Shen, Ping and Wu, Peihua and Maleitzke, Tazio and Reisener, Marie-Jacqueline and Heinz, Gitta A. and Heinrich, Frederik and Durek, Pawel and Gwinner, Clemens and Winkler, Tobias and Pumberger, Matthias and Perka, Carsten and Mashreghi, Mir-Farzin and Löhning, Max (2022) Optimization of chondrocyte isolation from human articular cartilage to preserve the chondrocyte transcriptome. Frontiers in Bioengineering and Biotechnology, 10. ISSN 2296-4185
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Abstract
The isolation of chondrocytes from human articular cartilage for single-cell RNA sequencing requires extensive and prolonged tissue digestion at 37 C. Modulations of the transcriptional activity likely take place during this period such that the transcriptomes of isolated human chondrocytes no longer match their original status in vivo. Here, we optimized the human chondrocyte isolation procedure to maximally preserve the in vivo transcriptome. Cartilage tissues were transferred into a hypoxia chamber (4% O2) immediately after being removed from OA patients and minced finely. Collagenase II at concentrations of 0.02%, 0.1%, 0.25%, 0.5%, 1%, and 2% was applied for 0.5, 1, 2, 4, and 18 h to digest the minced tissue. Actinomycin D (ActD) was added to test its capacity in stabilizing the transcriptome. Cell yield, viability, cell size, and transcriptome were determined using counter chamber, flow cytometry, and RNA sequencing (RNA-seq). Collagenase II at 2% concentration released small chondrocytes from cartilage matrix during the first digestion hour and started to release large cells thereafter, reaching a complete release at 4 h. During 4-h digestions, collagenase II at 2% and 1% but not at lower concentrations yielded maximal release also of the large chondrocyte population. RNA-seq analysis revealed that a 4-h digestion period with 1% or 2% collagenase II plus Actinomycin D optimally preserved the transcriptome. Thus, this study provides an isolation protocol for single chondrocytes from human articular cartilage optimized for transcriptome preservation and RNA-seq analysis.
Item Type: | Article |
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Subjects: | STM Library > Biological Science |
Depositing User: | Managing Editor |
Date Deposited: | 09 Mar 2023 07:32 |
Last Modified: | 19 Jun 2024 11:42 |
URI: | http://open.journal4submit.com/id/eprint/1030 |