The State of the Art in Biodefense Related Bacterial Pathogen Detection Using Bacteriophages: How It Started and How It’s Going

Accurate pathogen detection and diagnosis is paramount in clinical success of treating patients. There are two general paradigms in pathogen detection: molecular and immuno-based, and phage-based detection is a third emerging paradigm due to its sensitivity and selectivity. Molecular detection methods look for genetic material specific for a given pathogen in a sample usually by polymerase chain reaction (PCR). Immuno-methods look at the pathogen components (antigens) by antibodies raised against that pathogen specific antigens. There are different variations and products based on these two paradigms with advantages and disadvantages. The third paradigm at least for bacterial pathogen detection entails bacteriophages specific for a given bacterium. Sensitivity and specificity are the two key parameters in any pathogen detection system. By their very nature, bacteriophages afford the best sensitivity for bacterial detection. Bacteria and bacteriophages form the predator-prey pair in the evolutionary arms race and has coevolved over time to acquire the exquisite specificity of the pair, in some instances at the strain level. This specificity has been exploited for diagnostic purposes of various pathogens of concern in clinical and other settings. Many recent reviews focus on phage-based detection and sensor technologies. In this review, we focus on a very special group of pathogens that are of concern in biodefense because of their potential misuse in bioterrorism and their extremely virulent nature and as such fall under the Centers for Disease and Prevention (CDC) Category A pathogen list. We describe the currently available phage methods that are based on the usual modalities of detection from culture, to molecular and immuno- and fluorescent methods. We further highlight the gaps and the needs for more modern technologies and sensors drawing from technologies existing for detection and surveillance of other pathogens of clinical relevance.

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A fully integrated bacterial pathogen detection system based on count-on-a-cartridge platform for rapid, ultrasensitive, highly accurate and culture-free assay

Biosensors and Bioelectronics ◽

10.1016/j.bios.2020.112007 ◽

2020 ◽

Vol 152 ◽

pp. 112007 ◽

Cited By ~ 2

Author(s):

Won-Il Lee ◽

Younghyeon Park ◽

Sajal Shrivastava ◽

Taekeon Jung ◽

Montri Meeseepong ◽

...

Keyword(s):

Pathogen Detection ◽

Detection System ◽

Bacterial Pathogen ◽

Fully Integrated

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A Portable Automatic Endpoint Detection System for Amplicons of Loop Mediated Isothermal Amplification on Microfluidic Compact Disk Platform

Sensors ◽

10.3390/s150305376 ◽

2015 ◽

Vol 15 (3) ◽

pp. 5376-5389 ◽

Cited By ~ 20

Author(s):

Shah Uddin ◽

Fatimah Ibrahim ◽

Abkar Sayad ◽

Aung Thiha ◽

Koh Pei ◽

...

Keyword(s):

Pathogen Detection ◽

Detection System ◽

Liquid Crystal Display ◽

Foodborne Pathogen ◽

Isothermal Amplification ◽

Detection Methods ◽

Endpoint Detection ◽

Compact Disk ◽

Loop Mediated Isothermal Amplification ◽

The Impact

In recent years, many improvements have been made in foodborne pathogen detection methods to reduce the impact of food contamination. Several rapid methods have been developed with biosensor devices to improve the way of performing pathogen detection. This paper presents an automated endpoint detection system for amplicons generated by loop mediated isothermal amplification (LAMP) on a microfluidic compact disk platform. The developed detection system utilizes a monochromatic ultraviolet (UV) emitter for excitation of fluorescent labeled LAMP amplicons and a color sensor to detect the emitted florescence from target. Then it processes the sensor output and displays the detection results on liquid crystal display (LCD). The sensitivity test has been performed with detection limit up to 2.5 × 10−3 ng/µL with different DNA concentrations of Salmonella bacteria. This system allows a rapid and automatic endpoint detection which could lead to the development of a point-of-care diagnosis device for foodborne pathogens detection in a resource-limited environment.

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In-House Validation of a Rinse–Membrane Filtration Method for Processing Fresh Produce Samples for Downstream Cultural Detection of Salmonella, Escherichia coli O157:H7, and Listeria

Journal of Food Protection ◽

10.4315/jfp-19-581 ◽

2020 ◽

Vol 83 (9) ◽

pp. 1592-1597

Author(s):

LAURA E. TIJERINA-RODRÍGUEZ ◽

LUISA SOLÍS-SOTO ◽

NORMA HEREDIA ◽

JUAN S. LEÓN ◽

LEE-ANN JAYKUS ◽

...

