Visualisation of gene expression within the context of tissues: an X-ray computed tomography-based multimodal approach

Kairiss, K.; Sokolova, N.; Zilova, L.; Schlagheck, C.; Reinhardt, R.; Baumbach, T.; Farago, T.; van de Kamp, T.; Wittbrodt, J.; Weinhardt, V.

doi:10.1101/2023.10.09.561491

bioRxiv · 10.1101/2023.10.09.561491

Visualisation of gene expression within the context of tissues: an X-ray computed tomography-based multimodal approach

Kairiss, K.·Sokolova, N.·Zilova, L.·Schlagheck, C.·Reinhardt, R.·Baumbach, T.·Farago, T.·van de Kamp, T.·Wittbrodt, J.·Weinhardt, V.

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Abstract

The development of an organism is orchestrated by the spatial and temporal expression of genes. Accurate visualisation of gene expression patterns in the context of the surrounding tissues offers a glimpse into the mechanisms that drive morphogenesis. We developed correlative light-sheet fluorescence microscopy and X-ray computed tomography approach to map gene expression patterns to the whole organisms 3D anatomy at cellular resolution. We show that this multimodal approach is applicable to gene expression visualised by protein-specific antibodies and fluorescence RNA in situ hybridisation, offering a detailed understanding of individual phenotypic variations in model organisms. Furthermore, the approach provides a unique possibility to identify tissues together with their 3D cellular and molecular composition in anatomically less-defined in vitro models, such as organoids. We anticipate that the visual and quantitative insights into the 3D distribution of gene expression within tissue architecture, by the multimodal approach developed here, will be equally valuable for reference atlases of model organisms development, as well as for comprehensive screens and morphogenesis studies of in vitro models.

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Kairiss, K., Sokolova, N., Zilova, L., Schlagheck, C., Reinhardt, R., Baumbach, T., Farago, T., van de Kamp, T., Wittbrodt, J., Weinhardt, V.. 2023-10-10. Visualisation of gene expression within the context of tissues: an X-ray computed tomography-based multimodal approach. https://doi.org/10.1101/2023.10.09.561491

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