Increasing reporting confidence in metabolomics; RP and HILIC LC-MS/MS analysis in multiple tissue studies

Importance of the Topic

The chemical and physical diversity of the metabolome poses significant analytical challenges in untargeted studies of complex biological tissues. High reporting confidence and broad metabolite coverage are essential for reliable biological interpretation, drug discovery, and clinical research. Combining complementary chromatographic strategies enhances the ability to detect and distinguish isobaric and highly polar metabolites, reducing false discovery rates and improving data quality.

Objectives and Study Overview

This study aimed to evaluate the performance of a standard reverse-phase (RP) LC-MS/MS workflow alongside a hydrophilic interaction (HILIC) LC-MS/MS separation for multiple murine tissue extracts. Key objectives included:

• Assessing metabolite coverage and analytical throughput of RP methods for lipids and polar compounds
• Applying HILIC to resolve isobaric features poorly separated by RP
• Comparing identification confidence in brain, liver, pancreas, gut, caecal, and faecal tissues
• Demonstrating reduced false discoveries and improved reporting confidence with dual-mode analysis

Methodology and Instrumentation

Samples from various tissues were extracted, dried, and reconstituted in 90% acetonitrile. Analysis was performed on a Shimadzu QTOF LCMS-9030 with external mass calibration.

• Reverse-phase LC: Acquity C18 BEH column (2.1×100 mm, 1.7 µm), 50 °C, 0.4 mL/min, water/0.1% FA and ACN/0.1% FA gradient, 35 min cycle
• HILIC LC: Shim-pack Velox HILIC column (2.1×100 mm, 2.7 µm), 40 °C, 0.3 mL/min, water+10 mM ammonium formate/0.1% FA and ACN:water+10 mM ammonium formate/0.1% FA (92:8), 18 min cycle
• MS scan: m/z 60–1000, 100 ms; DIA-MS/MS: 28 windows (35 Da width), m/z 40–1000, collision energy spread 5–55 V, total cycle 0.99 s
• Data processing: LabSolutions Insight with in-house library of 225 metabolites and authentic standards for high confidence

Main Results and Discussion

Reverse-phase analysis delivered extensive lipid coverage (LPCs, LPEs, fatty acids, conjugates) and broad detection of polar compounds (nucleotides, amino acids, purines). However, several highly polar isobaric features co-eluted early (<0.9 min), complicating assignment in complex matrices.

HILIC separation successfully:

• Resolved co-eluting signals at m/z 118.0853 into valine, 5-aminopentanoic acid, norvaline, and trimethylglycine in gut and faecal extracts
• Distinguished acetylcholine and 4-trimethylammoniobutanoate at m/z 146.1176 in pancreas tissue
• Separated isoleucine and leucine, as well as alanine and beta-alanine, in brain and caecal samples

DIA-MS/MS spectra matched authentic standards or third-party repositories, reinforcing identification confidence.

Benefits and Practical Applications

Implementing a dual-mode LC-MS/MS strategy offers:

• Enhanced metabolome coverage by integrating complementary retention mechanisms
• Increased reporting confidence for highly polar analytes, reducing false discovery rates
• Reliable identification of isobaric and structurally similar metabolites across diverse tissue types
• High throughput with acceptable cycle times for routine metabolomic profiling

Future Trends and Potential Applications

Further developments may include:

1. Automation of method switching and data integration pipelines for RP and HILIC workflows
2. Expansion of spectral libraries with collision cross section (CCS) and ion mobility data
3. Integration with machine-learning algorithms to predict chromatographic retention and fragmentation patterns
4. Application to human clinical samples and microbiome-host interaction studies

Conclusion

Combining reverse-phase and HILIC LC-MS/MS significantly improves the detection and accurate identification of both lipid and highly polar metabolites in complex tissue matrices. The complementary approaches deliver high metabolome coverage, resolve isobaric compounds, and enhance reporting confidence, supporting robust untargeted metabolomics workflows.

Reference

Barnes A, Armitage E, Loftus N. Increasing reporting confidence in metabolomics; RP and HILIC LC-MS/MS analysis in multiple tissue studies. Shimadzu Corporation, Manchester, UK.