Cardoso Ana S, Whitby Alison, Green Martin J, Kim Dong-Hyun, Randall Laura V
School of Veterinary Medicine and Science, University of Nottingham, Sutton Bonington Campus, Sutton Bonington, Leicestershire LE12 5RD, UK.
Centre for Analytical Bioscience, Advanced Materials & Healthcare Technologies Division, School of Pharmacy, University of Nottingham, Nottingham NG7 2RD, UK.
Animals (Basel). 2024 Jul 10;14(14):2030. doi: 10.3390/ani14142030.
The aim of this study was to identify with a high level of confidence metabolites previously identified as predictors of lameness and understand their biological relevance by carrying out pathway analyses. For the dairy cattle sector, lameness is a major challenge with a large impact on animal welfare and farm economics. Understanding metabolic alterations during the transition period associated with lameness before the appearance of clinical signs may allow its early detection and risk prevention. The annotation with high confidence of metabolite predictors of lameness and the understanding of interactions between metabolism and immunity are crucial for a better understanding of this condition. Using liquid chromatography-tandem mass spectrometry (LC-MS/MS) with authentic standards to increase confidence in the putative annotations of metabolites previously determined as predictive for lameness in transition dairy cows, it was possible to identify cresol, valproic acid, and gluconolactone as L1, L2, and L1, respectively which are the highest levels of confidence in identification. The metabolite set enrichment analysis of biological pathways in which predictors of lameness are involved identified six significant pathways ( < 0.05). In comparison, over-representation analysis and topology analysis identified two significant pathways ( < 0.05). Overall, our LC-MS/MS analysis proved to be adequate to confidently identify metabolites in urine samples previously found to be predictive of lameness, and understand their potential biological relevance, despite the challenges of metabolite identification and pathway analysis when performing untargeted metabolomics. This approach shows potential as a reliable method to identify biomarkers that can be used in the future to predict the risk of lameness before calving. Validation with a larger cohort is required to assess the generalization of these findings.
本研究的目的是高度确信地鉴定先前被确定为跛行预测指标的代谢物，并通过进行通路分析来了解它们的生物学相关性。对于奶牛养殖行业而言，跛行是一项重大挑战，对动物福利和农场经济有很大影响。了解在出现临床症状之前与跛行相关的过渡期代谢变化，可能有助于早期发现和预防风险。对跛行代谢物预测指标进行高度确信的注释以及了解代谢与免疫之间的相互作用，对于更好地理解这种情况至关重要。使用液相色谱 - 串联质谱法（LC-MS/MS）和真实标准品来提高对先前确定为过渡期奶牛跛行预测指标的代谢物假定注释的可信度，有可能分别将甲酚、丙戊酸和葡萄糖酸内酯鉴定为L1、L2和L1，这是鉴定中最高的置信水平。对涉及跛行预测指标的生物途径进行代谢物集富集分析，确定了六个显著途径（<0.05）。相比之下，过表达分析和拓扑分析确定了两个显著途径（<0.05）。总体而言，我们的LC-MS/MS分析证明足以可靠地鉴定先前发现可预测跛行的尿液样本中的代谢物，并了解它们潜在的生物学相关性，尽管在进行非靶向代谢组学时存在代谢物鉴定和途径分析的挑战。这种方法显示出作为一种可靠方法来鉴定生物标志物的潜力，这些生物标志物未来可用于预测产犊前跛行的风险。需要用更大的队列进行验证，以评估这些发现的普遍性。
