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Phenotyping senescent mesenchymal stromal cells using AI image translation.
Leya Weber1, Brandon S Lee2, Sara Imboden1
1Department of Mechanical and Aerospace Engineering, University of California, Los Angeles 90095, CA, United States.
Current Research in Biotechnology
|December 4, 2023
Summary
Artificial intelligence accurately predicts mesenchymal stromal cell (MSC) senescence from standard images, enabling consistent cell therapies. This AI tool helps ensure the quality and efficacy of MSCs for clinical applications.
Area of Science:
- Biotechnology
- Cell Biology
- Artificial Intelligence
Background:
- Mesenchymal stromal cells (MSCs) are crucial for regenerative medicine and immunotherapy.
- MSC therapies face challenges due to cell heterogeneity and senescence, impacting therapeutic consistency.
- Accurate characterization of MSCs is vital for reliable clinical applications.
Purpose of the Study:
- To develop an AI-driven method for noninvasively assessing MSC senescence.
- To predict MSC senescence markers from phase contrast microscopy images using AI.
- To ensure the quality and consistency of MSCs for therapeutic use.
Main Methods:
- Utilized AI image translation algorithms to predict immunofluorescence images of MSC senescence markers.
- Trained deep-learning models on phase contrast images to predict senescence markers (SABG, p16, p21, p38).
- Validated the AI model on Doxorubicin-induced, irradiation-induced, and replicative MSC senescence models.
Main Results:
- AI models accurately predicted the expression levels of key MSC senescence markers.
- The AI platform successfully distinguished between senescent and non-senescent MSC populations.
- The model captured cell-to-cell variability within MSC populations, reflecting heterogeneity.
Conclusions:
- AI image translation offers a powerful, noninvasive tool for characterizing MSC senescence.
- This approach can enhance MSC engineering and manufacturing by ensuring cell consistency.
- The developed platform facilitates accessible quality control for MSC-based therapies.
