Kidney Week

Abstract: FR-PO169

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

Session Information

• AKI: Mechanisms
  October 25, 2024 | Location: Exhibit Hall, Convention Center
  Abstract Time: 10:00 AM - 12:00 PM

Category: Acute Kidney Injury

• 103 AKI: Mechanisms

Authors

• Singh, Srujan, Johns Hopkins University, Baltimore, Maryland, United States

Srujan Singh, PhD

• Noel, Sanjeev, Johns Hopkins University, Baltimore, Maryland, United States

Sanjeev Noel, PhD

• Patel, Shishir Kumar, Johns Hopkins University, Baltimore, Maryland, United States

Shishir Kumar Patel, PhD

• Sun, Zhaoli, Johns Hopkins University, Baltimore, Maryland, United States

Zhaoli Sun, DrMed, DrPH

• Rabb, Hamid, Johns Hopkins University, Baltimore, Maryland, United States

Hamid Rabb, MD, FASN

• Fan, Jean, Johns Hopkins University, Baltimore, Maryland, United States

Jean Fan, PhD

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 4^oC (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