Journal of Integrative Agriculture 2016, 15(0): 60345-7
Available online at www.sciencedirect.com
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RESEARCH ARTICLE
Comparison of rumen archaeal diversity in adult and elderly yaks
(Bos grunniens) using 16S rRNA gene high-throughput sequencing
WANG Li-zhi, Wang Zhi-sheng, Xue Bai, Wu De, PENG Quan-hui
Animal Nutrition Institute, Sichuan Agricultural University, Ya’an 625014, P.R.China
Abstract
This study was conducted to investigate the phylogenetic diversity of archaea in the rumen of adult and elderly yaks. Six
domesticated female yaks, 3 adult yaks ((5.3±0.6) years old), and 3 elderly yaks ((10.7±0.6) years old), were used for the
rumen contents collection. Illumina MiSeq high-throughput sequencing technology was applied to examine the archaeal
composition of rumen contents. A total of 92 901 high-quality archaeal sequences were analyzed, and these were assigned
to 2 033 operational taxonomic units (OTUs). Among these, 974 OTUs were unique to adult yaks while 846 OTUs were
unique to elderly yaks; 213 OTUs were shared by both groups. At the phylum level, more than 99% of the obtained OTUs
belonged to the Euryarchaeota phylum. At the genus level, the archaea could be divided into 7 archaeal genera. The 7
genera (i.e., Methanobrevibacter, Methanobacterium, Methanosphaera, Thermogymnomonas, Methanomicrobiu, Methanimicrococcus and the unclassified genus) were shared by all yaks, and their total abundance accounted for 99% of the
rumen archaea. The most abundant archaea in elderly and adult yaks were Methanobrevibacter and Thermogymnomonas,
respectively. The abundance of Methanobacteria (class), Methanobacteriales (order), Methanobacteriaceae (family), and
Methanobrevibacter (genus) in elderly yaks was significantly higher than in adult yaks. In contrast, the abundance of Thermogymnomonas in elderly yaks was 34% lower than in adult yaks, though the difference was not statistically significant.
The difference in abundance of other archaea was not significant between the two groups. These results suggested that the
structure of archaea in the rumen of yaks changed with age. This is the first study to compare the phylogenetic differences
of rumen archaeal structure and composition using the yak model.
Keywords: yak, archaea, rumen, diversity, high-throughput sequencing
1. Introduction
Yak (Bos grunniens) is a unique species, which exclusively
lives in alpine and subalpine regions at altitudes ranging from
Received 16 May, 2016 Accepted 14 July, 2016
WANG Li-zhi, Mobile: +86-13882438306, E-mail:184750130@
qq.com; Correspondence PENG Quan-hui, Tel: +86-8352885125, Fax: +86-835-2885065, E-mail: pengquanhui@126.
com
© 2016, CAAS. All rights reserved. Published by Elsevier Ltd.
doi: 10.1016/S2095-3119(16)61454-5
3 000 to 5 000 m (Wang et al. 2006). There are 15 million
yaks in the Qinghai-Tibetan Plateau of China, accounting for
more than 90% of the total yak population worldwide (Zhang
et al. 2014). The Qinghai-Tibetan Plateau is located at high
altitude with severe weather and poor natural conditions.
Yaks are normally managed under free grazing conditions
*** et al. Journal of Integrative Agriculture 2016, 15(0): 60345-7
all year round with no concentrate supplementation, even
in the winter when grass is covered by snow (Ding et al.
2007). To adapt to this harsh natural environment, yaks have
evolved physiologically to survive in such poor conditions
(Ishizaki et al. 2005; Wang et al. 2009; Shao et al. 2010).
It was documented that yaks produce less enteric methane
to reduce energy loss compared with other ruminants (Ding
et al. 2010). The methane (CH4) energy loss accounts for
over 7% of the total energy intake in ruminant animals given forage-based diets (Yan et al. 2000). Although the CH4
emission rate may be relatively low, yaks remain a significant source of CH4 production in China due to their large
population (Xue et al. 2014). The reduction of enteric CH4
emission has been recognized as an effective approach to
lower the global methane emission, which can also enhance
the livestock production efficiency (Johnson et al. 1993).
Methane that is emitted by ruminants is produced by archaea
in the rumen. To reduce ruminant methane emissions, it is
essential to understand the archaeal community composition
in the rumen and to characterize its phylogeny.
