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Integrated Spatial Metabolomics and Proteomics from the Same Tissue Section Using a Conductive ITO-PET Slide

wang, h.; Li, Y.

2026-09-14 molecular biology
10.64898/2026.09.07.749981 bioRxiv
Show abstract

Integrating spatial metabolomics and spatial proteomics on the same tissue section remains challenging because matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) and laser capture microdissection (LCM)-based proteomics impose different requirements on sample slides. Here, we developed and systematically evaluated a conductive indium tin oxide-coated polyethylene terephthalate (ITO-PET) slide that enables sequential MALDI-MSI and LCM-liquid chromatography-mass spectrometry (LCM-LC-MS) analysis of the same tissue section. Using mouse brain tissue as a model, ITO-PET provided MALDI-MSI performance closely comparable to conventional ITO-glass, including spectral concordance (Pearson correlation, R = 0.90), ion detection coverage, metabolite annotation, signal intensity distribution, and preservation of spatial molecular patterns. Following MALDI-MSI, the ITO-PET slide enabled cutting-mode LCM and yielded proteomic signal intensities and numbers of identified protein groups comparable to those obtained with conventional PEN-glass slides. Across different tissue sampling areas, proteomic signal intensity distributions, precursor ion counts, and protein group identifications remained broadly comparable before and after MALDI-MSI, with substantial overlap in identified protein groups. Similar patterns were observed in mouse kidney, lung, spleen, and liver tissues, further supporting the applicability of the workflow across different tissue types. By combining the electrical conductivity required for MALDI-MSI with the mechanical properties required for LCM cutting, the ITO-PET slide addresses a major material incompatibility between the two analytical modalities and enables sequential spatial metabolomic and proteomic analysis from the same tissue section. This workflow provides a practical analytical platform for obtaining complementary molecular information from spatially limited biological specimens.

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