Untargeted spatial lipidomics combines mass spectrometry imaging (MSI) with lipid profiling to visualize the distribution and relative abundance of lipids directly within tissue sections. Unlike bulk lipidomics, it preserves tissue architecture and reveals where specific lipid species are localized, enriched, or redistributed, enabling studies of tissue-specific lipid organization, heterogeneity, and metabolic remodeling.

Untargeted spatial metabolomics provides broad coverage of most small-molecule metabolites using a general analysis workflow and annotation via the spatial metabolomics database. It typically detects 1,400+ compounds, including various metabolite classes and some lipids, making it ideal for exploratory studies of diverse metabolic pathways.

Untargeted spatial lipidomics, in contrast, is specifically optimized for lipid detection. It uses lipid-focused methods and a dedicated lipid database, with typical detection of 600+ lipids in animal tissues, providing higher-confidence lipid identification. This approach is ideal for studies specifically focused on lipid metabolism and spatial lipid organization.

Samples can be submitted as fresh-frozen tissue blocks or tissue sections. Tissue blocks should be rapidly dissected under cold conditions and embedded in a suitable medium (e.g., CMC or FSC22). Sections should be cut to 8–50 µm thickness and mounted on ITO-coated slides for MALDI-MSI analysis. Storage at −80°C and dry ice shipping is required. For sections, 4 per sample are recommended: 1 for H&E staining, 3 for MSI analysis or backup.

For MALDI-based Spatial Lipidomics, available spatial resolutions include 5, 10, 20, 50, and 100 µm.

The resolution should be chosen based on the sample type, the spatial heterogeneity of the lipids, and the desired level of detail for analysis. For large or heterogeneous samples (e.g., organs), lower resolutions (100 µm to 50 µm) are typically sufficient to observe broad metabolite distributions, while higher resolutions (10 µm to 5 µm) are necessary for smaller, more homogeneous samples (e.g., cellular or subcellular structures) to capture finer details. If lipids are widely distributed, a lower resolution is adequate, but if they are localized to small regions (e.g., organelles or specific cell types), a higher resolution provides better visualization of spatial heterogeneity.

Typical Resolutions Used:

• 100 µm: Suitable for large tissue sections or general metabolite distribution mapping.
• 50 µm: Provides a good balance between resolution and data volume for tissues or larger regions of interest.
• 20 µm: Used for more detailed mapping of tissue microstructures.
• 10 µm or 5 µm: High-resolution imaging for single cells or specific subcellular structures.

Different lipid classes respond better to specific ionization modes due to their chemical properties. For example, MG, DG, and TG (glycerolipids) are detected more efficiently in positive ion mode, while FFA, LPG, and LPS perform better in negative ion mode. Some lipids, such as Cer and SM, show similar detection in both modes. If you have specific lipid classes of interest, please contact us, and we will select the optimal ionization mode tailored to your study.