<i>Glomage</i> : A Multimodal Platform for High‐Content Morphological and RNA Profiling of Glomeruli in Zebrafish and Mouse Models

ABSTRACT Chronic kidney disease affects more than 850 million people worldwide, yet effective treatment strategies remain limited. The glomerulus is the central filtering unit of the kidney and critically depends on the complex 3D architecture of podocytes. As terminally differentiated and essentially non‐regenerative cells, podocytes are highly vulnerable to injury, and their loss is an irreversible factor in kidney function decline. However, their complex morphology has prevented scalable analysis and slowed progress in drug discovery. To overcome these limitations, Glomage was developed as a cross‐species high‐throughput platform for scalable 3D analysis of glomeruli. In zebrafish larvae, the workflow enables simultaneous isolation, staining, volumetric imaging, and RNA extraction of hundreds of glomeruli. By preserving spatial architecture, the protocol supports rapid, reproducible quantification of podocyte number and structure, enabling systematic assessment of cellular phenotypes at an unprecedented scale. To extend translational relevance, the workflow was adapted to isolated mouse glomeruli, enabling rapid 3D imaging and sensitive detection of key pathological features such as age‐related podocyte depletion. Compatibility across species underscores the robustness, versatility, and broad applicability of the platform. Overall, Glomage creates a powerful high‐content framework for glomerular profiling, accelerates mechanistic studies of podocyte biology, and supports the discovery of urgently needed therapeutic interventions.

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Publication Details

Journal
Advanced Science
Published
2026-04-16
DOI
https://doi.org/10.1002/advs.202523662
Primary Topic
Single-cell and spatial transcriptomics
Type
article
Field-Weighted Citation Impact
0.00

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article

Glomage : A Multimodal Platform for High‐Content Morphological and RNA Profiling of Glomeruli in Zebrafish and Mouse Models

Soeren S. Lienkamp, Tim Lange, Maximilian Schindler, Nicole Endlich et al.
Advanced Science
Single-cell and spatial transcriptomics
article

Glomage : A Multimodal Platform for High‐Content Morphological and RNA Profiling of Glomeruli in Zebrafish and Mouse Models

Soeren S. Lienkamp, Tim Lange, Maximilian Schindler, Nicole Endlich, Sophia‐Marie Bach
article en

Abstract

ABSTRACT Chronic kidney disease affects more than 850 million people worldwide, yet effective treatment strategies remain limited. The glomerulus is the central filtering unit of the kidney and critically depends on the complex 3D architecture of podocytes. As terminally differentiated and essentially non‐regenerative cells, podocytes are highly vulnerable to injury, and their loss is an irreversible factor in kidney function decline. However, their complex morphology has prevented scalable analysis and slowed progress in drug discovery. To overcome these limitations, Glomage was developed as a cross‐species high‐throughput platform for scalable 3D analysis of glomeruli. In zebrafish larvae, the workflow enables simultaneous isolation, staining, volumetric imaging, and RNA extraction of hundreds of glomeruli. By preserving spatial architecture, the protocol supports rapid, reproducible quantification of podocyte number and structure, enabling systematic assessment of cellular phenotypes at an unprecedented scale. To extend translational relevance, the workflow was adapted to isolated mouse glomeruli, enabling rapid 3D imaging and sensitive detection of key pathological features such as age‐related podocyte depletion. Compatibility across species underscores the robustness, versatility, and broad applicability of the platform. Overall, Glomage creates a powerful high‐content framework for glomerular profiling, accelerates mechanistic studies of podocyte biology, and supports the discovery of urgently needed therapeutic interventions.

Advanced Science
University of Zurich (CH), Zurich Insurance Group (Switzerland) (CH), Universitätsmedizin Greifswald (DE), ETH Zurich (CH)
Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung, Bundesministerium für Bildung und Forschung
Openalex Percentile: Top 15%
Single-cell and spatial transcriptomics
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