MetaboLightsapplication/xmlftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS14192/m_MTBLS14192_LC-MS_negative_reverse-phase_v2_maf.tsvftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS14192/m_MTBLS14192_LC-MS_positive_reverse-phase_v2_maf.tsvftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS14192/i_Investigation.txtftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS14192/s_MTBLS14192.txtftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS14192/a_MTBLS14192_LC-MS_negative_reverse-phase.txtftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS14192/a_MTBLS14192_LC-MS_positive_reverse-phase.txtprimaryOK200ftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS14192<p>Lipid identification was performed by searching the processed MS/MS data against the LipidSearch built-in database (which contains 8 major categories, 300 subclasses, and approximately 1.7 million lipid ions and their predicted fragment ions). Lipids were identified based on precursor ion mass, retention time, and, crucially, fragmentation patterns (product ions and neutral losses). Only identifications with a mass tolerance of 5 ppm for both precursor and product ions were retained. The identified lipids were categorized according to the LIPID MAPS® classification system (Fahy et al., 2009), including categories such as glycerolipids (GL), glycerophospholipids (GP), and sphingolipids (SP). The final dataset included the lipid subclass (class), fatty acyl chain composition, and relative abundance (peak intensity) for each identified lipid species.</p>MetaboLightsPublicLiquid Chromatography MS - negative - reverse-phaseLiquid Chromatography MS - positive - reverse-phase<p>Chromatographic separation was performed using a&nbsp;UHPLC Nexera LC-30A system (SHIMADZU)&nbsp;equipped with a&nbsp;Waters ACQUITY UPLC CSH C18 column (1.7 µm, 2.1 mm × 100 mm). The column temperature was maintained at 45°C, and the flow rate was set to 300 μL/min. Mobile phase A consisted of acetonitrile/water (6:4, v/v) containing 0.1% formic acid and 0.1 mM ammonium formate. Mobile phase B consisted of acetonitrile/isopropanol (1:9, v/v) containing 0.1% formic acid and 0.1 mM ammonium formate. The gradient elution program was as follows: 0–2 min, 30% B; 2–25 min, linear gradient from 30% to 100% B; 25–35 min, maintained at 30% B. The sample manager temperature was set at 10°C, and samples were analyzed in random order.</p>Nitrate-Sialin2 Axis Couples ER-Mitochondrial Calcium Signaling with Fatty Acid Metabolism to Drive White Adipose Browning.Capital Medical UniversityOu JiangWhite adipose tissuemass spectrometry assay<p>Lipids were extracted using a methyl tert-butyl ether (MTBE) method. Briefly, an appropriate amount of each tissue sample was homogenized with 200 μL of water and vortexed. Subsequently, 800 μL of MTBE and 240 μL of pre-cooled methanol were added. The mixture was vortexed, sonicated in a low-temperature water bath for 20 min, and then allowed to stand at room temperature for 30 min. After centrifugation at 14,000 × g for 15 min at 10°C, the upper organic phase was collected and dried under a nitrogen stream. The dried lipid extracts were stored at -80°C until LC-MS analysis. Prior to analysis, each residue was reconstituted in 200 μL of 90% isopropanol/acetonitrile (v/v), vortexed, and centrifuged at 14,000 × g for 15 min at 10°C. The supernatant (90 μL) was transferred to an autosampler vial for analysis. A pooled quality control (QC) sample was prepared by mixing equal volumes of all sample extracts.</p>Mus musculushttps://www.ebi.ac.uk/metabolights/MTBLS14192Ou Jiang. Capital Medical University. 010744@ccmu.edu.cn.