The raw data were converted to the mzXML format using ProteoWizard and processed with an in-house program. which was developed using R and based on XCMS, for feature detection, extraction, alignment, and integration. The R package and the BiotreeDB(V3.0) were applied in metabolite identification.
"],"repository":["MetaboLights"],"study_status":["Public"],"ptm_modification":[""],"instrument_platform":["Liquid Chromatography MS - negative - reverse phase","Liquid Chromatography MS - positive - reverse phase"],"chromatography_protocol":["For polar metabolites, LC-MS/MS analyses were performed using an UHPLC system (Vanquish, Thermo Fisher Scientific) with a Waters ACQUITY UPLC BEH Amide (2.1 mm × 50 mm, 1.7 μm) coupled to Orbitrap Exploris 120 mass spectrometer (Orbitrap MS, Thermo). The mobile phase consisted of 25 mmol/L ammonium acetate and 25 ammonia hydroxide in water(pH = 9.75)(A) and acetonitrile (B). The auto-sampler temperature was 4 °C, and the injection volume was 2 μL.
"],"publication":["Multi-Omics Reveals that Alkaline Mineral Complex Enhances Nutrient Digestion–Absorption and Gut Health."],"submitter_affiliation":["Sichuan Agricultural University"],"submitter_name":["li gu"],"organism_part":["Jejunal Content"],"technology_type":["mass spectrometry assay"],"disease":[""],"extraction_protocol":["The bacteria pellets (about 10^7 bacteria) were taken, mixed with 1000 μL of extraction solution (MeOH:ACN:H2O, 2:2:1 (v/v)), the extraction solution contain deuterated internal standards, the mixed solution were vortexed for 30 s. Add 2 homogenization beads and homogenize for 4 min (35 Hz), then transferred to an ice-water bath to sonicate for 5 min. (Repeat 3 times) The samples were then allowed to thaw at room temperature and vortexed for 30 s. This freeze–thaw cycle was repeated three times.Then the samples were sonicated for 10 min in 4 °C water bath, and incubated for 1 h at -40 °C to precipitate proteins. The samples were centrifuged at 12000 rpm (RCF=13800(×g), R= 8.6cm) for 15 min at 4 °C. The supernatant was transferred to a fresh glass vial for analysis. The quality control (QC) sample was prepared by mixing an equal aliquot of the supernatant of samples.
"],"organism":["Bos taurus"],"full_dataset_link":["https://www.ebi.ac.uk/metabolights/MTBLS13175"],"author":["Li Gu. Sichuan Agricultural University. 1030448279@qq.com."],"data_transformation_protocol":["The raw data were converted to the mzXML format using ProteoWizard and processed with an in-house program. which was developed using R and based on XCMS, for feature detection, extraction, alignment, and integration. The R package and the BiotreeDB(V3.0) were applied in metabolite identification.
"],"study_factor":["Treatment"],"submitter_email":["1030448279@qq.com"],"sample_collection_protocol":["Group A was the control group (finishing cattle fed a high-concentrate diet). Group B received the same high-concentrate diet supplemented with 10g AMC/head/day, and Group C received the same high-concentrate diet supplemented with 20g AMC/head/day. The 16S rRNA sequencing and metabolomics analyses were performed on the jejunal content of these finishing cattle.
"],"omics_type":["Metabolomics"],"study_design":["Nutrient","untargeted metabolites","high fat diet","Intestinal"],"curator_keywords":["untargeted metabolites","Nutrient","high fat diet","Intestinal"],"mass_spectrometry_protocol":["The Orbitrap Exploris 120 mass spectrometer was used for its ability to acquire MS/MS spectra on information-dependent acquisition (IDA) mode in the control of the acquisition software (Xcalibur, Thermo). In this mode, the acquisition software continuously evaluates the full scan MS spectrum. The ESI source conditions were set as following: sheath gas flow rate as 50 Arb, Aux gas flow rate as 15 Arb, capillary temperature 320 °C, full MS resolution as 60000, MS/MS resolution as 15000, collision energy: SNCE 20/30/40, spray voltage as 3.8 kV (positive) or -3.4 kV (negative), respectively.
"],"metabolite_name":["2-Aminoisobutyric acid"],"additional_accession":[]},"is_claimable":false,"name":"Multi-Omics Reveals that Alkaline Mineral Complex Enhances Nutrient Digestion–Absorption and Gut Health","description":"This study, conducted under a high-concentrate finishing context, used an integrated multi-omics approach to evaluate the effects of an Alkaline Mineral Complex (AMC) on jejunal digestion–absorption and gut health in beef cattle. The results showed that AMC alleviated mucosal pathological injury and inflammatory cell infiltration in the jejunum, significantly reduced crypt depth and increased the villus height/crypt depth (VH/CD) ratio (p = 0.0004 and 0.0002, respectively), and modulated redox homeostasis, evidenced by a significant decrease in MDA accompanied by concurrent reductions in SOD and CAT, with T-AOC and GSH-Px remaining overall unchanged (MDA, SOD, CAT all p < 0.0162; others p > 0.05). Pro-inflammatory cytokines IL-6 and IL-1β showed downward trends, whereas TNF-α slightly increased; none reached statistical significance (p > 0.05). While overall α-diversity and community structure did not separate between groups, the relative abundances of Olsenella and Cyanobacteria were higher in the AMC group (p < 0.05), and enrichment of Massilia/Oxalobacteraceae/Burkholderiales in controls suggested stronger Proteobacteria-related signals. Metabolomics achieved OPLS-DA separation and identified 28 differential metabolites, enriching pathways such as “Protein digestion and absorption.” Proteomics identified 382 differentially expressed proteins, enriched in carbon metabolism, glycolysis/gluconeogenesis, pentose phosphate pathway, fatty-acid degradation, glutathione metabolism, as well as tight junction and AMPK/insulin signaling. Functionally, digestive enzyme activities showed overall upward but non-significant trends, whereas nutrient-sensing/transport and barrier-related molecules (GPR43, FABP2, SNAT2, LAT2, ZO-1) were significantly upregulated (all p < 0.05). Integrating multi-omics and phenotypic evidence, AMC appears to enhance jejunal digestion–absorption and improve gut health by metabolic remodeling and barrier strengthening, jointly optimizing the “oxidative stress–microbiome/metabolite–nutrient transport” axis.
","dates":{"publication":"2026-07-14","submission":"2025-10-19"},"accession":"MTBLS13175","cross_references":{}}