microbial community structure in a biogas digester utilizing the marine energy crop saccharina...
TRANSCRIPT
ORIGINAL ARTICLE
Microbial community structure in a biogas digester utilizingthe marine energy crop Saccharina latissima
Phillip B. Pope • Vivekanand Vivekanand •
Vincent G. H. Eijsink • Svein J. Horn
Received: 26 September 2012 / Accepted: 5 October 2012 / Published online: 25 October 2012
� The Author(s) 2012. This article is published with open access at Springerlink.com
Abstract Seaweed is a highly attractive marine crop for
the production of biofuels, due to its rapid growth rate as
well as high polysaccharide and low lignin content. One
appealing exploitation route is the production of biogas by
anaerobic digestion. Interestingly, despite the composi-
tional differences between seaweed and lignocellulosic
biomass, available data indicate that conditions and inocula
traditionally used for the latter may work well for seaweed.
To gain more insight into the underlying microbial pro-
cesses, we have generated 16S rRNA gene amplicon py-
rosequencing data to comparatively describe microbial
communities in biogas digesters containing either the sea-
weed Saccharina latissima or wheat straw. The seaweed
digesters gave better biogas yield and a higher relative
abundance of core group Methanosaeta-affiliated Archaea.
Conversely, variation in biomass had only minor abun-
dance effects towards dominant bacterial lineages and
influenced only low-abundant bacterial OTUs. Affiliations
between dominant archaeal and bacterial phylotypes
described here and previously identified anaerobic diges-
tion core groups indicate that trends are beginning to
emerge within these newly explored microbial ecosystems,
the understanding of which is currently impeded by limited
published datasets.
Keywords Biogas � Anaerobic digestion � Seaweed �Macroalgae � Methane
Biogas production, particularly in the purified form of bi-
omethane, is seen as a vital component of renewable
energy technologies due to the wide variety of organic
sources that can be used and the compatibility of methane
with existing energy infrastructure. Efforts to augment the
biogas processes have focused on utilizing waste materials
as well as alternative biomass substrates that lessen the
impact on arable land. To that end, seaweed species have
been identified as high potential substrates for biomethane
production, due to their rapid growth rate as well as high
polysaccharide (*60 %) and low lignin content (Horn
2009). Compared to organic waste streams and terrestrial
biomasses, relative little is known on the anaerobic
digestion (AD) of marine substrates. Available data for
seaweed are, however, quite promising, in particular for the
brown seaweed Saccharina latissima (Nielsen and Heiske
2011; Vivekanand et al. 2012). Seaweed is less recalcitrant
than lignocellulosic materials meaning that thermal pre-
treatments that are often used to speed up biogas processes
can be milder, thus reducing the risk of inhibitor formation
that is common during the harsher pretreatments (Viveka-
nand et al. 2012).
In this study, we report compositional and comparative
analysis of the microbial communities in anaerobic
digesters. 16S rRNA gene amplification for both bacterial
and archaeal domains was performed to ensure that rep-
resentatives for all the key metabolic stages of AD were
enveloped, that is, polymer hydrolysis, sugar fermentation,
acetogenesis (all Bacteria) and methanogenesis (Archaea).
Samples were collected from three 1.1 L batch digesters
run in triplicate for 119 days at 37 �C (stable pH 7.3 over
the course of the experiment). All three digesters were
inoculated with 600 mL of pre-incubated waste water
sludge containing 10.5 g L-1 of volatile solids (VS)
(Vivekanand et al. 2012), and were defined according to
P. B. Pope (&) � V. Vivekanand � V. G. H. Eijsink � S. J. Horn
Department of Chemistry, Biotechnology and Food Science,
Norwegian University of Life Sciences,
Post Office Box 5003, 1432 As, Norway
e-mail: [email protected]
123
3 Biotech (2013) 3:407–414
DOI 10.1007/s13205-012-0097-x
the new substrate added (1.05 g VS added at day 0 and 67,
2.1 g VS total): inoculum containing no additional organic
substrate (IC), inoculum with seaweed (S. latissima,
IC ? SW) and inoculum with steam exploded wheat straw
(Triticum aestivum, IC ? WS). The total liquid volume in
all digesters was then adjusted to 700 mL by adding dis-
tilled water. Total methane production in IC ? SW
(223 ± 61 mL g-1 VS) was approximately twice as high
as in IC ? WS (98 ± 44 mL g-1 VS); note that SW and
WS materials have different C/N ratios of 8.8 and 98.4,
respectively (Vivekanand et al. 2012). For each digester,
sub-samples from each triplicate (equal volume) were
pooled, and DNA extraction was performed as described
by Rosewarne et al. (2010). Rrs genes were amplified using
the broadly conserved primer sets 27F-515R [Bacteria:
(Pope et al. 2012)] and 340F-1000R [Archaea: (Gantner
et al. 2011)], both containing the 454 Life Sciences primer
A sequence and a unique 8-nt multiplex identifier (Hamady
et al. 2008). Rrs gene sequences were quality filtered using
the QIIME software package (Caporaso et al. 2010), whilst
error correction and chimera removal were performed
using OTUPIPE which incorporates UCHIME (Edgar et al.
