Microbiology (2012), 158, 1808–1817
DOI 10.1099/mic.0.057984-0
Structures of free-living and protozoa-associated
methanogen communities in the bovine rumen differ
according to comparative analysis of 16S rRNA
and mcrA genes
Lisa D. Tymensen,3 Karen A. Beauchemin and Tim A. McAllister
Correspondence
Lisa D. Tymensen
[email protected]
Received 23 January 2012
Revised
22 April 2012
Accepted 23 April 2012
Agriculture and Agri-Food Canada, Lethbridge, AB TIJ 4B1, Canada
Structures of free-living and protozoa-associated methanogen (PAM) communities from foragefed cattle were investigated by comparative sequence analysis of 16S rRNA and methyl
coenzyme M reductase (mcrA) gene clone libraries. The free-living and protozoa-associated
communities were composed of the same three genera [namely Methanobrevibacter,
Methanomicrobium and rumen cluster C (RCC), which is distantly related to Thermoplasma];
however, the distribution of the methanogen genera differed between the two communities.
Despite previous reports of potential bias for the degenerate mcrA primer set, the 16S rRNA
(n5100 clones) and mcrA (n592 clones) gene libraries exhibited a similar distribution pattern for
the three methanogenic genera. RCC was more abundant in the free-living community and
represented 72 and 42 % of the 16S rRNA and mrcA gene sequences, respectively, versus 54
and 13 % of the 16S rRNA and mrcA gene sequences from the PAM community, respectively.
The majority of RCC sequences from the free-living and protozoa-associated communities
belonged to different species-level operational taxonomic units. Methanobrevibacter species were
more abundant in the PAM community and represented 42 and 79 % of clones for the 16S rRNA
and mrcA gene libraries, respectively, versus 9 and 27 % of 16S rRNA and mrcA gene clones
from the free-living community, respectively. Methanomicrobium species were predominantly
free-living. Primers for quantitative PCR were designed to target specific methanogen groups and
used to assess the effect of a high-grain diet on methanogen species composition. Switching the
ruminant diet from forage to high-grain resulted in reduced protozoal diversity, along with a
profound overall reduction in the relative abundance of RCC and an increase in the relative
abundance of free-living Methanobrevibacter spp. It was unclear whether the reduced abundance
of RCC in grain-fed animals was due to the loss of symbiotic protozoa species or due to broader
changes in the rumen environment that affected both RCC and protozoa. Importantly, results from
this study emphasize the need to consider the different methanogen communities when
developing strategies for mitigating methane emissions in ruminants.
INTRODUCTION
Ruminants are recognized as a major contributor to
methane (CH4) emissions within the agricultural sector.
Methane, which is an end product of fermentation, is of
concern because of its detrimental environmental effects
3Present address: Alberta Agriculture and Rural Development, 100,
5401-1st Avenue South, Lethbridge, AB T1J 4V6, Canada.
Abbreviations: OTU, operational taxonomic unit; PAM, protozoaassociated methanogen; qPCR, quantitative PCR; RCC, rumen cluster C.
The GenBank/EMBL/DDBJ accession numbers for the sequences
identified in this study are JN315156–JN315347.
Three supplementary figures and four supplementary tables are
available with the online version of this paper.
1808
(IPCC, 2007) and it represents a substantial loss of dietary
energy (up to 12 %) to the animal (Johnson & Johnson,
1995). Practical and efficacious methods for decreasing
ruminant enteric CH4 emissions have yet to be developed,
but are critical to ensuring environmentally and economically sustainable ruminant production.
Methane is produced by methanogenic archaea (‘methanogens’), which typically comprise ,3 % of the rumen
prokaryotic microbiota (Sharp et al., 1998). The diversity
of the rumen methanogen community is relatively limited.
According to a recent meta-analysis study, the majority of
rumen methanogens belong to only three principal genera,
namely Methanobrevibacter (Mbb), which accounts for
approximately 62 % of methanogens, Methanomicrobium,
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Free-living and protozoa-associated methanogens
which accounts for approximately 15 % of methanogens,
and a genus-level clade designated ‘rumen cluster C’ (RCC)
that is distantly related to Thermoplasma and accounts for
16 % of methanogens (Janssen & Kirs, 2008). Although it
has yet to be confirmed that RCC are methanogenic, the
methyl coenzyme M reductase (mcrA) gene, which is a key
enzyme for methanogenesis, has been recently sequenced
by P. N. Evans, J. Padmanahba, S. E. Hook, L. I. Sly, S. E.
Denman, C. S. McSweeney & A.-D. G. Wright (unpublished data) for three RCC strains, namely DCM1
(GenBank accession no. GQ339873), WGK1 (GQ339874)
and CRM1 (GQ339872), suggesting that members of the
RCC are indeed methanogenic. Some methanogen species
derive energy from hydrogen by using it to reduce CO2
to CH4. To increase access to hydrogen, these methanogens may engage in a symbiotic relationship with rumen
protozoa, which produce hydrogen via their hydrogenosomes (Finlay & Fenchel, 1989). It has been estimated that
approximately 37 % of CH4 from ruminants is produced
by protozoa-associated methanogens (PAMs) (Finlay et al.,
1994). Whilst elimination of protozoa (defaunation)
generally lowers CH4 emissions (Hegarty, 1999), the reason
for its efficacy is unknown. One hypothesis is that
defaunation leads to decreased total methanogen abundance. Recent studies suggest that this is unlikely, as there is
little correlation between methanogen abundance and CH4
emissions (Mosoni et al., 2011; Zhou et al., 2009). An
alternative hypothesis is that defaunation results in the
elimination of a specific subset of methanogens (i.e.
