Integrated Tn-seq and MAGE-assisted rapid genome engineering targeting in Escherichia coli

Area of Science:

• Metabolic Engineering
• Synthetic Biology
• Microbial Strain Improvement

Background:

• Economic viability of bio-based chemical production relies on efficient microbial strains.
• Identifying effective genetic engineering targets is complex due to intricate metabolic networks and gene interactions.

Purpose of the Study:

• To develop an integrated approach (iTARGET) for identifying novel and synergistic genetic targets.
• To overcome challenges in predicting genetic targets through rational design.
• To enhance bio-based chemical production by improving microbial strains.

Main Methods:

• iTARGET integrates in situ transposon mutagenesis, biosensor-guided selection, and multiplex automated genome engineering (MAGE).
• Phase 1: Transposon mutagenesis and sequencing (Tn-seq) for genetic diversity and target identification.
• Phase 2: MAGE for combinatorial knockout (KO) libraries and high-throughput screening for synergistic interactions.

Main Results:

• Application to naringenin (NRN) production yielded a 1.7-fold population-level titer increase.
• Nine unpredictable genetic targets were identified, leading to a 2.3-fold titer increase with single KOs.
• Combinatorial KOs revealed synergistic effects, with a double-KO mutant showing a 2.8-fold improvement.

Conclusions:

• iTARGET accelerates the discovery of challenging genetic targets for microbial strain engineering.
• The approach enables high-throughput identification of synergistic gene interactions.
• iTARGET significantly enhances bio-based chemical production efficiency.