A Simple Phase-Sensitive Surface Plasmon Resonance Sensor Based on Simultaneous Polarization Measurement Strategy

Li, Meng‐Chi; Chen, Kai‐Ren; Kuo, C.; Lin, Yu‐Xen; Su, Li

doi:10.3390/s21227615

Cited by 14 publications

(14 citation statements)

References 43 publications

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“…By using specific molecules or nanoparticles to enhance SPR, it is also possible to reduce the detection limit of the sensor [ 41 , 42 , 43 ]. For glyphosate detection, several highly sensitive sensors based on the SPR phenomenon have been proposed recently, e.g., a localized surface plasmon resonance (LSPR) sensor using anisotropic gold nanoparticles with gold nanobipyramids [ 44 ], a phase-sensitive SPR sensor with internal referencing [ 45 ], or an electrochemical surface plasmon resonance (ESPR) sensor based on a molecularly imprinted polymer deposition on a gold chip/electrode [ 46 ]. All these sensors aim for improved sensitivity and good selectivity towards glyphosate.…”

Section: Resultsmentioning

confidence: 99%

Surface Plasmon Resonance Imaging Sensor for Detection of Photolytically and Photocatalytically Degraded Glyphosate

Vráblová

Smutná

Koutník

et al. 2022

Sensors

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Glyphosate is one of the most widely used pesticides, which, together with its primary metabolite aminomethylphosphonic acid, remains present in the environment. Many technologies have been developed to reduce glyphosate amounts in water. Among them, heterogeneous photocatalysis with titanium dioxide as a commonly used photocatalyst achieves high removal efficiency. Nevertheless, glyphosate is often converted to organic intermediates during its degradation. The detection of degraded glyphosate and emerging products is, therefore, an important element of research in terms of disposal methods. Attention is being paid to new sensors enabling the fast detection of glyphosate and its degradation products, which would allow the monitoring of its removal process in real time. The surface plasmon resonance imaging (SPRi) method is a promising technique for sensing emerging pollutants in water. The aim of this work was to design, create, and test an SPRi biosensor suitable for the detection of glyphosate during photolytic and photocatalytic experiments focused on its degradation. Cytochrome P450 and TiO2 were selected as the detection molecules. We developed a sensor for the detection of the target molecules with a low molecular weight for monitoring the process of glyphosate degradation, which could be applied in a flow-through arrangement and thus detect changes taking place in real-time. We believe that SPRi sensing could be widely used in the study of xenobiotic removal from surface water or wastewater.

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Section: Resultsmentioning

confidence: 99%

Surface Plasmon Resonance Imaging Sensor for Detection of Photolytically and Photocatalytically Degraded Glyphosate

Vráblová

Smutná

Koutník

et al. 2022

Sensors

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“…The principle is explained in detail in our previous study. 47 All analytes flowed through the prepared SPR chip to interact with the immobilized S‐mAb at a constant flow rate of 40 μl/min. The testing sample including spike protein, SASR‐CoV‐2 pseudovirus and clinical COVID‐19 nasopharyngeal swab.…”

Section: Methodsmentioning

confidence: 99%

“… 44 , 45 , 46 , 47 Nevertheless, the PS‐SPR usually requires complex optical configurations or specific techniques for measuring phase due to the high optical frequencies. 45 , 46 , 47 …”

Section: Introductionmentioning

confidence: 99%

“…The proposed PS‐SPR has been successfully implemented to the detection of glyphosate, with low molecular weight and the most frequently used herbicide worldwide, for a detection limit of 15 ng/ml (0.015 ppm). 47 Although, the PS‐SPR offers good performance in detecting small molecules of glyphosate, with the detection limit below the worldwide strictest residual level, the value is not outstanding enough to detect other proteins. It may be limited by the affinity of the capture receptors, which is known as a significant issue that affects the assay performance for affinity‐based biosensing systems.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Boosting the detection performance of severe acute respiratory syndrome coronavirus 2 test through a sensitive optical biosensor with new superior antibody