PAMs), thereby altering the methanogen community
composition such that it is potentially less efficient at
producing CH4. In support of this premise, results of a
recent study have indicated that feed efficiency and CH4
production are correlated with differences in methanogen
community structure (Zhou et al., 2009). It therefore
appears that differences in methanogen community
structure are an important determining factor of CH4
emissions.
Few studies have thus far examined PAMs, hence the
structure of this community has not been well-characterized. By consensus, Methanobrevibacter spp. appear
to be the predominant PAM (Irbis & Ushida, 2004;
Regensbogenova et al., 2004; Sharp et al., 1998; Tokura et
al., 1999). PAMs belonging to the RCC have only been
reported in one study, where they accounted for approximately 1.5 % of methanogens (Irbis & Ushida, 2004). With
respect to Methanomicrobium sp., data are contradictory.
In one study it was identified as the principal protozoaassociated taxon (Regensbogenova et al., 2004), while in
another comparative study, Methanomicrobium sp. represented approximately 12 % of total rumen methanogens
but were not detected in protozoa, and were therefore
deemed to be essentially free-living (Sharp et al., 1998).
Overall, these studies suggest that PAMs belong to the same
genera as free-living methanogens; however, with the
exception of Sharp et al. (1998), comparisons of PAM
and free-living methanogen communities are lacking.
http://mic.sgmjournals.org
In the present study, we examined the hypothesis that freeliving rumen methanogen and PAM communities differ.
Structures of free-living and PAM communities in foragefed cattle were investigated by comparative sequence
analysis of 16S rRNA and mcrA gene clone libraries.
Given that the introduction of grains into the ruminant
diet generally decreases protozoal diversity (Hegarty, 1999)
and also reduces CH4 production per unit of feed digested
(Beauchemin et al., 2009), we also used quantitative PCR
(qPCR) to measure changes in the relative abundance of
different methanogen taxa when the diet was switched
from forage to high-grain.
METHODS
Collection of rumen fluid. Rumen fluid samples were obtained from
four 10-month-old rumen-cannulated Black Angus heifers that were
initially forage-fed and then transitioned to a high-concentrate diet.
Procedures involving cattle were conducted in accordance with the
guidelines established by the Canadian Council on Animal Care
(Olfert et al., 1993) and were approved by the Lethbridge Research
Centre Animal Care Committee. Heifers were specifically raised on a
forage diet consisting of grass hay and had never received grain prior
to the transition period. Over a 5-week period, heifers were
transitioned from forage to a high-grain diet that consisted of 9 %
barley silage, 81 % dry-rolled barley and 10 % vitamin and mineral
supplement (dry matter). Animals were fed the high-grain diet for
5 weeks prior to sampling. Feed was offered ad libitum once per day,
and one sample for each diet (i.e. forage and high-grain) was collected
1 h prior to feeding. Rumen fluid samples (250 ml) were collected
from each of four sites (reticulum, ventral and caudal sacs, and dorsoventral midline) and pooled for each animal. Samples were strained
twice through two layers of PTEX mesh (355 mm pore size; Sefar Inc.)
to remove large feed particles, stored in pre-warmed (39 uC) air-tight
containers and transported to the laboratory for fractionation and
analysis.
Microscopic identification of protozoa. Rumen fluid was fixed for
at least 2 h at room temperature in an equal volume of methyl green–
formaldehyde–saline (MFS) solution containing 3.5 % (v/v) formaldehyde, 8 g NaCl l21 and 0.6 g methyl green l21 (Sigma–Aldrich).
Samples (approx. 10 ml) were loaded into a Neubauer improved
counting chamber and viewed at 6100 magnification. Protozoa were
identified and enumerated to at least the genus level according to
Dehority (1993). Each sample was enumerated in duplicate and
average values were used for data analysis.
Fractionation of rumen fluid. Strained rumen fluid (500 ml) was
incubated at 39 uC for 30 min to allow separation. Following
incubation, the top layer, containing plant debris, was removed and
discarded, and the sample was gently mixed by inversion. Wholerumen fluid samples (200 ml) were collected and stored at 220 uC
until processed for DNA extraction. Protozoa were separated from
fresh rumen fluid by filtration through NITEX mesh (11 mm pore
size; Sefar Inc.). For the protozoa-free rumen fluid samples (i.e.
containing predominantly free-living methanogens), the filtrate
(1 ml) was centrifuged (21 000 g) for 2 min, 700 ml of supernatant
was removed and the cell pellet was suspended in the remaining
liquid. Protozoa were isolated as described by Irbis & Ushida (2004).
Briefly, protozoa that were retained on the NITEX mesh were
exhaustively washed with sterile anoxic basal salt solution (pH 6.8–
7.0; 2.0 g NaCl, 4.9 g K2HPO4, 3.8 g KH2PO4, 0.07 g MgSO4 . 7H2O
and 0.05 g CaCl2 . 2H2O l21) and collected in 25 ml salt solution.
Precautions were taken to minimize contact with oxygen and keep the
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L. D. Tymensen, K. A. Beauchemin and T. A. McAllister
protozoa warm (39 uC). Washed protozoa were fixed in 70 % (v/v)
ethanol. All samples were stored at 220 uC until processed for DNA
extraction.
DNA extraction. Genomic DNA from duplicate rumen fluid samples
was isolated using a QIAamp DNA Stool Mini kit (Qiagen) according
to the manufacturer’s directions and subsequently pooled. We have
previously validated this kit for extraction of microbial DNA from
total rumen contents (Sharma et al., 2003). DNA was extracted from
protozoa as described by Irbis & Ushida (2004). Briefly, ethanol-fixed
protozoa were washed and suspended in PBS (Sigma-Aldrich).
