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Spatial transcriptomics in health and disease

Nature Reviews Nephrology (2024)Cite this article

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Abstract

The ability to localize hundreds of macromolecules to discrete locations, structures and cell types in a tissue is a powerful approach to understand the cellular and spatial organization of an organ. Spatially resolved transcriptomic technologies enable mapping of transcripts at single-cell or near single-cell resolution in a multiplex manner. The rapid development of spatial transcriptomic technologies has accelerated the pace of discovery in several fields, including nephrology. Its application to preclinical models and human samples has provided spatial information about new cell types discovered by single-cell sequencing and new insights into the cell–cell interactions within neighbourhoods, and has improved our understanding of the changes that occur in response to injury. Integration of spatial transcriptomic technologies with other omics methods, such as proteomics and spatial epigenetics, will further facilitate the generation of comprehensive molecular atlases, and provide insights into the dynamic relationships of molecular components in homeostasis and disease. This Review provides an overview of current and emerging spatial transcriptomic methods, their applications and remaining challenges for the field.

Key points

  • Spatially resolved transcriptomic technologies allow the spatial mapping of transcripts at single-cell or near single-cell resolution in a multiplex manner, and currently include sequencing-based technologies and imaging-based methodologies. Sequencing-based technologies include whole transcriptome-wide in situ capture and region of interest-based spatial RNA analysis platforms; imaging-based technologies include a variety of massively multiplexed in situ hybridization methodologies.

  • Key data outputs from spatial transcriptomic technologies include the anchoring of cell types and states derived from disaggregated single-cell technologies, determination of spatially variable gene expression, and the annotation of functional neighbourhoods.

  • Spatial technologies enable the localization of biologically relevant cellular interactions in the histopathological context and identification of disease-relevant cell signalling pathways associated with morphological and histopathological changes.

  • Spatial technologies are rapidly advancing to provide single-cell signatures at a whole transcriptome level. Further, these technologies are becoming increasingly multiplexed with orthogonal technologies such as spatial proteomics or epigenomics to define gene and protein regulatory patterns.

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Fig. 1: Methodologies underlying spatial transcriptomic technologies.
Fig. 2: Analytical workflow for the processing of spatial transcriptomic data.
Fig. 3: Establishment of neighbourhoods.
Fig. 4: Examples of neighbourhoods in health and disease.

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Acknowledgements

S.J. is supported by NIH funding (U54DK134301, U01DK114933, UH3DK114933 and P50DK133943). M.T.E. is supported by NIH funding (R01AT011463-01A1, U54 DK134301-01 and U01 DK114923).

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  1. Division of Nephrology, Department of Medicine, Washington University School of Medicine, St. Louis, MO, USA

    Sanjay Jain

  2. Division of Nephrology, Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, USA

    Michael T. Eadon

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Jain, S., Eadon, M.T. Spatial transcriptomics in health and disease. Nat Rev Nephrol (2024). https://doi.org/10.1038/s41581-024-00841-1

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