Previous research indicated that archaeal methanogen
diversity in the gastrointestinal tract could vary between animal species (Pei et al. 2010; Luo et al. 2013), and animals
of different ages could have different microbial communities
in the rumen (Jami et al. 2013). However, currently, there is
little information on the diversity of archaea in the rumen of
yaks and on the effects of ageing process on their ruminal
archaea composition. We hypothesized that the structure
and composition of archaea in the rumen of yaks might
be different compared with other ruminants, and changes
would happen with ageing. Therefore, the present work
was conducted to (i) examine the diversity of archaea in the
rumen of yaks and to (ii) compare the differences in archaeal
composition in the rumen of adult and elderly yaks using
the high-throughput gene sequencing technology. This
comprehensive knowledge can promote the understanding
of the factors that affect the archaeal diversity in the rumen
and lay the foundation to study the widely applicable and
long-term regulation of the rumen methane production.
2. Materials and methods
2.1. Animals and sampling
The experimental protocol used in the present study was
approved by the Animal Policy and Welfare Committee
of the Agricultural Research Organization of the Sichuan
Province, China and was in accordance with the guidelines
of the Animal Care and Ethical Committee of the Sichuan
Agricultural University, China.
Six female domesticated yaks were used in the present
3
study - 3 adult yaks ((5.3±0.6) years old and (214.5±18.3)
kg of live weight) and 3 elderly yaks ((10.7±0.6) years old and
(294.3±17.3) kg of live weight). One month before sample
collection, all yaks grazed on a single natural grassland
sward with no concentrate supplementation at the commercial farm at the Ganzi-Tibetan Autonomous Prefecture, Sichuan Province, China. The average altitude of this farm was
3 500 m with a plateau monsoon climate. Rumen content
samples (approximately 100 mL) were collected from different positions of the rumen (Petri et al. 2013) immediately
after the yaks were slaughtered at the commercial abattoir.
The rumen content was filtered through 4 layers of cheese
cloth, and the rumen fluid was immediately placed in liquid
nitrogen (Guo et al. 2015). The samples were taken to the
laboratory and stored at –80°C until the DNA extraction.
2.2. DNA extraction
Total DNA was extracted separately from the rumen contents using a commercially available kit (TIANGEN, Peking,
China) according to the manufacturer instructions. Each
sample was analyzed in triplicates and finally pooled.
DNA samples were purified using a PCR Clean-Up system
(Promega, Madison, USA) and then stored at −20°C for
further processing.
2.3. PCR and amplicon sequencing
The archaea-specific primers, U519F (5´-CAGYMGCCRCGGKAAHACC-3´) and U806R (5´-GGACTACHVGGGTWTCAAT-3´), were used to amplify the V4 hypervariable
region of the archaeal 16S rRNA gene (Shehab et al. 2013).
Three replicates of the DNA extract from each sample were
amplified using PCR. PCR was carried out using a PCR
thermal cycler Model C1000 (Bio-Rad, Richmond, CA) with
the following thermal cycling conditions: initial denaturation
at 94°C for 3 min, followed by 30 cycles at 94°C for 30 s,
annealing at 56°C for 30 s and at 72°C for 30 s. The reaction
was terminated after the extension step at 72°C for 5 min.
The total volume of the reaction mixture was 50 μL, which
consisted of 0.5 μL of each primer (50 pmol each), 5 μL of
2.5 mmol L–1 dNTP mixture, 5 μL of 10× Ex Taq buffer (20
mmol L–1 Mg2+; TaKaRa, Dalian, China), 0.25 μL of Ex Taq
DNA polymerase (TaKaRa), 1 μL of an environmental DNA
template, and 37.75 μL milli-Q water. The PCR products
were visualized using a 2% agarose gel electrophoresis
and purified using a PCR Purification Kit (QIAGEN, Australia). The purified PCR product was quantified using a
Quant-iTPicoGreen dsDNA Reagent Kit (Life Technologies)
according to the manufacturer instructions and combined in
equimolar ratios into a single tube. Then, the samples were
4
*** et al. Journal of Integrative Agriculture 2016, 15(0): 60345-7
sent to Macrogen Inc. (South Korea) for sequencing using
the Illumina MiSeq 300PE Sequencing Platform.
