Metabolomics
Capture the direct signals of phenotypic change through precise metabolite quantification — a direct readout of physiological status.
Lipidomics Analysis
Lipids, alongside proteins and nucleic acids, are key biomacromolecules participating in energy storage, membrane construction, signaling and inflammatory regulation; their dysregulation links to tumors, cardiovascular disease, neurodegeneration and metabolic syndrome. Lipidomics, a metabolomics branch, systematically studies lipid composition, structure, abundance and interactions via sensitive, high-resolution MS and bioinformatics, capturing thousands of lipid dynamics to reveal metabolic networks. It is widely used in biomarker screening, drug-target discovery, nutrition assessment, plant-stress mechanisms and environmental toxicology.
Principle Introduction
Lipidomics separates, identifies and quantifies lipids based on physicochemical differences (polarity, MW, hydrophobicity) through pretreatment, purification, MS and analysis. MS-based lipidomics has two modes: untargeted (detect as many lipids as possible for discovery) and targeted (absolute quantification of known classes/pathways with higher sensitivity and reproducibility). Under ESI, lipids ionize ([M+H]+, [M−H]−) and enter analyzers (Q-TOF, Q-Trap); m/z infers formula, MS/MS infers structure (chain length, double-bond position); databases (LIPID MAPS) and bioinformatics build lipid profiles of dynamic changes.
Literature
In "Hepatic adaptation to chronic metabolic stress primes tumorigenesis" (Cell Metabolism), lipidomics revealed liver lipid remodeling under chronic metabolic stress and its tumor-priming role. Mice on high-fat diet plus insulin resistance and metabolic-hepatocarcinoma patients were analyzed by UHPLC-MS/MS targeted lipidomics. Among ~1,000 lipids, membrane PCs/PEs重构 with long-chain PUFA PCs (PC 38:4, PC 40:6) declining and saturated-chain PCs rising. Mechanism: SREBP-1c-activated lipid synthesis lowered membrane fluidity and activated STAT3, enhancing proliferation; supplementing long-chain PUFA or modulating PC synthase reversed remodeling and suppressed tumorigenesis.
Sample Requirements
≥0.5 g, snap-freeze −80°C, dry ice; note site, condition, strain/sex/age
≥1 g, snap-freeze −80°C, dry ice; note variety, stage, treatment
≥1×10⁷ pellet, PBS wash ×2, snap-freeze −80°C, dry ice; note cell line, culture, treatment
serum/plasma ≥200 μL, urine ≥500 μL, CSF/bile ≥100 μL; serum non-hemolyzed, plasma note anticoagulant (EDTA/heparin); −80°C, dry ice
culture ≥1 mL (OD600≥1.0), pellet snap-freeze −80°C, dry ice; note strain, culture
confirm beforehand; follow analogous storage/shipping
Deliverables
Lipidomics raw data
MS raw spectra (.raw), lipid ID/quantification table (name, formula, m/z, peak area, relative/absolute content).
Differential-lipid report
multivariate plots (PCA, OPLS-DA, volcano), differential results (Fold Change, P, VIP), classification and abundance heatmap.
Bioinformatics
pathway enrichment (KEGG), lipid–disease/process association, biomarker suggestions.
FAQ
Improve chromatography (gradient, column, temperature), tune source/collision energy, add SPE/gel-filtration cleanup, subtract blank controls.
Standardize workflow, add isotope internal standards (ISTD), calibrate MS and insert QC every 10–15 samples, normalize by total peak area or ISTD.
Cross-search LIPID Maps/SwissLipids/HMDB, relax P/VIP thresholds, integrate transcriptomics/proteomics into gene–protein–lipid networks, consult literature or validate in vitro.
