MetaboLightsapplication/xmlftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS15480/m_MTBLS15480_GC-MS_positive_medium-polarity_v2_maf.tsvftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS15480/a_MTBLS15480_GC-MS_positive_medium-polarity.txtftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS15480/s_MTBLS15480.txtftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS15480/i_Investigation.txtftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS15480/FILES/Hk26DM_JN_131_10.mzMLftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS15480/FILES/Hk26DM_JN_131_9.mzMLftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS15480/FILES/Hk26DM_JN_132_124.mzMLftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS15480/FILES/S2.mzMLftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS15480/FILES/Hk26DM_JN_131_16.mzMLftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS15480/FILES/S5.mzMLftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS15480/FILES/Hk26DM_JN_QC1.mzMLftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS15480/FILES/S0.mzMLftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS15480/FILES/Hk26DM_JN_131_14.mzMLftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS15480/FILES/Hk26DM_JN_131_11.mzMLftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS15480/FILES/Hk26DM_JN_QC3.mzMLftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS15480/FILES/S6.mzMLftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS15480/FILES/S7.mzMLftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS15480/FILES/S3.mzMLftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS15480/FILES/Hk26DM_JN_131_8.mzMLftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS15480/FILES/Hk26DM_JN_QC2.mzMLftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS15480/FILES/S4.mzMLftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS15480/FILES/Hk26DM_JN_131_18.mzMLftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS15480/FILES/S1.mzMLftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS15480/FILES/Hk26DM_JN_131_12.mzMLftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS15480/FILES/Hk26DM_JN_132_23.mzMLprimaryOK200ftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS15480<p>Targeted short-chain fatty acids were identified and quantified based on retention time, characteristic ion fragments, and calibration curves generated from authentic standards. All metabolites were quantified using the corresponding standard curves. The analytical method showed good linearity (R² &gt; 0.99), supporting reliable quantitative analysis.&nbsp;</p>MetaboLightsPublicGas Chromatography MS - positive - medium-polarity<p>Chromatographic separation was performed using an Agilent 8890B gas chromatograph equipped with an HP-FFAP capillary column (30 m × 0.25 mm × 0.25 μm; Agilent J&amp;W Scientific). Helium (&gt;99.999% purity) was used as the carrier gas at a flow rate of 1.0 mL/min. The injection volume was 1 μL with a split ratio of 10:1. The inlet temperature was set at 180°C. The oven temperature program was initiated at 80°C, increased to 120°C at 20°C/min, then increased to 160°C at 5°C/min, and finally maintained at 220°C for 3 min.</p>Increased adipose tissue Fas alters gut microbiota to aggravate colitis in obesity— Adipose Fas aggravates colitis via gut microbiota in obesity.Fei YangZhejiang UniversitymixtureIntestinal Contentmass spectrometry assay<p>Approximately 20 mg of intestinal content sample was accurately weighed into a 2 mL grinding tube. Samples were extracted with 800 μL of 0.5% phosphoric acid solution containing 2-ethylbutyric acid (10 μg/mL) as an internal standard. Samples were homogenized by cryogenic grinding for 3 min at 50 Hz, followed by ultrasonic extraction for 10 min. After centrifugation at 13,000 × g for 15 min at 4°C, 200 μL of supernatant was transferred and mixed with 200 μL n-butanol for extraction. The mixture was vortexed for 10 s, sonicated at low temperature for 10 min, and centrifuged at 13,000 × g for 5 min at 4°C. The resulting supernatant was transferred into autosampler vials for GC-MS analysis.</p>Mus musculusreference compoundhttps://www.ebi.ac.uk/metabolights/MTBLS15480Fei Yang. Zhejiang University. yangfei919@zju.edu.cn.