Determination of β-glucosidase activity using single-particle enumeration with Au@CeO2 nanoparticles

Xiang, Yuan; Zhang, Huiling; Cao, Huijuan; Mao, Guojiang; Wei, Lin

doi:10.1007/s00604-022-05580-3

Cited by 6 publications

(2 citation statements)

References 35 publications

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“…The results in Figure S5a,b showed that the signal intensity increased with the increase of the concentration of MPO, which a good linear relationship existed in the concentration range 50 ng/mL to 10 μg/mL. Due to MPO being a lysosomal enzyme with cleavage activity, we chose other types of lysosomal enzymes (β-glucosidase 37 and βgalactosidase 38 ) or endonucleases (Nb.BbvCI) similar to MPO, and the results in Figure S5c showed that the fluorescence response of the switch was highly selective for MPO over other enzymes, demonstrating that this method was specific to MPO, and the enzyme reaction was correctly triggered to further induce successful transcription. Table S2 showed the comparisons of the quantitative performances of our method with those of other methods; the dominance of our method is evident in terms of both the detection limit and applicability.…”

Section: ■ Experimental Sectionmentioning

confidence: 99%

Enzyme Reaction-Assisted Programmable Transcriptional Switches for Bioactive Molecule Detection

Tang,

Chen,

et al. 2023

Anal. Chem.

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Bioactive molecules are highly worthwhile to recognize and explore the latent pathogenic mechanism. Conventional methods for bioactive molecule detection, including mass spectrometry and fluorescent probe imaging, are limited due to the complex processing and signal interference. Here, we designed enzyme-reaction-assisted programmable transcriptional switches for the detection of bioactive molecules. The approach is based on the use of programmable enzyme site-specific cleavage-assisted DNA triplex-based conformational switches that, upon responding to bioactive molecules, can trigger the transcription of fluorescent light-up aptamers. Thanks to the programmable nature of the sensing platform, the method can be adapted to different bioactive molecules, and we demonstrated the enzyme-small molecule catalytic reaction combination of myeloperoxidase (MPO)–hydrogen peroxide (H2O2) as a model that transcriptional switches was capable of detecting H2O2 and possessed the specificity and anti-interference ability in vitro. Furthermore, we successfully applied the switches into cells to observe the detection feasibility in vivo, and dynamically monitored changes of H2O2 in cellular oxidative stress levels. Therefore, we attempt to amalgamate the advantages of enzyme reaction with the pluripotency of programmable transcriptional switches, which can take both fields a step further, which may promote the research of biostimuli and the construction of DNA molecular devices.

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Section: ■ Experimental Sectionmentioning

confidence: 99%

Enzyme Reaction-Assisted Programmable Transcriptional Switches for Bioactive Molecule Detection

Tang,

Chen,

et al. 2023

Anal. Chem.

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“…The common approach for building LSPR-based sensors relies on the scattering signal assay that detects the intensity and color of the scattering light of nanoparticles, which can be efficiently observed using dark-field microscopy (DFM). With the advantages of high sensitivity, high signal-to-noise, and high spatial and temporal resolution, DFM has been broadly used for quantitative analysis, , dynamic monitoring, , biological sensing, − and material performance evaluation − by observing the color change of the scattering light of nanoparticles in DFM images. However, due to the heterogeneity of the sample, the scattering information on a single nanoparticle cannot reflect the real distribution of the whole situation accurately.…”

Section: Introductionmentioning

confidence: 99%

Holistic Prediction of AuNP Aggregation in Diverse Aqueous Suspensions Based on Machine Vision and Dark-Field Scattering Imaging

Wang,

Hong,

Zhou

et al. 2024

Anal. Chem.

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The localized surface-plasmon resonance of the AuNP in aqueous media is extremely sensitive to environmental changes. By measuring the signal of plasmon scattering light, the dark-field microscopic (DFM) imaging technique has been used to monitor the aggregation of AuNPs, which has attracted great attention because of its simplicity, low cost, high sensitivity, and universal applicability. However, it is still challenging to interpret DFM images of AuNP aggregation due to the heterogeneous characteristics of the isolated and discontinuous color distribution. Herein, we introduce machine vision algorithms for the training of DFM images of AuNPs in different saline aqueous media. A visual deep learning framework based on AlexNet is constructed for studying the aggregation patterns of AuNPs in aqueous suspensions, which allows for rapid and accurate identification of the aggregation extent of AuNPs, with a prediction accuracy higher than 0.96. With the aid of machine learning analysis, we further demonstrate the prediction ability of various aggregation phenomena induced by both cation species and the concentration of the external saline solution. Our results suggest the great potential of machine vision frameworks in the accurate recognition of subtle pattern changes in DFM images, which can help researchers build predictive analytics based on DFM imaging data.

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Single Particle Colorimetric Acid Phosphatase Activity Assay with CeO2-modified Gold Nanoparticles

Zhu,

Yuan,

Mao

et al. 2024

Chem. Res. Chin. Univ.

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Determination of β-glucosidase activity using single-particle enumeration with Au@CeO2 nanoparticles

Cited by 6 publications

References 35 publications

Enzyme Reaction-Assisted Programmable Transcriptional Switches for Bioactive Molecule Detection

Enzyme Reaction-Assisted Programmable Transcriptional Switches for Bioactive Molecule Detection

Holistic Prediction of AuNP Aggregation in Diverse Aqueous Suspensions Based on Machine Vision and Dark-Field Scattering Imaging

Single Particle Colorimetric Acid Phosphatase Activity Assay with CeO2-modified Gold Nanoparticles

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