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Abstract: FR-PO014

Regulation of the Adaptive Proximal Tubule Cell State by ELF3, KLF6, and KLF10

Session Information

Category: Augmented Intelligence, Digital Health, and Data Science

  • 300 Augmented Intelligence, Digital Health, and Data Science

Authors

  • Gisch, Debora L., Indiana University School of Medicine, Indianapolis, Indiana, United States
  • Lake, Blue, San Diego Institute of Science, Altos Labs, San Diego, California, United States
  • Basta, Jeannine M., Washington University in St Louis School of Medicine, St Louis, Missouri, United States
  • Pherson, Michelle, Saint Louis University, Saint Louis, Missouri, United States
  • Cheng, Ying-Hua, Indiana University School of Medicine, Indianapolis, Indiana, United States
  • Melo Ferreira, Ricardo, Indiana University School of Medicine, Indianapolis, Indiana, United States
  • Barwinska, Daria, Indiana University School of Medicine, Indianapolis, Indiana, United States
  • Asghari, Mahla, Indiana University School of Medicine, Indianapolis, Indiana, United States
  • El-Achkar, Tarek M., Indiana University School of Medicine, Indianapolis, Indiana, United States
  • Mollah, Shamim, Washington University in St Louis School of Medicine, St Louis, Missouri, United States
  • Himmelfarb, Jonathan, University of Washington, Seattle, Washington, United States
  • Kretzler, Matthias, Michigan State University, East Lansing, Michigan, United States
  • Dagher, Pierre C., Indiana University School of Medicine, Indianapolis, Indiana, United States
  • Jain, Sanjay, Washington University in St Louis School of Medicine, St Louis, Missouri, United States
  • Rauchman, Michael I., Washington University in St Louis School of Medicine, St Louis, Missouri, United States
  • Eadon, Michael T., Indiana University School of Medicine, Indianapolis, Indiana, United States

Group or Team Name

  • KPMP.
Background

Gene regulatory regions modulate gene expression and maintain cell function. In response to injury, the proximal tubule (PT) undergoes adaptation, including differentiation or epithelial to mesenchymal transition, resulting in successful or failed repair. Single-cell multiome, whole genome bisulfite sequencing (WGBS), and CUT&RUN were used to study the regulatory control of the PT as it undergoes this adaptation.

Methods

Single-cell multiome with ATAC-seq data was generated and analyzed for 12 kidney tissue samples. TRIPOD and scMEGA were used for analysis. Celloracle in silico perturbation tested DEG changes after the knockout of transcription factors (TFs). scMEGA was used to map TF activity in spatial transcriptomics samples (N=3). Regulatory relationships were characterized by WGBS and CUT&RUN.

Results

Between the PT-S12 and aPT, we observed 25,356 DARs and 4194 DEGs at adj-P<0.05. aPT marker genes like TPM1 were targeted by the TFs ELF3, KLF6, and KLF10 which also cross-regulated each other, suggesting a regulatory network of adaptation in the PT. The TF ELF3 targeted 316 DARs of the aPT, including 248 in positively regulated genes. In silico perturbation resulted in the downregulation of TPM1 and other aPT genes such as VCAM1 and ITGB8. The correlation matrix estimated by scMEGA for ELF3 transcription factor activity predicted that 495 genes are bound by ELF3 with a correlation >90%. By transferring these labels to spatial transcriptomics samples, colocalization of TF activity was identified in injured cortical regions with PT. By WGBS and CUT&RUN, the TPM1 peak 106234, targeted by ELF3 was an active promoter with reduced DNA methylation.

Conclusion

ELF3, KLF6, and KLF10 contribute to the PT’s adaptative response to injury as a regulatory network, specifically localized to the PT.

Funding

  • NIDDK Support