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ARS Home » Midwest Area » Madison, Wisconsin » U.S. Dairy Forage Research Center » Cell Wall Biology and Utilization Research » Research » Publications at this Location » Publication #228191

Title: A New HPLC Purine Assay for Quantifying Microbial Flow

item Broderick, Glen

Submitted to: Journal of Dairy Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 10/30/2008
Publication Date: 3/1/2009
Citation: Reynal, S.M., Broderick, G.A. 2009. A New HPLC Purine Assay for Quantifying Microbial Flow. Journal of Dairy Science. 92:1177-1181.

Interpretive Summary: The microbes living in the rumen, the first compartment of the cow’s stomach, make much of the protein that is used by dairy cows to produce milk. This protein is of very high quality and results in optimal nitrogen efficiency—the point at which the most milk protein is produced with the least loss of waste nitrogen in manure. So, finding out what factors influence the amount of microbial protein produced in the rumen is one of the most critical issues in dairy cattle nutrition. Dairy scientists use cows with rumen cannulas (holes put into their rumens by veterinarians using surgery) to measure the total amount of protein flowing out of the rumen. However, distinguishing between protein made by the rumen microbes and feed protein that has not yet been digested is difficult and requires using markers. Purines, which are components of the RNA and DNA in microbial cells, are among the best markers with which to measure the microbial protein in the digesta flowing out of the rumen. We applied chromatography, a technique that employs columns and solutions called solvents to separate chemicals one from another, in order to separate the true purines from their breakdown products that are produced in the rumen. These breakdown products interfere in the determination of true purines and can invalidate measurements of microbial protein flow based on use of purine markers. Our new procedure is much more accurate, giving about 100% recovery of purines when they are added to samples of digesta taken from the cow’s stomach. This research already has been applied in our laboratory in two experiments with dairy cows to determine the effects of feeding different carbohydrates and different proteins on microbial protein formation in the rumen. This research can be used by other dairy scientists to assess the effects of many other nutritional and management factors on protein formation by the rumen microbes, and whether these factors improve the economic and environmental sustainability of U.S. dairy production.

Technical Abstract: A HPLC method was developed to quantify the purines adenine and guanine and their metabolites xanthine and hypoxanthine in hydrolysates of isolated bacteria and omasal digesta and to assess the effect of using either purines only, or purines plus metabolites, as microbial markers for estimating microbial flow from the rumen. Individual purines and their metabolites were completely resolved on a C18 column using gradient elution with two mobile phases. Intra-assay CV ranged from 0.6 to 3.1%. Hydrolytic recovery of the 4 purine bases from their corresponding nucleosides averaged 101% (control), 103% (when added to bacterial isolates), and 104% (when added to omasal digesta). Mean concentrations of adenine, guanine, xanthine, and hypoxanthine were, respectively, 53, 58, 2.8, and 3.5 µmol/g of DM in omasal bacteria and 10, 12, 7.5, and 7.5 µmol/g of DM in omasal digesta, indicating that xanthine plus hypoxanthine represented 5% of total purines in bacterial hydrolysates but 41% of total purines in digesta hydrolysates. A significant negative relationship (R2 = 0.53) between the sum of adenine and guanine and the sum of xanthine and hypoxanthine in digesta samples (but not bacterial isolates) indicated that at least a portion of the adenine and guanine were recovered as xanthine and hypoxanthine. These results suggested that, when total purines are used as the microbial marker, both purines and their metabolites should be quantified and used to compute microbial nonammonia N and organic matter flows.