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Running title: Ruminal epithelial bacterial colonization 1
2
Taxonomic identification of the ruminal epithelial bacterial diversity during rumen development 3
in goats 4
5
Jinzhen Jiao1,2, Jinyu Huang1,2, Chuanshe Zhou1 and Zhiliang Tan1,# 6
7
1Key Laboratory for Agro-Ecological Processes in Subtropical Region, and South-Central 8
Experimental Station of Animal Nutrition and Feed Science in Ministry of Agriculture, Institute 9
of Subtropical Agriculture, The Chinese Academy of Sciences, Changsha, Hunan 410125, P.R. 10
China; 11
2Graduate University of Chinese Academy of Sciences, Beijing 100049, P. R. China; 12
#Corresponding author: Zhiliang Tan. Address: Institute of Subtropical Agriculture, the Chinese 13
Academy of Sciences, Changsha, Hunan 410125, P. R. China. E-mail: zltan@isa.ac.cn; Tel: +86 14
731 4615230; Fax: +86 731 4612685 15
16
Key words: epithelial bacteria, rumen, microbial colonization, diversity. 17
18
AEM Accepted Manuscript Posted Online 13 March 2015Appl. Environ. Microbiol. doi:10.1128/AEM.00203-15Copyright © 2015, American Society for Microbiology. All Rights Reserved.
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Abstract 19
20
Understanding of the colonization process of epithelial bacteria attached to the rumen tissue 21
during rumen development is very limited. Ruminal epithelial bacterial colonization is of great 22
significance to explore the relationship between the microbiota and the host, as well as can 23
influence host early development and health. Miseq sequencing of 16S rRNA genes and 24
quantitative real-time PCR (qPCR) were applied to characterize ruminal epithelial bacterial 25
diversity during rumen development in this study. Seventeen kid goats were selected to reflect 26
the non-rumination (0 and 7 d), transition (28 and 42 d) and rumination (70 d) phases of animal 27
development. Alpha diversity indices (OTU numbers, Chao and Shannon index) increased (P < 28
0.01) with age, and PCoA analysis revealed that the samples clustered together according to their 29
particular age groups. Phylogenetic analysis revealed that Proteobacteria, Firmicutes and 30
Bacteroidetes were detected as the dominant phyla regardless of the age group, whilst 31
Proteobacteria abundance declined quadratically with age (P < 0.001), while Bacteroidetes (P = 32
0.088) and Firmicutes (P = 0.009) increased with age. At the genus level, Escherichia (80.79%) 33
dominated at 0 d, while Prevotella, Butyrivibrio and Campylobacter surged (linearly, P < 0.01) 34
in abundance at 42 and 70 d. qPCR showed that total epithelial bacteria copy number linearly 35
increased (P = 0.013) with age. In addition, the abundances of genera Butyrivibrio, 36
Campylobacter, Desulfobulbus were positively correlated with rumen weight, rumen papilla 37
length, ruminal ammonia and total volatile fatty acid concentrations, and activities of 38
carboxymethylcellulase (CMCase) and xylanase, respectively. Collectively, colonization of 39
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ruminal epithelial bacteria is age-related (achieved at 2 months), as well as they might participate 40
in the anatomic and functional development of the rumen. 41
42
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Introduction 44
45
The recent years have witnessed growing interest in the diversity and function of ruminal 46
epithelial bacteria. It has been demonstrated that ruminal epithelial bacteria are involved in 47
oxygen scavenging, tissue recycling and urea digestion (1). Furthermore, in steers, ruminal 48
epithelial bacterial community is different between acidosis-resistant and acidosis-susceptible 49
groups during subacute ruminal acidosis development, and such difference can be recognized by 50
the host TLRs (Toll like receptors) which are associated with the variation of the rumen epithelial 51
tissue barrier function (2). Similarly, in mice colon, epithelial bacterial diversity correlated with 52
TLR2 and TLR4 gene expressions (3). These reveal that as epithelial bacteria are directly 53
attached to the epithelial surface, their end products may directly or indirectly play a role in host 54
immune responses and tissue barrier function. 55
56
The ruminal epithelial bacteria are distinctly different at taxonomic level from those associated 57
with rumen contents (4, 5). Using culture-based techniques, the ruminal epithelial communities 58
have been found to comprise predominantly Gram-positive, facultatively anaerobic flora, with 59
Butyrivibrio sp. (31.1%), Bacteroides sp. (22.4%), Selenomonas ruminantium (9.9%), 60
Succinivibrio dextrinosolvens (8.7%) and Streptococcus bovis (8.1%) predominant (6). Through 61
pyrosequencing, ruminal epithelial bacteria at the class level were mainly composed of 62
Clostridia (67%), Bacteroidia (9%), Deltaproteobacteria (4%) and Erysipelotrichia (3%) (7). 63
64
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Diet is an indispensable determinant influencing the structure and function of microbial diversity 65
both in rumen content and tissue-attached. In the rumen contents of dairy cows, deep amplicon 66
sequencing of the 16S rRNA gene revealed higher abundance of the Fibrobacteraceae family in 67
total mixed ration samples while lower members of the propionate-producing Veillonelaceae 68
compared with pasture samples (8). Moreover, based on the sequence information from the 69
reference marker of PCR-DGGE, the phyla Firmicutes and Proteobacteria abundances in heifer 70
ruminal epithelial bacterial community decreased in response to the rapid dietary transition from 71
a diet containing 97% hay to a diet containing 8% hay (9). 72
73
The bacterial colonization process in the developing rumen is of interest to understand the 74
achievement of rumen functions. It can influence the early development and productive 75
efficiency of the mature animal (10). In cow rumen contents, the bacterial composition 76
underwent dynamic changes during the first two years, with the Proteobacteria phylum 77
