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Journal of Integrative Agriculture  2016, Vol. 15 Issue (11): 2596-2603    DOI: 10.1016/S2095-3119(16)61346-1
Animal Science · Veterinary Science Advanced Online Publication | Current Issue | Archive | Adv Search |
Diversity shifts of rumen bacteria induced by dietary forages in dairy cows and quantification of the changed bacteria using a new primer design strategy
JIN Di1, 2*, ZHAO Sheng-guo1*, ZHANG Yang-dong1, SUN Peng1, BU Deng-pan1, Yves Beckers2, WANG Jia-qi1
1 State Key Laboratory of Animal Nutrition, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, P.R.China
2 Animal Science Unit, Gembloux Agro-Bio Tech, University of Liège, Gembloux 5030, Belgium
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Abstract      The partial 16S rRNA gene sequences (100 to 500 bp) were widely used to reveal rumen bacterial composition influenced by diets, while quantification of the changed uncultured bacteria was inconvenient due to difficult designing of specific primers based on short sequences. This study evaluated the effect of forage resources on rumen bacterial diversity and developed new strategy for primer design based on short sequences to quantify the changed uncultured bacteria. Denaturing gradient gel electrophoresis (DGGE) analysis and subsequent band sequencing were used to reveal the distinct rumen bacteria composition in cows fed with two forage sources (single corn stover vs. mixed forages including alfalfa hay and corn silage). The bacterial diversity in the rumen of dairy cows fed with corn stover was lower than that with mixed forages (P<0.05). The bacterium named R-UB affiliating to uncultured Succinivibrionaceae was identified, and it was abundant in the rumen of cows fed with mixed forages compared to corn stover. The full length 16S rRNA gene sequences with identity of >97% to the R-UB 16S rRNA gene sequence were obtained from GenBank and used to design specific primers to quantify uncultured bacterium R-UB. All sequences of amplicon from the new primers were of 100% identity to R-UB sequences indicating the high specificity of new primers. Quantitative PCR confirmed that abundance of R-UB in the rumen of cows fed with corn stover was lower than those fed with mixed forages (P<0.01). New strategy for designing primers based on partial 16S rRNA genes to quantify targeted uncultured bacteria was successfully developed. The rumen bacteria descending significantly in the cows fed corn stover compared to those fed mixed forages was identified as uncultured R-UB from Succinivibrionaceae.
Keywords:  rumen        bacterial diversity        forage source        primers        qPCR  
Received: 23 November 2015   Accepted:
Fund: 

This work was supported by the National Natural Science Foundation of China (31261140365), the National Basic Research Program of China (2011CB100804) and the Agricultural Science and Technology Innovation Program of Chinese Academy of Agricultural Sciences (ASTIP-IAS12).

Corresponding Authors:  WANG Jia-qi, Tel: +86-10-62816069, Fax: +86-10-62897587, E-mail: jiaqiwang@vip.163.com; BU Deng-pan, Tel: +86-10-62815833, Fax: +86-10-62897587, E-mail: budengpan@126.com   
About author:  JIN Di, E-mail: jindi0718@163.com; ZHAO Sheng-guo, E-mail: zhaoshengguo1984@163.com;

Cite this article: 

JIN Di, ZHAO Sheng-guo, ZHANG Yang-dong, SUN Peng, BU Deng-pan, Yves Beckers, WANG Jia-qi. 2016. Diversity shifts of rumen bacteria induced by dietary forages in dairy cows and quantification of the changed bacteria using a new primer design strategy. Journal of Integrative Agriculture, 15(11): 2596-2603.

Allen M S. 2000. Effects of diet on short-term regulation of feed intake by lactating dairy cattle. Journal of Dairy Science, 83, 1598–1624.

Carberry C A, Kenny D A, Han S, McCabe M S, Waters S M. 2012. Effect of phenotypic residual feed intake and dietary forage content on the rumen microbial community of beef cattle. Applied and Environmental Microbiology, 78, 4949–4958.