Lin

Wang

et al. 2022

Bioengineering & Transla Med

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The severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) virus emerged in late 2019 leading to the COVID‐19 disease pandemic that triggered socioeconomic turmoil worldwide. A precise, prompt, and affordable diagnostic assay is essential for the detection of SARS‐CoV‐2 as well as its variants. Antibody against SARS‐CoV‐2 spike (S) protein was reported as a suitable strategy for therapy and diagnosis of COVID‐19. We, therefore, developed a quick and precise phase‐sensitive surface plasmon resonance (PS‐SPR) biosensor integrated with a novel generated anti‐S monoclonal antibody (S‐mAb). Our results indicated that the newly generated S‐mAb could detect the original SARS‐CoV‐2 strain along with its variants. In addition, a SARS‐CoV‐2 pseudovirus, which could be processed in BSL‐2 facility was generated for evaluation of sensitivity and specificity of the assays including PS‐SPR, homemade target‐captured ELISA, spike rapid antigen test (SRAT), and quantitative reverse transcription polymerase chain reaction (qRT‐PCR). Experimentally, PS‐SPR exerted high sensitivity to detect SARS‐CoV‐2 pseudovirus at 589 copies/ml, with 7‐fold and 70‐fold increase in sensitivity when compared with the two conventional immunoassays, including homemade target‐captured ELISA (4 × 10 3 copies/ml) and SRAT (4 × 10 4 copies/ml), using the identical antibody. Moreover, the PS‐SPR was applied in the measurement of mimic clinical samples containing the SARS‐CoV‐2 pseudovirus mixed with nasal mucosa. The detection limit of PS‐SPR is calculated to be 1725 copies/ml, which has higher accuracy than homemade target‐captured ELISA (4 × 10 4 copies/ml) and SRAT (4 × 10 5 copies/ml) and is comparable with qRT‐PCR (1250 copies/ml). Finally, the ability of PS‐SPR to detect SARS‐CoV‐2 in real clinical specimens was further demonstrated, and the assay time was less than 10 min. Taken together, our results indicate that this novel S‐mAb integrated into PS‐SPR biosensor demonstrates high sensitivity and is time‐saving in SARS‐CoV‐2 virus detection. This study suggests that incorporation of a high specific recognizer in SPR biosensor is an alternative strategy that could be applied in developing other emerging or re‐emerging pathogenic detection platforms.

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“…Currently, one of the most commonly used tools for this purpose is the real-time affinity sensor which is based on the selective affinity between the analyte and receptor because such a sensor could be used to monitor the biomolecular interactions in real time and potentially provide the approaches to evaluate both the kinetic constants of the analyte. Among them, the most common option is the surface plasmon resonance (SPR) biosensor which is a reliable platform popularly used for studying biomolecular interactions such as measuring the analyte–receptor binding kinetics or detection. − This is because the SPR is based on the excitation of surface plasmons which tends to be extremely sensitive to changes in the refractive index caused by the binding events between the analyte and the receptor. − Based on this capability, SPR-based instruments (such as Biacore) have necessitated the study of biomolecular interactions and biological detection. − In addition, the real-time SPR sensorgram (see Figure a) also facilitates the visualization of the biomolecular interactions which allows researchers to estimate the kinetic constants with algorithms, for example, the Langmuir model. Nonetheless, the measurement of the kinetic constants is severely time-consuming (i.e., takes several hours before completion) even with the use of the most powerful SPR system, thereby posing to be the limitation of the SPR conventional method.…”

Section: Introductionmentioning

confidence: 99%

Easy and Rapid Approach to Obtaining the Binding Affinity of Biomolecular Interactions Based on the Deep Learning Boost

et al. 2022

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Recently, the deep learning (DL) dimension of artificial intelligence has received much attention from biochemical researchers and thus has gradually become the key approach adopted in the area of biosensing applications. Studies have shown that the use of DL techniques for sensing can not only shorten the time of data analysis but also significantly increase the accuracy of data analysis and prediction, resulting in the performance improvement of biosensing systems in comparison to conventional methods. However, obtaining reliable equilibrium and rate constants of biomolecular interactions during the detection process remains difficult and time-consuming to date. In this study, we propose a transformed model based on the deep transfer learning and sequence-to-sequence autoencoder that can successfully transfer the SPR sensorgram to the protein-binding constants, that is, the association rate constant (k a) and dissociation rate constant (k d), which provide crucial information to understand the mechanisms of drug action and the functional structures of biomolecules. Experimentally, we first trained and tested the pre-trained model using the Langmuir model which generated ideal SPR sensorgrams and then we fine-tuned the pre-trained model through the augmented SPR sensorgrams which were synthesized by using the synthesized minority oversampling technique (SMOTE) through the moderate-scale experiment. Next, the fine-tuned model was inputted with a short experimental SPR sensorgram that only needs 110 s, and the sensorgram was directly transformed into a reconstructed ideal sensorgram. Finally, the binding kinetic constants, that is, k a and k d, as outputs, were obtained through fitting the reconstructed ideal sensorgram. The results showed that the prediction errors of k a and k d obtained by our model were less than 12 and 24%, respectively. Based on the convenience, accuracy, and reliability of the proposed DL approach, we believe our strategy significantly boosts the feasibility to monitor the binding affinity of antibodies online during production.

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A Simple Phase-Sensitive Surface Plasmon Resonance Sensor Based on Simultaneous Polarization Measurement Strategy

Cited by 14 publications

References 43 publications

Surface Plasmon Resonance Imaging Sensor for Detection of Photolytically and Photocatalytically Degraded Glyphosate

Surface Plasmon Resonance Imaging Sensor for Detection of Photolytically and Photocatalytically Degraded Glyphosate

Boosting the detection performance of severe acute respiratory syndrome coronavirus 2 test through a sensitive optical biosensor with new superior antibody

Easy and Rapid Approach to Obtaining the Binding Affinity of Biomolecular Interactions Based on the Deep Learning Boost

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