<p>Raw LC-MS data were processed using LipidSearch software (Thermo Scientific™) for peak detection, peak alignment, lipid identification (level 2 identification based on MS/MS matching), and quantification. The main processing parameters were: precursor tolerance, 5 ppm; product tolerance, 5 ppm; product ion threshold, 5%. The resulting data matrix (containing lipid species, retention time, and peak intensity) was exported. Data were normalized prior to statistical analysis. The quality of the data was evaluated by monitoring QC samples, which showed good analytical reproducibility (e.g., &gt;80% of QC features had relative standard deviation (RSD) ≤ 30%; QC samples clustered tightly in PCA).</p>Treatment010744@ccmu.edu.cn<p>White adipose tissue (WAT) samples were collected from 12 male mice, including 6 wild-type (WT) and 6 Slc17a5 ∆FABP4 conditional&nbsp;knockout (cKO) mice (Capital Medical University, Beijing, China). The Slc17a5 gene encodes Sialin2, a dual-organelle transporter that localizes to mitochondria and the endoplasmic reticulum (ER) and couples ER-mitochondrial calcium signaling with fatty acid metabolism. To investigate the nitrate-Sialin2 axis in white adipose browning, all mice were maintained on a standard diet with or without nitrate supplementation as indicated. Following euthanasia,&nbsp;inguinal white adipose tissue (iWAT) susceptible to browning, were rapidly dissected. All tissue samples were immediately snap-frozen in liquid nitrogen and stored at -80°C until lipid extraction.</p>MetabolomicsMus musculusWhite adipose tissueUHPLC Nexera LC-30Auntargeted analysisLipidomicsmzminenitratepooled sampleQ Exactive (Thermo Fisher Scientific)untargeted metabolite profilingexperimental sampleMus musculusWhite adipose tissueUHPLC Nexera LC-30Auntargeted analysisLipidomicsmzminenitratepooled sampleuntargeted metabolite profilingQ Exactive (Thermo Fisher Scientific)experimental sample<p>Mass spectrometry was performed using a&nbsp;Q-Exactive Plus mass spectrometer (Thermo Scientific)&nbsp;equipped with an electrospray ionization (ESI) source operating in both positive and negative ion modes. The ESI source parameters were set as follows: heater temperature, 300 °C; sheath gas flow rate, 45 arb; auxiliary gas flow rate, 15 arb; sweep gas flow rate, 1 arb; spray voltage, 3.0 kV; capillary temperature, 350 °C; S-Lens RF Level, 50%. Data were acquired in full scan mode followed by data-dependent MS2 scans (HCD, 10 MS2 scans per full scan). The&nbsp;mass scan range&nbsp;was set from&nbsp;m/z 200 to 1800. The resolution was set at 70,000 for MS1 (at m/z 200) and 17,500 for MS2 (at m/z 200).</p>falseNitrate-Sialin2 Axis Couples ER-Mitochondrial Calcium Signaling with Fatty Acid Metabolism to Drive White Adipose BrowningNutrient cues shape adipose homeostasis; however, the mechanism by which inorganic signals engage organelle networks to drive white fat browning remains unclear. Here, we identify a nitrate-Sialin2 pathway that converts dietary nitrate into a spatially confined thermogenic program. Sialin2 localizes to mitochondria and endoplasmic reticulum (ER) to strengthen ER-mitochondria contacts and engage the inositol 1,4,5-trisphosphate receptor type 1 (IP3R1)-voltage-dependent anion channel 1 (VDAC1)-mitochondrial calcium uniporter 1 (MCU1) conduit, boosting inducible mitochondrial Ca2+ uptake. In parallel, Sialin2 associates with lysosomal acid lipase (LIPA), Acyl-CoA Synthetase Long Chain Family Member 3 (ACSL3), and carnitine palmitoyltransferase 1A (CPT1A) to direct lipid-droplet-derived fatty acids into β-oxidation, thereby fueling the tricarboxylic acid (TCA) cycle and uncoupling protein 1 (UCP1)-dependent respiration. Loss of Slc17a5 abolishes nitrate-evoked browning and metabolic benefits, whereas nitrate supplementation improves adipose thermogenesis and systemic indices in diet-induced obesity without adrenergic stimulation. These findings reveal an organelle-specific nitrate-sensing mechanism that couples ionic signaling with substrate routing to reprogram adipocytes, providing a non-hormonal strategy for restoring metabolic homeostasis.2026-05-172026-03-31MTBLS14192