Name: High-throughput Imaging and Analysis Workflow for Evaluating Skin Cell Phenotypes and Proliferation States in Tissue Samples (Video) | JoVE Journal
Uploaded: 2025-10-31T14:20:00.000+00:00
Duration: 11 min 24 s
Description: Learn IBEX multiplex imaging with Click-iT EdU labeling to detect proliferating cell types in murine skin repair. This open-source pipeline enables high-throughput analysis without programming skills.

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We would like to acknowledge the Center for Microscopy and Image Analysis for their support with the MD ImageXpress microscope and the Laboratory Animal Services Center for the mouse husbandry. L.S. was funded by two Swiss National Science Foundation grants (310030_192075 and 310030_207801), a Swiss Cancer Research Foundation grant (KLS-5391-08-2021) and by the SKINTEGRITY.CH collaborative research consortium. S.S. was funded by a University of Zurich Postdoc Grant (FK-22-056).

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<li>Radtke, A. J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((IBEX%3A+An+iterative+immunolabeling+and+chemical+bleaching+method+for+high-content+imaging+of+diverse+tissues%5BTitle%5D)+AND+%22Nat+Protoc%22%5BJournal%5D)">IBEX: An iterative immunolabeling and chemical bleaching method for high-content imaging of diverse tissues.</a> Nat Protoc. 17 (2), 378-401 (2022).</li>
<li>Uxa, S., Castillo-Binder, P., Kohler, R., Stangner, K., Müller, G. A., Engeland, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Ki-67+gene+expression%5BTitle%5D)+AND+%22Cell+Death+Differ%22%5BJournal%5D)">Ki-67 gene expression.</a> Cell Death Differ. 28 (12), 3357-3370 (2021).</li>
<li>Sun, X., Kaufman, P. D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Ki-67%3A+More+than+a+proliferation+marker%5BTitle%5D)+AND+%22Chromosoma%22%5BJournal%5D)">Ki-67: More than a proliferation marker.</a> Chromosoma. 127 (2), 175-186 (2018).</li>
<li>Peng, T., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((A+BaSiC+tool+for+background+and+shading+correction+of+optical+microscopy+images%5BTitle%5D)+AND+%22Nat+Commun%22%5BJournal%5D)">A BaSiC tool for background and shading correction of optical microscopy images.</a> Nat Commun. 8 (1), 14836(2017).</li>
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<li>Parfejevs, V., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Injury-activated+glial+cells+promote+wound+healing+of+the+adult+skin+in+mice%5BTitle%5D)+AND+%22Nat+Commun%22%5BJournal%5D)">Injury-activated glial cells promote wound healing of the adult skin in mice.</a> Nat Commun. 8 (1), 14396(2018).</li>
<li>Peña, O. A., Martin, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Cellular+and+molecular+mechanisms+of+skin+wound+healing%5BTitle%5D)+AND+%22Nat+Rev+Mol+Cell+Biol%22%5BJournal%5D)">Cellular and molecular mechanisms of skin wound healing.</a> Nat Rev Mol Cell Biol. 25 (8), 599-616 (2024).</li>
<li>Eming, S. A., Wynn, T. A., Martin, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Inflammation+and+metabolism+in+tissue+repair+and+regeneration%5BTitle%5D)+AND+%22Science%22%5BJournal%5D)">Inflammation and metabolism in tissue repair and regeneration.</a> Science. 356 (6342), 1026-1030 (2017).</li>
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</ol>

The authors have no competing interests to declare.

Cell proliferation is one of the four main stages of skin repair, and the transition between the inflammatory phase and the proliferative phase is critical for a successful repair process20. A well-regulated immune response is essential, as prolonged inflammation can lead to chronic wounds, a significant global health issue1,21. Proliferation is a key biological process, not only important for tissue repair but also for organism developmen...

