Novel MALDI Imaging solution empowered by a timsTOF fleX and dedicated bioinformatics pipeline for identification of lipids from tissue

Significance of the Topic

The spatial mapping of lipids in tissue sections is crucial for understanding disease mechanisms and tissue biochemistry. MALDI Imaging delivers label-free detection of diverse compounds with high spatial resolution, enabling insights into molecular distributions relevant to pathology and drug research.

Study Objectives and Overview

This study presents a novel automated workflow for lipid identification in MALDI Imaging datasets acquired on a timsTOF fleX mass spectrometer. The pipeline integrates high-speed, high-resolution data acquisition with dedicated bioinformatics to generate annotated spatial images of lipids in rat brain tissue.

Methodology

Sample preparation and data processing steps:

• Fresh-frozen rat brain sections mounted on conductive glass slides
• Matrix application using a TM Sprayer
• Data acquisition on timsTOF fleX in positive ion mode (m/z 300–1000), 20 μm pixel size, 10 kHz laser repetition
• Spectral visualization and ROI definition in SCiLS Lab
• Feature extraction, de-isotoping and deconvolution in MetaboScape using the T-ReX2 algorithm
• Lipid annotation via a custom Analyte List matched to the LIPID MAPS database
• Annotation Quality scoring based on accurate mass and isotopic fidelity

Instrumentation

Key instrumentation:

• timsTOF fleX mass spectrometer (Bruker Daltonik GmbH)
• TM Sprayer matrix deposition system (HTX Technologies)
• SCiLS Lab and MetaboScape software for data analysis (Bruker)

Main Results and Discussion

The workflow successfully annotated tens of lipids automatically, demonstrating high-confidence identifications exemplified by PC(36:1) localized to white matter regions in rat brain. Comparative visualization confirmed agreement with literature distributions. The combined use of MetaboScape and SCiLS Lab streamlines annotation and spatial mapping of hundreds to thousands of molecular features.

Benefits and Practical Applications

This pipeline enhances throughput and reproducibility in spatial lipidomics, supporting:

• Molecular marker discovery across tissue regions
• Region-specific biochemical analysis
• Integration into SpatialOMx studies for morphological and molecular correlation

Future Trends and Potential Applications

Emerging directions include integration with multimodal imaging, expansion of lipid databases, machine learning for automated annotation, and translation to clinical diagnostics and drug development workflows.

Conclusion

The described MALDI Imaging workflow on timsTOF fleX coupled with a dedicated bioinformatics pipeline enables rapid, automated lipid annotation and spatial visualization, advancing spatial lipidomics and enabling deeper tissue-based molecular insights.

References

Li et al. (2016). Sci Rep. 6:37903