Effect of different feeding methods on rumen microbes in growing Chinese Tan sheep

Zilin Fu Xiaofeng Xu Jie Zhang Lili Zhang About the authors

ABSTRACT

We evaluated the difference between rumen bacteria in Tan sheep fed either by grazing or in a feedlot. The aim was to provide a theoretical basis for ruminant nutrition and meat quality based on rumen fermentation. Twenty-four three-month-old Tan sheep were randomly and equally divided into two groups, the grazing group and ration group. Five sheep of each group were selected for slaughter at six months of age. Ruminal contents were collected and assessed to identify rumen bacteria, based on 16S rDNA sequencing analysis. A total of 17 phyla were identified, among which Bacteroidetes, Firmicutes, and Proteobacteria were dominant in both groups. The abundance of Firmicutes was higher in grazing group than in the ration group, while that of Proteobacteria was opposite. Besides the dominant phyla differences, the abundance of Fibrobacteres, Tenericutes, Elusimicrobia, and Cyanobacteria was significantly higher in the grazing group compared with the ration group. At genus level, a total of 174 genera were identified. The abundance of Rikenellaceae_RC9_gut_group, Dialister, Lachnospiraceae_NA, Catonella, Ruminococcaceae_UCG-014, Lachnospiraceae_NK3A20_group, and Fibrobacter in the grazing group was higher than in the ration group. However, the abundance of Succinivibrionaceae_NA was lower in the grazing group, and Succinivibrionaceae_UCG-001 showed a decreasing trend in the grazing group. The two feeding methods may influence the rumen bacterial composition, including the abundance of dominant bacteria, as well as the cellulolytic- and carbohydrate-degrading bacteria in the rumen of Tan sheep.

Keywords:
feedlot; grazing; rumen microorganism; Tan sheep

Introduction

Tan sheep are an endemic breed to northwestern China, mainly found in the arid desert areas. The wool of Tan sheep is popular in both domestic and overseas markets for its delicate curl, soft texture, and snow-white appearance. The meat of Tan sheep is also considered top grade, because it is tender, without a goaty flavor (Kang et al., 2013Kang, X.; Liu, G.; Liu, Y.; Xu, Q.; Zhang, M. and Fang, M. 2013. Transcriptome profile at different physiological stages reveals potential mode for curly fleece in Chinese Tan sheep. PLoS One 8:e71763. https://doi.org/10.1371/journal.pone.0071763
https://doi.org/10.1371/journal.pone.007...
). Owing to environmental concerns in recent years (Chen et al., 2013Chen, Y.; Luo, H.; Liu, X.; Wang, Z.; Zhang, Y; Liu, K.; Jiao, L.; Chang, Y. and Zuo, Z. 2013. Effect of restricted grazing time on the foraging behavior and movement of Tan sheep grazed on desert steppe. Asian-Australasian Journal of Animal Sciences 26:711-715. https://doi.org/10.5713/ajas.2012.12556
https://doi.org/10.5713/ajas.2012.12556...
), feeding methods for Tan sheep have started to shift from full-forage grazing in desert and arid grasslands to the feedlot, which has also caused a change in the composition of animal diets (Morand-Fehr et al., 2007Morand-Fehr, P.; Fedele, V.; Decandia, M. and Le Frileux, Y. 2007. Influence of farming and feeding systems on composition and quality of goat and sheep milk. Small Ruminant Research 68:20-34. https://doi.org/10.1016/j.smallrumres.2006.09.019
https://doi.org/10.1016/j.smallrumres.20...
).

