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Establishing a High Throughput Epidermal Spheroid Culture System to Model Keratinocyte Stem Cell Plasticity
Published on: January 30, 2021
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Automated collective motion analysis validates human keratinocyte stem cell cultures
Koji Kinoshita1, Takuya Munesue2, Fujio Toki3
1Graduate School of Science and Engineering, Ehime University, 3 Bunkyo-cho, Matsuyama, Ehime, 790-8577, Japan. kinoshita@cs.ehime-u.ac.jp.
Scientific Reports
|December 12, 2019
Summary
This study introduces an automated image-processing pipeline for identifying and assessing the quality of human keratinocyte stem cells. The method uses cell locomotion speed to ensure stem cell culture quality for therapeutic applications.
Area of Science:
- Stem Cell Biology
- Biotechnology
- Image Analysis
Background:
- Accurate identification and quality control of stem cells are crucial for effective stem cell therapies.
- Culturing stem cells in mixed populations presents challenges for quality assurance.
Purpose of the Study:
- To develop an automated image-processing pipeline for identifying and assessing human keratinocyte stem cells.
- To enable high-throughput screening of compounds affecting stem cell behavior.
Main Methods:
- Utilized image processing and kernel density estimation to isolate keratinocyte colonies from phase-contrast images.
- Employed the DeepFlow algorithm to quantify colony locomotion speed from serial images.
Main Results:
- Successfully identified keratinocyte stem cell colonies based on measured locomotion speed.
- Assessed the impact of nutrient-poor (oligotrophic) conditions and chemical inhibitors on keratinocyte behavior.
Conclusions:
- The developed pipeline provides automated, image-based quality control for stem cell cultures.
- This method facilitates high-throughput screening of small molecules targeting stem cells.