2.4. Data analysis
Using fast length adjustment of short reads (FLASH)
(Magoč and Salzberg 2011), the raw paired-end reads
were merged into sequences according to the relationship
between the overlap (the shortest overlap length was 10
bp, the longest was 220 bp). The Quantitative Insights
into Microbial Ecology (QIIME) pipeline software (ver.
1.8.0) (Caporaso et al. 2010) was used to differentiate the
obtained sequences according to their barcodes. Then,
the sequences were assigned to their designated rumen
sample. The poor/low quality sequences were discarded
if they met one of the following conditions: their average
quality value was less than 20 over a 50 bp sliding window,
the number of unknown bases they contained was greater
than 6, there was a mismatch between the primer and
the barcode used, and their length was less than 200 bp.
Then, the Uclust method (Edgar et al. 2010) was used to
cluster the obtained sequence into Operational Taxonomic
Units (OTUs) for eventual taxonomy assignment based
on a 97% sequence similarity. The chimeric OTUs were
removed from the analysis by comparing them against the
sequence from the SILIVA database (http://www.mothur.
org/wiki/Silva-reference-files) using Usearch 7.0. The most
abundant sequence was selected as the representative for
each OTU and was assigned taxonomy using the RDP Classifier (at the 80% confidence threshold). The non-archaeal
OTUs were removed using custom Perl scripts and were
not involved in the following analysis. Three alpha diversity
indices (Shannon-Wiener, Chao1, and Observed_species)
were computed at a depth of 11 600 sequences than the
lowest sequence sample. The weighted uniFrac distance
within pairwise samples was measured using the QIIME
pipeline. To determine if the archaeal communities in the
two age groups were different, the PERMANOVA analysis
that was based on the weighted uniFrac distance metric was
performed using the Adonis function in the vegan package
in R. In addition, the samples were clustered based on the
weighted uniFrac distance matrix using the unweighted pair
group method analysis (UPGMA). The shared genera that
existed in all of the samples were selected using custom Perl
scripts, and a heatmap was created using the R ver. 3.0.2
software program to show them. An unpaired two-tailed
t-test (SPSS Statistics for Windows, ver. 22.0, IBM) was
used to assess whether there was a significant difference
(P<0.05) between the adult and elderly yaks. All sequence
data in the present study were deposited to the SRA of the
NCBI database under the BioProject PRJNA290544.
3. Results
3.1. Sequences and OTUs statistics
After size filtering, quality control, and chimera removal,
a total of 92 901 high quality archaeal sequences were
generated, with an average of 15 484±3 239 sequences per
sample. The clean sequences were clustered into OTUs
based on a 97% sequence similarity. A total of 2 033 OTUs
were obtained, of which 974 OTUs were unique to adult
yaks, while 846 OTUs were unique to elderly yaks, and 213
OTUs were shared by both groups.
3.2. Taxonomical profiles of the yak rumen archaea
The obtained OTUs were assigned to taxonomy from phylum
to genus, and the detailed results are presented in Table 1.
At the phylum level, no significant difference was found in
the archaeal abundance between the two groups (P>0.05).
More than 99% of the obtained OTUs in this study belonged
to Euryarchaeota, and the abundance of Crenarchaeota and
of the unclassified archaea was less than 1%. The archaea
in the phylum of Euryarchaeota were divided into 4 classes
including Methanobacteria, Thermoplasmata, Methanomicrobia, and Unclassified Euryarchaeota. These could be
further assigned to 7 genera, representing 4 orders and
6 families. Methanobacteria was composed of 1 order, 1
family, 3 existing genera, and 1 unclassified genus. Thermoplasmata was composed of 1 order, 1 existing family and 1
unclassified family, and 1 existing genus. Methanomicrobia
was composed of 2 orders, 2 families, and 2 genera. At the
genus level, only the abundance of Methanobrevibacter in
the elder yak group was significantly higher compared with
the adult yak group (P=0.007). Compared with the adult
group, the abundance of Thermogymnomonas in the elder
group was on average 34% lower, but the difference was
not significant (P=0.131).
