One-Step Reverse-Transcription Digital PCR for Reliable Quantification of Different Pepino Mosaic Virus Genotypes

Molecular Methods for the Simultaneous Detection of Tomato Fruit Blotch Virus and Identification of Tomato Russet Mite, a New Potential Virus-Vector System Threatening Solanaceous Crops Worldwide

Tomato fruit blotch virus (ToFBV) (Blunervirus solani, family Kitaviridae) was firstly identified in Italy in 2018 in tomato plants that showed the uneven, blotchy ripening and dimpling of fruits. Subsequent High-Throughput Sequencing (HTS) analysis allowed ToFBV to be identified in samples collected in Australia, Brazil, and several European countries, and its presence in tomato crops was dated back to 2012. In 2023, the virus was found to be associated with two outbreaks in Italy and Belgium, and it was included in the EPPO Alert list as a potential new threat for tomato fruit production. Many epidemiologic features of ToFBV need to be still clarified, including transmission. Aculops lycopersici Massee (Acariformes: Eriophyoidea), the tomato russet mite (TRM), is a likely candidate vector, since high population densities were found in most of the ToFBV-infected tomato cultivations worldwide. Real-time RT-PCR tests for ToFBV detection and TRM identification were developed, also as a duplex assay. The optimized tests were then transferred to an RT-ddPCR assay and validated according to the EPPO Standard PM 7/98 (5). Such sensitive, reliable, and validated tests provide an important diagnostic tool in view of the probable threat posed by this virus-vector system to solanaceous crops worldwide and can contribute to epidemiological studies by simplifying the efficiency of research. To our knowledge, these are the first molecular methods developed for the simultaneous detection and identification of ToFBV and TRM.

Evaluation of sequencing and PCR-based methods for the quantification of the viral genome formula

Viruses show great diversity in their genome organization. Multipartite viruses package their genome segments into separate particles, most or all of which are required to initiate infection in the host cell. The benefits of such seemingly inefficient genome organization are not well understood. One hypothesised benefit of multipartition is that it allows for flexible changes in gene expression by altering the frequency of each genome segment in different environments, such as encountering different host species. The ratio of the frequency of segments is termed the genome formula (GF). Thus far, formal studies quantifying the GF have been performed for well-characterised virus-host systems in experimental settings using RT-qPCR. However, to understand GF variation in natural populations or novel virus-host systems, a comparison of several methods for GF estimation including high-throughput sequencing (HTS) based methods is needed. Currently, it is unclear how HTS-methods compare a golden standard, such as RT-qPCR. Here we show a comparison of multiple GF quantification methods (RT-qPCR, RT-digital PCR, Illumina RNAseq and Nanopore direct RNA sequencing) using three host plants (Nicotiana tabacum, Nicotiana benthamiana, and Chenopodium quinoa) infected with cucumber mosaic virus (CMV), a tripartite RNA virus. Our results show that all methods give roughly similar results, though there is a significant method effect on genome formula estimates. While the RT-qPCR and RT-dPCR GF estimates are congruent, the GF estimates from HTS methods deviate from those found with PCR. Our findings emphasize the need to tailor the GF quantification method to the experimental aim, and highlight that it may not be possible to compare HTS and PCR-based methods directly. The difference in results between PCR-based methods and HTS highlights that the choice of quantification technique is not trivial.

Application of One-Step Reverse Transcription Droplet Digital PCR for Dengue Virus Detection and Quantification in Clinical Specimens

Detection and quantification of viruses in laboratory and clinical samples are standard assays in dengue virus (DENV) studies. The quantitative reverse transcription polymerase chain reaction (qRT-PCR) is considered to be the standard for DENV detection and quantification due to its high sensitivity. However, qRT-PCR offers only quantification relative to a standard curve and consists of several "in-house" components resulting in interlaboratory variations. We developed and optimized a protocol for applying one-step RT-droplet digital PCR (RT-ddPCR) for DENV detection and quantification. The lower limit of detection (LLOD95) and the lower limit of quantification (LLOQ) for RT-ddPCR were estimated to be 1.851 log10-copies/reaction and 2.337 log10-copies/reaction, respectively. The sensitivity of RT-ddPCR was found to be superior to qRT-PCR (94.87% vs. 90.38%, p = 0.039) while no false positives were detected. Quantification of DENV in clinical samples was independently performed in three laboratories showing interlaboratory variations with biases <0.5 log10-copies/mL. The RT-ddPCR protocol presented here could help harmonize DENV quantification results and improve findings in the field such as identifying a DENV titer threshold correlating with disease severity.