Keyword(s):

Escherichia Coli ◽

Membrane Filtration ◽

Pathogen Detection ◽

Fresh Produce ◽

Bacterial Pathogen ◽

Relative Sensitivity ◽

Good Alternative ◽

Detection Methods ◽

Filtration Method ◽

Relative Specificity

ABSTRACT More efficient sampling and detection methods of pathogens on fresh produce are needed. The purpose of this study was to compare a novel rinse–membrane filtration method (RMFM) to a more traditional sponge rubbing or stomaching method in processing jalapeño peppers and cantaloupe samples for detection of Escherichia coli, Salmonella enterica, and Listeria monocytogenes. For jalapeño peppers inoculated with 106, 104, and 102 CFU of each pathogen and cantaloupes inoculated at 106 and 104 CFU, all pathogens were detected in all (100%) samples by RMFM at a 10-mL filtration volume, as well as by the stomacher and sponge rubbing methods. However, for cantaloupe inoculated at 102 CFU, detection differed by pathogen: S. enterica (20% RMFM, 60% stomacher, and 20% sponge), L. monocytogenes (40% RMFM, 60% stomacher, and 20% sponge), and E. coli O157:H7 (100% RMFM, 75% stomacher, and 75% sponge). When RMFM was compared with the other methods, in accordance with guidelines in the International Organization for Standardization 16140:2003 protocol, it produced values >95% in relative accuracy, relative specificity, and relative sensitivity. Overall, the RMFM performed similar to or better than the homogenization and sponge surface rubbing methods and is a good alternative for processing large numbers of produce samples for bacterial pathogen detection.

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AFM-based technologies as the way towards the reverse Avogadro number

Biomeditsinskaya Khimiya ◽

10.18097/pbmc20156102239 ◽

2015 ◽

Vol 61 (2) ◽

pp. 239-253 ◽

Cited By ~ 1

Author(s):

T.O. Pleshakova ◽

I.D. Shumov ◽

Yu.D. Ivanov ◽

K.A. Malsagova ◽

A.L. Kaysheva ◽

...

Keyword(s):

Detection System ◽

Biological Fluids ◽

Chemical Properties ◽

Protein Detection ◽

Detection Methods ◽

Practical Implementation ◽

Advantages And Disadvantages ◽

Avogadro Number ◽

Modern Development ◽

Concentration Detection Limit

Achievement of the concentration detection limit for proteins at the level of the reverse Avogadro number determines the modern development of proteomics. In this review, the possibility of approximating the reverse Avogadro number by using nanotechnological methods (AFM-based fishing with mechanical and electrical stimulation, nanowire detectors, and other methods) are discussed. The ability of AFM to detect, count, visualize and characterize physico-chemical properties of proteins at concentrations up to 10-17-10-18 M is demonstrated. The combination of AFM-fishing with mass-spectrometry allows the identification of proteins not only in pure solutions, but also in multi-component biological fluids (serum). The possibilities to improve the biospecific fishing efficiency by use of SOMAmers in both AFM and nanowire systems are discussed. The paper also provides criteria for evaluation of the sensitivity of fishing-based detection systems. The fishing efficiency depending on the detection system parameters is estimated. The practical implementation of protein fishing depending on the ratio of the sample solution volume and the surface of the detection system is discussed. The advantages and disadvantages of today's promising nanotechnological protein detection methods implemented on the basis of these schemes.