The rumen, as an important digestive organ of ruminants, has an abundance of microorganisms, the composition of which is mainly influenced by the animal diet (Henderson et al., 2015Henderson, G.; Cox, F.; Ganesh, S.; Jonker, A.; Young, W.; Global Rumen Census Collaborators and Janssen, P. H. 2015. Rumen microbial community composition varies with diet and host, but a core microbiome is found across a wide geographical range. Scientific Reports 5:14567. https://doi.org/10.1038/srep14567
https://doi.org/10.1038/srep14567...
). A previous study showed that diet composition can alter the content and composition of rumen bacteria (Bas et al., 2003Bas, P.; Archimède, H.; Rouzeau, A. and Sauvant, D. 2003. Fatty acid composition of mixed-rumen bacteria: Effect of concentration and type of forage. Journal of Dairy Science 86:2940-2948. https://doi.org/10.3168/jds.S0022-0302(03)73891-0
https://doi.org/10.3168/jds.S0022-0302(0...
). Furthermore, rumen microbes affect fermentation that is associated with fat metabolism and nitrogen storage, which are closely related to ruminant digestion and a range of production traits such as feed efficiency and milk yield and components (Schären et al., 2018Schären, M.; Frahm, J.; Kersten, S.; Meyer, U.; Hummel, J.; Breves, G. and Dänicke, S. 2018. Interrelations between the rumen microbiota and production, behavioral, rumen fermentation, metabolic, and immunological attributes of dairy cows. Journal of Dairy Science 101:4615-4637. https://doi.org/10.3168/jds.2017-13736
https://doi.org/10.3168/jds.2017-13736...
; Spanghero et al., 2017Spanghero, M.; Mason, F.; Zanfi, C. and Nikulina, A. 2017. Effect of diets differing in protein concentration (low vs medium) and nitrogen source (urea vs soybean meal) on in vitro rumen fermentation and on performance of finishing Italian Simmental bulls. Livestock Science 196:14-21. https://doi.org/10.1016/j.livsci.2016.12.004
https://doi.org/10.1016/j.livsci.2016.12...
). Fat storage, an important factor of meat quality and flavor, is positively linear with the abundance of Firmicutes and negatively linear with that of Bacteroidetes in the porcine gut (Guo, 2009Guo, X. L. 2009. Detection of Firmicutes and Bacteroidetes in the pig gut and the correlation between their abundance and fat deposit. Thesis (D. Sc.). Sichuan Agricultural University, Yaan, Sichuan, China.). Therefore, improving the composition of rumen microorganisms has become a focus of recent ruminant research. However, only a few studies have evaluated the total rumen bacteria of Tan sheep.

The population of rumen bacteria in goats usually becomes stable around six months of age (Guo, 2015Guo W. 2015. The research on the composition structure of archaea and bacteria in the rumen of goat at different age stage. Thesis (D. Sc.). Sichuan Agricultural University, Yaan, Sichuan, China.). As a result, the present study sampled the rumen content of six-month-old Tan sheep fed at three months of age to determine the effects of different feeding methods on bacterial populations in the developing rumen, based on the 16S rDNA sequencing technique. The objective was to provide a theoretical basis for animal nutrition and meat quality control in Tan sheep. We hypothesized that the diversity and variety of rumen bacteria can be altered with different feeding methods.

Material and Methods

The experimental procedure was approved by the Institutional Animal Care and Use Committee (NXU1074901).

Twenty-four healthy three-month-old Tan ewes of similar weight (17.16±0.58 kg) were randomly divided into the grazing group (G6) and ration group (R6), (12 ewes in each group). The pasture was available for ad libitum feeding of the sheep in the grazing group. The pasture included 40% Astragalus adsurgens, 20% Lespedeza davurica, 5% Sophora alopecuroides, 10% Caragana korshinskii 10%, Glycyrrhizae radix, and 10% Achnatherum splendens. The sheep in the ration group were fed roughage supplemented with concentrate in feedlots (Table 1). Both groups had free access to water.

