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Spatial tissue profiling by imaging-free molecular tomography

Abstract

Several techniques are currently being developed for spatially resolved omics profiling, but each new method requires the setup of specific detection strategies or specialized instrumentation. Here we describe an imaging-free framework to localize high-throughput readouts within a tissue by cutting the sample into thin strips in a way that allows subsequent image reconstruction. We implemented this framework to transform a low-input RNA sequencing protocol into an imaging-free spatial transcriptomics technique (called STRP-seq) and validated it by profiling the spatial transcriptome of the mouse brain. We applied the technique to the brain of the Australian bearded dragon, Pogona vitticeps. Our results reveal the molecular anatomy of the telencephalon of this lizard, providing evidence for a marked regionalization of the reptilian pallium and subpallium. We expect that STRP-seq can be used to derive spatially resolved data from a range of other omics techniques.

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Fig. 1: Sampling and reconstruction approach to resolve the spatial localization of genomics data.
Fig. 2: Reconstruction performance of Tomographer on simulated data.
Fig. 3: STRP-seq reconstructions of spatial expression profiles for the mouse brain.
Fig. 4: Reconstruction of the molecular anatomy of the lizard brain de novo.
Fig. 5: Identification of regional identities in the lizard brain.

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Data availability

RNA-seq data are available at the Gene Expression Omnibus repository (https://www.ncbi.nlm.nih.gov/geo) under accession GSE152989. Results of the reconstruction can be accessed at this paper’s companion website: https://strpseq-viewer.epfl.ch/.

Code availability

Source code and templates for customized 3D-printable cryosectioning adaptor manifolds are available at https://github.com/lamanno-epfl/tomographer.

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Acknowledgements

We thank S. Linnarsson (Karolinska Insitutet) for allowing proof-of-principle tests in his laboratory; N. Shental, B. Shalem (Open University Israel) and A. Zeisel (Technion) for stimulating discussions; M. Schuelke (Charité) for enabling the participation of C.G.S. in this project; G. Laurent for discussion and providing samples; M. Weigert and L. Talamanca for discussing our formulation; A. Jacobi for contributing lizard in situ hybridizations; and P. Gönczy, B. Deplanke and F. Naef for constructive criticism of the manuscript. This work was supported by a grant from the Swiss National Science Foundation (CRSK-3_190495) to G.L.M. G.L.M. was also supported by CZI seed network grant HCA3-0000000081 and Swiss National Science Foundation grant PZ00P3_193445.

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Authors

Contributions

G.L.M. conceived the study design and supervised the project. G.L.M., H.H.S. and C.G.S. analyzed, annotated and interpreted the tomography data and wrote the manuscript. M.A.T. and T.M.Y. performed P. vitticeps experiments and contributed to interpreting the results. G.L.M., A.R. and H.H.S. designed and wrote the reconstruction algorithm. S.C. and L.E.B. designed the cryosectioning scheme. S.C. and J.S. performed the mouse experiments and sectioning. G.L.M. performed the sequencing. P.L. ran the bioinformatics pipeline. F.P.A.D. built the companion website. All authors critically reviewed the manuscript and approved the final version.

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Correspondence to Gioele La Manno.

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The authors declare no competing interests.

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Peer review information Nature Biotechnology thanks Mor Nitzan, Dominic Grun, and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Schede, H.H., Schneider, C.G., Stergiadou, J. et al. Spatial tissue profiling by imaging-free molecular tomography. Nat Biotechnol 39, 968–977 (2021). https://doi.org/10.1038/s41587-021-00879-7

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