Spatial Omics:
Spatial omics is an emerging field that combines omics technologies like genomics, transcriptomics and proteomics with spatial information to map biological molecules within tissues and cells at high resolution. Traditional bulk omics methods average molecular information from whole tissues or cell populations, losing important biological context at the spatial level. Spatial omics techniques seek to retain this context by pairing molecular measurements with spatial information from the locations they originate within a sample. This allows researchers to map biological networks, cellular interactions and pathways within complex tissues. In this article, we will explore the key techniques in spatial omics and how they are enhancing our understanding of both normal biology and disease mechanisms.
Spatial Transcriptomics
One of the earliest and most widely used spatial omics methods is spatial transcriptomics. This technique maps the expression of RNA transcripts to their location within tissues at a resolution of 50-100 microns. Fixed tissue sections are placed on slides containing >1 million DNA probe dots with unique barcodes. As the tissue is lysed, mRNAs from cells diffuse and hybridize to probes matching their sequence. After sequencing, the location of each transcript can be mapped back to its originating cell based on the barcode of the capturing probe.
This has provided unprecedented spatial views of gene expression across entire tissues. In the brain, researchers have mapped region-specific transcriptomic signatures and identified new cell types based on their spatial gene expression profiles. Studies of tumor tissues have revealed intratumoral heterogeneity and traced metastatic routes by mapping migration of invasive cancer cell populations. Spatial transcriptomics has also offered novel perspectives on tissue development, remodeling and response to injury. With higher throughput and resolution platforms continually emerging, this technique is becoming a mainstay for mapping gene regulation within complex tissues.
Spatial Proteomics and Lipidomics
While transcriptomic data provides insights into cellular states and functions, direct measurement of proteins and other biomolecules gives a more complete picture of biological processes and signaling within tissues. Mass-spectrometry based spatial proteomics and lipidomics methods have recently been developed which work on similar principles to spatial transcriptomics but profile proteins and lipids rather than RNA.
In spatial proteomics, tissue sections are patterned with antibodies that capture proteins in situ according to their spatial location. Mass-spectrometry then identifies and quantifies the captured proteins. Researchers have applied this to map regulatory protein expression and activity gradients in model organisms as well as differences in cancer cell invasion fronts. Spatial lipidomics follows the same workflow but with probes targeting specific lipids like phospholipids and sphingolipids involved in cellular signaling. This provides unique views of spatial organization of biomolecule classes that are crucial for cellular phenotype but whose regulation has not been well characterized at high resolution in tissues. The combination of proteomic and lipidomic data with transcriptomic maps gives researchers an unmatched multi-omics view of molecular networks and cellular interactions within native tissue architecture and microenvironments.
Imaging Mass Cytometry
While the above techniques provide an unbiased perspective across entire tissue sections, imaging mass cytometry takes a targeted multiplexed imaging approach. Tissue samples are stained with heavy metal-tagged antibodies against a pre-selected panel of biomolecules like proteins, phosphoproteins and RNA epitopes. Using mass cytometry, the sample is ablated with a laser and resulting ion clouds representing each staining target are detected and correlated to their spatial location with subcellular resolution.
Researchers have applied this technique to profile over 40 markers simultaneously in tissues and cell populations. This has enabled analysis of rare cell phenotypes, intracellular signaling gradients, and molecular categorization of cell types in complex tissues. One study used a 100+ marker panel to reveal unsuspected diversity in mouse brain cell types and states. Imaging mass cytometry also provides a targeted approach for validation and spatial context for discoveries from spatial omics mappings. The high multiplex capability means it can profile core signaling and regulatory nodes within intrinsic molecular networks mapped out through untargeted spatial omics. Overall, imaging mass cytometry fills an important niche as a targeted high-resolution imaging technique complementary to global spatial profiling methods.
Applications and Future Directions
The emerging field of spatial omics has already provided transformative insights across biology and medicine in just a few short years since the first methods were developed. Applications so far include developmental biology studies elucidating tissue patterning, neuroscience work unraveling regulatory hierarchies in the brain, immunology research characterizing immune cell coordination, and oncology using tumors to map disease progression and therapeutic resistance. Spatial omics is also being applied to profile aging, metabolic disease, inflammation and more.
As technologies continue to advance with higher resolution, greater multiplexing, and integration of multi-omics modalities, our understanding of biology within its native architecture will accelerate. Researchers are working on methods like spatial transcriptomics at single-cell resolution as well as platforms integrating measurements of DNA, RNA, epigenetics, proteins and metabolites from the same spatial locations. Spatial systems biology approaches applying computational models and machine learning to these rich datasets also hold great promise. Overall, as spatial omics matures it is poised to revolutionize how we study living systems, propelling major discoveries across basic science and advancing development of more effective diagnostics and precision therapies.
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