbon sources (Schill et al., 1999). The statistical analysis
of DGGE profiles evidenced a stable, highly specialized (Rr < 4)
community. A notable change (37%) occurred only at day 60 in
correspondence to a partial accumulation of VFAs. The Co
values were around 40e50, usually reported for good perfor-
mance reactors (Carballa et al., 2011).
PCR-DGGE analysis carried out on Bacteria evidenced in R2,
like in R1, a bacterial community dominated by Firmicutes
(Fig. 2B0 and Table S2). In R2was found C. cellulosi (band T1) and
other microorganisms (bands T3, T7, T8) already identified in
R1 and assigned to unclassified Ruminococcaceae. The other
identified sequences could not be attributed to known species,
but were highly similar (>99%) to sequences from thermo-
philic reactors (Tang et al., 2011; Sasaki et al., 2011; Goberna
et al., 2009; Shiratori et al., 2006); in particular, bands T10
and T11 matched (99e100%) with the unknown DAD cluster 3
(Tang et al., 2011). Band T2 was affiliated to the Thermotogae
Fig. 5 e Phylogenetic tree showing the phylogenetic relationships of archaeal 16S rRNA sequences with reference sequences
deposited at the GenBank database. Sequences from feeding source, R1, R2 and R3 are indicated with the lower-case letters
f, h, t and s, respectively. Un indicates an uncultered bacterium. Numbers at nodes represent bootstrap values. The scale bar
represents a sequence divergence of 10%.
wat e r r e s e a r c h 4 7 ( 2 0 1 3 ) 1 9 8 3e1 9 9 51990
phylum, consisting of anaerobic hyperthermophilic bacteria
capable of using a great variety of carbohydrates, and gen-
erating hydrogen (Eriksen et al., 2010).
In R2 the abundance of the different populations remained
almost constant during theprocess (Fig. 6).Archaea and Bacteria
were present at rather similar concentrations. Methanogen
numberwas higher than in R1, around 107e108 bacteria perml,
a range typical of anaerobic reactors (Yu et al., 2005; Lee et al.,
2008). Methanosarcinales were the dominant methanogens rep-
resenting approx. 50% of the total Archaea, in agreement with
the PCR-DGGE data. Archaea and Methanosarcinales showed the
same trend during the operation. The number of Meth-
anosarcinales decreased in correspondence to the partial inhi-
bition of the process, in accordance with PCR-DGGE data.
SRB, potential competitors of methanogens, were four
order magnitude lower than Archaea (103 bacteria per ml),
while acetogens and the HPB remained relatively stable dur-
ing all the operation (average values of 2 � 107 and 5 � 106
bacteria per ml, respectively).
3.3. Microbial community characterization of single-stage anaerobic process
PCR-DGGE bands of Archaea (Fig. 2C0) belonged mainly to the
Methanosarcinales (Fig. 5 and Table S2). Bands s1, s2 and s3,
identical to those detected in R2, were associated to the same
sludge used for the start-up of the two processes. Bands s4 and
s6 were related (>97.7%) to Methanosarcina spp. Bands s9 and
s10 both matched, with 97.3% and 99.5% similarity respec-
tively, with Methanosarcina mazeii and Methanosarcina lacustris.
Band s5, which showed a strong intensity after 15 day, was
affiliated to Methanosaeta concilii. The faint bands s7 and s8
were affiliated (>98.0%) to Methanothermobacter. The archaeal
community structure, on the contrary of R2, changed over
time. After two weeks, the community was drastically shifted
(rate of 88%) and thereafter stabilized. The community was
richer than in R2 (Rr average value of 6.8). Co values were on
slightly higher than those of R2, indicating a moderately
organized community.
PCR-DGGE analysis of Bacteria indicated a dominance of
Firmicutes, Clostridia and Bacilli classes (Fig. 2C). The bands of
Bacilli (S1eS3) were replaced after day 15 by high intensity
bands related to Bacteroidetes (S4eS7). Bands S1eS3 were
highly similar (99.1e100%) to Bacillus infernus (96.8e97.8%), an
anaerobic species able to ferment glucose and utilize formate
and lactate for growth (Boone et al., 1995). Bands S4eS7 were
assigned to unclassified Porphyromonadaceae, bacteria capable
of producing VFA from carbohydrates or proteins (Ziganshin
et al., 2011). Considering the strong intensity of these bands,
probably these bacteria played an important role in
Fig. 6 e Concentrations of microorganisms in R1 (A), R2 (B) and R3 (C) during the observed period. Values are averages of two
measurements. HPB and SRB were not detected at day 0 (after heat-shock treatment).
