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Fluorescence Based Biosensing Applications
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Fluorescence Based Biosensing Applications

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Biosensors".

Deadline for manuscript submissions: closed (30 June 2021) | Viewed by 20965

Special Issue Editor

Prof. Dr. Akio Kuroda

E-Mail Website
Guest Editor
Hiroshima University, Higashi-Hiroshima, Hiroshima 739-8530, Japan
Interests: fluorescence; luminescence; luciferase; protein immobilization; protein/peptide probes; inorganic surface; enzymatic sensors; point-of-care testing; on-site detection; microscopic analysis; extracellular vesicles; exosome

Special Issue Information

Dear Colleagues,

Fluorescence-based biosensing has been applied in various fields such as medical diagnostics, environmental monitoring, and inspection for food safety. Fluorescence detection is based on the use of fluorophores that emit light when excited by light of a shorter wavelength. In the simplest enzymatic fluorescence-based biosensing, an increase in the fluorescence intensity, resulting from the enzymatic conversion of a fluorogenic substrate to a fluorophore, is measured. Nowadays, numerous parameters besides the intensity, such as fluorescence anisotropy, decay time, energy transfer, and quenching have been explored in fluorescence-based biosensing. Aggregation-induced emission is a novel photophysical phenomenon which offers a new platform of fluorescence application. These fluorescence signals can also be used to monitor dynamic intracellular events of protein conformational changes upon protein-protein or protein-target interaction. Thus, fluorescence-based biosensing can be exploited to develop high-throughput screening for drug discovery. On the other hand, fluorescent labeling of a specific binder (e.g., antibodies or proteins) to a target allows the use of fluorescent microscopy, which has numerous advantages compared to other kinds of optical and even electron microscopy. The development of fluorescent specific probes could expand the possibilities of biosensing capabilities. This Special Issue aims to present the wide range of exciting applications using the latest technologies and methodologies developed in fluorescence-based biosensing.

Prof. Akio Kuroda
Guest Editor

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Keywords

  • Fluorescence-based biosensing
  • Medical diagnostics
  • Environmental monitoring
  • Inspection for food safety
  • Drug discovery
  • Fluorescence anisotropy
  • Fluorescence energy transfer
  • Quenching
  • Aggregation-induced emission
  • Fluorescent microscopy

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Published Papers (5 papers)

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16 pages, 3170 KiB  
Article
Construction of Fluorescent Immunosensor Quenchbody to Detect His-Tagged Recombinant Proteins Produced in Bioprocess
by Xuerao Ning, Takanobu Yasuda, Tetsuya Kitaguchi and Hiroshi Ueda
Sensors 2021, 21(15), 4993; https://doi.org/10.3390/s21154993 - 22 Jul 2021
Cited by 7 | Viewed by 3732
Abstract
With the widespread application of recombinant DNA technology, many useful substances are produced by bioprocesses. For the monitoring of the recombinant protein production process, most of the existing technologies are those for the culture environment (pH, O2, etc.). However, the production [...] Read more.
With the widespread application of recombinant DNA technology, many useful substances are produced by bioprocesses. For the monitoring of the recombinant protein production process, most of the existing technologies are those for the culture environment (pH, O2, etc.). However, the production status of the target protein can only be known after the subsequent separation and purification process. To speed up the monitoring of the production process and screening of the higher-yield target protein variants, here we developed an antibody-based His-tag sensor Quenchbody (Q-body), which can quickly detect the C-terminally His-tagged recombinant protein produced in the culture medium. Compared with single-chain Fv-based Q-body having one dye, the Fab-based Q-body having two dyes showed a higher response. In addition, not only was fluorescence response improved but also detection sensitivity by the mutations of tyrosine to tryptophan in the heavy chain CDR region. Moreover, the effect of the mutations on antigen-binding was successfully validated by molecular docking simulation by CDOCKER. Finally, the constructed Q-body was successfully applied to monitor the amount of anti-SARS CoV-2 nanobody secreted into the Brevibacillus culture media. Full article
(This article belongs to the Special Issue Fluorescence Based Biosensing Applications)
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14 pages, 2223 KiB  
Article
Rapid and Sensitive Inhibitor Screening Using Magnetically Modulated Biosensors
by Shira Roth and Amos Danielli
Sensors 2021, 21(14), 4814; https://doi.org/10.3390/s21144814 - 14 Jul 2021
Cited by 7 | Viewed by 2766
Abstract
Inhibitor screening is an important tool for drug development, especially during the COVID-19 pandemic. The most used in vitro inhibitor screening tool is an enzyme-linked immunosorbent assay (ELISA). However, ELISA-based inhibitor screening is time consuming and has a limited dynamic range. Using fluorescently [...] Read more.
Inhibitor screening is an important tool for drug development, especially during the COVID-19 pandemic. The most used in vitro inhibitor screening tool is an enzyme-linked immunosorbent assay (ELISA). However, ELISA-based inhibitor screening is time consuming and has a limited dynamic range. Using fluorescently and magnetically modulated biosensors (MMB), we developed a rapid and sensitive inhibitor screening tool. This study demonstrates its performance by screening small molecules and neutralizing antibodies as potential inhibitors of the interaction between the spike protein 1 (S1) of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and the angiotensin-converting enzyme 2 (ACE2) receptor. The MMB-based assay is highly sensitive, has minimal non-specific binding, and is much faster than the commonly used ELISA (2 h vs. 7–24 h). We anticipate that our method will lead to a remarkable advance in screening for new drug candidates. Full article
(This article belongs to the Special Issue Fluorescence Based Biosensing Applications)
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Graphical abstract

