~1H NMR And GC/MS Based Plasma Metabolic Profiling Of Dairy Cows With Ketosis

In some past researches, the exploration for pathogenesis of ketosis mainly focuses onphysiology, biochemistry and pathology. However, there is little report about the metabolomicsof ketosis. Therefore, this report has an important significance in this study to reveal the globalchange of life functions during the development of ketosis, enrich and develop the itspathogenesis. Ketosis is a metabolic disorder in dairy cattle. Primary or secondary ketosis canresult during early lactation. Generally, high milk production during lactation and/or inadequateenergy intakes result in a negative energy balance, which induces ketosis. Because ketosis canlead to substantial economic losses in the dairy industry, it is of outmost importance to preventketosis in dairy cattle.Through the application of metabolomics technology combines principal component analysis(PCA) and orthogonal partial least-squares discriminant analysis (OPLS-DA), changes ofendogenous metabolites with clinical and subclinical ketosis cows were analyzed, which to studythe affects of ketosis on cow metabolic process, and find the differences metabolites.In this study,80lactation Holstein cows were selected as experimental animals7to21dayspostpartum, at the same time experimental cow plasma samples were collected according to theplasma β-hydroxybutyrate (BHBA) concentration and clinical symptoms. Clinical ketosis groupsof cows (CK, n=24) showed obvious clinical symptoms postpartum and plasma BHBAconcentration is more than1.60mmol/L, subclinical ketosis groups of cows (SK, n=33) didn’tshow clinical symptoms postpartum and plasma BHBA concentration is more than1.20mmol/L;healthy groups of cows (C, n=23) had no clinical symptoms and plasma BHBA concentration isless than1.00mmol/L. Experimental animals selected had no other concurrency and secondarydiseases in addition to ketosis. The plasma metabolites were detected by1H nuclear magneticresonance (1H NMR) and gas chromatography/mass spectrometry (GC/MS) technique. Changesof metabolite contents were analyzed among3groups using principal component analysis andpartial lease squares. Finally, metabolites were analyzed by using bioinformatics technologybiology. The plasma metabolic profiles of the three groups were obtained by1H NMR. Compared withthe healthy control group,23different metabolites were obtained in subclinical and clinicalketosis groups, in which Acetylacetonate (ACAC), β-hydroxybutyric acid (BHBA), acetone andacetic acid, etc are increased, while histidine, lysine, glutamic acid, glutamine, lactic acid andglucose, etc are decreased. By comparison,28different metabolites were obtained betweenclinical ketosis group and subclinical ketosis group, in which BHBA, ACAC, and acetone, etcare increased, while citric acid, formic acid, histidine, alanine, proline, tyrosine, low densitylipoprotein, and very low density lipoprotein, etc are decreased. The plasma metabolome wasmeasured by GC/MS, which led to the detection of267variables. There were40types ofmetabolites without difference among3groups. Compared with the healthy control group,32different metabolites were obtained in subclinical and clinical ketosis groups, in which BHBA,α-aminobutyric acid, sitoesterol, isoleucine, leucine, glycine, myristic acid and palmitic acid, etcare increased, while glucose, lactose, glyoxylic acid, alanine, glutamic acid, lactic acid, etc aredecreased. By comparison,13different metabolites were obtained between clinical ketosis groupand subclinical ketosis group, in which heptadecanoic acid, stearic acid and3-hydroxy valericacid, etc are increased, while proline, serine, proline, α-aminobutyric acid and3,4-docosahexaenoic acid, etc are decreased. Through the KEGG database analysis, thesemetabolites primarily were related with amino acid metabolism, fat metabolism andcarbohydrate metabolism.The results showed1H NMR and GC/MS combined with pattern recognition technique caneffectively get the different metabolites of diagnosing clinical and subclinical ketosis. Thesubstances of different content and contributing to classification may be the potential metabolicmarker and objective indicators for diagnosing as ketosis, and panoramic reveal that widelymetabolic disorder on cows in the process of ketosis, which lays the foundation for theexploration of ketosis mechanism and obtaining new biomarkers in the future.