wat e r r e s e a r c h 4 7 ( 2 0 1 3 ) 1 9 8 3e1 9 9 5 1991
hydrolysis and acidogenesis. A microorganism stably detec-
ted throughout the process was Anaerobaculum (band S8), able
to ferment mainly peptides and organic acids to acetate,
hydrogen and CO2 (Menes and Muxı, 2002). Bands S9 and S10
belonged to the Clostridiaceae cluster I. Bands S11 and S12
clustered with unknown clones, from thermophilic reactors,
grouping in the cluster DAD 1 (Tang et al., 2011) and DAD3,
respectively. Band S13 and S14 were correlated to Thermace-
togenium (Hattori et al., 2000) and Tepidanaerobacter (Sekiguchi
et al., 2006), thermophilic syntrophic acetate-oxidizing bac-
teria capable to form methane in association with hydro-
genotrophic methanogens. Statistical analysis of bacterial
PCR-DGGE profiles indicated a very high diversity (average
Rr value of 65), higher than in R1. Dy had a very similar trend
to that observed for Archaea, with a notable community shift
at day 15 (rate 66%). Constant Co values of approx. 40 indi-
cated a moderately even community that remained stable
during the operations.
wat e r r e s e a r c h 4 7 ( 2 0 1 3 ) 1 9 8 3e1 9 9 51992
Quantitativemeasurements of Bacteria, acetogens, SRB and
HPB in reactor R3 showed values similar to those in R2 (Fig. 6).
On the contrary, both totalArchaea andMethanosarcinaleswere
estimated in lower numbers than in R2 (below 107 bacteria per
ml). The number of Methanosarcinales decreased with the
changing of the community structure, dropping to 32% of total
Archaea at day 15 and increasing again to 58% at day 29.
4. Discussion
In this study the dynamics of microbial community structure
in a two- and a single-stage AD reactors have been inves-
tigated and compared. As models were used I-CTSR reactors
operating with some equal working conditions (inocula from
the same methanogenic sludge, feeding source, temperature,
and non-controlled pH) and some operational parameters
(HRT, loading rate, heat-shock treatment of acidogenic reac-
tor) specifically designed for the two AD processes.
Overall, the study showed that the microbial community
structure and dynamic was different in twoAD processes both
for Bacteria and Archaea. Resistant spore-formers Firmicutes
selected by the heat-shock treatment dominated in R1 and R2,
whereas a more diverse community (Firmicutes, Bacteroidetes,
Synergistes) was found in R3. In R1 and R2, most of the bacteria
were related to the order Clostridiales, more specifically to the
Clostridium genus. Clostridium spp. are capable of ferment
cellulose and various carbohydrates mainly to acetate, buty-
rate and hydrogen (Valdez-Vazquez and Poggi-Varaldo, 2009)
and their prevalence in stable H2-producing systems has been
already documented (Jo et al., 2007). Hence, they can account
for the hydrogen production recorded in the acidogenic reac-
tor. The majority of identified species, however, were not
referable to known cultured species, with the exception of C.
cellulosi. Nevertheless, many of the identified microorganisms
were phylogenetically related to microorganisms from ther-
mophilic acidogenic anaerobic reactors fed with vegetable
kitchen waste and, more distantly, to Clostridium species
(Clostridium sp. BS-1, Clostridium sp. Z6) included into the
Ruminococcaceae cluster. The presence in the digester of spe-
cies with degrading ability similar to that of Clostridium sp. BS-
1 may account for the detection of high hexanoic acid in the
reactor. Bioavailable D-galactitol, a reduced form of D-gal-
actose, is in fact contained in many fruit and vegetable resi-
dues like those used as feeding source. On the other hand, the
dominance of uncultured bacteria affiliated to Clostridium sp.
Z6 has been previously reported in other hydrogen-producing
reactors (Chu et al., 2010; Lee et al., 2010a) which operated at
55 �C treating food waste without heat treatment of inoculum.