10 pages, 2004 KiB  
Communication
Asbestos Detection with Fluorescence Microscopy Images and Deep Learning
by Changjie Cai, Tomoki Nishimura, Jooyeon Hwang, Xiao-Ming Hu and Akio Kuroda
Sensors 2021, 21(13), 4582; https://doi.org/10.3390/s21134582 - 4 Jul 2021
Cited by 10 | Viewed by 4064
Abstract
Fluorescent probes can be used to detect various types of asbestos (serpentine and amphibole groups); however, the fiber counting using our previously developed software was not accurate for samples with low fiber concentration. Machine learning-based techniques (e.g., deep learning) for image analysis, particularly [...] Read more.
Fluorescent probes can be used to detect various types of asbestos (serpentine and amphibole groups); however, the fiber counting using our previously developed software was not accurate for samples with low fiber concentration. Machine learning-based techniques (e.g., deep learning) for image analysis, particularly Convolutional Neural Networks (CNN), have been widely applied to many areas. The objectives of this study were to (1) create a database of a wide-range asbestos concentration (0–50 fibers/liter) fluorescence microscopy (FM) images in the laboratory; and (2) determine the applicability of the state-of-the-art object detection CNN model, YOLOv4, to accurately detect asbestos. We captured the fluorescence microscopy images containing asbestos and labeled the individual asbestos in the images. We trained the YOLOv4 model with the labeled images using one GTX 1660 Ti Graphics Processing Unit (GPU). Our results demonstrated the exceptional capacity of the YOLOv4 model to learn the fluorescent asbestos morphologies. The mean average precision at a threshold of 0.5 ([email protected]) was 96.1% ± 0.4%, using the National Institute for Occupational Safety and Health (NIOSH) fiber counting Method 7400 as a reference method. Compared to our previous counting software (Intec/HU), the YOLOv4 achieved higher accuracy (0.997 vs. 0.979), particularly much higher precision (0.898 vs. 0.418), recall (0.898 vs. 0.780) and F-1 score (0.898 vs. 0.544). In addition, the YOLOv4 performed much better for low fiber concentration samples (<15 fibers/liter) compared to Intec/HU. Therefore, the FM method coupled with YOLOv4 is remarkable in detecting asbestos fibers and differentiating them from other non-asbestos particles. Full article
(This article belongs to the Special Issue Fluorescence Based Biosensing Applications)
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17 pages, 5416 KiB  
Article
Low-Cost Chlorophyll Fluorescence Imaging for Stress Detection
by Reeve Legendre, Nicholas T. Basinger and Marc W. van Iersel
Sensors 2021, 21(6), 2055; https://doi.org/10.3390/s21062055 - 15 Mar 2021
Cited by 20 | Viewed by 6237
Abstract
Plants naturally contain high levels of the stress-responsive fluorophore chlorophyll. Chlorophyll fluorescence imaging (CFI) is a powerful tool to measure photosynthetic efficiency in plants and provides the ability to detect damage from a range of biotic and abiotic stresses before visible symptoms occur. [...] Read more.