Current Developments and Challenges in Plant Viral Diagnostics: A Systematic Review

Plant viral diseases are the foremost threat to sustainable agriculture, leading to several billion dollars in losses every year. Many viruses infecting several crops have been described in the literature; however, new infectious viruses are emerging frequently through outbreaks. For the effective treatment and prevention of viral diseases, there is great demand for new techniques that can provide accurate identification on the causative agents. With the advancements in biochemical and molecular biology techniques, several diagnostic methods with improved sensitivity and specificity for the detection of prevalent and/or unknown plant viruses are being continuously developed. Currently, serological and nucleic acid methods are the most widely used for plant viral diagnosis. Nucleic acid-based techniques that amplify target DNA/RNA have been evolved with many variants. However, there is growing interest in developing techniques that can be based in real-time and thus facilitate in-field diagnosis. Next-generation sequencing (NGS)-based innovative methods have shown great potential to detect multiple viruses simultaneously; however, such techniques are in the preliminary stages in plant viral disease diagnostics. This review discusses the recent progress in the use of NGS-based techniques for the detection, diagnosis, and identification of plant viral diseases. New portable devices and technologies that could provide real-time analyses in a relatively short period of time are prime important for in-field diagnostics. Current development and application of such tools and techniques along with their potential limitations in plant virology are likewise discussed in detail.

Digital PCR: What Relevance to Plant Studies?

Simple Summary

Digital PCR is a third-generation technology based on the subdivision of the analytical sample into numerous partitions that are amplified individually. This review presents the major applications of digital PCR (dPCR) technology developed so far in the field of plant science. In greater detail, dPCR assays have been developed to trace genetically modified plant components, pathogenic and non-pathogenic microorganisms, and plant species. Other applications have concerned the study of the aspects of structural and functional genetics.

Abstract

Digital PCR (dPCR) is a breakthrough technology that able to provide sensitive and absolute nucleic acid quantification. It is a third-generation technology in the field of nucleic acid amplification. A unique feature of the technique is that of dividing the sample into numerous separate compartments, in each of which an independent amplification reaction takes place. Several instrumental platforms have been developed for this purpose, and different statistical approaches are available for reading the digital output data. The dPCR assays developed so far in the plant science sector were identified in the literature, and the major applications, advantages, disadvantages, and applicative perspectives of the technique are presented and discussed in this review.

Moving from qPCR to Chip Digital PCR Assays for Tracking of some Fusarium Species Causing Fusarium Head Blight in Cereals

Fusarium Head Blight (FHB) is one of the major diseases affecting small-grain cereals, worldwide spread and responsible for severe yield and quality losses annually. Diagnostic tools, able to track Fusarium species even in the early stages of infection, can contribute to mycotoxins' risk control. Among DNA-based technologies for Fusarium detection, qPCR (single and multiplex assays) is currently the most applied method. However, pathogen diagnostics is now enforced by digital PCR (dPCR), a breakthrough technology that provides ultrasensitive and absolute nucleic acid quantification. In our work, a panel of chip digital PCR assays was developed to quantify Fusarium graminearum, F.culmorum, F. sporotrichioides, F. poae and F. avenaceum. The primers/probes combinations were evaluated on pure fungal samples with cdPCR technique, in comparison with the qPCR approach. Moreover, the cdPCR assays were applied to quantify Fusarium in durum wheat and oat samples, naturally contaminated or spiked with fungal DNA. For a better evaluation of infection level in plants, duplex assays were developed, able to co-amplify both plant and fungal DNA. To the best of our knowledge, this is the first study directed to the application of digital PCR to Fusarium diagnosis in plants.

A Chip Digital PCR Assay for Quantification of Common Wheat Contamination in Pasta Production Chain

Pasta, the Italian product par excellence, is made of pure durum wheat. The use of Triticum durum derived semolina is in fact mandatory for Italian pasta, in which Triticum aestivum species is considered a contamination that must not exceed the 3% maximum level. Over the last 50 years, various electrophoretic, chemical, and immuno-chemical methods have been proposed aimed to track the possible presence of common wheat in semolina and pasta. More recently, a new generation of methods, based on DNA (DeoxyriboNucleic Acid) analysis, has been developed to this aim. Species traceability can be now enforced by a new technology, namely digital Polymerase Chain Reaction (dPCR) which quantify the number of target sequence present in a sample, using limiting dilutions, PCR, and Poisson statistics. In our work we have developed a duplex chip digital PCR (cdPCR) assay able to quantify common wheat presence along pasta production chain, from raw materials to final products. The assay was verified on reference samples at known level of common wheat contamination and applied to commercial pastas sampled in the Italian market.