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Spatial transcriptomics using multiplexed deterministic barcoding in tissue

Author

Listed:
  • 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
    Technical University of Munich)

  • Matthias Meier

    (Helmholtz Pioneer Campus, Helmholtz Munich
    University of Leipzig)

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.

Suggested Citation

  • Johannes Wirth & Nina Huber & Kelvin Yin & Sophie Brood & Simon Chang & Celia P. Martinez-Jimenez & Matthias Meier, 2023. "Spatial transcriptomics using multiplexed deterministic barcoding in tissue," Nature Communications, Nature, vol. 14(1), pages 1-15, December.
    • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-37111-w
    DOI: 10.1038/s41467-023-37111-w
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    1. Seitaro Nomura & Masahiro Satoh & Takanori Fujita & Tomoaki Higo & Tomokazu Sumida & Toshiyuki Ko & Toshihiro Yamaguchi & Takashige Tobita & Atsuhiko T. Naito & Masamichi Ito & Kanna Fujita & Mutsuo H, 2018. "Cardiomyocyte gene programs encoding morphological and functional signatures in cardiac hypertrophy and failure," Nature Communications, Nature, vol. 9(1), pages 1-17, December.
    2. Madhav Mantri & Gaetano J. Scuderi & Roozbeh Abedini-Nassab & Michael F. Z. Wang & David McKellar & Hao Shi & Benjamin Grodner & Jonathan T. Butcher & Iwijn De Vlaminck, 2021. "Spatiotemporal single-cell RNA sequencing of developing chicken hearts identifies interplay between cellular differentiation and morphogenesis," Nature Communications, Nature, vol. 12(1), pages 1-13, December.
    3. Anjali Rao & Dalia Barkley & Gustavo S. França & Itai Yanai, 2021. "Exploring tissue architecture using spatial transcriptomics," Nature, Nature, vol. 596(7871), pages 211-220, August.
    4. Chee-Huat Linus Eng & Michael Lawson & Qian Zhu & Ruben Dries & Noushin Koulena & Yodai Takei & Jina Yun & Christopher Cronin & Christoph Karp & Guo-Cheng Yuan & Long Cai, 2019. "Transcriptome-scale super-resolved imaging in tissues by RNA seqFISH+," Nature, Nature, vol. 568(7751), pages 235-239, April.
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