Dataset Information

Hydrogen Peroxide Detection by Super-Porous Hybrid CuO/Pt NP Platform: Improved Sensitivity and Selectivity.

ABSTRACT: A super-porous hybrid platform can offer significantly increased number of reaction sites for the analytes and thus can offer advantages in the biosensor applications. In this work, a significantly improved sensitivity and selectivity of hydrogen peroxide (H2O2) detection is demonstrated by a super-porous hybrid CuO/Pt nanoparticle (NP) platform on Si substrate as the first demonstration. The super-porous hybrid platform is fabricated by a physiochemical approach combining the physical vapor deposition of Pt NPs and electrochemical deposition of super-porous CuO structures by adopting a dynamic hydrogen bubble technique. Under an optimized condition, the hybrid CuO/Pt biosensor demonstrates a very high sensitivity of 2205 µA/mM·cm2 and a low limit of detection (LOD) of 140 nM with a wide detection range of H2O2. This is meaningfully improved performance as compared to the previously reported CuO-based H2O2 sensors as well as to the other metal oxide-based H2O2 sensors. The hybrid CuO/Pt platform exhibits an excellent selectivity against other interfering molecules such as glucose, fructose, dopamine, sodium chloride and ascorbic acid. Due to the synergetic effect of highly porous CuO structures and underlying Pt NPs, the CuO/Pt architecture offers extremely abundant active sites for the H2O2 reduction and electron transfer pathways.

SUBMITTER: Kulkarni R

PROVIDER: S-EPMC7602549 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

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Hydrogen Peroxide Detection by Super-Porous Hybrid CuO/Pt NP Platform: Improved Sensitivity and Selectivity.

Kulkarni Rakesh R Kunwar Sundar S Mandavkar Rutuja R Jeong Jae-Hun JH Lee Jihoon J

Nanomaterials (Basel, Switzerland) 20201015 10

A super-porous hybrid platform can offer significantly increased number of reaction sites for the analytes and thus can offer advantages in the biosensor applications. In this work, a significantly improved sensitivity and selectivity of hydrogen peroxide (H<sub>2</sub>O<sub>2</sub>) detection is demonstrated by a super-porous hybrid CuO/Pt nanoparticle (NP) platform on Si substrate as the first demonstration. The super-porous hybrid platform is fabricated by a physiochemical approach combining ...[more]

PMID: 33076432

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Project description:Hydrogen peroxide (H2O2) is used by phagocytic cells of the innate immune response to kill engulfed bacteria. H2O2 diffuses freely into bacteria, where it can wreak havoc on sensitive biomolecules if it is not rapidly detoxified. Accordingly, bacteria have evolved numerous systems to defend themselves against H2O2, and the importance of these systems to pathogenesis has been substantiated by the many bacteria that require them to establish or sustain infections. The kinetic competition for H2O2 within bacteria is complex, which suggests that quantitative models will improve interpretation and prediction of network behavior. To date, such models have been of limited scope, and this inspired us to construct a quantitative, systems-level model of H2O2 detoxification in Escherichia coli that includes detoxification enzymes, H2O2-dependent transcriptional regulation, enzyme degradation, the Fenton reaction and damage caused by •OH, oxidation of biomolecules by H2O2, and repair processes. After using an iterative computational and experimental procedure to train the model, we leveraged it to predict how H2O2 detoxification would change in response to an environmental perturbation that pathogens encounter within host phagosomes, carbon source deprivation, which leads to translational inhibition and limited availability of NADH. We found that the model accurately predicted that NADH depletion would delay clearance at low H2O2 concentrations and that detoxification at higher concentrations would resemble that of carbon-replete conditions. These results suggest that protein synthesis during bolus H2O2 stress does not affect clearance dynamics and that access to catabolites only matters at low H2O2 concentrations. We anticipate that this model will serve as a computational tool for the quantitative exploration and dissection of oxidative stress in bacteria, and that the model and methods used to develop it will provide important templates for the generation of comparable models for other bacterial species.

Dataset Information

Hydrogen Peroxide Detection by Super-Porous Hybrid CuO/Pt NP Platform: Improved Sensitivity and Selectivity.

Publications

Hydrogen Peroxide Detection by Super-Porous Hybrid CuO/Pt NP Platform: Improved Sensitivity and Selectivity.

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