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Metagenome approaches revealed a biological prospect for improvement on mesophilic cellulose degradation

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Abstract

Improvement on the bioconversion of cellulosic biomass depends much on the expanded knowledge on the underlying microbial structure and the relevant genetic information. In this study, metagenomic analysis was applied to characterize an enriched mesophilic cellulose-converting consortium, to explore its cellulose-hydrolyzing genes, and to discern genes involved in methanogenesis. Cellulose conversion efficiency of the mesophilic consortium enriched in this study was around 70 %. Apart from methane, acetate was the major fermentation product in the liquid phase, while propionate and butyrate were also detected at relatively high concentrations. With the intention to uncover the biological factors that might shape the varying cellulose conversion efficiency at different temperatures, results of this mesophilic consortium were then compared with that of a previously reported thermophilic cellulose-converting consortium. It was found that the mesophilic consortium harbored a larger pool of putative carbohydrate-active genes, with 813 of them in 54 GH modules and 607 genes in 13 CBM modules. Methanobacteriaceae and Methanosaetaceae were the two methanogen families identified, with a preponderance of the hydrogenotrophic Methanobacteriaceae. In contrast to its relatively high diversity and high abundance of carbohydrate-active genes, the abundance of genes involved in the methane metabolism was comparatively lower in the mesophilic consortium. A biological enhancement on the methanogenic process might serve as an effective option for the improvement of the cellulose bioconversion at mesophilic temperature.
ENVIRONMENTAL BIOTECHNOLOGY
Metagenome approaches revealed a biological prospect
for improvement on mesophilic cellulose degradation
Yubo Wang
1
&Yu Xia
1
&Feng Ju
1
&Tong Zhang
1
Received: 6 June 2015 /Revised: 11 August 2015 /Accepted: 18 August 2015
#Springer-Verlag Berlin Heidelberg 2015
Abstract Improvement on the bioconversion of cellulosic
biomass depends much on the expanded knowledge on the
underlying microbial structure and the relevant genetic infor-
mation. In this study, metagenomic analysis was applied to
characterize an enriched mesophilic cellulose-converting con-
sortium, to explore its cellulose-hydrolyzing genes, and to dis-
cern genes involved in methanogenesis. Cellulose conversion
efficiency of the mesophilic consortium enriched in this study
was around 70 %. Apart from methane, acetate was the major
fermentation product in the liquid phase, while propionate and
butyrate were also detected at relatively high concentrations.
With the intention to uncover the biological factors that might
shape the varying cellulose conversion efficiency at different
temperatures, results of this mesophilic consortium were then
compared with that of a previously reported thermophilic
cellulose-converting consortium. It was found that the
mesophilic consortium harbored a larger pool of putative
carbohydrate-active genes, with 813 of them in 54 GH modules
and 607 genes in 13 CBM modules. Methanobacteriaceae and
Methanosaetaceae were the two methanogen families identi-
fied, with a preponderance of the hydrogenotrophic
Methanobacteriaceae. In contrast to its relatively high diversity
and high abundance of carbohydrate-active genes, the abun-
dance of genes involved in the methane metabolism was com-
paratively lower in the mesophilic consortium. A biological
enhancement on the methanogenic process might serve as an
effective option for the improvement of the cellulose biocon-
version at mesophilic temperature.
Keywords Mesophilic .Cellulose degradation .
Metagenomics .Methanogenesis
Introduction
Cellulosic biomass is considered to be a potential renewable
energy source as it contains photosynthetic energy that can be
released through thermochemical or biological processes
(McKendry 2002a). Recycling of agricultural cellulosic resid-
uals provides huge quantity of resources for energy generation
and is also of great environmental benefit since it has less extra
CO
2
emission (McKendry 2002b). Although lots of research
works have been carried out on the bioconversion processes,
the recalcitrant nature of cellulose and its low conversion ef-
ficiency still stand in the way of efficient bio-recycling.
Cellulose-degrading microorganisms which could produce a
battery of cellulose-hydrolyzing enzymes are common in the
natural and in some artificial systems, e.g., termiteshindgut
(Warnecke et al. 2007), soil (Donnelly et al. 1990), wastewater
treatment plants (Xia et al. 2013a), and cow rumen (Hess et al.
2011). Many researchers have tried to investigate on these
microbial communities for a better understanding on the bio-
logical foundations of the cellulose bioconversion processes
(Jaenicke et al. 2011; Krause et al. 2008). With the introduc-
tion of metagenomic approach, Hess etc. observed an expand-
ed catalog of genes and genomes that were active in cellulose
hydrolysis (Hess et al. 2011). Xia et al identified the domi-
nance of Clostridium and Methanothermobacter in a thermo-
philic batch reactor fed with cellulose (Xia et al. 2013a). Such
Electronic supplementary material The online version of this article
(doi:10.1007/s00253-015-6945-y) contains supplementary material,
which is available to authorized users.
*Tong Zhang
zhangt@hkucc.hku.hk
1
Environmental Biotechnology Lab, The University of Hong Kong
SAR, Pokfulam Road, Hong Kong, China
Appl Microbiol Biotechnol
DOI 10.1007/s00253-015-6945-y
bio-information is important for possible control and optimi-
zation efforts towards an improved cellulose bioconversion.