Approximately 100 protozoa were transferred to a 1.5 ml tube and
washed once with PBS. DNA from the protozoal fraction was isolated
by adding 100 ml of a solution containing Chelex-100 (5 % w/v; BioRad) and proteinase K (100 mg ml21; Qiagen) in sterile distilled water
to each tube. Samples were vortexed for 30 s and incubated at 56 uC
for 2 h. The samples were centrifuged at 21 000 g for 3 min, and the
supernatant was transferred to a new tube and incubated at 95 uC for
10 min to inactivate the proteinase K.
Construction and sequencing of 16S rRNA and mcrA gene
clone libraries. Clone libraries of the 16S rRNA and mcrA genes
were constructed for the protozoa-free rumen fluid (free-living
methanogens) and protozoa (PAMs) DNA samples. Separate libraries
were constructed for each animal (n516 libraries; four animals 6
two fractions 6 two diets). Partial fragments of the 16S rRNA and
mcrA genes were PCR-amplified with the universal methanogenspecific primers Met86f/Met915r and mlas/mcrA-rev, respectively
(see Table S1, available with the online version of this paper). Each
50 ml PCR contained 1.25 U ExTaq DNA polymerase (TaKaRa Bio),
16 PCR buffer with Mg2+, 0.8 mM dNTPs, 0.5 mmol of each primer
and 100 ng DNA. Cycling conditions included an initial denaturation
at 94 uC for 30 s, followed by 30 cycles of 98 uC for 10 s, 55 uC (16S
rRNA) or 60 uC (mcrA) for 30 s and 72 uC for 1 min and a final
elongation of 5 min at 72 uC. Amplified products were cloned into
the pCR2.1 TOPO vector (Invitrogen) and transformed into
Escherichia coli Top10 cells according to the manufacturer’s directions. To ensure representative sampling of clones, approximately
equal numbers of clones were sequenced for each library, and
sequence data for each of the four fractions/diets were pooled (i.e.
free-living/forage-fed, free-living/grain-fed, protozoa-associated/forage-fed and protozoa-associated/grain-fed). Plasmid DNA extraction
and capillary sequencing were performed by Functional Biosciences
using M13 forward and reverse primers.
Phylogenetic, network and statistical analysis of clone libraries. All sequences were compared with entries in the GenBank nr
(non-redundant) database (filtered to exclude sequences from
environmental and uncultured clones) using BLASTN (Zhang et al.,
2000). Chimeric 16S rRNA gene sequences were identified using
Bellerophon v. 3 (Huber et al., 2004). Non-methanogen and chimeric
sequences were eliminated from further analysis. Sequences were
aligned with CLUSTAL W (Thompson et al., 1994) and evolutionary
distance matrices were calculated according to the Kimura twoparameter algorithm using MEGA 5.05 (Tamura et al., 2011).
Sequences were assigned to operational taxonomic units (OTUs) on
the basis of ¢97 % (16S rRNA) or ¢95 % (mcrA) sequence identity
using the furthest-neighbour algorithm as implemented in mothur v.
1.20.0. (Schloss et al., 2009). Methanogen networks were visualized
with Cytoscape v. 2.8 (Smoot et al., 2011), using the attribute circle
model. Phylogenetic trees were constructed using one representative
sequence from each OTU plus sequences of reference strains obtained
from GenBank. Sequences were aligned with CLUSTAL W and all
positions containing gaps were removed. Phylogenetic trees were
constructed in MEGA 5.05 using the neighbour-joining method and
bootstrap analysis of 1000 replicates. Species richness and diversity
were estimated using the Chao1 and Shannon indices as implemented
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in mothur. Libraries were compared using #-Libshuff, which calculates
the integral form of the Cramér–von Mises statistic, to determine the
probability that they have the same community structure by chance
(Schloss et al., 2004). Community structures of the libraries were also
compared in a phylogenetic context using the unweighted UniFrac
test, which measures the fraction of a tree’s branch length that is
unique to each library represented in the tree (Lozupone et al., 2006).
P-values for #-Libshuff and UniFrac analyses were corrected using
Bonferroni’s correction and significance was defined at P,0.05.
Real-time qPCR. Methanogen 16S rRNA gene copy numbers were
estimated using a nested PCR approach in which all methanogens
were first amplified using the same archaeal primers that were used
for the clone libraries (Met86f/Met915r), followed by quantification
of the amplicons using group-specific primers. The nested approach
was used to ensure comparability between qPCR and clone library
results, as we have observed previously that methanogen species
composition can be affected by PCR bias depending on which
archaeal primer sets are used (Tymensen & McAllister, 2012). As
such, the nested approach ensured that any primer bias introduced by
the Met86f/Met915r primer set would be consistent for both the clone
library and qPCR experiments. Nested qPCR primers were designed
to target the 16S rRNA gene of all methanogens, Methanobrevibacter
spp., plus two groups of methanogens belonging to the RCC clade,
namely those methanogens from OTUs RCC a and f and OTUs RCC
c, d, e, j, k and l which were more predominant in free-living
methanogen and PAM libraries, respectively (Table S1). Primary PCR
was conducted with primers Met86f/Met915r as described above,
except that only 20 amplification cycles were used. The resultant PCR
product served as a template for qPCR. All qPCRs were carried out in
20 ml volumes and contained 16 Brilliant II SYBR Green qPCR
Master Mix (Stratagene), 0.5 mM of each primer (Table S1) and 1 ml
of the primary PCR product. Quantitative PCR was conducted using
an Mx3005P Stratagene thermocycler. Amplification conditions were
one cycle at 95 uC for 10 min followed by 30 cycles of 95 uC for 30 s,
63 uC for 30 s and 72 uC for 30 s. Melting-curve analysis was
conducted over a range of 55–95 uC to assess specificity of the
amplification products. The numbers of Mbb, RCC a and f and RCC
c, d, e, j, k and l amplicons in each sample were normalized to total
methanogen amplicon numbers, and fold differences in amplicon
abundance, relative to one sample from a forage-fed animal for which
the amplicon abundance was arbitrarily set to 1, were calculated using
the comparative threshold cycle (22DDC t ) method (Livak &
Schmittgen, 2001).
