Enhanced Single-Cell Shotgun Lipidomics Workflow with the SELECT SERIES Cyclic IMS

Significance of the topic

The molecular complexity of lipid species within individual cells underpins critical biological processes and disease states. Conventional bulk lipidomics can obscure cell-to-cell variations, whereas single-cell approaches reveal heterogeneity in cellular lipidomes, providing deeper insights into cell function, pathology and therapeutic responses.

Objectives and overview of the study

This work introduces an enhanced shotgun lipidomics workflow combining the SELECT SERIES Cyclic Ion Mobility Spectrometry (IMS) with automated data processing to achieve confident identification and quantification of lipids at the single-cell level. The primary goals were to minimize background interference, improve isomer separation, and generate aligned data matrices suitable for multivariate analysis across cell cohorts.

Methodology

THP-1 leukemia cells served as a proof-of-concept model. Lipids were extracted from bulk suspensions and single-cell equivalents (200, 40, 8 and 1.6 cells per 100 nL) using protein precipitation with deuterated internal standards in 96-well plates. A robotic nanospray ion source delivered samples at 50 nL/min for 2 minutes into a mass spectrometer. Data acquisition employed High Definition MSE in single-pass mode, with 2 ppm mass tolerance and a 3 % CCS window against a predicted CCS library.

Used Instrumentation

• SELECT SERIES Cyclic IMS system (Waters Corporation)
• MassLynx software for data capture
• waters_connect and LipidXplorer for data processing
• EquiSPLASH deuterated lipid standards (Avanti Polar Lipids)

Main results and discussion

Blank experiments revealed volatile polydimethylcyclosiloxane contaminants in ambient air, which were effectively separated in the drift-time dimension, reducing false positives. The optimized workflow identified approximately 295 lipid species at the single-cell level with high mass accuracy (≤2 ppm) and CCS deviation under 3 %. Lipid class distributions remained consistent from low to high abundance species across 1, 8, 40 and 200 cell equivalents. Drift-time separation allowed resolution of isobaric phosphatidylcholine isomers (e.g., PC(34:1) at m/z 758.6) through multipass IMS, enhancing structural coverage.

Benefits and practical applications

• High-confidence lipid identification at minuscule sample volumes
• Reduced chemical background via IMS drift-time filtering
• Aligned quantitative data matrices for statistical analysis
• Applicability in cell biology, disease biomarker discovery, and pharmaceutical screening

Future trends and opportunities

Advancements may include integration of multiplexed internal standards for better quantification, higher-order IMS multipass methods to resolve challenging isomeric species, and coupling with spatially resolved sampling techniques. Machine learning algorithms applied to combined mass, CCS and fragmentation data will further refine lipid annotations and enable predictive lipidomics in single-cell studies.

Conclusion

The enhanced Cyclic IMS shotgun lipidomics workflow provides a robust platform for single-cell lipid profiling, delivering precise identification, contamination removal, and quantitative consistency. This approach paves the way for deeper understanding of cellular lipid heterogeneity and its role in health and disease.

References

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4. Schlosser A, Volkmer-Engert R (2003) Volatile polydimethylcyclosiloxanes in the ambient laboratory air identified as source of extreme background signals in nanoelectrospray mass spectrometry. J Mass Spectrom, 38(5):523–525.