2011). Operational taxonomic units (OTUs) were clustered
at 97 % sequence identity using UCLUST software (Edgar
2010) and taxonomy was assigned using the Ribosomal
Database Project classifier (Cole et al. 2003). After filtering
and normalization (datasets randomly ‘‘subsampled’’ to
remove sample heterogeneity), 1,992 bacterial and 651
archaeal 16S rRNA sequences (in total) clustered into 63
and 14 OTUs, respectively (Table 1; Acc. Numbers
JX279942–JX280018). Rarefaction analysis showed that
the three digester datasets afforded a similar degree of
adequate coverage of bacterial biodiversity within each
digester (Fig. 1; Table 1). Moreover, Fig. 1 illustrated that
the addition of seaweed appears to reduce archaeal species
diversity.
Comparisons of the archaeal communities revealed that
OTUs ARC_nor-1, ARC_nor-2 and ARC_nor-3, affiliated
to the Taxonomic Order-ranks Methanosarcinales, Met-
hanomicrobiales and Methanobacteriales, respectively,
were dominant in all three samples (Fig. 2a–b). However,
their composition varied considerably depending on the
digester substrate (Fig. 2b–c). The increased dominance of
ARC_nor-1 in the IC ? SW digester coincided with higher
methane production [Fig. 2; (Vivekanand et al. 2012)], as
well as a slightly higher methane content in the biogas
(57 % vs. 53 % in IC ? WS). Affiliation of ARC_nor-1 to
an acetoclastic methanogen (Methanosaeta concilii; 98 %
ID) was also in agreement with Methanosaeta dominance
in AD communities that utilize freshwater algae substrates
(Ellis et al. 2012). In contrast, hydrogenotrophic metha-
nogens, of which ARC_nor-2 is putatively categorized,
were most dominant in the inoculum digester (IC), and
their relative abundance decreased in digesters containing
either IC ? WS or IC ? SW (Fig. 2b). Interestingly, both
ARC_nor-1 and ARC_nor-3 were affiliated (99 % ID;
Table 1) to previously described and repeatedly detected
core group phylotypes (OTU-VI and OTU-V, respec-
tively), which dominate sludge AD communities (Riviere
et al. 2009).
Spirochaetes, Bacteroidetes and Chloroflexi were the
dominant bacterial phyla in all three samples (Fig. 3a).
Dominance of these phyla, with the exception of the Spi-
rochaetes, is commonly observed in biogas processes
(Nelson et al. 2011), whilst the low relative abundance of
Proteobacteria- and Firmicutes-affiliated OTUs is in con-
trast with previous studies that have demonstrated their
abundance in AD reactors (Kampmann et al. 2012; Nelson
et al. 2011). The majority of the bacterial OTUs were
distantly related to cultured relatives, whereas close simi-
larities were observed with previous biogas microbial
community studies describing uncultured phylotypes
(Table 1). In particular, both BAC_nor-3 and BAC_nor-4
exhibited 99 % sequence identity to dominant Chloroflexi-
affiliated OTUs that have been previously defined as highly
prevalent core phylotypes involved in AD of sludge [Core
group a-III and a-VI; (Riviere et al. 2009)]. The repeated
detection of Chloroflexi-affiliated phylotypes in high
abundance within biogas processes points towards a sig-
nificant role and reveals a need for future investigations.