The skin is the largest organ of the human body and the primordial barrier to protect the body from the outside environment1. Consequently, it is exposed to a plethora of external challenges that compromise its barrier function. Therefore, the skin has developed complex mechanisms to restore tissue integrity and functionality following damage. Skin wound healing takes place in three overlapping stages: inflammation, proliferation, and maturation/remodeling. These three stages involve several different cell types, such as dermal fibroblasts and immune cells, that act together to restore the initial biological properties of the injured skin tissue1,2,3.
The skin is a densely innervated organ, and it is known that nerve innervation is crucial for a successful repair process4,5,6. Apart from axonal signaling4,7,8, the peripheral glia, normally ensheathing the axons, participate in successful tissue regeneration9,10,11. However, the role of underrepresented cell types, such as peripheral glial cells, remains poorly understood in dynamic processes like skin tissue regeneration. To better determine the function of these cells, it is critical to analyze the cellular microenvironment and the neighboring cell types with which they may interact during the regenerative process. Moreover, since cell proliferation is a key stage for tissue regeneration, it is important to accurately detect and classify the proliferating cell types throughout the repair process.
Multiplexed, high-content, optical imaging methods, such as IBEX12, have been developed to characterize the cellular composition, visualize and quantify cell-cell interactions, and dissect microenvironmental patterns within complex tissues at spatial resolution. Whereas other multiplexing methods require specialized instruments and proprietary reagents, a particular advantage of IBEX is that it can be established at relatively low costs using commercially available antibodies, reagents, and microscopes accessible in a standard research environment. While anti-Ki-67 antibodies, often used in IBEX panels, reliably label proliferating cell types in many tissues13,14, the number of Ki-67-positive (Ki-67+) cells was found to be underestimated compared to other methodologies in fixed frozen tissue sections of acute murine skin wounds. Therefore, we combined the Click-iT EdU chemistry with IBEX and found that the number of EdU+ cells more accurately represents the total number of proliferating cells obtained by other methodologies.
Furthermore, by employing a fully automated spinning disk confocal microscope, a high-throughput workflow was established for iterative imaging of tissue sections placed into a 24-well plate. The resulting images are then processed by combining multiple open-source Python tools into a novel image processing pipeline that corrects the images for uneven illumination, performs the stitching of the individual tiles, and ultimately, image registration. In detail, the BaSiCPy library15 was used for illumination correction, the m2stitch library for stitching the images, and phase-cross-correlation for cycle registration. The registered images are saved as OME-TIFFs and can then be loaded into conventional image analysis software, such as Fiji17 and QuPath18, where the images are then further processed, and cell type categorization and other measurements, like intensity and distance calculations, can be performed. Taken together, the present protocol allowed us to perform a detailed, highly efficient characterization of the main cell types of the regenerating skin, with a particular focus on the cellular microenvironment surrounding the peripheral glial cell population.

