Comparison of Ileum Microflora of Pigs Fed Corn-, Wheat-, or Barley-Based Diets by Chaperonin-60 Sequencing and Quantitative PCR
2005
Hill, Janet E. | Hemmingsen, Sean M. | Goldade, Blair G. | Dumonceaux, Tim J. | Klassen, Jonathan | Zijlstra, Ruurd T. | Goh, Swee Han | Van Kessel, Andrew G.
We have combined the culture-independent methods of high-throughput sequencing of chaperonin-60 PCR product libraries and quantitative PCR to profile and quantify the small-intestinal microflora of pigs fed diets based on corn, wheat, or barley. A total of 2,751 chaperonin-60 PCR product clones produced from samples of ileum digesta were examined. The majority (81%) of these clones contained sequences independently recovered from all three libraries; 372 different nucleotide sequences were identified, but only 14% of the 372 different sequences were recovered from all three libraries. Taxonomic assignments of the library sequences were made by comparison to a reference database of chaperonin-60 sequences combined with phylogenetic analysis. The taxa identified are consistent with previous reports of pig ileum microflora. Frequencies of each sequence in each library were calculated to identify taxa that varied in frequency between the corn, barley, and wheat libraries. The chaperonin-60 sequence inventory was used as a basis for designing PCR primer sets for taxon-specific quantitative PCR. Results of quantitative PCR analysis of ileum digesta confirmed the relative abundances of targeted taxa identified with the library sequencing approach. The results of this study indicate that chaperonin-60 clone libraries can be valid profiles of complex microbial communities and can be used as the basis for producing quantitative PCR assays to measure the abundance of taxa of interest during experimentally induced or natural changes in a community.
Afficher plus [+] Moins [-]Mots clés AGROVOC
Informations bibliographiques
Cette notice bibliographique a été fournie par National Agricultural Library
Découvrez la collection de ce fournisseur de données dans AGRIS