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Updated: May 11, 2026

Real Time Monitoring of Intracellular Bile Acid Dynamics Using a Genetically Encoded FRET-based Bile Acid Sensor
Published on: January 4, 2016
Real-Time Monitoring of Microbial Metabolic Dynamics through a Carbon Dot-Functionalized Whole-Cell Electrochemical
Jiaqi Wu1, Tianchong Li1, Bowen Yu1
1State Key Laboratory of Woody Oil Resources Utilization, Northeast Forestry University, Harbin 150040, China.
None:
Metabolic regulation─the dynamic biochemical network governing energy transduction, substrate conversion, and metabolic flux─represents a fundamental determinant of microbial viability and functional output. While temporal metabolite fluctuations provide critical insights into metabolic network dynamics, conventional analytical platforms face fundamental limitations in real-time monitoring within native microbial environments. This study presents a novel whole-cell electrochemical biosensing platform integrating carbon dot (CD)-engineered Escherichia coli (E. coli) with advanced cyclic voltammetry (CV) for dynamic metabolic interrogation. This biohybrid system synergizes microbial biochemical specificity with CD-enhanced electron transfer efficiency, achieving nearly a 20-fold amplification in the electrochemical signal amplitude through quantum-enhanced charge transport mechanisms. The platform enables precise quantification of redox-active metabolites via distinct voltammetric fingerprints, as demonstrated through the detection of lactic acid─a pivotal biomarker in industrial biotechnology and clinical diagnostics. Featuring a modular bioarchitectural design, this technology permits seamless adaptation across diverse microbial systems, offering unprecedented capabilities for real-time bioprocess optimization, dynamic metabolic pathway analysis, and pathogen metabolic profiling. By interfacing nanomaterial-enhanced electrochemistry with synthetic biology, our platform surmounts traditional analytical constraints, establishing a versatile analytical tool for spatiotemporal mapping of metabolic networks in complex biological matrices.