RESULTS
Sequence analysis and phylogeny of 16S rRNA
and mcrA clone libraries
In total, 209 sequences were obtained for the 16S rRNA
and mcrA libraries combined. Seventeen sequences (8.1 %)
were chimeras or non-methanogens, and were eliminated.
For the 16S rRNA gene, 47 and 53 methanogen sequences
were obtained from free-living methanogen and PAM
libraries, respectively. The sequences were assigned to 19
species-level OTUs based on a minimum sequence identity
of 97 % (Table S2). BLASTN analysis indicated that 12 of the
OTUs, representing 63 % of the sequences, had the highest
identity to sequences from RCC strains of intestinal origin
(i.e. DMC1, CH1270, CRM1 and WGK1). Four OTUs,
representing 26 % of the sequences, had the highest
sequence identity to Methanobrevibacter strains (1Y,
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Microbiology 158
Free-living and protozoa-associated methanogens
YE288 and WBY1) that were isolated from the bovine/
ovine rumen or the foregut of the Tammar wallaby, while
two OTUs, representing 10 % of the sequences, had the
highest sequence identity to Methanomicrobium spp., and
one OTU, representing 1 % of the sequences, had the
highest sequence identity to Methanobacterium spp. Phylogenetic analysis confirmed that members of the same OTU
clustered together along with their respective reference
sequences from the BLASTN analysis (Fig. S1). Notably,
among the RCC 16S rRNA sequences, those derived from
the free-living community (Fig. S1, #) clustered together
and separately from sequences derived from PAMs ($).
Phylogenetic placement of the 16S rRNA OTUs with
respect to major genera of methanogenic archaea is shown
in Fig. 1. Representative PAM sequences from previous
studies (Chagan et al., 1999; Regensbogenova et al., 2004;
Tokura et al., 1999) were also included in the phylogenetic
analysis.
For the mcrA gene, 45 and 47 sequences were obtained
from free-living methanogen and PAM libraries, respectively. The mcrA gene sequences were grouped into 16
OTUs using a minimum sequence identity of 95 % (Table
S3). BLASTN analysis indicated that 11 of the OTUs,
representing 27 % of the sequences, had the highest
identity to sequences from RCC strains of intestinal origin
(i.e. DMC1 and WGK1). Four OTUs, representing 53 % of
the sequences, had the highest sequence identity to
Methanobrevibacter spp. isolated from the bovine rumen
(Methanobrevibacter millerae ZA10) and pig faeces (Methanobrevibacter gottschalkii PG) and one OTU, representing 19 % of the sequences, had the highest identity to
Methanomicrobium spp. There were no mcrA sequences
with identity to Methanobacterium spp. Phylogenetic analysis confirmed that members of the same OTU clustered
together along with their respective reference sequences
from the BLASTN analysis (Fig. S2). A phylogenetic tree
depicting the placement of OTUs with respect to most
major genera of methanogenic archaea is shown in Fig. 2.
Sequences for the mcrA genes of rumen PAMs have not
been previously reported, and were thus not included.
Coleman rarefaction curves, which are an indicator of species
richness and represent how extensively genetic diversity of
each community was sampled, are shown for free-living
methanogen and PAM libraries (Fig. S3). Rarefaction
analysis indicated that the majority of the methanogen
diversity was captured by the cloning analysis (i.e. 80–90 %
coverage for the PAM community and 63–72 % coverage for
the free-living methanogen community). Chao1 and
Shannon index values revealed no differences in species
richness or diversity between free-living methanogen and
PAM 16S rRNA libraries (Table 1). In contrast, Coleman
rarefaction curves, Chao1 and Shannon indices indicated
that the free-living methanogen mcrA library had greater
species richness and diversity than the PAM mcrA library.
Analysis of the 16S rRNA and mcrA libraries using #-Libshuff
and unweighted UniFrac indicated that community structures
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of the free-living methanogen and PAM libraries differed
significantly (Table S4). Unweighted UniFrac principal
coordinate analysis indicated that free-living methanogen
communities from different cattle tended to cluster together
and separately (albeit diffusely) from PAM communities
(Fig. 3). The diffuse clustering pattern suggested that there is
substantial variability among methanogen communities
of individual animals. Network analysis indicated that the
methanogens from free-living and protozoa-associated
communities are predominantly from different OTUs
(Fig. 4). Community structures of the libraries were
examined by assessing the distribution of the OTUs
(Fig. 5). For the 16S rRNA libraries, OTUs belonging to
the RCC clade were approximately 1.4-fold more
abundant in the free-living methanogen library than in
the PAM library. In particular, OTUs RCC a, b, f, g, h and
i were unique or more abundant in the free-living
methanogen library, while OTUs RCC c, d, e, j, k and l
were unique or more abundant in the PAM library. OTUs
belonging to Methanobrevibacter spp. were approximately
4.7-fold more abundant in the PAM library compared
with the free-living methanogen library. OTUs Mbb a and
c were unique in the free-living methanogen library while
OTUs Mbb b and d were unique or more abundant in the
PAM library. OTUs belonging to Methanomicrobium spp.
were more abundant in the free-living methanogen
library.