Table 1
Dietary composition and nutrition level of Tan sheep in the ration group

At six months of age, five sheep from each group were slaughtered. The rumen fluid of the slaughtered sheep was filtered through four layers of gauze and collected separately. A volume of 50 mL of each sample, which contained digested plant particles and rumen fluid, were stored in CO2-containing centrifugal tubes and kept on ice for no longer than 30 min, before being stored in a refrigerator at −80 °C. Sample handling that entails cooling on ice and at −80 °C has little effect on the sample integrity or subsequent analyses (Wu et al., 2010Wu, G. D.; Lewis, J. D.; Hoffmann, C.; Chen, Y. Y.; Knight, R.; Bittinger, K.; Hwang, J.; Chen, J.; Berkowsky, R.; Nessel, L.; Li, H. and Bushman, F. D. 2010. Sampling and pyrosequencing methods for characterizing bacterial communities in the human gut using 16S sequence tags. BMC Microbiology 10:206. https://doi.org/10.1186/1471-2180-10-206
https://doi.org/10.1186/1471-2180-10-206...
). A total of 10 samples were tested for rumen bacteria. The DNA extraction was then conducted as previously described (Denman and McSweeney, 2006Denman, S. E. and McSweeney, C. S. 2006. Development of a real-time PCR assay for monitoring anaerobic fungal and cellulolytic bacterial populations within the rumen. FEMS Microbiology Ecology 58:572-582. https://doi.org/10.1111/j.1574-6941.2006.00190.x
https://doi.org/10.1111/j.1574-6941.2006...
) using a FastDNA Kit and FastPrep Instrument. The final samples were either stored at 4 °C for a short term, or −80 °C for a long term.

After genomic DNA was extracted from the rumen samples, we conducted PCR amplification for the pre-experiments. Agarose gel electrophoresis was used to detect the purity and concentration of DNA samples before PCR amplification. After extracting genomic DNA from the samples, the V3 + V4 area of 16S rDNA was amplified. The primer sequence was as follows: 341F: CCTACGGGNGGGCWGCAG; 806R: GGACTACHVGGTATCTAAT. The 16S rDNA was sequenced using the Illumina Hiseq2500 PE250 platform (Guangzhou Gene Denovo Technology Co., Ltd. in Guangzhou, China).

The operational taxonomic units (OTU) were obtained from the clustered effective tags of more than 97% similarity using the Uparse (version 9.2.64) software (Edgar, 2013Edgar, R. C. 2013. UPARSE: highly accurate OTU sequences from microbial amplicon reads. Nature Methods 10:996-998. https://doi.org/10.1038/nmeth.2604
https://doi.org/10.1038/nmeth.2604...
), and then the abundances of OTU were calculated. Venn analysis was performed in R project VennDiagram package (version 1.6.16, Chen and Boutros, 2011Chen, H. and Boutros, P. C. 2011. VennDiagram: a package for the generation of highly-customizable Venn and Euler diagrams in R. BMC Bioinformatics 12:35. https://doi.org/10.1186/1471-2105-12-35
https://doi.org/10.1186/1471-2105-12-35...
). The alpha indexes were calculated in QIIME (version 1.9.1, Caporaso et al., 2010Caporaso, J. G.; Kuczynski, J.; Stombaugh, J.; Bittinger, K.; Bushman, F. D.; Costello, E. K.; Fierer, N.; Peña, A. G.; Goodrich, J. K.; Gordon, J. I.; Huttley, G. A.; Kelley, S. T.; Knights, D.; Koenig, J. E.; Ley, R. E.; Lozupone, C. A.; McDonald, D.; Muegge, B. D.; Pirrung, M.; Reeder, J.; Sevinsky, J. R.; Turnbaugh, P. J.; Walters, W. A.; Widmann, J.; Yatsunenko, T.; Zaneveld, J. and Knight, R. 2010. QIIME allows analysis of high-throughput community sequencing data. Nature Methods 7:335-336. https://doi.org/10.1038/nmeth.f.303
https://doi.org/10.1038/nmeth.f.303...
) and then processed by the Excel 2007 software and analyzed by the SAS software (Statistical Analysis System, version 8.2) using a completely random design. Principal component analysis (PCA) was performed in R project Vegan package (version 2.5.3, Oksanen et al., 2011Oksanen, J.; Blanchet, F. G.; Kindt, R.; Legendre, P.; O'Hara, R. and Simpson, G. L. 2011. Vegan: Community Ecology Package. R Package Version 1.17-6. Available at: <http://vegan.r-forge.r-project.org>. Accessed on: July 16, 2018.
http://vegan.r-forge.r-project.org...
). Anosim analysis was conducted by the Mothur software and calculated in R project Vegan package (version 2.5.3, Oksanen et al., 2011Oksanen, J.; Blanchet, F. G.; Kindt, R.; Legendre, P.; O'Hara, R. and Simpson, G. L. 2011. Vegan: Community Ecology Package. R Package Version 1.17-6. Available at: <http://vegan.r-forge.r-project.org>. Accessed on: July 16, 2018.
http://vegan.r-forge.r-project.org...
). The representative sequences were classified into bacteria based on SILVA database (version 132, Pruesse et al., 2007Pruesse, E.; Quast, C.; Knittel, K.; Fuchs, B. M.; Ludwig, W.; Peplies, J. and Glöckner, F. O. 2007. SILVA: a comprehensive online resource for quality checked and aligned ribosomal RNA sequence data compatible with ARB. Nucleic Acids Research 35:7188-7196. https://doi.org/10.1093/nar/gkm864
https://doi.org/10.1093/nar/gkm864...
) and Greengene database (version gg_13_5, DeSantis et al., 2006DeSantis, T. Z.; Hugenholtz, P.; Larsen, N.; Rojas, M.; Brodie, E. L.; Keller, K.; Huber, T.; Dalevi, D.; Hu, P. and Andersen, G. L. 2006. Greengenes, a chimera-checked 16S rRNA gene database and workbench compatible with ARB. Applied and Environmental Microbiology 72:5069-5072. https://doi.org/10.1128/aem.03006-05
https://doi.org/10.1128/aem.03006-05...
), with the confidence threshold values ranging from 0.8 to 1. The abundance statistics of each taxonomy was visualized using Krona (version 2.6, Ondov et al., 2011Ondov, B. D.; Bergman, N. H. and Phillippy, A. M. 2011. Interactive metagenomic visualization in a Web Browser. BMC Bioinformatics 12:385. https://doi.org/10.1186/1471-2105-12-385
https://doi.org/10.1186/1471-2105-12-385...
).