3.3. Alpha diversity analysis
The Shannon-Wiener index, Chao1 index, and the Observed_species index of adult and elderly yaks are listed
in Table 2. No significant difference was observed in the
Chao1 index or in the Observed_species index between
adult and elderly yaks (P>0.05). However, compared with
the elder yak group, the Shannon-Wiener index of the adult
yak group trended to be higher (P=0.084).
3.4. Beta diversity analysis
The weighted uniFrac distance within the samples was mea-
5
*** et al. Journal of Integrative Agriculture 2016, 15(0): 60345-7
Table 1 Comparison of the rumen archaeal composition and abundance in adult and elderly yaks at the phylum, class, order,
family, and genus levels
Item1)
p_Unclassified archaea
p_Crenarchaeota
c_Thermoprotei
o_Unclassified
p_Euryarchaeota
c_Methanobacteria
o_Methanobacteriales
f_Methanobacteriaceae
g_Methanobacterium
g_Methanobrevibacter
g_Methanosphaera
g_Unclassified
c_Thermoplasmata
o_Thermoplasmatales-affiliated lineage C
f_Thermoplasmatales_incertae_sedis
g_Thermogymnomonas
f_Unclassified
c_Methanomicrobia
o_Methanomicrobiales
f_ Methanomicrobiaceae
g_Methanomicrobium
o_Methanosarcinales
f_Methanosarcinaceae
g_Methanimicrococcus
c_Unclassified
% of sequences
Adult
Elderly
0.01±0.01
0.02±0.02
0.28±0.05
0.27±0.27
0.28±0.05
0.27±0.27
0.28±0.05
0.27±0.27
99.71±0.04
99.71±0.27
26.11±8.19
55.82±7.87
26.11±8.19
55.82±7.87
26.11±8.19
55.82±7.87
0.06±0.09
0.00±0.00
25.07±8.15
54.54±8.44
0.84±0.23
1.07±0.32
0.15±0.13
0.20±0.29
59.19±16.91
37.00±9.98
59.19±16.91
37.00±9.98
47.54±10.81
31.43±9.83
47.54±10.81
31.43±9.83
11.66±7.89
5.58±2.27
0.87±0.66
2.39±2.49
0.04±0.04
0.03±0.02
0.04±0.04
0.03±0.02
0.04±0.04
0.03±0.02
0.83±0.64
2.36±2.51
0.83±0.64
2.36±2.51
0.83±0.64
2.36±2.51
13.53±9.43
4.50±1.40
P-value
0.272
0.932
0.932
0.932
0.991
0.007
0.007
0.007
0.384
0.007
0.363
0.731
0.041
0.041
0.131
0.131
0.452
0.373
0.554
0.582
0.582
0.362
0.362
0.362
0.171
1)
p, c, o, f, and g stands for phylum, class, order, family and genus, respectively.
Data are means±standard deviation, n=3. The same as below.
Table 2 Archaeal alpha diversity of adult and elderly yaks
Chao1
Adult
595.58±57.81
Elderly 517.73±77.50
P-value
0.242
Shannon-Wiener
5.49±0.11
4.56±0.80
0.084
E1
E2
E3
A1
A2
Observed_species
459.33±23.21
389.56±95.92
0.291
sured according to the OTU table. The weighted uniFrac
distances of the samples in the adult yak group and in the
elder group and between the 2 groups were 0.21±0.03,
0.18±0.03, and 0.32±0.05, respectively. The PERMANOVA
analysis of the resulting uniFrac distance matrix indicated
that there were significant differences in the archaeal communities between the two age groups (P=0.002). Based
on the weighted uniFrac distance, UPGMA was used for
the clustering analysis of the samples (Fig. 1). Fig. 1 illustrates that the samples cluster together according to their
age group.
3.5. Analysis of shared genera
A genus-level analysis of the composition and abundance
of core archaea shared by all of the 6 yaks was performed,
and 8 genera that were shared by all of the samples were
A3
0.05
Fig. 1 UPGMA tree (based on the weighted uniFrac distance
metric) showed the relationships among the individual yaks.
