High-throughput, organ-scale 3D tubule tracking using TubuleMAP

Advances in tissue clearing and lightsheet microscopy enable mesoscale imaging of intact and convoluted tubular networks, yet analytical tools to map tubule continuity and assess injury patterns within and across tubules are limited. Here, we introduce TubuleMAP, a semi-automated pipeline for 3D tubule tracking and reconstruction that adapts to various morphological and staining patterns, leverages parallel processing of terabyte-scale data for large-scale analysis of tubular networks, and uses a napari interface for human oversight. Using TubuleMAP, we reconstruct 1,000 intact mouse nephrons in ~1-millimeter-thick kidney slab with ~400-fold higher throughput and <1% human effort compared to prior approaches. These reconstructions enable analysis of mesoscale nephron organization, quantitative profiling of pathologic morphologies, whole-nephron cytometry, and identification of rare morphologies at unprecedented scales. We demonstrate generalizability by reconstructing all seminiferous tubules in a mouse testis within a day. TubuleMAP is released as an open-source Python package.

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Publication Details

Journal
bioRxiv (Cold Spring Harbor Laboratory)
Published
2026-04-27
DOI
https://doi.org/10.64898/2026.04.23.720231
Primary Topic
Renal and related cancers
Type
article
Field-Weighted Citation Impact
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article

High-throughput, organ-scale 3D tubule tracking using TubuleMAP

Nina Fan, Stuart J. Shankland, Ruben M. Sandoval, David Brenes et al.
bioRxiv (Cold Spring Harbor Laboratory)
Renal and related cancers
article

High-throughput, organ-scale 3D tubule tracking using TubuleMAP

Nina Fan, Stuart J. Shankland, Ruben M. Sandoval, David Brenes, Kenneth W. Dunn, Wenhui Xie, Pierre C. Dagher, Chetan Poudel, Yvonne Guan, Diana G. Eng, Jonathan Liu, Joshua C. Vaughan, Madeline K. Wong, Eesha Konatham, Pedro Vasquez, Naren Mahadevan, Ziyu Guo, Nicolas J Porter, Michelle M. Martinez
article en

Abstract

Advances in tissue clearing and lightsheet microscopy enable mesoscale imaging of intact and convoluted tubular networks, yet analytical tools to map tubule continuity and assess injury patterns within and across tubules are limited. Here, we introduce TubuleMAP, a semi-automated pipeline for 3D tubule tracking and reconstruction that adapts to various morphological and staining patterns, leverages parallel processing of terabyte-scale data for large-scale analysis of tubular networks, and uses a napari interface for human oversight. Using TubuleMAP, we reconstruct 1,000 intact mouse nephrons in ~1-millimeter-thick kidney slab with ~400-fold higher throughput and <1% human effort compared to prior approaches. These reconstructions enable analysis of mesoscale nephron organization, quantitative profiling of pathologic morphologies, whole-nephron cytometry, and identification of rare morphologies at unprecedented scales. We demonstrate generalizability by reconstructing all seminiferous tubules in a mouse testis within a day. TubuleMAP is released as an open-source Python package.

bioRxiv (Cold Spring Harbor Laboratory)
University of Washington (US), University School (US), Indiana University School of Medicine, Indiana University (US), Stanford University (US)
Openalex Percentile: Top 15%
Renal and related cancers
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