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Assessment Criteria and Approaches for Rapid Detection Methods To Be Used in the Food Industry

Journal of Food Protection ◽

10.4315/0362-028x.jfp-13-138 ◽

2014 ◽

Vol 77 (4) ◽

pp. 670-690 ◽

Cited By ~ 11

Author(s):

MARTIN WIEDMANN ◽

SIYUN WANG ◽

LAURIE POST ◽

KENDRA NIGHTINGALE

Keyword(s):

Nucleic Acid ◽

Foodborne Pathogens ◽

Rapid Detection ◽

Food Industry ◽

Pathogen Detection ◽

Assessment Criteria ◽

Detection Methods ◽

Advantages And Disadvantages ◽

Specific Focus

The number of commercially available kits and methods for rapid detection of foodborne pathogens continues to increase at a considerable pace, and the diversity of methods and assay formats is reaching a point where it is very difficult even for experts to weigh the advantages and disadvantages of different methods and to decide which methods to choose for a certain testing need. Although a number of documents outline quantitative criteria that can be used to evaluate different detection methods (e.g., exclusivity and inclusivity), a diversity of criteria is typically used by industry to select specific methods that are used for pathogen detection. This article is intended to provide an overall outline of criteria that the food industry can use to evaluate new rapid detection methods, with a specific focus on nucleic acid–based detection methods.

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Recent Advances in AIV Biosensors Composed of Nanobio Hybrid Material

Micromachines ◽

10.3390/mi9120651 ◽

2018 ◽

Vol 9 (12) ◽

pp. 651 ◽

Cited By ~ 9

Author(s):

Taek Lee ◽

Jae-Hyuk Ahn ◽

Sun Yong Park ◽

Ga-Hyeon Kim ◽

Jeonghyun Kim ◽

...

Keyword(s):

Detection Method ◽

Detection System ◽

Transportation Systems ◽

Detection Methods ◽

Localized Surface Plasmon ◽

Process Time ◽

Human Beings ◽

Adequate Treatment ◽

Sensitivity And Selectivity ◽

Living Organisms

Since the beginning of the 2000s, globalization has accelerated because of the development of transportation systems that allow for human and material exchanges throughout the world. However, this globalization has brought with it the rise of various pathogenic viral agents, such as Middle East respiratory syndrome coronavirus (MERS-CoV), severe acute respiratory syndrome coronavirus (SARS-CoV), Zika virus, and Dengue virus. In particular, avian influenza virus (AIV) is highly infectious and causes economic, health, ethnical, and social problems to human beings, which has necessitated the development of an ultrasensitive and selective rapid-detection system of AIV. To prevent the damage associated with the spread of AIV, early detection and adequate treatment of AIV is key. There are traditional techniques that have been used to detect AIV in chickens, ducks, humans, and other living organisms. However, the development of a technique that allows for the more rapid diagnosis of AIV is still necessary. To achieve this goal, the present article reviews the use of an AIV biosensor employing nanobio hybrid materials to enhance the sensitivity and selectivity of the technique while also reducing the detection time and high-throughput process time. This review mainly focused on four techniques: the electrochemical detection system, electrical detection method, optical detection methods based on localized surface plasmon resonance, and fluorescence.

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Autonomous Pathogen Detection System (APDS) NYC Spring 2005 Field Test Report May to July 2005

10.2172/898459 ◽

2005 ◽

Author(s):

J M Dzenitis ◽

A J Makarewicz ◽

D R Hadley ◽

D M Gutierrez ◽

T R Metz ◽

...

Keyword(s):

Field Test ◽

Pathogen Detection ◽

Detection System ◽

Test Report

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Adaptive Detection of Direct-Sequence Spread-Spectrum Signals Based on Knowledge-Enhanced Compressive Measurements and Artificial Neural Networks

Sensors ◽

10.3390/s21072538 ◽

2021 ◽

Vol 21 (7) ◽

pp. 2538

Author(s):

Shuang Zhang ◽

Feng Liu ◽

Yuang Huang ◽

Xuedong Meng

Keyword(s):

Neural Networks ◽

Artificial Neural Networks ◽

Spread Spectrum ◽

High Efficiency ◽

Detection System ◽

Direct Sequence Spread Spectrum ◽

Detection Performance ◽

Detection Methods ◽

Direct Sequence ◽

Artificial Neural

The direct-sequence spread-spectrum (DSSS) technique has been widely used in wireless secure communications. In this technique, the baseband signal is spread over a wider bandwidth using pseudo-random sequences to avoid interference or interception. In this paper, the authors propose methods to adaptively detect the DSSS signals based on knowledge-enhanced compressive measurements and artificial neural networks. Compared with the conventional non-compressive detection system, the compressive detection framework can achieve a reasonable balance between detection performance and sampling hardware cost. In contrast to the existing compressive sampling techniques, the proposed methods are shown to enable adaptive measurement kernel design with high efficiency. Through the theoretical analysis and the simulation results, the proposed adaptive compressive detection methods are also demonstrated to provide significantly enhanced detection performance efficiently, compared to their counterpart with the conventional random measurement kernels.

