Search the repository

A+ | A- | | SLO | ENG

Abstract: Waterborne plant viruses can destroy entire crops, leading not only to high financial losses but also to food shortages. Potato virus Y (PVY) is the most important potato viral pathogen that can also affect other valuable crops. Recently, it has been confirmed that this virus is capable of infecting host plants via water, emphasizing the relevance of using proper strategies to treat recycled water in order to prevent the spread of the infectious agents. Emerging environmentally friendly methods such as hydrodynamic cavitation (HC) provide a great alternative for treating recycled water used for irrigation. In the experiments conducted in this study, laboratory HC based on Venturi constriction with a sample volume of 1 L was used to treat water samples spiked with purified PVY virions. The ability of the virus to infect plants was abolished after 500 HC passes, corresponding to 50 min of treatment under pressure difference of 7 bar. In some cases, shorter treatments of 125 or 250 passes were also sufficient for virus inactivation. The HC treatment disrupted the integrity of viral particles, which also led to a minor damage of viral RNA. Reactive species, including singlet oxygen, hydroxyl radicals, and hydrogen peroxide, were not primarily responsible for PVY inactivation during HC treatment, suggesting that mechanical effects are likely the driving force of virus inactivation. This pioneering study, the first to investigate eukaryotic virus inactivation by HC, will inspire additional research in this field enabling further improvement of HC as a water decontamination technology.
Keywords: hydrodynamic cavitation, potato virus Y, virus inactivation, water decontamination
Published in DiRROS: 16.07.2024; Views: 27; Downloads: 11
Full text (3,43 MB)
This document has many files! More...

Abstract: The advances in high-throughput sequencing (HTS) technologies and bioinformatic tools have provided new opportunities for virus and viroid discovery and diagnostics. Hence, new sequences of viral origin are being discovered and published at a previously unseen rate. Therefore, a collective effort was undertaken to write and propose a framework for prioritizing the biological characterization steps needed after discovering a new plant virus to evaluate its impact at different levels. Even though the proposed approach was widely used, a revision of these guidelines was prepared to consider virus discovery and characterization trends and integrate novel approaches and tools recently published or under development. This updated framework is more adapted to the current rate of virus discovery and provides an improved prioritization for filling knowledge and data gaps. It consists of four distinct steps adapted to include a multi-stakeholder feedback loop. Key improvements include better prioritization and organization of the various steps, earlier data sharing among researchers and involved stakeholders, public database screening, and exploitation of genomic information to predict biological properties.
Keywords: plant viruses and viroids, high throughput sequencing (HTS), biological characterization, plant health, regulatory agencies, Pest Risk Analysis (PRA), virus disease
Published in DiRROS: 12.07.2024; Views: 39; Downloads: 18
Full text (1,09 MB)
This document has many files! More...

Abstract: High-throughput sequencing (HTS), more specifically RNA sequencing of plant tissues, has become an indispensable tool for plant virologists to detect and identify plant viruses. During the data analysis step, plant virologists typically compare the obtained sequences to reference virus databases. In this way, they are neglecting sequences without homologies to viruses, which usually represent the majority of sequencing reads. We hypothesized that traces of other pathogens might be detected in this unused sequence data. In the present study, our goal was to investigate whether total RNA-seq data, as generated for plant virus detection, is also suitable for the detection of other plant pathogens and pests. As proof of concept, we first analyzed RNA-seq datasets of plant materials with confirmed infections by cellular pathogens in order to check whether these non-viral pathogens could be easily detected in the data. Next, we set up a community effort to re-analyze existing Illumina RNA-seq datasets used for virus detection to check for the potential presence of non-viral pathogens or pests. In total, 101 datasets from 15 participants derived from 51 different plant species were re-analyzed, of which 37 were selected for subsequent in-depth analyses. In 29 of the 37 selected samples (78%), we found convincing traces of non-viral plant pathogens or pests. The organisms most frequently detected in this way were fungi (15/37 datasets), followed by insects (13/37) and mites (9/37). The presence of some of the detected pathogens was confirmed by independent (q)PCRs analyses. After communicating the results, 6 out of the 15 participants indicated that they were unaware of the possible presence of these pathogens in their sample(s). All participants indicated that they would broaden the scope of their bioinformatic analyses in future studies and thus check for the presence of non-viral pathogens. In conclusion, we show that it is possible to detect non-viral pathogens or pests from total RNA-seq datasets, in this case primarily fungi, insects, and mites. With this study, we hope to raise awareness among plant virologists that their data might be useful for fellow plant pathologists in other disciplines (mycology, entomology, bacteriology) as well.
Keywords: plant viruses, plant virus detection, plant virology, high-throughput sequencing, RNA sequencing, plant tissues, plant pathogen, diagnostics, high-throughput sequencing, metagenomics, metatranscriptomics
Published in DiRROS: 12.07.2024; Views: 42; Downloads: 11
Full text (1,70 MB)

Abstract: The proliferation of genetically modified organisms (GMOs) presents challenges to GMO testing laboratories and policymakers. Traditional methods, like quantitative real-time PCR (qPCR), face limitations in quantifying the increasing number of GMOs in a single sample. Digital PCR (dPCR), specifically multiplexing, offers a solution by enabling simultaneous quantification of multiple GMO targets. This study explores the use of the Naica six-color Crystal dPCR platform for quantifying five GM soybean lines within a single six-plex assay. Two four-color assays were also developed for added flexibility. These assays demonstrated high specificity, sensitivity (limit of detection or LOD < 25 copies per reaction) and precision (bias to an estimated copy number concentration <15%). Additionally, two approaches for the optimization of data analysis were implemented. By applying a limit-of-blank (LOB) correction, the limit of quantification (LOQ) and LOD could be more precisely determined. Pooling of reactions additionally lowered the LOD, with a two- to eight-fold increase in sensitivity. Real-life samples from routine testing were used to confirm the assays’ applicability for quantifying GM soybean lines in complex samples. This study showcases the potential of the six-color Crystal dPCR platform to revolutionize GMO testing, facilitating comprehensive analysis of GMOs in complex samples.
Keywords: digital PCR, dPCR, quantification, multiplexing, genetically modified organisms, 6-color system, virus diagnostics, virology
Published in DiRROS: 29.03.2024; Views: 306; Downloads: 136
Full text (1,83 MB)
This document has many files! More...

Keywords: viral carcinogenesis, simian virus 40, mesothelioma, T antigen
Published in DiRROS: 08.03.2024; Views: 268; Downloads: 66
Full text (427,91 KB)