Sun Huizeng, Wang Bing, Wang Jiakun, Liu Hongyun, Liu Jianxin
Institute of Dairy Science, MoE Key Laboratory of Molecular Animal Nutrition, College of Animal Sciences, Zhejiang University, Hangzhou, 310058 People's Republic of China.
J Anim Sci Biotechnol. 2016 Aug 31;7(1):49. doi: 10.1186/s40104-016-0107-7. eCollection 2016.
Alfalfa hay and corn stover are different type of forages which can significantly impact a cow's lactation performance, but the underlying metabolic mechanism has been poorly studied. We used biomarker and pathway analyses to characterize related biomarkers and pathways based on urine metabolomics data from different forage treatments. Urine was collected from 16 multiparous Holstein dairy cows fed alfalfa hay (AH, high-quality forage, n = 8) and corn stover (CS, low-quality forage, n = 8) respectively. Gas chromatography-time of flight/mass spectrometry (GC-TOF/MS) was performed to identify metabolites in urine and the metaboanalyst online platform was used to do biomarker and pathway analysis.
Hippuric acid (HUA) and N-methyl-glutamic (NML-Glu) indicated the most significant difference between the two diets, when statistically validated by biomarker analysis. HUA was also validated by standard compound quantitative method and showed significant higher concentration in CS group than AH group (2.8282 vs. 0.0005 mg/mL; P < 0.01). The significant negative correlation between milk yield and HUA (R(2) = 0.459; P < 0.01) and significant positive correlation between milk yield and NML-Glu (R(2) = 0.652; P < 0.01) were characterized. The pathway analysis revealed that these different metabolites were involved in 17 pathways including 7 influential pathways (pathway impact value > 0): Tyr metabolism, starch and sucrose metabolism, amino sugar and nucleotide sugar metabolism, galactose metabolism, Phe, Tyr and Try biosynthesis, purine metabolism, and glycerolipid metabolism. Based on the metabolome view map, the Phe, Tyr and Try biosynthesis pathway exhibited the highest impact value (0.50), and the Holm-Bonferroni multiple testing-based analysis revealed the most significant difference in the Tyr metabolism pathway (Holm P = 0.048).
The identified HUA and NML-Glu may serve as potential biomarkers for discriminating CS and AH diets and could be used as candidates for milk yield related mechanistic investigations. Integrated network pathways associated with related metabolites provide a helpful perspective for discovering the effectiveness of forage quality in lactation performance and provides novel insights into developing strategies for better utilization of CS and other low-quality forage in China.
苜蓿干草和玉米秸秆是不同类型的草料，它们会对奶牛的泌乳性能产生显著影响，但相关的代谢机制研究较少。我们基于不同草料处理的尿液代谢组学数据，通过生物标志物和通路分析来表征相关生物标志物和通路。分别从16头经产荷斯坦奶牛收集尿液，其中8头饲喂苜蓿干草（AH，优质草料），8头饲喂玉米秸秆（CS，劣质草料）。采用气相色谱 - 飞行时间质谱联用仪（GC - TOF/MS）鉴定尿液中的代谢物，并使用在线代谢组分析平台进行生物标志物和通路分析。
通过生物标志物分析进行统计学验证时，马尿酸（HUA）和N - 甲基谷氨酸（NML - Glu）显示出两种日粮之间最显著的差异。HUA也通过标准化合物定量方法得到验证，且CS组浓度显著高于AH组（2.8282对0.0005 mg/mL；P < 0.01）。研究发现牛奶产量与HUA之间存在显著负相关（R(2) = 0.459；P < 0.01），与NML - Glu之间存在显著正相关（R(2) = 0.652；P < 0.01）。通路分析表明，这些不同的代谢物参与了17条通路，包括7条有影响的通路（通路影响值> 0）：酪氨酸代谢、淀粉和蔗糖代谢、氨基糖和核苷酸糖代谢、半乳糖代谢、苯丙氨酸、酪氨酸和色氨酸生物合成、嘌呤代谢以及甘油脂质代谢。基于代谢组视图图谱，苯丙氨酸、酪氨酸和色氨酸生物合成通路显示出最高的影响值（0.50），基于霍尔姆 - 邦费罗尼多重检验的分析表明酪氨酸代谢通路差异最为显著（霍尔姆P = 0.048）。
鉴定出的HUA和NML - Glu可能作为区分CS和AH日粮的潜在生物标志物，并可作为与产奶量相关机制研究的候选指标。与相关代谢物相关的综合网络通路为发现草料质量对泌乳性能的影响提供了有益视角，并为中国更好地利用CS和其他劣质草料制定策略提供了新见解。