A1, 2, 3=adult yaks 1, 2, 3; E1, 2, 3=elderly yaks 1, 2, 3. The
same as below.
identified (Fig. 2). The genera that were shared by all of the
samples mainly belonged to the orders of Thermoplasmatales-affiliated Lineage C (TALC) and Methanobacteriales,
which all belonged to the Euryarchaeota phylum. The
shared genera Methanobrevibacter and Thermogymnomonas were the dominant archaea across all of the samples, and each accounted for an average of 39% of all the
rumen archaeal genera. While the other genera, such as
the Methanosphaera genus (Fig. 2), were shared by all of
the samples, they accounted for an average of less than
1% of all the rumen archaeal genera. Most of the shared
6
*** et al. Journal of Integrative Agriculture 2016, 15(0): 60345-7
Fig. 2 Heatmap with double hierarchical clustering of shared archaeal genera of all the yaks. The taxa that could not be assigned
a genus but were still present in all of the samples were displayed using the highest taxonomic level that could be assigned to
them, and the level is shown in parentheses.
genera varied in abundance across the samples.
4. Discussion
In the present study, 92 901 archaeal sequences were
generated in the rumen of 6 yaks and were clustered into
2 033 OTUs. Previous studies reported that only approximately 1 000 archaeal clones and 100 archaeal OTUs
were generated in a single trial in the gastrointestinal tract
of cattle (Shin et al. 2004; Pei et al. 2010), sheep (Tajima
et al. 2000; Wright et al. 2004), buffalo (Chaudhary et al.
2012; Singh et al. 2012), and yak (Huang et al. 2012). Our
experiment generated 20 times more data compared with
the previous studies. The obtained OTUs in the present
study were assigned to 3 archaeal phyla and to 8 genera
after the taxonomical classification. However, approximately
all of the archaea that were found in the previous studies
belonged to Euryarchaeota at the phylum level and could
only be classified into 4 or 5 genera in a single experiment.
Clearly, in the present study, a more complex archaeal
community was discovered in the rumen of yaks. The
discrepancy probably was attributed to the difference in
technologies used for analyzing the archaeal community. In
the present study, the high-throughput sequencing technique
(the Illumina MiSeq 300PE Sequencing platform) was used
to identify the archaea. While in the previous studies, the
methodology used was either a conventional microbiological method (Wolin et al. 1997) or a molecular fingerprinting
technique (Shin et al. 2004; Wright et al. 2004; Huang
et al. 2012). These previous technologies were costly,
time-consuming, and labor intensive in comparison with the
high-throughput sequencing, and they discovered only the
predominant microbes (Highlander et al. 2012). Kim et al.
(2011) indicated that at least 24 480 archaeal sequences
would be needed to reach a 99.9% coverage of archaea.
Furthermore, based on the rarefaction estimate, rumen may
contain more than 1 400 species-level OTUs. The developments in high-throughput sequencing, specifically targeted
gene sequencing, provide the means for in-depth analysis
of complex microbial ecosystems (Tringe and Hugenholtz
2008). Therefore, in comparison with the previous study in
yak (Huang et al. 2012), the present trial revealed a more
detailed archaeal profile in the rumen of yaks.
The previous studies indicated that Methanobrevibacter
was the predominant archaea at the genus level in the rumen
of ruminant animals (Whitford et al. 2001; Skillman et al.
2006; Nicholson et al. 2007; Ouwerkerk et al. 2008). Wright
et al. (2004) revealed 65 sequences of methanogens from
the rumen of sheep using the phylogenetic analysis, and 62
of them belonged to the Methanobrevibacter genus. In the
present study, the predominant archaeon in the rumen of
elderly yaks also was Methanobrevibacter. However, some
early experiments found that the predominant archaeon in
rumen was not Methanobrevibacter. Sundset et al. (2009)
found that 53% of the clones in the rumen of Svalbard
reindeer were associated with a cluster of uncultivated
*** et al. Journal of Integrative Agriculture 2016, 15(0): 60345-7
ruminal archaea. In the present study, the abundance of
Methanobrevibacter in adult yak was only 25%, and the
most abundant archaeon was the Thermogymnomonas
genus, which belonged to the TALC order. Additionally,
Huang et al. (2012) reported that the dominant archaea in
the rumen of yak were different from the other ruminants,
80.9% of methanogens belonged to the TALC order, and
only 14.9% belonged to the Methanobacteriales order. The
samples used by Huang et al. (2012) were harvested from
the yaks of approximately 4 years of age, which was a similar age to the adult yaks used in the present study. Their
results were in agreement with the present study though
different technologies were used. Thermogymnomonas was
an unusual archaea in the rumen and was reported to be
present in low abundance in cattle (Wright et al. 2007) and in
reindeer (Sundset et al. 2009). Furthermore, previous study
showed that Thermogymnomonas was usually found in rice
fields (Großkopf et al.1998; Chin et al. 1999) or in deep-sea
hydrothermal vents (Takai et al. 1999; Reysenbach et al.
