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ANIMAL NUTRITION |
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* Department of Animal and Veterinary Sciences, Clemson University, Clemson, SC 29634;
and
Rowett Research Institute, Bucksburn, Aberdeen AB21 9SB, United Kingdom;
and
University of Pennsylvania, Kennett Square 19348; and and
University of Idaho, Department of Animal and Veterinary Science, Moscow 83844
2 Corresponding author: tjnkns{at}clemson.edu
Recent advances in chromatographic identification of CLA isomers, combined with interest in their possible properties in promoting human health (e.g., cancer prevention, decreased atherosclerosis, improved immune response) and animal performance (e.g., body composition, regulation of milk fat synthesis, milk production), has renewed interest in biohydrogenation and its regulation in the rumen. Conventional pathways of biohydrogenation traditionally ignored minor fatty acid intermediates, which led to the persistence of oversimplified pathways over the decades. Recent work is now being directed toward accounting for all possible trans-18:1 and CLA products formed, including the discovery of novel bioactive intermediates. Modern microbial genetics and molecular phylogenetic techniques for identifying and classifying microorganisms by their small-subunit rRNA gene sequences have advanced knowledge of the role and contribution of specific microbial species in the process of biohydrogenation. With new insights into the pathways of biohydrogenation now available, several attempts have been made at modeling the pathway to predict ruminal flows of unsaturated fatty acids and biohydrogenation intermediates across a range of ruminal conditions. After a brief historical account of major past accomplishments documenting biohydrogenation, this review summarizes recent advances in 4 major areas of biohydrogenation: the microorganisms involved, identification of intermediates, the biochemistry of key enzymes, and the development and testing of mathematical models to predict biohydrogenation outcomes.
Key Words: biohydrogenation rumen microorganism conjugated linoleic acid modeling
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