So far, most of the studies on the bioconversion of cellu-
losic biomass have been carried out either at a thermophilic or
at a mesophilic temperature. Although the energy input for the
mesophilic operation will be much more economically prom-
ising, the thermophilic process has the merits of higher cellu-
lose conversion efficiency (Xia et al. 2013b). One of the major
objectives of this study is to figure out the underlying micro-
bial attributes for the varying performance of cellulose bio-
conversionat the two temperatures, and to discern the possible
biological opportunities for improvement on the cellulose
degradation at mesophilic temperature. To begin with, a
cellulose-converting consortium was enriched at mesophilic
temperature and metagenomic approach was applied to inves-
tigate its microbial community. Such investigation on the
mesophilic cellulose-converting consortium was further ex-
tended through comparison with the previously reported ther-
mophilic consortium enriched in similar procedures (Xia et al.
2012; Xia et al. 2013a). The comparison was carried out on
aspects as follows: firstly, the performance of cellulose degra-
dation at different temperatures; secondly, shift in the overall
microbial populations; thirdly, genetic potential of carbohy-
drate hydrolysis in terms of the diversity and abundance of
carbohydrate-active genes (CAGs) identified; and lastly, the
genetic potential of methanogen metabolism.
Materials and methods
Enrichment of mesophilic cellulose-converting consortium
Anaerobic digestion sludge sampled from Shek Wu Hui
wastewater treatment plant was utilized as seed inoculum in
this experiment. Cellulose was added to impose the substrate
selection pressure on the microbes resident in the reactor; glu-
cose and yeast extract were utilized as co-substrates to help
improve the reactor stability (Xia et al. 2012). Table S1 sum-
marized concentrations of substrate and co-substrates applied
throughout the enrichment process. The enrichment of the
mesophilic cellulose-converting consortium was carried out
in a sequencing batch mode: sludge harvested from the previ-
ous batch by centrifugation at 4000 rpm for 10 min was uti-
lized to seed the next batch.
Sequencing batch reactor (SBR) with a working volume of
800 ml was operated at 35± 5 °C and pH of 67.2 (pH 201,
MSITECH, Singapore). Argon was purged into the reactor to
provide the initial anaerobic environment. The chemical com-
ponents of the solution medium per liter were as follows:
KH
2
PO
4
0.5 g, KH
2
PO
4
0.5 g, CaCl
2
0.05 g, MgSO
4
0.024 g, NH
4
Cl 0.5 g, and 1 ml trace element solution (Xia
et al. 2012). Biogas generated from cellulose degradation was
collected in a Tedlar bag, and its volume was measured
regularly. The fermentation slurry was also sampled on a reg-
ular basis, and its supernatant through a 0.45-μmfilterwas
utilized to detect the concentrations of ammonium ion, total
organic carbon (TOC), volatile fatty acids (VFAs), and alco-
hols. The detection methods for these chemicals and calcula-
tion of cellulose conversion ratio were the same as previously
reported for the thermophilic cellulose-converting consortium
(Xia et al. 2012).
Metagenomic dataset of the mesophilic consortium
After 32 batches of enrichment, DNAwas extracted from 2 ml
of the mesophilic fermentation slurry using FastDNA SPIN
Kit for Soil (MP Biomedicals, LLC, Illkirch, France).
Concentration of the extracted DNA was 203 ng/μl, with
260/280=1.87 and 260/230 = 0.32 (Nanodrop, ND-1000).
DNA libraries of 180 bp were prepared following the man-
ufacturers instruction (Illumina). Raw data of the Illumina
sequencing has been deposited in the NCBI dataset with an
accession number of SAMN03766781. The 35 million 100 bp
paired-end reads generated were firstly de-duplicated accord-
ing to the principle utilized by the MG-RAST platform: reads
sharing the same first 50 bps were recognized as replicated
and only one of them was pickedout to represent all the others
(Meyer et al. 2008). The clear read pairs with an overlap
length of at least 10 bps were then merged to get longer se-
quences (called metagenomic tags here) for more accurate
taxa annotation. The tags obtained here had an average length
of 166 bps as summarized in Table S2.
For the interpretation of the overall microbial struc-
ture, Silva SSU (version 111) rRNA database was uti-
lized to identify the 16S rRNA genes from these tags
through NCBIs BLASTN (Altschul et al. 1990)atan
E-value cutoff of 1E20. The top 50 hits were then
imported to MEGAN (V4.70.4) for taxonomy annotation
through the lowest common ancestor (LCA) algorithm.
Parameters for taxa annotation were set as default ex-
cept that the percent identity filter was activated for
sequencesalignment at different ranks: species 99 %,
genus 97 %, family 95 %, order 90 %, class 85 %, and
phylum 80 % (Huson et al. 2007).
Investigation on CAGs and genes involved in the methane
metabolism were interpreted based on functional genes in
terms of open reading frames (ORFs) predicted from contigs.
The raw reads generated from high-throughput sequencing
were firstly imported into the CLC Genomic Workbench (ver-
sion 4.9), and contigs were assembled from these raw reads
through CLCs de novo assembly algorithm with default set-
ting (Lee and Rittmann 2009). ORFs were then derived from
contigs longer than 1000 bp through MetaGeneMark (Zhu
et al. 2010). Statistics of the assembly were summarized in
Tab le S3.
