Spatial Multiomics Toward Understanding Neurological Systems

Abstract

Dynamic biological processes in the brain involve complex interactions between various cell types, and these interactions span multiple biological scales. Each of these domains are crucial in maintaining brain health. Traditional methods, such as transcriptomics and protein labeling, provide valuable insights but fail to capture the full molecular landscape of neurological function. Multimodal imaging, combining multiple imaging techniques, offers a more comprehensive approach to studying biological systems by integrating different omics technologies. Spatial metabolomics involves using techniques like mass spectrometry imaging to enable detection of metabolites within their native tissue context and reveals functional roles that are crucial for understanding disease. Spatial transcriptomics and proteomics contribute information on gene expression and protein function but face challenges in resolution and integration with other omics approaches. Combining metabolomics, transcriptomics, and proteomics will enhance our understanding of cellular interactions, but challenges remain in optimizing sample preparation, maintaining molecular integrity, and integrating data across omics layers. Future advancements in spatial multiomics, incorporating epigenetics and extending to whole-body or nanoscale imaging, will significantly advance our understanding of neuroscience and complex diseases like Alzheimer's disease or autism spectrum disorder.