Creevey C J, Kelly W J, Henderson G, Leahy S C. 2014. Determining the culturability of the rumen bacterial microbiome. Microbial Biotechnology, 7, 467–479.

Fernando S C, Purvis H T, Najar F Z, Sukharnikov L O, Krehbiel C R, Nagaraja T G, Roe B A, Desilva U. 2010. Rumen microbial population dynamics during adaptation to a high-grain diet. Applied and Environmental Microbiology, 76, 7482–7490.

Fu Q, Ruegger P, Bent E, Chrobak M, Bomeman J. 2008. PRISE (PRImer SElector): Software for designing sequence-selective PCR primers. Journal of Medical Microbiology, 72, 263–267.

Hristov A, Price W, Shafii B. 2004. A meta-analysis examining the relationship among dietary factors, dry matter intake, and milk and milk protein yield in dairy cows. Journal of Dairy Science, 87, 2184–2196.

Huse S M, Dethlefsen L, Huber J A, Welch D M, Relman D A, Sogin M L. 2008. Exploring microbial diversity and taxonomy using SSU rRNA hypervariable tag sequencing. PLoS Genetics, 4, e1000255.

Huws S A, Lee M R, Muetzel S M, Scott M B, Wallace R J, Scollan N D. 2010. Forage type and fish oil cause shifts in rumen bacterial diversity. FEMS Microbiology Ecology, 73, 396–407.

Kamra D N. 2005. Rumen microbial ecosystem. Current Science, 89, 124–135.

Kawai M, Matsutera E, Kanda H, Yamaguchi N, Tani K, Nasu M. 2002. 16S ribosomal DNA-based analysis of bacterial diversity in purified water used in pharmaceutical manufacturing processes by PCR and denaturing gradient gel electrophoresis. Applied and Environmental Microbiology, 68, 699–704.

Kim M, Yu Z. 2012. Quantitative comparisons of select cultured and uncultured microbial populations in the rumen of cattle fed different diets. Journal of Animal Science and Biotechnology, 3, 28.

Kong Y, Teather R, Forster R. 2010. Composition, spatial distribution, and diversity of the bacterial communities in the rumen of cows fed different forages. FEMS Microbiology Ecology, 74, 612–622.

Li D, Wang J Q, Bu D P. 2012. Ruminal microbe of biohydrogenation of trans-vaccenic acid to stearic acid in vitro. BMC Research Notes, 5, 97.

Liu J, Wang J K, Zhu W, Pu Y Y, Guan L L, Liu J X. 2014. Monitoring the rumen pectinolytic bacteria Treponema saccharophilum using real-time PCR. FEMS Microbiology Ecology, 87, 576–585.

Minas K, McEwan N R, Newbold C J, Scott K P. 2011. Optimization of a high-throughput CTAB-based protocol for the extraction of qPCR-grade DNA from rumen fluid, plant and bacterial pure cultures. FEMS Microbiology Letters, 325, 162–169.

Pang Y Z, Liu Y P, Li X J, Wang K S, Yuan H R. 2008. Improving biodegradability and biogas production of corn stover through sodium hydroxide solid state pretreatment. Energy and Fuels, 22, 2761–2766.

Pawluczyk M, Weiss J, Links M G, Egana Aranguren M, Wilkinson M D, Egea-Cortines M. 2015. Quantitative evaluation of bias in PCR amplification and next-generation sequencing derived from metabarcoding samples. Analytical and Bioanalytical Chemistry, 407, 1841–1848.

Pinto A J, Raskin L. 2012. PCR biases distort bacterial and archaeal community structure in pyrosequencing datasets. PLoS ONE, 7, e43093.

Pruesse E, Peplies J, Glockner F O. 2012. SINA: Accurate high-throughput multiple sequence alignment of ribosomal RNA genes. Bioinformatics, 28, 1823–1829.

