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.