For the mcrA libraries, OTUs belonging to the RCC clade
were approximately 3.2-fold more abundant in the freeliving methanogen library than in the PAM library. Three
of the OTUs (RCC d, f and k) were shared between the
libraries, while seven of the OTUs (RCC a, b, c, e, g, i and j)
were unique to the free-living methanogen and one OTU
(RCC h) was unique to the PAM library. OTUs belonging
to Methanobrevibacter spp. were approximately threefold
more abundant in the PAM library compared with the freeliving-methanogen library. Two OTUs (Mbb a and c) were
shared between the libraries, while two OTUs (Mbb b and
d) were unique to the PAM library. Methanomicrobium
spp. were approximately 3.4-fold more abundant in the
free-living methanogen library, and all sequences from
both libraries belonged to the same OTU (i.e. shared
¢95 % sequence identity).
Effect of high-grain diet on protozoa–
methanogen interactions
As determined via microscopy, grain feeding reduced the
number of protozoa taxa present in the rumen from an
average of seven genera per animal (which included
Entodinium, Isotricha, Dasytricha, Diplodinium, Eudiplodinium, Ostracodinium, Metadinium, Eremoplastron, Polyplastron and/or Epidinium) when the animals were fed a
forage diet to a mean of two genera (namely Entodinium,
Isotricha and/or Dasytricha) when the animals were
switched to a high-grain diet (results not shown). To
examine the effect of a high-grain diet on the distribution
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L. D. Tymensen, K. A. Beauchemin and T. A. McAllister
65
Methanobrevibacter thaueri CW (U55236)
Methanogen associated with Euaiploainium (AB026171)
67 Methanobrevibacter sp. SM9 (AJ009958)
67 Methanobrevibacter millerae ZA10 (AY196673)
67 Methanogen associated with Isotricha (AB026169)
Mbba (JN315202)
Methanobrevibacter sp. WBY1 (EU919428)
Methanobrevibacter gottschalkii HO (U55238)
Methanobrevibacter sp. 1Y (DQ135988)
Methanogen associated with Polyplastron (AB026174)
Methanogen associated with Polyplastron (AB026173)
Mbbb (JN315212)
Mbb
Methanobrevibacter smithii PS. (AY19669)
Methanobrevibacter woesei GS. (U55237)
Mbbc (JN315176)
100 Methanobrevibacter sp. AbM4 (AJ550156)
Methanobrevibacter wolinii SH (U55240)
Methanobrevibacter arboriphilius AZ (AY196663)
98
Methanobrevibacter sp. YE288 (GQ906571)
81 Methanogen associated with Eudiplodinium (AB026170)
84 Methanobrevibacter sp. NT7 (AJ009959)
Mbbd (JN315242)
93
Methanobrevibacter olleyae KM1H51P (AY615201)
89
Methanobrevibacter ruminantium (AY196666)
Methanogen associated with Isotricha (AB026168)
Methanosphaera stadtmanae (AY196684)
99
Methanogen associated with Eudiplodinium (AB026172)
Methanobacterium formicicum (AY196659)
99
Methanobacterium bryantii MOH (AY196657)
Methanobacterium sp. GH (EU333914)
50
93 Methanogen associated with Polyplastron (AB026175)
64 Ma (JN315243)
Methanococus voltae (U38461)
100
Methanococus vannielii (AY196675)
Thermoplasma acidophilum (M38637)
65 RCCa (JN315181)
Methanogenic archaeon DCMI (GQ339876)
Methanogenic archaeon CH1270 (DQ445723)
Methanogenic archaeon WGK1 (GQ339877)
RCCb (JN315174)
RCCc (JN315208)
Bovine rumen clone ONCAN09 (DQ123879)
97
99
52 80 RCCd (JN315206)
75 RCCe (JN315210)
RCC
RCCf (JN315171)
RCCg (JN315197)
68
RCCh (JN315159)
RCCi (JN315193)
75 Bovine rumen clone PECAN01 (DQ123861)
100
RCCj (JN315222)
100 RCCk (JN315252)
Bovine rumen clone ONCAN17 (DQ123887)
RCCl (JN315251)
77
99 Methanogenic archaeon CRM1 (GQ339875)
68 Methanosarcina mazei (AY196685)
100 Methanosarcina acetivorans (M59137)
95
Methanosarcina barkeri (AY196682)
Methanimicrococcus blatticola (AY196680)
82
Methanogen associated with Ophryoscolex (AJ606404)
79
Methanosaeta thermophila (AB071701)
Methanospirillum hungatei (AY196683)
100
76
Methanofollis liminatans (AY196677)
Methanoculleus bourgensis (AY196674)
100
100 Methanoplanus petrolearius (AY196681)
83
Methanolacinia paynteri (AY196678)
Methanogen associated with Metadinium (AJ606410)
98
Methanogen associated with Ophryoscolex (AJ606400)
Mm
Methanomicrobium mobile (AY196679)
Mma (JN315192)
Mmb (JN315180)
Methanopyrus kandleri (AB301476)
0.02
of different methanogen species/strains, nested qPCR
primers were designed for quantification of Methanobrevibacter spp. and the RCC clade. Three groups of the RCC
1812
Fig. 1. Phylogenetic analysis of partial 16S
rRNA gene sequences from free-living and
protozoa-associated methanogen libraries.
