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      Lateral Flow Immunoassay for Rapid Detection of Grapevine Leafroll-Associated Virus

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          Abstract

          Grapevine leafroll-associated virus 3 (GLRaV-3) is one of the main pathogens of grapes, causing a significant loss in yield and decrease in quality for this agricultural plant. For efficient widespread control of this infection, rapid and simple analytical techniques of on-site testing are requested as a complementary addition for the currently applied hybridization (PCR) and immunoenzyme (ELISA) approaches. The given paper presents development and approbation of the immunochromatographic assay (ICA) for rapid detection of GLRaV-3. The ICA realizes a sandwich immunoassay format with the obtaining complexes ((antibody immobilized on immunochromatographic membrane)–(virus in the sample)–(antibody immobilized on gold nanoparticles (GNP)) during sample flow along the membrane compounds of the test strip. Three preparations of GNPs were compared for detection of GLRaV-3 at different dilutions of virus-containing sample. The GNPs with maximal average diameters of 51.0 ± 7.9 nm provide GLRaV-3 detection for its maximal dilutions, being 4 times more than when using GNPs with a diameter of 28.3 ± 3.3 nm, and 8 times more than when using GNPs with a diameter of 18.5 ± 3.3 nm. Test strips have been manufactured using the largest GNPs conjugated with anti-GLRaV-3 antibodies at a ratio of 1070:1. When testing samples containing other grape wine viruses, the test strips have not demonstrated staining in the test zone, which confirms the ICA specificity. The approbation of the manufactured test strips indicated that when using ELISA as a reference method, the developed ICA is characterized by a sensitivity of 100% and a specificity of 92%. If PCR is considered as a reference method, then the sensitivity of ICA is 93% and the specificity is 92%. The proposed ICA can be implemented in one stage without the use of any additional reactants or devices. The testing results can be obtained in 10 min and detected visually. It provides significant improvement in GLRaV-3 detection, and the presented approach can be transferred for the development of test systems for other grape wine pathogens.

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          Most cited references 41

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          Membrane-based lateral flow immunochromatographic strip with nanoparticles as reporters for detection: A review.

          Membrane-based lateral flow immunochromatographic strip (LFICS) is widely used in various fields because of its simplicity, rapidity (detection within 10min), and low cost. However, early designs of membrane-based LFICS for preliminary screening only provide qualitative ("yes/no" signal) or semi-quantitative results without quantitative information. These designs often suffer from low-signal intensity and poor sensitivity and are only capable of single analyte detection, not simultaneous multiple detections. The performance of existing techniques used for detection using LFICS has been considerably improved by incorporating different kinds of nanoparticles (NPs) as reporters. NPs can serve as alternative labels and improve analytical sensitivity or limit of detection of LFICS because of their unique properties, such as optical absorption, fluorescence spectra, and magnetic properties. The controlled manipulation of NPs allows simultaneous or multiple detections by using membrane-based LFICS. In this review, we discuss how colored (e.g., colloidal gold, carbon, and colloidal selenium NPs), luminescent (e.g., quantum dots, up-converting phosphor NPs, and dye-doped NPs), and magnetic NPs are integrated into membrane-based LFICS for the detection of target analytes. Gold NPs are also featured because of their wide applications. Different types and unique properties of NPs are briefly explained. This review focuses on examples of NP-based LFICS to illustrate novel concepts in various devices with potential applications as screening tools. This review also highlights the superiority of NP-based approaches over existing conventional strategies for clinical analysis, food safety, and environmental monitoring. This paper is concluded by a short section on future research trends regarding NP-based LFICS.
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            Current and Prospective Methods for Plant Disease Detection

            Food losses due to crop infections from pathogens such as bacteria, viruses and fungi are persistent issues in agriculture for centuries across the globe. In order to minimize the disease induced damage in crops during growth, harvest and postharvest processing, as well as to maximize productivity and ensure agricultural sustainability, advanced disease detection and prevention in crops are imperative. This paper reviews the direct and indirect disease identification methods currently used in agriculture. Laboratory-based techniques such as polymerase chain reaction (PCR), immunofluorescence (IF), fluorescence in-situ hybridization (FISH), enzyme-linked immunosorbent assay (ELISA), flow cytometry (FCM) and gas chromatography-mass spectrometry (GC-MS) are some of the direct detection methods. Indirect methods include thermography, fluorescence imaging and hyperspectral techniques. Finally, the review also provides a comprehensive overview of biosensors based on highly selective bio-recognition elements such as enzyme, antibody, DNA/RNA and bacteriophage as a new tool for the early identification of crop diseases.
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              Immunochromatographic methods in food analysis

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                Author and article information

                Journal
                Biosensors (Basel)
                Biosensors (Basel)
                biosensors
                Biosensors
                MDPI
                2079-6374
                15 November 2018
                December 2018
                : 8
                : 4
                Affiliations
                [1 ]A.N. Bach Institute of Biochemistry, Research Center of Biotechnology of the Russian Academy of Sciences, Leninsky Prospect 33, Moscow 119071, Russia; nbyzova@ 123456inbi.ras.ru (N.A.B.); zherdev@ 123456inbi.ras.ru (A.V.Z.)
                [2 ]Institute of Bioengineering, Research Center of Biotechnology of the Russian Academy of Sciences, Leninsky Prospect 33, Moscow 119071, Russia; svetlana.vinogradova@ 123456biengi.ac.ru (S.V.V.); plantvirus@ 123456mail.ru (E.V.P.); terekhova_uliana@ 123456mail.ru (U.D.T.)
                Author notes
                [* ]Correspondence: dzantiev@ 123456inbi.ras.ru ; Tel.: +7-495-954-3142
                Article
                biosensors-08-00111
                10.3390/bios8040111
                6315891
                30445781
                © 2018 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

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