Deep-Tissue Spatial Omics: Imaging Whole-Embryo Transcriptomics and Subcellular Structures at High Spatial Resolution

Gandin, V.; Kim, J.; Yang, L.-Z.; Lian, Y.; Kawase, T.; Hu, A.; Rokicki, K.; Fleishman, G.; Tillberg, P.; Aguilera Castrejon, A.; Stringer, C.; Preibisch, S.; Liu, Z. J.

doi:10.1101/2024.05.17.594641

bioRxiv · 10.1101/2024.05.17.594641

Deep-Tissue Spatial Omics: Imaging Whole-Embryo Transcriptomics and Subcellular Structures at High Spatial Resolution

Gandin, V.·Kim, J.·Yang, L.-Z.·Lian, Y.·Kawase, T.·Hu, A.·Rokicki, K.·Fleishman, G.·Tillberg, P.·Aguilera Castrejon, A.·Stringer, C.·Preibisch, S.·Liu, Z. J.

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Abstract

The inherent limitations of fluorescence microscopy, notably the restricted number of color channels, have long constrained comprehensive spatial analysis in biological specimens. Here, we introduce cycleHCR technology that leverages multicycle DNA barcoding and Hybridization Chain Reaction (HCR) to surpass the conventional color barrier. cycleHCR facilitates high-specificity, single-shot imaging per target for RNA and protein species within thick specimens, mitigating the molecular crowding issues encountered with other imaging-based spatial omics techniques. We demonstrate whole-mount transcriptomics imaging of 254 genes within an E6.5[~]7.0 mouse embryo, achieving precise three-dimensional gene expression and cell fate mapping across a specimen depth of [~] 310 {micro}m. Utilizing expansion microscopy alongside protein cycleHCR, we unveil the complex network of 10 subcellular structures in primary mouse embryonic fibroblasts. Furthermore, in mouse hippocampal slice, we image 8 protein targets and profile the transcriptome of 120 genes, uncovering complex gene expression gradients and cell-type specific nuclear structural variances. cycleHCR provides a unifying framework for multiplex RNA and protein imaging, offering a quantitative solution for elucidating spatial regulations in deep tissue contexts for research and potentially diagnostic applications.

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Gandin, V., Kim, J., Yang, L.-Z., Lian, Y., Kawase, T., Hu, A., Rokicki, K., Fleishman, G., Tillberg, P., Aguilera Castrejon, A., Stringer, C., Preibisch, S., Liu, Z. J.. 2024-05-17. Deep-Tissue Spatial Omics: Imaging Whole-Embryo Transcriptomics and Subcellular Structures at High Spatial Resolution. https://doi.org/10.1101/2024.05.17.594641

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