Subsequently, the software was employed for characteristic peak library search and identification by matching MS and MS/MS mass spectrometry data with a metabolite database. The MS mass error was set to less than 10 ppm, and metabolites were identified based on the matching scores from the secondary mass spectrum analysis. The primary databases include mainstream public databases such as http://www.hmdb.ca/ and https://metlin.scripps.edu/, as well as self-developed databases.
"],"repository":["MetaboLights"],"study_status":["Public"],"ptm_modification":[""],"instrument_platform":["Liquid Chromatography MS - negative - reverse-phase","Liquid Chromatography MS - positive - reverse-phase"],"chromatography_protocol":["Chromatographic conditions: The chromatographic column used was an ACQUITY UPLC HSS T3 (100 mm × 2.1 mm inner diameter, 1.8 µm; Waters, Milford, USA); mobile phase A consisted of 95% water + 5% acetonitrile (containing 0.1% formic acid), and mobile phase B consisted of 47.5% acetonitrile + 47.5% isopropanol + 5% water (containing 0.1% formic acid); the injection volume was 3 μL, and the column temperature was maintained at 40°C.
"],"publication":["Rumen Fluid Metabolomic Profiles of Postpartum Tan Ewes Fed Diets with Different Nutrient Levels."],"submitter_affiliation":["Northwest Agriculture & Forestry University"],"submitter_name":["Lele Zhu"],"organism_part":["Rumen fluid"],"technology_type":["mass spectrometry assay"],"disease":[""],"extraction_protocol":["After filtration through four layers of gauze, the rumen fluid was immediately tested for pH, then aliquoted for fermentation parameter analysis, metagenomic studies, and non-targeted metabolomic analysis, and stored at −80°C. For each sample, 100 μL of rumen fluid or serum was added to 400 μL of pre-cooled acetonitrile–methanol extraction solution (1:1, v/v, containing an internal standard). After vortexing, low-temperature sonication, protein precipitation, and centrifugation, the supernatant was collected. The samples were dried under nitrogen and resolventized in acetonitrile–water (1:1, v/v) for UHPLC-MS/MS analysis. Equal volumes of all samples were mixed to prepare quality control samples, with one control sample added to every 5–10 test samples during analysis.
"],"organism":["sheep"],"full_dataset_link":["https://www.ebi.ac.uk/metabolights/MTBLS15107"],"author":["Lele Zhu. Northwest Agriculture & Forestry University. 3514953885@qq.com."],"data_transformation_protocol":["The raw data were imported into the metabolomics analysis software Progenesis QI v3.0 (Waters Corporation, Milford, USA) for baseline filtering, peak identification, integration, retention time calibration, and peak alignment, ultimately yielding a data matrix containing information such as retention times, mass-to-charge ratios, and peak intensities.
"],"study_factor":["Treatment"],"submitter_email":["3514953885@qq.com"],"sample_collection_protocol":["The sheep were divided into three groups for feeding: the low-nutrient group (LND), the medium-nutrient group (MND), and the high-nutrient group (HND).
Metabolite detection was performed using the UHPLC-Q Exactive HF-X system with Waters HSS T3 chromatographic columns. Mass spectrometry signals were collected in both positive and negative ion modes, with a scanning range of m/z 70–1050. Raw data were processed with Progenesis QI for peak identification, peak integration, retention time calibration, and peak alignment. Metabolites were identified by matching MS and MS/MS data against HMDB, Metlin, and proprietary databases [40,41].
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