MetaboLights

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ftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS14062/m_MTBLS14062_LC-MS_alternating_reverse-phase_metabolite_profiling-1_v2_maf.tsvftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS14062/i_Investigation.txtftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS14062/a_MTBLS14062_LC-MS_alternating_reverse-phase_metabolite_profiling-1.txtftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS14062/s_MTBLS14062.txtprimaryOK200ftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS14062Intestinal contentsmass spectrometry assayBMDB Library(BGI Metabolome Database) is a inhouse-developed standard database, including retention time (RT), MS1 spectrum (MS1), and MS2 spectrum (MS2) of all standards. Key primary metabolites and metabolic intermediates in the key metabolic pathways are covered, including carboxylic acids, amino acids, biogenic amines, polyamines, nucleotides, coenzymes and vitamins, monosaccharides and disaccharides, fatty acids, lipids, steroids and hormones .Metabolite extraction was primarily performed according to previously reported methods[6].In short, 25 mg tissues were weighed and extracted by directly adding 800 µL of precooled extraction reagent (methanol: acetonitrile: water (2:2:1, v/v/v)), internal standards mix were added for quality control of sample preparation. After homogenizing for 5min using TissueLyser (JXFSTPRP, China), samples were then sonicated for 10min and incubate at -20 °C for 1 hours. Samples were centrifuged for 15 min at 25000 rpm at 4 °C, and the supernatant was then transferred for vacuum freeze drying. The metabolites were resuspended in 600 µL of 10% methanol and sonicated for 10min at 4 °C, after centrifuging for 15min at 25000 rpm, and the supernatants were transferred to autosampler vials for LC-MS analysis. A quality control (QC) sample was prepared by pooling the same volume of each sample to evaluate the reproducibility of the whole LC-MS analysis.Mus musculushttps://www.ebi.ac.uk/metabolights/MTBLS14062The mass spectrometry raw data (raw file) collected by LC-MS/MS was imported into Compound Discoverer 3.1 (Thermo Fisher Scientific, USA) for data processing, including: peak extraction, retention time correction within and between groups, additive ion pooling. , missing value filling, background peak labeling, and metabolite identification, and finally information on compound molecular weight, retention time, peak area, and identification results were exported. The identification of metabolites is a combined result of BMDB database, mzCloud and ChemSpider (HMDB, KEGG, LipidMaps) databases.Main parameters of metabolite identification:Precursor Mass Tolerance<5 ppm,Fragment Mass Tolerance<10 ppm,RT Tolerance<0.2 min.TreatmentNumberAge2022205020@stu.njau.edu.cnAll samples were collected from ICR mice.The mice were gavaged daily with the antibiotic mix for 3 days. Fresh fecal materials were collected from young and aged mice every day, and FMT was carried out via oral gavage with a fecal suspensionin on days 4-8 and 15. 6 replicates of samples for each group (100 mg intestinal digesta per replicate) were collected for metabolite extraction.MetaboLightsPublicMetabolomicsLiquid Chromatography MS - alternating - reverse-phaseAgingmicrobiomefecal microbiota transplantationuntargeted metabolite profilingThe samples were analyzed on a Waters 2D UPLC (Waters, USA), coupled to a Q-Exactive mass spectrometer (Thermo Fisher Scientific, USA) with a heated electrospray ionization (HESI) source and controlled by the Xcalibur 2.3 software program (Thermo Fisher Scientific, Waltham, MA, USA). Chromatographic separation was performed on a Waters ACQUITY UPLC BEH C18 column (1.7 μm, 2.1 mm × 100 mm, Waters, USA), and the column temperature was maintained at 45 °C. The mobile phase consisted of 0.1% formic acid (A) and acetonitrile (B) in the positive mode, and in the negative mode, the mobile phase consisted of 10 mM ammonium formate (A) and acetonitrile (B). The gradient conditions were as follows: 0-1 min, 2% B; 1-9 min, 2%-98% B; 9-12 min, 98% B; 12-12.1 min, 98% B to 2% B; and 12.1-15min, 2% B. The flow rate was 0.35 mL/min and the injection volume was 5 μL.Please update the publication title.Agingmicrobiomefecal microbiota transplantationuntargeted metabolite profilingZhejiang UniversityFeixue WangThe mass spectrometric settings for positive/negative ionization modes were as follows: spray voltage, 3.8/−3.2 kV; sheath gas flow rate, 40 arbitrary units (arb); aux gas flow rate, 10 arb; aux gas heater temperature, 350 °C; capillary temperature, 320 °C. The full scan range was 70–1050 m/z with a resolution of 70000, and the automatic gain control (AGC) target for MS acquisitions was set to 3e6 with a maximum ion injection time of 100 ms. Top 3 precursors were selected for subsequent MSMS fragmentation with a maximum ion injection time of 50 ms and resolution of 30,000, the AGC was 1e5. The stepped normalized collision energy was set to 20, 40 and 60 eV.falseGut microbiota-modulated glutamic acid rejuvenates the quality of oocytes deteriorated by advanced reproductive ageThe gut microbiota plays a vital role in maintaining the physiological function of host health and the pathogenesis of various diseases. However, its relationship with maternal age-associated decline in oocyte quality remains elusive. Here, we report that establishment of gut microbiota from young donors in aged mice by fecal microbiota transplantation (FMT) is an effective method to rejuvenate the quality of maternally aged oocytes. Specifically, young gut microbiota promoted the ovulation and maturation of aged oocytes, and inhibited occurrence of cytoplasm fragmentation and spindle/chromosome abnormalities, hence enhancing the oocyte quality and female fertility. By integrating metagenome and untargeted metabolome of intestinal digesta, as well as targeted metabolome of ovaries and micro-transcriptome of oocytes, we identified that Bacteroides_caecimuris-modulated glutamic acid levels mediated the restorative effects of young gut microbiota on the aged oocytes through strengthening the mitochondria function. In addition, we demonstrated that in vivo supplementation of glutamic acid also enhanced the quality of aged oocytes, and the improvement of oocyte quality by glutamic acid was conserved across species. Altogether, our findings highlight the importance of gut microbiota in the oocyte aging and provide potential improvement strategies for age-related decline in oocyte quality and female fertility.2026-05-072026-03-17MTBLS14062