Two highly specific growth-coupled biosensor for glycolaldehyde detection across micromolar and millimolar...

Area of Science:

• Biotechnology
• Metabolic Engineering
• Synthetic Biology

Background:

• Glycolaldehyde (GA) is a small sugar with potential as a biomass-derived platform chemical.
• GA is a key metabolite in one-carbon metabolism and novel photorespiration pathways.

Purpose of the Study:

• To engineer Escherichia coli into sensitive biosensors for glycolaldehyde (GA).
• To enable quantification of both externally supplied and intracellularly produced GA.
• To demonstrate novel applications in metabolic engineering and synthetic biology.

Main Methods:

• Engineered *E. coli* using two metabolic schemes to create GA-dependent auxotrophies.
• Linked microbial growth to GA-dependent biosynthesis of essential compounds (pyridoxal-5-phosphate, 2-ketoglutarate).
• Characterized and optimized biosensor strains for GA quantification (2 µM to 1.5 mM) and intracellular detection.

Main Results:

• Developed two distinct *E. coli* biosensor strains for glycolaldehyde detection.
• Demonstrated successful quantification of external GA and intracellular GA from various substrates (xylose, ethylene glycol, glycolate).
• Achieved the first *in vivo* demonstration of glycolate reduction to GA via a novel engineered enzymatic pathway.

Conclusions:

• Engineered *E. coli* biosensors provide sensitive and versatile tools for GA detection.
• These biosensors facilitate metabolic engineering and synthetic biology applications, including monitoring novel metabolic routes.
• The study highlights the potential of GA as a platform chemical and the utility of engineered biosensors in its study.