decreased with age while Bacteroidetes and Firmicutes increased with age (11). Our earlier study 78
showed that during the three typical phases of rumen development process (non-rumination, 0 to 79
3 weeks; transition, 3 to 8 week; rumination period, from 8 week on) in goats, microbial 80
colonization in the rumen content is achieved at 1 month, functional achievement at 2 months, 81
and anatomic development after 2 months (12). Nonetheless, research into the age-related 82
dynamic colonization of ruminal epithelial bacterial populations is very limited. Therefore, we 83
aimed to characterize the sequential dynamics of ruminal epithelial bacterial colonization and to 84
explore its relationship with previously published rumen anatomic and functional parameters. 85
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Materials and Methods 87
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Sample collection 89
90
This is a companion study conducted using samples collected from selected 17 supplemental 91
feeding kid goats (offered kids with some concentrate to the forage after 20 d of birth) used in 92
our previous study (12). The use of animals, including welfare, husbandry, experimental 93
procedures, and the collection of rumen samples used for this study, was approved by the Animal 94
Care Committee, Institute of Subtropical Agriculture, the Chinese Academy of Sciences, 95
Changsha, China. Post-birth, the kid goat was immediately placed in an individual pen to avoid 96
direct contact with other adult animals and other kids. The kids were then maintained within an 97
individual pen for the duration of the study. From 0 to 20 d, the kids were twice offered with goat 98
milk (1 L per meal) at 08.00 and 17.00 h. Between 20 and 40 d, feeds were provided individually 99
twice daily, at 08.00 and 17.00 h, at each meal the kids received a bucket of goat milk (0.5 L), 100
and a separate bucket containing a mixture of forage (fresh grass; 0.04 kg DM/meal) and 101
concentrate starter (0.12 kg DM/meal). The kids were weaned at 40 d, and from there until 70 d, 102
they were fed with concentrate starter (0.17 kg DM/meal)) and forage (0.06 kg DM/meal). The 103
concentrate starter (kg−1 DM basis) was composed of 74.1 g whey powder, 211 g corn flour, 320 104
g bean meal, 65 g fish meal, 220 g fat powder, 51 g milk powder, 8.6 g CaCO3, 25.3 g CaHPO4, 105
5 g NaCl and 20 g premix. The concentrate starter and forage were offered ad libitum. Four kids 106
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were slaughtered at 0 and 42 d, and three kids were slaughtered at 7, 28 and 70 d. Immediately 107
after the kids were slaughtered, the rumen tissue were scraped to remove attached feed particles 108
and rinsed three times with sterile phosphate buffered saline (pH = 7.4) to remove non-adherent 109
bacteria. The samples were then transferred into RNA-later solution (Invitrogen, Carlsbad, CA) 110
and stored at -20°C until further molecular analysis. 111
112
DNA extraction and amplicon preparation for high-throughput sequencing 113
114
Total DNA was extracted from the 17 rumen mucosal tissue samples using the bead beating 115
method as suggested by Chen, et al. (9). The quality and quantity of DNA were measured using a 116
NanoDrop ND1000 (NanoDrop Technologies Inc., DE, USA). Total DNA of rumen tissue was 117
then diluted to 50 ng/μl and used in amplicon preparation for high-throughput sequencing. 118
Conventional PCR was performed to amplify the V2 and V3 region of 16S rRNA gene using 119
universal primer 104F (5'-NNNNNN GGCGVACGGGTGAGTAA-3') and 530R 120
(5'-CCGCNGCNGCTGGCAC-3') (13), with the forward primer 104F contained 6 base barcode 121
sequence (italicized poly-N section of primer above) at the 5’ terminus. All 104F primer barcodes 122
used are presented in Table S1. PCR reactions (50 ul) contained 30 ng DNA template, 5μl of 10 × 123
Pfx Amplification Buffer, 2μl of 10 mM dNTP mixture, 2μl of 50 mM MgSO4, 1μl of Platinum® 124
Pfx DNA Polymerase, 0.25 μl of bovine serum albumin (20 mg/mL) and 2μl of each primer (10 125
uM) (Invitrogen, Life Sciences, USA). Reaction conditions consisted of an initial 95oC for 3 min, 126
followed by 35 cycles of 95oC for 30 s, 58oC for 30 s, and 72oC for 45 s, and a final extension of 127
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72oC for 10 min. PCR products were excised from a 1.5% agarose gel and purified using 128
Wizard® SV Gel and PCR Clean-Up System (Promega, Madison, USA). Barcoded V2–V3 129
amplicons were mixed at equal molar rations, submitted to Illumina paired-end library 130
preparation, cluster generation, and 300 bp pair-end sequencing on an Illumina MiSeq PE300 131
instrument. 132
133
Data analysis 134
135
Raw data were filtered through a quality control pipeline using Quantitative Insight into 136
Microbial Ecology (QIIME) tool kit (14) and mothur (15). Specifically, the 300-bp reads were 137
truncated at any site of more than three sequential bases receiving a quality score < Q20, and any 138
read containing ambiguous base calls or barcode/primer errors were discarded, as were reads 139
with < 80% (of total read length) consecutive high-quality base calls. Sequences were 140
deconvoluted into individual samples based on their barcodes. For pair-end reads, only sequences 141
that overlap longer than > 10% and with < 10 % mismatch were assembled according to their 142
overlap sequence using Connecting Overlapped Pair-End (COPE) (16). The assembled 143
sequences were then trimmed of primers, assigned to operational taxonomic units (OTUs) at 144
97% identity threshold using UPASE (17). Chimeric sequences were identified and removed 145
using UCHIME (18). Taxonomy classification was assigned against the latest Greengenes 146
database (Greengenes May 2013 release) (19) using the mothur-based implementation of the 147
RDP Bayesian classifier with a 0.80 confidence threshold. Sequence alignment was performed 148
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by PyNAST and phylogenetic tree was constructed using FastTree (20). The taxonomic 149
