Spatially Isolated Two-Working-Electrode Cellular Electrochemical Platform for Synchronous Determination of Adenine...

The simultaneous quantification of multiple analytes in complex biological matrices represents a critical bottleneck for deciphering metabolic reprogramming in translational research. In this paper, a two-working-electrode cellular electrochemical platform (TWECP) was developed for the simultaneous determination of adenine (A) and hypoxanthine (H). The platform integrates two spatially isolated functional electrodes: A-functional electrodes (A-FE) and H-functional electrodes (H-FE). These electrodes were fabricated by coating molecularly imprinted polymer-grafted multi-walled carbon nanotubes (MWCNTs@A-MIPs and MWCNTs@H-MIPs) onto glassy carbon electrodes and were connected to independent signal transduction channels. The A or H template-to-functional monomer ratio was optimized to 1:3, maximizing selectivity via hydrogen bonding interactions. TWECP achieved complete DPV peak height signal isolation for A (E_p,A = 1.03 V vs Ag/AgCl) and H (E_p,H = 1.068 V vs Ag/AgCl) within physiological concentration ranges (A: 0.4-30 μM; H: 1-30 μM) (DPV peak potentials were measured with 10 mV accuracy), with detection limits of 0.26 μM (A) and 0.20 μM (H) (S/N = 3). The platform exhibited negligible crosstalk and recoveries of 95.83-104.17% for cellular A and H detection. Strong linear correlations were established between intracellular A and H signals and MCF-7 cell densities (1.0-8.5 × 10⁶ cells mL^-1). Crucially, TWECP detected metabolic shifts indicative of entry into the log phase 48 h earlier than traditional cell counting. Synchronous A and H dynamics revealed distinct purine metabolic reprogramming, from which it was inferred that cell entry into the decline phase was suggested to be driven by external factors rather than apoptosis. This study establishes a crosstalk-free method for multiplex metabolite monitoring, and this high-temporal-resolution decoding of purine flux provides mechanistic insights into cancer metabolic adaptation.