Spatial metabolomics - a metabolic microscope for respiratory medicine

Spatial metabolomics enables in situ, pixel-resolved mapping of small molecules across tissues, providing a powerful complement to conventional bulk metabolomics, which lacks cellular and anatomical resolution. By adapting mass spectrometry (MS) ionization approaches such as matrix-assisted laser desorption/ionization (MALDI) and desorption electrospray ionization (DESI), spatial metabolomics generates high-resolution metabolic maps that link metabolite distributions to defined tissue regions, cellular niches, and biological functions. This "metabolic microscopy" enables localization of biosynthetic pathways, identification of region-specific metabolic signatures, and integration with histology and other spatial omics modalities. High-resolution MS platforms support untargeted discovery, while targeted approaches enable sensitive detection of low-abundance metabolites. In respiratory research, spatial metabolomics has begun to reveal regional heterogeneity in lung metabolism, including surfactant remodeling, lipid mediator localization, fibrosis-associated metabolic reprogramming, infection-specific airway responses, and tumor-associated phospholipid dysregulation. These studies highlight the capacity of the method to connect localized biochemistry with pulmonary physiology and disease mechanisms. However, challenges remain, including limited sensitivity, difficulties in metabolite identification and isomer discrimination, restricted quantification strategies, and incompatibility with commonly used FFPE tissue preservation, underscoring the need for standardized fresh-frozen tissue workflows. Future integration of spatial metabolomics with spatial transcriptomics and proteomics promises comprehensive, multi-layered metabolic mapping of the airways, enabling the cross talk between multiple orders of biology to be understood from specific tissue microenvironments. As part of a multimodal spatial biology framework, spatial metabolomics has strong potential to define disease endotypes, inform therapeutic target discovery, and generate spatial metabolic atlases that advance mechanistic understanding and precision medicine in respiratory disease.