Hence, it is likely that in this study the selection and the
dominance of these clostridia has been favoured by a combi-
nation of various operational parameters (temperaure, feed-
ing source, reactor type, TS, pH and HRT) rather than by the
inoculum pre-treatment, in agreement with the findings of
Luo et al. (2011).
In R2, as well in R1, not only the species diversity was rel-
atively low, but a relatively dynamic bacterial community
simplified over time. A specialized community, however,
though highly functional, is more sensitive to changes since it
lacks alternative players when impaired by stresses. This may
explain the partially inefficient biodegradation observed in R2
as deduced by the chemical characterization of reactors ma-
terials. The high concentrations of VFAs, alcohols and other
intermediatemetabolites (amines, amino acids, phenols) in R2
(Schievano et al., 2012) probably exerted inhibiting effects on
many microorganisms, including methanogens, decreasing
the community diversity and its potential of adaptation. On
the contrary, in R3 was maintained a more diverse and dy-
namic community that probably has a richest network of
metabolic pathways explaining the most efficient degrading
activity observed in this digester. In particular, in R3 were
found microorganisms related to the Porphyromonadaceae
family and Anaerobaculum genus. These bacteria, capable of
fermenting peptides and amino acids, were possibly respon-
sible for the low levels of nitrogenous compounds detected in
R3 and found instead undegraded in R2. Bacteroidetes are more
efficient than Firmicutes in degrading plant polyphenols and
less sensitive to phenols (Rastmanesh, 2011 and references
therein). It is speculated that a phenol/polyphenols rich
feeding promoted the Bacteroidetes growth in R3, but left these
compounds not degraded in R2.
The archaeal community in two methanogenic reactors
was dominated, though at different levels, by the Meth-
anosarcinales (average value of 70% and 58% of total Archaea in
R2 and R3, respectively), suggesting that acetoclastic meth-
anogenesis was the major pathway of methane production in
both systems. In R2, Methanosarcinales were up to 90% of
methanogens andwere represented at the steady state only by
the genus Methanosarcina. Methanosarcina spp., prevailing at
high acetate concentration (Jetten et al., 1992), were previously
detected as dominant in other thermophilic methanogenic
reactors from two-stage processes (Chu et al., 2010; Luo et al.,
2011) and in general from digesters treating manure (Demirel
and Scherer, 2008). Hence, their abundance in R2 is sustained
by the high levels of acetate (after hexanoic acid) detected in
gas and liquidphasesof R1 (Schievanoet al., 2012). Particularly,
the identified Methanosarcina-like species were related to M.
mazei andM. siciliaewhich are able to utilize various substrates
(methanol, methylamines and also H2/CO2 in the case of M.
siciliae) other than acetate (Liu et al., 2009; Lee et al., 2010a).
In R3, though the high level of Methanosarcinales also pre-
sent, the archaeal community was more diverse and dynamic
as compared to R2. Methanosarcina, Methanosaeta and Meth-
anothermobacter specieswere simultaneously detected, though
at different density over the course of the operation. The
contribution of hydrogenotrophic methanogenesis in R3 was
highest than in R2 as confirmed by the detection in the latter
of thermophilic acetate-oxidizing bacteria (Thermacetogenium
and Tepidanaerobacter) capable of form methane in coopera-
tion with hydrogenotrophic methanogens (Hattori, 2008).
Such an archaeal community may have been advantageous to
the process performance, promoting an improved adaptation
potential.
Data of quantitative determinations of AD functional
groups indicated that their abundance remained rather con-
stant at the steady state despite some variations in biogas
production during the period.
In the two methanogenic reactors the abundance of dif-
ferent microbial groups were at the same order of magnitude,
except for higher methanogens in R2, probably enriched by
wat e r r e s e a r c h 4 7 ( 2 0 1 3 ) 1 9 8 3e1 9 9 5 1993
the separation of acidogenic and methanogenic phases. In R1
the high abundance of acetogens suggested that theywere the
major competitors of HPB. Acetogens are capable to catalyse
the reductive synthesis of acetate from CO2 switching be-
tween heterotrophic and autotrophic metabolism depending
on substrate availability (Drake et al., 2002). Their contribution
to hydrogen consumption in bioreactors depends on several
chemical and physical factors (acetate concentrations,
hydrogen partial pressure, mass transfer phenomena be-
tween H2-producers and H2-consumers) and the history of the
inocula. The abundance of acetogens in R1 reactor ranged
from 1.4 � 108 to 9.3 � 108 FTHFS (formyltetrahydrofolate
synthetase) genes per gram dry weight, in accordance with Xu
et al. (2009) who reported 108-109 FTHFS gene copies per gram
dry weight in a sludge under H2/CO2 enrichment conditions.
