Spatially Mapping Disease at the Lipid Level

Lipids help compose cell membranes, act as signaling molecules, and play a role in energy storage. Profiling lipid distribution, composition, and relative abundance illuminates the complex biological processes within tissues. “Metabolites and lipids offer more dynamic molecular measures of health and disease than conventional histology,” says Boone Prentice, Associate Professor in the Department of Chemistry at the University of Florida. “Lipids and metabolites are downstream, functional readouts. They report what the tissue is actually doing, which is why they complement transcriptomic and proteomic layers rather than duplicating them.” Researchers explore the lipidome in numerous areas including cancer, neurodegeneration, and metabolic disorders, analyzing lipid dynamics in response to changing environments, diets, disease states, and their treatments.

Moving away from bulk analysis

Technological improvements have driven the lipidomics field, particularly due to advances in mass spectrometry and computational methods. Conventionally, scientists employed bulk methods where tissue samples are homogenized prior to lipid extraction, separation, and detection. The resulting analysis provides information on the average dynamic processes within a tissue, which dilutes or even hides localized lipid signals.

To gain a better understanding of cells as their pathological or physiological states change, researchers are turning toward spatial lipidomics methods.¹ “Lipid localization data can reveal spatial context that bulk lipidomics cannot, such as where specific lipids accumulate within tissues or cells. This helps connect lipid changes to biological function and microenvironments,” notes Francine Yanchik-Slade, Life Sciences Product Specialist at Shimadzu Scientific Instruments.

“Making the measurements spatially offers morphological context and can also improve the limit of detection for certain molecules that are highly abundant in the areas of analysis. Some of the small foci and molecular information that are present can be lost in bulk lipidomics measurements in plasma or other biofluids, even if they are highly abundant in a small section of the sample,” adds Prentice.

Spatial lipidomics with MALDI-MSI

Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) is a laser-based, soft-ionization method that brings spatial analysis to lipidomics.^2,3 Rather than processing bulk samples, it works on thin tissue sections mounted on conductive microscope slides, allowing lipids to be detected in their original environment. “Preserving native tissue architecture is critical for accurate interpretation and validation of spatial lipid data,” says Yanchik-Slade.

MALDI-MSI requires minimal sample prep, detects a broad lipid range with high sensitivity, and combines fast analysis with imaging capabilities.⁴ Fresh frozen tissue, free of chemical modifications, is preferred to preserve the tissue morphology. To begin sample prep, scientists cryosection their tissue to the desired thickness and mount slices to the appropriate slides. Next, they add MALDI matrix to their slides, covering the tissue. The matrix will absorb the laser wavelength and ionize the analyte once inside the instrument. The type of matrix to add depends on several factors, including the lipid class of interest, ionization mode, and resolution.

When it is time for analysis, the MALDI-MSI instrument scans the slide with a laser that penetrates the matrix layer but leaves the underlying tissue intact. This releases lipid ions, and the instrument records the mass spectrum for each pixel throughout the sample. Image processing software creates a 2D spatial map of the tissue’s composition, identifying thousands of lipids in the process in a label-free manner.

“Many researchers rely on optical or fluorescence microscopy to co-register tissue morphology with MSI data,” says Yanchik-Slade. However, combining MALDI-MSI with other imaging modalities can be difficult if the tissue was not handled carefully in the preparation stage. “As a result, experimental design must prioritize preservation of morphology, including careful sample preparation, optimized sectioning, and fixation methods that maintain structural integrity.” Some MALDI-MSI methods are integrating these additional microscopy techniques, enabling direct correlation of lipid distributions with cellular morphology without serial sectioning or separate staining steps.⁵

Spatial lipidomics in disease research and beyond

Lipid dysregulation plays a role in numerous diseases, including metabolic and neurological disorders and cancer.⁶ Spatial lipidomics provides researchers with insights into heterogeneous lipid alterations within these disease states. “Spatial lipidomics enables researchers to resolve localized lipid changes that distinguish disease from control samples, helping to uncover spatially specific mechanisms of action,” notes Yanchik-Slade.

One example of spatial lipidomics providing crucial information comes from researchers studying nonalcoholic fatty liver disease (NAFLD).⁷ Lipid accumulation in the liver is a hallmark of this disorder, but scientists have debated the types of lipids and the importance of their localization within the organ. The researchers performed MALDI-MSI on fresh frozen liver biopsies from patients with varying degrees of NAFLD. The spatial lipid profiles showed metabolic and lipid composition differences in fatty versus non-fatty tissue, highlighting the utility of spatial lipidomics for future NAFLD studies.⁸

One cause of dopaminergic neuron destruction in the brain, leading to Parkinson’s disease-like symptoms, is the metabolism of 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) into a neurotoxin. Researchers used MALDI-MSI on non-human primate coronal brain tissue sections to assess the distribution of various lipids.⁹ They found that MPTP-lesioned samples had depletion of certain long-chain hydroxylated sulfatides in motor-related brain regions, while some long-chain non-hydroxylated sulfatides were elevated in those same regions. This dysregulation of sulfatide metabolism in diseased brains suggested that there was oxidative stress and damage in disease-relevant brain regions, providing grounds for further exploration of this mechanism in Parkinson’s disease.