Results

After removing the low-frequency and insignificant tags, effective tags were spliced and clustered into OTU. The results of OTU clustering of the different samples were analyzed, and a Venn diagram (Figure 1) was constructed, based on the common and unique OTU information. The OTU of the sheep in the grazing group was 1797, while that in the ration group was 1761 (Figure 1), without any significant difference between the groups. A total of 1332 common OTU were shared between the two groups.

Figure 1
Venn diagram of microorganism operational taxonomic units between groups.

Alpha diversity indexes (Table 2), Chao1, ACE, Shannon, and Simpson were used to analyze species diversity and abundance. The Chao1 and ACE indexes predict the species of microorganisms (the number of OTU) in the sample based on the number of measured tags, OTU, and their relative proportions. The Shannon index reflects the species diversity according to OTU homogeneity and richness. The Simpson index refers to the probability that the randomly sampled species in two successive evaluations belong to different species. The Shannon and Simpson indexes both reflect the synthesis of species richness and evenness.

Table 2
Alpha indexes of rumen bacteria of Tan sheep in the grazing and ration groups

Favorable coverage was more than 99% in both groups (Table 2), which suggests that the indexes could fully reflect the situation of rumen bacteria. The values of the ACE index and the Chao1 index of the grazing group were higher than those of the ration group; however, this difference was not significant (P = 0.260 and 0.214, respectively). The value of the Shannon index of the grazing group was higher than that of the ration group; however, this difference was not significant (P = 0.129). The Simpson index of the grazing group tended to be closer to 1 than that of the ration group (P = 0.064).

The PCA plot was based on species abundance of the OTU list and evaluated the distance between samples by reducing dimensionality. The more similar the sample compositions were, the closer the distance reflected on the PCA plot. By evaluating the variance decomposition, the PCA (Figure 2) could identify the main elements and structures in data and simplify the complex relationships of sample composition, by reflecting the two eigenvalues of the abscissa and ordinate.

