Spatial multiomics is an approach in biological research that allows scientists to explore the intricate workings of life with great detail. This field combines the precise location of biological components within tissues or cells with a comprehensive analysis of various molecular layers. By merging “where” things happen with “what” is present, spatial multiomics overcomes limitations of traditional methods that often lose spatial context, providing a more complete picture of biological processes. This discipline offers new avenues for discovery, moving beyond bulk analyses to reveal organization and interactions that govern living systems.
The Power of Location: Why Spatial Matters in Biology
Understanding biological functions requires knowing not only what molecules or cells exist, but also precisely where they are located. Traditional methods often involve grinding up tissue samples, which mixes all components together and destroys spatial relationships. This loss of architectural context can obscure how cells interact with their neighbors or how molecular gradients influence cellular behavior. For instance, a city’s function is not just about its buildings, but how those buildings are arranged and interact within specific districts.
Within a biological tissue, the immediate environment influences cell identity and activity. A fibroblast in the healthy periphery of an organ behaves differently from one embedded within a tumor’s core, even if they share similar genetic material. The spatial organization of cells, the architecture of tissues, and the localized interactions between cells and their surrounding microenvironment dictate biological outcomes. Without this spatial information, researchers might miss changes in disease progression or developmental pathways.
Integrating Multiple Biological Layers: What “Multiomics” Adds
Life operates through a complex interplay of various molecular components, each representing a different layer of biological information. Genes (DNA) provide the blueprint, while messenger RNA (transcriptomics) indicates which genes are actively being read. Proteins (proteomics) carry out most cellular functions, and small molecules like metabolites (metabolomics) reflect the cell’s metabolic state. Each “omic” layer offers a distinct perspective on cellular activity, but no single layer tells the whole story.
Studying only one of these biological layers provides an incomplete view. For example, high levels of a specific RNA molecule do not always translate into high levels of its corresponding protein, due to post-transcriptional regulation. By combining genomics, transcriptomics, proteomics, and metabolomics, researchers gain a more holistic understanding of how these different layers interact and influence each other. This comprehensive integration reveals the interconnectedness of biological processes, moving beyond isolated observations to decipher the complexity of living systems.
How Spatial Multiomics Works: A Conceptual Overview
Spatial multiomics integrates the precise location of biological molecules with their molecular identities. The general process begins with a tissue sample, which is carefully preserved to maintain its original cellular and tissue architecture. Instead of homogenizing the sample, researchers analyze different omic layers directly in situ, meaning they study the molecules right where they are found within the tissue. This preservation of spatial context is a key feature of the approach.
Specialized techniques identify and quantify molecules while retaining their spatial coordinates. For example, methods involve taking high-resolution images of a tissue section to capture its structure, then identifying specific RNA molecules or proteins within that image using molecular probes. Other approaches might involve micro-dissecting small regions of interest from the tissue and performing detailed omic analysis on those spatially defined samples. The molecular data is then “mapped” back to its spatial location, creating a detailed molecular landscape of the tissue that reveals how different molecules are distributed and organized.
Revolutionizing Disease Understanding and Beyond
Spatial multiomics is profoundly changing how scientists investigate diseases and fundamental biological processes. In cancer research, this approach offers insights into tumor heterogeneity, revealing how cancer cells and their surrounding microenvironment vary across different regions of a tumor. Researchers can identify specific immune cell populations excluded from tumor areas, or map the spatial distribution of drug resistance markers, which could lead to more targeted therapies. Understanding the precise location of specific immune checkpoints within a tumor can inform immunotherapeutic strategies.
In neuroscience, spatial multiomics is advancing our understanding of brain organization and neurodegenerative disorders. It enables researchers to map distinct neuronal cell types and their connections within specific brain layers, providing a detailed atlas of brain circuitry. This technology can also pinpoint the spatial localization of amyloid plaques and tau tangles in Alzheimer’s disease, along with surrounding cellular responses, offering new targets for intervention. In Parkinson’s disease, it can reveal spatial changes in dopamine-producing neurons and associated inflammatory cells in specific brain regions.
Beyond disease, spatial multiomics provides deeper insights into developmental biology, allowing scientists to trace cell fates and observe the emergence of complex tissue structures with remarkable clarity. It can show how different cell types organize themselves during organ formation, revealing the molecular gradients that guide their differentiation and migration. For drug discovery, this technology helps identify novel therapeutic targets by pinpointing specific cell populations or molecular pathways active in disease-affected regions. It also aids in discovering new biomarkers that are spatially restricted, offering more precise diagnostic and prognostic tools.