identification and comparisons were performed at the phylum and genus level. 150
151
Alpha diversity of ruminal epithelial bacterial communities of kids at different ages (0, 7, 28, 42 152
and 70 d) was obtained using various diversity indices (observed species, Chao1, ACE, Shannon 153
and Simpson index) using the alpha rarefaction pipeline at a sequence depth of 27,000 as the 154
nearest number to the minimum number of all 17 sequences (27,120). PCoA and hierarchical 155
clustering of microbial communities (Jackkinfied beta diversity of 100 times resampling at a 156
depth of 20250 sequences) was performed using Bray Curtis distance. The clustering method of 157
hierarchical clustering was unweighted pair group method with arithmetic mean (UPGMA). 158
Within-group similarity was calculated as the average of the pairwise similarity between each 159
paired sample within each group using the Bray-Curtis metric. Sequencing data in this study 160
were deposited in the MG-RAST server under IDs 4613702.3 to 4613735.3. And they were also 161
deposited in the NCBI sequence read archive (SRA) under the accession numbers SRR1823055, 162
SRR1823127, SRR1823131, SRR1823138, SRR1823141, SRR1830869, SRR1830870 and 163
SRR1830872- SRR1830881. 164
165
A transformation-based principal components analysis (tb-PCA) (21) using the Hellinger 166
distance was used to ordinate the 17 samples according to OTU abundance data. Only the top 10 167
OTUs for which variation of abundance contributed most to the clustering obtained from the 168
tb-PCA were selected and represented in the tb-PCA. The OTUs were identified using the largest 169
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contributors, to the first two principal components as selection criteria. 170
171
Quantification of total bacteria and selected bacterial genera 172
173
Absolute quantitative real-time PCR was performed to quantify copy numbers of 16S rRNA 174
genes of total bacteria and two selected bacterial genera (Prevotella and Bacteroides). The 175
previous validated primers (22-24) are listed in Table S2. The qPCR was performed using 176
SYBR® Premix Ex Taq™ (Perfect Real Time) (Takara, Japan) on an ABI 7900HT Fast Real 177
Time PCR system (Applied Biosystems, Foster City, CA, USA). The standard curves for total 178
bacteria and each bacterial genus were prepared using plasmid DNA containing each unique 16S 179
rRNA insert. The copy numbers of 16S rRNA gene/g of fresh tissue were calculated as described 180
by Zhou, et al. (25). The relative abundance of bacterial genera was calculated by dividing the 181
16S rRNA gene copy number of each genus by the 16S rRNA gene copy number of total 182
bacteria. 183
184
Statistical analysis 185
186
For data of apparent relative abundance of communities at the phylum and genus level, alpha 187
diversity indices (Miseq sequencing) as well as qPCR results of total ruminal epithelial bacteria 188
and abundant bacterial genera, they were analyzed as a completely randomized design with the 189
MIXED procedures of SAS (SAS Inst. Inc., Cary, NC). The model included the fixed effect of 190
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age and the random effect of animal within age, with individual animal as the experiment unit. 191
Orthogonal contrasts were used to test for linear and quadratic effects of age. Statistical 192
significance was accepted at P < 0.05 and a trend was considered at P < 0.10. All presented data 193
are expressed as least-squares means. 194
195
Spearman’s rank correlations between ruminal bacterial community (MiSeq relative abundance) 196
and anatomic, functional variables were analyzed using the PROC CORR procedure of SAS. 197
Only bacterial groups that represented > 2% of the total community in at least one sample and 198
that were detected in > 50% of the rumen tissue samples were included in the analysis. 199
200
Results 201
202
Sampling depth, coverage and alpha diversity 203
204
After data filtering, quality control, pair-end reads assembling, primer, chimera, and low 205
confidence singleton removal, a total of 1,064,895 of V2-V3 16S rRNA sequences reads from the 206
17 samples with an average of 62,641 sequences reads for each sample (the minimum value of 207
one sample was 27,120 and the maximum was 130,437) were used in this project. The average 208
length of sequences reads after primer removal was 383bp. The overall number of OTUs 209
detected by the analysis reached 2409 based on 97% nucleotide sequence identity between reads. 210
211
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With subsample of 27,000 reads every sample, the rarefaction curves (Fig.S1) showed that most 212
of our sampling effort provided sufficient OTU coverage to accurately describe the bacterial 213
composition of each group. Alpha diversity measures (Table 1) indicated that age unaffected (P > 214
0.05) coverage and had an increasing trend (P = 0.058) on Ace index. Moreover, number of 215
OTUs, Chao and Shannon index increased linearly with age (P < 0.05) while Simpson index 216
declined linearly (P = 0.001) with age. 217
218
Taxonomic composition of ruminal epithelial bacterial composition across different age groups 219
220
In total, twenty-six phyla were identified within the ruminal epithelial microbiota. The 221
abundance of 15 phyla in all the samples was < 0.5% and they were Acidobacteria, 222
Cyanobacteria, Elusimicrobia, Gemmatimonadetes, Lentisphaerae, NC10, Nitrospirae, OD1, 223
OP11, Planctomycetes, Spirochaetes, Synergistetes, TM6, Tenericutes and Verrucomicrobia. 224
Among the 26 phyla, the Proteobacteria, Firmicutes and Bacteroidetes were detected as the 225
dominant phyla regardless of the age group (Table 2), but their ratio and composition among the 226
groups varied considerately. The phylum Proteobacteria was the most abundant phylum in 227
samples from 0 and 7 d, reaching as high as more than 85%. Afterwards, it declined quadratically 228
(P < 0.001) with age. The Bacteroidetes phylum exhibited low values during the first week (< 229
5%), and increased significantly afterwards (approximately 10%). The Firmicutes increased 230
