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http://dx.doi.org/10.5713/ajas.17.0167

Analysis of metabolomic patterns in thoroughbreds before and after exercise  

Jang, Hyun-Jun (College of Pharmacy, Dankook University)
Kim, Duk-Moon (Department of Animal Biotechnology, College of Applied Life Sciences, Jeju National University)
Kim, Kyu-Bong (College of Pharmacy, Dankook University)
Park, Jeong-Woong (Department of Animal Science, College of Natural Resources and Life Sciences, Pusan National University)
Choi, Jae-Young (Department of Animal Science, College of Natural Resources and Life Sciences, Pusan National University)
Oh, Jin Hyeog (Department of Animal Science, College of Natural Resources and Life Sciences, Pusan National University)
Song, Ki-Duk (Department of Animal Biotechnology, Chonbuk National University)
Kim, Suhkmann (Department of Chemistry and Chemistry Institute for Functional Materials, Pusan National University)
Cho, Byung-Wook (Department of Animal Science, College of Natural Resources and Life Sciences, Pusan National University)
Publication Information
Asian-Australasian Journal of Animal Sciences / v.30, no.11, 2017 , pp. 1633-1642 More about this Journal
Abstract
Objective: Evaluation of exercise effects in racehorses is important in horseracing industry and animal health care. In this study, we compared metabolic patterns between before and after exercise to screen metabolic biomarkers for exercise effects in thoroughbreds. Methods: The concentration of metabolites in muscle, plasma, and urine was measured by $^1H$ nuclear magnetic resonance (NMR) spectroscopy analysis and the relative metabolite levels in the three samples were compared between before and after exercise. Subsequently, multivariate data analysis based on the metabolic profiles was performed using orthogonal partial least square discriminant analysis (OPLS-DA) and variable important plots and t-test was used for basic statistical analysis. Results: From $^1H$ NMR spectroscopy analysis, 35, 25, and 34 metabolites were detected in the muscle, plasma, and urine. Aspartate, betaine, choline, cysteine, ethanol, and threonine were increased over 2-fold in the muscle; propionate and trimethylamine were increased over 2-fold in the plasma; and alanine, glycerol, inosine, lactate, and pyruvate were increased over 2-fold whereas acetoacetate, arginine, citrulline, creatine, glutamine, glutarate, hippurate, lysine, methionine, phenylacetylglycine, taurine, trigonelline, trimethylamine, and trimethylamine N-oxide were decreased below 0.5-fold in the urine. The OPLS-DA showed clear separation of the metabolic patterns before and after exercise in the muscle, plasma, and urine. Statistical analysis showed that after exercise, acetoacetate, arginine, glutamine, hippurate, phenylacetylglycine trimethylamine, trimethylamine N-oxide, and trigonelline were significantly decreased and alanine, glycerol, inosine, lactate, and pyruvate were significantly increased in the urine (p<0.05). Conclusion: In conclusion, we analyzed integrated metabolic patterns in the muscle, plasma, and urine before and after exercise in racehorses. We found changed patterns of metabolites in the muscle, plasma, and urine of racehorses before and after exercise.
Keywords
Racehorse; Thoroughbred; Metabolic Analysis; Exercise;
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1 Ball D. Metabolic and endocrine response to exercise: sympathoadrenal integration with skeletal muscle. J Endocrinol 2015;224:R79-95.   DOI
2 Hargreaves M. Skeletal muscle metabolism during exercise in humans. Clin Exp Pharmacol Physiol 2000;27:225-8.   DOI
3 Van Hall G, Jensen-Urstad M, Rosdahl H, et al. Leg and arm lactate and substrate kinetics during exercise. Am J Physiol Endocrinol Metab 2003;284:E193-205.   DOI
