Animal Bioscience

Asian Australasian Association of Animal Production Societies (아세아태평양축산학회)
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Metabolomics comparison of rumen fluid and milk in dairy cattle using proton nuclear magnetic resonance spectroscopy

  • Eom, Jun Sik (Division of Applied Life Science (BK21Four), Gyeongsang National University) ;
  • Kim, Eun Tae (National Institute of Animal Science, Rural Development Administration) ;
  • Kim, Hyun Sang (Division of Applied Life Science (BK21Four), Gyeongsang National University) ;
  • Choi, You Young (Division of Applied Life Science (BK21Four), Gyeongsang National University) ;
  • Lee, Shin Ja (Institute of Agriculture and Life Science & University-Centered Labs, Gyeongsang National University) ;
  • Lee, Sang Suk (Ruminant Nutrition and Anaerobe Laboratory, College of Bio-industry Science, Sunchon National University) ;
  • Kim, Seon Ho (Ruminant Nutrition and Anaerobe Laboratory, College of Bio-industry Science, Sunchon National University) ;
  • Lee, Sung Sill (Division of Applied Life Science (BK21Four), Gyeongsang National University)
  • Received : 2020.03.31
  • Accepted : 2020.06.05
  • Published : 2021.02.01
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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.

Keywords

References

  1. Xu C, Sun L, Xia C, Zhang H, Zheng J, Wang J. 1H-nuclear magnetic resonance-based plasma metabolic profiling of dairy cows with fatty liver. Asian-Australas J Anim Sci 2016;29:219-29. https://doi.org/10.5713/ajas.15.0439
  2. Nicholson JK, Lindon JC, Holmes E. 'Metabonomics': understanding the metabolic responses of living systems to pathophysiological stimuli via multivariate statistical analysis of biological NMR spectroscopic data. Xenbiotica 1999;29:1181-9. https://doi.org/10.1080/004982599238047
  3. Tikunov AP, Johnson CB, Lee H, Stoskopf MK, Macdonald JM. Metabolomic investigations of American oysters using 1H-NMR spectroscopy. Mar Drugs 2010;8:2578-96. https://doi.org/10.3390/md8102578
  4. Zhu C, Li C, Wang Y, Laghi L. Characterization of yak common biofluids metabolome by means of proton nuclear magnetic resonance spectroscopy. Metabolites 2019;9:41. https://doi.org/10.3390/metabo9030041
  5. Wishart DS. Metabolomics: applications to food science and nutrition research. Trends Food Sci Technol 2008;19:482-93. https://doi.org/10.1016/j.tifs.2008.03.003
  6. O'Callaghan TF, Vazquez-Fresno R, Serra-Cayuela A, et al. Pasture feeding changes the bovine rumen and milk metabolome. Metabolites 2018;8:27. https://doi.org/10.3390/metabo8020027
  7. Zhang H, Tong J, Zhang Y, Xiong B, Jiang L. Metabolomics reveals potential biomarkers in the rumen fluid of dairy cows with different levels of milk production. Asian-Australas J Anim Sci 2020;33:79-90. https://doi.org/10.5713/ajas.19.0214
  8. Nyberg NT, Nielsen MO, Jaroszewski JW. Metabolic trajectories based on 1H NMR spectra of urines from sheep exposed to nutritional challenges during prenatal and early postnatal life. Metabolomics 2010;6:489-96. https://doi.org/10.1007/s11306-010-0229-4
  9. Klein MS, Buttchereit N, Miemczyk SP, et al. NMR metabolomic analysis of dairy cows reveals milk glycerophosphocholine to phosphocholine ratio as prognostic biomarker for risk of ketosis. J Proteome Res 2012;11:1373-81. https://doi.org/10.1021/pr201017n
  10. Yang Y, Zheng N, Zhao X, et al. Metabolomic biomarkers identify differences in milk produced by Holstein cows and other minor dairy animals. J Proteom 2016;136:174-82. https://doi.org/10.1016/j.jprot.2015.12.031
  11. Lee J, Choi M, Kang J, et al. Physicochemical, structural, pasting, and rheological properties of potato starch isolated from different cultivars. Korean J Food Sci Technol 2017;49:360-8. https://doi.org/10.9721/KJFST.2017.49.4.360
  12. Jung JY, Jung Y, Kim JS, Ryu DH, Hwang GS. Assessment of peeling of Astragalus roots using 1H NMR- and UPLC-MS-based metabolite profiling. J Agric Food Chem 2013;61:10398-407. https://doi.org/10.1021/jf4026103