Thus, it is likely that acetogens, even at low percentages
(Kraemer and Bagley, 2008), may have somehow contributed
to hydrogen consumption in R1, suggesting that heat-
treatment is not sufficient to control spore-forming H2-con-
sumers. In addition, it was observed that, after some days of
operation, acetogens prevailed over methanogens. This is in
agreement with previous findings indicating that generally
methanogenesis prevails over acetogenesis due to its more
favourable thermodynamics and affinity for H2 (Liu and
Whitman, 2008). However, acetogenesis can effectively out-
competemethanogenesis in certain conditions, like under low
pH and accumulation of H2 (Drake et al., 2002). The methane
detected in the acidogenic reactor, presumably generated by
Metanogenium species, was in biogas in low percentage and for
a limited operational time, confirming the efficacy of low pH
condition to inhibit methanogenesis.
Quantitative data allowed also to explain some failures in
biogas production of the two-stage process occurred after the
steady state, like the hydrogen production drop occurred from
days 48e50 accompanied by an almost one order magnitude
decrease of HPB.
Partial accumulation of VFAs, particularly acetate and
propionate (370 and 325 mg/L, respectively, at day 59) may
explain the one order magnitude decrease of methanogens
and the acetotrophic methanogen proportion (50%). This VFA
accumulation may also account for the appearance in the
methanogen population ofMethanothermobacter, less sensitive
than acetoclastic methanogens to increases in VFAs concen-
tration (Hori et al., 2006). All these microbiological evidences
support the non-optimal condition in general occurring in R2.
Overall, the higher diversity and dynamic of prokaryote
community, especially the fermentative bacterial one, in the
single stage process as compared to the two-stage process,
may account for the best degradation efficiency observed in
R3. The difference in bacterial community and performance
between the two AD processes is likely a consequence of
decoupling of acidogenesis from methanogenesis in the two
stage stystem and of the different configurations and opera-
tional parameters of the two systems. In the two-stage pro-
cess, the separation of fermentative and methanogenic
environments might have affected negatively syntrophic as-
sociations among microorganisms and probably reduced the
number of degradation pathways. Particularly, the enriched
simplified community established in R2 proved to be unable to
completely degrade many intermediate metabolites causing
inhibition effects determining a methane production lower
than the expected one. Further research is needed to evaluate
the possibility of optimization of two-stage process ensuring
a stable and efficient microbial community.
5. Conclusions
The study showed that qualitative and quantitative data on
microbial community provided valuable information on the
functionality of the AD processes. In particular, the data
allowed to: i) correlate the structure of microbial communities
to the functionality of the processes accounting for the partial
inefficiency of R2 and highest performance of R3; ii) inves-
tigate the relations (and their fluctuations) among the differ-
ent trophicmicrobial groups, and with the functionality of the
AD processes iii) evidence the key role of operational param-
eters and of reactors configuration in driving the dominant
microbial communities. Microbiological investigation pro-
vided a useful tool to get a better insight into the factors
determining the performance of the two processes.
Acknowledgements
This study was funded by the project “Produzione di bio-
idrogeno ed energia rinnovabile da residui agro-zootecnici e
AgrIdEn” by Regione Lombardia. Partial support comes from
the project “Miniaturizzazione e semplificazione di linee di
trasformazione per piccole produzioni agroalimentari e
impiego di energie rinnovabili e MIERI” by Ministero per le
Politiche Agricole Alimentari e Forestali.
Appendix A. Supplementary data
Supplementary data related to this article can be found at
http://dx.doi.org/10.1016/j.watres.2013.01.007.
r e f e r e n c e s
Angenent, L.T., Karim, K., Al-Dahhan, M.H., Wrenn, B.A.,Domıguez-Espinosa, R., 2004. Production of bioenergy andbiochemicals from industrial and agricultural wastewater.Trends in Biotechnology 22, 477e485.
Boone, D.R., Liu, Y., Zhao, Z.J., Balkwill, D.L., Drake, G.R.,Stevens, T.O., Aldrich, H.C., 1995. Bacillus infernus sp. nov., anFe (III)- and Mn (1V)-reducing anaerobe from the deepterrestrial subsurface. International Journal of Systematic andEvolutionary Bacteriology 45, 441e448.
