Development
Low-input and spatially defined lipidomics: bringing 4D lipidomics to small cell populations and microdissected tissue regions.
Many biologically relevant samples, such as defined tissue regions, sorted cell populations, organoids, or organelle fractions, contain too little material for conventional lipidomics. We are implementing nano-UPLC lipidomics and low-input sample preparation, and coupling these to laser microdissection, so that lipid composition can be studied where it matters biologically.
Development lines
- Nano-UPLC-MS/MS lipidomics on ion mobility and Orbitrap platforms
- Low-input sample preparation with minimal losses and contamination
- Laser microdissection via NL-BioImaging at Amsterdam UMC
- Structural annotation from limited material
- Status: method development and pilot projects
Nano-UPLC lipidomics
Nano-flow chromatography substantially improves ionization efficiency and sensitivity compared with conventional flow rates, bringing species-level lipidomics within reach for samples of tens of cells.
- Sensitivity for small cell populations and tissue micro-regions
- Compatibility with ion mobility for 4D annotation
- Validation of linearity, carry-over, and blank contributions at low input
- QC harmonized with standard-flow workflows
Spatially defined sampling
Imaging defines where to sample. Laser microdissection at the NL-BioImaging facility at Amsterdam UMC isolates selected tissue regions or cell groups, which are then analysed by nano-UPLC 4D lipidomics.
- Region selection guided by histology, fluorescence, or immunostaining
- Microdissection of regions down to tens of cells
- Lipid extraction optimized for microdissected material
- Lipid profiles linked back to their tissue context
From tissue region to lipid profile
Figure 3. Spatially informed low-input lipidomics (in development). Tissue sections are imaged to select regions of interest, which are isolated by laser microdissection, extracted with low-input protocols, and analysed by nano-UPLC 4D lipidomics, yielding lipid profiles anchored to their tissue context.
These workflows are under active development. We welcome pilot collaborations with groups that have well-defined questions requiring low-input or spatially defined lipidomics.