Horseradish peroxidase (HRP) and glucose oxidase (GOX) based dual-enzyme system: Sustainable release of H2O2 and its effect on the desirable ping pong bibi degradation mechanism

Controllable ion design in flexible metal organic framework film for performance regulation of electrochemical biosensing

The limitations of solvent residues, unmanageable film growth regions, and substandard performance impede the extensive utilization of metal-organic framework (MOF) films for biosensing devices. Here, we report a strategy for ion design in gas-phase synthesized flexible MOF porous film to attain universal regulation of biosensing performances. The key fabrication process involves atomic layer deposition of induced layer coupled with lithography-assisted patterning and area-selective gas-phase synthesis of MOF film within a chemical vapor deposition system. Sensing platforms are subsequently formed to achieve specific detection of H2O2, dopamine, and glucose molecules by respectively implanting Co, Fe, and Ni ions into the network structure of MOF films. Furthermore, we showcase a practical device constructed from Co ions-implanted ZIF-4 film to accomplish real-time surveillance of H2O2 concentration at mouse wound. This study specifically elucidates the electronic structure and coordination mode of ion design in MOF film, and the obtained knowledge aids in tuning the electrochemical property of MOF film for advantageous sensing devices.

Understanding atrazine elimination via treatment of the enzyme-based Fenton reaction: Kinetics, mechanism, reaction pathway, and metabolites toxicity

The degradation kinetics and mechanism of atrazine (ATZ) via an enzyme-based Fenton reaction were investigated at various substrate concentrations and pH values. Toxicological assessment was conducted on ATZ and its degradation products, and the associated reaction pathway was examined. The in situ production of hydrogen peroxide (H2O2) was monitored within the range of 3-15 mM, depending on the increase in glucose concentration, while decreasing the pH to 3.2-5.1 (initial pH of 5.8) or 6.5-7.4 (initial pH of 7.7). The degradation efficiency of ATZ was approximately 2-3 times higher at an initial pH of 5.8 with lower glucose concentrations than at an initial pH of 7.7 with higher substrate concentrations during the enzyme-based Fenton reaction. The apparent pseudo-first-order rate constant for H2O2 decomposition under various conditions in the presence of ferric citrate was 1.9-6.3 × 10-5 s-1. The •OH concentration ([•OH]ss) during the enzyme-based Fenton reaction was 0.5-4.1 × 10-14 M, and the second-order rate constant for ATZ degradation was 1.5-3.3 × 109 M-1 s-1. ATZ intrinsically hinders the growth and development of Arabidopsis thaliana, and its inhibitory effect is marginal, depending on the reaction time of the enzyme-based Fenton process. The ATZ transformation during this process occurs through dealkylation, hydroxylation, and dechlorination via •OH-mediated reactions. The degradation kinetics, mechanism, and toxicological assessment in the present study could contribute to the development and application of enzyme-based Fenton reactions for in situ pollutant abatement. Moreover, the enzyme-based Fenton reaction could be an environmentally benign and applicable approach for eliminating persistent organic matter, such as herbicides, using diverse H2O2-producing microbes and ubiquitous ferric iron with organic complexes.

Breaking boundaries: Artificial intelligence for pesticide detection and eco-friendly degradation

Pesticides are extensively used agrochemicals across the world to control pest populations. However, irrational application of pesticides leads to contamination of various components of the environment, like air, soil, water, and vegetation, all of which build up significant levels of pesticide residues. Further, these environmental contaminants fuel objectionable human toxicity and impose a greater risk to the ecosystem. Therefore, search of methodologies having potential to detect and degrade pesticides in different environmental media is currently receiving profound global attention. Beyond the conventional approaches, Artificial Intelligence (AI) coupled with machine learning and artificial neural networks are rapidly growing branches of science that enable quick data analysis and precise detection of pesticides in various environmental components. Interestingly, nanoparticle (NP)-mediated detection and degradation of pesticides could be linked to AI algorithms to achieve superior performance. NP-based sensors stand out for their operational simplicity as well as their high sensitivity and low detection limits when compared to conventional, time-consuming spectrophotometric assays. NPs coated with fluorophores or conjugated with antibody or enzyme-anchored sensors can be used through Surface-Enhanced Raman Spectrometry, fluorescence, or chemiluminescence methodologies for selective and more precise detection of pesticides. Moreover, NPs assist in the photocatalytic breakdown of various organic and inorganic pesticides. Here, AI models are ideal means to identify, classify, characterize, and even predict the data of pesticides obtained through NP sensors. The present study aims to discuss the environmental contamination and negative impacts of pesticides on the ecosystem. The article also elaborates the AI and NP-assisted approaches for detecting and degrading a wide range of pesticide residues in various environmental and agrecultural sources including fruits and vegetables. Finally, the prevailing limitations and future goals of AI-NP-assisted techniques have also been dissected.

Immobilization of Horseradish Peroxidase for Phenol Degradation

The use of enzymes to degrade environmental pollutants has received wide attention as an emerging green approach. Horseradish peroxidase (HRP) can efficiently catalyze the degradation of phenol in the environment; however, free HRP exhibits poor stability and temperature sensitivity and is easily deactivated, which limit its practical applications. In this study, to improve their thermal stability, HRP enzymes were immobilized on mesoporous molecular sieves (Al-MCM-41). Specifically, Al-MCM-41(W) and Al-MCM-41(H) were prepared by modifying the mesoporous molecular sieve Al-MCM-41 with glutaraldehyde and epichlorohydrin, respectively, and used as carriers to immobilize HRP on their surface, by covalent linkage, to form the immobilized enzymes HRP@Al-MCM-41(W) and HRP@Al-MCM-41(H). Notably, the maximum reaction rate of HRP@Al-MCM-41(H) was increased from 2.886 × 105 (free enzyme) to 5.896 × 105 U/min-1, and its half-life at 50 °C was increased from 745.17 to 1968.02 min; the thermal stability of the immobilized enzyme was also significantly improved. In addition, we elucidated the mechanism of phenol degradation by HRP, which provides a basis for the application of this enzyme to phenol degradation.

Iron-Coordinated L-Lysine-Based Nanozymes with High Peroxidase-like Activity for Sensitive Hydrogen Peroxide and Glucose Detection

It is crucial to develop sensitive and accurate sensing strategies to detect H₂O₂ and glucose in biological systems. Herein, biocompatible iron-coordinated L-lysine-based hydrogen peroxide (H₂O₂)-mimetic enzymes (Lys-Fe-NPs) were prepared by precipitation polymerization in aqueous solution. The coordinated Fe²⁺ ion acted as centers of peroxidase-like enzymes of Lys-Fe-NPs, and the catalytic activity was evaluated via the oxidation of 3,3',5,5'-tetramethylbenzidine (TMB) by H₂O₂. Therefore, a sensitive colorimetric detection sensor for H₂O₂ was constructed with a linear range of 1 to 200 μM and a detection limit of 0.51 μM. The same method could also be applied to highly sensitive and selective detection of glucose, with a linear range of 0.5 to 150 μM and a detection limit of 0.32 μM. In addition, an agarose-based hydrogel biosensor colorimetric was successfully implemented for visual assessment and quantitative detection of glucose. The design provided a novel platform for constructing stable and nonprotein enzyme mimics with lysine and showed great potential applications in biorelevant assays.