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A novel GPU based intrusion detection system using deep autoencoder with Fruitfly optimization

SN Applied Sciences ◽

10.1007/s42452-021-04579-4 ◽

2021 ◽

Vol 3 (6) ◽

Author(s):

R. Sekhar ◽

K. Sasirekha ◽

P. S. Raja ◽

K. Thangavel

Keyword(s):

Intrusion Detection ◽

Intrusion Detection System ◽

Missing Values ◽

Detection System ◽

Radial Basis Function Network ◽

Detection Methods ◽

Support Vector ◽

Parameter Method ◽

List Type ◽

Fuzzy C Means

Abstract Intrusion Detection Systems (IDSs) have received more attention to safeguarding the vital information in a network system of an organization. Generally, the hackers are easily entering into a secured network through loopholes and smart attacks. In such situation, predicting attacks from normal packets is tedious, much challenging, time consuming and highly technical. As a result, different algorithms with varying learning and training capacity have been explored in the literature. However, the existing Intrusion Detection methods could not meet the desired performance requirements. Hence, this work proposes a new Intrusion Detection technique using Deep Autoencoder with Fruitfly Optimization. Initially, missing values in the dataset have been imputed with the Fuzzy C-Means Rough Parameter (FCMRP) algorithm which handles the imprecision in datasets with the exploit of fuzzy and rough sets while preserving crucial information. Then, robust features are extracted from Autoencoder with multiple hidden layers. Finally, the obtained features are fed to Back Propagation Neural Network (BPN) to classify the attacks. Furthermore, the neurons in the hidden layers of Deep Autoencoder are optimized with population based Fruitfly Optimization algorithm. Experiments have been conducted on NSL_KDD and UNSW-NB15 dataset. The computational results of the proposed intrusion detection system using deep autoencoder with BPN are compared with Naive Bayes, Support Vector Machine (SVM), Radial Basis Function Network (RBFN), BPN, and Autoencoder with Softmax. Article Highlights A hybridized model using Deep Autoencoder with Fruitfly Optimization is introduced to classify the attacks. Missing values have been imputed with the Fuzzy C-Means Rough Parameter method. The discriminate features are extracted using Deep Autoencoder with more hidden layers.

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How Far Are Non-Viral Vectors to Come of Age and Reach Clinical Translation in Gene Therapy?

International Journal of Molecular Sciences ◽

10.3390/ijms22147545 ◽

2021 ◽

Vol 22 (14) ◽

pp. 7545

Author(s):

Myriam Sainz-Ramos ◽

Idoia Gallego ◽

Ilia Villate-Beitia ◽

Jon Zarate ◽

Iván Maldonado ◽

...

Keyword(s):

Gene Therapy ◽

Clinical Practice ◽

Gene Delivery ◽

Viral Vectors ◽

Viral Vector ◽

Clinical Success ◽

Genetic Material ◽

Viral Gene ◽

Promising Alternative ◽

Vector Systems

Efficient delivery of genetic material into cells is a critical process to translate gene therapy into clinical practice. In this sense, the increased knowledge acquired during past years in the molecular biology and nanotechnology fields has contributed to the development of different kinds of non-viral vector systems as a promising alternative to virus-based gene delivery counterparts. Consequently, the development of non-viral vectors has gained attention, and nowadays, gene delivery mediated by these systems is considered as the cornerstone of modern gene therapy due to relevant advantages such as low toxicity, poor immunogenicity and high packing capacity. However, despite these relevant advantages, non-viral vectors have been poorly translated into clinical success. This review addresses some critical issues that need to be considered for clinical practice application of non-viral vectors in mainstream medicine, such as efficiency, biocompatibility, long-lasting effect, route of administration, design of experimental condition or commercialization process. In addition, potential strategies for overcoming main hurdles are also addressed. Overall, this review aims to raise awareness among the scientific community and help researchers gain knowledge in the design of safe and efficient non-viral gene delivery systems for clinical applications to progress in the gene therapy field.

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