The partial 16 S r RNA 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 diffic...The partial 16 S r RNA 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（P0.05）. 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 16 S r RNA gene sequences with identity of 97% to the R-UB 16 S r RNA gene sequence were obtained from Gen Bank 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（P0.01）. New strategy for designing primers based on partial 16 S r RNA 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.展开更多
基金supported by the National Natural Science Foundation of China(31261140365)the National Basic Research Program of China(2011CB100804)the Agricultural Science and Technology Innovation Program of Chinese Academy of Agricultural Sciences(ASTIP-IAS12)
文摘The partial 16 S r RNA 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（P0.05）. 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 16 S r RNA gene sequences with identity of 97% to the R-UB 16 S r RNA gene sequence were obtained from Gen Bank 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（P0.01）. New strategy for designing primers based on partial 16 S r RNA 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.