quadratically (P = 0.009) with age, becoming dominant at 42 and 70 d (54.71% and 40.29%, 231
respectively). The Actinobacteria (P = 0.096) and TM7 tended to increase linearly (P = 0.067) 232
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with age while age had quadratic effects on Chloroflexi (P = 0.014) and Thermi (P = 0.051) 233
abundance. Furthermore, the Fibrobacteres and Fusobacteria peaked at 0.49% relative 234
abundance at 42 d and 1.18% at 0 d, respectively. 235
236
Of the 26 genera observed with over 0.5% of relative abundance, fifteen changed significantly 237
over age (Table 3), others remained relatively stable. Moreover, a great proportion of sequences 238
(ranging from 13.38% to 82.99%) remained unclassified at the genus level. Within the 239
Bacteroidetes phylum, the genus Bacteroides peaked at 2.46% (7 d), Porphyromonas decreased 240
linearly (P = 0.011) with age, while Prevotella increased linearly (P = 0.022) with age. In the 241
Firmicutes phylum, Butyrivibrio genus exhibited low values during the first week (< 1%), 242
becoming the most dominant afterwards, peaked at 42.38% relative abundance at 42 d. 243
Mogibacterium increased linearly (P = 0.003) with age, p-75-a5 tended to increase quadratically 244
(P = 0.077) with age. In contrast, the relative proportions of Oscillospira and Streptococcus 245
declined with age. In the Proteobacteria phylum, genus Escherichia was very dominant at 0 d 246
(80.79%), decreased quadratically (P < 0.001) with age, and reached stable values (about 1%) 247
after 28 d. On the contrary, Campylobacter was very minor during the first week (< 1%), surged 248
in proportion afterwards, and peaked at 29.99% at 70 d. Age had decreasing effects on genera 249
Arcobacter (linearly, P = 0.038) and Enterobacter (linearly, P = 0.077), while conversely had 250
effects on Desulfobulbus (linearly, P = 0.033) and Paracoccus (quadratically, P = 0.075). Of 251
other minor genera did not belong to these three phyla, Actinomyces, SHD-231, Fibrobacter, 252
Fusobacterium and Thermus peaked at 0.21% (70 d), 0.80% (28 d), 0.49% (42 d), 1.18% (0 d) 253
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and 1.31% (42 d), respectively. 254
255
OTU diversity and similarity analysis 256
257
To minimize the variation created by different sample depth, Jackkinfied subsampling (100 times 258
resampling at a depth of 20250 sequences) was used in our study before performing beta 259
diversity analysis. PCoA analysis using Bray-Curtis similarity metric revealed that the samples 260
clustered together according to their particular age group (Fig.1). The average within-group 261
similarity showed a significant difference between different age groups, with their values at 28, 262
42 and 70 d exceeded those at 0 and 7 d (Fig. 2). 263
264
Ten dominant OTUs were identified that contributed to the separation of ruminal bacterial 265
community at five different ages (Fig. 3). The two dominant OTUs that separated samples at 0 d 266
from others were identified as Escherichia spp. Two OTUs Neisseriaceae and Ruminococcaceae 267
family separated samples at 7 d from others. Likewise, for the separation of 28 d, one OTU was 268
identified (Ruminococcus spp.). The four OTUs contributing to the separation of 42 d and 70 d 269
from others displayed high identity to Butyrivibro spp. and Campylobacter spp. 270
271
Quantification of total ruminal epithelial bacteria and abundant bacterial genera 272
273
As illustrated by qPCR, total ruminal epithelial bacterial copy numbers (P = 0.013) and genus 274
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Prevotella abundance increased linearly (P = 0.049) with age (Table 4). Age did not affect (P > 275
0.05) genus Bacteroides abundance. 276
277
Relationship between bacterial community, anatomic and functional variables 278
279
Bacterial community at the genus level and anatomic, functional variables were regarded as 280
correlated with each other if their correlation coefficients were above 0.55. The relative 281
abundances of genera Bacteroides, Escherichia and Fusobacterium were negatively correlated 282
with live weight and rumen weight, while the relative abundances of Butyrivibrio, 283
Campylobacter, Desulfobulbus, Prevotella and Ruminococcus were positively correlated with 284
live weight and rumen weight (Fig. 4). Rumen papilla length was positively correlated with the 285
relative abundances of Butyrivibrio, Campylobacter, Desulfobulbus and Ruminococcus while 286
negatively correlated with the relative abundances of Escherichia and Fusobacterium. Ammonia 287
concentration was positively correlated with total bacteria copy number, Butyrivibrio, 288
Campylobacter and Ruminococcus abundances, while negatively correlated with Escherichia and 289
Fusobacterium. Total VFA concentration was positively correlated with Butyrivibrio, 290
Campylobacter, Desulfobulbus abundances while negatively correlated with Bacteroides, 291
Escherichia and Fusobacterium abundances. Furthermore, xylanase activity was positively 292
correlated with Butyrivibrio, Campylobacter and Desulfobulbus abundances, while negatively 293
correlated with Acinetobacter, Bacteroides, Escherichia, Fusobacterium and Thermus 294
abundances. CMCase activity was positively correlated with Desulfobulbus abundance, while 295
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negatively correlated with Acinetobacter, Bacteroides, Escherichia, Fusobacterium and Thermus 296
abundances. Amylase activity was negatively correlated with Butyrivibrio abundance. 297
298
Discussion 299
300
Relationships between gastrointestinal microbial communities and their hosts have been shown 301
in recent years to have an important role in host’s well-being and proper function. The objective 302
of this study was to evaluate how bacteria colonized within the rumen epithelium during normal 303
development. Using Miseq sequencing, we obtained 62,641 reads on average for each sample 304
(the least one at 27,120 reads) with good coverage (> 99.6%). Furthermore, our results suggest 305