Figure 2
Principal component analysis (PCA) plots.

The abscissa was the first principal factor (73.7%) and the ordinate was the second principal factor (13.5%) (Figure 2). The samples in the grazing group were in close proximity to each other when considering the first factor, while two samples (G6-1 and G6-3) were separately distributed based on the second factor. Three samples (R6-2, R6-3, and R6-4) were concentrated, and the other two (R6-1 and R6-5) were separately distributed in the ration group. In addition, some samples in different groups (e.g., G6-3 and R6-5) showed a clustering trend.

Anosim analysis is a non-parametric test for microbial community structure. It determines whether a significant difference exists between groups compared to within groups. Unweighted UniFrac only considers whether there are changes in the species composition. Weighted UniFrac synthesizes both the changes in species composition and abundance. The medians of the grazing and ration groups differed (Figure 3), indicating statistical significance, whether the analysis was weighted or not (P<0.05). Animal-to-animal variation was higher in the ration group than in the grazing group.

Figure 3
Unifrac Boxplots.

The species taxonomic tree shows those species with an abundance greater than 1%, as selected by the Perl + SVG software, based on species annotation of the OTU. Seven levels of microbial species are displayed: kingdom, phylum, class, order, family, genus, and species. As the taxonomic tree (Figure 4) shows, most Proteobacteria were in the ration group at the phylum level, while most Spirochaetae and Firmicutes were in the grazing group. The abundance of Bacteroidetes was similar between the groups. In addition, in the Bacteroidetes phylum, most of the Bacteroidetes_S24_7_group were in the ration group at the family level, while most Rikenellaceae were in the grazing group. In the Negativicutes class, Firmicutes phylum, most Acidaminococcaceae were in the ration group at the family level, while most Veillonellaceae were in the grazing group.

Figure 4
Species taxonomic tree.

A total of 17 phyla were identified in the rumen of Tan sheep: Bacteroidetes, Firmicutes, Proteobacteria, Spirochaetae, Cyanobacteria, Fibrobacteres, Verrucomicrobia, Synergistetes, Actinobacteria, Saccharibacteria, Elusimicrobia, Tenericutes, Lentisphaerae, Bacteria_NA, Planctomycetes, Euryarchaeota, and SR1. In terms of the abundance of rumen bacteria at the phylum level, Bacteroidetes, Firmicutes, and Proteobacteria were the dominant bacteria in both groups (Table 3), which accounted for more than 85% of the total rumen bacteria.

Table 3
Phyla of rumen bacteria of Tan sheep in grazing and ration groups (%)

The abundance of Fibrobacteres and Tenericutes was significantly higher in the grazing group than in the ration group (P<0.01). The abundance of Firmicutes, Cyanobacteria, and Elusimicrobia was significantly higher in the grazing group than in the ration group (P<0.05). The abundance of Actinobacteria showed a greater increasing trend in the grazing group than in the ration group; however, this difference was not significant (P = 0.068). Furthermore, the abundance of Proteobacteria was significantly lower in the grazing group than in the ration group (P<0.05).

A total of 174 genera were identified and analyzed in the rumen fluid. Only the dominant bacteria (with an abundance of more than 5%), subdominant bacteria (with an abundance of 0.5%–5%), and bacteria that showed significant group differences are listed in Table 4. Eight dominant genera were identified in the grazing group: Succinivibrionaceae_UCG-001, Prevotella_1, Prevotella_7, Prevotellaceae_NA, Rikenellaceae_RC9_gut_group, Prevotellaceae_UCG-001, Veillonellaceae_NA, and Dialister. Five dominant genera were identified in the ration group: Succinivibrionaceae_UCG-001, Prevotella_1, Prevotella_7, Bacteroidales_S24-7_group_NA, and Succinivibrionaceae_NA. Moreover, the abundance of the Rikenellaceae_RC9_gut_group, Lachnospiraceae_NA, Ruminococcaceae_UCG-014, Lachnospiraceae_NK3A20_group, Erysipelotrichaceae_UCG-004, and Fibrobacter was significantly higher in the grazing group than in the ration group (P<0.01). In addition, the abundance of Dialister, Catonella, Roseburia, and Nodatum_group in the grazing group was significantly higher than in the ration group (P<0.05). However, the abundance of Succinivibrionaceae_NA in the grazing group was significantly lower than that in the ration group (P<0.01), and the abundance of Succinivibrionaceae_UCG-001 showed a decreasing trend in the ration group (P = 0.065).

