Tissue is highly organized with diverse cells that interact and communicate. Together with numerous biomolecules (e.g. metabolites and lipids), the multilevel heterogeneities drive the biological function and disease-associated discoordination. The spatial complexities are often ignored by traditional bulk assay. Mass spectrometry imaging holds the potential to visualize cellular/biomolecular heterogeneity directly in tissue. However, it is challenging to achieve high spatial resolution and high chemical sensitivity toward different biomolecules. Moreover, the correlation of spatial omics in a single sample is impossible due to the difficulty of preserving the transient metabolites. To overcome these analytical hurdles, we developed water cluster ion beam secondary ion mass spectrometry and established multimodal imaging to dissect single cells in tissue. The successive (H2O)n (n&gt;28k)-GCIB-SIMS and C60-SIMS imaging were employed to profile untargeted metabolites/lipids and targeted proteins by lanthanides antibodies (~ 40 in one acquisition) at 1 µm resolution.1, 2 The primary ion source, (H2O)n(n&gt;28k)-GCIB enhances chemical sensitivity, improves beam focus, reduces matrix effect, and extends detection ranges up to m/z 6000. 3 Coupled with cryogenic analysis, the spatiotemporal distribution of metabolites and lipids the tissue is revealed at a near-nature-state. 4 The AI-aided computational processing is used to register the omics in different cell types for further discriminant analysis. With the new development, a number of tissues are imaged. On breast cancer tissue, the variation of over 100 biomolecules are observed in different types of cells (e.g., macrophages, epithelial cancer cell, immune cells), demonstrating the metabolic reprogramming and biomolecular marker for tumor cell survival and neoplastic transformation of breast tissue. 5 On liver tissue, distinct lipid clusters colocalize with periportal and pericentral proteins, and metabolic and lipidomic signature varies in distinct liver cells (e.g., sinusoidal, Kupffer, hepatocytes, Ito stellate, immune cells). Similar to protein markers, further clustering analysis shows that metabolites and lipids classify the cell types for the first time. Multimodal SIMS imaging opens broad applications for exploring various biological phenomena of cellular/biomolecular interactions in health/disease.

3D single-cell spatial biology using giant cluster ion beam secondary ion mass spectrometry

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