MetaboLights

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ftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS13135/m_MTBLS13135_LC-MS_alternating_reverse-phase_metabolite_profiling_v2_maf.tsvftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS13135/i_Investigation.txtftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS13135/a_MTBLS13135_LC-MS_alternating_reverse-phase_metabolite_profiling.txtftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS13135/s_MTBLS13135.txtprimaryOK200ftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS13135Metabolite identification was conducted using Compound Discoverer™ 3.3 software. Features were annotated by matching accurate mass (MS1), retention time, and MS/MS fragmentation spectra against online and local databases, including mzCloud, mzVault (containing NIST_2020_MSMS), HMDB, LIPID MAPS, MoNA, and an in-house standard library (PSNGM Database). The mass tolerance for MS1 was set to 15 ppm, and the MS2 Match Factor Threshold was set to 50. Validated metabolites were identified based on comparisons with standards or high-confidence database matches.MetaboLightsPublicLiquid Chromatography MS - alternating - reverse phaseChromatographic separation was performed using a Thermo Vanquish Flex UHPLC system equipped with an ACQUITY UPLC HSS T3 column (100 Å, 1.8 µm, 2.1 mm × 100 mm; Waters). The column temperature was maintained at 40°C, and the autosampler at 8°C. The flow rate was set to 0.4 mL/min, and the injection volume was 2 µL.The mobile phases consisted of 0.1% formic acid in water (Phase A) and acetonitrile containing 0.1% formic acid (Phase B). The elution gradient was as follows: 0–1 min, 5% B; 1–7 min, 5% to 95% B; 7–8 min, 95% B; 8–8.1 min, 95% to 5% B; 8.1–12 min, 5% B for re-equilibration.Gut commensal Odoribacter splanchnicus alleviates hyperlipidemic periodontitis via the β-GPA-TLR4 axis.Jing XuJilin University Stomatological Hospitalfecesmass spectrometry assayApproximately 50 mg of fecal sample was weighed into a 2 mL centrifuge tube. 500 µL of pre-cooled methanol containing 5 ppm 2-chlorophenylalanine (as an internal standard) was added, followed by 2 steel beads. The mixture was vortexed for 30 s, then homogenized using a high-throughput tissue grinder at 55 Hz for 60 s; this step was repeated once. Samples were ultrasonicated for 10 min in an ultrasonic cleaning machine and subsequently placed at -20°C for 30 min for protein precipitation. After centrifugation at 12,000 rpm and 4°C for 10 min, the supernatant was filtered through a 0.22 µm membrane into a detection vial.Control samples: Quality Control (QC) samples were prepared by pooling 10-20 µL of the filtered supernatant from each study sample to monitor instrument stability and data quality throughout the analysis.Homo sapienshttps://www.ebi.ac.uk/metabolights/MTBLS13135Hu Min. Hospital of Stomatology, Jilin University. humin@jlu.edu.cn.Xu Jing. Hospital of Stomatology, Jilin University. xujing23@mails.jlu.edu.cn.Raw data files (.raw) were imported into Compound Discoverer™ 3.3 software (version 3.3.2.31, Thermo Scientific) for processing. The workflow included peak alignment, peak picking, and retention time correction based on the software's algorithms. Peaks not detected in more than 50% of QC samples were filtered out to reduce noise. Missing values for undetected peaks were filled using the 'Fill Gaps' algorithm. Data normalization was performed using the 'Sum of total peak area' method.Diseasehuzz22@mails.jlu.edu.cnFecal samples were collected from patients with hyperlipidemic periodontitis (HPD) and healthy volunteers (NC) under sterile conditions. Samples were immediately frozen after collection and stored at -80°C until metabolite extraction.MetabolomicsHumanPeriodontitishyperlipemiaHumanPeriodontitishyperlipemiaMass spectrometry was performed on a Thermo Orbitrap Exploris 120 instrument equipped with a heated electrospray ionization (HESI) source, controlled by Xcalibur software (version 4.7). Data were acquired in data-dependent acquisition (DDA) mode for both positive and negative ions.Source parameters: Spray voltage was 3.5 kV for positive mode and -3.0 kV for negative mode. Sheath gas and auxiliary gas flow rates were set to 40 and 15 arbitrary units, respectively. Capillary temperature was 325°C, and auxiliary gas heater temperature was 300°C.Scan parameters: MS1 scan range was 100–1000 m/z at a resolution of 60,000 (FWHM). Top 4 ions were selected for MS2 fragmentation using Higher-energy C-trap Dissociation (HCD) with a collision energy of 30%. MS2 resolution was set to 15,000, with a dynamic exclusion time of 8 s.Run sequence: 2-4 QC samples were injected to equilibrate the system before analyzing study samples. One QC sample was injected after every 5-10 study samples.falseGut commensal Odoribacter splanchnicus alleviates hyperlipidemic periodontitis via the β-GPA-TLR4 axis Background: Hyperlipidemia is a well-established systemic metabolic disorder and a significant risk factor for periodontitis, a localized inflammatory condition; however, the precise mechanisms underpinning this comorbidity remain uncharacterized. Emerging evidence implicates the gut microbiota as a crucial mediator in the pathogenesis linking hyperlipidemia with periodontitis. Therefore, this study was designed to elucidate the causal role of the gut microbiota and its associated metabolic pathways in this interaction, with the ultimate goal of identifying microbiome-targeted therapeutic strategies. Results: We found that hyperlipidemia exacerbates periodontal destruction by inducing specific gut microbiota dysbiosis. Notably, Odoribacter splanchnicus was significantly depleted in patients and mice with hyperlipidemic periodontitis (HPD). Through fecal microbiota transplantation, we established a causal link between HPD-associated gut microbiota and disease phenotypes. Oral administration of live O. splanchnicus attenuated periodontal bone loss and systemic metabolic dysfunction by remodeling the gut microbiome and upregulating the metabolite, β-guanidinopropionic acid (β-GPA). Crucially, direct supplementation with β-GPA similarly alleviated HPD phenotypes. Further mechanistic investigations revealed that β-GPA remotely inhibited the pro-inflammatory Toll-like receptor 4 (TLR4) signaling pathway in periodontal tissues. Conclusions: Our findings establish the 'O. splanchnicus - β-GPA - TLR4' axis as a crucial protective pathway in HPD. This provides a mechanistic framework for the crosstalk between systemic metabolic disorders and local inflammatory diseases, representing an advance in microbiome-targeted therapeutic strategies for this complex comorbidity.2026-06-082025-10-14MTBLS13135