At the same time, the metabolites were identified by searching database, and the main databases were the HMDB (http://www.hmdb.ca/), Metlin ( https://metlin.scripps.edu/) and Majorbio Database .
"],"repository":["MetaboLights"],"study_status":["Public"],"ptm_modification":[""],"instrument_platform":["Liquid Chromatography MS - alternating - reverse-phase"],"chromatography_protocol":["Metabolic extracts were separated on a Thermo Scientific Dionex UltiMate 3000 Rapid Separation LC (RSLC) using an ACQUITY UPLC HSS T3 analytical column (2.1 × 150 mm, 1.8 μm, 100 Å, Waters) protected by an ACQUITY UPLC HSS T3 VanGuard pre-column (2.1 × 5 mm, 1.8 μm, 100 Å, Waters). Mobile phase solvents for positive ionization mode were 0.1% formic acid in water (A) and 0.1% formic acid in acetonitrile (B); mobile phase solvents for negative ionization mode were 0.01% formic acid in water (A) and acetonitrile (B). The following gradient elution was used: 0–3 min, 95% A; 5–13 min, 80%–30% A; 15–18 min, 2% A; 18.1–22 min, 5% A. The flow rate was 0.3 mL/min, the injection volume was 2 μL and the column oven was set at 35 °C.
"],"publication":["Omega-3 polyunsaturated fatty acids modulate gut microbiota-derived 18β-glycyrrhetinic acid to alleviate type 1 diabetes mellitus."],"submitter_affiliation":["The Fifth Affiliated Hospital, Sun Yat- sen University"],"submitter_name":["Yifan Guo"],"organism_part":["fecal"],"technology_type":["mass spectrometry assay"],"disease":[""],"extraction_protocol":["Metabolite extraction was performed by adding 1 mL of ice-cold 80% methanol to ∼150 mg fecal samples, vortexing for 30 s, and centrifuging (16,000g) at 4 °C for 10 min. The supernatants were evaporated to dryness under nitrogen, reconstituted in 150 μL of 0.1% formic acid in 5% acetonitrile, and kept at −80 °C until analysis.
"],"organism":["Mus musculus"],"full_dataset_link":["https://www.ebi.ac.uk/metabolights/MTBLS13979"],"author":["Li Cong. The First Affiliated Hospital, Sun Yat-sen University. congli@mail.sysu.edu.cn.","Yifan Guo. The First Affiliated Hospital, Sun Yat-sen University. guoyf28@mail2.sysu.edu.cn."],"data_transformation_protocol":["The pretreatment of LC/MS raw data was performed by Progenesis QI (Waters Corporation, Milford, USA) software, and a three-dimensional data matrix in CSV format was exported. The information in this three-dimensional matrix included: sample information, metabolite name and mass spectral response intensity. Internal standard peaks, as well as any known false positive peaks (including noise, column bleed, and derivatized reagent peaks), were removed from the data matrix, deredundant and peak pooled.
"],"study_factor":["Treatment"],"submitter_email":["guoyf2018@163.com"],"sample_collection_protocol":["mice were assigned to two dietary intervention groups (n = 5): a semi-purified control diet group and an Omega-3 PUFAs diet group sup-plemented with 10% fish oil
"],"omics_type":["Metabolomics"],"study_design":["type 1 diabetes mellitus","Gastrointestinal Microbiome","macrophage","Omega-3 Fatty Acid","untargeted metabolite profiling"],"curator_keywords":["type 1 diabetes mellitus","Gastrointestinal Microbiome","macrophage","Omega-3 Fatty Acid","untargeted metabolite profiling"],"mass_spectrometry_protocol":["Data were acquired on an Orbitrap Fusion Lumos Tribrid mass spectrometer fitted with a HESI source in both positive and negative ionization modes with an independent run for each polarity and a spray voltage of +3500 V and −3500 V, respectively (Thermo Scientific, San Jose, CA, USA). The ion transfer tube temperature was 300 °C, the vaporized temperature was 350 °C, the sheath gas flow was 40 units, the auxiliary gas flow was 15 arbitrary units, and the sweep gas was 1 unit. Metabolite profiling was profiled in full scan mode using a mass range of m/z 100–1000 with a resolution of 120 K at m/z 200, an AGC target of 5 × 104, and a maximum injection time of 50 ms. For metabolite identification, data dependent MS/MS data were acquired on quality control samples (QC) containing equally volumes of all samples used in this study.
"],"additional_accession":[]},"is_claimable":false,"name":"Omega-3 polyunsaturated fatty acids modulate gut microbiota-derived 18β-glycyrrhetinic acid to alleviate type 1 diabetes mellitus_fecal_Omega-3 PUFAs","description":"Background
Omega-3 polyunsaturated fatty acids (PUFAs) are known to protect against type 1 diabetes mellitus (T1DM), but how they act through the gut-islet axis is not fully understood. This study explored how Omega-3 PUFA-influenced gut microbiota and their metabolites help protect pancreatic islets in T1DM.
Methods
We used fecal microbiota transplantation (FMT) to test the effects of Omega-3 PUFA-derived gut microbiota in NOD mice. Immune cell changes in the islets were analyzed using transcriptomics, flow cytometry, and immunohistochemistry. Metabolomics identified key metabolites in serum related to gut microbiota changes. Co-culture experiments examined the role of specific metabolites in macrophage polarization and β-cell function.
Results
Omega-3 PUFA-treated and FMT mice showed reduced islet inflammation and an increased abundance of the Eubacterium coprostanoligenes group. Enhanced M2 macrophage polarization was observed in the islet microenvironment of FMT mice. Among gut microbiota metabolites, 18β-glycyrrhetinic acid (18β-GA) was strongly linked to E. coprostanoligenes and stood out as a key molecule. In co-culture experiments, 18β-GA shifted macrophages to an M2 phenotype, which boosted insulin production and secretion in β-cells.
Conclusions
Omega-3 PUFA-derived gut microbiota and the metabolite 18β-GA play a key role in protecting pancreatic islets in T1DM by modulating macrophage polarization and improving β-cell function. These findings suggest new ways to use gut microbiota for T1DM treatment.
","dates":{"publication":"2026-06-13","submission":"2026-03-05"},"accession":"MTBLS13979","cross_references":{}}