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

Taro Watanabe^1,2, Yuki Kimura¹, Daisuke Umeno¹

¹Department of Applied Chemistry, Faculty of Science and Engineering, Waseda University, 3-4-1 Ohkubo, Shinjuku-ku, Tokyo 169-8555, Japan.

ACS Synthetic Biology

|January 29, 2024

Summary

This summary is machine-generated.

Researchers developed novel S-adenosylmethionine (SAM) sensors to identify metabolic engineering mutants. This system enhances the detection of high-value compounds by overcoming biological production bottlenecks.

Keywords:

MetJ S-adenosylmethionine biosensor methylation transcriptional interference

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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.