Carballa, M., Smits, M., Etchebehere, C., Boon, N., Verstraete, W.,2011. Correlations between molecular and operationalparameters in continuous lab-scale anaerobic reactors.Applied Microbiology and Biotechnology 89, 303e314.
Chu, C.-F., Ebie, Y., Xu, K.-Q., Li, Y.-Y., Inamori, Y., 2010.Characterization of microbial community in the two-stageprocess for hydrogen and methane production from foodwaste. International Journal of Hydrogen Energy 35,8253e8261.
wat e r r e s e a r c h 4 7 ( 2 0 1 3 ) 1 9 8 3e1 9 9 51994
Demirel, B., Scherer, P., 2008. The roles of acetotrophic andhydrogenotrophic methanogens during anaerobic conversionof biomass to methane: a review. Reviews in EnvironmentalScience and Biotechnology 7, 173e190.
Demirel, B., Scherer, P., Yenigun, O., Onay, T.T., 2010. Productionof methane and hydrogen from biomass through conventionaland high-rate anaerobic digestion processes. Critical Reviewsin Environmental Science and Technology 40, 116e146.
Drake, H.L., Kusel, K., Matthies, C., 2002. Ecological consequencesof the phylogenetic and physiological diversities of acetogens.Antonie van Leeuwenhoek 81, 203e213.
Einen, J., Thorseth, I.H., Øvreas, L., 2008. Enumeration ofArchaea andBacteria in seafloor basalt using real-time quantitative PCR andfluorescencemicroscopy.FEMSMicrobiologyLetters282,182e187.
Eriksen, N.T., Riis, M.L., Holm, N.K., Iversen, N., 2010. H2 synthesisfrom pentoses and biomass in Thermotoga spp. BiotechnologyLetters 33, 293e300.
Favia, G., Ricci, I., Damiani, C., Raddadi, N., Crotti, E.,Marzorati, M., Rizzi, A., Urso, R., Brusetti, L., Borin, S., Mora, D.,Scuppa, P., Pasqualini, L., Clementi, E., Genchi, M., Corona, S.,Negri, I., Grandi, G., Alma, A., Kramer, L., Esposito, F., Bandi, C.,Sacchi, L., Daffonchio, D., 2007. Bacteria of the genus Asaiastably associate with Anopheles stephensi, an Asian malarialmosquito vector. PNAS 104, 9047e9051.
Goberna, M., Insam, H., Franke-Whittle, I.H., 2009. Effect ofbiowaste sludge maturation on the diversity of thermophilicbacteria and archaea in an anaerobic reactor. AppliedEnvironmental Microbiology 75, 2566e2572.
Guo, X.M., Trably, E., Latrille, E., Carrere, H., Steyer, J.-P., 2010.Hydrogen production from agricultural waste by darkfermentation: a review. International Journal of HydrogenEnergy 35, 10660e10673.
Hattori, S., 2008. Syntrophic acetate-oxidizing microbes inmethanogenic environments. Microbes and Environments 23,118e127.
Hattori, S., Kamagata, Y., Hanada, S., Shoun, H., 2000.Thermacetogenium phaeum gen. nov., sp. nov., a strictlyanaerobic, thermophilic, syntrophic acetate-oxidizingbacterium. International Journal of Systematic andEvolutionary Microbiology 50, 1601e1609.
Hori, T., Haruta, S., Ueno, Y., Ishii, M., Igarashi, Y., 2006. Dynamictransition of a methanogenic population in response to theconcentration of volatile fatty acids in a thermophilicanaerobic digester. Applied and Environmental Microbiology72, 1623e1630.
Hwang, K., Shin, S.G., Kim, J., Hwang, S., 2008. Methanogenicprofiles by denaturing gradient gel electrophoresis usingorder-specific primers in anaerobic sludge digestion. Appliedand Environmental Microbiology 80, 269e276.
Jeon, B.S., Kim, B.C., Um, Y., Sang, B.I., 2010. Production ofhexanoic acid from D-galactitol by a newly isolated Clostridiumsp. BS-1. Applied Microbiology Biotechnology 88, 1161e1167.
