Computational Workflow for Spatiotemporal Transcriptomics Analysis of Cold vs. Warm Ischemic Kidney Injury

Background: Increasing cold ischemia (CI) time leads to AKI, limits lifespan of transplanted organs and increases organ discard. However, there is limited comparison of the molecular pathogenesis between CI and warm ischemia (WI) injury. We performed full-transcriptome characterization in a CI murine model using the 10X Visium spatial transcriptomics (ST) platform for comparison with previously published WI data. Methods: We induced CI in murine kidneys in UW solution at 4oC (0, 12, 24 and 48 hours), then generated ST datasets (n=1 per timepoint), containing 12530 spatial spots with 19465 shared gene species profiled per kidney tissue section. We developed a computational workflow which facilitates batch correction (via Harmony) to identify shared cell types across all datasets. We segmented kidney tissues into three different compartments, namely the cortex, medulla, and corticomedullary junction based on cell types and their anatomical location. We identified differentially expressed genes (DEGs) across time points unique to each compartment using DESeq2, clustered DEGs into different temporal trends, and further characterized enriched pathways per compartment per trend using ClusterProfiler. We implemented a similar workflow on WI injury kidneys. Results: We integrated 0, 12, 24 and 48 hours CI kidney ST datasets and identified shared cell types across all timepoints that demarcated similar anatomical locations. We identified shared temporal trends affecting distinct genes and pathways within different kidney compartments. In particular, autophagy-related pathways were uniquely upregulated in the cortex of CI kidney at an early timepoint (12 hours) whereas upregulation of immune-related pathways emerged in the medulla at a later timepoint (48 hours). Comparisons between CI and WI further elucidated molecular differences within corresponding kidney compartments. For example, the Fosb gene was upregulated early in the cortex of the CI kidneys while it was confined to the medulla of WI kidneys. Conclusion: CI and WI induce pleiotropic transcriptional effects in a spatially and temporally distinct manner. Developing strategy for spatiotemporal molecular characterization can enhance our understanding of CI to improve outcomes and reduce organ discard. Funding: NIDDK Support

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Journal
Journal of the American Society of Nephrology
Published
2024-10-01
DOI
https://doi.org/10.1681/asn.2024gg9vyt06
Primary Topic
Molecular Biology Techniques and Applications
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article
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article

Computational Workflow for Spatiotemporal Transcriptomics Analysis of Cold vs. Warm Ischemic Kidney Injury

Hamid Rabb, Jean Fan, Zhaoli Sun, Srujan Singh et al.
Journal of the American Society of Nephrology
Molecular Biology Techniques and Applications
article

Computational Workflow for Spatiotemporal Transcriptomics Analysis of Cold vs. Warm Ischemic Kidney Injury

Hamid Rabb, Jean Fan, Zhaoli Sun, Srujan Singh, Sanjeev Noel, Shishir Kumar Patel
article en

Abstract

Background: Increasing cold ischemia (CI) time leads to AKI, limits lifespan of transplanted organs and increases organ discard. However, there is limited comparison of the molecular pathogenesis between CI and warm ischemia (WI) injury. We performed full-transcriptome characterization in a CI murine model using the 10X Visium spatial transcriptomics (ST) platform for comparison with previously published WI data. Methods: We induced CI in murine kidneys in UW solution at 4oC (0, 12, 24 and 48 hours), then generated ST datasets (n=1 per timepoint), containing 12530 spatial spots with 19465 shared gene species profiled per kidney tissue section. We developed a computational workflow which facilitates batch correction (via Harmony) to identify shared cell types across all datasets. We segmented kidney tissues into three different compartments, namely the cortex, medulla, and corticomedullary junction based on cell types and their anatomical location. We identified differentially expressed genes (DEGs) across time points unique to each compartment using DESeq2, clustered DEGs into different temporal trends, and further characterized enriched pathways per compartment per trend using ClusterProfiler. We implemented a similar workflow on WI injury kidneys. Results: We integrated 0, 12, 24 and 48 hours CI kidney ST datasets and identified shared cell types across all timepoints that demarcated similar anatomical locations. We identified shared temporal trends affecting distinct genes and pathways within different kidney compartments. In particular, autophagy-related pathways were uniquely upregulated in the cortex of CI kidney at an early timepoint (12 hours) whereas upregulation of immune-related pathways emerged in the medulla at a later timepoint (48 hours). Comparisons between CI and WI further elucidated molecular differences within corresponding kidney compartments. For example, the Fosb gene was upregulated early in the cortex of the CI kidneys while it was confined to the medulla of WI kidneys. Conclusion: CI and WI induce pleiotropic transcriptional effects in a spatially and temporally distinct manner. Developing strategy for spatiotemporal molecular characterization can enhance our understanding of CI to improve outcomes and reduce organ discard. Funding: NIDDK Support

Journal of the American Society of NephrologyVol. 35(10S)
Johns Hopkins University (US)
Zero hunger
Openalex Percentile: Top 83%
Molecular Biology Techniques and Applications
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