Shimadzu Selection Guide Metabolite Analysis - Metabolomics Product Portfolio

Importance of the topic

Metabolomics provides a window into the dynamic changes of small molecules produced in living systems. By systematically profiling metabolites, researchers can gain insight into disease mechanisms, discover biomarkers, optimize fermentation in biotechnology, assess food quality, and guide drug development. High-throughput, reproducible analytical platforms are key to unlocking its practical potential across medical, food, and industrial biotechnology sectors.

Objectives and Study Overview

This white paper reviews Shimadzu’s end-to-end metabolomics portfolio, spanning targeted quantitative LC-MS/MS and GC-MS/MS, high-resolution Q-TOF non-targeted workflows, imaging mass spectrometry, and comprehensive method databases and software. It aims to illustrate how integrated technologies enable wide-targeted analysis of primary metabolites, lipids, bile acids, short-chain fatty acids, D/L amino acids, phospholipids, and cell culture exometabolites, as well as multi-omics data interpretation.

Methodology and Used Instrumentation

A series of ready-to-use method packages streamline quantitation by combining optimized sample preparation protocols, chromatography conditions, and MRM transitions:

• Wide-target quantitative metabolomics: LCMS-8060/MS and GCMS-TQ8050NX for simultaneous analysis of >475 compounds.
• Lipid mediators and phospholipids: Triple-quad LC-MS/MS method packages covering 214 bioactive lipids and 867 phospholipid transitions.
• Cell culture profiling: 17-minute MRM method for 95 culture medium components.
• Bile acid panel: 28 primary and secondary bile acids with glycine/tauro-conjugates.
• Short-chain fatty acids and organic acids: 22 analytes derivatized with 3-NPH.
• D/L amino acids: high-sensitivity chiral separation without derivatization.

Non-targeted analysis is performed on the Q-TOF LCMS-9030, delivering high-mass accuracy and sensitivity, paired with Signpost MS multivariate software. Imaging metabolomics uses the iMScope TRIO MALDI-TOF for spatial mapping. Advanced sampling via DPiMS-8060 probe electrospray ionization allows direct analysis without chromatographic separation. Software solutions include LabSolutions Insight for high-throughput quantitation, Traverse MS for MRM data processing, and the GARUDA-based Multi-omics Analysis Package for pathway visualization and statistical analysis.

Main Results and Discussion

• Simultaneous quantitation of primary metabolites enabled discrimination of commercial beers and clustering by flavor profiles.
• GC-MS/MS with Smart Metabolites Database achieved 475-compound MRM analysis; PLS regression linked coffee bitterness to glycine-3TMS and mannitol-6TMS.
• Q-TOF workflows detected known and unknown metabolites in culture supernatants, mapping temporal changes in tryptophan metabolites such as N′-formylkynurenine.
• Imaging metabolomics localized green tea polyphenol strictinin in mouse kidney pelvis and mapped imidacloprid pesticide within tomato stem.
• Lipid mediator profiling in tissues quantified 196 eicosanoids in 20-minute runs; phospholipid MRM libraries revealed organ-specific PUFA–PC distributions.
• Cell culture profiling identified dynamic shifts in 27 amino acids and vitamins over six days of iPS cell culture.
• DPiMS-8060 probe-MS enabled direct mouse liver and brain metabolome analysis, flagging taurine variations in a liver injury model.

Benefits and Practical Applications

Shimadzu’s integrated portfolio offers:

• Rapid deployment with “ready-to-use” methods, eliminating extensive method development.
• High throughput and robust quantitation across diverse matrices (blood, tissue, food, cell media).
• Flexible workflows supporting targeted, non-targeted, imaging, and multi-omics approaches.
• Comprehensive software suite for data processing, statistical evaluation, and pathway mapping.
• Enhanced reproducibility and cross-laboratory comparability through standardized protocols and internal standards.

Future Trends and Potential Applications

Emerging directions in metabolomics include:

• AI-driven peak picking and automated data workflows to reduce manual intervention.
• Expansion of probe-based ionization for real-time, in situ metabolome monitoring.
• Integration of single-cell metabolomics and spatial omics for finer resolution of biological heterogeneity.
• Cloud-based analytic platforms and open data standards (e.g., GARUDA) for seamless multi-laboratory collaboration.
• Application of LLMs for predictive biomarker discovery and metabolic pathway inference.

Conclusion

Shimadzu’s comprehensive suite—combining versatile mass spectrometers, curated method and compound databases, and advanced data-analysis software—empowers researchers to conduct high-sensitivity, high-throughput metabolomics across medical, food, and biotechnological fields. These integrated solutions accelerate discovery, enhance reproducibility, and pave the way for future innovations in multi-omics research.

References

No external references provided; method packages and application notes are part of Shimadzu’s documentation.