A closed-loop catalytic nanoreactor system on a transistor

Abstract

Precision chemistry demands miniaturized catalytic systems for sophisticated reactions with well-defined pathways. An ideal solution is to construct a nanoreactor system functioning as a chemistry laboratory to execute a full chemical process with molecular precision. However, existing nanoscale catalytic systems fail to in situ control reaction kinetics in a closed-loop manner, lacking the precision toward ultimate reaction efficiency. We find an inter-electrochemical gating effect when operating DNA framework-constructed enzyme cascade nanoreactors on a transistor, enabling in situ closed-loop reaction monitoring and modulation electrically. Therefore, a comprehensive system is developed, encapsulating nanoreactors, analyzers, and modulators, where the gate potential modulates enzyme activity and switches cascade reaction "ON" or "OFF." Such electric field-effect property enhances catalytic efficiency of enzyme by 343.4-fold and enables sensitive sarcosine assay for prostate cancer diagnoses, with a limit of detection five orders of magnitude lower than methodologies in clinical laboratory. By coupling with solid-state electronics, this work provides a perspective to construct intelligent nano-systems for precision chemistry.

Fig. 1.. Closed-loop catalytic nanoreactor system on a transistor.

(A) Closed-loop reaction control architecture of cascade reaction system in the laboratory. (B) Working principle of the closed-loop nanoreactor system on a g-FET. (C) Photograph of the packaged nanoreactor system (scale bar, 1 cm). (D) Optical microscope image of the graphene channel (scale bar, 100 μm). (E) AFM image (in 1× TM buffer) of TDD structures (scale bar, 100 nm).

Fig. 2.. Real-time reaction monitoring.

(A) Real-time |∆I_ds/I_ds,0| of the nanoreactor system upon consecutive addition of sarcosine solutions (blue) and control molecules (red). (B) |∆I_ds/I_ds,0| response comparison upon the addition of target analytes (2.5 × 10⁻¹⁷ M) and non-target (5 × 10⁻¹³ M) analytes. (C) |∆I_ds/I_ds,0| response comparison between the nanoreactor system and g-FET with randomly functionalized enzymes upon sarcosine. (D) Inter-enzyme distance histogram for random enzyme functionalization on graphene and Gaussian fit. Inset: AFM image of enzyme-modified graphene surface. Scale bar, 50 nm. (E) Simulated radial density of intermediate, defined as the molecule number in an area of 1 nm², with respect to diffusion radius. Inset: scattering chart of intermediate distribution. (F) |∆I_ds/I_ds,0| response of TDD and TDT-based nanoreactor system as a function of sarcosine concentration. Error bars in (B), (C), (E), and (F) are obtained from the SD of three repeated measurements.

Fig. 3.. Electrified modulation of reaction.

(A) Real-time |∆I_ds/I_ds,0| and (B) |∆I_ds/I_ds,0| responses of the nanoreactor system upon consecutive addition of sarcosine at V_g = 0 V, V_g = 0.3 V, and V_g = −0.3 V. (C) Electric-field effect |∆I_ds/I_ds,0| response of the nanoreactor system upon sarcosine. (D) Lineweaver-Burk plots for enzymes on graphene at V_g = 0 V, enzymes on graphene at V_g = 0.3 V, free enzymes in solution at V_g = 0 V, and free enzymes in solution at V_g = 0.3 V. (E) Mechanism illustration of electrified modulation of enzyme activity. (F) Ultraviolet-visible absorbance spectra of HRP-coupled colorimetric assay at different pH. Inset: enzyme activity with respect to increased pH from 4.2 to 9.5. Error bars in (B), (C), and (F) are obtained from the SD of three repeated measurements.

Fig. 4.. Application in sarcosine testing.

(A) Workflow of PCa-relevant sarcosine testing by the portable nanoreactor system. (B) Representative real-time |ΔI_ds/I_ds,0| response upon sequential addition of BPH and PCa samples at V_g = 0.3 V and V_g = −0.3 V. (C) |ΔI_ds/I_ds,0| response upon clinical PCa and BPH samples. Inset: photomicrographs of the biopsy slides of PCa and BPH patients. The green dashed line indicates the cutoff value in the diagnoses. (D) PSA concentrations of clinical PCa and BPH samples. Statistical analysis between PCa and BPH samples by sarcosine (E) and PSA (F) testing, determined by one-way ANOVA followed by a t test (^aP: P value > 0.05, ***P < 0.001). (G) |ΔI_ds/I_ds,0| response to the P9 sample with serial dilution. (H) LoD comparison of sarcosine testing between the nanoreactor system and other reported mythologies including commercial kits. Detailed information is provided in table S6.