Spatial transcriptomics defines injury specific microenvironments and cellular interactions in kidney regeneration and disease
Abstract
Kidney injury disrupts the intricate renal architecture and triggers limited regeneration, together with injury-invoked inflammation and fibrosis. Deciphering the molecular pathways and cellular interactions driving these processes is challenging due to the complex tissue structure. Here, we apply single cell spatial transcriptomics to examine ischemia-reperfusion injury in the mouse kidney. Spatial transcriptomics reveals injury-specific and spatially-dependent gene expression patterns in distinct cellular microenvironments within the kidney and predicts Clcf1-Crfl1 in a molecular interplay between persistently injured proximal tubule cells and their neighboring fibroblasts. Immune cell types play a critical role in organ repair. Spatial analysis identifies cellular microenvironments resembling early tertiary lymphoid structures and associated molecular pathways. Collectively, this study supports a focus on molecular interactions in cellular microenvironments to enhance understanding of injury, repair and disease.
Copyright and License
Open Access. This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.
Acknowledgement
Work in APM’s and LC’s laboratory was supported by a Broad Innovation Grant from the Eli and Edythe Broad Center for Regenerative Medicine and Stem Cell Research at the University of Southern California and a grant from the NIH to APM (NIDDK UC2DK126024). Additional support from the German Research Foundation grant GE 3179/1-1 (L.M.S.G.) and German Society of Internal Medicine (DGIM) Clinician Scientist grant (L.M.S.G.). The authors thank Inna-Marie Strazhnik for help with figure illustration and design.
Data Availability
The raw and processed data generated in this study were deposited in the Dryad database (https://datadryad.org/stash/dataset/doi:10.5061/dryad.bnzs7h4hj) and Zenodo (https://doi.org/10.5281/zenodo.12709329). The codebooks and probe sequences used to generate seqFISH probes used in this study are available as Supplementary Data 2 and 3. The probe sequences used to generate serial probes are available as Supplementary Data 4. Processed data can be browsed interactively at https://woldlab.caltech.edu/ci2-celltiles/Mouse-Kidney-Fibrosis/. Mouse sequencing data generated by Ransick et al. and by Kirita et al. and used in this study are available on GEO with accessions GSE129798 and GSE139107. Mouse T cell expression profiles were obtained from figshare (https://figshare.com/articles/dataset/ProjecTILs_murine_reference_atlas_of_tumor-infiltrating_T_cells_version_1/12478571/2). Human sequencing data was obtained from cellxgene (https://cellxgene.cziscience.com/collections/bcb61471-2a44-4d00-a0af-ff085512674c). Source data are provided with this paper.
Code Availability
Scripts used for processing seqFISH images can be found in GitHub (https://github.com/CaiGroup/pyfish_tools) and Zenodo (https://doi.org/10.5281/zenodo.12192195).
Additional Information
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Additional details
- PMCID
- PMC11377535
- PMID
- 39237549
- University of Southern California
- National Institutes of Health
- NIDDK UC2DK126024
- Deutsche Forschungsgemeinschaft
- GE 3179/1-1
- Accepted
-
2024-08-01Accepted
- Caltech groups
- Division of Biology and Biological Engineering
- Publication Status
- Published