spatial-molecular-imaging-of-the-glycome-using-mass-spectrometry

Spatial Molecular Imaging of the Glycome Using Mass Spectrometry

The spatial organization of the glycome within tissues is key to the molecular basis for physiological function. The diverse and dynamic glycome is ...

University of Florida, Gainesville

Matrix assisted laser desorption/ionization imaging has greatly improved our understanding of spatial biology, however a robust bioinformatic pipeline for data analysis is lacking. Here, we demonstrate the application of high-dimensionality reduction/spatial clustering and histopathological annotation of matrix assisted laser desorption/ionization imaging datasets to assess tissue metabolic heterogeneity in human lung diseases. Using metabolic features identified from this pipeline, we hypothesize that metabolic channeling between glycogen and N-linked glycans is a critical metabolic process favoring pulmonary fibrosis progression. To test our hypothesis, we induced pulmonary fibrosis in two different mouse models with lysosomal glycogen utilization deficiency. Both mouse models displayed blunted N-linked glycan levels and nearly 90% reduction in endpoint fibrosis when compared to WT animals. Collectively, we provide conclusive evidence that lysosomal utilization of glycogen is required for pulmonary fibrosis progression. In summary, our study provides a roadmap to leverage spatial metabolomics to understand foundational biology in pulmonary diseases.

Spatial metabolomics reveals glycogen as an actionable target for pulmonary fibrosis.

Lung adenocarcinoma (LUAD) is an aggressive cancer defined by oncogenic drivers and metabolic reprogramming. Here we leverage next-generation spatial screens to identify glycogen as a critical and previously underexplored oncogenic metabolite. High-throughput spatial analysis of human LUAD samples revealed that glycogen accumulation correlates with increased tumour grade and poor survival. Furthermore, we assessed the effect of increasing glycogen levels on LUAD via dietary intervention or via a genetic model. Approaches that increased glycogen levels provided compelling evidence that elevated glycogen substantially accelerates tumour progression, driving the formation of higher-grade tumours, while the genetic ablation of glycogen synthase effectively suppressed tumour growth. To further establish the connection between glycogen and cellular metabolism, we developed a multiplexed spatial technique to simultaneously assess glycogen and cellular metabolites, uncovering a direct relationship between glycogen levels and elevated central carbon metabolites essential for tumour growth. Our findings support the conclusion that glycogen accumulation drives LUAD cancer progression and provide a framework for integrating spatial metabolomics with translational models to uncover metabolic drivers of cancer.

Glycogen drives tumour initiation and progression in lung adenocarcinoma.

High-resolution spatial imaging is transforming our understanding of foundational biology. Spatial metabolomics is an emerging field that enables the dissection of the complex metabolic landscape and heterogeneity from a thin tissue section. Currently, spatial metabolism highlights the remarkable complexity in two-dimensional (2D) space and is poised to be extended into the three-dimensional (3D) world of biology. Here we introduce MetaVision3D, a pipeline driven by computer vision, a branch of artificial intelligence focusing on image workflow, for the transformation of serial 2D MALDI mass spectrometry imaging sections into a high-resolution 3D spatial metabolome. Our framework uses advanced algorithms for image registration, normalization and interpolation to enable the integration of serial 2D tissue sections, thereby generating a comprehensive 3D model of unique diverse metabolites across host tissues at submesoscale. As a proof of principle, MetaVision3D was utilized to generate the mouse brain 3D metabolome atlas of normal and diseased animals (available at https://metavision3d.rc.ufl.edu ) as an interactive online database and web server to further advance brain metabolism and related research.

AI-driven framework to map the brain metabolome in three dimensions.

Analysis of metabolites provides key insights into brain physiology and function. Due to post-mortem metabolism, both the euthanasia method and dissection time can make a critical difference. Here, we describe a protocol to euthanize rodents by microwave irradiation. This workflow details steps for animal placement, tissue fixation, and post-fixation processing. This protocol enables the rapid halting of metabolic activity for the accurate assessment of the metabolome in situ for analyses such as mass spectrometry and nuclear magnetic resonance. For complete details on the use and execution of this protocol, please refer to Juras et al..

Protocol for high-power, brain-focused microwave fixation to define rodent metabolism.

Metabolites, lipids, and glycans are fundamental but interconnected classes of biomolecules that form the basis of the metabolic network. These molecules are dynamically channeled through multiple pathways that govern cellular physiology and pathology. Here, we present a framework for the simultaneous spatial analysis of the metabolome, lipidome, and glycome from a single tissue section using mass spectrometry imaging. This workflow integrates a computational platform, the Spatial Augmented Multiomics Interface (Sami), which enables multiomics integration, high-dimensional clustering, spatial anatomical mapping of matched molecular features, and metabolic pathway enrichment. To demonstrate the utility of this approach, we applied Sami to evaluate metabolic diversity across distinct brain regions and to compare wild-type and Ps19 Alzheimer's disease (AD) mouse models. Our findings reveal region-specific metabolic demands in the normal brain and highlight metabolic dysregulation in the Ps19 model, providing insights into the biochemical alterations associated with neurodegeneration.

Article	Year
Spatial metabolomics reveals glycogen as an actionable target for pulmonary fibrosis. Nature communications\| PubMed ID: 37179348	2023
Glycogen drives tumour initiation and progression in lung adenocarcinoma. Nature metabolism\| PubMed ID: 40069440	2025
AI-driven framework to map the brain metabolome in three dimensions. Nature metabolism\| PubMed ID: 40102678	2025
Protocol for high-power, brain-focused microwave fixation to define rodent metabolism. STAR protocols\| PubMed ID: 40287939	2025
Spatial mapping of the brain metabolome lipidome and glycome. Nature communications\| PubMed ID: 40355410	2025

Ramon C. Sun

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