基于GC/MS技术的产后卵巢静止奶牛血浆代谢谱分析

doi:10.3864/j.issn.0578-1752.2017.15.018

摘要/Abstract

摘要： 【目的】运用代谢组学中气相色谱/质谱联用技术（GC/MS）筛选卵巢静止奶牛和正常发情奶牛的血浆差异代谢物，探究奶牛发生卵巢静止时其体内代谢的变化。【方法】在黑龙江省某集约化牛场选取产后60—90 d，年龄、胎次、体况相近的经产高产奶牛为实验动物。根据奶牛的发情表现、直肠检查、B超检查及激素检测的结果，将奶牛分为发情组（A）22头和卵巢静止组（B）20头。应用GC/MS对两组奶牛的血浆样品进行检测得到其代谢组图谱，利用Chroma TOF软件对得到的峰图进行分析，得到原始数据。将标准化的GC/MS数据矩阵导入SIMCA-P+14.0软件包中，进行多元统计分析，先进行无监督的主成分分析PCA来观察各样本之间的总体分布和整个分析过程的稳定性，然后用有监督的（正交）偏最小二乘法分析(O)PLS-DA来区分各组间代谢轮廓的总体差异，找到组间的差异代谢物。为防止模型过拟合，采用七次循环交互验证和200次响应排序检验的方法来考察模型的质量。采用多维分析(O)PLS-DA和单维分析（t-test）相结合的办法，来筛选组间差异代谢物。在（O）PLS-DA分析中，变量权重值VIP＞1的变量为差异变量；在t-test中，P＜0.05的变量为差异变量。筛选VIP＞1且P＜0.05的代谢物作为差异代谢物，最后采用KEGG途径数据库对两组奶牛血浆样本进行代谢组学差异代谢物通路富集及互作网络构建分析。【结果】与正常发情奶牛相比，卵巢静止奶牛血浆中共有20种代谢产物表现异常，其中17种差异表达代谢物与奶牛卵巢静止的发生密切相关，包括水平增加的胆酸，水平下降的香草扁桃酸、烟酸甘氨酸、6-羟基烟酸、β-丙氨酸、L-酪氨酸、苯丙酮酸等，这些代谢产物参与了苯丙氨酸、酪氨酸、色氨酸的生物合成，并参与了丙酸乙酯、烟酸烟碱、苯丙氨酸和酪氨酸的代谢，它们通过单一途径或综合途径对奶牛卵泡的正常生长产生干扰，从而引起卵巢静止。另外3种化合物亚氨基二乙酸、N-甲基-L-谷氨酸、3-氨基异丁酸可能与氨基酸代谢和细胞能量转运有关，其在奶牛卵巢静止中的生物学作用有待进一步证实。【结论】应用GC/MS技术有效的筛选出正常发情奶牛和卵巢静止奶牛之间的血浆差异代谢物，这些差异代谢物提示奶牛产后发生卵巢静止与体内多种物质代谢紊乱有关。这为今后深入探索奶牛产后卵巢静止的发病机理以及防治策略奠定了基础。

关键词: 气相色谱/质谱联用技术, 奶牛, 卵巢静止, 多元统计分析, 差异代谢物

Abstract: 【Objective】This trial was designed to screen plasma differential metabolites between postpartum dairy cows with inactive ovaries and estrous cows and to clarify the changes of metabolites in dairy cows suffering from inactive ovaries by gas chromatography/mass spectrometry technique (GC/MS).【Method】Dairy cows which had similar age, parity and body condition score were selected at 60-90 d postpartum from an intensive dairy farm in Heilongjiang Province. According to clinical manifestations, B-ultrasound scan, rectal palpation and hormone tests, 22 cows were divided into estrous group (A) and 20 to the inactive ovaries group (B). All plasma samples were detected by GC/MS to obtain plasma metabolic profiles between the groups, and ChromaTOF software was used to analyze peak figures and obtain raw data. The standardized GC/MS data matrix was imported into SIMCA-p＋14 to conduct multivariate statistical analysis including principal component analysis (PCA) to observe the overall distribution between the samples and the stability of the whole analysis process, and (orthogonal) signal correction-partial least squares-discriminant analysis (O)PLS-DA to distinguish the overall differences in metabolic profiles between groups and find differential metabolites between groups. In order to prevent the model from over-fitting, the quality of the model was examined by seven cycles of reciprocal verification and 200 response sequencing tests. Differential metabolites between groups were screened by (O)PLS-DA and t-test. In the PLS-DA analysis, the variable weight value VIP＞1 was considered as the difference variable; in the t-test, the variable with P＜0.05 was considered as the difference variable. The metabolites with VIP＞1 and P＜0.05 were screened as differential metabolites. Finally, plasma differential metabolites between two groups were analyzed by KEGG pathway database including channel enrichment and interaction network construction.【Result】Compared to estrous cows, there were 20 differential metabolites in cows with ovarian inactivity, of which 17 differential metabolites were closely related to cows with ovarian inactivity, including level increased cholic acid and decreased vanillylmandelic acid, nicotinoylglycine, 6-hydroxynicotinic acid, beta-alanine, L-Tyrosine, phenylpyruvate and so on. These metabolites were involved in biosynthesis of phenylalanine, tyrosine and tryptophan, and metabolism of ethyl propionate, nicotinic acid, nicotine, phenylalanine and tyrosine. The normal growth of follicle in cows was interfered with these differential metabolites by a single or comprehensive pathway. The other three compounds, Iminodiacetic acid, N-Methyl-L-glutamic acid and 3-Aminoisobutyric acid, may be related to amino acid metabolism and cell energy transport, and their biological role in dairy cows’ inactive ovaries remains to be further confirmed.【Conclusion】The plasma differential metabolites between cows with inactive ovaries and estrous cows were identified effectively by GC/MS technology. These differential metabolites suggested that the occurrence of ovarian inactivity may be related with metabolic disorders of various substances. Results of this study will lay a foundation for further study on the pathogenesis, prevention and treatment of postpartum inactive ovaries in dairy cows.

Key words: gas chromatography/mass spectrometry, dairy cows, inactive ovaries, multivariate statistical analysis, differential metabolites

范子玲，许楚楚，舒适，肖鑫焕，王刚，白云龙，张江，赵畅，夏成. 基于GC/MS技术的产后卵巢静止奶牛血浆代谢谱分析[J]. 中国农业科学, 2017, 50(15): 3042-3051.

FAN ZiLing, XU ChuChu, SHU Shi, XIAO XinHuan, WANG Gang, BAI YunLong, ZHANG Jiang, ZHAO Chang, XIA Cheng. Plasma Metabolic Profiling of Postpartum Dairy Cows with Inactive Ovaries Based on GC/MS Technique[J]. Scientia Agricultura Sinica, 2017, 50(15): 3042-3051.

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