Department of Chemistry, Oregon State University, Corvallis 97331.
Department of Veterinary Clinical Sciences, Oregon State University, Corvallis 97331.
J Dairy Sci. 2018 Jun;101(6):5531-5548. doi: 10.3168/jds.2017-13977. Epub 2018 Mar 21.
Clinical mastitis (CM), the most prevalent and costly disease in dairy cows, is diagnosed most commonly shortly after calving. Current indicators do not satisfactorily predict CM. This study aimed to develop a robust and comprehensive mass spectrometry-based metabolomic and lipidomic workflow using untargeted ultra-performance liquid chromatography high-resolution mass spectrometry for predictive biomarker detection. Using a nested case-control design, we measured weekly during the prepartal transition period differences in serum metabolites, lipids, inflammation markers, and minerals between clinically healthy Holstein dairy cows diagnosed with mastitis postcalving (CMP; n = 8; CM diagnosis d 1 = 3 cows, d 2 = 2 cows, d 4 = 1 cow; d 25 = 1 cow, and d 43 = 1 cow that had subclinical mastitis since d 3) or not (control; n = 9). The largest fold differences between CMP and control cows during the prepartal transition period were observed for 3'-sialyllactose in serum. Seven metabolites (N-methylethanolamine phosphate, choline, phosphorylcholine, free carnitine, trimethyl lysine, tyrosine, and proline) and 3 metabolite groups (carnitines, AA metabolites, and water-soluble phospholipid metabolites) could correctly classify cows for their future CM status at both 21 and 14 d before calving. Biochemical analysis using lipid and metabolite-specific commercial diagnostic kits supported our mass spectrometry-based omics results and additionally showed elevated inflammatory markers (serum amyloid A and visfatin) in CMP cows. In conclusion, metabolic phenotypes (i.e., metabotype) with elevated protein and lipid metabolism and inflammation may precede CM in prepartal transition dairy cows. The discovered serum metabolites and lipids may assist in predictive diagnostics, prevention strategies, and early treatment intervention against CM, and thereby improve cow health and welfare.
临床乳腺炎(CM)是奶牛中最常见和最昂贵的疾病,通常在产后不久就被诊断出来。目前的指标不能令人满意地预测 CM。本研究旨在开发一种稳健且全面的基于质谱的代谢组学和脂质组学工作流程,使用无靶向超高效液相色谱高分辨率质谱法进行预测性生物标志物检测。使用嵌套病例对照设计,我们在产前过渡期每周测量临床健康荷斯坦奶牛之间的血清代谢物、脂质、炎症标志物和矿物质差异,这些奶牛产后被诊断为乳腺炎(CMP;n=8;CM 诊断 d1=3 头奶牛,d2=2 头奶牛,d4=1 头奶牛;d25=1 头奶牛,d43=1 头奶牛从 d3 开始患有亚临床乳腺炎)或未患有乳腺炎(对照;n=9)。在产前过渡期,CMP 和对照奶牛之间最大的折叠差异是血清中的 3'-唾液酸乳糖。在分娩前 21 天和 14 天,有 7 种代谢物(N-甲乙醇胺磷酸盐、胆碱、磷酸胆碱、游离肉碱、三甲赖氨酸、酪氨酸和脯氨酸)和 3 种代谢物组(肉碱、AA 代谢物和水溶性磷脂代谢物)可以正确分类奶牛未来的 CM 状态。使用脂质和代谢物特异性商业诊断试剂盒进行的生化分析支持了我们基于质谱的组学结果,并额外显示了 CMP 奶牛中升高的炎症标志物(血清淀粉样蛋白 A 和内脂素)。总之,在产前过渡期奶牛中,代谢表型(即代谢型)可能与蛋白质和脂质代谢以及炎症升高有关,可能先于 CM。发现的血清代谢物和脂质可能有助于 CM 的预测性诊断、预防策略和早期治疗干预,从而改善奶牛的健康和福利。