<p>Raw GC-MS data were processed using MassHunter quantitative analysis software (Agilent Technologies, USA; version 10.0.707.0). Target SCFA peaks were automatically identified and integrated according to characteristic ion fragments, followed by manual inspection. Quantification was performed using calibration curves generated from standard solutions. The concentrations of SCFAs were calculated and converted into actual contents according to sample weight.</p>Genotypeyangfei919@zju.edu.cn<p>Intestinal content samples were collected from male FasCKI/CKI×Adi-cre and FasCKI/CKI mice . FasCKI/CKI×Adi-cre mice were generated by crossing FasCKI/CKI mice with adiponectin-Cre mice to achieve adipose tissue-specific Fas overexpression. All mice were maintained under specific pathogen-free (SPF) conditions during the experimental period. At the designated experimental endpoint, mice were euthanized, and intestinal contents were aseptically collected. Samples were immediately frozen and stored at −80°C until targeted short-chain fatty acid (SCFA) analysis.</p>Metabolomicsbiological samplepooled quality control sampleMetabolomicsObesityShort-chain fatty acidsMus musculustargeted analysisFecal microbiota transplantationIntestinal Contentreference compound mixexperimental sampleInflammatory bowel diseaseMicrobiotareference compoundmixtureAgilent 5977B MSDFasQC sampleAgilent 8890 GCpooled quality control samplebiological sampleObesityMetabolomicsShort-chain fatty acidsMus musculustargeted analysisFecal microbiota transplantationIntestinal Contentreference compound mixexperimental sampleInflammatory bowel diseaseMicrobiotareference compoundmixtureAgilent 5977B MSDFasQC sampleAgilent 8890 GC<p>Mass spectrometry analysis was performed using an Agilent 7000D mass selective detector coupled with the GC system. Electron ionization (EI) mode was applied with an ionization energy of 70 eV. The ion source temperature was 230°C, quadrupole temperature was 150°C, and transfer line temperature was 230°C. Data acquisition was performed using selected ion monitoring (SIM) mode.</p>falseIncreased adipose tissue Fas alters gut microbiota to aggravate colitis in obesity— Adipose Fas aggravates colitis via gut microbiota in obesityObesity is increasingly recognized as a factor that may exacerbate inflammatory bowel disease (IBD), yet the underlying mechanisms remain poorly understood. This study investigates whether upregulated Fas (CD95) expression in adipose tissue contributes to obesity-associated aggravation of colitis, with a particular focus on the role of the gut microbiota and its metabolic products. To address this question, we employed a mouse model with adipose tissue-specific Fas overexpression (FasCKI/CKI×Adi-cre) alongside littermate controls (FasCKI/CKI). All animals were maintained on a high-fat diet (HFD) both before and during colitis induction, which was achieved using dextran sulfate sodium (DSS). Disease severity was assessed through clinical scores, histopathological evaluation, and inflammatory markers. Gut microbial composition was analyzed via 16S rRNA sequencing, and fecal short-chain fatty acid (SCFA) levels were quantified using targeted metabolomics. Additionally, fecal microbiota transplantation (FMT) experiments were performed to establish a causal link between microbiota alterations and disease phenotype. Biological samples collected include colonic tissues, adipose tissues, serum, and fecal specimens. Metabolomic data were generated from fecal samples, with a focus on short-chain fatty acids (SCFAs) including acetate, propionate, and butyrate. These metabolomic measurements were integrated with microbial community data and phenotypic parameters to explore correlations between metabolic shifts, microbial dysbiosis, and colitis severity. Our results demonstrate that adipose tissue Fas overexpression exacerbates DSS-induced colitis under obese conditions, accompanied by significant alterations in the gut microbiota—specifically reduced Roseburia abundance and increased Escherichia–Shigella, Erysipelatoclostridium, and UCG_005—alongside decreased fecal SCFA levels. FMT experiments confirmed that the altered microbiota directly contributes to disease aggravation. This study provides novel insights into the crosstalk between adipose tissue Fas signaling, gut microbial metabolism, and intestinal inflammation, highlighting potential metabolic targets for therapeutic intervention.2026-09-032026-08-28MTBLS15480