Representative OTUs (see Table S2, shown
in bold type) were defined at ¢97 %
sequence identity. Reference sequences of
protozoa-associated rumen methanogens from
three other studies (Chagan et al., 1999;
Regensbogenova et al., 2004; Tokura et al.,
1999) were also included. GenBank accession numbers are presented in parentheses.
Bar, 0.02 nucleotide substitutions per base.
The bootstrap consensus tree was inferred
from 1000 replicates, and bootstrap values
(¢50 %) are indicated. Abbreviations: Mbb,
Methanobrevibacter spp.; Mm, Methanomicrobium spp.; RCC, rumen cluster C.
clade were originally targeted, specifically OTUs RCC a and
f and RCC b, g, h and i (as defined in Table S2), which were
more abundant in the free-living methanogen library, and
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Free-living and protozoa-associated methanogens
Mbba (JN315310)
Mbbb (JN315333)
Methanobrevibacter millerae ZA10 (EU919430)
53 Mbbc (JN315338)
Methanobrevibacter sp. WBY1 (EU919429)
Methanobrevibacter gottschalkii PG (EU919431)
Mbb
56
Methanobrevibacter smithii (DQ251046)
97
Mbbd (JN315329)
Methanobrevibacter oralis (DQ251045)
55
Methanobrevibacter ruminantium DSM1093 (AF414046)
81
Methanobrevibacter arboriphilus (AB300777)
Methanobrevibacter woesei GS (EU919432)
75
Methanobacterium bryantii DSM863 (AF313806)
Methanobacterium formicicum DSM1535 (EF465108)
51
99
Methanobacterium formicicum DSM1312 (AF414050)
Methanobacterium formicicum DSM1312 (AF414051)
Methanosphaera stadtmanae DSM3091 (AF414047)
67
Methanotorris igneus DSM5666 (AF414039)
99
97
77
Methanocaldococcus jannaschii DSM2661 (AF414040)
89
Methanococcus voltae (X07793)
98
Methanothermococcus thermolithotrophicus DSM2095 (AF414048)
Methanothermobacter thermophilus DSM6529 (AY289752)
100 Methanobacterium thermoautotrophicum (U10036)
Methanoculleus thermophilus DSM2624 (AF313804)
97
99
Methanoculleus bourgensis DSM3045 (AF414036)
Methanofollis liminatans DSM4140 (AF414041)
Methanospirillum hungatei DSM864 (AF414038)
100
Methanocorpusculum aggregans DSM3027 (AF414034)
Methanomicrobium mobile DSM539 (AF414044)
84
Mm
100 Mma (JN315257)
Methanosaeta concilii DSM3671 (AF414037)
Methanosarcina barkeri (Y00158)
69
100
Methanosarcina mazei DSM2053 (AF414043)
RCCa (JN315273)
Bovine rumen clone CL152 (EF379272)
RCCb (JN315263)
RCCc (JN315279)
RCCd (JN315301)
RCCe (JN315283)
71
53 Bovine rumen clone CLI34 (EF379254)
67
RCCf (JN315282)
RCC
RCCg (JN315294)
Methanogenic archaeon DCM1 (GQ339873)
RCCi (JN315289)
92
RCCj (JN315275)
90
RCCk (JN315299)
57
100 Bovine rumen clone CLI46 (EF379266)
100
RCCh (JN315309)
74
Methanogenic archaeon WGK1 (GQ339874)
Bovine rumen clone CLI40 (EF379260)
Methanopyrus kandleri DSM6324 (AF414042)
0.05
Fig. 2. Phylogenetic analysis of partial mcrA gene sequences from free-living and protozoa-associated methanogen libraries.
Representative OTUs (see Table S3, shown in bold type) were defined at ¢95 % sequence identity. GenBank accession
numbers are presented in parentheses. Bar, 0.05 nucleotide substitutions per base. The bootstrap consensus tree was inferred
from 1000 replicates, and bootstrap values (¢50 %) are indicated on the tree. Abbreviations: Mbb, Methanobrevibacter spp.;
Mm, Methanomicrobium spp.; RCC, rumen cluster C.
RCC c, d, e, j, k and l, which were more abundant in the
PAM library (see Fig. 5). However, the primer for the RCC
b, g, h and i group was not specific and was consequently
omitted from the study. In whole-rumen fluid containing
both free-living methanogens and PAMs, the relative
abundance of both groups of RCC decreased, whereas the
abundance of Methanobrevibacter spp. increased when the
animals were fed a high-grain diet (Fig. 6). A similar trend
was observed for the free-living methanogen community.
For the PAM community, a decrease in the abundance of
http://mic.sgmjournals.org
RCC was observed for the high-grain diet, while there was no
change in the relative abundance of Methanobrevibacter spp.
DISCUSSION
The rumen methanogen community is characterized by
limited species diversity (Janssen & Kirs, 2008). Consistent
with this, nearly all 16S rRNA and mcrA gene sequences in
this study belonged to the three most abundant archaea
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L. D. Tymensen, K. A. Beauchemin and T. A. McAllister
Table 1. Diversity and richness estimators for methanogen 16S RNA and mcrA gene sequences from free-living and protozoaassociated methanogen (PAM) libraries
Library
16S free-living
16S PAM
mcrA free-living
mcrA PAM
No. of sequences
No. of OTUs*
47
53
45
47
12
12
13
9
Chao1 richness estimateD
19.00
15.33
18.00
10.00
(13.34–48.54)
(12.50–34.07)
(13.86–41.1)
(9.09–19.68)
Coverage (%)
(OTUs/Chao1)
63.2
80.0
72.2
90.0
Shannon index
1.79
1.95
2.08
1.52
(1.46–2.12)
(1.68–2.22)
(1.79–2.38)
(1.20–1.85)
*OTUs for 16S rRNA and mcrA gene libraries were defined at 97 and 95 % sequence similarity, respectively.