4 Lewis GD, Farrell L, Wood MJ, et al. Metabolic signatures of exercise in human plasma. Sci Transl Med 2010;2:33ra7.
5 Olesen J, Gliemann L, Bienso R, et al. Exercise training, but not resveratrol, improves metabolic and inflammatory status in skeletal muscle of aged men. J Physiol 2014;592:1873-86.   DOI
6 Pierce GL, Donato AJ, LaRocca TJ, et al. Habitually exercising older men do not demonstrate age-associated vascular endothelial oxidative stress. Aging Cell 2011;10:1032-7.   DOI
7 Henderson GC, Alderman BL. Determinants of resting lipid oxidation in response to a prior bout of endurance exercise. J Appl Physiol 2014;116:95-103.   DOI
8 Kjaer M, Galbo H. Effect of physical training on the capacity to secrete epinephrine. J Appl Physiol 1988;64:11-6.   DOI
9 Rivero JL, Hill EW. Skeletal muscle adaptations and muscle genomics of performance horses. Vet J 2016;209:5-13.   DOI
10 Geor RJ, Hinchcliff KW, McCutcheon LJ, Sams RA. Epinephrine inhibits exogenous glucose utilization in exercising horses. J Appl Physiol 2000;88:1777-90.   DOI
11 Brojer J, Holm S, Jonasson R, Hedenstrom U, Essen-Gustavsson B. Synthesis of proglycogen and macroglycogen in skeletal muscle of standardbred trotters after intermittent exercise. Equine Vet J Suppl 2006;38:335-9.   DOI
12 Kim KB, Um SY, Chung MW, et al. Toxicometabolomics approach to urinary biomarkers for mercuric chloride ($HgCl_{2}$)-induced nephrotoxicity using proton nuclear magnetic resonance ($^{1}H$ NMR) in rats. Toxicol Appl Pharmacol 2010;249:114-26.   DOI
13 Waller AP, Heigenhauser GJ, Geor RJ, Spriet LL, Lindinger MI. Fluid and electrolyte supplementation after prolonged moderate-intensity exercise enhances muscle glycogen resynthesis in Standardbred horses. J Appl Physiol 2009;106:91-100.   DOI
14 Jang HJ, Kim JW, Ryu SH, et al. Metabolic profiling of antioxidant supplement with phytochemicals using plasma 1H NMR-based metabolomics in humans. J Funct Foods 2016;24:112-21.   DOI
15 Barding GA, Jr., Salditos R, Larive CK. Quantitative NMR for bioanalysis and metabolomics. Anal Bioanal Chem 2012;404:1165-79.   DOI
16 van den Berg RA, Hoefsloot HC, Westerhuis JA, Smilde AK, van der Werf MJ. Centering, scaling, and transformations: improving the biological information content of metabolomics data. BMC Genomics 2006;7:142.   DOI
17 Zang Q, Keire DA, Wood RD, et al. Class modeling analysis of heparin 1H NMR spectral data using the soft independent modeling of class analogy and unequal class modeling techniques. Anal Chem 2011;83:1030-9.   DOI
18 Xia J, Sinelnikov IV, Han B, Wishart DS. MetaboAnalyst 3.0-making metabolomics more meaningful. Nucleic Acids Res 2015;43:W251-7.   DOI
19 German JB, Hammock BD, Watkins SM. Metabolomics: building on a century of biochemistry to guide human health. Metabolomics 2005;1:3-9.   DOI
20 Oresic M, Vidal-Puig A, Hanninen V. Metabolomic approaches to phenotype characterization and applications to complex diseases. Expert Rev Mol Diagn 2006;6:575-85.   DOI
21 Moore RE, Kirwan J, Doherty MK, Whitfield PD. Biomarker discovery in animal health and disease: the application of post-genomic technologies. Biomark Insights 2007;2:185-96.
22 Weckwerth W. Metabolomics in systems biology. Annu Rev Plant Biol 2003;54:669-89.   DOI
23 Schauer N, Fernie AR. Plant metabolomics: towards biological function and mechanism. Trends Plant Sci 2006;11:508-16.   DOI
24 Kell DB. Metabolomics and systems biology: making sense of the soup. Curr Opin Microbiol 2004;7:296-307.   DOI
25 Nicholson JK, Connelly J, Lindon JC, Holmes E. Metabonomics: a platform for studying drug toxicity and gene function. Nat Rev Drug Discov 2002;1:153-61.   DOI
26 Hodgson DR, Rose RJ. The athletic horse. Principles and practice of equine sports medicine. Philadelphia, PA, USA: Saunders; 1994.
27 Brindle JT, Antti H, Holmes E, et al. Rapid and noninvasive diagnosis of the presence and severity of coronary heart disease using $^{1}H$-NMRbased metabonomics. Nat Med 2002;8:1439-44.   DOI
28 Whitfield PD, Noble PJM, Major H, et al. Metabolomics as a diagnostic tool for hepatology: validation in a naturally occurring canine model. Metabolomics 2005;1:215-25.   DOI
29 Dumas ME, Canlet C, Vercauteren J, Andre F, Paris A. Homeostatic signature of anabolic steroids in cattle using $^{1}H-^{13}C$ HMBC NMR metabonomics. J Proteome Res 2005;4:1493-502.   DOI
30 Evans DL. Physiology of equine performance and associated tests of function. Equine Vet J 2007;39:373-83.   DOI
31 Vervuert I. Energy metabolism of the performance horse. In: Proceedings of the 5th European Equine Nutrition & Health Congress 2011; 2011 Apr 15-16: Waregem, Belgium: The Scientific Committee of the European Equine Health and Nutrition Congress; 2011.
32 Vervuert I, Coenen M, Watermulder E. Metabolic responses to oral tryptophan supplementation before exercise in horses. J Anim Physiol Anim Nutr (Berl) 2005;89:140-5.   DOI
33 Dohm GL, Tabscott EB, Kasperek GJ. Protein degradation during exercise and recovery. Med Sci Sports Exerc Suppl 1987;189:166-71.
34 Struder KH, Hollmann W, Platen P, et al. lterations in plasma free tryptophan and large neutral amino acids do not affect perceived exertion and prolactin during 90 min of treadmill exercise. Int J Sports Med 1996;17:73-9.   DOI
35 Luck MM, Le Moyec L, Barrey E, et al. Energetics of endurance exercise in young horses determined by nuclear magnetic resonance metabolomics. Front Physiol 2015;6:198.
36 Shulman GI. Cellular mechanisms of insulin resistance in humans. Am J Cardiol 1999;84:3J-10J.
37 Adeva-Andany M, Lopez-Ojen M, Funcasta-Calderon R, et al. Comprehensive review on lactate metabolism in human health. Mitochondrion 2014;17:76-100.   DOI
38 Hubbard JL. The effect of exercise on lactate metabolism. J Physiol 1973;231:1-18.
39 Katz J, Tayek JA. Recycling of glucose and determination of the Cori Cycle and gluconeogenesis. Am J Physiol 1999;277:E401-7.
40 Leguina-Ruzzi A. Therapeutic targets of glutamine in parenteral nutrition: a medical science review. Int J Prev Treat 2015;4:34-9.