  13. Jeong JY, Hwang GS, Park JC, Kim DH, Ha M. 1H NMR-based urinary metabolic profiling of gender and diurnal variation in healthy Korean subjects. Environ Anal Health Toxicol 2010;25:295-306.
  14. Jeong JY, Kim MS, Jung HJ, Kim MJ, Lee HJ, Lee SD. Screening of the liver, serum, and urine of piglets fed zearalenone using a NMR-based metabolomic approach. Korean J Agric Sci 2018;45:447-54. https://doi.org/10.7744/kjoas.20180041
  15. Kim MS, Kim IY, Sung HR, et al. Metabolic dysfunction following weight regain compared to initial weight gain in a high-fat diet-induced obese mouse model. J Nutr Biochem 2019;69:44-52. https://doi.org/10.1016/j.jnutbio.2019.02.011
  16. Eom JS, Lee SJ, Lee YG, Lee SS. Comparison of volatile fatty acids, monosaccharide analysis and metabolic profiling in rumen fluid according to feeding methods. J Korea Acad Ind Coop Soc 2018;19:814-24. https://doi.org/10.5762/KAIS.2018.19.12.814
  17. Eom JS, Lee SJ, Lee SK, et al. Effects of different roughage to concentrate ratios on the changes of productivity and metabolic profiles in milk of dairy cows. Korean J Org Agric 2019;27:147-60. https://doi.org/10.11625/KJOA.2019.27.2.147
  18. Saleem F, Bouatra S, Guo AC, et al. The bovine ruminal fluid metabolome. Metabolomics 2013;9:360-78. https://doi.org/10.1007/s11306-012-0458-9
  19. Eriksson L. Introduction to multi-and megavariate data analysis using projection methods (PCA & PLS). Champaign, IL, USA: Umetrics AB; 1999.
  20. Jiang G, Leem JY. Comparative analysis of cultivation region of Angelica gigas using a GC-MS-based metabolomics approach. Korean J Med Crop Sci 2016;24:93-100. https://doi.org/10.7783/KJMCS.2016.24.2.93
  21. Nocek JE. Bovine acidosis: implications on laminitis. J Dairy Sci 1997;80:1005-28. https://doi.org/10.3168/jds.S0022-0302(97)76026-0
  22. Ametaj BN, Zebeli Q, Saleem F, et al. Metabolomics reveals unhealthy alterations in rumen metabolism with increased proportion of cereal grain in the diet of dairy cows. Metabolomics 2010;6:583-94. https://doi.org/10.1007/s11306-010-0227-6
  23. Wang DS, Zhang RY, Zhu WY, Mao SY. Effects of subacute ruminal acidosis challenges on fermentation and biogenic amines in the rumen of dairy cows. Livest Sci 2013;155:262-72. https://doi.org/10.1016/j.livsci.2013.05.026
  24. Sato H, Shiogama Y. Acetone and isopropanol in ruminal fluid and feces of lactating dairy cows. J Vet Med Sci 2010;72:297-300. https://doi.org/10.1292/jvms.09-0227
  25. Sundekilde UK, Larsen LB, Bertram HC. NMR-Based milk metabolomics. Metabolites 2013;3:204-22. https://doi.org/10.3390/metabo3020204
  26. Sundekilde UK, Poulsen NA, Larsen LB, Bertram HC. Nuclear magnetic resonance metabonomics reveals strong association between milk metabolites and somatic cell count in bovine milk. J Dairy Sci 2013;96:290-9. https://doi.org/10.3168/jds.2012-5819
  27. Sundekilde UK, Frederiksen PD, Clausen MR, Larsen LB, Bertram HC. Relationship between the metabolite profile and technological properties of bovine milk from two dairy breeds elucidated by NMR-based metabolomics. J Agric Food Chem 2011;59:7360-7. https://doi.org/10.1021/jf202057x
  28. Hu F, Furihata K, Ito-Ishida M, Kaminogawa S, Tanokura M. Nondestructive observation of bovine milk by NMR spectroscopy: analysis of existing states of compounds and detection of new compounds. J Agric Food Chem 2004;52:4969-74. https://doi.org/10.1021/jf049616o
  29. Hu F, Furihata K, Kato Y, Tanokura M. Nondestructive quantification of organic compounds in whole milk without pretreatment by two-dimensional NMR spectroscopy. J Agric Food Chem 2007;55:4307-11. https://doi.org/10.1021/jf062803x
  30. Lamanna R, Braca A, Di Paolo E, Imparato G. Identification of milk mixtures by 1H NMR profiling. Magn Reson Chem 2011;49(Suppl 1):S22-6. https://doi.org/10.1002/mrc.2807

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