Several OTUs of lower abundance demonstrated marked
shifts depending on which substrate was present (Fig. 3b–
c). BAC_nor-13, a Petrobacter-affiliated betaproteobacte-
ria decreased approximately seven-fold in IC ? SW
digesters, whereas, the Bacteroidales-affiliated BAC_nor-
12 and Victivallis-affiliated BAC_nor-26 experienced an
eight-fold and nine-fold increase, respectively. The phe-
notype of BAC_nor-26 may be potentially interesting, as
Victivallis sp. isolates have previously been described as
capable of fermenting a variety of sugars including glucose
and mannitol [found in brown seaweed; (Horn and Ostg-
aard 2001)] subsequently producing acetate, H2 and etha-
nol as end-products (Zoetendal et al. 2003).
The present study shows that the microbial consortia
involved in AD of seaweed comprise deeply branched
OTUs. However, there are indications that trends in AD
microbial profiles are beginning to emerge with the
detection of several previously identified core group ar-
chaeal and bacterial phylotypes (Table 1; Riviere et al.
2009). Compared to the IC ? WS digester, the IC ? SW
digester showed some conspicuous differences, the most
prominent being an increase in methane production and the
relative abundance of the Methanosaeta concilii-affiliated
(presumably acetoclastic) ARC_nor-1. Given that metha-
nogens are believed to rely on syntrophic relationships with
bacteria for key metabolites (i.e., acetate, H2/CO2),
408 3 Biotech (2013) 3:407–414
123
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3 Biotech (2013) 3:407–414 409
123
Ta
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1co
nti
nu
ed
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IC?
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SW
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nse
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ph
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(AY
36
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04
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p_
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p_
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s(A
Y7
35
09
7)
85
WW
S(J
Q1
59
99
5)
98
BA
C-2
60
09
p_
Len
tisp
ha
era
e;f_
Vic
tiva
lla
cea
eV
icti
vall
isva
den
sis
str.
AT
CC
BA
A-5
48
(NR
_0
27
56
5)
94
MF
Cp
alm
oil
mil
lef
flu
ent
(JF
30
91
89
)
99
BA
C-2
72
12
p_
Sp
iro
cha
etes
Sp
iro
cha
eta
xyla
no
lyti
cus
(AY
73
50
97
)8
5W
WS
(JQ
15
89
80
)9
8
BA
C-2
81
34
p_
Fir
mic
ute
s;c_
Clo
stri
dia
Ca
lora
ma
tor
sp.
str.
8(E
U6
21
40
6)
84
Fo
od
-pro
cess
ing
was
tes
(GU
38
98
08
)9
8
BA
C-2
91
24
p_
Sp
iro
cha
etes
;f_
Sp
iro
cha
eta
cea
eS
pir
och
aet
azu
elze
rae
(M8
87
25
)9
2W
WS
(JQ
11
13
24
)9
9
BA
C-3
02
04
p_
OP
8G
eob
aci
llu
sth
erm
od
enit
rifi
can
sst
r.B
GS
C9
4A
1
(AY
60
89
60
)
79
WW
S(G
Q4
80
15
4)
99
BA
C-3
13
10
p_
WS
1S
trep
tom
yces
sca
bri
spo
rus
(EU
84
17
00
)7
8W
WS
(CU
91
77
40
)9
9
BA
C-3
23
13
k_
Ba
cter
iaM
oo
rell
ath
erm
oa
ceti
cast
r.D
SM
74
17
(FJ8
88
65
4)
82
WW
S(J
Q0
96
45
8)
98
BA
C-3
31
30
p_
Ch
loro
flex
i;f_
An
aer
oli
na
cea
eT
her
mo
des
ulf
ob
ium
na
rug
ens
(AB
07
78
17
)8
0W
WS
(CU
92
73
49
)9
9
BA
C-3
40
31
p_
Ba
cter
oid
etes
;o
_B
act
ero
ida
les
Per
sici
virg
asp
.st
r.P
HS
CD
-1(H
M8
54
01
7)
80
WW
S(J
Q1
27
39
6)
99
BA
C-3
53
11
p_
Sp
iro
cha
etes
;f_
Sp
iro
cha
eta
cea
eS
pir
och
aet
axy
lan
oly
ticu
s(A
Y7
35
09
7)
85
WW
S(J
Q0
91
69
7)
99
BA
C-3
61
23
p_
Syn
erg
iste
tes;
f_S
yner
gis
tace
ae
Syn
erg
iste
ssp
.st
r.R
MA
16
08
8(D
Q4
12
71
8)
89
BR
(EF
58
35
00
)9
9
BA
C-3
71
02
p_
Pro
teo
ba
cter
ia;
f_S
yntr
op
ha
cea
eS
mit
hel
lap
rop
ion
ica
str.
