Mapping and exploring the organoid state space using synthetic biology

Area of Science:

• Biotechnology
• Developmental Biology
• Cell Biology

Background:

• Organoid functional relevance is determined by differentiation, morphology, cell arrangement, and biophysical properties.
• Organoids may explore a broader state space than in vivo organs due to altered niche signaling and boundary conditions.
• Characterizing organoid states is crucial for understanding their biological relevance and potential applications.

Purpose of the Study:

• To develop a framework for characterizing and comparing organoid states to their in vivo counterparts.
• To investigate the expanded state space explored by organoids in vitro.
• To establish methods for controlling organoid states through data-driven inference and modeling.

Main Methods:

• Transcriptomics and high-content image analysis were used to characterize organoid state variables.
• Data-driven state inference and in silico modeling were employed to analyze organoid states.
• Phase diagrams were constructed to systematically sort organoids along biochemical or biophysical axes.

Main Results:

• Organoid states can be quantitatively characterized using transcriptomics and image analysis.
• Organoids exhibit a wider range of states in vitro compared to in vivo organs.
• Phase diagrams provide a tool for visualizing and understanding organoid state variability.

Conclusions:

• Phase diagrams enable the identification of control strategies to modulate organoid state.
• Manipulation of the biochemical and biophysical environment, as well as seeding cells, can guide organoid development.
• This approach facilitates the optimization of organoid cultures for research and therapeutic applications.