Table 4
Genera of rumen bacteria of Tan sheep in the grazing and ration groups

Discussion

The rumen provides a relatively stable living environment for rumen microorganisms, including bacteria, protozoa, and fungi, among which bacteria are the most abundant (Pitta et al., 2016aPitta, D. W.; Indugu, N.; Kumar, S.; Vecchiarelli, B.; Sinha, R.; Baker, L. D.; Bhukya, B. and Ferguson, J. D. 2016a. Metagenomic assessment of the functional potential of the rumen microbiome in Holstein dairy cows. Anaerobe 38:50-60. https://doi.org/10.1016/j.anaerobe.2015.12.003
https://doi.org/10.1016/j.anaerobe.2015....
). In the present study, rumen bacteria were investigated under two feeding methods, full-forage grazing and feedlot feeding with high levels of concentrates. The analyses showed relatively high animal-to-animal variation, but significant group differences in some aspects. In terms of the rumen bacteria diversity, Kocherginskaya et al. (2001)Kocherginskaya, S. A.; Aminov, R. I. and White, B. A. 2001. Analysis of the rumen bacterial diversity under two different diet conditions using denaturing gradient gel electrophoresis, random sequencing, and statistical ecology approaches. Anaerobe 7:119-134. https://doi.org/10.1006/anae.2001.0378
https://doi.org/10.1006/anae.2001.0378...
identified greater diversity in high-grain diets relative to hay diets; however, this was not supported by the results of the current study. This might be due to differences in the nutrition level of the diets. In the present study, the diversity and evenness of rumen bacteria showed an increasing trend in the grazing group, according to the Simpson index. These results are consistent with those of Grilli et al. (2016)Grilli, D. J.; Fliegerová, K.; Kopečný, J.; Lama, S. P.; Egea, V.; Sohaefer, N.; Pereyra, C.; Ruiz, M. S.; Sosa, M. A.; Arenas, G. N. and Mrázek, J. 2016. Analysis of the rumen bacterial diversity of goats during shift from forage to concentrate diet. Anaerobe 42:17-26. https://doi.org/10.1016/j.anaerobe.2016.07.002
https://doi.org/10.1016/j.anaerobe.2016....
.