Appl Microbiol Biotechnol
Exploration of the carbohydrate-active genes
As is known, CAGs are of pronounced significance in cellulose
hydrolysis. Traditionally, exploration of the cellulolytic enzymes
followed the procedures of isolation, purification, and character-
ization of their activities (Li et al. 2003). These fundamental
research works have contributed profoundly to our knowledge
on a wide spectrum of cellulolytic enzymes. Taking
carbohydrate-active enzymes (CAZy) database as an example,
it is a collection of genomic, structural, and catalytic information
on CAGs that have verified activities (Cantarel et al. 2009).
Nowadays, with the introduction of high-throughput sequencing,
the availability of the fundamental information on enzymes, and
the development of protein similarity search tools such as
BLAST (Altschul et al. 1990), RAPSearch (Ye et al. 2011),
HMM Scan (Eddy 2011) etc., intensive exploration of the genetic
information on candidate enzymes based on huge amount of
DNA sequences has become feasible and has demonstrated its
power in the exploration of novel cellulolytic enzymes in cow
guts (Hess et al. 2011), in the thermophilic cellulose-converting
consortium (Xia et al. 2013a), and soil (Bhat et al. 2013). In this
study, following the method described in these previous studies,
ORFs were first annotated via the HMM scan against the Pfam-
A database (Eddy 2011), and putatively carbohydrate-active
genes were further identified based on the corresponding infor-
mation between the Pfam number and the CAZy modules.
Investigation on genes involved in the methane
metabolism
Methanogenesis, accompanied with hydrolysis, acidogenesis, and
acetogenesis, completes the cellulose degradation process. Due to
the well-acknowledged recalcitrant nature of cellulose, most of the
previous research work applying metagenomic has naturally fo-
cused on the exploration of cellulose-hydrolyzing genes and en-
zymes (Hess et al. 2011;Wongetal.2013); yet, not much atten-
tion has been paid to the comparison-orientated investigation on
the genetic potential of the methane metabolism evolved during
the cellulose degradation process. Considering such limitation, in
this study, information on genes involved in the methane metab-
olism were also derived from the metagenomic dataset, through
searching against a self-extracted KEGG sub-database specialized
in methane metabolism through the sub-database annotation pipe-
line (SAP) approach (Yu and Zhang 2013).
Results
Performance of cellulose degradation in the enriched
mesophilic consortium
The currently reported cellulose bioconversion efficiency was
in a range of 4090 % (Cheng and Liu 2012; Nissila et al.
2011;Gengetal.2010; Forrest et al. 2011). In this study, after
200 daysenrichment, the cellulose conversion capacity of the
mesophilic consortium (Figure S1) was enhanced significant-
ly from 12 to 70 %, and this conversion ratio was slightly
lower than that of 85 % at the thermophilic temperature in
our previous study (Xia et al. 2012). Methane and carbon
dioxide accounted for 60 and 40 %, respectively, in the
biogas. As summarized in Table S4, acetate was the major
fermentation product, the same as that in the thermophilic
fermentation (Xia et al. 2012), while concentrations of propi-
onate (70 mg/l) and butyrate (40 mg/l) were higher than those
reported in the thermophilic fermentation (propionate 36 mg/
l and butyrate 3 mg/l) (Xia et al. 2012).
Microbial structure of the mesophilic consortium
Based on the assumption that only those microbial popula-
tions active in the mesophilic cellulose degradation process
were likely to be enriched in this specific experiment, it is
reasonable to propose that, comparing with the seed sludge,
microbial populations enriched in this experiment were those
that were active in the mesophilic cellulose bioconversion;
besides, the shift in the overall microbial structures between
this mesophilic consortium and the formerly reported thermo-
philic consortium might also shed light on the essential micro-
bial information for the varying performance of cellulose deg-
radation at the two temperatures.
Results of the comparative taxa information indicated that,
at the kingdom level, an increment in the relative abundance
of the Archaea populations was observed from 5 % in the seed
sludge to 9 and 11 % in the enriched mesophilic and thermo-
philic consortium, respectively. Figure 1summarizes the shift
in major phyla among the seed sludge and the two cellulose-
converting consortia. Chloroflexi,Euryarchaeota,and
Firmicutes were the three major phyla in the mesophilic con-
sortium, the same as that in the thermophilic enrichment. Not
surprisingly, temperature also acted as a selection pressure on
the enrichment of some specific taxa, for example,
Verrucomicrobia was one of the phyla that got enriched only
in the mesophilic consortium and disappeared under the ther-
mophilic condition; while Thermotogae, which was washed
out dramatically in the mesophilic consortium, got enriched in
the thermophilic consortium.
Figure 2was the weight Venn diagram of the shared and
distinct classes (a) and families (b) among the seed sludge, the
mesophilic consortium, and the thermophilic consortium.
