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Biosensors
Special Issues
Biosensing Technologies for Bacteria and Virus Detections
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Biosensing Technologies for Bacteria and Virus Detections

A special issue of Biosensors (ISSN 2079-6374). This special issue belongs to the section "Biosensors and Healthcare".

Deadline for manuscript submissions: closed (1 October 2023) | Viewed by 10033

Special Issue Editors

Prof. Dr. Xiaoping Yu

E-Mail Website
Guest Editor
College of Life Sciences, China Jiliang University, Hangzhou, China
Interests: rapid detection technology for animal and plant pathogens and development of biosensor devices
Prof. Dr. Jian Wu

E-Mail Website
Guest Editor
College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310058, China
Interests: application of bio-detection technology in the field of food safety; nucleic acid biosensors; nanotechnology biosensors
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Pathogens like bacteria and viruses pose a substantial threat to humans, animals, and plants. Rapid detection of these pathogens is required for effective disease diagnosis and biomonitoring. Traditional methods based on immunological, morphological and PCR technology have many drawbacks, such as long detection time, complex preprocessing steps, and low detection efficiency. As an alternative to these methods, biosensor technology is gaining increasing interest in the detection of bacterial and viral pathogens due to its advantages of being more specific, sensitive and affordable. Therefore, this Special Issue, entitled "Biosensing Technologies for Bacteria and Virus Detections", gathers a collection of research articles, reviews, and communications addressing the application of biosensing technologies in bacteria and virus diagnostic. Topics include (but are not limited to) the design, fabrication, and application of advanced biosensors based on new principles, strategies, and methods.

Prof. Dr. Xiaoping Yu
Prof. Dr. Jian Wu
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Biosensors is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • bacteria
  • viruses
  • disease diagnosis
  • pathogen
  • infectious disease
  • biosensors
  • DNA/RNA and protein detection

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Published Papers (4 papers)

