Spatial Multi-Omics in Veterinary Infectious Diseases

Spatial multi-omics is transforming veterinary infectious disease research by integrating genomic, transcriptomic, proteomic, and metabolomic data with spatial and histological context. This approach reveals host–pathogen interactions, cellular heterogeneity, and localized immune or metabolic responses that shape disease outcomes. Emerging technologies such as SM-Omics, SpatialGlue, and MOSAIK enable multi-layered data integration across imaging and molecular scales. In veterinary medicine, spatial multi-omics provides insights into pathogen localization, immune microenvironments, and species-specific mechanisms in bacterial, viral, and parasitic infections. Combined with artificial intelligence (AI) and digital pathology, it enhances diagnostic accuracy, biomarker discovery, and outbreak prediction. Despite challenges in cost and data standardization, the convergence of spatial omics, AI, and One Health strategies is paving the way for precision veterinary medicine and improved surveillance of zoonotic diseases.