Spatial metabolomics reveals glycogen as an actionable target for pulmonary fibrosis

Spatial metabolomics are used to describe the location and chemistry of small molecules involved in metabolic phenotypes. Here, Conroy et al. present a bioinformatic pipeline to analyze MALDI data and show that it can be used to identify actionable targets such as glycogen in fibrotic lungs of both human and mice. 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.

Automated summary

Spatial metabolomics was used to analyze the location and chemistry of small molecules in fibrotic lungs. A bioinformatic pipeline was developed to identify actionable targets and assess tissue metabolic heterogeneity in human lung diseases. The findings suggest that lysosomal utilization of glycogen is required for pulmonary fibrosis progression.