LY
P(A
F1
26
28
2)
89
WW
S(J
Q0
99
71
3)
99
BA
C-3
82
20
p_
Pro
teo
ba
cter
ia;
f_S
yntr
op
ho
rha
bd
ace
ae
Myx
oco
ccu
sfu
lvu
sst
r.0
19
8-1
(EU
26
30
01
)8
0P
etro
leu
mre
serv
oir
(JN
62
79
45
)9
9
BA
C-3
91
22
p_
WS
1S
trep
taci
dip
hil
us
sp.
str.
Aac
-20
(AB
18
07
66
)7
9W
WS
(JQ
14
12
19
)9
9
BA
C-4
03
40
p_
Fir
mic
ute
s;c_
Clo
stri
dia
Ca
lora
ma
tor
sp.
str.
8(E
U6
21
40
6)
86
WW
S(C
U9
21
65
7)
99
BA
C-4
10
42
p_
SA
R4
06
Des
ulf
uro
mo
na
sa
cete
xig
ens
(U2
31
40
)8
0W
WS
(CU
92
29
95
)9
9
BA
C-4
21
02
p_
Sp
iro
cha
etes
;f_
Sp
iro
cha
eta
cea
eS
pir
och
aet
axy
lan
oly
ticu
s(A
Y7
35
09
7)
85
WW
S(J
Q1
58
98
0)
99
BA
C-4
32
01
p_
Pro
teo
ba
cter
ia;
f_C
om
am
on
ad
ace
ae
Aci
do
vora
xst
r.R
-25
07
5(A
M0
84
10
9)
98
Fre
shw
ater
spri
ng
(AB
42
50
64
)9
9
BA
C-4
40
41
p_
Ch
loro
flex
i;f_
An
aer
oli
na
cea
eC
lost
rid
ium
pro
teo
lyti
cum
str.
DS
M3
09
0
(X7
34
48
)
75
WW
S(C
U9
21
61
4)
99
410 3 Biotech (2013) 3:407–414
123
Ta
ble
1co
nti
nu
ed
IDIC
IC?
WS
IC?
SW
Co
nse
nsu
sL
inea
gea
Cu
lt_
rep
(Acc
.n
um
ber
)ID
(%)
Clo
ne_
rep
_en
v(A
cc.
nu
mb
er)
ID(%
)
BA
C-4
52
12
p_
Ch
loro
flex
i;f_
An
aer
oli
na
cea
eC
lost
rid
ium
bo
tuli
nu
mst
r.A
TC
C1
93
97
(CP
00
07
26
)
77
An
aero
bic
swin
ela
go
on
(AY
95
32
35
)9
7
BA
C-4
60
41
p_
Ch
loro
flex
i;f_
An
aer
oli
na
cea
eC
lost
rid
ium
dif
fici
lest
r.6
30
(NC
_0
09
08
9)
74
WW
S(J
Q1
37
63
3)
99
BA
C-4
70
05
p_
Sp
iro
cha
etes
;f_
Sp
iro
cha
eta
cea
eS
pir
och
aet
ast
eno
stre
pta
str.
JCM
16
53
4
(AB
54
19
84
)
89
WW
S(J
Q3
46
77
3)
99
BA
C-4
81
20
p_
Sp
iro
cha
etes
;f_
Sp
iro
cha
eta
cea
eT
rep
on
ema
pri
mit
iast
r.Z
AS
-1(A
F0
93
25
1)
89
WW
S(J
Q3
46
77
3)
99
BA
C-4
90
04
p_
Pro
teo
ba
cter
ia;
f_D
esu
lfo
vib
rio
na
cea
e
Des
ulf
ovi
bri
ost
r.D
s3(E
U3
26
02
9)
99
BR
-car
rot
was
te(J
F5
33
85
0)
99
BA
C-5
05
00
p_
Sp
iro
cha
etes
;f_
Sp
iro
cha
eta
cea
eS
pir
och
aet
axy
lan
oly
ticu
s(A
Y7
35
09
7)
85
WW
S(J
Q1
58
98
0)
99
BA
C-5
14
00
k_
Ba
cter
iaS
pir
och
aet
axy
lan
oly
ticu
s(A
Y7
35
09
7)
86
Oil
-co
nt.