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Research

9 pages, 2580 KiB  
Communication
RT-RPA-PfAgo System: A Rapid, Sensitive, and Specific Multiplex Detection Method for Rice-Infecting Viruses
by Yan Liu, Wenqiang Xia, Wei Zhao, Peiying Hao, Zhengliang Wang, Xiaoping Yu, Xuping Shentu and Kai Sun
Biosensors 2023, 13(10), 941; https://doi.org/10.3390/bios13100941 - 20 Oct 2023
Cited by 6 | Viewed by 2344
Abstract
The advancement in CRISPR-Cas biosensors has transmuted the detection of plant viruses owing to their rapid and higher sensitivity. However, false positives and restricted multiplexing capabilities are still the challenges faced by this technology, demanding the exploration of novel methodologies. In this study, [...] Read more.
The advancement in CRISPR-Cas biosensors has transmuted the detection of plant viruses owing to their rapid and higher sensitivity. However, false positives and restricted multiplexing capabilities are still the challenges faced by this technology, demanding the exploration of novel methodologies. In this study, a novel detection system was developed by integrating reverse transcriptome (RT) techniques with recombinase polymerase isothermal amplification (RPA) and Pyrococcus furiosus Argonaute (PfAgo). The RT-RPA-PfAgo system enabled the simultaneous detection of rice ragged stunt virus (RRSV), rice grassy stunt virus (RGSV), and rice black streaked dwarf virus (RBSDV). Identifying targets via guide DNA without being hindered by protospacer adjacent motif sequences is the inherent merit of PfAgo, with the additional advantage of it being simple, cost-effective, and exceptionally sensitive, with detection limits between 3.13 and 5.13 copies/µL, in addition to it effectively differentiating between the three distinct viruses. The field evaluations were also in accordance with RT-PCR methods. The RT-RPA-PfAgo system proved to be a robust, versatile, highly specific, and sensitive method with great potential for practicality in future plant virus diagnostics. Full article
(This article belongs to the Special Issue Biosensing Technologies for Bacteria and Virus Detections)
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17 pages, 3391 KiB  
Article
Bacteria-Infected Artificial Urine Characterization Based on a Combined Approach Using an Electronic Tongue Complemented with 1H-NMR and Flow Cytometry
by Carolin Psotta, Emelie J. Nilsson, Thomas Sjöberg and Magnus Falk
Biosensors 2023, 13(10), 916; https://doi.org/10.3390/bios13100916 - 5 Oct 2023
Cited by 2 | Viewed by 2043
Abstract
The prevailing form of bacterial infection is within the urinary tract, encompassing a wide array of bacteria that harness the urinary metabolome for their growth. Through their metabolic actions, the chemical composition of the growth medium undergoes modifications as the bacteria metabolize urine [...] Read more.
The prevailing form of bacterial infection is within the urinary tract, encompassing a wide array of bacteria that harness the urinary metabolome for their growth. Through their metabolic actions, the chemical composition of the growth medium undergoes modifications as the bacteria metabolize urine compounds, leading to the subsequent release of metabolites. These changes can indirectly indicate the existence and proliferation of bacterial organisms. Here, we investigate the use of an electronic tongue, a powerful analytical instrument based on a combination of non-selective chemical sensors with a partial specificity for data gathering combined with principal component analysis, to distinguish between infected and non-infected artificial urine samples. Three prevalent bacteria found in urinary tract infections were investigated, Escherichia coli, Klebsiella pneumoniae, and Enterococcus faecalis. Furthermore, the electronic tongue analysis was supplemented with 1H NMR spectroscopy and flow cytometry. Bacteria-specific changes in compound consumption allowed for a qualitative differentiation between artificial urine medium and bacterial growth. Full article
(This article belongs to the Special Issue Biosensing Technologies for Bacteria and Virus Detections)
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16 pages, 5822 KiB  
Article
Europium Nanoparticle-Based Lateral Flow Strip Biosensors Combined with Recombinase Polymerase Amplification for Simultaneous Detection of Five Zoonotic Foodborne Pathogens
by Bei Jin, Biao Ma, Qing Mei, Shujuan Xu, Xin Deng, Yi Hong, Jiali Li, Hanyue Xu and Mingzhou Zhang
Biosensors 2023, 13(6), 652; https://doi.org/10.3390/bios13060652 - 14 Jun 2023
Cited by 5 | Viewed by 2284
Abstract
The five recognized zoonotic foodborne pathogens, namely, Listeria monocytogenes, Staphylococcus aureus, Streptococcus suis, Salmonella enterica and Escherichia coli O157:H7, pose a major threat to global health and social–economic development. These pathogenic bacteria can cause human and animal diseases through [...] Read more.
The five recognized zoonotic foodborne pathogens, namely, Listeria monocytogenes, Staphylococcus aureus, Streptococcus suis, Salmonella enterica and Escherichia coli O157:H7, pose a major threat to global health and social–economic development. These pathogenic bacteria can cause human and animal diseases through foodborne transmission and environmental contamination. Rapid and sensitive detection for pathogens is particularly important for the effective prevention of zoonotic infections. In this study, rapid and visual europium nanoparticle (EuNP)-based lateral flow strip biosensors (LFSBs) combined with recombinase polymerase amplification (RPA) were developed for the simultaneous quantitative detection of five foodborne pathogenic bacteria. Multiple T lines were designed in a single test strip for increasing the detection throughput. After optimizing the key parameters, the single-tube amplified reaction was completed within 15 min at 37 °C. The fluorescent strip reader recorded the intensity signals from the lateral flow strip and converted the data into a T/C value for quantification measurement. The sensitivity of the quintuple RPA-EuNP-LFSBs reached a level of 101 CFU/mL. It also exhibited good specificity and there was no cross-reaction with 20 non-target pathogens. In artificial contamination experiments, the recovery rate of the quintuple RPA-EuNP-LFSBs was 90.6–101.6%, and the results were consistent with those of the culture method. In summary, the ultrasensitive bacterial LFSBs described in this study have the potential for widespread application in resource-poor areas. The study also provides insights in respect to multiple detection in the field. Full article
(This article belongs to the Special Issue Biosensing Technologies for Bacteria and Virus Detections)
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12 pages, 6071 KiB  
Article
Development of a Dual Mode UCNPs-MB Biosensor in Combination with PCR for Sensitive Detection of Salmonella
by Lu Han, Min Chen, Yaqi Song, Zhongyu Yan, Dandan Zhou, Leiqing Pan and Kang Tu
Biosensors 2023, 13(4), 475; https://doi.org/10.3390/bios13040475 - 13 Apr 2023
Cited by 5 | Viewed by 1915
Abstract
In recent years, the high prevalence of Salmonella has emerged as a serious threat to public safety, prompting attempts to utilize accurate, rapid, and direct methods to ensure food safety. In this study, a multifunctional platform featuring dual-mode detection channels (colorimetric-fluorescence) combined with [...] Read more.
In recent years, the high prevalence of Salmonella has emerged as a serious threat to public safety, prompting attempts to utilize accurate, rapid, and direct methods to ensure food safety. In this study, a multifunctional platform featuring dual-mode detection channels (colorimetric-fluorescence) combined with polymer chain reaction (PCR) was proposed for the sensitive and rapid detection of Salmonella. Additionally, the colorimetric measurements were achieved by color changes induced by methylene blue (MB) insertion into the double-stranded DNA, and the fluorescence measurements were performed by internal filter effect (IFE)-induced fluorescence quenching of upconversion nanoparticles (UCNPs) by MB. The results showed that the IFE and PCR amplification processes improved the sensitivity of the sensor towards Salmonella detection, with a limit of detection (LOD) of 21.8 CFU/mL. Moreover, this colorimetric-fluorescence dual-mode PCR biosensor was applied to determine Salmonella in food samples, such as chicken, egg, and fish, which produced satisfactory results. Overall, the present study results demonstrate the potential for combining PCR amplification with IFE to develop an efficient and reliable dual-mode analysis platform to safeguard food security. Full article
(This article belongs to the Special Issue Biosensing Technologies for Bacteria and Virus Detections)
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