Jetten, M.S.M., Stams, A.J.M., Zehnder, A.J.B., 1992.Methanogenesis from acetate: a comparison of acetatemethabolism in Methanothrix soehngenii and Methanosarcinaspp. FEMS Microbiology Letters 88, 181e198.
Jo, J.H., Jeon, C.O., Lee, D.S., Park, J.M., 2007. Process stability andmicrobial community structure in anaerobic hydrogen-producing microflora from food waste containing kimchi.Journal of Biotechnology 131, 300e308.
Kondo, R., Nedwell, D.B., Purdy, K.J., de Queiroz Silva, S., 2004.Detection and enumeration of sulphate-reducing bacteria inestuarine sediments. Geomicrobiology Journal 21, 145e157.
Kraemer, J.T., Bagley, D.M., 2008. Measurement of H2 consumptionand its role in continuous fermentative hydrogen production.Water Science and Technology 57, 681e685.
Lee, C., Kim, J., Shin, S.G., Hwang, S., 2008. Monitoring bacterialand archaeal community shifts in a mesophilic anaerobic
batch reactor treating a high-strength organic wastewater.FEMS Microbiology Ecology 65, 544e554.
Lee, C., Kim, J., Shin, S.G., O’Flaherty, V., Hwang, S., 2010a.Quantitative and qualitative transitions of methanogencommunity structure during the batch anaerobic digestion ofcheese-processing wastewater. Applied Microbiology andBiotechnology 87, 1963e1973.
Lee, Z.M.-P., Bussema III, C., Schmidt, T.M., 2009. rrnDB:documenting the number of rRNA and tRNA genes in bacteriaand archaea. Nucleic Acids Research 37, D489eD493. http://rrndb.mmg.msu.edu/search.php.
Lee, Z.-K., Li, S.-L., Kuo, P.-C., Chen, I.-C., Tien, Y.-M., Huang, Y.-J.,Chuang, C.-P., Wong, S.-C., Cheng, S.-S., 2010b. Thermophilicbio-energy process study on hydrogen fermentation withvegetable kitchen waste. International Journal of HydrogenEnergy 35, 13458e13466.
Liu, F.H., Wang, S.B., Zhang, J.S., Zhang, J., Yan, X., Zhou, H.K.,Zhao, G.P., Zhou, Z.H., 2009. The structure of the bacterial andarchaeal community in a biogas digester as revealed bydenaturinggradient gel electrophoresis and16S rDNAsequencinganalysis. Journal of Applied Microbiology 106, 952e966.
Liu, Y., Whitman, W.B., 2008. Metabolic, phylogenetic, andecological diversity of the methanogenic archaea. Annals ofthe New York Academy of Sciences 1125, 171e189.
Luo, G., Karakashev, D., Xie, L., Zhou, Q., Angelidaki, I., 2011. Long-term of inoculums pretreatment on fermentative hydrogenproduction by repeated batch cultivations: homoacetogenesisand methanogenesis as competitors to hydrogen production.Biotechnology and Bioengineering 108, 1816e1827.
Luo, G., Xie, L., Zhou, Q., Angelidaki, I., 2011b. Enhancement ofbioenergy production from organic wastes by two-stageanaerobic hydrogen and methane production process.Bioresource Technology 102, 8700e8706.
Marzorati, M., Wittebolle, L., Boon, N., Daffonchio, D.,Verstraete, W., 2008. How to get more out of molecularfingerprints: practical tools for microbial ecology.Environmental Microbiology 10, 1571e1581.
Menes, R.J., Muxı, L., 2002. Anaerobaculum mobile sp. nov., a novelanaerobic, moderately thermophilic, peptide-fermentingbacterium that uses crotonate as an electron acceptor, andemended description of the genus Anaerobaculum.International Journal of Systematic and EvolutionaryMicrobiology 52, 157e164.
Merlino, G., Rizzi, A., Villa, F., Sorlini, C., Brambilla, M.,Navarotto, P., Bertazzoni, B., Zagni, M., Araldi, F.,Daffonchio, D., 2012. Shifts of microbial community structureduring anaerobic digestion of agro-industrial energetic cropsand food industry byproducts. Journal of ChemicalTechnology and Biotechnology 9, 1302e1311.
Rastmamesh, R., 2011. High Polyphenol, Low Prebiotico Diet forWeight Loss Because of Intestinal Microbiota Interaction, 189,pp. 1e8.
