Elucidating Molecular Drivers of Kidney Disease using 3-Dimensional Multimodal Imaging Mass Spectrometry: A Feasibility Study
New insights into the cellular heterogeneity within tissues are being gained using single cell transcriptional profiling, and more recently with new, antibody-based cell dissociation methods (e.g., fluorescence or mass cytometry). However, most of these approaches require dissociation of tissues and separation of cells, which may affect the functional properties of each cell and obscure information about structural relationships between cells in the intact tissues. To date, few attempts have been made using traditional approaches to elucidate the three-dimensional relationships between molecular signatures and tissue morphology. Understanding the three-dimensional relationships between molecular signatures and tissue morphology is of particular importance for the kidney. The human kidney is composed of an average of 1 million functional units, or nephrons, each with at least 26 distinct cell types. These form a network of filtration units, or glomeruli, linked to tubular segments with distinct re-absorptive functions, capillaries, lymphatics and peri-tubular interstitial spaces. Each of these cellular and extracellular compartments function as components of a coordinated network of interdigitating functional elements that are required to maintain normal salt and water homeostasis and blood pressure control. The overall structure and anatomical relationships among different cell types within the human kidney are fairly well understood, and experimental studies have defined the molecular and functional characteristics of individual kidney cell types. However, remarkably little is known about the integration, interactions, and molecular cross-talk between the different cellular compartments in normal kidneys, particularly as they relate to kidney disease. Here we leverage a 3-dimensional multimodal molecular imaging pipeline developed by our research group as part of the Human Biomolecular Atlas Program (HuBMAP) to demonstrate its feasibility for studying kidney disease. Our approach utilizes ultra-high content mass spectrometry (MS)-based 3-dimensional (3-D) imaging to characterize the molecular signatures (lipids, metabolites and proteins) of different cell types and extracellular matrix components at high resolution in the intact human kidney. The imaging data acquired by this unique platform is aligned and fused with 3-D immunofluorescence and histochemical based images to provide an unprecedented combination of molecular and spatial information. As part of this proposal, the development of methods for differential analysis of 3-D molecular imaging data will enable the elucidation of molecular drivers of kidney disease at cellular resolution.

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