Spatial genomics transcriptomics (SGT) is an emerging technique that allows researchers to analyze gene expression patterns within tissues at single-cell resolution without having to physically isolate individual cells. By preserving the spatial organization and tissue architecture, Spatial genomics transcriptomics provides insights into how cells within specific tissue locations and microenvironments express genes. This technology helps map gene expression patterns and identify cell types across intact tissues.
How Does it Work?
SGT techniques utilize fluorescence in situ hybridization (FISH) to simultaneously detect many mRNA transcripts within intact tissues or whole tissue sections. In the SGT workflow, fresh or frozen tissue is placed onto a glass slide coated with an array of barcoded oligonucleotides. The tissue is then subjected to fragmentation, reverse transcription and barcoding of mRNA molecules. This results in capture and spatial labeling of mRNAs released from their original locations. The slide is then fluorescently probed to detect the labeled transcripts and imaged using fluorescent microscopy. Finally, computational analysismaps the transcriptomic profile to individual tissue locations, allowing reconstruction of gene expression patterns across the original tissue architecture at high resolution.
Applications in Health and Disease
SGT has enabled new discoveries by providing spatially-resolved molecular profiles of tissues. It has been utilized to map diverse cell types in the brain and identify disease-associated transcriptional signatures. For example, one study profiled more than 4000 brain sections from humans and mice using SGT. They were able to reconstruct cell types in over twenty brain regions and distinguish neuronal subpopulations based on spatial transcriptomic profiles. SGT has also proven useful in cancer research by characterizing tumor heterogeneity. In one application, SGT revealed distinct gene expression patterns between tumor cores and invasive fronts in breast cancer, suggesting molecular differences driving invasion. It has potential to transform our understanding of cancer evolution and progression within tissues.
Another key application is in immunology and mapping immune cell distributions. One SGT analysis of human lymph nodes uncovered previously unknown subsets of dendritic cells based on their spatial organization and transcriptomic profiles. Spatially resolved studies of inflamed colon tissues in mouse models have provided new hypotheses on compartmentalization of immune responses in inflammatory bowel disease. Going forward, SGT promises to enhance our understanding of the complex interplay between immune cells and their microenvironments in healthy and diseased states.
Improving Resolution and Throughput
While powerful, initial SGT methods had limitations including modest spatial resolution (~100 microns) and ability to profile only a few hundred genes per experiment. Rapid technical advances are now pushing the boundaries. For example, the latest Visium platform from 10x Genomics uses an expanded gene library of around 20,000 transcripts and a much denser array of spots spaced just 5 microns apart, leading to subcellular level mapping across tissues. Combining SGT with expansion microscopy further improves optical resolution down to the single cell level. Massively parallel processing now also allows whole slide profiling within a single experiment. These improvements will enable new maps of cell types and networks across complex intact tissues at an unprecedented scale and resolution.
Challenges and Future Outlook
A current challenge is integrating spatial maps with single cell transcriptomic atlases to achieve consensus between spatial context and isolated cell characterization. Computationally linking spatial profiles to reference cell type databases remains an active area of research. Additional work is also still needed to fully characterize cellular composition in spatial maps, as SGT does not currently provide information about factors like cell markers. Future development of multiplexed techniques combining RNA and protein detection within tissues could help overcome these limitations.
Looking ahead, spatial genomics transcriptomics promises to transform our molecular understanding of tissues, development, disease mechanisms and drug response in their native multi-cellular settings. As technology continues to rapidly evolve, the throughput and resolution of spatial transcriptomic studies will increase exponentially. Within this decade, we may see comprehensive and detailed “cell atlases” of entire organs and organisms directly from intact samples without need for prior dissociation, giving unprecedented insight into gene regulation in living biological systems.
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1. Source: Coherent Market Insights, Public sources, Desk research
2. We have leveraged AI tools to mine information and compile it