soil
(HQ
68
92
00
)9
5
BA
C-5
22
10
p_
Ba
cter
oid
etes
;o
_B
act
ero
ida
les
Ca
pn
ocy
top
ha
ga
can
imo
rsu
sst
r.C
IP1
03
93
6
(AY
64
30
75
)
88
BR
-ref
use
(GQ
45
36
34
)9
4
BA
C-5
30
21
k_
Ba
cter
iaB
aci
llu
ssp
.st
r.JS
4(A
Y3
72
92
4)
83
WW
S(J
Q1
44
54
6)
10
0
BA
C-5
40
41
p_
Ch
loro
flex
i;f_
An
aer
oli
na
cea
eT
her
mo
des
ulf
ob
ium
na
rug
ense
DS
M1
47
96
(NR
_0
24
78
9)
77
WW
S(C
U9
18
06
0)
99
BA
C-5
52
00
p_
Act
ino
ba
cter
ia;
o_
Co
rio
Ba
cter
iale
sS
trep
tom
yces
sp.
str.
Z6
1(E
F0
12
13
1)
85
Nat
ura
lg
asen
rich
men
t(E
U0
37
97
1)
99
BA
C-5
60
12
p_
Arm
ati
mo
na
det
esS
ymb
iob
act
eriu
mth
erm
op
hil
um
str.
IAM
14
86
3
(NC
_0
06
17
7)
76
Mic
rob
ial
mat
(FJ2
07
11
2)
84
BA
C-5
71
00
p_
Pro
teo
ba
cter
ia;
f_S
yntr
op
ho
ba
cter
ace
ae
Syn
tro
ph
ob
act
ersu
lfa
tere
du
cen
sst
r.T
B8
10
6
(AY
65
17
87
)
99
WW
S(C
U9
23
99
2)
99
BA
C-5
81
02
p_
WS
1T
her
mo
act
ino
myc
essa
cch
ari
str.
KC
TC
97
90
(AF
13
87
37
)
81
BR
-bre
wer
yw
aste
(EF
51
56
25
)9
9
BA
C-5
92
10
p_
Ba
cter
oid
etes
;o
_B
act
ero
ida
les
Per
sici
virg
asp
.st
r.P
HS
CD
-1(H
M8
54
01
7)
79
Was
tesi
lkre
fin
ing
syst
em
(HQ
45
33
34
)
98
BA
C-6
00
12
k_
Ba
cter
iaA
list
ipes
pu
tred
inis
str.
AT
CC
29
80
0
(NR
_0
25
90
9)
76
WW
S(J
Q0
93
37
7)
95
BA
C-6
12
01
p_
Pro
teo
ba
cter
ia;
c_B
etaP
rote
ob
act
eria
Azo
nex
us
sp.
str.
HM
E6
65
4(H
M5
90
82
8)
99
WW
S(J
Q4
13
51
5)
99
BA
C-6
22
00
p_
Pro
teo
ba
cter
ia;
f_R
ho
do
cycl
acea
eR
ho
do
cycl
us
sp.
str.
HO
D5
(AY
69
14
23
)9
6W
WS
(JQ
17
72
98
)9
8
BA
C-6
30
30
p_
Pro
teo
ba
cter
ia;
f_C
om
amo
nad
acea
eA
cid
ovo
rax
sp.
str.
GP
TS
A1
00
-27
(DQ
85
49
67
)9
4A
ctiv
ated
slu
dg
e(E
U1
04
26
7)
97
aH
iera
rch
ical
tax
on
om
icas
sig
nm
ent
for
each
OT
Uca
lcu
late
du
sin
gth
eR
DP
naı
ve
Bay
esia
nC
lass
ifier
(Co
leet
al.
