Integrated multi-dimensional modeling of non-model bacteria identifies engineering targets for acarbose biosynthesis...

Area of Science:

• Microbiology
• Metabolic Engineering
• Systems Biology

Background:

• Acarbose, a vital diabetes drug, production relies on understanding complex metabolic regulation in Actinoplanes sp. SE50/110.
• Engineering non-model microorganisms for high-value compound synthesis presents significant challenges due to limited biological data.

Purpose of the Study:

• To develop a systems biology framework for enhancing acarbose production in the non-model bacterium Actinoplanes sp. SE50/110.
• To identify and validate static and dynamic metabolic engineering targets and regulatory elements governing acarbose biosynthesis.

Main Methods:

• Reconstruction and validation of an improved genome-scale metabolic model (iASE1267) with high metabolic coverage.
• Application of a dual-objective OptRAM strain design strategy and time-course metabolic modeling.
• Integration of metabolic models with transcriptional networks to identify key transcription factors (TFs).

Main Results:

• An improved metabolic model (iASE1267) with an 80% MEMOTE score was developed, enhancing phenotype prediction accuracy.
• Static engineering targets (e.g., AcbR overexpression, specific gene repression) and dynamic metabolic valves (ASPO1, PC, PYK) were identified.
• Experimental validation confirmed that targeting identified TFs and metabolic genes increased acarbose titers by 18-23%.

Conclusions:

• A comprehensive systems biology framework integrating static and dynamic metabolic modeling with transcriptional networks was established for non-model microbe engineering.
• The study successfully identified novel targets and TFs, significantly improving acarbose production.
• This approach provides a robust strategy for optimizing the biosynthesis of high-value compounds in industrial microorganisms.