More detailed and quantitative information on these classes
and families was summarized in Table S5 and Table S6,re-
spectively. Based on the previous assumption that the enriched
taxa might be those that were active in the cellulose biocon-
version process and also based on some literature review, the
proposed functional roles of the enriched families are summa-
rized in Fig. 3.Clostridiaceae and Ruminococcaceae were the
Appl Microbiol Biotechnol
two cellulose-hydrolyzing families (Nissila et al. 2011;Wu
and He 2013) enriched in both the mesophilic and the thermo-
philic consortia, while Opitutaceae and Spirochaetaceae were
the cellulose hydrolysers (Rodrigues and Isanapong 2014;
Karami et al. 2014) specifically enriched in the mesophilic
consortium and the thermophilic consortium, respectively. In
consistent with the higher propionate concentration detected
in the mesophilic cellulose conversion process, enrichment of
Propionibacteriaceae, the taxa capable in propionate genera-
tion from lactate (Falentin et al. 2010), was observed in the
mesophilic consortium. Besides, the enrichment of
Syntrophobacteraceae and Syntrophaceae, the two possible
syntrophs that would oxidize propionate to acetate/H
2
and
CO
2
, the two substrates which could be further utilized for
methane generation or sulfate reduction (Plugge et al. 2011)
was also detected only in the mesophilic consortium.
Methanobacteriaceae and Methanosaetaceae were the
two methanogen families identified in both the thermo-
philic and mesophilic cellulose-converting consortium.
Methanobacteriaceae, which was not observed in the
seed sludge, was the predominant methanogen family, occu-
pying 9.5 % of the 16S rRNA genes annotated at the family
level in the thermophilic consortium and 3.5 % in the
mesophilic consortium. Similarly, the enrichment in
Methanosaetaceae was also noted, taking 2 % (mesophilic)
and 5 % (thermophilic), respectively. Comparatively,
Euryarchaeota
Bacteroidetes
Spirochaetes
Thermotogae
Nitrospirae
Synergistetes
Acidobacteria
Chlorobi
Verrucomicrobia
Caldiserica
Lentisphaerae
Proteobacteria
Actinobacteria
P
lanctomycetes
Chloroflexi
Mesophilic
00%
10%
1000
20%
2000
30%
40%
3000
50%
4000
60%
5000
70%
80%
6000
90%
7000
100%
Thermophilic
00%
10%
1000
20%
2000
30%
40%
3000
50%
4000
60%
70%
5000
80%
6000
90%
7000
100%
Seed
00%
10%
1000
30%
2000
40%
50%
3000
60%
4000
70%
80%
5000
90%
100%
Firmicutes
20%
Fig. 1 Shift of the major phyla enriched in the seed sludge (the present
study), the mesophilic cellulose-converting consortium (the present
study), and the thermophilic consortium (Xia et al. 2013a). Each phylum
was represented by a specific color of the ribbon, and the width of each
ribbon would denote the abundance of each phylum in the consortium.
Numbers in percentage showed the proportions of the different phyla in
each of the consortia; and the inner numbers specified the count of 16S
rRNA gene tags assigned to each phylum
Appl Microbiol Biotechnol
Methanosarcinaceae, the principle methanogen in the seed
sludge (2.1 %), decreased significantly in the thermophilic
enrichment (0.9 %) and was even not detected in the
mesophilic enrichment. Despite such consistency in the diver-
sity of methanogen families identified, the relative abundance
of methanogen families annotated in the mesophilic consor-
tium (5.5 %) was only around one third of that annotated in the
thermophilic consortium (14.5 %).
KEGG annotation of the methanogenesis pathways
Besides the above investigation on the microbial populations,
identification on the genetic potential of the methane metabo-
lism was conducted based on the functional genes (ORFs),
and the results were compared with that of the thermophilic
consortium (Xia et al. 2013a), as summarized in Fig. 4:acetate
and formate/(CO
2
and H
2
) were the two direct carbon sources
for methanogens and they could be converted to methane
through a series of biochemical reactions, namely the
acetoclastic methanogenesis and the hydrogenotrophic
methanogenesis. The synthesis of coenzyme M and coenzyme
B, which respectively are the terminal methyl carrier and the
hydrogen carrier for methane generation (Scheller et al. 2013),
was also included in the methanogenic pathways as summa-
rized. Enzymes involved in each of the bioconversion proce-
dures were represented by an enzyme commission number
(EC number), and the abundance of functional genes annotat-
ed to each of the EC numbers was differentiated in different
Total number of classes annotated :
Seed sludge: 19
Mesophilic consortium: 17
Thermophilic consortium: 13
Mesophilic
Seed
Thermophilic
2
6
2
13
1
1
6
Mesophilic
Thermophilic
Seed
1
2
6
0
3
10
Total number of families annotat ed:
Seed sludge: 21
Mesophilic consortium: 15
Thermophilic consortium: 11
2
a: Shared and distinct classes among the three consortia b: Shared and distinct families among the three consortia
Fig. 2 Weighed Venn diagrams of the distinct and shared classes (a)and
families (b) among the seed sludge (the present study, circle in pink), the
mesophilic consortium (the present study, circle in purple), and the
thermophilic consortium (Xia et al. 2013a,circle in green). The
junction area is proportional to the number of shared classes/families
Cellulose Glucose Pyruvate
Propionate
Acetate
H
2
,CO
2
CH
4
,CO
2
Methanosaetaceae
Methanobacteriaceae
Propionibacteriaceae
Ruminococcaceae;
Clostridiaceae
Acidogenesis
s
HCOOH
Opitutaceae
Syntrophaceae
Syntrophoba
cteriaceae
Fig. 3 The proposed functional
roles of families enriched in the
cellulose-converting consortia
Appl Microbiol Biotechnol
colors. Judging from Fig. 4, in the mesophilic consortium, the
relative abundance of genes assigned to each of the EC num-
bers involved in the methane metabolism was much less than
that in the thermophilic consortium, consistent with results of
the above taxa annotation that one third less methanogen pop-
ulations (Methanobacteriaceae and Methanosaetaceae)were
annotated in the mesophilic consortium.