DConfidence intervals (95 % CI) are indicated in parentheses.
genera within the rumen, namely RCC (46 %), Methanobrevibacter (39 %) and Methanomicrobium (15 %). While
Methanobrevibacter spp. are generally considered to be the
most abundant rumen methanogens (Janssen & Kirs,
2008), the majority of sequences in this study were related
to the RCC. Similarly, several other studies have also
identified RCC as predominant members of the rumen
archaea consortium (Ohene-Adjei et al., 2007; Wright
et al., 2006, 2007). The reason for differences in the
methanogen species composition among studies may relate
to host factors, such as differences in genetic variation, diet
or geographical region, or differences in experimental
P1 – percentage variation explained 19.5 %
0.4
0.3
0.2
0.1
methodology associated with rumen sampling and library
construction.
PCR-derived libraries may be affected by primer bias, in
which certain taxa are preferentially amplified (CadilloQuiroz et al., 2008; Skillman et al., 2006; Tajima et al.,
2001). Multiple primer approaches may give a more complete picture of methanogen diversity and lend confidence
to observed compositional trends among communities;
thus, clone libraries for the 16S rRNA and mcrA genes were
constructed. Different species compositions were observed
for the libraries, with RCC predominating in the 16S rRNA
gene clone library, while in the mcrA gene clone library,
Methanobrevibacter spp. were most abundant (Fig. 5). A
similar bias of the mcrA primer set for Methanobrevibacter
sequences relative to RCC sequences has been observed
previously for libraries constructed with mcrA versus 16S
rRNA primer sets (Evans et al., 2009). Although the mcrA
gene is commonly used in community structure analyses,
(a)
(b)
0.0
–0.1
–0.2
–0.3
–0.4
–0.3
0.1
0.2
0.3
–0.2
–0.1
0.0
P2 – percentage variation explained 14.4 %
0.4
Fig. 3. Principal coordinate analysis showing the relationship
between free-living methanogen (blue triangles) and PAM (red
squares) communities from different cattle. Unweighted UniFrac
was used to generate a matrix of pairwise distances between 16S
rRNA gene sequences of methanogen communities, and a
scatterplot was generated using the matrix. Percentages of
variance explained by each principal coordinate (P1 and P2) are
shown on the x- and y-axes.
1814
Fig. 4. Network analysis of methanogen communities according to
(a) 16S rRNA gene sequences and (b) mcrA gene sequences.
Blue triangles represent free-living methanogen communities and
red squares represent PAM communities from four individual
cattle. Circles represent different methanogen OTUs (purple,
RCC; green, Methanomicrobium; yellow, Methanobrevibacter;
orange, Methanobacterium). Methanogen OTUs are connected
by a line to individual methanogen communities (blue triangles/ red
squares) that contain the particular OTU. Size of circles and line
weight correspond to the presence and abundance of an OTU in a
methanogen community, respectively.
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Free-living and protozoa-associated methanogens
Mm
(19 %)
a
Mbb d
(9 %) c
a
i
h
g
16S rRNA
Mm
M (2a %)
a b
(2 %)
b
c
RCC
(72%)
d
d
a
e
Mbb
(42%)
f e
b
a bc
Mm
(31%)
mcrA
d
e
f RCC
(42 %)
g
RCC
b
(54 %)
l k j
RCC
Mm
d f h (13 %)
(9 %)
k
d
a
b
i
j
k
Mbb
(27 %) c
a
Mbb
(79 %)
c
Free-living
Protozoa-associated
Fig. 5. Distribution of 16S rRNA and mcrA gene sequences from
free-living and protozoa-associated methanogen libraries. Small
letters refer to different OTUs for 16S rRNA and mcrA gene
libraries as defined at ¢97 and ¢95 % sequence identity,
respectively (see Tables S2 and S3). Abbreviations: Mbb,
Methanobrevibacter spp.; Mm, Methanomicrobium spp.; RCC,
rumen cluster C.
5
Total methanogens
(whole rumen fluid)
PAMs
Forage
Grain
*
4
Relative abundance
Free-living
methanogens
*
3
2
1
*
a
*
*
*
b
c
a
b
*
c
a
*
b
c
Fig. 6. Effect of switching cattle diets from forage to high-grain on
the relative abundance of different methanogen species/strains in
free-living and protozoa-associated methanogen communities. xaxis: (a) OTUs RCC a and f (as defined in Table S2, also see Fig.
3); (b) OTUs RCC c, d, e, j, k and l; (c) Methanobrevibacter spp.
The y-axis indicates the relative abundance of each group of
methanogens (normalized to total methanogen 16S rRNA gene
copy number). *P,0.05 compared with respective forage-fed
sample; n54 animals.
http://mic.sgmjournals.org
the degeneracy of the primers may lead to biased
amplification, indicating that relative community compositions of libraries constructed with this primer set need to
be interpreted carefully (Lueders & Friedrich, 2003).
Despite the differences in sequence composition between
the 16S rRNA and mcrA libraries, similar overall distribution patterns were observed. Methanobrevibacter spp.
were proportionally more abundant in association with
protozoa, whereas RCC and Methanomicrobium spp. were
proportionally more abundant in the free-living methanogen community.
