Translatomics With RIBOmap: The Missing Multiomic Layer in 3D Spatial Biology

True three-dimensional (3D) spatial biology provides a more physiologically relevant view of tissue biology and cellular interactions than conventional single-cell or two-dimensional (2D) thin-tissue spatial biology techniques.

By imaging thick tissue sections up to 100 microns, cells can now be analyzed within intact tissue, allowing researchers to interrogate multiple intact cell layers while preserving tissue architecture. By extending 3D analysis to include several multiomic layers, scientists can—for the first time—obtain a complete picture of tissue biology encompassing the transcriptome, translatome, proteome, and morpholome.

Translatomics bridges the gap between mRNA and protein expression

Translatomics bridges the gap between static levels of mRNA and protein in cells by using ribosome-bound mRNA as a proxy for active protein translation—detecting transcripts that are actively being translated.

Ribosome-bound mRNA mapping (RIBOmap), a 3D translatomic mapping technology, advances efforts to build a more comprehensive understanding of healthy and diseased biological systems. RIBOmap provides an active view of protein production at the single-cell level, using ribosome-bound mRNA as a proxy for protein expression. This marks a significant advancement in understanding protein production by contextualizing high-plex spatially resolved localized translation.

There is a strong correlation between established ribosome profiling and proteome datasets in matched cell types, and RIBOmap data likewise correlates with proteome data in both cultured cells and brain tissue.

When combined with STARmap (spatially-resolved transcript amplicon readout mapping), which detects RNA in intact, thick tissue sections at subcellular resolution, RIBOmap adds a complementary multiomic layer to gene expression analysis.

Applications of RIBOmap in translational research

By analyzing ribosome-bound mRNAs, RIBOmap enables the characterization of subcellular and tissue region–specific translational regulation, providing deeper insights into protein expression. Initial studies using RIBOmap identified differential spatial patterns of translation at the subcellular level in glia and neurons across different brain regions.

For example, researchers used RIBOmap to identify subcellular localized protein translation in the cell body versus processes of neurons. In a mouse model of schizophrenia, RIBOmap demonstrated* that decreased levels of key synaptic proteins are driven by a translational control mechanism rather than decreased mRNA levels.

Emerging applications of RIBOmap

Traditional 2D analysis often obscures tissue heterogeneity, driving demand for 3D tools that can capture the true biological complexity of intact tissue volumes. Beyond the applications mentioned above, we envision RIBOmap being used alongside other tools to better understand RNA biology in the context of health and disease.

Understanding spatial relationships within the tumor microenvironment is critical for advancing oncology research, where tissue architecture and localized signaling dictate cellular behavior and disease progression. The oncology field is poised to leverage RIBOmap to extend upon both 2D translatomics and 3D transcriptomics data.

STARmap has been leveraged to study human cutaneous squamous cell carcinoma, mapping patterns of cell‒cell adjacency that uncovered a localized anti-tumor immune response driven by the interaction between Langerhans cells and tumor-specific keratinocytes. Thin-tissue analyses fail to capture this pattern as they cannot account for axially adjacent neighbors, effectively severing the 3D context of the cellular neighborhood. The integration of thick-tissue RIBOmap would greatly accelerate such studies.

RIBOmap also has applications in evaluating the efficacy of cell and gene therapies. In combination with STARmap, it can be used to assess CAR-T cell therapies by detecting rare cell populations within large tissue volumes and monitoring CAR-T activity via translation of recombinant receptors. RIBOmap can also be used to assess the efficacy of antisense oligonucleotide (ASO)-mediated modulation of translation, mRNA vaccines, and gene therapies such as CRISPR-based gene editing. For example, a study demonstrated the use of STARmap and RIBOmap to assess the stability and durability of CRISPR-based therapeutics in the liver.

Conclusion

RIBOmap can be leveraged across many translational research applications to provide a more comprehensive picture of tissue biology. This method allows for the detection of actively translated mRNAs in 3D, providing insight into spatially resolved translation events and a high-plex proxy for protein production.

*This article includes research findings that are yet to be peer-reviewed. Results are therefore regarded as preliminary and should be interpreted as such. Find out about the role of the peer review process in research here. For further information, please contact the cited source.