Automating the design-build-test-learn cycle towards next-generation bacterial cell factories

Area of Science:

• Synthetic Biology
• Metabolic Engineering
• Automation

Background:

• Automation is increasingly vital in synthetic biology, significantly speeding up microbial cell factory development over the last two decades.
• Integrating advanced tools like genome engineering and analytical techniques into the design-build-test-learn cycle (DBTLc) is transforming metabolic engineering from artisanal work to automated workflows.

Purpose of the Study:

• To provide a perspective on utilizing a fully automated DBTLc for constructing next-generation bacterial cell factories.
• To review innovative toolsets and approaches that advance each stage of the automated DBTLc.
• To highlight recent automation efforts paving the way for autonomous synthetic biology pipelines.

Main Methods:

• Review of groundbreaking technologies in genome engineering and analytical techniques.
• Analysis of innovative toolsets and approaches within each segment of the DBTLc.
• Examination of recent advancements in the automation of the DBTLc.

Main Results:

• The integration of advanced tools into the DBTLc is shifting metabolic engineering towards automated workflows.
• Innovative toolsets and approaches have pushed the boundaries in each segment of the DBTLc.
• Recent automation efforts indicate a future with fully autonomous pipelines for synthetic biology.

Conclusions:

• A fully automated DBTLc can enable the fast, high-throughput construction of next-generation bacterial cell factories.
• The ongoing automation of the DBTLc heralds a fully autonomous pipeline for synthetic biology.
• This approach represents a significant paradigm shift in metabolic engineering and synthetic biology development.