In addition to disease studies, novel spatial lipidomics technologies are playing a role in broad scientific endeavors. “We’re also seeing an increased use in the pharmaceutical industry, in drug discovery applications including drug pharmacokinetics and pharmacodynamics,” says Prentice. “We are seeing its use in agriculture to study seeds, plant growth and disease, and in forensics, where spatial lipidomics can detect which lipids or fatty acids are present in a fingerprint and help build a profile of that person’s activity.”

New technology on the rise

Enhancing traditional MALDI-MSI provides new capabilities and biological insights. “The field is expected to progress toward higher spatial resolution, potentially reaching single-cell or even subcellular levels. This will allow researchers to better understand intercellular and intracellular lipid dynamics in spatial context,” says Yanchik-Slade.

For example, MALDI-2 (matrix-assisted laser desorption/ionization combined with laser-induced post-ionization) increases sensitivity by enabling smaller pixel sizes, allowing for better spatial single-cell analysis of tissues with more detectable features and ion signal intensities.^5,10

In addition, to better study lipid metabolism and dynamics during development, scientists working with zebrafish embryos developed a MALDI-MSI technique that can image single cells in 3D by analyzing and stacking consecutive cross sections, turning 2D ion maps into volumetric datasets.¹¹

Scientists are also complementing lipidomics studies with other omics modalities to gain deeper insights. “Using a single imaging modality or omics layer can be limiting, whereas integrating lipid and metabolite data with other omics datasets provides a holistic analysis of tissue biochemistry, allowing for a more mechanistic connection of molecular action to phenotype,” says Michael L. Easterling, Vice President of MALDI Imaging at Bruker Daltonics.

This combination is particularly relevant when characterizing tumor heterogeneity. Researchers recently performed spatial lipid, glycan, and peptide analysis on the same breast cancer tissue section with MALDI-MSI.¹² Their results showed the importance of lipids and glycans to tumor subtype characterization in addition to the proteomic data.

Researchers performing spatial multiomics analyses with MALDI-MSI do need to carefully craft their experiments to obtain reliable results. “A key challenge is acquiring sufficient signal quality across sequential runs of the same tissue for each modality,” says Yanchik-Slade. “Sequential imaging can capture multiple data types, but at a high financial and operational cost. Additionally, limitations in instrumentation sensitivity and tagging technologies remain barriers to scalable, routine use. Advances in these areas will be critical to reducing costs and improving throughput.”

Thankfully, as Prentice notes, these advances are underway. “In the next five years, multiomics workflows will become more popular, with better integrations across platforms. Technical aspects will continue to improve, in terms of data integration, image co-registration and pathway analysis, supported both by AI and accessible benchtop technology.”

References

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3. Aichler M, Walch A. MALDI Imaging mass spectrometry: current frontiers and perspectives in pathology research and practice. Laboratory Investigation. 2015;95(4):422-431.

4. Aebisher D, et al. The MALDI method to analyze the lipid profile, including cholesterol, triglycerides and other lipids. Current Issues in Molecular Biology. 2026;48(1):59.

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7. Ščupáková K, Soons Z, Ertaylan G, et al. Spatial systems lipidomics reveals nonalcoholic fatty liver disease heterogeneity. Analytical Chemistry. 2018;90(8):5130-5138.

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9. Kaya I, Nilsson A, Luptáková D, et al. Spatial lipidomics reveals brain region-specific changes of sulfatides in an experimental MPTP Parkinson's disease primate model. Npj Parkinson S Disease. 2023;9(1):118.

10. Soltwisch J, et al. MALDI-2 on a trapped ion mobility quadrupole Time-of-Flight instrument for rapid mass spectrometry imaging and ion mobility separation of complex lipid profiles. Analytical Chemistry. 2020;92(13):8697-8703.

11. Dueñas ME, et al. 3D MALDI Mass spectrometry imaging of a single cell: spatial mapping of lipids in the embryonic development of zebrafish. Scientific Reports. 2017;7(1):14946.

12. Golestan SMJS, Monza N, Fatahian F, et al. Sequential MALDI-MSI-Based multiomics reveals spatial lipid, glycan, and tryptic peptide signatures in breast tumor histopathology. Analytical Chemistry. 2026;98(19):14503-14515.