With further intention to assess the significance of the two
methanogen families in the methane metabolism, ORFs
assigned to each of the EC numbers involved in the methan-
ogenic procedures were extracted and were then annotated
through the MEGAN software to determine their taxa affilia-
tion. Reads were mapped to the ORFs to correct the quantita-
tive taxa annotation results (Xia et al. 2013a). As is shown in
Fig. 5, 74 % of the reads involved in the acetoclastic methan-
ogenic procedures (section a) were affiliated to
Methanosaetaceae. While for the methane production from
formate, 71 % of the reads assigned to the EC number of
1.12.98.1, which is involved in the regeneration of the key
coenzyme F420H
2
, were from Methanobacteriaceae.When
it comes to the synthesis of coenzyme M and coenzyme B, it
was found that Methanobacteriaceae harbored significantly
more diverse genes that were essential for the synthesis of
the both coenzymes, and this might in a certain extent explain
the preponderance of the hydrogenotrophic
Methanobacteriaceae over the acetoclastic
Methanosaetaceae.
Exploration of carbohydrate-active genes
Cellulose hydrolysis involved a large diversity of enzymes
which harbored the catalytic modules (GH modules) or the
noncatalytic carbohydrate-binding modules (CBMs) or the
both. CBMs are recognized for their targeting and proximity
capabilities to the hydrophobic surface of cellulose, and GH
modules are active in the hydrolysis of glycoside bonds
(Cantarel et al. 2009). Synergistic actions of the different types
of cellulolytic enzymes, such as the exoglucanase,
endoglucanase, and the cellobiase, and also GH modules
and the CBM modules, etc., were adapted for efficient hydro-
lysis of cellulose to glucose. In this study, genetic potential of
the carbohydrate hydrolysis in the mesophilic cellulose deg-
radation was investigated and compared with that in the ther-
mophilic consortium.
The abundance of CBM modules and the GH modules
annotated in the mesophilic enrichment are summarized in
Formate
CO
2
H2
H+
Formyl -MFR
N5 - Formyl -THMPT
5,10 -Methenyl-
THMPT
5,10 -Methylene -THMPT 5-Methyl-THMPT
Coenzyme F420H2
Methyl-CoM Methane
CoM-S-S-CoB
Acetate
Acetyl phosphate
Acetyl-CoA
Coenzyme M
Sulfoacetaldehyde
3 - Sulfophyruvate
(2R)- 3-Sulfolactate
(2R)-Phosphosulfolactate
Phosphoenolpyruvate
Methanol
5- 10 ppm
20- 40 ppm
50- 70 ppm
90- 100 ppm
100- 200 ppm
200- 300 ppm
300- 400 ppm
400- 500 ppm
500- 600 ppm
1000- 1300 ppm
1
2
1: mesophilic
2: thermophilic
1.2.99.5
0ppm
3.5.4.27
21
2.1.1.86
Meta A,B,C
1.8.98.1
2.8.4.1
CO
1.2.1.2
1.12.1.2
1.12.7.2
2.3.1.101
1.12.98.2
1.5.98.1
1.12.98.1
1.5.98.2
CODHACS
2.3.1.8
2.7.2.1
4.4.1.19 3.1.3.71
1.1.1.272
4.1.1.79
1.2.7.4
1.2.99.2
1700-1800 ppm
Coenzyme B
Coenzyme F420
6.2.1.1
Fig. 4 Comparative genetic potential of the diverse procedures in the
methane metabolism under mesophilic condition (the present study) and
thermophilic condition (Xia et al. 2013a). Note: Enzymes involved in
each of the conversion procedures were represented by an Enzyme
Commission number (EC number as inserted), and the abundance of
genes assigned to each of the EC number was differentiated by different
colors. The top or left half (1) refers to the gene abundance assigned to
each EC number in the mesophilic consortium; while the bottom or right
half (2) refers to the gene abundance in the thermophilic consortium.
Appl Microbiol Biotechnol
Tab le S7 and Table S8. In the mesophilic cellulose-converting
consortium, the relative abundance of CAGs in all the protein
coding genes was about twice as much as that in the thermo-
philic consortium. Figure 6summarizes the diversity and rel-
ative abundance of all the CAZy modules identified in the
mesophilic cellulose-converting consortia. Comparing with
the 30 GH modules and the 5 CBM modules reported in the
thermophilic consortium, the mesophilic consortium harbored
a relatively higher diversity of putative carbohydrate-active
genes in 54 GH modules and 13 CBM modules. Most of the
major GH modules harbored in the thermophilic enrichment,
such as GH2, GH3, GH9, and GH38, were also identified in
comparable percentages in the mesophilic enrichment; yet, the
GH5, GH29, and GH78 modules, respectively, taking 12.2,
9.2, and 9.0 % of the GH modules annotated in the mesophilic
consortium, were absent in the thermophilic consortium.
