Towards an Aspect-Oriented Design and Modelling Framework for Synthetic Biology.

Area of Science:

• Synthetic Biology
• Computational Biology
• Software Engineering

Background:

• Traditional synthetic biology relies on a component-based approach.
• Incorporating contextual design issues (compositional, host, environmental) is crucial for complex applications.

Purpose of the Study:

• To present a novel design framework for synthetic biology using aspect-oriented software engineering concepts.
• To move beyond a purely parts-based paradigm by introducing the concept of 'concerns' for system synthesis.

Main Methods:

• Utilized aspect-oriented software engineering concepts to separate core design concerns from cross-cutting concerns.
• Developed the Python tool SynBioWeaver to implement this framework, enabling the 'weaving' of concerns.
• Demonstrated the framework's application through examples including part context and context-dependent circuit design.

Main Results:

• The framework successfully separates modular design aims (core concerns) from system-wide attributes (cross-cutting concerns).
• Explicit handling of cross-cutting concerns allows for modular integration of contextual information.
• SynBioWeaver generated rule, logic, and reaction models from synthetic circuit designs.

Conclusions:

• The aspect-oriented approach offers a powerful and biologically credible method for synthetic biology system synthesis.
• This framework enhances the modularity and flexibility of designing complex biological systems by managing contextual information.
• The SynBioWeaver tool provides a practical implementation for combining core and cross-cutting concerns in synthetic biology design.