20
03
).D
eep
est
lin
eag
eas
sig
nm
ents
(kk
ing
do
m,
pp
hy
lum
,c
clas
s,o
ord
er,
ffa
mil
y)
are
dis
pla
yed
on
lyw
her
eO
TU
sco
uld
be
assi
gn
edw
ith
an8
0%
bo
ots
trap
con
fid
ence
esti
mat
eb
Ind
icat
esaf
fili
atio
nto
hig
hly
pre
val
ent
core
ph
ylo
typ
esin
vo
lved
inA
Do
fsl
ud
ge
that
wer
ep
rev
iou
sly
des
crib
edin
(Riv
iere
etal
.2
00
9)
BR
bio
gas
reac
tor,
WW
Sw
aste
wat
ersl
ud
ge,
MF
Cm
icro
bia
lfu
elce
ll
3 Biotech (2013) 3:407–414 411
123
IC IC+WS: 98 ± 44mL g-1 VS* IC+SW: 223 ± 61mL g-1 VS*
Crenarchaeota; C2; GrfC26 Euryarchaeota; Methanobacteria; Methanobacteriales Euryarchaeota; Methanomicrobia; MethanomicrobialesEuryarchaeota; Methanomicrobia; Methanosarcinales
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
80.0
1 2 3 4 5 6 7 8 9 10 11 12 13 14
IC
IC+WS
IC+SW
-6
-4
-2
0
2
4
6
1 2 3 4 5 6 7 8 9 10 11 12 13 14
~98%: Methanosaeta conccilii GP6 Core-group OTU-VI (Methanosarcinales)
~96%: Methanosphaerula palustris str. E1-9c (Methanomicrobiales)
~85%: Methanobacterium alcaliphilum Core-group OTU-V (Methanobacteriales)
A
B C
Rel
ativ
e ab
unda
nce
(%)
97% OTUs 97% OTUs
OT
U a
bund
ance
shi
ft (f
old
x)
Fig. 2 Relative abundance and comparison profiles of archaeal 16S
rRNA OTUs identified in anaerobic digesters containing either waste
water sludge with no additional organic substrate (inoculum, IC), IC
plus wheat straw (IC ? WS), or IC plus seaweed (IC ? SW). a,
b The relative abundance of archaeal lineages at a phylum-level and
OTU-level, respectively. OTU abundance shifts between WS and SW
digesters c were measured as either fold-change increases (?) or
decreases (-) against IC measurements. Colour coding in b and c are
as follows: blue indicates IC, red indicates IC ? WS and green
indicates IC ? SW. Lineage information for selected OTUs and OTU
affiliation to previously described, highly prevalent core phylotypes
(Riviere et al. 2009) is provided. OTUs numbers in the x-axis
correspond to ARC_nor-terminology referred to in the text. Total
methane yields are included in a for IC ? WS and IC ? SW,
which are provided in the original publication on methane produc-
tion (Vivekanand et al. 2012) and normalized for production in IC.
VS* volatile solids
A B
Fig. 1 Rarefaction analyses using operational taxonomic unit (OTU)
frequency of archaeal (a) and bacterial (b) rrs gene datasets obtained
from the biogas digesters containing waste water sludge as inoculum
(IC blue), IC plus wheat straw (IC ? WS red) or IC plus seaweed
(IC ? SW green). A 97 % sequence identity threshold has been
employed for the OTU constructions used in these analyses
412 3 Biotech (2013) 3:407–414
123
ARC_nor-1 dominance is conceivably linked to bacterial
population shifts and/or changes in bacterial metabolism.
Surprisingly, dominant bacterial populations showed little
variation between the digesters with larger shifts only
observed for several low-abundant OTUs. Regardless, the
large phylogenetic variation between biogas-producing
communities and cultured representatives makes drawing
definitive functional or interactive conclusions, a signifi-
cant challenge. The functioning of biogas-producing
microbial communities on the whole is insufficiently
explored and requires further in depth structure–function
analysis involving a combination of cultivation directed
strategies and ‘‘meta-omic’’ approaches (i.e., metagenom-
ics, metatranscriptomics).
Acknowledgments This work was supported by The Research
Council of Norway’s RENERGI program (Grant numbers 190877)
and a Marie Curie International Incoming Fellowship from the
European Commission (awarded to PBP; PIIF-GA-2010-274303).
Conflict of interest The authors declare that they have no conflict
of interest.
Open Access This article is distributed under the terms of the
Creative Commons Attribution License which permits any use, dis-
tribution, and reproduction in any medium, provided the original
author(s) and the source are credited.
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A
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