Jun Sik Eom1, Eun Tae Kim2, Hyun Sang Kim1, You Young Choi1, Shin Ja Lee3, Sang Suk Lee4, Seon Ho Kim4, Sung Sill Lee1,3. 1. Division of Applied Life Science (BK21Four), Gyeongsang National University, Jinju 52828, Korea. 2. National Institute of Animal Science, Rural Development Administration, Cheonan 31000, Korea. 3. Institute of Agriculture and Life Science & University-Centered Labs, Gyeongsang National University, Jinju 52828, Korea 4 Ruminant Nutrition and Anaerobe. 4. Ruminant Nutrition and Anaerobe Laboratory, College of Bio-industry Science, Sunchon National University, Suncheon 57922, Korea.
Abstract
OBJECTIVE: The metabolites that constitute the rumen fluid and milk in dairy cattle were analyzed using proton nuclear magnetic resonance (1H-NMR) spectroscopy and compared with the results obtain for other dairy cattle herds worldwide. The aim was to provide basic dataset for facilitating research on metabolites in rumen fluid and milk. METHODS: Six dairy cattle were used in this study. Rumen fluid was collected using a stomach tube, and milk was collected using a pipeline milking system. The metabolites were determined by 1H-NMR spectroscopy, and the obtained data were statistically analyzed by principal component analysis, partial least squares discriminant analysis, variable importance in projection scores, and metabolic pathway data using Metaboanalyst 4.0. RESULTS: The total numbers of metabolites in rumen fluid and milk were measured to be 186 and 184, and quantified as 72 and 109, respectively. Organic acid and carbohydrate metabolites exhibited the highest concentrations in rumen fluid and milk, respectively. Some metabolites that have been associated with metabolic diseases (acidosis and ketosis) in cows were identified in rumen fluid, and metabolites associated with ketosis, somatic cell production, and coagulation properties were identified in milk. CONCLUSION: The metabolites measured in rumen fluid and milk could potentially be used to detect metabolic diseases and evaluate milk quality. The results could also be useful for metabolomic research on the biofluids of ruminants in Korea, while facilitating their metabolic research.
OBJECTIVE: The metabolites that constitute the rumen fluid and milk in dairy cattle were analyzed using proton nuclear magnetic resonance (1H-NMR) spectroscopy and compared with the results obtain for other dairy cattle herds worldwide. The aim was to provide basic dataset for facilitating research on metabolites in rumen fluid and milk. METHODS: Six dairy cattle were used in this study. Rumen fluid was collected using a stomach tube, and milk was collected using a pipeline milking system. The metabolites were determined by 1H-NMR spectroscopy, and the obtained data were statistically analyzed by principal component analysis, partial least squares discriminant analysis, variable importance in projection scores, and metabolic pathway data using Metaboanalyst 4.0. RESULTS: The total numbers of metabolites in rumen fluid and milk were measured to be 186 and 184, and quantified as 72 and 109, respectively. Organic acid and carbohydrate metabolites exhibited the highest concentrations in rumen fluid and milk, respectively. Some metabolites that have been associated with metabolic diseases (acidosis and ketosis) in cows were identified in rumen fluid, and metabolites associated with ketosis, somatic cell production, and coagulation properties were identified in milk. CONCLUSION: The metabolites measured in rumen fluid and milk could potentially be used to detect metabolic diseases and evaluate milk quality. The results could also be useful for metabolomic research on the biofluids of ruminants in Korea, while facilitating their metabolic research.
Authors: Jun Sik Eom; Shin Ja Lee; Hyun Sang Kim; Youyoung Choi; Seong Uk Jo; Sang Suk Lee; Eun Tae Kim; Sung Sill Lee Journal: J Anim Sci Technol Date: 2022-03-31
Authors: Youyoung Choi; Shin Ja Lee; Hyun Sang Kim; Jun Sik Eom; Seong Uk Jo; Le Luo Guan; Jakyeom Seo; Hanbeen Kim; Sang Suk Lee; Sung Sill Lee Journal: Sci Rep Date: 2021-12-16 Impact factor: 4.379