that each age group has its own distinct epithelial microbiota, as reflected by clustering of 306
samples by age group using PCoA and tb-PCA. Meanwhile, most of the alpha diversity indices 307
(except ACE and Simpson) increased with age, suggesting that microbiota in older age group is 308
more diverse than those in the earlier age group. This is similar to the microbial colonization 309
process in the rumen contents (11, 26). 310
311
Individual variation is an indispensable determinant affecting microbiota taxa. Although the 312
experimental conditions, diet and sampling procedures were similar between bovine rumen 313
samples, a large fraction of the OTUs (50%) occurred in only a small number of samples (0 to 314
30%), implying bacterial taxa varied considerably between individual bovine rumen contents 315
(27). Similarly, within-group similarity in rumen epithelial bacterial community in our study 316
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during the first week is quite low (around 0.2). Despite this, we observed a drastic increase in 317
within-group similarity with age. This suggests that the rumen epithelium in older groups is a 318
more restricted environment, housing a more homogeneous bacterial community compared to the 319
earlier heterogeneous community. 320
321
Host genetics is another factor affecting gastrointestinal microbial adaption and evolution (28). 322
In new born calves, bacterial community of fecal content samples from twin calves revealed 323
higher similarity in PCR single strand conformation polymorphism (PCR-SSCP) profiles for 324
twins compared to their co-residents of the same age, indicating that the individual microbial 325
diversity might be genetically influenced (29). In our study, effects of age on rumen epithelial 326
bacterial diversity were compared using different groups of kids, which also accounted for the 327
variation. Moreover, total epithelial bacterial populations for alfalfa hay and oats-fed dairy calves 328
(30), hay-fed sheep(31), concentrate and fresh grass-fed kid goats (this study) ranged from 4.4 × 329
109 to 4.2 × 1010, 4.4 × 107 to 2.2 × 108, 1.4 × 108 to 4.4 × 107 per g of wet tissue, respectively. 330
Besides the variation in model animal, diet, DNA extraction method, PCR primers and 331
conditions, the host might also be an important determinant in regulating bacterial density. 332
333
In all age groups, Firmicutes, Bacteroidetes and Proteobacteria were the dominant phyla in the 334
epithelial microbiota, with their abundance and genus composition varied remarkably, in line 335
with other previous studies(7, 32). Similarly, at the genus level, although the abundance of some 336
genera changed with age, however, they were present in all groups, representing a core 337
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microbiome in the ruminal epithelial microbiota of goats. When compared to those in the rumen 338
contents (11), after 20 d, the current study showed the epithelial microbiota harbored more 339
genera Butyrivibrio and Campylobacter, indicating these two genera might be unique abundant 340
epithelial bacteria. 341
342
The ruminal epithelial bacterial composition of kid goats undergoes sequential changes during 343
rumen development process. On the day born, Proteobacteria (90.13%) phylum far exceeded 344
other phylum, with the majority belonging to the genus Escherichia. These microbiota might 345
derive from the microbiota of mother’s vagina(33), skin, colostrum(34) and environment. This 346
genus is a facultative anaerobic bacteria, with some commensal strains of E. coli can reduce 347
intestinal epithelial inflammatory signaling in vitro (35), while some pathogenic strains of E.coli 348
can invade host cells (36). As reflected by tb-PCA, two dominant OTUs that separated samples 349
at 0 d from others also displayed high identity to this genus. These facultative anaerobes could 350
create the reduced-environment that is required for anaerobic microbes (37). Further work would 351
be needed to ascertain the rumen functions of this genus. Moreover, this genus declined 352
considerately in abundance at 7 d, and a great many genera belonged to unclassified 353
Proteobacteria. The remarkable changes observed in ruminal epithelial bacterial communities 354
during the first week after birth indicated a rapid change in the rumen environment. 355
356
A noticeable change occurring at 28 d after solid food offered (20 d) was the increase in ruminal 357
epithelial bacterial density, and this was reflected by qPCR (almost three times in copy numbers). 358
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Similar observations have been reported in rumen and gut contents (37). Moreover, similar to the 359
compositional changes in rumen contents (11), in rumen tissues, genus Bacteriodes declined in 360
abundance while genera Prevotella, Butyrivibrio, Campylobacter and Succinivibrio surged in 361
proportion. Collectively, solid food caused disruption in ruminal epithelial microbiota by 362
selecting bacterial taxa that were more specific and adapted to new substrates. The genus 363
Prevotella, numerically predominant ruminants, are capable of utilizing starches, other 364
noncellulosic polysaccharides, and simple sugars as energy sources (24). Butyrivibrio group 365
(including the genera Butyrivibrio and Pseudobutyrivibrio) represented 12.98% of total bacteria 366
the rumen of goats (38) and were involved in the biohydrogenation of unsaturated C18 fatty acid 367
(39). Although some species of Campylobacter such as Campylobacter concisus and other 368
non–Campylobacter jejuni Campylobacter species have been implicated in the initiation of 369
gastrointestinal diseases (40), they represent persistent residents of rumen microbial communities 370
(10). Some species of genus Succinivibrio could ferment maltose and glucose, thus participating 371
in the last stage of starch digestion (41). From 28 to 70 d, the abundance of genera Prevotella, 372
Butyrivibrio and Campylobacter still increased with age, implying they were dominant genera in 373
