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Aurore Dupin¹, Lukas Aufinger¹, Igor Styazhkin¹

¹Physics Department (E14), TU Munich, 85748 Garching, Germany.

Science Advances

|April 8, 2022

Summary

This summary is machine-generated.

Synthetic cells can determine their position using morphogen gradients, mimicking biological development. Gene expression noise and gradient dynamics limit this positional information (PI) in synthetic multicellular systems.

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Area of Science:

Synthetic biology
Biomaterials engineering
Developmental biology

Background:

Biological systems utilize morphogen gradients for positional information (PI) during development.
Synthetic cells offer a platform to engineer adaptive and differentiating biomaterials.
Understanding PI in synthetic systems is crucial for creating functional artificial tissues.

Purpose of the Study:

To investigate the ability of synthetic cells to determine their position within multicellular assemblies.
To analyze the factors limiting positional information acquisition in synthetic cellular systems.
To demonstrate controlled differentiation in larger, tissue-like structures using synthetic cells.

Main Methods:

Constructed synthetic cellular assemblies using emulsion droplets with cell-free gene circuits.
Exposed assemblies to genetic inducer gradients to mimic morphogen signaling.
Employed computational modeling to rationalize PI generation and analyze limiting factors.
Utilized 3D printing to scale the system for larger, tissue-like constructs.

Main Results:

Positional information (PI) in synthetic cells is quantifiable and influenced by gene expression noise.
Temporal dynamics of morphogen gradients and cell-free expression systems impact PI accuracy.
Computational models successfully rationalized PI generation within the synthetic system.
Demonstrated morphogen-guided differentiation in larger, 3D-printed tissue-like assemblies.

Conclusions:

Synthetic cells can acquire positional information from morphogen gradients, albeit with limitations.
Gene expression noise and gradient dynamics are key factors affecting PI in synthetic systems.
This work provides a framework for engineering complex behaviors in synthetic multicellular biomaterials.