What is spatial biology?
Spatial biology is the study of the diverse cellular landscape across multiple dimensions.
Spatial biology studies look at which cells are present, where they are located in tissue, their biomarker coexpression patterns, and how they organize and interact to influence the tissue microenvironment. By studying cells and biomarkers in context, you will gain novel biological insights.
True spatial biology studies combine whole-slide imaging at single-cell resolution to visualize and quantitate biomarker expression to reveal how cells interact and organize across the entire tissue landscape. We call this approach spatial phenotyping.
Why spatial biology matters
- Decode complex tissues
- Map tissue microenvironments
- Understand therapeutic response
- Accelerate biomarker discovery
The evolution of single-cell spatial analysis
Bulk Measurement
Bulk measurement methods, such as RNA sequencing and mass spectrometry, measure the average RNA and protein abundance in an entire sample. These methods are useful for understanding overall population-level diversity but cannot reveal the characteristics of individual cells.
Single-cell analysis
Single-cell analysis techniques, such as flow cytometry and single-cell sequencing, provide detailed information at the individual cell level. By capturing the RNA and/or protein expression of single cells, researchers can identify all the different cell types and functional states present, enabling the study of cellular diversity. However, these methods do not reveal how cells are organized or how they interact with one another.
Spatial, single-cell analysis
Spatial biology adds a critical layer of context to single-cell analysis—location. Knowing where cells are located and how they interact within tissue is essential to understanding disease mechanisms and therapeutic responses. Spatial phenotyping, enabled by multiplex imaging, reveals these spatial relationships and interactions across entire tissue sections at single-cell resolution—revealing organization, interactions, and functional states that traditional methods cannot capture.
Key applications of each analysis method
| Key applications | Bulk Measurement | Single-cell analysis | Spatial, single-cell analysis |
|---|---|---|---|
|
Measure analyte abundance |
X |
X |
X |
|
Access population-level diversity |
X |
X |
X |
|
Distinguish cell types and functional states |
X |
X |
|
|
Reveal cellular organization and interactions |
X |
Connect protein function and gene expression in spatial context
Understanding complex tissue biology requires more than a single perspective. Combining spatial proteomics and spatial transcriptomics delivers a multiomic approach that connects protein function with gene expression. This integration provides a comprehensive view of cellular organization, interactions, and molecular pathways—enabling discoveries that drive precision medicine, therapeutic development, and companion diagnostics.
Spatial proteomics
Proteins are the functional molecules of biology and the primary targets for most drugs, making protein biomarkers essential for therapy development and diagnostics.
Spatial proteomics enables large-scale analysis of proteins and their localization within tissue. Ultrahigh-plex imaging of more than 100 protein markers of whole-tissue sections at single-cell resolution provides unprecedented depth for immune profiling, oncology, and neuroscience research.
Spatial transcriptomics
Transcriptomic analysis, such as RNA-seq and single-cell RNA-seq, reveals gene expression patterns that define cellular states and functions. Spatial transcriptomics extends these revelations by preserving tissue architecture, enabling researchers to study gene expression in its native context at subcellular resolution with whole-transcriptome coverage. Profiling thousands of genes while maintaining spatial fidelity makes spatial transcriptomics a critical tool for unbiased discovery and highly complementary to spatial proteomics.
Spatial biology applications
Oncology
Spatial biology enables precise mapping of cancer cell organization, immune infiltration, and tissue architecture, revealing tumor heterogeneity, identifying spatial biomarkers, and improving understanding of how cellular neighborhoods influence tumor progression and therapeutic response.
Immunology
Spatial biology uncovers how immune cells are positioned, activated, and interacting within tissues, offering deep insight into inflammatory pathways, cellular communication networks, and the spatial drivers of immune activation, suppression, or dysregulation in complex diseases.
Neuroscience
Spatial biology maps neural, glial, and immune cell interactions across brain tissue, illuminating cellular states, neuroinflammatory signatures, and microenvironmental changes that underlie neurodegeneration and disease pathology while preserving the intricate architecture of the nervous system tissues.
Infectious disease
Spatial biology visualizes pathogen–host interactions and immune responses directly in tissue, revealing how infection spreads, how immune cells localize and react, and how tissue architecture changes during disease progression, enabling more precise understanding of host defense mechanisms.
Answer questions across the research continuum
Biological research spans a continuum—from early discovery to translational studies to clinical applications. Each stage has unique questions and challenges. Spatial biology provides the context to address these questions and challenges at each stage, enabling scientists to uncover new cell types, define cellular functions, map interactions, and identify patterns that accelerate therapeutic development, companion diagnostic utility, and precision medicine objectives.
Discover Spatial Biology
Spatial Technology
Understand how spatial proteomics maps protein expression across tissues with spatial context.
PhenoCycler Fusion 2.0
Enable ultrahigh‑plex, single‑cell spatial phenotyping with rapid, automated whole‑slide imaging.
PhenoImager HT 2.0
Achieve high‑throughput spatial phenotyping with fast multispectral whole‑slide imaging.
PhenoCode Signature Assays
Profile tumor microenvironments for specific biomarkers using optimized, multiplex panels for predictive insights.
FAQs about spatial biology
Spatial biology is the study of where cells, proteins, and biomolecules are located within intact tissues and how their spatial organization influences biological function and disease. Unlike traditional bulk or single‑cell assays that lose spatial context, spatial biology preserves the architecture of the tissue microenvironment, enabling high‑resolution mapping of cell–to-cell interactions, protein expression, and molecular pathways in situ.
The difference lies in which biological molecules are measured and mapped within the tissue microenvironment. Spatial proteomics is a facet of spatial biology focused on the localization and abundance of proteins in situ, while spatial transcriptomics maps RNA expression patterns back to their precise positions in the tissue. Along with additional modalities such as spatial genomics, spatial metabolomics, multiplex immunofluorescence, and high‑plex in situ imaging, these approaches converge to deliver a multiomic, high‑resolution understanding of cellular function, tissue architecture, and disease biology.
Spatial biology assays typically rely on both formalin‑fixed, paraffin‑embedded (FFPE) and fresh‑frozen tissue samples, supporting whole‑slide, single‑cell imaging of tissue architecture. In routine practice, labs run tissue microarrays (TMAs) for cohort‑scale studies and archival slides generated from existing blocks, providing flexibility based on the availability of limited, precious specimen types.
Spatial phenotyping is the process of identifying and mapping cell types, functional states, and protein expression profiles within their precise locations in tissue. Using multiplexed, high‑resolution spatial proteomics, spatial phenotyping reveals how immune, stromal, and tumor cells interact within the microenvironment. This enables detailed characterization of cellular niches, signaling pathways, and disease‑associated phenotypes that cannot be captured by traditional single-cell technologies.