Transcription factor sensor system for parallel quantification of metabolites on-chip

Area of Science:

• Synthetic biology
• Analytical chemistry
• Biotechnology

Background:

• Increasing demand for high-throughput cellular metabolite identification and quantification.
• Need for novel analytical technologies to meet these demands.
• Exploitation of bacterial transcription factors for metabolite sensing.

Purpose of the Study:

• To develop a synthetic biological sensor system for quantifying cellular metabolites.
• To integrate this system onto a microfluidic large-scale integration (mLSI) chip for high-throughput analysis.
• To demonstrate the system's functionality by measuring diurnal metabolite changes.

Main Methods:

• Functionalization of bacterial repressor proteins (PdhR, TreR, ArgR) to detect specific metabolites (pyruvate, trehalose-6-phosphate, arginine).
• Determination of metabolite-DNA binding behavior, working ranges, and orthogonality for each transcription factor.
• Integration of the sensor system onto an mLSI chip for parallel processing and automation.

Main Results:

• Successful development of a synthetic biological sensor system for metabolite quantification.
• Demonstration of high-throughput, parallel processing, and automation capabilities via mLSI chip integration.
• Measurement of diurnal concentration changes of pyruvate and trehalose-6-phosphate in Arabidopsis thaliana cell extracts.

Conclusions:

• The developed transcription factor-based sensor system provides a generic and extendable platform for cellular metabolite quantification.
• Integration with mLSI technology enables high-throughput, automated analysis of biological samples.
• This approach offers a powerful tool for advancing metabolic research and diagnostics.