The Achievability of Single Cell Lipidomics Utilizing the Novel Xevo™ MRT Mass Spectrometer

Importance of the Topic

Single-cell lipidomic profiling uncovers metabolic and phenotypic heterogeneity that is hidden in bulk analyses.
Understanding lipid diversity at the individual cell level is critical for elucidating cellular functions, disease mechanisms, and therapeutic responses.

Goals and Overview of the Study

This application note evaluates the feasibility of detecting and identifying lipids from the equivalent of a single THP-1 cell using the Waters Xevo™ MRT mass spectrometer coupled to an ACQUITY™ Premier LC system.
The authors aim to demonstrate system sensitivity, dynamic range, mass accuracy, and data reproducibility for single-cell lipidomics applications.

Methodology

THP-1 cells were cultured, counted, and harvested before extraction in isopropanol spiked with EquiSPLASH™ internal standards.
Extracts were serially diluted over five orders of magnitude (10,000 to 1 cell equivalents) and injected (2 µL) onto a reversed-phase C18 CSH column with a 12-minute gradient.
Data were acquired in positive ESI mode at 10 Hz with MSE continuum and lockmass correction using leucine enkephalin.
Raw mzML files were processed in Lipostar for peak picking and database matching against in-house and LipidMaps collections, then visualized in MetaboAnalyst.

Used Instrumentation

• Mass Spectrometer: Waters Xevo™ MRT MS with electrospray ionization (capillary 2.8 kV, cone 40 V, desolvation 500 °C) and MSE acquisition at 10 Hz.
• Liquid Chromatography: ACQUITY™ Premier UPLC C18 CSH column (1.7 µm, 2.1×100 mm) with ACN/H2O and IPA/ACN mobile phases, 12 min total run time, column at 55 °C.
• Software: waters_connect for acquisition, Lipostar v2.1.7b3 for data processing, MetaboAnalyst for statistical analysis.

Main Results and Discussion

High sensitivity enabled detection of over 150 lipids at single-cell levels and nearly 700 lipids at bulk levels (10,000 cells) using stringent curation.
Dynamic range spanned five orders of magnitude with consistent sub-ppm mass accuracy (<500 ppb RMS).
Key lipids such as PC(36:2) and PE(36:1) were tracked linearly from bulk to single-cell samples, with clear isotopic patterns and MS2 fragmentation confirming identifications.
Use of Lipostar’s confidence scoring and in silico MS/MS validation reduced false positives and facilitated robust annotation.

Benefits and Practical Applications

• Enables interrogation of cell heterogeneity in immunology, cancer, and developmental biology.
• Supports QA/QC workflows by providing reproducible lipid profiles across wide concentration ranges.
• Seamless export in mzML format allows integration with third-party informatics platforms.

Future Trends and Opportunities

Integration of single-cell lipidomics with transcriptomics and proteomics will deepen multi-omics insights.
Advances in microfluidic sample handling and ionization techniques may further reduce sample requirements and boost throughput.
Machine learning-driven spectral annotation could accelerate high-confidence lipid identification in complex biological matrices.

Conclusion

The Xevo™ MRT MS paired with ACQUITY Premier LC demonstrates the capability to reliably identify hundreds of lipids from single-cell equivalents with high sensitivity, accuracy, and reproducibility.
This platform, combined with Lipostar processing, offers a robust workflow for advancing single-cell lipidome research.

References

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4. G. Liebisch et al., J. Lipid Res., 2020, 61, 1539–1555.
5. Z. Pang et al., Nat Commun, 2024, 15, 3675.
6. L. Goracci et al., Anal Chem, 2024, 96, 1468–1477.