2000). The reason for its high abundance (47.54% in adult
yaks vs. 37.43% in elderly yaks) in the rumen of yaks was
unknown, though, it may be related to thousands of years
of domestication in the high altitude region. Poulsen et al.
(2013) reported that the methane emission was significantly
mitigated by the reduction in the abundance of Thermoplasmatales in the bovine rumen (Thermogymnomonas is
the dominant component of the TALC order). Therefore,
Thermogymnomonas is an important target for developing
future strategies to mitigate methane emissions from yaks.
In the present study, compared with the adult yaks, the
elderly yaks had a significantly higher abundance of Methanobrevibacter, and a marginally lower abundance of Thermogymnomonas as well as a lower alpha diversity index.
These results indicated that adult yaks might have a different
ruminal archaeal community than elder yaks. To date, there
have been no publications concerning the impact of age
on the development feature of ruminal archaea. However,
some previous studies indicated that age could affect the
diversity of bacteria in gastrointestinal tract. For example,
Jami et al. (2013) evaluated the bovine rumen bacterial
community from birth to adulthood. They suggested that
each sampled age group had its own distinct microbiota.
Tun et al. (2014) compared microbial communities from
fecal samples taken from geriatric and adult captive giant
pandas and revealed that some bacteria that were found
in adult giant pandas were absent in geriatric giant pandas.
Therefore, the gastrointestinal microorganisms, including
archaea, probably would undergo developmental changes
during different growth stages. In the present study, the difference in archaeal communities between adult and elderly
yaks could have been caused by the difference of the feed
intake. Although all yaks grazed in a single grassland sward,
7
the elder yaks might have a slightly lower feed intake per
kg of live weight than the adult yaks because elder animals
may have a lower metabolic rate (Agnew and Yan 2000).
Further work is needed to verify this assumption.
Huang et al. (2012) found that yak had higher methanogen diversity, and the methanogen community was significantly different compared with cattle. Meanwhile, they found
that yak had higher levels of acetate, proprionate, isobutyric,
isovaleric, and total volatile fatty acids in the rumen compared with cattle. Some of these fermentation products are
the main substrates for methane formation. The archaeal
structure and composition in the rumen may affect rumen
fermentation and finally result in a lower methane emission
(Ding et al. 2010). In the current study, significant differences in archaeal community between elderly and adult yaks
were observed. However, further investigation is required to
determine whether these differences lead to the discrepancy
in the rumen fermentation products and methane emission
and what the relationship is between the archaeal community and the fermentation pattern.
In present study, although the average abundance of
Thermogymnomonas of elderly yaks was 34% lower than
that of adult yaks, the difference between the two age
groups was not statistically significant. This could have
resulted from the relatively small number of replicates (3
animals per group). Due to the small number of replicates,
the standard deviations of some archaea, especially those
with a low abundance, were close to or even greater than
the corresponding means in the current study. This phenomenon had repeatedly appeared in previous studies on the
diversity of rumen microorganisms using the high-throughput
sequencing technology (Jami et al. 2013; Tun et al. 2014;
Guo et al. 2015). Due to the small number of samples, the
present study took the risk in assuming that some of the
archaea that were significantly different between the elderly
and adult yaks were omitted during the process of statistical
tests. However, this did not affect the general conclusions
of this study.
5. Conclusion
The present study revealed that elder yaks had a significantly higher abundance of ruminal Methanobrevibacter and a
lower abundance of Thermogymnomon compared with adult
yaks. This result indicates that the aging process influences
the archaeal diversity in the gastrointestinal tract of yaks.
Acknowledgements
We would like to thank the International Cooperation Project of the Ministry of Sciences and Technology of China
(2014DFA32860) and National Natural Science Foundation
8
*** et al. Journal of Integrative Agriculture 2016, 15(0): 60345-7
of China (31402104) for their financial support.
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(Managing editor ZHANG Juan)