Plants naturally contain high levels of the stress-responsive fluorophore chlorophyll. Chlorophyll fluorescence imaging (CFI) is a powerful tool to measure photosynthetic efficiency in plants and provides the ability to detect damage from a range of biotic and abiotic stresses before visible symptoms occur. However, most CFI systems are complex, expensive systems that use pulse amplitude modulation (PAM) fluorometry. Here, we test a simple CFI system, that does not require PAM fluorometry, but instead simply images fluorescence emitted by plants. We used this technique to visualize stress induced by the photosystem II-inhibitory herbicide atrazine. After applying atrazine as a soil drench, CFI and color images were taken at 15-minute intervals, alongside measurements from a PAM fluorometer and a leaf reflectometer. Pixel intensity of the CFI images was negatively correlated with the quantum yield of photosystem II (ΦPSII) (p < 0.0001) and positively correlated with the measured reflectance in the spectral region of chlorophyll fluorescence emissions (p < 0.0001). A fluorescence-based stress index was developed using the reflectometer measurements based on wavelengths with the highest (741.2 nm) and lowest variability (548.9 nm) in response to atrazine damage. This index was correlated with ΦPSII (p < 0.0001). Low-cost CFI imaging can detect herbicide-induced stress (and likely other stressors) before there is visual damage. Full article
(This article belongs to the Special Issue Fluorescence Based Biosensing Applications)
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13 pages, 2277 KiB  
Letter
Novel Time-Resolved Fluorescence Immunochromatography Paper-Based Sensor with Signal Amplification Strategy for Detection of Deoxynivalenol
by Haowei Dong, Xingshuang An, Yaodong Xiang, Fukai Guan, Qi Zhang, Qingqing Yang, Xia Sun and Yemin Guo
Sensors 2020, 20(22), 6577; https://doi.org/10.3390/s20226577 - 18 Nov 2020
Cited by 27 | Viewed by 3095
Abstract
Immunoassay has the advantages of high sensitivity, high specificity, and simple operation, and has been widely used in the detection of mycotoxins. For several years, time-resolved fluorescence immunochromatography (TRFIA) paper-based sensors have attracted much attention as a simple and low-cost field detection technology. [...] Read more.
Immunoassay has the advantages of high sensitivity, high specificity, and simple operation, and has been widely used in the detection of mycotoxins. For several years, time-resolved fluorescence immunochromatography (TRFIA) paper-based sensors have attracted much attention as a simple and low-cost field detection technology. However, a traditional TRFIA paper-based sensor is based on antibody labeling, which cannot easily meet the current detection requirements. A second antibody labeling method was used to amplify the fluorescence signal and improve the detection sensitivity. Polystyrene fluorescent microspheres were combined with sheep anti-mouse IgG to prepare fluorescent probes (Eu-IgGs). After the probe fully reacted with the antibody (Eu-IgGs-Abs) in the sample cell, it was deployed on the paper-based sensor using chromatography. Eu-IgGs-Abs that were not bound to the target were captured on the T-line, while those that were bound were captured on the C-line. The paper-based sensor reflected the corresponding fluorescence intensity change. Because a single molecule of the deoxynivalenol antibody could bind to multiple Eu-IgGs, this method could amplify the fluorescence signal intensity on the unit antibody and improve the detection sensitivity. The working standard curve of the sensor was established under the optimum working conditions. It showed the lower limit of detection and higher recovery rate when it was applied to actual samples and compared with other methods. This sensor has the advantages of high sensitivity, good accuracy, and good specificity, saving the amount of antibody consumed and being suitable for rapid field detection of deoxynivalenol. Full article
(This article belongs to the Special Issue Fluorescence Based Biosensing Applications)
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