Spatial transcriptomics using multiplexed deterministic barcoding in tissue

Johannes Wirth, Nina Huber, Kelvin Yin, Sophie Brood, Simon Chang, Celia P. Martinez-Jimenez () and Matthias Meier ()
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Johannes Wirth: Helmholtz Pioneer Campus, Helmholtz Munich
Nina Huber: Helmholtz Pioneer Campus, Helmholtz Munich
Kelvin Yin: Helmholtz Pioneer Campus, Helmholtz Munich
Sophie Brood: Helmholtz Pioneer Campus, Helmholtz Munich
Simon Chang: Helmholtz Pioneer Campus, Helmholtz Munich
Celia P. Martinez-Jimenez: Helmholtz Pioneer Campus, Helmholtz Munich
Matthias Meier: Helmholtz Pioneer Campus, Helmholtz Munich

Nature Communications, 2023, vol. 14, issue 1, 1-15

Abstract: Abstract Spatially resolved transcriptomics of tissue sections enables advances in fundamental and applied biomedical research. Here, we present Multiplexed Deterministic Barcoding in Tissue (xDBiT) to acquire spatially resolved transcriptomes of nine tissue sections in parallel. New microfluidic chips were developed to spatially encode mRNAs over a total tissue area of 1.17 cm2 with a 50 µm resolution. Optimization of the biochemical protocol increased read and gene counts per spot by one order of magnitude compared to previous reports. Furthermore, the introduction of alignment markers allowed seamless registration of images and spatial transcriptomic spots. Together with technological advances, we provide an open-source computational pipeline to prepare raw sequencing data for downstream analysis. The functionality of xDBiT was demonstrated by acquiring 16 spatially resolved transcriptomic datasets from five different murine organs, including the cerebellum, liver, kidney, spleen, and heart. Factor analysis and deconvolution of spatial transcriptomes allowed for in-depth characterization of the murine kidney.

Date: 2023
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DOI: 10.1038/s41467-023-37111-w

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