<table><tbody><tr><td>Antibodies and reagents&amp;nbsp;</td><td>SOURCE</td><td>IDENTIFIER</td><td>Comments</td></tr><tr><td>&lt;strong&gt;Antibodies&lt;/strong&gt;</td><td></td><td></td><td></td></tr><tr><td>CD31 Alexa Fluor 647 (Cycle 2)&amp;nbsp;</td><td>BioLegend</td><td>Cat#102516</td><td>1:100</td></tr><tr><td>AB_2161029</td><td></td><td></td><td></td></tr><tr><td>CD45 Alexa Fluor 488 (Cycle 2)&amp;nbsp;</td><td>BioLegend</td><td>Cat#103122</td><td>1:100</td></tr><tr><td>AB_493531</td><td></td><td></td><td></td></tr><tr><td>Ki-67 FITC (Cycle 1)&amp;nbsp;</td><td>BioLegend</td><td>Cat#151212</td><td>1:50</td></tr><tr><td>AB_2814055</td><td></td><td></td><td></td></tr><tr><td>Ki-67 chicken (ck)</td><td>LSBio</td><td>Cat#LS-C772946</td><td>1:800</td></tr><tr><td>Ki-67 rat (rt)&amp;nbsp;</td><td>BioLegend</td><td>Cat#652402</td><td>1:100</td></tr><tr><td>AB_11204254</td><td></td><td></td><td></td></tr><tr><td>Neurofilament H&amp;amp;M (NF-H/NF-M) Alexa Fluor 647 (Cycle 3)&amp;nbsp;</td><td>BioLegend&amp;nbsp;</td><td>Cat#837710</td><td>1:300</td></tr><tr><td>AB_2734613</td><td></td><td></td><td></td></tr><tr><td>p75NTR (Cycle 1)&amp;nbsp;</td><td>Cell Signaling Technology</td><td>Cat#8238&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; AB_10839265</td><td>1:1500</td></tr><tr><td>Vimentin Alexa Fluor 488 (Cycle 3)&amp;nbsp;</td><td>BioLegend</td><td>Cat#699305</td><td>1:100</td></tr><tr><td>AB_2888889</td><td></td><td></td><td></td></tr><tr><td>Alexa Fluor 647 donkey anti rabbit</td><td>Jackson ImmunoResearch</td><td>Cat#711-605-152</td><td></td></tr><tr><td>&lt;strong&gt;Reagents&lt;/strong&gt;&amp;nbsp;</td><td></td><td></td><td></td></tr><tr><td>Cellvis 24 well Glass Bottom Plate</td><td>Cellvis&amp;nbsp;</td><td>P24-1.5H-N</td><td></td></tr><tr><td>Chrome alum gelatin</td><td>Newcomer Supply</td><td>Cat#1033A</td><td></td></tr><tr><td>Click-iT EdU kit&amp;nbsp;</td><td>Thermo Fisher Scientific</td><td>C10637</td><td></td></tr><tr><td>Hoechst 33342</td><td>Sigma-Aldrich</td><td>Cat#14533; CAS# 23491-52-3</td><td></td></tr><tr><td>LiBH&lt;sub&gt;4, &lt;/sub&gt;Lithium Borohydride, 95%</td><td>Thermo Fisher Scientific</td><td>Cat#10438443</td><td></td></tr><tr><td>Tissue-Tek O.C.T Compound Sakura</td><td>Biosystems Switzerland</td><td>Cat#7109-4583</td><td></td></tr><tr><td>PBS</td><td>Thermo Fisher Scientific</td><td>Cat#10010-015</td><td></td></tr><tr><td>Superfrost Plus Adhesion Microscope Slides&amp;nbsp;</td><td>Epredia</td><td>Cat#J1800AMNZ</td><td></td></tr><tr><td>Triton X-100</td><td>Sigma-Aldrich&amp;nbsp;</td><td>Cat#T8787</td><td></td></tr><tr><td>&lt;strong&gt;Equipment&lt;/strong&gt;</td><td></td><td></td><td></td></tr><tr><td>Hair brush&amp;nbsp;</td><td>Faust AG</td><td>Cat#9172051 and 9172050</td><td></td></tr><tr><td>Microtome blades&amp;nbsp;</td><td>Biosystems Switzerland</td><td>Cat#207500011</td><td></td></tr><tr><td>Microscope</td><td>Molecular Devices, ImageXpress Confocal HT.ai</td><td></td><td></td></tr><tr><td>Oven&amp;nbsp;</td><td>Thermo Fisher Scientific</td><td>Cat#HBMCR4220</td><td></td></tr><tr><td>Rocker shaker</td><td>Edmund B&amp;uuml;hler GmbH</td><td>Cat#32310015</td><td></td></tr></tbody></table>

high-throughput imaging and analysis workflow for evaluating skin cell phenotypes and proliferation states in tissue samples

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.

This method allows adequate detection of proliferating cell types by combining EdU Click-iT chemistry with IBEX in fixed frozen murine skin sections. Detection of proliferating cell types was compared using different methodologies, in particular, labeling of proliferating cell types with Ki-67 antibody and detection of cell proliferation using the EdU Click-iT chemistry approach (Figure 1). We observed that Ki-67 antibody labeling underestimates the number of...

The combination of iterative-bleaching-extends-multiplexity (IBEX) and a commercial nucleotide labeling assay (Click-iT EdU) enables the detection and categorization of dividing cell types in highly dynamic processes in fixed frozen murine tissue sections. Furthermore, a novel open-source image processing pipeline provides high-throughput image acquisition and analysis.

Skin injuries initiate a complex regenerative cascade that engages various cell types. Amongst those, peripheral glial cells play a critical role in ...

