Abstract: SA-PO0001
Kidney Connectomics: Mapping 1,000 Whole Nephrons in a Single Kidney Tissue
Session Information
- Intelligent Imaging and Omics: Phenotyping and Risk Stratification
November 08, 2025 | Location: Exhibit Hall, Convention Center
Abstract Time: 10:00 AM - 12:00 PM
Category: Artificial Intelligence, Digital Health, and Data Science
- 300 Artificial Intelligence, Digital Health, and Data Science
Authors
- Poudel, Chetan, University of Washington, Seattle, Washington, United States
- Brenes, David, University of Washington, Seattle, Washington, United States
- Xie, Wenhui, University of Washington, Seattle, Washington, United States
- Dagher, Pierre C., Indiana University School of Medicine, Indianapolis, Indiana, United States
- Liu, Jonathan T. C., University of Washington, Seattle, Washington, United States
- Vaughan, Joshua C., University of Washington, Seattle, Washington, United States
Group or Team Name
- Vaughan Lab.
Background
Comprehensive 3D mapping of individual nephrons is crucial for uncovering the kidney’s spatial architecture and segment-specific patterns of injury that underlie many renal diseases. Yet, current methods rely on labor-intensive manual tracking, making them too low-throughput for broader application beyond small-scale, proof-of-concept studies. Developing automated computational approaches for 3D nephron reconstruction holds the potential to uncover previously inaccessible insights into nephron function, structural variation, and pathological remodeling across the entire renal tubule.
Methods
We developed an end-to-end pipeline for high-throughput 3D nephron mapping in mouse kidney tissues. One-millimeter-thick slabs were processed using FLARE staining, optical tissue clearing, and imaged via high-resolution lightsheet microscopy. We created Tubule Tracker, an open-source software that performs deep-learning-based segmentation and 3D tracing, mimicking virtual travel through nephron tubules.
Results
Our automated pipeline has dramatically reduced manual effort required for nephron reconstruction, cutting segmentation time from 35 hours to just 10 minutes per nephron. We successfully reconstructed over 1,000 intact nephrons from a single 1.5 mm-thick kidney slab within a few months—a task that would have taken roughly 12 years using traditional manual approaches (Figure 1a,b). Notably, we also segmented entire collecting duct trees, revealing their characteristic binary branching patterns and demonstrating that 200–400 nephrons drain into a single duct of Bellini (Figure 1d). These reconstructions provide the first large-scale maps of nephron-to-duct connectivity, enabling new insights into kidney organization at the systems level.
Conclusion
Tubule Tracker enables largely automated, organ-scale nephron reconstruction, transforming a previously labor-intensive process into a scalable, high-throughput workflow. This powerful tool opens new avenues for studying nephron morphology, spatial organization, and connectivity across the entire kidney in both health and disease.
Funding
- NIDDK Support