Viruses Infecting Trees and Herbs That Produce Edible Fleshy Fruits with a Prominent Value in the Global Market: An Evolutionary Perspective

Trees and herbs that produce fruits represent the most valuable agricultural food commodities in the world. However, the yield of these crops is not fully achieved due to biotic factors such as bacteria, fungi, and viruses. Viruses are capable of causing alterations in plant growth and development, thereby impacting the yield of their hosts significantly. In this work, we first compiled the world's most comprehensive list of known edible fruits that fits our definition. Then, plant viruses infecting those trees and herbs that produce fruits with commercial importance in the global market were identified. The identified plant viruses belong to 30 families, most of them containing single-stranded RNA genomes. Importantly, we show the overall picture of the host range for some virus families following an evolutionary approach. Further, the current knowledge about plant-virus interactions, focusing on the main disorders they cause, as well as yield losses, is summarized. Additionally, since accurate diagnosis methods are of pivotal importance for viral diseases control, the current and emerging technologies for the detection of these plant pathogens are described. Finally, the most promising strategies employed to control viral diseases in the field are presented, focusing on solutions that are long-lasting.

Biosensor Technologies for Early Detection and Quantification of Plant Pathogens

Plant pathogens are a major reason of reduced crop productivity and may lead to a shortage of food for both human and animal consumption. Although chemical control remains the main method to reduce foliar fungal disease incidence, frequent use can lead to loss of susceptibility in the fungal population. Furthermore, over-spraying can cause environmental contamination and poses a heavy financial burden on growers. To prevent or control disease epidemics, it is important for growers to be able to detect causal pathogen accurately, sensitively, and rapidly, so that the best practice disease management strategies can be chosen and enacted. To reach this goal, many culture-dependent, biochemical, and molecular methods have been developed for plant pathogen detection. However, these methods lack accuracy, specificity, reliability, and rapidity, and they are generally not suitable for in-situ analysis. Accordingly, there is strong interest in developing biosensing systems for early and accurate pathogen detection. There is also great scope to translate innovative nanoparticle-based biosensor approaches developed initially for human disease diagnostics for early detection of plant disease-causing pathogens. In this review, we compare conventional methods used in plant disease diagnostics with new sensing technologies in particular with deeper focus on electrochemical and optical biosensors that may be applied for plant pathogen detection and management. In addition, we discuss challenges facing biosensors and new capability the technology provides to informing disease management strategies.

Research advances and applications of biosensing technology for the diagnosis of pathogens in sustainable agriculture

Plant diseases significantly impact the global economy, and plant pathogenic microorganisms such as nematodes, viruses, bacteria, fungi, and viroids may be the etiology for most infectious diseases. In agriculture, the development of disease-free plants is an important strategy for the determination of the survival and productivity of plants in the field. This article reviews biosensor methods of disease detection that have been used effectively in other fields, and these methods could possibly transform the production methods of the agricultural industry. The precise identification of plant pathogens assists in the assessment of effective management steps for minimization of production loss. The new plant pathogen detection methods include evaluation of signs of disease, detection of cultured organisms, or direct examination of contaminated tissues through molecular and serological techniques. Laboratory-based approaches are costly and time-consuming and require specialized skills. The conclusions of this review also indicate that there is an urgent need for the establishment of a reliable, fast, accurate, responsive, and cost-effective testing method for the detection of field plants at early stages of growth. We also summarized new emerging biosensor technologies, including isothermal amplification, detection of nanomaterials, paper-based techniques, robotics, and lab-on-a-chip analytical devices. However, these constitute novelty in the research and development of approaches for the early diagnosis of pathogens in sustainable agriculture.

The Incorporation of Amplified Metal-Enhanced Fluorescence in a CMOS-Based Biosensor Increased the Detection Sensitivity of a DNA Marker of the Pathogenic Fungus Colletotrichum gloeosporioides

Half of the global agricultural fresh produce is lost, mainly because of rots that are caused by various pathogenic fungi. In this study, a complementary metal-oxide-semiconductor (CMOS)-based biosensor was developed, which integrates specific DNA strands that allow the detection of enoyl-CoA-hydratase/isomerase, which is a quiescent marker of Colletotrichum gloeosporioides fungi. The developed biosensor mechanism is based on the metal-enhanced fluorescence (MEF) phenomenon, which is amplified by depositing silver onto a glass surface. A surface DNA strand is then immobilized on the surface, and in the presence of the target mRNA within the sample, the reporter DNA strand that is linked to horseradish peroxidase (HRP) enzyme will also bind to it. The light signal that is later produced from the HRP enzyme and its substrate is enhanced and detected by the coupled CMOS sensor. Several parameters that affect the silver-deposition procedure were examined, including silver solution temperature and volume, heating mode, and the tank material. Moreover, the effect of blocking treatment (skim milk or bovine serum albumin (BSA)) on the silver-layer stability and nonspecific DNA absorption was tested. Most importantly, the effect of the deposition reaction duration on the silver-layer formation and the MEF amplification was also investigated. In the study findings a preferred silver-deposition reaction duration was identified as 5–8 min, which increased the deposition of silver on the glass surface up to 13-times, and also resulted in the amplification of the MEF phenomenon with a maximum light signal of 50 relative light units (RLU). It was found that MEF can be amplified by a customized silver-deposition procedure that results in increased detection sensitivity. The implementation of the improved conditions increased the biosensor sensitivity to 3.3 nM (4500 RLU) with a higher detected light signal as compared to the initial protocol (400 RLU). Moreover, the light signal was amplified 18.75-, 11.11-, 5.5-, 11.25-, and 3.75-times in the improved protocol for all the tested concentrations of the target DNA strand of 1000, 100, 10, 3.3, and 2 nM, respectively. The developed biosensor system may allow the detection of the pathogenic fungus in postharvest produce and determine its pathogenicity state.

Detection of quiescent fungi in harvested fruit using CMOS biosensor: A proof of concept study

Postharvest fruit decay is caused by fungal pathogens and leads to major losses. In this study, specific mRNA sequences that are upregulated in the fungus Colletotrichum gloeosporioides during its quiescent stage in fruits, were identified using a CMOS sensor. The identification process was based on sandwich approach, where strands complementary to the C. gloeosporioides mRNA sequences (quiescent stage-specific) were immobilized on the CMOS surface, and exposed to the target complementary reporter strands. In the presence of a target sequence, the reporter strand (linked to the enzyme horseradish peroxidase (HRP)) was left in the system and a measurable light signal was produced. The complementary strands specifically anneal to the mRNA in the sample. The sensitivity of the technology was assessed by mRNA sequences isolated from C. gloeosporioides, and identified as 10 nM RNA. The effect of the pathogenicity state on the sensor performance was also evaluated. The CMOS sensor could detect quiescent fungi, which are barely detectable by other means. The unique capability of the proposed system to detect and recognize the fungus during both pathogenic and quiescent stages, will allow the development of new sensors that can monitor the amount of undetectable quiescent fungi in harvested fruit, enabling improved food management.