Rumen fermentation is influenced by the species composition of bacteria (Oliveira et al., 2006Oliveira, M. L. S.; Arêas, A. P. M.; Campos, I. B.; Monedero, V.; Perez-Martínez, G.; Miyaji, E. N.; Leite, L. C. C.; Aires, K. A. and Ho, P. L. 2006. Induction of systemic and mucosal immune response and decrease in Streptococcus pneumoniae colonization by nasal inoculation of mice with recombinant lactic acid bacteria expressing pneumococcal surface antigen A. Microbes and Infection 8:1016-1024. https://doi.org/10.1016/j.micinf.2005.10.020
https://doi.org/10.1016/j.micinf.2005.10...
; Ley et al., 2008Ley, R. E.; Lozupone, C. A.; Hamady, M.; Knight, R. and Gordon, J. I. 2008. Worlds within worlds: evolution of the vertebrate gut microbiota. Nature Reviews Microbiology 6:776-788. https://doi.org/10.1038/nrmicro1978
https://doi.org/10.1038/nrmicro1978...
; Singh et al., 2012Singh, K. M.; Ahir, V. B.; Tripathi, A. K.; Ramani, U. V.; Sajnani, M.; Koringa, P. G.; Jakhesara, S.; Pandya, P. R.; Rank, D. N.; Murty, D. S.; Kothari, R. K. and Joshi, C. G. 2012. Metagenomic analysis of Surti buffalo (Bubalus bubalis) rumen: A preliminary study. Molecular Biology Reports 39:4841-4848. https://doi.org/10.1007/s11033-011-1278-0
https://doi.org/10.1007/s11033-011-1278-...
). The phyla of rumen bacteria detected by gene sequencing mainly include Bacteroidetes, Firmicutes, Proteobacteria, Spirochaetae, Fibrobacteria, and Actinobacteria (Huws et al., 2007Huws, S. A.; Edwards, J. E.; Kim, E. J. and Scollan, N. D. 2007. Specificity and sensitivity of eubacterial primers utilized for molecular profiling of bacteria within complex microbial ecosystems. Journal of Microbiological Methods 70:565-569. https://doi.org/10.1016/j.mimet.2007.06.013
https://doi.org/10.1016/j.mimet.2007.06....
; Pitta et al., 2016aPitta, D. W.; Indugu, N.; Kumar, S.; Vecchiarelli, B.; Sinha, R.; Baker, L. D.; Bhukya, B. and Ferguson, J. D. 2016a. Metagenomic assessment of the functional potential of the rumen microbiome in Holstein dairy cows. Anaerobe 38:50-60. https://doi.org/10.1016/j.anaerobe.2015.12.003
https://doi.org/10.1016/j.anaerobe.2015....
). These findings are consistent with those of the present study, although the abundance of individual species showed a disparity.

The dominant bacteria of the 17 phyla identified in the rumen of both groups were Bacteroidetes, Firmicutes, and Proteobacteria. The abundance of the dominant phyla of the grazing and feedlot-fed groups was as follows: Bacteroidetes, 51 and 39%, respectively; Firmicutes, 28 and 14%, respectively; and Proteobacteria, 16 and 46%, respectively. Significant differences were observed in the Firmicutes and Proteobacteria phyla, indicating the existence of a strong effect on the abundance of dominant rumen bacteria under different feeding conditions.

Proteobacteria, as an important phylum in rumen metabolism, tends to become co-dominant in ruminants fed starch-based diets (Pitta et al., 2016bPitta, D. W.; Pinchak, W. E.; Indugu, N.; Vecchiarelli, B.; Sinha, R. and Fulford, J. D. 2016b. Metagenomic analysis of the rumen microbiome of steers with wheat-induced frothy bloat. Frontiers in Microbiology 7:689. https://doi.org/10.3389/fmicb.2016.00689
https://doi.org/10.3389/fmicb.2016.00689...
). However, in the present study, Proteobacteria became the most abundant phylum in sheep fed a high concentrate diet. The Fibrobacteres are closely associated with the degradation of cellulose and lignin (Ransom-Jones et al., 2012Ransom-Jones, E.; Jones, D. L.; McCarthy, A. J. and McDonald, J. E. 2012. The Fibrobacteres: an important phylum of cellulose-degrading bacteria. Microbial Ecology 63:267-281. https://doi.org/10.1007/s00248-011-9998-1
https://doi.org/10.1007/s00248-011-9998-...
). Their abundance in the grazing group was significantly higher than that in the ration group, which was consistent with the differences in fiber intake between the groups.

Roughage is a major feed component for ruminants. Fiber in roughage is degraded rapidly by rumen microorganisms into nutrients that provide energy for ruminants (Aschenbach et al., 2011Aschenbach, J. R.; Penner, G. B.; Stumpff, F. and Gäbel, G. 2011. Ruminant nutrition symposium: Role of fermentation acid absorption in the regulation of ruminal pH. Journal of Animal Science 89:1092-1107. https://doi.org/10.2527/jas.2010-3301
https://doi.org/10.2527/jas.2010-3301...
). Bacteria and fungi, including cellulolytic bacteria, play an important role in enzymatic decomposition, by degrading cellulose and hemicellulose into small molecules that can be absorbed by the rumen (Zebeli et al., 2012Zebeli, Q.; Aschenbach, J. R.; Tafaj, M.; Boguhn, J.; Ametaj, B. N. and Drochner, W. 2012. Invited review: Role of physically effective fiber and estimation of dietary fiber adequacy in high-producing dairy cattle. Journal of Dairy Science 95:1041-1056. https://doi.org/10.3168/jds.2011-4421
https://doi.org/10.3168/jds.2011-4421...
).

