Multimodal mass spectrometry imaging of mouse and human liver

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Project summary We request an administrative supplement to build the first spatially-resolved 3D map of the human liver integrating both cellular components and metabolites and the extracellular matrix for the first time. This collaborative effort between the HuBMAP Transformative Technology Development team led by Dr. Tian (University of Pittsburgh, Pitt) and Dr. Stockwell (Columbia University, CU) and the Demonstration Program team led by Dr. Naba (University of Illinois Chicago, UIC) is in line with HuBMAP’s vision for comprehensive organ mapping, providing an unprecedented view into liver architecture with a depth never achieved before. An extensive effort has been made to profile the extracellular matrix (ECM) composition – or matrisomes – of various organs; however, there is still lack of study on the spatial distribution of ECM components surrounding cells and contributing to functional multicellular structures, their variation in normal vs. disease, and molecular signaling/crosstalk with cells. The challenges lie in (1) the lack of panels of validated anti-ECM antibodies, (2) the difficulty in performing multiplexed mapping of multi-level biomolecules at single-cell resolution, and (3) the difficulty to integrate datasets generated using multiple “-omic” modalities in a single sample. The team led by Dr. Tian developed a mass spectrometry imaging (H2O)n>25k-GCIB-SIMS dual-SIMS workflow, integrating untargeted metabolomics, lipidomics, and targeted proteomics (up to 40 targets) on the same tissue section at subcellular spatial resolution (1 µm). Together with the team led by Dr. Stockwell, a robust multimodal imaging workflow has been established to generate a spatially-resolved atlas of liver tissue, visualizing major tissue structures, cell types, and metabolic states of cell types. Leveraging the draft of the human liver matrisome obtained by Dr. Naba and the content of MatrisomeDB, the database of ECM proteomics datasets her team created, we propose to create a spatially-resolved map of essential human liver matrisome components, along with our current multiplexed liver map at the single-cell level. This project will present a new opportunity to delineate the spatial organization of cellular and extracellular biomolecules, the definition of functional tissue units, including information on microenvironmental niches. This will allow, in the future, to define the nature of the interactions and signals established between cells and their surrounding ECM, and to begin to understand disease-associated dysregulations (e.g., fibrosis, cirrhosis, hepatocellular carcinoma).