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Updated: Aug 6, 2025
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Reprogramming Human Somatic Cells into Induced Pluripotent Stem Cells iPSCs Using Retroviral Vector with GFP
Published on: April 3, 2012
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Predicting reprogramming-related gene expression from cell morphology in human induced pluripotent stem cells.
Takashi Wakui1, Mitsuru Negishi2, Yuta Murakami3
1Bio Science & Engineering Laboratories, Fujifilm Corporation, Madison, WI 53711.
Molecular Biology of the Cell
|March 22, 2023
Summary
This study links human induced pluripotent stem cell (hiPSC) morphology to gene expression, enabling prediction of gene levels from cell images. This offers a practical way to monitor hiPSC purification within specific batches.
Area of Science:
- Stem cell biology
- Bioinformatics
- Cellular imaging
Background:
- Purification of human induced pluripotent stem cells (hiPSCs) is crucial for differentiation into specific cell types.
- Current purification relies on gene expression or morphology, but their relationship is not well understood.
Purpose of the Study:
- To investigate the correlation between hiPSC morphology and gene expression levels.
- To develop a predictive model linking cell morphology to gene expression for purification monitoring.
Main Methods:
- Analysis of live-cell phase-contrast images and mRNA profiles during hiPSC purification.
- Application of unsupervised image feature extraction to build a predictive model.
- Validation of the model using cancer gene expression from tissue images.
Main Results:
- A model was developed to predict gene expression levels from hiPSC morphology.
- Two specific genes were identified as well-predicted by cell morphology in hiPSCs.
- Prediction accuracy was robust within reprogramming batches but affected by batch/donor effects.
Conclusions:
- Cell morphology can serve as a proxy for estimating gene expression levels in hiPSCs.
- The developed model provides a practical method for monitoring hiPSC purification within batches.
- Further research is needed to overcome batch effects for broader applicability.
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