OptSSeq explores enzyme expression and function landscapes to maximize isobutanol production rate

Area of Science:

• Metabolic Engineering
• Synthetic Biology
• Biofuel Production

Background:

• Microbial production of isobutanol (IBA), a next-generation biofuel, faces limitations due to metabolic bottlenecks.
• Determining optimal enzyme ratios within the IBA biosynthetic pathway is crucial for efficient flux and high yields.

Purpose of the Study:

• To identify optimal enzyme expression levels and ratios for maximizing isobutanol production in Escherichia coli.
• To overcome metabolic bottlenecks in the isobutanol biosynthetic pathway using a novel selection and sequencing approach.

Main Methods:

• The OptSSeq (Optimization by Selection and Sequencing) method was employed to screen a combinatorial library for optimal gene expression elements.
• Growth rate-linked selection was used to identify expression elements that enhance flux through the five-step IBA pathway.
• Enzyme levels were optimized for Acetolactate synthase (AlsS), Keto-acid reductoisomerase (KARI), Di-hydroxy acid dehydratase (DHAD), Ketoisovalerate decarboxylase (Kivd), and Alcohol dehydrogenase (Adh).

Main Results:

• Keto-acid reductoisomerase (KARI) was identified as the primary rate-limiting enzyme, requiring the highest expression levels.
• Optimal enzyme ratios were determined, with KARI, AlsS, and AdhA needing higher expression than DHAD and Kivd.
• Optimized constructs achieved high isobutanol titers (~3 g/L/h) with 20% of cellular protein dedicated to pathway enzymes, and identified an improved Adh variant.

Conclusions:

• The OptSSeq method effectively identifies optimal enzyme ratios for maximizing biofuel production in microbial systems.
• The determined enzyme levels and ratios provide a foundation for optimizing isobutanol production in various microbial hosts and fermentation conditions.
• Further limitations in the host metabolic network were identified, suggesting avenues for future metabolic engineering efforts.