Revolutionizing Hydrogen Peroxide Detection: An Innovative Cascade Enzyme System for Enhanced Sensitivity and Range


Accurate detection of hydrogen peroxide (H₂O₂) is important in various fields due to its widespread use and significant impact on both industrial processes and biological systems. For example, H₂O₂ plays a critical role in biological systems, particularly in immune responses where it acts as a signaling molecule and as a defense mechanism against pathogens. Precise detection is essential for understanding cellular processes, diagnosing diseases, and developing treatments, including wound healing and cancer therapy. In clinical diagnostics, the detection of H₂O₂ can be linked to various diseases, as its production is often elevated in certain conditions. Accurate detection methods can help in early diagnosis and monitoring of diseases. Moreover, hydrogen peroxide is used as a disinfectant and bleaching agent in various industries, including paper and textile manufacturing. Monitoring its concentration in industrial effluents is essential to assess and mitigate its environmental impact, ensuring compliance with environmental regulations. In the food industry, H₂O₂ is used for sterilization and as a bleaching agent. Accurate detection ensures that its levels are within safe limits for consumption, maintaining food safety standards. Furthermore, H₂O₂ is used as a reagent in various chemical reactions, including oxidation processes. Its accurate measurement is crucial for process control, ensuring the efficiency and safety of chemical production. Due to these diverse applications and the potential hazards associated with improper handling or accidental exposure to high concentrations of H₂O₂, reliable and accurate detection methods are essential for safety, environmental protection, and effective utilization in various applications. Traditional methods for H₂O₂ detection, particularly those employing peroxidase (POD) mimics, have been limited by narrow linear ranges (LRs) and low LR maximums, primarily due to the constraints imposed by the Michaelis-Menten kinetics of enzyme reactions. This limitation is particularly problematic when dealing with samples containing high concentrations of H₂O₂, such as bacterial cleaners and industrial effluents, where extensive dilution is required to bring the H₂O₂ concentration within the detectable range, complicating the assay procedure and potentially leading to inaccuracies.

To overcome this challenge, a new study published in Journal Small by Dr. Baoji Du and conducted by Haiwei Hou, Lan Liu, Qiuyue Li, and Jianming Wang from the Jiaotong University the research team developed a novel cascade enzyme system (CES) that integrates a POD mimic with catalase (CAT) to expand the LR for H₂O₂  detection. The key innovation lies in the use of catalase to decompose a portion of the H₂O₂  present in a sample, thereby allowing for the detection of H₂O₂  over a wider concentration range without the need for dilution.

The team synthesized ruthenium-decorated reduced graphene oxide (rGO@RuNPs, or rGR) with inherent POD activity and then coupled it with natural catalase to create the rGO@RuNPs@CAT complex (rGRC). This complex exhibited both POD and CAT activities, enabling the expanded LR for H2O2 detection. They conducted various analytical techniques, including UV–vis spectroscopy, X-ray photoelectron spectroscopy , transmission electron microscopy, and Fourier-transform infrared spectroscopy, the researchers characterized the synthesized rGR and rGRC. These characterizations confirmed the successful synthesis and the intended structural properties of the CES.

The authors evaluated the POD-like activity of rGR and the catalytic function of rGRC. They demonstrated that rGR could catalyze H₂O₂ to produce hydroxyl radicals and oxidize substrates, such as 3,3′,5,5′-Tetramethylbenzidine (TMB), leading to a colorimetric signal. The introduction of CAT in rGRC allowed for the decomposition of H₂O₂, reducing its concentration in the reaction mixture and thus expanding the LR for H₂O₂ detection. They proposed and validated a mechanism for the LR expansion observed with the rGRC-based sensor. They showed that the relative enzyme activity between CAT and POD within the CES influenced the apparent Km (Michaelis-Menten constant) of the POD-catalyzed reaction, leading to an expanded LR. This was achieved by modulating factors such as pH and the amounts of POD and CAT. The rGRC-based sensor was successfully applied to detect high concentrations of H₂O₂ in contact lens care solutions, demonstrating its practical utility. The sensor achieved near 100% recovery at high H₂O₂ concentrations, indicating its accuracy and potential for real-world applications.

In a nutshell, the study by Dr. Du and his team represents a significant advancement in the field of chemical sensing, particularly for the detection of hydrogen peroxide. By integrating a POD mimic with catalase in a cascade enzyme system, the researchers were able to overcome the limitations of narrow linear ranges associated with traditional POD-based sensors. This breakthrough has broad implications for various applications, including environmental monitoring, healthcare diagnostics, and industrial processes, where accurate and efficient detection of H₂O₂  is crucial. The implications of this research are profound, offering a new paradigm in H₂O₂  sensing that can accurately detect high H₂O₂  concentrations without the need for extensive dilution. The rGRC-based sensor achieves near 100% recovery at high H₂O₂  concentrations, showcasing its potential for practical applications, particularly in analyzing samples with high H₂O₂  content such as contact lens care solutions.

Revolutionizing Hydrogen Peroxide Detection: An Innovative Cascade Enzyme System for Enhanced Sensitivity and Range - Advances in Engineering

About the author

Baoji Du received his Ph.D. degree of Analytical Chemistry from Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, China in 2016. From 2017 to 2020, he worked as a postdoctoral associate at Weill Cornell Medical College of Cornell University. Since 2020, he has been a research professor of Xi’an Jiaotong University, China. His main research interests focus on developing advanced biosensors by the integration with enzymes, hydrogels and sponges, as well as applying enzyme reactions to disease diagnosis and treatment.


Hou H, Liu L, Li Q, Wang J, Du B. A Cascade Enzyme System Integrating Peroxidase Mimic with Catalase for Linear Range Expansion of H2 O2 Assay: A Mechanism and Application Study. Small. 2023 Jun;19(25):e2300444. doi: 10.1002/smll.202300444.

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