The structure of rumen microflora is related to the dietary method (Yáñez-Ruiz et al., 2010Yáñez-Ruiz, D. R.; Macías, B.; Pinloche, E. and Newbold, C. J. 2010. The persistence of bacterial and methanogenic archaeal communities residing in the rumen of young lambs. FEMS Microbiology Ecology 72:272-278. https://doi.org/10.1111/j.1574-6941.2010.00852.x
https://doi.org/10.1111/j.1574-6941.2010...
). In one study of the effects on rumen flora of goats fed a high-grain diet (Liu et al., 2015Liu, J.; Bian, G.; Zhu, W. and Mao, S. 2015. High-grain feeding causes strong shifts in ruminal epithelial bacterial community and expression of Toll-like receptor genes in goats. Frontiers in Microbiology 6:167. https://doi.org/10.3389/fmicb.2015.00167
https://doi.org/10.3389/fmicb.2015.00167...
), the results showed that such diets improve the abundance of Succiniclasticum and decreases the abundance of unclassified Rikenellaceae and unclassified Erysipelotrichaceae. Ruminococcaceae, Fibrobacter, and Lachnospiraceae, which are associated with cellulose and hemicellulose degradation (Biddle et al., 2013Biddle, A.; Stewart, L.; Blanchard, J. and Leschine, S. 2013. Untangling the genetic basis of fibrolytic specialization by Lachnospiraceae and Ruminococcaceae in diverse gut communities. Diversity 5:627-640. https://doi.org/10.3390/d5030627
https://doi.org/10.3390/d5030627...
; Li et al., 2014Li, J.; Rui, J.; Zhang, S.; Sun, X.; Yan, Z.; Liu, X.; Zheng, T. and Li, X. 2014. Spatial differentiation of prokaryotes enhancing performance of co-fermentation with straw and swine manure. CIESC Journal 65:1792-1799.).

In the present study, the abundance of the Rikenellaceae_RC9_gut_group, Lachnospiraceae_NA, Ruminococcaceae_UCG-014, Lachnospiraceae_NK3A20_group, Erysipelotrichaceae_UCG-004, and Fibrobacter in the ration group was significantly lower than that in the grazing group. Most of these species are associated with cellulose and hemicellulose degradation. Moreover, in the present study, the abundance of Succinivibrionaceae_NA was significantly increased and that of Succinivibrionaceae_UCG-001 showed an increasing trend, when the feeding method was switched from grazing to feedlot feeding. The genera of the Succinivibrionaceae family detected in the rumen mostly play a role in the degradation of starch (Santos and Thompson, 2014Santos, E. O. and Thompson, F. 2014. The Family Succinivibrionaceae. p.639-648. In: The Prokaryotes. 4th ed. Rosenberg E.; DeLong, E. F.; Lory, S.; Stackebrandt, E. and Thompson, F., eds. Springer, Berlin, Heidelberg.), which could explain the results of this study.

Conclusions

The different feeding methods employed in this study have no significant effect on the diversity of rumen bacteria in Tan sheep, but affect the structure of bacterial populations. The change in methods from grazing to feedlot feeding with higher levels of concentrate feed decreases the abundance of cellulolytic bacteria, but increases that of the Succinivibrionaceae family, which is associated with starch decomposition in this study.

Acknowledgments

The authors thank for the support of the National Natural Science Foundation of China (31660668).

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Publication Dates

  • Publication in this collection
    24 July 2020
  • Date of issue
    2020

History

  • Received
    23 Dec 2019
  • Accepted
    08 May 2020
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