This protocol combines the multiplex optical imaging method, IBEX and Click-iT EDU labeling to detect and categorize dividing cell types in highly dynamic processes, such as skin repair. Moreover, we provide a novel open-source imaging processing pipeline for high throughput image acquisition and analysis. Coat the 24 well plate with 200 microliters of chrome aluminum gelatin and incubate the plate for 15 minutes on a rocker shaker.Then completely remove the gelatin and dry the coated wells for 60 minutes in a 40 degrees oven. Cut the OCT-embedded tissue at 15 to 30 micrometer thickness at the cryostat and transfer it quickly into a coated well containing two milliliters of PBS. Carefully remove the PBS using a one milliliter pipette aiming to keep the tissue section centered in the well.To do this effectively, slowly aspirate the PBS from the edges of the well, adjusting the pipette position as needed to prevent the tissue from shifting. Dry the tissue sections for one hour in a 37 degrees Celsius oven. Rehydrate with one milliliter PBS for five minutes.Permeabilize the tissue with 500 microliters of 0.5%Triton for 30 minutes at room temperature. Wash the tissue briefly twice with PBS and perform the Click-iT reaction for 30 minutes at room temperature. Keep the samples protected from light.Wash the tissue briefly twice with PBS. Block for one hour with a blocking buffer at room temperature. Add the primary antibodies for the first cycle.And incubate the plate overnight at four degrees Celsius. Wash with PBS three times. Perform the secondary antibody staining.For the first cycle, apply the secondary antibodies for the uncoupled primary antibodies together with a nuclear counterstain. Incubate the samples protected from light for 60 minutes at room temperature. Wash the tissue three times with one milliliter PBS for five minutes at room temperature.Leave about 500 microliters of PBS in each well and bring the plate to the microscope. In the Meta Express software, click on Screening and then Acquisition Setup. Click on the Eject button.Clean the bottom of the plate with 70%ethanol and insert plate into the microscope. Click the Load Plate button. Within the Objective and Camera tab, select the desired magnification.As acquisition mode, select the confocal 51 micrometer slit mode. Within the Plate tab, select the plate model. Go to the Plates Sites Visit tab.Under Site Options, click on fixed number of sites. Set the number of both columns and rows such that roughly the entire well is covered. Click on the overlap sites 10%Select only the first well for acquisition by right clicking the corresponding well on the plate map.Go to the Acquisition Autofocus tab. For well-to-well autofocus, select the plate and well bottom option. For site autofocus, select the All Sites option.Go to the Wavelengths tab and choose the number of dyes to be imaged in the current cycle. Go to the first wavelength tab. Choose laser with Z offset for the Z-positioning, and click the Calculate Offset button to set the correct imaging height.Choose the image where the sample is best in focus. Press the Focus button. An in-focus image of the tissue is shown.Set the illumination power to 50%Set the target max intensity to 2000 and press Auto Expose. For Z-series, choose Z-series and 2D projection image, and for shading correction, choose FL shading only. Repeat the steps for other wavelengths, but instead of laser with Z-offset, choose Z-offset from W1 and choose zero.Go to the Z-series step and enter the desired step size. Click the Focus button. Drag the current position arrow until the bottom of the tissue is reached and click the Set B button.Drag the position arrow to the top of the tissue and click Set T button. Click on F2, Stop, press Start Live again. Ensure that the stage is at the first well by left clicking on it.Find the border of the tissue and mark all sites containing tissue for acquisition by right clicking. Go to the Run tab and type the name of the plate. Click on Save Protocol.Set up the acquisition region for all the other wells. Run Control, Journal, start recording and then immediately Control, Journal, stop recording. Save the created journal and open it again via Control, Journal, Edit Journal.In the left panel, go to Plate Acquisition, load protocol from file and click on Plate Acquisition to add those steps to the journal. Double click on the Edit Plate Acquisition, load protocol from file, and choose the protocol saved for the first well. Repeat the steps for each well to be acquired, making sure to always load the respective protocol.Click on Run Journal to start the acquisition. 30 minutes before the end of the journal, start to prepare the bleaching reagent. Dissolve 10 milligrams of lithium borohydride in 10 milliliter of double distilled H2O and pass through a 0.22 micrometers filter.Leave for 10 minutes. The solution should start to form bubbles. To ensure efficient bleaching, use the bleaching reagent within four hours after preparation.Add the bleaching solution to the samples and incubate for 15 minutes whilst keeping the samples exposed to ambient lighting. Small bubbles should appear on the tissue. Wash the bleached samples three times with one milliliter PBS for five minutes, each at room temperature.Add the primary antibodies for the next cycle and incubate overnight at four degrees Celsius. Multiplexed IBEX imaging combined with Click-iT EDU labeling reveals different structures and proliferating cell types in the wounded skin. EDU labeling on cryopreserved samples shows to be similar when performing antibody immunofluorescence labeling for KI-67 on paraffin-embedded tissue sections, as well as labeling cells with KI 67 using flow cytometry.Using this protocol allows accurate detection of cell proliferation in complex biological processes. Moreover, the open source imaging processing pipeline does not require any programming experience and generates files that can be processed with non-commercial software, such as Fiji and quPath. Furthermore, this protocol does not require any expensive equipment and therefore, can be performed in most research settings.

high-throughput-imaging-analysis-workflow-for-evaluating-skin-cell

Research

JoVE Journal

Biology

Carcinogenesis is a process involving interactions between cancer cells and the cancer microenvironment. To dissect the molecular events, one needs to isolate different cell populations at different stages during cancer development. Using a mouse model for basal cell carcinoma, we describe a protocol for cell analyses during carcinogenesis.

