Key Laboratory of Dairy Cow Genetic Improvement and Milk Quality Research of Zhejiang Province, College of Animal Sciences, Zhejiang University, Hangzhou 310058, China; Ministry of Education Key laboratory of Molecular Animal Nutrition, Zhejiang University, Hangzhou 310058, China.
Key Laboratory of Dairy Cow Genetic Improvement and Milk Quality Research of Zhejiang Province, College of Animal Sciences, Zhejiang University, Hangzhou 310058, China; Ministry of Education Key laboratory of Molecular Animal Nutrition, Zhejiang University, Hangzhou 310058, China; Ministry of Education Innovation Team of Development and Function of Animal Digestive System, Zhejiang University, Hangzhou 310058, China.
J Dairy Sci. 2024 Jan;107(1):573-592. doi: 10.3168/jds.2022-23066. Epub 2023 Sep 9.
The transition period in dairy cows is a critical stage and peripartum oxidative status, negative energy balance (NEB), and inflammation are highly prevalent. Fecal microbial metabolism is closely associated with blood oxidative status and nonesterified fatty acids (NEFA) levels. Here, we investigated dynamic changes in total oxidative status markers and NEFA in blood, fecal microbiome, and metabolome of 30 dairy cows during transition (-21, -7, +7, +21 d relative to calving). Then the Bayesian network and 9 machine-learning algorithms were applied to dismantle their relationship. Our results show that the oxidative status indicator (OSI) of -21, -7, +7 d was higher than +21 d. The plasma concentration of NEFA peaked on +7 d. For fecal microenvironment, a decline in bacterial α diversity was observed at postpartum and in bacterial interactions at +7 d. Conversely, microbial metabolites involved in carbohydrate, lipid, and energy metabolism increased on +7 d. A correlation analysis revealed that 11 and 10 microbial metabolites contributed to OSI and NEFA variations, respectively (arc strength >0.5). The support vector machine (SVM) radial model showed the highest average predictive accuracy (100% and 88.9% in the test and external data sets) for OSI using 1 metabolite and 3 microbiota. The SVM radial model also showed the highest average diagnostic accuracy (100% and 91% in the test and external data sets) for NEFA with 2 metabolites and 3 microbiota. Our results reveal a relationship between variation in the fecal microenvironment and indicators of oxidative status, NEB, and inflammation, which provide a theoretical basis for the prevention and precise regulation of peripartum oxidative status and NEB.
奶牛的过渡期是一个关键阶段，围产期氧化状态、负氮平衡（NEB）和炎症非常普遍。粪便微生物代谢与血液氧化状态和非酯化脂肪酸（NEFA）水平密切相关。在这里，我们研究了 30 头奶牛在过渡期（产犊前-21、-7、+7、+21 天）血液、粪便微生物组和代谢组中的总氧化状态标志物和 NEFA 的动态变化。然后，我们应用贝叶斯网络和 9 种机器学习算法来拆解它们之间的关系。我们的结果表明，-21、-7、+7 天的氧化状态指标（OSI）高于+21 天。血浆 NEFA 浓度在+7 天达到峰值。对于粪便微环境，产后细菌 α多样性下降，+7 天细菌相互作用增加。相反，涉及碳水化合物、脂质和能量代谢的微生物代谢物在+7 天增加。相关性分析表明，11 种和 10 种微生物代谢物分别与 OSI 和 NEFA 的变化相关（弧强度>0.5）。支持向量机（SVM）径向模型使用 1 种代谢物和 3 种微生物群落对 OSI 的平均预测准确率最高（测试和外部数据集分别为 100%和 88.9%）。SVM 径向模型对 NEFA 的平均诊断准确率也最高（测试和外部数据集分别为 100%和 91%），使用 2 种代谢物和 3 种微生物群落。我们的结果揭示了粪便微环境变化与氧化状态、NEB 和炎症指标之间的关系，为围产期氧化状态和 NEB 的预防和精确调节提供了理论依据。
