Stochastic modeling and simulation of reaction-diffusion system with Hill function dynamics

Introducing Parameter Clustering to the OED Procedure for Model Calibration of a Synthetic Inducible Promoter in S. cerevisiae

In recent years, synthetic gene circuits for adding new cell features have become one of the most powerful tools in biological and pharmaceutical research and development. However, because of the inherent non-linearity and noisy experimental data, the experiment-based model calibration of these synthetic parts is perceived as a laborious and time-consuming procedure. Although the optimal experimental design (OED) based on the Fisher information matrix (FIM) has been proved to be an effective means to improve the calibration efficiency, the required calculation increases dramatically with the model size (parameter number). To reduce the OED complexity without losing the calibration accuracy, this paper proposes two OED approaches with different parameter clustering methods and validates the accuracy of calibrated models with in-silico experiments. A model of an inducible synthetic promoter in S. cerevisiae is adopted for bench-marking. The comparison with the traditional off-line OED approach suggests that the OED approaches with both of the clustering methods significantly reduce the complexity of OED problems (for at least 49.0%), while slightly improving the calibration accuracy (11.8% and 19.6% lower estimation error in average for FIM-based and sensitivity-based approaches). This study implicates that for calibrating non-linear models of biological pathways, cluster-based OED could be a beneficial approach to improve the efficiency of optimal experimental design.

Nanozyme-Modified Metal-Organic Frameworks with Multienzymes Activity as Biomimetic Catalysts and Electrocatalytic Interfaces

Many metal-organic frameworks have been designed and synthesized for biosensors because of high surface area and porosity, suitable size, and good biocompatibility. Despite recent advances, however, most of them are only used as a nanocarrier. In this work, a new artificial nanozyme was constructed on a metalloporphyrinic metal-organic framework (PMOF(Fe)), which was formed by Fe porphyrin and Zr⁴⁺ ions. Then, ultrasmall Pt nanoparticles (Pt NPs) were loaded on the surface of PMOF(Fe) to form Pt@PMOF(Fe). Because of the high surface area and exposed Fe activity center, PMOF(Fe) works as a nanocarrier to hinder the Pt NP aggregation and exhibits high peroxidase-mimicking activity. Hence, Pt NPs decorated on the surface of PMOF(Fe) possessed high stability and exhibited high activity. Due to the synergistic effect between PMOF(Fe) and Pt NPs, Pt@PMOF(Fe) exhibits superior catalase- and peroxidase-like activities. Moreover, Pt@PMOF(Fe) possesses high electrocatalytic activity toward the reduction of H₂O₂ and the oxygen reduction reaction (ORR). This strategy may serve as a strong foundation to design MOF-based artificial nanozymes and develop an ideal platform for MOFs and nanozymes toward artificial enzymatic catalytic systems, fuel cells and new analytical applications.