Sasaki, D., Hori, T., Haruta, S., Ueno, Y., Ishii, M., Igarashi, Y.,2011. Methanogenic pathway and community structure ina thermophilic anaerobic digestion process of organic solidwaste. Journal of Bioscience and Bioengineering 111, 41e46.
Sass, A.M., Sass, H., Coolen, M.J., Cypionka, H., Overmann, J., 2001.Microbial communities in the chemocline of a hypersalinedeep-sea basin (Urania basin, Mediterranean Sea). Appliedand Environmental Microbiology 67, 5392e5402.
Schievano, A., Tenca, A., Scaglia, B., Merlino, G., Rizzi, A.,Daffonchio, D., Oberti, R., Adani, F., 2012. Two-stage vs. single-stage anaerobic digestion: comparison of energy productionand biodegradation efficiencies. Environmental Science andTechnology 46, 8502e8510.
Schill, N.A., Liu, J.-S., von Stockar, U., 1999. Thermodynamicanalysis of growth of Ethanobacterium thermoautotrophicum.Biotechnology and Bioengineering 64, 74e81.
wat e r r e s e a r c h 4 7 ( 2 0 1 3 ) 1 9 8 3e1 9 9 5 1995
Sekiguchi, Y., Imachi, H., Susilorukmi, A., Muramatsu, M.,Ohashi, A., Harada, H., Hanada, S., Kamagata, Y., 2006.Tepidanaerobacter syntrophicus gen. nov., sp. nov., an anaerobic,moderately thermophilic, syntrophic alcohol- and lactate-degrading bacterium isolated from thermophilic digestedsludges. International Journal of Systematic and EvolutionaryMicrobiology 56, 1621e1629.
Shiratori, H., Ikeno, H., Ayame, S., Kataoka, N., Miya, A.,Hosono, K., Beppu, T., Ueda, K., 2006. Isolation andcharacterization of a new Clostridium sp. that performseffective cellulosic waste digestion in a thermophilicmethanogenic bioreactor. Applied and EnvironmentalMicrobiology 72, 3702e3709.
Tamura, K., Peterson, D., Peterson, N., Stecher, G., Nei, M.,Kumar, S., 2011. MEGA5: molecular evolutionary geneticsanalysis using maximum likelihood, evolutionary distance,and maximum parsimony methods. Molecular Biology andEvolution 28, 2731e2739.
Tang, Y.-Q., Ji, P., Hayashi, J., Koike, Y., Wu, X.-L., Kida, K., 2011.Characteristic microbial community of a dry thermophilicmethanogenic digester: its long-term stability and changewith feeding. Applied Microbiology and Biotechnology 91,1447e1461.
Ueno, Y., Haruta, S., Ishii, M., Igarashi, Y., 2001. Characterizationof a microorganism isolated from the effluent of hydrogen
fermentation by microflora. Journal of Bioscience andBioengineering 92, 397e400.
Valdez-Vazquez, I., Poggi-Varaldo, H.M., 2009. Hydrogenproduction by fermentative consortia. Renewable andSustainable Energy Reviews 13, 1000e1013.
Wang, Y.H., 2008. Process study and hydrolysis mechanism studyof thermophilic hydrogen production with starch-richedkitchen waste fermentation. Phd thesis.
Xing, D., Ren, N., Rittmann, B., 2008. Genetic diversity ofhydrogen-producing bacteria in an acidophilic ethanol-H2-coproducing system, analyzed using the [Fe]-hydrogenasegene. Applied and Environmental Microbiology 74, 1232e1239.
Xu, K., Liu, H., Du, G., Chen, J., 2009. Real-time PCR assaystargeting formyltetrahydrofolate synthetase gene toenumerate acetogens in natural and engineeredenvironments. Anaerobe 15, 204e213.
Yu, Y., Lee, C., Kim, J., Hwang, S., 2005. Group-specific primer andprobe sets to detect methanogenic communities usingquantitative real-time Polymerase Chain Reaction.Biotechnology and Bioengineering 89, 670e679.
Ziganshin, A.M., Schmidt, T., Scholwin, F., Il’inskaya, O.N.,Harms, H., Kleinsteuber, S., 2011. Bacteria and archaeainvolved in anaerobic digestion of distillers grains withsolubles. Applied Microbiology and Biotechnology 89,2039e2052.