HIGH THROUGHPUT MULTI-OMIC ANALYSES AT THE SINGLE CELL LEVEL USING ANALYTICAL SCALE CHROMATOGRAPHY WITH A MULTI-REFLECTING HIGH RESOLUTION MASS SPECTROMETER

Significance of the topic

Single-cell multi-omic profiling is essential for resolving biological heterogeneity masked in bulk analyses. Lipidomics and polar metabolomics at the single-cell level enable discovery of cell-to-cell variation relevant to disease mechanisms, pharmacology and biomarker discovery. However, single-cell analyses demand workflows with exceptional sensitivity, dynamic range, reproducibility and throughput to measure low-abundance analytes reliably.

Study objectives and overview

This study demonstrates a high-throughput LC-MS workflow for concurrent single-cell lipidomic and polar metabolomic profiling using analytical-scale chromatography (2.1 mm) coupled to a multi-reflecting high-resolution time-of-flight mass spectrometer (Xevo MRT P10). The aims were to: (1) adapt standard analytical flow LC for single-cell extracts; (2) evaluate sensitivity, dynamic range and identification confidence; (3) establish a single mobile-phase, multi-omic solution that reduces contamination and increases throughput; and (4) characterize lipid and metabolite differences between two colorectal cell lines (HT-29 and Caco-2).

Methodology

Sample preparation and single-cell sampling:

• HT-29 and Caco-2 cells cultured in DMEM, passaged to ~80% confluency and prepared by trypsinization.
• Cells diluted to ~15,000 cells/mL and individual cells picked with the isoPick platform into LC-MS vials.
• Cells extracted with isopropanol (IPA) prior to LC-MS analysis.

Chromatography and mass spectrometry:

• Analytical-scale reversed-phase chromatography using a CSH Phenyl-Hexyl column (2.1 mm geometry) with MaxPeak coating technology to reduce non-specific adsorption and improve recovery of polar headgroup-containing lipids.
• Short active gradient: 6.0 min (approximately 6 min injection-to-injection), enabling high throughput.
• Mass spectrometry performed on the Xevo MRT P10 multi-reflecting high-resolution TOF instrument using both data-dependent acquisition (DDA) and data-independent acquisition (DIA/SWATH-style) strategies.
• Data exported as mzML automatically during acquisition for downstream processing.

Data processing and identification:

• Lipidomic data processed with LipoStar2 for peak picking, normalization, rules-based curation and database searching (LipidMaps and in-house database).
• Polar metabolite extracts processed with MS-DIAL using an .msp library of authentic standards for putative and curated identifications.
• Statistical analyses included hierarchical clustering (Ward, Euclidean) of top features, volcano plots for fold-change and significance, and quality curation requiring adequate signal-to-noise and MS/MS spectral evidence.

Instrumentation used

• LC: Analytical-scale UHPLC configured with a Waters CSH Phenyl-Hexyl column with MaxPeak surface coating.
• Single-cell picker: isoPick (IotaSciences).
• Mass spectrometer: Waters Xevo MRT P10 multi-reflecting high-resolution TOF.
• Software: LipoStar2 for lipidomics; MS-DIAL for metabolomics; mzML format for data exchange.

Main results and discussion

Analytical performance and data quality:

• High sensitivity and mass accuracy of the Xevo MRT P10 achieved exceptional in-sample dynamic ranges, exceeding five orders of magnitude for curated lipid features in single-cell extracts.
• No carryover or contamination was observed in blank injections bracketing single-cell analyses, demonstrating cleanliness of the workflow.
• Use of the CSH Phenyl-Hexyl column and the selected mobile-phase strategy eliminated problematic isopropanol (IPA) in the mobile phase, reducing background contamination and improving baseline stability.

Identification coverage and biological findings:

• The workflow delivered over 400 high-confidence lipid identifications and more than 300 curated polar metabolite identifications from individual single-cell extracts.
• Major lipid classes detected included triglycerides (TAGs) and multiple phospholipid classes; differential expression between HT-29 and Caco-2 cells was evident across TAG subclasses, phospholipids and ceramides.
• Metabolite identifications included amino acids (e.g., aspartic acid) and other polar compounds relevant to colon cancer biology.

Statistical insights:

• Hierarchical clustering and volcano-plot analyses of top features revealed robust separation between cell lines driven largely by lipidomic differences.
• Stringent curation rules (minimum S/N, MS/MS quality) supported confident annotation despite the low-input nature of single-cell extracts.

Benefits and practical applications of the method

• High throughput: short gradients (~6 min) enable large-scale single-cell studies with analytical-scale instrumentation accessible to many labs.
• Single-workflow multi-omics: phenyl-hexyl chemistry and compatible mobile phases allow lipidomics and polar metabolomics without changing mobile phases or columns, simplifying operations.
• Improved robustness and recovery: MaxPeak coating minimizes non-specific adsorption (notably for phosphate- and carboxylate-containing lipids), improving recovery and S/N.
• Data interoperability: real-time mzML export and compatibility with third-party informatics facilitate flexible downstream analysis and integration.

Future trends and potential applications

• Integration with single-cell isolation platforms and automation for large cohort studies in clinical and translational research (e.g., tumor heterogeneity, drug response profiling).
• Expanding spectral libraries and machine-learning–driven annotation to increase confident identifications, particularly for isomeric lipids and low-abundance metabolites.
• Combining the approach with spatially resolved sampling and orthogonal separations (ion mobility) to refine structural assignments and localize metabolic phenotypes.
• Further optimization of sample handling and extraction chemistry to increase recovery of labile metabolites and improve quantitative accuracy at the single-cell level.

Conclusion

The study demonstrates that conventional analytical-scale LC coupled to a multi-reflecting high-resolution TOF can deliver high-throughput, high-confidence single-cell lipidomic and metabolomic profiling. The combination of rapid chromatography, phenyl-hexyl stationary phase, MaxPeak surface technology and the Xevo MRT P10 provides the sensitivity, dynamic range and robustness needed to identify hundreds of lipids and metabolites from individual cells while minimizing contamination and carryover. This workflow lowers the barrier for adoption across laboratories and supports large-scale single-cell multi-omics applications in biomedical research.

Reference

1. Tsugawa H., Cajka T., Kind T., et al. SWATH-MS/MS and DIA-MS: MS-DIAL data independent MS/MS deconvolution for comprehensive metabolome analysis. Nature Methods. 2015;12:523-526.
2. Authors. Development of a single mobile phase for LC-IM-MS-based discovery lipidomics and metabolic phenotyping: Application to methapyrilene hepatoxicity in the rat. Journal of Chromatography A. 2024;1714:464552.