Sadet S, Martin C, Meunier B, Morgavi D P. 2007. PCR-DGGE analysis reveals a distinct diversity in the bacterial population attached to the rumen epithelium. Animal, 1, 939–944.

Santos E, Thompson F. 2014. The family Succinivibrionaceae. In: Rosenberg E, DeLong E, Lory S, Stackebrandt E, Thompson F, eds., The Prokaryotes. Springer, Berlin Heidelberg. pp. 639–648.

Saro C, Ranilla M J, Carro M D. 2012. Postprandial changes of fiber-degrading microbes in the rumen of sheep fed diets varying in type of forage as monitored by real-time PCR and automated ribosomal intergenic spacer analysis. Journal of Animal Science, 90, 4487–4494.

SAS (Statistical Analysis System). 2000. SAS User’s Guide: Statistics. ver. 8.01. SAS Institute Inc., Cary, NC.

Shaw C. 2010. Analysis of rumen bacterial populations in dairy cattle fed different forages. Ph D thesis, The Ohio State University, Columbus, USA.

Stevenson D M, Weimer P J. 2007. Dominance of Prevotella and low abundance of classical ruminal bacterial species in the bovine rumen revealed by relative quantification real-time PCR. Applied Microbiology and Biotechnology, 75, 165–174.

Stiverson J, Morrison M, Yu Z. 2011. Populations of select cultured and uncultured bacteria in the rumen of sheep and the effect of diets and ruminal fractions. International Journal of Microbiology, doi: 10.1155/2011/750613

Thoetkiattikul H, Mhuantong W, Laothanachareon T, Tangphatsornruang S, Pattarajinda V, Eurwilaichitr L, Champreda V. 2013. Comparative analysis of microbial profiles in cow rumen fed with different dietary fiber by tagged 16S rRNA gene pyrosequencing. Current Microbiology, 67, 130–137.

Wanapat M, Cherdthong A. 2009. Use of real-time PCR technique in studying rumen cellulolytic bacteria population as affected by level of roughage in swamp buffalo. Current Microbiology, 58, 294–299.

Wanapat M, Khampa S. 2007. Effect of levels of supplementation of concentrate containing high levels of cassava chip on rumen ecology, microbial N supply and digestibility of nutrients in beef cattle. Asian-Australasian Journal of Animal Sciences, 20, 75–81.

Wang J Q. 2011. Five key indicators leading the direction of China dairy industry. China Animal Husbandry and Veterinary Medicine, 38, 5–9. (in Chinese)

Welkie D G, Stevenson D M, Weimer P J. 2010. ARISA analysis of ruminal bacterial community dynamics in lactating dairy cows during the feeding cycle. Anaerobe, 16, 94–100.

Wu S, Baldwin R L, Li W, Li C, Connor E E, Li R W. 2012. The bacterial community composition of the bovine rumen detected using pyrosequencing of 16S rRNA genes. Metagenomics, 1, 1–11.

Yu Z, Michel Jr F C, Hansen G, Wittum T, Morrison M. 2005. Development and application of real-time PCR assays for quantification of genes encoding tetracycline resistance. Applied and Environment Microbiology, 71, 6926–6933.

Zhang R, Zhu W, Zhu W, Liu J, Mao S. 2014. Effect of dietary forage sources on rumen microbiota, rumen fermentation and biogenic amines in dairy cows. Journal of the Science of Food and Agriculture, 94, 1886–1895.

Zhao S, Zhao J, Bu D, Sun P, Wang J, Dong Z. 2014. Metabolomics analysis reveals large effect of roughage types on rumen microbial metabolic profile in dairy cows. Letters in Appied Microbiology, 59, 79–85.

Zhu W, Fu Y, Wang B, Wang C, Ye J A, Wu Y M, Liu J X. 2013. Effects of dietary forage sources on rumen microbial protein synthesis and milk performance in early lactating dairy cows. Journal of Dairy Science, 96, 1727–1734.
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