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zIncubascope: Long-term quantitative imaging of multi-cellular assemblies inside an incubator
Anirban Jana1,2,3, Naveen Mekhileri1,2, Adeline Boyreau1,2
1LP2N, Laboratoire Photonique Numérique et Nanosciences, University Bordeaux, Talence, France.
Plos One
|January 23, 2025
Summary
We developed an incubator-friendly imaging platform for high-throughput monitoring of cell growth and organoid morphogenesis. This system provides quantitative insights into how confinement impacts self-organized biological systems.
Area of Science:
- Bioengineering
- Developmental Biology
- Cell Biology
Background:
- Bioengineering enables complex in vitro systems to mimic organ functions.
- Monitoring multicellular aggregates like organoids is vital for understanding morphogenesis but challenging.
- Quantitative data extraction from developing tissues is crucial for biological insight.
Purpose of the Study:
- To present an incubator-compatible imaging platform for high-throughput, long-term monitoring of cell assemblies.
- To enable quantitative analysis of self-organized biological systems under confinement.
- To investigate the impact of confinement on morphogenesis in various cell types.
Main Methods:
- Development of an incubator-integrated imaging platform for continuous monitoring.
- High-throughput tracking of cell assemblies over extended periods (days to weeks).
- Application of a customized image analysis pipeline for quantitative data extraction.
Main Results:
- Demonstrated system capabilities using human induced pluripotent stem cells (hiPSCs) in spherical and tubular capsules.
- Successfully monitored yeast cells in spherical capsules.
- Obtained quantitative insights into the effects of confinement on cellular self-organization and morphogenesis.
Conclusions:
- The developed imaging platform facilitates high-throughput, in situ monitoring of biological self-organization.
- The system provides valuable data for deciphering morphogenetic mechanisms under confinement.
- This technology aids in understanding how physical constraints influence the development of engineered biological systems.