ruminal epithelial microbiota after solid feed provision. However, what role these genera played 374
and how they interacted with the host have not been exploited and remain to be elucidated. 375
376
Based on the already published data on rumen functional variables in the same kid goats, we 377
explored the relationship between ruminal epithelial microbiota and rumen functions. The 378
abundance of genera Butyrivibrio, Campylobacter, Desulfobulbus and Ruminococcus were 379
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positively correlated with rumen weight, rumen papilla length, ammonia concentration and total 380
volatile fatty acid concentration, suggesting they might be involved in ammonia and volatile fatty 381
acid metabolism as well as anatomic development of the rumen. Similarly, genera Butyrivibrio, 382
Campylobacter, Desulfobulbus might also participate in fibrolytic enzyme secretion and genus 383
Fusobacterium is related to starch degradation. Furthermore, specific commensal microbes have 384
been reported to modulate host immune responses via pro-inflammatory and anti-inflammatory 385
pathways, as well as epithelial cell mediated signals (42, 43). Therefore, further investigation is 386
warranted to better explain the symbiotic relationship between ruminal epithelial microbiota and 387
its host. 388
389
Conclusion 390
391
In conclusion, ruminal epithelial bacterial communities were more diverse in the older groups 392
than those in the earlier groups and each age group had its distinct microbiota. Of the three 393
dominant phyla, Proteobacteria declined with age while Bacteroidetes and Firmicutes increased 394
with age. Genus Escherichia dominated at the day born, while Prevotella, Butyrivibrio and 395
Campylobacter surged in abundance at around two months. Furthermore, the correlations 396
between particular genus of the ruminal epithelial bacteria and anatomic, functional variables 397
might indicate a variety of different types of relationships with the host. This study provides 398
some preliminary information of the potential role of the ruminal epithelial bacteria, and further 399
investigations are required to determine their actual roles and interactions with the host. 400
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401
Acknowledgements 402
403
We acknowledge the financial support received from the National Natural Science Foundation of 404
China (Grant No. 31320103917), "Strategic Priority Research Program - Climate Change: 405
Carbon Budget and Relevant Issues" (Grant No. XDA05020700), “CAS Visiting Professorship 406
for Senior International Scientists (Grant No. 2010T2S13, 2012T1S0009), and Hunan Provincial 407
Creation Development Project (2013TF3006). 408
409
410
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411
References 412
413
1. Cheng K. J., R. P. Mccowan and J. W. Costerton. 1979. Adherent epithelial bacteria in ruminants 414
and their roles in digestive-tract function. Am J Clin Nutr. 32: 139-148. 415
2. Chen Y. H., M. Oba and L. L. Guan. 2012. Variation of bacterial communities and expression of 416
Toll-like receptor genes in the rumen of steers differing in susceptibility to subacute ruminal acidosis. 417
Vet. Microbiol. 159: 451-459. 418
3. Wang Y., S. Devkota, M. W. Musch, B. Jabri, C. Nagler, D. A. Antonopoulos, A. Chervonsky 419
and E. B. Chang. 2010. Regional mucosa-associated microbiota determine physiological expression 420
of TLR2 and TLR4 in murine colon. PloS one. 5: e13607. 421
4. Pei C. X., S. Y. Mao, Y. F. Cheng and W. Y. Zhu. 2010. Diversity, abundance and novel 16S rRNA 422
gene sequences of methanogens in rumen liquid, solid and epithelium fractions of Jinnan cattle. 423
Animal. 4: 20-29. 424
5. Cho S. J., K. M. Cho, E. C. Shin, W. J. Lim, S. Y. Hong, B. R. Choi, J. M. Kang, S. M. Lee, Y. H. 425
Kim, H. Kim and H. D. Yun. 2006. 16S rDNA analysis of bacterial diversity in three fractions of 426
cow rumen. J. Microbiol. Biotechnol. 16: 92-101. 427
6. Mead L. J. and G. A. Jones. 1981. Isolation and presumptive identification of adherent epithelial 428
bacteria ("epimural" bacteria) from the ovine rumen wall. Appl Environ Microbiol. 41: 1020-1028. 429
7. Petri R. M., T. Schwaiger, G. B. Penner, K. A. Beauchemin, R. J. Forster, J. J. McKinnon and T. 430
A. McAllister. 2013. Changes in the rumen epimural bacterial diversity of beef cattle as affected by 431
diet and induced ruminal acidosis. Appl. Environ. Microbiol. 79: 3744-3755. 432
8. de Menezes A. B., E. Lewis, M. O'Donovan, B. F. O'Neill, N. Clipson and E. M. Doyle. 2011. 433
Microbiome analysis of dairy cows fed pasture or total mixed ration diets. FEMS Microbiol. Ecol. 78: 434
256-265. 435
9. Chen Y., G. B. Penner, M. Li and M. Oba. 2011. Changes in bacterial diversity associated with 436
on June 29, 2018 by guesthttp://aem
.asm.org/
Dow
nloaded from
23
epithelial tissue in the beef cow rumen during the transition to a high-grain diet. Appl. Environ. 437
Microbiol. 77: 5770-5781. 438
10. Li R. W., E. E. Connor, C. Li, R. L. Baldwin and M. E. Sparks. 2012. Characterization of the 439
rumen microbiota of pre-ruminant calves using metagenomic tools. Environ Microbiol. 14: 129-139. 440
11. Jami E., A. Israel, A. Kotser and I. Mizrahi. 2013. Exploring the bovine rumen bacterial 441
community from birth to adulthood. Isme J. 7: 1069-1079. 442
12. Jiao J., X. Li, K. A. Beauchemin, Z. Tan, S. Tang and C. Zhou. 2015. Rumen development 443
process in goats as affected by supplemental feeding versus grazing: age-related anatomic 444
development, functional achievement and microbial colonization. Brit J Nutr.Accepted. 445
13. Hristov A. N., T. R. Callaway, C. Lee and S. E. Dowd. 2012. Rumen bacterial, archaeal, and fungal 446
diversity of dairy cows in response to ingestion of lauric or myristic acid. J Anim Sci. 90: 4449-4457. 447
14. Caporaso J. G., J. Kuczynski, J. Stombaugh, K. Bittinger, F. D. Bushman, E. K. Costello, N. 448
Fierer, A. G. Pena, J. K. Goodrich, J. I. Gordon, G. A. Huttley, S. T. Kelley, D. Knights, J. E. 449
Koenig, R. E. Ley, C. A. Lozupone, D. McDonald, B. D. Muegge, M. Pirrung, J. Reeder, J. R. 450
