MetJ-Based Mutually Interfering SAM-ON/SAM-OFF Biosensors.

Area of Science:

• Metabolic Engineering
• Synthetic Biology
• Biotechnology

Background:

• S-adenosylmethionine (SAM) is a crucial metabolite for methylation and a bottleneck in producing valuable compounds.
• Existing methods struggle to identify mutants that enhance SAM-dependent metabolic pathways due to strong cellular homeostasis.

Purpose of the Study:

• To engineer novel SAM-sensing systems for improved mutant screening.
• To develop a robust method for identifying SAM synthetase (MetK) mutants with enhanced activity.

Main Methods:

• Constructed SAM-OFF and SAM-ON sensors utilizing MetJ, an SAM-dependent transcriptional regulator.
• Employed transcriptional interference and evolutionary tuning to create the SAM-ON sensor.
• Linked interfering fluorescent protein reporter genes to enhance signal-to-noise ratio and reduce variability.

Main Results:

• Developed a SAM-ON sensor that responds to increasing SAM concentrations.
• Achieved higher signal-to-noise ratios and reduced batch-to-batch deviations in sensor output.
• Successfully identified MetK mutants with increased SAM synthetase activity from a random library.

Conclusions:

• The engineered SAM-sensing systems provide a powerful tool for identifying metabolic engineering mutants.
• This strategy is broadly applicable for discovering mutants that enhance metabolite production, overcoming limitations of metabolic homeostasis.