Byoung-Kyu Cho (St. Louis, MO / US), Jessica Lukowski (St. Louis, MO / US), Minsoo Son (St. Louis, MO / US), Antonia Zamacona Calderon (St. Louis, MO / US), Young Ah Goo (St. Louis, MO / US)
Background: Spatial omics technology has revolutionized biomolecular analysis by preserving molecular spatial context in tissues, offering applications in neuroscience, cancer biology, and drug discovery. We introduce an advanced approach, MALDI-MSI-guided LCM-MS, which combines mass spectrometry imaging (MSI) with laser capture microdissection (LCM). This approach allows for comprehensive profiling and quantitative analysis of the proteome, metabolome, and lipidome, offering new insights into complex biological systems and molecular distribution in a wide range of tissue types.
Methods: We employed fresh frozen mouse brain tissues (n=3) for method development. MALDI-MSI used timsTOF fleX MALDI-2, processed with SCiLS, METASPACE, and SwissLipids. LCM-proteomics utilized timsTOF Pro2, processed with Mascot and Scaffold Quant. LCM-metabolomics and lipidomics used Orbitrap IDX Tribrid Mass Spectrometer, processed with Compound Discoverer. We tested the method on six mouse brain tissues from old and young groups (n=3 each), which underwent MALDI-MSI and LCM-proteomics.
Results: MALDI-MSI identified 300+ putative metabolites and lipids in mouse brain, with [PC (38:2) +K]+ and [PC (32:0) +Na]+ showing high abundance in the hippocampus and cortex. LCM-omics of MALDI-guided regions (1 million cells) detected 300+ small molecules and 2800 proteins. When applied to different age groups of mice, our approach identified 3900+ proteins in LCM-proteomics. Among these, 778 and 161 proteins exhibited differential expression in the cortex and hippocampus, respectively, between the two age groups. Biological network analysis revealed the involvement of differentially expressed proteins in aging-related pathways, such as mitochondrial dysfunction, glutamatergic synapse, and AMPK signaling.
Conclusions: Our integrated approach of MALDI-MSI and LCM-MS in spatial omics provides a comprehensive and quantitative understanding of complex biological systems. This method holds great potential for advancing neuroscience research and gaining deeper insights into molecular mechanisms underlying age-related changes in the brain.