Transcription Factor-Based Biosensors in High-Throughput Screening: Advances and Applications

Area of Science:

• Synthetic biology
• Molecular biology
• Biotechnology

Background:

• Cells utilize molecular mechanisms to sense environmental changes, informing synthetic biology applications.
• While RNA-mediated sensing exists in nature, most genetic biosensors rely on transcription factors (TF) and DNA.
• TF-based biosensors are increasingly integrated into engineering workflows.

Purpose of the Study:

• To review recent advances in TF-based biosensors for metabolic and protein engineering.
• To differentiate between production-driven and competitive screening systems for enzyme evolution.
• To analyze the strengths and weaknesses of current TF-based biosensors.

Main Methods:

• Review of literature on TF-based biosensors in engineering screens.
• Analysis of TF biosensor performance metrics (dynamic range, sensitivity, robustness).
• Comparison of TF-based screening with alternative approaches.

Main Results:

• TF-based biosensors are effectively integrated into production-driven and competitive screening systems.
• TF biosensors show potential for enzyme evolution under physiological conditions.
• Advantages and disadvantages of TF biosensors vary regarding dynamic range, sensitivity, and robustness.

Conclusions:

• TF-based biosensors demonstrate significant promise as screening tools in laboratory evolution.
• These biosensors are valuable for both protein engineering and metabolic pathway optimization.
• Further development can enhance their utility in synthetic biology.