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Bacterial growth is closely tied to nutrient availability, with cells proliferating exponentially under favorable conditions and entering a stationary phase when resources become scarce. This transition is mediated by a regulatory mechanism known as the stringent response, which allows bacteria to adapt to nutrient deprivation by modulating gene expression and metabolic activity.During nutrient scarcity, intracellular amino acid levels decline. It results in the accumulation of uncharged tRNAs...
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Engineering Programmable Tryptophan-Responsive Biosensors Based on RNA-Binding Attenuation Protein for Strain

Xianhao Xu1,2, Keyi Zou1,2, Weihao Qian1,2

  • 1Key Laboratory of Carbohydrate Chemistry and Biotechnology, Ministry of Education, Jiangnan University, Wuxi 214122, China.

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|January 13, 2026
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Summary
This summary is machine-generated.

Researchers developed novel tryptophan biosensors in E. coli using the TRAP system, improving dynamic range and response thresholds for enhanced strain engineering and metabolic network regulation.

Keywords:
Escherichia coliTRAPbiosensorhigh-throughput screeningmolecular dynamics simulationstryptophan

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Area of Science:

  • Microbiology
  • Synthetic Biology
  • Biotechnology

Background:

  • Biosensors are crucial for high-throughput strain screening and metabolic network regulation.
  • Current tryptophan sensors have limitations in dynamic range and response threshold.

Purpose of the Study:

  • To develop novel tryptophan-responsive biosensors in Escherichia coli using the TRAP system.
  • To engineer and optimize these biosensors for improved performance.
  • To utilize the biosensors for screening enzyme variants and studying metabolic pathways.

Main Methods:

  • Engineered tryptophan-activated RNA-binding attenuation protein (TRAP) based biosensors in E. coli.
  • Fine-tuned TRAP expression and optimized TRAP-leader sequence interactions.
  • Screened TRAP variants and beneficial enzyme variants in the tryptophan biosynthetic pathway.
  • Employed molecular dynamics simulations to investigate enzyme catalytic mechanisms.

Main Results:

  • Developed two novel tryptophan biosensors with distinct dynamic ranges (up to 22.1-fold).
  • Achieved response thresholds as low as 0-2.2 g/L.
  • Successfully screened beneficial variants of rate-limiting enzymes in tryptophan biosynthesis.
  • Provided insights into enzyme catalytic mechanisms via molecular dynamics simulations.

Conclusions:

  • The developed TRAP-based biosensors offer improved tools for engineering high tryptophan-producing strains.
  • This study presents new strategies for designing robust and sensitive biosensors.
  • The findings contribute to advancements in metabolic engineering and synthetic biology.