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N‐linked protein glycosylation in the brain is an understudied facet of glucose utilization that impacts a myriad of cellular processes including resting membrane potential, axon firing, and synaptic vesicle trafficking. Currently, a spatial map of N‐linked glycans within the normal and Alzheimer's disease (AD) human brain does not exist. A comprehensive analysis of the spatial N‐linked glycome would improve our understanding of brain energy metabolism, linking metabolism to signaling events perturbed during AD progression, and could illuminate new therapeutic strategies. Herein we report an optimized in situ workflow for enzyme‐assisted, matrix‐assisted laser desorption and ionization (MALDI) mass spectrometry imaging (MSI) of brain N‐linked glycans. Using this workflow, we spatially interrogated N‐linked glycan heterogeneity in both mouse and human AD brains and their respective age‐matched controls. We identified robust regional‐specific N‐linked glycan changes associated with AD in mice and humans. These data suggest that N‐linked glycan dysregulation could be an underpinning of AD pathologies.

Prostate cancer is the most common cancer in men worldwide. Despite its prevalence, there is a critical knowledge gap in understanding factors driving disparities in survival among different cohorts of patients with prostate cancer. Identifying molecular features separating disparate populations is an important first step in prostate cancer research that could lead to fundamental hypotheses in prostate biology, predictive biomarker discovery, and personalized therapy. N-linked glycosylation is a cotranslational event during protein folding that modulates a myriad of cellular processes. Recently, aberrant N-linked glycosylation has been reported in prostate cancers. However, the full clinical implications of dysregulated glycosylation in prostate cancer has yet to be explored. Herein, we performed direct on-tissue analysis of N-linked glycans using matrix-assisted laser desorption ionization-mass spectrometry imaging (MALDI-MSI) from tissue microarrays of over 100 patient tumors with over 10 years of follow-up metadata. We successfully identified a panel of N-glycans that are unique between benign and prostate tumor tissue. Specifically, high-mannose as well as tri-and tetra-antennary N-glycans were more abundant in tumor tissue and increase proportionally with tumor grade. Further, we expanded our analyses to examine the N-glycan profiles of Black and Appalachian patients and have identified unique glycan signatures that correlate with recurrence in each population. Our study highlights the potential applications of MALDI-MSI for digital pathology and biomarker discovery for prostate cancer. Implications: MALDI-MSI identifies N-glycan perturbations in prostate tumors compared with benign tissue. This method can be utilized to predict prostate cancer recurrence and study prostate cancer disparities.

Glycogen dysregulation is a hallmark of aging, and aberrant glycogen drives metabolic reprogramming and pathogenesis in multiple diseases. However, glycogen heterogeneity in healthy and diseased tissues remains largely unknown. Herein, we describe a method to define spatial glycogen architecture in mouse and human tissues using matrix-assisted laser desorption/ionization mass spectrometry imaging. This assay provides robust and sensitive spatial glycogen quantification and architecture characterization in the brain, liver, kidney, testis, lung, bladder, and even the bone. Armed with this tool, we interrogated glycogen spatial distribution and architecture in different types of human cancers. We demonstrate that glycogen stores and architecture are heterogeneous among diseases. Additionally, we observe unique hyperphosphorylated glycogen accumulation in Ewing sarcoma, a pediatric bone cancer. Using preclinical models, we correct glycogen hyperphosphorylation in Ewing sarcoma through genetic and pharmacological interventions that ablate in vivo tumor growth, demonstrating the clinical therapeutic potential of targeting glycogen in Ewing sarcoma.

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.