Retropath: automated pipeline for embedded metabolic circuits

Area of Science:

• Synthetic Biology
• Metabolic Engineering
• Computational Biology

Background:

• Metabolic circuits are key components in synthetic biology, offering modular functionalities.
• Current metabolic circuit design primarily focuses on production, limiting applications in sensing and regulation.
• Emerging applications like smart therapeutics necessitate advanced metabolic circuits capable of sensing and regulation.

Purpose of the Study:

• To present RetroPath, an automated pipeline for designing embedded metabolic circuits.
• To explore the design space of metabolic circuits for synthetic biology applications.
• To enable the development of circuits for sensing, regulation, and autonomous therapeutic functions.

Main Methods:

• Developed RetroPath, an automated computational pipeline.
• Explored the metabolic circuit design space based on user-defined specifications and constraints.
• Enumerated synthetic biology circuits within a chassis organism for molecule control.

Main Results:

• RetroPath efficiently identifies and selects optimal metabolic circuits from a vast design space.
• The pipeline facilitates the design of circuits for complex functions including sensing and regulation.
• Demonstrated the capability to design circuits for autonomous disease diagnosis and treatment.

Conclusions:

• RetroPath streamlines the design and implementation of advanced metabolic circuits.
• The automated pipeline supports the optimization of synthetic biology applications, particularly in therapeutics.
• Enables the creation of sophisticated circuits for sensing, processing, and releasing molecules within chassis organisms.