MetaboLights

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ftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS14266/m_MTBLS14266_LC-MS_negative_hilic_v2_maf.tsvftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS14266/m_MTBLS14266_LC-MS_positive_hilic_v2_maf.tsvftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS14266/a_MTBLS14266_LC-MS_negative_hilic.txtftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS14266/i_Investigation.txtftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS14266/s_MTBLS14266.txtftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS14266/a_MTBLS14266_LC-MS_positive_hilic.txtprimaryOK200ftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS14266Metabolite identification was performed by matching the accurate mass (mass tolerance < 5 ppm) and MS/MS fragmentation patterns against public databases, including HMDB, KEGG, and MassBank, as well as in-house standard libraries where available.MetaboLightsPublicLiquid Chromatography MS - positive - hilicLiquid Chromatography MS - negative - hilicAnalysis was performed using an UHPLC (1290 Infinity LC, Agilent Technologies) coupled to a quadrupole time-of-flight (AB Sciex TripleTOF 6600). For HILIC separation, samples were analyzed using a 2.1 mm × 100 mm ACQUIY UPLC BEH Amide 1.7 µm column (waters, Ireland). In both ESI positive and negative modes, the mobile phase contained A=25 mM ammonium acetate and 25 mM ammonium hydroxide in water and B= acetonitrile. The gradient was 95% B for 0.5 min and was linearly reduced to 65% in 6.5 min, and then was reduced to 40% in 1 min and kept for 1 min, and then increased to 95% in 0.1 min, with a 3 min re-equilibration period employed. Dysbiosis of Gut Microbiota and Metabolomic Alterations in Myasthenia Gravis: Insights from 16S rRNA Sequencing and Untargeted Metabolomics.The First Affiliated Hospital of Shandong First Medical UniversityYunan Shanfecesmass spectrometry assayAfter the sample was thawed slowly at 4 ° C, an appropriate amount of sample was added to the precooled methanol/acetonitrile/water solution (2:2: 1, v/v), vortexed and mixed, sonicated at low temperature for 30min, stood at -20 ° C for 10 min, centrifuged at 14000 g at 4 ° C for 20 min, took the supernatant and dried under vacuum, and added 100 μL aqueous acetonitrile solution for mass spectrometry analysis (acetonitrile: Water =1:1, v/v), vortexed, centrifuged at 14000 g at 4 ° C for 15 min, and the supernatant was injected for analysis.Homo sapienshttps://www.ebi.ac.uk/metabolights/MTBLS14266Yanbin Li. Department of Neurology, The First Affiliated Hospital of Shandong First Medical University. Nanh080507@163.com.The raw MS data were converted to MzXML files using ProteoWizard MSConvert before importing into freely available XCMS software. For peak picking, the following parameters were used: centWave m/z = 10 ppm, peakwidth = c (10, 60), prefilter = c (10, 100). For peak grouping, bw = 5, mzwid = 0.025, minfrac = 0.5 were used. CAMERA (Collection of Algorithms of MEtabolite pRofile Annotation) was sued for annotation of isotopes and adducts. In the extracted ion features, only the variables having more than 50% of the nonzero measurement values in at least one group were kept. Compound identification of metabolites was performed by comparing of accuracy m/z value (<10 ppm), and MS/MS spectra with an in-house database established with available authentic standards. Disease statusaccept0507@gmail.comFecal samples were collected from Myasthenia Gravis (MG) patients and healthy controls using sterile containers. Fresh samples were immediately snap-frozen in liquid nitrogen upon collection and subsequently transferred to a -80°C freezer for long-term storage until further metabolite extraction and sequencing analysis.MetabolomicsProteoWizard msconvertMetabolomicsAB Triple TOF 6600untargeted analysisButanoic acidmyasthenia gravisHomo sapiensAgilent 1290 Infinity LCpooled samplefecesexperimental sampleProteoWizard msconvertMetabolomicsAB Triple TOF 6600untargeted analysisButanoic acidmyasthenia gravisHomo sapiensAgilent 1290 Infinity LCpooled samplefecesexperimental sampleThe ESI source conditions were set as follows: Ion Source Gas1 (Gas1) as 60, Ion Source Gas2 (Gas2) as 60, curtain gas (CUR) as 30, source temperature: 600℃, IonSpray Voltage Floating (ISVF) ± 5500 V. In MS only acquisition, the instrument was set to acquire over the m/z range 60-1000 Da, and the accumulation time for TOF MS scan was set at 0.20 s/spectra. In auto MS/MS acquisition, the instrument was set to acquire over the m/z range 25-1000 Da, and the accumulation time for product ion scan was set at 0.05 s/spectra. The product ion scan is acquired using information dependent acquisition (IDA) with high sensitivity mode selected. The parameters were set as follows: the collision energy (CE) was fixed at 35 V with ± 15 eV; declustering potential (DP), 60 V (+) and −60 V (−); exclude isotopes within 4 Da, candidate ions to monitor per cycle: 10.falseDysbiosis of Gut Microbiota and Metabolomic Alterations in Myasthenia Gravis: Insights from 16S rRNA Sequencing and Untargeted MetabolomicsBackground: Myasthenia gravis (MG) is an autoimmune disorder of neuromuscular transmission. Gut dysbiosis has been implicated in autoimmune pathogenesis, yet integrated microbial and metabolomic profiling in MG remains scarce.Objectives:  To characterize gut microbiota and the fecal metabolome in MG, identify diagnostic biomarkers, and explore associations between microbial taxa, metabolites, and clinical severity.Methods: Fecal samples from 29 MG patients and 10 healthy controls underwent 16S rRNA sequencing and UHPLC-Q-TOF MS metabolomics. LEfSe identified differential taxa; metabolites were screened by VIP > 1.0, P < 0.05, FDR q < 0.05. Random Forest and Spearman correlation assessed biomarker performance and microbiota–metabolite–clinical associations.Results: MG patients showed significantly reduced alpha- and beta-diversity. LEfSe identified 232 discriminative taxa, with depletion of butanoic acid-producing commensals (Faecalibacterium prausnitzii, Ruminococcus bromii, Bifidobacterium bifidum) and enrichment of Klebsiella. Metabolomics revealed 567 altered metabolites (424 downregulated), including reduced short-chain fatty acids (SCFAs) and secondary bile acids (lithocholic, isolithocholic, allolithocholic acids). The Random Forest metabolite model achieved AUC = 1.0. Spearman analysis showed lithocholic acid ( P < 0.05) and allocholic acid (P < 0.001) positively correlated with QMG score, and Ruminococcus abundance correlated with butanoic acid (P < 0.01). KEGG analysis implicated cholinergic synapse, bile secretion, sphingolipid signaling, and mTOR pathways.Conclusions: MG patients exhibit a distinct profile of gut dysbiosis and metabolic disturbances. The specific microbial and metabolic biomarkers identified in this study may offer novel insights for auxiliary diagnosis of MG and guide future microbiota-targeted intervention strategies.2026-04-132026-04-13MTBLS14266