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