GH5, GH9, and GH48 were the major GH modules that had
activities as glucanase; while GH1, GH2, GH3, GH29, and
GH38 were the main glucosidase which could hydrolyze the
cellulase product into individual monosaccharides. The ten-
dency of higher abundance of carbohydrate-active genes in
the mesophilic consortium was also reported before
(Hollister et al. 2012), and this might suggest that comparing
with the thermophilic consortium, the genetic potential for
cellulose hydrolysis in the mesophilic consortium was more
elevated.
Discussion
Comparing with the previously reported thermophilic cellulose
conversion efficiency of 85 % (Xia et al. 2012), cellulose
0
1000
2000
3000
4000
5000
6000
7000
8000
9000
Reads number
EC number
Methanosaetaceae
Methanobacteriaceae
abc
Fig. 5 Contribution of
Methanobacteriaceae and
Methanosaetaceae to the two
paralleled methanogenesis
pathways. aConversion of format
to 5, 10-Methylene-THMPT; b
Conversion of acetate to 5-
Methyl-THMPT; cSynthesis of
coenzyme M and coenzyme B
0%
2%
4%
6%
8%
10%
12%
14%
16% Glucanase Endohemicellulases Cellobiase Debranching
enzymes
0%
20%
40%
60%
CBM2
CBM3
CBM4,9…
CBM5,12
CBM6
CBM10
CBM11
CBM13
CBM17,28
CBM19
CBM20
CBM21
CBM25
CBM27
CBM32
CBM33
CBM34
CBM40
CBM48
CBM49
CBM50
CBM51
Fig. 6 Comparison of the GH
modules and the CBM modules
identified in the mesophilic
consortium. The lateral index is
the GH modules (upper)
corresponding with different
activities in cellulose hydrolysis
and the CBM modules (bottom);
the vertical index shows the
relative abundance of each GH or
CBM modules
Appl Microbiol Biotechnol
conversion efficiency of the mesophilic consortium enriched in
this study was slightly lower at 70 %. Higher concentrations of
propionate and butyrate were detected in the mesophilic fermen-
tation slurry. The phenomenon of higher electron flux to more
reduced intermediates in the mesophilic fermentation was also
observed in Hollisters study (Hollister et al. 2012). It has been
reported that a higher electron flux to propionate generally ac-
companied with lower efficiency of anaerobic digestion (Amani
et al. 2011), partially due to the reason that syntrophic propionate
oxidizers are generally rare in the seed sludge and they have an
even slower growing rate than the methanogens. In view of
results observed in this study, it was proposed that the possible
microbial roots that induced the higher generation of propionate
and butyrate would somewhat relate to the lower cellulose bio-
conversion efficiency at mesophilic temperature.
Based on the taxa annotation from the metagenomic anal-
ysis, Propionibacteriaceae, the taxa capable in propionate
generation from lactate, was noted being enriched only in
the mesophilic consortium, and the two possible propionate-
degrading syntrophs of Syntrophobacteraceae and
Syntrophaceae, although in low abundances at 0.6 and
0.8 %, respectively, were also observed only in the mesophilic
consortium. The mesophilic and the thermophilic cellulose-
converting consortium had some shared and distinct
cellulose-hydrolyzing populations. In the mesophilic consor-
tium, the genetic capacity for carbohydrate hydrolysis was
more elevated in terms of both higher diversity and higher
abundance of carbohydrate-active genes. So, comparing with
the thermophilic consortium, the biological potential for cellulose
hydrolysis may not be a constraint factor here in the mesophilic
consortium. Methanosaetaceae and Methanobacteriaceae were
the two major methanogen families annotated, with the
hydrogenotrophic Methanobacteriaceae being dominant in both;
yet, the total abundance of methanogen populations in the
mesophilic consortium was only around one third of that in the
thermophilic consortium. Further investigation on the genetic
potential of the methane metabolism showed that one third less
functional genes related to the methanogenesis was annotated in
the mesophilic metagenomic dataset. Considering that smoother
methanogenesis from acetate and formate will benefit with a
reduction on the portion of electron flowing to butyrate and
propionate, the weaker genetic potential for methane metabolism
might be an inducer for the higher generation of propionate and
butyrate in the mesophilic fermentation.
Based on the above analysis which investigated the under-
lying microbial attributes of the cellulose-converting consor-
tia, respectively, enriched at mesophilic and thermophilic tem-
perature, it could be suggested that in further biological at-
tempt to improve the cellulose degradation at mesophilic tem-
perature, bio-augmentation on the methanogenesis process
would be of higher significance than that on the cellulose
hydrolysis process, and an elevated biological potential of
methanogenesis may help to improve methane generation
from acetate and format, benefit in reducing the electron flow
to propionate and butyrate, and ultimately improve its overall
cellulose conversion efficiency.
Acknowledgments This work was supported by Guangdong-Hong
Kong Technology Cooperation Funding Scheme (GHP/015/11SZ) and
ShenZhen Knowledge Innovation ProgramBasic Research
Project from Shenzhen Municipal Science and Technology Innovation
Council (JCYJ20130401141412386). Feng Ju, Yu Xia, and Yubo Wang
are thankful to The University of Hong Kong for the postgraduate stu-
dentship. The authors would also like to thank Vicky Fung for her tech-
nical assistance.