Cell Population Analyses During Skin Carcinogenesis

Here we describe a workflow for rapidly analyzing and exploring collections of fluorescence microscopy images using PhenoRipper, a recently developed image-analysis platform.

Rapid Analysis and Exploration of Fluorescence Microscopy Images

Presented is a flexible informatics workflow enabling multiplexed image-based analysis of fluorescently labeled cells. The workflow quantifies nuclear and cytoplasmic markers and computes marker translocation between these compartments. Procedures are provided for perturbation of cells using siRNA and reliable methodology for marker detection by indirect immunofluorescence in 96-well formats.

Workflow for High-content, Individual Cell Quantification of Fluorescent Markers from Universal Microscope Data, Supported by Open Source Software

This study describes an experimental platform to rapidly characterize engineered stem cells and their behaviors before their application in long-term in vivo transplant studies for nervous system rescue and repair.

High Throughput Characterization of Adult Stem Cells Engineered for Delivery of Therapeutic Factors for Neuroprotective Strategies

Cell differentiation is regulated by a host of microenvironmental factors, including both matrix composition and substrate material properties. We describe here a technique utilizing cell microarrays in conjunction with traction force microscopy to evaluate both cell differentiation and biomechanical cell–substrate interactions as a function of microenvironmental context.

A High-throughput Cell Microarray Platform for Correlative Analysis of Cell Differentiation and Traction Forces

We have developed a novel protocol for studying heterocellular population dynamics in response to perturbations. This manuscript describes an imaging-based platform that produces quantitative datasets for simultaneous characterization of multiple cellular phenotypes of heterocellular populations in a robust manner.

Discrimination and Characterization of Heterocellular Populations Using Quantitative Imaging Techniques

Studying tumor microenvironment may identify prognostic or predictive biomarkers of clinical response to immunotherapy. Presented here, is an innovative method based on in situ fluorescence multispectral imaging to analyze and count automatically various subpopulations of CD8+ T cells. This reproducible and reliable technique is suitable for large cohort analyses.

Multiplexed Immunofluorescence Analysis and Quantification of Intratumoral PD-1+ Tim-3+ CD8+ T Cells

Multiplexed barcoding image analysis has recently improved the characterization of the tumor microenvironment, permitting comprehensive studies of cell composition, functional state, and cell-cell interactions. Herein, we describe a staining and imaging protocol using the barcoding of oligonucleotide-conjugated antibodies and cycle imaging, which allows for the use of a high-dimensional image analysis technique.

Multiplexed Barcoding Image Analysis for Immunoprofiling and Spatial Mapping Characterization in the Single-Cell Analysis of Paraffin Tissue Samples

Here, we describe the application of the Iterative Bleaching Extends Multiplicity (IBEX) method utilizing commercially available, automated tissue stainers and optimization considerations for the use of tyramide signal amplification-based reagents.

Iterative Bleaching Extends Multiplicity with Use of Staining Automation for Core Facilities

Here, we provide a method for live cell imaging analysis that can be used to manually track the lineages of passage 0 keratinocytes and that allows the collection of proliferation metrics, including cell division fate and cell cycle duration.

Live Cell Imaging with Time Lapse Photography to Study Epidermal Keratinocyte Proliferation Kinetics

Here, we present a semi-automated protocol for identifying and quantifying immune and non-immune cells in skin sections using SCAnED, a free ImageJ-based macro for skin segmentation.

SCAnED - An Open-source Skin Segmentation Macro for Semi-automated Cell and Nuclei Detection in Epidermal and Dermal Skin Compartments

Learn IBEX multiplex imaging with Click-iT EdU labeling to detect proliferating cell types in murine skin repair. This open-source pipeline enables high-throughput analysis without programming skills.

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

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