High-throughput Imaging and Analysis Workflow for Evaluating Skin Cell Phenotypes and Proliferation States in Tissue Samples

Skin injuries initiate a complex regenerative cascade that engages various cell types. Amongst those, peripheral glial cells play a critical role in ensuring the success of the repair process. However, our understanding of these processes remains incomplete due to limitations in current technologies. Therefore, the iterative-bleaching-extends-multiplexity (IBEX) method was employed to characterize changes to the cellular composition of the skin using antibodies directed against proteins expressed by key cell types and structures involved in tissue regeneration. Importantly, antibodies directed against cell proliferation markers often underestimate the number of dividing cells in the skin. To overcome this limitation, Click-iT EdU chemistry was combined with the IBEX method, allowing detailed characterization of proliferating cell types. Using a fully automated spinning disk confocal microscope, a high-throughput workflow was developed for iterative imaging of samples sectioned into 24-well plates. Beyond extending the IBEX method to evaluate cell states in situ with Click-iT EdU, a novel open-source image processing pipeline was also introduced to perform image correction, stitching, and registration, and can be used by researchers without extensive programming experience. Moreover, a detailed documentation on processing and visualizing highly multiplexed imaging data (using conventional image analysis software, including Fiji and QuPath) is also provided. In summary, this protocol highlights the versatility of the IBEX protocol and demonstrates its adaptation to an established conventional imaging platform. Notably, combining IBEX with Click-iT EdU labeling enables the detection and categorization of actively dividing cell types in intact tissues and during highly dynamic processes at spatial resolution.

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Publication Details

Journal
Journal of Visualized Experiments
Published
2025-10-31
DOI
https://doi.org/10.3791/67696
Citations
1
Primary Topic
Cell Image Analysis Techniques
Type
article
Field-Weighted Citation Impact
1.63
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article

High-throughput Imaging and Analysis Workflow for Evaluating Skin Cell Phenotypes and Proliferation States in Tissue Samples

Whitney Jordaan, Lukas Sommer, Joana Raquel Martins, Salome Stierli et al.
1 citations
Journal of Visualized Experiments
Cell Image Analysis Techniques
1.63
article

High-throughput Imaging and Analysis Workflow for Evaluating Skin Cell Phenotypes and Proliferation States in Tissue Samples

Whitney Jordaan, Lukas Sommer, Joana Raquel Martins, Salome Stierli, Sofia Micheli, Flurin Sturzenegger
article en
1 citations

Abstract

Skin injuries initiate a complex regenerative cascade that engages various cell types. Amongst those, peripheral glial cells play a critical role in ensuring the success of the repair process. However, our understanding of these processes remains incomplete due to limitations in current technologies. Therefore, the iterative-bleaching-extends-multiplexity (IBEX) method was employed to characterize changes to the cellular composition of the skin using antibodies directed against proteins expressed by key cell types and structures involved in tissue regeneration. Importantly, antibodies directed against cell proliferation markers often underestimate the number of dividing cells in the skin. To overcome this limitation, Click-iT EdU chemistry was combined with the IBEX method, allowing detailed characterization of proliferating cell types. Using a fully automated spinning disk confocal microscope, a high-throughput workflow was developed for iterative imaging of samples sectioned into 24-well plates. Beyond extending the IBEX method to evaluate cell states in situ with Click-iT EdU, a novel open-source image processing pipeline was also introduced to perform image correction, stitching, and registration, and can be used by researchers without extensive programming experience. Moreover, a detailed documentation on processing and visualizing highly multiplexed imaging data (using conventional image analysis software, including Fiji and QuPath) is also provided. In summary, this protocol highlights the versatility of the IBEX protocol and demonstrates its adaptation to an established conventional imaging platform. Notably, combining IBEX with Click-iT EdU labeling enables the detection and categorization of actively dividing cell types in intact tissues and during highly dynamic processes at spatial resolution.

Journal of Visualized Experiments(224)
University of Zurich (CH)
Openalex Percentile: Top 11%
Cell Image Analysis Techniques
1.63
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