Comparative sequence analyses (i.e. #-Libshuff and
UniFrac) indicated that the structures of the free-living
and PAM communities differed. In agreement with
previous studies, Methanobrevibacter spp. were the primary
methanogen taxon associated with protozoa and represented 59 % of the sequences from 16S rRNA and mcrA
libraries combined (Chagan et al., 1999; Irbis & Ushida,
2004; Sharp et al., 1998; Tokura et al., 1999). Only a small
percentage of PAMs was identified as Methanomicrobium
(5 versus 25 % in the free-living methanogen community),
indicating that this methanogen is primarily free-living
within the rumen. Similarly, using a DNA-hybridization
technique to identify major methanogen families, Sharp
et al. (1998) observed that only members of the family
Methanobacteriaceae (which encompasses Methanobrevibacter spp.) associated with protozoa, while members of
the order Methanomicrobiales, which represented approximately 12 % of total rumen methanogens, were not
detected in association with protozoa and were deemed
to be essentially free-living (Sharp et al., 1998). It should be
noted that some ‘contamination’ of taxa between the two
communities would be expected due to the lysis of fragile
protozoa (which would release PAMs into the rumen fluid)
and predatory feeding of rumen methanogens by protozoa
(which would result in free-living methanogens being
detected in association with protozoa).
Methanogens belonging to the RCC clade also represented
a considerable fraction of the PAMs from both 16S rRNA
and mcrA gene libraries (54 and 13 %, respectively). The
association of this taxon with rumen protozoa has been
reported only once, but it was present as a minor taxon,
representing approximately 1.5 % of PAMs (Irbis &
Ushida, 2004). Our analyses indicate that the reported
lack of protozoa-associated RCC in previous studies of
PAMs (Irbis & Ushida, 2004; Regensbogenova et al., 2004;
Sharp et al., 1998; Tokura et al., 1999) is likely to be due to
PCR bias as a result of the use of different archaeal primers
that contain nucleotide mismatches with the RCC clade
(Tymensen & McAllister, 2012). Notably, RCC sequences
from the PAM 16S rRNA libraries generally clustered
separately from free-living RCC sequences (Fig. S1), indicating that methanogens within each environment (i.e.
protozoa-associated) were more related than methanogens obtained from an individual cow. Low bootstrap
values in the phylogenetic analysis precluded assigning the
RCC sequences to robust clades. However, most of the
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L. D. Tymensen, K. A. Beauchemin and T. A. McAllister
sequences from each of the communities belonged to
different OTUs that have .3 % sequence difference, which
is typically used to delineate different species (Stackebrandt
& Goebel, 1994), suggesting that different species or strains
of RCC are present in the free-living and protozoaassociated communities. A more detailed phylogenetic
comparison (i.e. involving other genes) of RCC from these
two populations is warranted.
Given that high-grain diets typically reduce protozoal
diversity (Hegarty, 1999), it seems likely that interactions
between protozoa and their associated methanogens would
also be affected. As such, the effect of a high-grain diet on
the methanogen community composition was examined.
Introduction of dietary grains resulted in a profound
decrease in the relative abundance of RCC in the protozoaassociated and free-living methanogen communities, while
in contrast, the relative abundance of Methanobrevibacter
spp. increased in the free-living community (Fig. 6). One
possible reason for the decrease of protozoa-associated
RCC may be the elimination of specific symbiotic protozoa
species, as all protozoa species except Isotricha, Entodinium
and Dasytricha were eliminated by the high-grain diet.
Free-living RCC also decreased in conjunction with grainfeeding, suggesting that free-living methanogens may also
be influenced by extreme changes in diet. Alternatively, the
decrease in RCC abundance may be related to broader dietrelated changes in the rumen environment that affected
both RCC and protozoa. Future studies using monofaunated animals would help clarify the interactions between
the RCC and specific protozoa species. In contrast to the
RCC, the high-grain diet also resulted in an increase in the
relative abundance of free-living Methanobrevibacter spp.
One explanation is that the grain diet may have altered the
rumen environment such that a new niche became
hospitable for occupancy by different species or strains of
Methanobrevibacter.
In conclusion, this study has revealed that free-living and
PAM community structures in the rumen differ at the
species or strain level. This study also demonstrated that
switching the ruminant diet from forage to high-grain
reduces protozoal diversity and affects the overall methanogen community structure by increasing the abundance of
free-living Methanobrevibacter spp. while decreasing the
abundance of methanogens belonging to the RCC clade.
Whether the decrease in RCC is due to the loss of
particular symbiotic protozoa species or due to other
broader changes in the rumen environment remains to be
determined. It has been well-established that increasing the
dietary grain content decreases CH4 emissions per unit of
feed digested (Beauchemin et al., 2009). Results of this
study suggest that the reduction in CH4 emissions
associated with feeding high-grain diets may be related to
changes in the overall methanogen community structure
in the rumen, and in particular with a reduction in
methanogens belonging to the RCC clade, rather than
decreases in methanogen abundance. Shifts in the methanogenic community from a protozoa-associated to a
1816
free-living structure may explain the transient reductions
in methane emissions that are frequently observed after
defaunation. This study contributes to our understanding
of the methanogen ecology within the rumen and underscores the need to consider the different methanogen
communities when developing strategies for mitigating
CH4 emissions. Future studies comparing free-living and
PAM communities with respect to the efficiency of
methanogenesis will help resolve the mechanism by which
dietary inclusion of grain reduces the intensity of CH4
emissions.
ACKNOWLEDGEMENTS
The authors wish to thank Cindy Barkley for assisting with rumen
fluid collections and protozoa isolation and Lili You for conducting
the microscopic identification and enumeration of rumen protozoa.
This work was funded by Agriculture and Agrifood Canada and a
grant from the Norwegian Research Council to T. A. M. This is
Lethbridge Research Centre (LRC) contribution no. 387-11039.
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