Introduction
Bacterial infections of the uterus are ubiquitous after parturition in dairy cattle, often causing uterine diseases (Sheldon et al., 2018). According to the severity and clinical manifestations of bacterial infection in the postpartum uterus, uterine diseases can be divided into puerperal metritis, pyometra, and endometritis (Sheldon et al., 2006). Endometritis mainly damages epithelial cells of the endometrium and affects early embryo implantation and other reproductive processes, decreasing the reproductive performance of dairy cows (Sheldon et al., 2002). Among them, clinical endometritis and subclinical endometritis are the most common. Clinical endometritis is characterized by the presence of purulent uterine discharge detectable in the vagina at 21 days or more following parturition, or mucopurulent discharge detectable in the vagina at 26 or more days postpartum (Dubuc et al. 2010). Endometritis is a common and costly disease affecting dairy farms and one of the major reasons for using antibiotics in dairy farming (Sheldon et al., 2010). In China, the incidence rate of endometriosis (20–50%) and infertility (60–90%) in dairy cows can be attributed to endometritis, which severely affects the conception rate and uterine secretion yield of dairy cows (Bao-Qi et al., 2016). These issues represent a bottleneck limiting the development of the cattle industry in China.
Metabolomics is a newly developed “omics” following genomics, transcriptomics, and proteomics. It refers to the analysis of the metabolic response of all small-molecule metabolites (amino acids, glycols, lipids, etc.) in organisms under environmental, temporal, and external stimuli, along with the research methods used to understand the relationship between metabolites, physiological changes, and pathological changes (Bais et al., 2011; Bolten et al., 2007). Briefly, metabolomics focuses on analyzing overall metabolite levels and understanding the metabolic grid, dynamic regulation, and control of metabolic pathways. Modern detection technologies are used to analyze and detect as many metabolites as possible (Tang et al., 2006; Wang et al., 2011). Thus, in this study, ultra-performance liquid chromatography/quadrupole time-of-flight mass spectrometry (UPLC-QTOF-MS) coupled with univariate and multivariate statistical analyses were used to compare the uterine secretion metabolomics between healthy cows and those with clinical endometritis. The non-targeted metabolomics method based on UPLC-QTOF-MS has higher resolution and high throughput and can be used for accurate qualitative and quantitative analysis of small- and medium-molecule characteristic compounds from uterine secretions (Boudonck et al., 2009). This study was conducted to identify metabolic signatures and biomarkers of uterine secretions specific to cow endometritis. Such data will further our understanding of endometritis-related metabolic changes and provide information on possible measures for enhancing the diagnosis and treatment of clinical endometritis.