Sevinsky, P. J. Turnbaugh, W. A. Walters, J. Widmann, T. Yatsunenko, J. Zaneveld and R. 451
Knight. 2010. QIIME allows analysis of high-throughput community sequencing data. Nat Methods. 452
7: 335-336. 453
15. Schloss P. D., S. L. Westcott, T. Ryabin, J. R. Hall, M. Hartmann, E. B. Hollister, R. A. 454
Lesniewski, B. B. Oakley, D. H. Parks and C. J. Robinson. 2009. Introducing mothur: 455
open-source, platform-independent, community-supported software for describing and comparing 456
microbial communities. Appl. Environ. Microbiol. 75: 7537-7541. 457
16. Liu B., J. Yuan, S. M. Yiu, Z. Li, Y. Xie, Y. Chen, Y. Shi, H. Zhang, Y. Li, T. W. Lam and R. Luo. 458
2012. COPE: an accurate k-mer-based pair-end reads connection tool to facilitate genome assembly. 459
Bioinformatics. 28: 2870-2874. 460
17. Edgar R. C. 2013. UPARSE: highly accurate OTU sequences from microbial amplicon reads. Nat 461
Methods. 10: 996-998. 462
18. Edgar R. C., B. J. Haas, J. C. Clemente, C. Quince and R. Knight. 2011. UCHIME improves 463
on June 29, 2018 by guesthttp://aem
.asm.org/
Dow
nloaded from
24
sensitivity and speed of chimera detection. Bioinformatics. 27: 2194-2200. 464
19. DeSantis T. Z., P. Hugenholtz, N. Larsen, M. Rojas, E. L. Brodie, K. Keller, T. Huber, D. Dalevi, 465
P. Hu and G. L. Andersen. 2006. Greengenes, a chimera-checked 16S rRNA gene database and 466
workbench compatible with ARB. Appl Environ Microbiol. 72: 5069-5072. 467
20. Price M. N., P. S. Dehal and A. P. Arkin. 2009. FastTree: computing large minimum evolution trees 468
with profiles instead of a distance matrix. Mol. Biol. Evol. 26: 1641-1650. 469
21. Legendre P. and E. Gallagher. 2001. Ecologically meaningful transformations for ordination of 470
species data. Oecologia. 129: 271-280. 471
22. Denman S. E. and C. S. McSweeney. 2006. Development of a real‐time PCR assay for monitoring 472
anaerobic fungal and cellulolytic bacterial populations within the rumen. FEMS Microbiol. Ecol. 58: 473
572-582. 474
23. Layton A., L. McKay, D. Williams, V. Garrett, R. Gentry and G. Sayler. 2006. Development of 475
Bacteroides 16S rRNA gene TaqMan-based real-time PCR assays for estimation of total, human, and 476
bovine fecal pollution in water. Appl Environ Microbiol. 72: 4214-4224. 477
24. Stevenson D. M. and P. J. Weimer. 2007. Dominance of Prevotella and low abundance of classical 478
ruminal bacterial species in the bovine rumen revealed by relative quantification real-time PCR. Appl. 479
Microbiol. Biot. 75: 165-174. 480
25. Zhou M., E. Hernandez-Sanabria and L. L. Guan. 2009. Assessment of the microbial ecology of 481
ruminal methanogens in cattle with different feed efficiencies. Appl Environ Microbiol. 75: 482
6524-6533. 483
26. Rey M., F. Enjalbert, S. Combes, L. Cauquil, O. Bouchez and V. Monteils. 2014. Establishment 484
of ruminal bacterial community in dairy calves from birth to weaning is sequential. J. Appl. 485
Microbiol. 116: 245-257. 486
27. Jami E. and I. Mizrahi. 2012. Composition and similarity of bovine rumen microbiota across 487
individual animals. Plos One. 7:e33306. 488
28. Ley R. E., M. Hamady, C. Lozupone, P. J. Turnbaugh, R. R. Ramey, J. S. Bircher, M. L. 489
Schlegel, T. A. Tucker, M. D. Schrenzel, R. Knight and J. I. Gordon. 2008. Evolution of 490
on June 29, 2018 by guesthttp://aem
.asm.org/
Dow
nloaded from
25
mammals and their gut microbes. Science. 320: 1647-1651. 491
29. Mayer M., A. Abenthum, J. Matthes, D. Kleeberger, M. Ege, C. Hölzel, J. Bauer and K. 492
Schwaiger. 2012. Development and genetic influence of the rectal bacterial flora of newborn calves. 493
Vet Microbiol. 161: 179-185. 494
30. Malmuthuge N., M. J. Li, Y. H. Chen, P. Fries, P. J. Griebel, B. Baurhoo, X. Zhao and L. L. 495
Guan. 2012. Distinct commensal bacteria associated with ingesta and mucosal epithelium in the 496
gastrointestinal tracts of calves and chickens. FEMS Microbiol. Ecol. 79: 337-347. 497
31. Wallace R. J., K. J. Cheng, D. Dinsdale and E. R. Orskov. 1979. Independent microbial-flora of 498
the epithelium and its role in the eco-microibiology og the rumen. Nature. 279: 424-426. 499
32. Sadet S., C. Martin, B. Meunier and D. P. Morgavi. 2007. PCR-DGGE analysis reveals a distinct 500
diversity in the bacterial population attached to the rumen epithelium. Animal. 1: 939-944. 501
33. Mändar R. and M. Mikelsaar. 1996. Transmission of mother’s microflora to the newborn at birth. 502
Neonatology. 69: 30-35. 503
34. Wise G. H. and G. W. Anderson. 1939. Factors affecting the passage of liquids into the rumen of the 504
dairy calf. I. Method of administering liquids: drinking from open pail versus sucking through a 505
rubber nipple. J Dairy Sci. 22: 697 - 705. 506
35. Collier-Hyams L. S., V. Sloane, B. C. Batten and A. S. Neish. 2005. Cutting edge: bacterial 507
modulation of epithelial signaling via changes in neddylation of cullin-1. J. Immunol. 175: 508
4194-4198. 509
36. Kalita A., J. Hu and A. G. Torres. 2014. Recent advances in adherence and invasion of pathogenic 510
Escherichia coli. Curr Opin Infect Dis. 27: 459-464. 511
37. Jost T., C. Lacroix, C. P. Braegger and C. Chassard. 2012. New insights in gut microbiota 512
establishment in healthy breast fed neonates. PloS one. 7: e44595. 513
38. Zhu Z., S. Hang, S. Mao and W. Zhu. 2014. Diversity of Butyrivibrio group bacteria in the rumen 514
of goats and its response to the supplementation of garlic oil. Asian-Australas J Anim Sci. 27: 515
179-186. 516
39. Boeckaert C., B. Vlaeminck, V. Fievez, L. Maignien, J. Dijkstra and N. Boon. 2008. 517
on June 29, 2018 by guesthttp://aem
.asm.org/
Dow
nloaded from
26
Accumulation of trans C-18:1 fatty acids in the rumen after dietary algal supplementation is 518
associated with changes in the Butyrivibrio community. Appl. Environ. Microbiol. 74: 6923-6930. 519
40. Man S. M., N. O. Kaakoush, S. T. Leach, L. Nahidi, H. K. Lu, J. Norman, A. S. Day, L. Zhang 520
and H. M. Mitchell. 2010. Host attachment, invasion, and stimulation of proinflammatory cytokines 521
by Campylobacter concisus and other non-Campylobacter jejuni Campylobacter species. J Infect Dis. 522