Compliance with ethical standards Yubo Wang declares that she has
no conflict of interest; Yu Xia declares that she has no conflict of interest;
Feng Ju declares that he has no conflict of interest; Tong Zhang declares
that he has no conflict of interest. This article does not contain any studies
with human participants or animals performed by any of the authors.
References
Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ (1990) Basic local
alignment search tool. J Mol Biol 215:403410
Amani T, Nosrati M, Mousavi SM, Kermanshahi RK (2011) Study of
syntrophic anaerobic digestion of volatile fatty acids using enriched
cultures at mesophilic conditions. Int J Environ Sci Technol 8:83
96. doi:10.1007/BF03326198
Bhat A, Riyaz-Ul-Hassan S, Ahmad N, Srivastava N, Johri S (2013)
Isolation of cold-active, acidic endocellulase from Ladakh soil by
functional metagenomics. Extremophiles 17:229239. doi:10.1007/
s00792-012-0510-8
CantarelBL,CoutinhoPM,RancurelC,BernardT,LombardV,
Henrissat B (2009) The Carbohydrate-Active EnZymes database
(CAZy): an expert resource for Glycogenomics. Nucleic Acids
Res 37:233238. doi:10.1093/nar/gkn663
Cheng XY, Liu CZ (2012) Fungal pretreatment enhances hydrogen pro-
duction via thermophilic fermentation of cornstalk. Appl Energy 91:
16. doi:10.1016/j.apenergy.2011.09.014
Donnelly PK, Entry JA, Crawford DL, Cromack K (1990) Cellulose and
lignin degradation in forest soils: response to moisture, temperature,
and acidity. Microb Ecol 20:289295. doi:10.1007/BF02543884
Eddy SR (2011) Accelerated profile HMM searches. PLoS Comput Biol
7, e1002195. doi:10.1371/journal.pcbi.1002195
Falentin H, Deutsch SM, Jan G, Loux V, Thierry A, Parayre S, Maillard
MB, Dherbécourt J, Cousin FJ, Jardin J, Siguier P, Couloux A,
Barbe V, Vacherie B, Wincker P, Gibrat JF, Gaillardin C, Lortal S
(2010) The complete genome of Propionibacterium freudenreichii
CIRM-BIA1, a hardy actinobacterium with food and probiotic ap-
plications. PLoS One 5, e11748. doi:10.1371/journal.pone.0011748
Forrest AK, Wales ME, Holtzapple MT (2011) Thermodynamic predic-
tion of hydrogen production from mixed-acid fermentations.
Bioresour Technol 102:98239826. doi:10.1016/j.biortech.2011.
08.018
Geng A, He Y, Qian C, Yan X, Zhou Z (2010) Effect of key factors on
hydrogen production from cellulose in a co-culture of Clostridium
thermocellum and Clostridium thermopalmarium.Bioresour
Technol 101:40294033. doi:10.1016/j.biortech.2010.01.042
Hess M, Sczyrba A, Egan R, Kim TW, Chokhawala H, Schroth G, Luo S,
Clark DS, ChenF, Zhang T, Mackie RI, Pennacchio LA, Tringe SG,
Visel A, Woyke T, Wang Z, Rubin EM (2011) Metagenomic dis-
covery of biomass-degrading genes and genomes from cow rumen.
Science 331:463467. doi:10.1126/science.1200387
Appl Microbiol Biotechnol
Hollister EB, Forrest AK, Wilkinson HH, Ebbole DJ, Tringe SG, Malfatti
S, Holtzapple MT, Gentry TJ (2012) Mesophilic and thermophilic
conditions select for unique but highly parallel microbial communi-
ties to perform carboxylate platform biomass conversion. PLoS One
7, e39689. doi:10.1371/journal.pone.0039689
Huson DH, Auch AF, Qi J, Schuster SC (2007) MEGAN analysis of
metagenomic data. Genome Res 17:377386. doi:10.1101/gr.5969107
Jaenicke S, Ander C, Bekel T, Bisdorf R, Droge M, Gartemann KH,
Junemann S, Kaiser O, Krause L, Tille F, Zakrzewski M, Puhler
A, Schluter A, Goesmann A (2011) Comparative and joint analysis
of two metagenomic datasets from a biogas fermenter obtained by
454-pyrosequencing. PLoS One 6, e14519. doi:10.1371/journal.
pone.0014519
Karami A, Sarshar M, Ranjbar R, Zanjani RS (2014) The phylum
Spirochaetaceae. In: Rosenberg E, DeLong EF, Lory S,
Stackebrandt E, Thompson F (eds) The prokaryotesother major
lineages of Bacteria and the Archaea, 4th edn. Springer, Berlin
Heidelberg, pp 915929. doi:10.1007/978-3-642-38954-2_156
Krause L, Diaz NN, Edwards RA, Gartemann KH, Kromeke H,
Neuweger H, Puhler A, Runte KJ, Schluter A, Stoye J,
Szczepanowski R, Tauch A, Goesmann A (2008) Taxonomic com-
position and gene content of a methane-producing microbial com-
munity isolated from a biogas reactor. J Biotechnol 136:91101. doi:
10.1016/j.jbiotec.2008.06.003
Lee HS, Rittmann BE (2009) Evaluation of metabolism using stoichiom-
etry in fermentative biohydrogen. Biotechnol Bioeng 102:749758.
doi:10.1002/bit.22107
Li DC, Lu M, Li YL, Lu J (2003) Purification and characterization of an
endocellulase from the thermophilic fungus Chaetomium
thermophilum CT2. Enzym Microb Technol 33:932937. doi:10.
