Spatial Mapping of Lipids and Elements by Mass Microscopy and Integration with LA-ICP-MS in the Diabetic Mouse Pancreata

Significance of the Topic

The islets of Langerhans play a vital role in glucose homeostasis by secreting insulin, glucagon and other hormones. Spatially resolved mapping of lipids and trace elements within intact pancreatic tissue can reveal metabolic heterogeneity and pathological alterations in diabetes models. Traditional bulk lipidomics often requires islet isolation, which may perturb basal metabolite levels, underlining the need for high‐resolution in situ approaches.

Objectives and Overview of the Study

This study aims to integrate high‐resolution mass microscopy imaging of lipids with laser ablation‐inductively coupled plasma‐mass spectrometry (LA‐ICP‐MS) to achieve spatial co‐mapping of lipids and elements in the pancreata of a diabetic mouse model overexpressing mitochondrial ferritin (FtMT). The goal is to characterize lipid distributions in islet subregions and to correlate these patterns with elemental profiles, providing insights into islet hyperplasia and diabetic pathophysiology.

Methodology and Instrumentation

Frozen mouse pancreata were cryosectioned at 10 µm and mounted onto In2O3–SnO2 slides. Matrix application was automated using the iMLayer system with 2‐mercaptobenzothiazole (positive mode) and 1,5‐diaminonaphthalene (negative mode). Lipid imaging was performed on an iMScope QT mass microscope at spatial resolutions down to 5–7 µm. Spatial elemental distribution was measured with an imageBIO266 laser ablation system coupled to an ICPMS‐2030. Data analysis and spatial segmentation were carried out using IMAGEREVEAL MS software; multivariate processing employed MetaboAnalyst 5.0.

Key Results and Discussion

• Unsupervised segmentation differentiated islet cores, alpha cell zones and exocrine regions based on lipid ion signatures.
• Principal component analysis and variable importance in projection highlighted distinct lipid species (e.g., SM 34:1;O2) enriched in islet subregions.
• FtMT transgenic mice exhibited pronounced islet hyperplasia with altered lipid profiles compared to wild‐type controls.
• LA‐ICP‐MS revealed that zinc localized predominantly to islets, iron accumulated in vasculature, and phosphorus showed uniform distribution.
• FtMT overexpression led to increased zinc levels in hyperplastic islets, linking mitochondrial ferritin to elemental homeostasis.

These findings demonstrate the power of combined lipid and elemental imaging to dissect cellular microenvironments within diabetic pancreas.

Benefits and Practical Applications

• Preservation of tissue architecture enables in situ metabolic and elemental analysis.
• High spatial resolution facilitates sub‐islet heterogeneity studies.
• Minimal sample manipulation reduces metabolite perturbation.
• Approach applicable to preclinical diabetes research and quality control in pharmaceutical development.

Future Trends and Potential Applications

• Extension to additional molecular classes (e.g., peptides, metabolites) via multimodal imaging.
• Integration with single‐cell technologies and machine learning for automated region classification.
• Development of in vivo compatible imaging probes for real‐time metabolic mapping.
• Translation of workflows to clinical biopsy analysis for improved diagnostic assays.

Conclusion

The integration of mass microscopy lipid imaging and LA‐ICP‐MS provides a comprehensive platform for spatial metabolomics and elemental profiling in diabetic pancreas models. This multimodal strategy uncovers molecular and elemental signatures relevant to islet biology and disease, offering a pathway to enhanced understanding and potential diagnostic innovations.

References

• Ye et al. J Clin Invest. 2018;128(3):1178–1189.
• Kusminski et al. Diabetes. 2020;69(3):313–330.
• MetaboAnalyst 5.0; available at www.metaboanalyst.ca.