202: 1855-1865. 523
41. Oherrin S. M. and W. R. Kenealy. 1993. Glucose and carbon-dioxide metabolism by 524
Succinivibrio-Dextrinosolvens. Appl. Environ. Microbiol. 59: 748-755. 525
42. Klaenhammer T. R., M. Kleerebezem, M. V. Kopp and M. Rescigno. 2012. The impact of 526
probiotics and prebiotics on the immune system. Nat. Rev. Immunol. 12: 728-734. 527
43. Thomas L. V. and T. Ockhuizen. 2012. New insights into the impact of the intestinal microbiota on 528
health and disease: a symposium report. Brit J Nutr. 107 Suppl 1: S1-13. 529
530
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Table 1. Alpha diversity measures of the ruminal epithelial bacterial communities at different ages in kids (27000 reads)
Alpha indices Age (d)
SEM P value
0 7 28 42 70 L Q OTUs 272.3 279.7 430.3 527.5 453.0 73.24 0.032 0.123 Chao 437.1 466.9 566.9 726.9 640.2 75.51 0.025 0.166 Ace 581.1 609.3 565.2 790.7 661.2 69.81 0.210 0.436 Shannon 1.61 1.37 2.91 2.96 3.22 0.383 0.002 0.158 Simpson 0.37 0.56 0.20 0.17 0.10 0.065 0.001 0.326 Coverage 0.995 0.995 0.995 0.993 0.994 0.001 0.151 0.456
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Table 2. Phylum level taxonomy composition (% of sequences) of the ruminal epithelial bacterial communities at different ages in kids (top 9 phyla)
Phylum Age (d)
SEM P value
0 7 28 42 70 L Q Actinobacteria 0.24 0.22 1.86 1.18 1.28 0.51 0.096 0.139 Bacteroidetes 1.57 3.31 12.80 8.61 10.57 3.77 0.088 0.227 Chloroflexi 0.00 0.01 0.80 0.22 0.42 0.11 0.013 0.014 Fibrobacteres 0.00 0.01 0.06 0.49 0.18 0.24 0.344 0.453 Firmicutes 1.94 7.06 16.99 54.71 40.29 4.84 <.0001 0.009 Fusobacteria 1.18 0.85 0.04 0.00 0.00 0.61 0.151 0.363 Proteobacteria 90.13 86.29 60.65 28.64 45.42 4.74 <.0001 0.0003 TM7 0.03 0.01 0.01 0.29 0.17 0.08 0.067 0.562 Thermi 0.23 1.21 1.13 1.31 0.00 0.49 0.511 0.051 Unclassified 4.63 0.81 0.74 4.06 1.12 1.73 0.565 0.891 Others (< 0.5%) 0.06 0.23 4.94 0.50 0.54 0.15 0.025 0.600
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Table 3. Genus level taxonomy composition (% of sequences) of the ruminal epithelial bacterial communities at different ages in kids
Phylum Genus Age (d)
SEM P value
0 7 28 42 70 L Q Bacteroidetes Bacteroides 0.12 2.46 0.80 0.03 0.01 0.591 0.107 0.759 Porphyromonas 0.70 0.44 0.02 0.00 0.00 0.178 0.011 0.083 Prevotella 0.47 0.20 4.86 5.76 5.18 1.718 0.022 0.149 Firmicutes Bulleidia 0.00 0.01 0.24 0.05 0.07 0.093 0.576 0.240 Butyrivibrio 0.10 0.56 8.90 41.38 30.13 5.606 0.000 0.086 Lysinibacillus 0.00 0.00 0.55 0.00 0.00 0.213 0.947 0.197 Mogibacterium 0.00 0.01 0.42 0.17 0.51 0.102 0.003 0.648 Oscillospira 0.02 0.91 0.12 0.04 0.04 0.095 0.005 0.839 Ruminococcus 0.02 0.05 0.82 0.52 0.30 0.351 0.441 0.158 Streptococcus 0.38 0.12 0.35 0.00 0.00 0.117 0.056 0.964 Succiniclasticum 0.00 0.01 0.28 0.04 0.12 0.107 0.468 0.353 p-75-a5 0.00 0.00 0.02 0.11 0.82 0.182 0.006 0.077 Proteobacteria Acidovorax 0.21 0.16 0.14 0.30 0.00 0.106 0.343 0.286 Acinetobacter 0.08 0.05 0.11 0.72 0.01 0.322 0.752 0.255 Actinobacillus 0.49 0.01 0.01 0.00 0.00 0.219 0.259 0.332 Arcobacter 0.37 0.75 0.08 0.02 0.00 0.206 0.038 0.406 Burkholderia 0.00 0.01 0.26 0.00 0.00 0.084 0.901 0.129 Campylobacter 0.02 0.50 4.27 20.33 29.99 4.467 <.0001 0.560 Desulfobulbus 0.00 0.01 0.00 0.40 3.78 1.154 0.033 0.160 Enterobacter 0.27 0.01 0.02 0.02 0.00 0.071 0.077 0.178 Escherichia 80.79 7.48 1.65 0.23 0.06 3.578 <.0001 <.0001 Herbaspirillum 0.00 0.06 1.09 0.00 0.00 0.376 0.896 0.156 Janthinobacterium 0.00 0.01 0.33 0.00 0.00 0.110 0.902 0.141 Mannheimia 0.31 0.01 0.01 0.00 0.00 0.141 0.269 0.366 Paracoccus 0.00 0.00 0.13 0.21 0.00 0.089 0.631 0.075 Succinivibrio 0.00 0.04 3.27 0.01 0.00 1.142 0.938 0.156 Variovorax 0.00 0.01 0.26 0.00 0.00 0.087 0.915 0.151 Actinobacteria Actinomyces 0.03 0.01 0.03 0.00 0.21 0.078 0.116 0.184 Chloroflexi SHD-231 0.00 0.01 0.80 0.21 0.42 0.111 0.013 0.014 Fibrobacteres Fibrobacter 0.00 0.01 0.06 0.49 0.18 0.237 0.344 0.453 Fusobacteria Fusobacterium 1.18 0.85 0.04 0.00 0.00 0.612 0.151 0.363 Thermi Thermus 0.23 1.21 1.13 1.31 0.00 0.490 0.510 0.051 Unclassified 13.38 82.99 66.02 26.00 27.13 7.535 0.055 0.014 Others(<0.5%) 0.83 1.05 2.91 1.65 1.00 0.812 0.845 0.107
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Table 4. qPCR results of total bacteria and two genera of the ruminal epithelial bacterial communities at different ages in kids
Genus Age (d) SEM P value
0 7 28 42 70 L Q Bacteriaa 1.37 1.43 3.72 3.09 4.40 0.838 0.013 0.510 Prevotella b 2.36 4.29 3.75 8.25 7.26 1.820 0.049 0.556 Bacteroides b 2.39 3.23 1.13 2.91 4.71 1.396 0.314 0.259
a, Total bacteria was expressed as ×108 copy numbers per gram rumen tissue. b, Prevotella and Bacteroides relative abundances (%) were expressed as by dividing the 16S rRNA gene copy number of each genus by the 16S rRNA gene copy number of total bacteria copy number.
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Figure legends
Figure 1. Principal co-ordinate analysis (PCoA) of the ruminal epithelial bacterial OTUs at
different ages in kids.
Figure 2. Within-group similarity, calculated as the average of the pairwise similarity between
each paired sample within each group using the Bray-Curtis metric. The closer the similarity
is to 1, the higher the average similarity within a group. Letters above the bars indicate
significance between groups; groups with different letters have significant different similarity
values at P < 0.05.
Figure 3. Transform-based PCA of ruminal epithelial bacterial OTUs at different ages in kids.
The top ten OTUs contributing to the separation of samples are displayed on the figure (OTU
number).
OTU2, Neisseriaceae family. OTU108, Ruminococcaceae family. OTU5, Escherichia genus.
OTU3977, Escherichia genus. OTU120, Ruminococcus genus. OTU6, Butyrivibro genus.
OTU7, Campylobacter genus. OTU12, Butyrivibro genus. OTU113, Campylobacter genus.
OTU1340, Butyrivibro genus.
Figure 4. Correlation coefficients between relative abundances of the ruminal epithelial
bacterial genera, anatomic and functional variables.
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