1016/S0141-0229(03)00245-X
McKendry P (2002a) Energy production from biomass (part 1): overview
of biomass. Bioresour Technol 83:3746. doi:10.1016/S0960-
8524(01)00118-3
McKendry P (2002b) Energy production from biomass (part 2): conver-
sion technologies. Bioresour Technol 83:4754. doi:10.1016/
S0960-8524(01)00119-5
Meyer F, Paarmann D, DSouza M, Olson R, Glass EM, Kubal M,
Paczian T, Rodriguez A, Stevens R, Wilke A, Wilkening J,
Edwards RA (2008) The metagenomics RAST servera public
resource for the automatic phylogenetic and functional analysis of
metagenomes. BMC Bioinformatics 9:386. doi:10.1186/1471-
2105-9-386
Nissila ME, Tahti HP, Rintala JA, Puhakka JA (2011) Effects of heat
treatment on hydrogen production potential and microbial commu-
nity of thermophilic compost enrichment cultures. Bioresour
Technol 102:45014506. doi:10.1016/j.biortech.2010.12.072
Plugge CM, Zhang W, Scholten JCM, Stams AJM (2011) Metabolic
flexibility of sulfate-reducing bacteria. Front Microbiol 2:81. doi:
10.3389/fmicb.2011.00081
Rodrigues JLM, Isanapong J (2014) The family Opitutaceae.In:
Rosenberg E, DeLong EF, Lory S, Stackebrandt E, Thompson F
(eds) The prokaryotesother major lineages of Bacteria and the
Archaea, 4th edn. Springer, Berlin Heidelberg, pp 751756. doi:
10.1007/978-3-642-38954-2_147
Scheller S, Goenrich M, Thauer RK, Jaun B (2013) Methyl-coenzyme M
reductase from methanogenic archaea: isotope effects on the forma-
tion and anaerobic oxidation of methane. J Am Chem Soc 135:
1497514984. doi:10.1021/ja406485z
Warnecke F, Luginbuhl P, Ivanova N, Ghassemian M, Richardson TH,
Stege JT, Cayouette M, McHardy AC, Djordjevic G, Aboushadi N,
Sorek R, Tringe SG, Podar M, Martin HG, Kunin V, Dalevi D,
Madejska J, Kirton E, Platt D, Szeto E, Salamov A, Barry K,
Mikhailova N, Kyrpides NC, Matson EG, Ottesen EA, Zhang X,
Hernandez M, Murillo C, Acosta LG, Rigoutsos I, Tamayo G, Green
BD, Chang C, Rubin EM, Mathur EJ, Robertson DE, Hugenholtz P,
Leadbetter JR (2007) Metagenomic and functional analysis of hind-
gut microbiota of a wood-feeding higher termite. Nature 450:560
565. doi:10.1038/nature06269
Wong MT, Zhang D, Li J, Hui RK, Tun HM, Brar MS, Park TJ, Chen Y,
Leung FC (2013) Towards a metagenomic understanding on en-
hanced biomethane production from waste activated sludge after
pH 10 pretreatment. Biotechnol Biofuels 6:38. doi:10.1186/1754-
6834-6-38
Wu YR, He J (2013) Characterization of anaerobic consortia coupled
lignin depolymerization with biomethane generation. Bioresour
Technol 139:512. doi:10.1016/j.biortech.2013.03.103
Xia Y, Cai L, Zhang T, Fang HHP (2012) Effects of substrate loading and
co-substrates on thermophilic anaerobic conversion of microcrystal-
line cellulose and microbial communities revealed using high-
throughput sequencing. Int J Hydrog Energy 37:1365213659.
doi:10.1016/j.ijhydene.2012.02.079
Xia Y, Ju F, Fang HH, Zhang T (2013a) Mining of novel thermo-stable
cellulolytic genes from a thermophilic cellulose-degrading consor-
tium by metagenomics. PLoS One 8, e53779. doi:10.1371/journal.
pone.0053779
Xia Y, Fang H, Zhang T (2013b) Recent studies on thermophilic anaer-
obic bioconversion of lignocellulosic biomass. RSC Adv 3:15528
15542. doi:10.1039/C3RA40866C
Ye Y, Choi JH, Tang H (2011) RAPSearch: a fast protein similarity search
tool for short reads. BMC Bioinformatics 12:159. doi:10.1186/
1471-2105-12-159
Yu K, Zhang T (2013) Construction of customized sub-databases from
NCBI-nr database for rapid annotation of huge metagenomic
datasets using a combined BLAST and MEGAN approach. PLoS
One 8, e59831. doi:10.1371/journal.pone.0059831
Zhu W, Lomsadze A, Borodovsky M (2010) Ab initio gene identification
in metagenomic sequences. Nucleic Acids Res 38, e132. doi:10.
1093/nar/gkq275
Appl Microbiol Biotechnol
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