Biological characterization of Physostegia chlorotic mottle virus, an emergent virus infecting vegetables in diversified production systems.

In 2014, Physostegia chlorotic mottle virus (PhCMoV) was discovered in Austria in Physostegia virginiana. Subsequent collaborative efforts established a link between the virus and severe fruit symptoms on important crops like tomato, eggplant, and cucumber across nine European countries. Thereafter, specific knowledge gaps, which are crucial to assess the risks PhCMoV can pose for the production and how to manage it, needed to be addressed. In this study, the transmission, prevalence, and disease severity of PhCMoV were examinated. This investigation led to the identification of PhCMoV presence in a new country, Switzerland. Furthermore, our research indicates that the virus was already present in Europe 30 years ago. Bioassays demonstrated PhCMoV can result in up to 100% tomato yield losses depending on the phenological stage of the plant at the time of infection. PhCMoV was found to naturally infect 12 new host plant species across eight families, extending its host range to 21 plant species across 15 plant families. The study also identified a polyphagous leafhopper (genus Anaceratagallia) as a natural vector of PhCMoV. Overall, PhCMoV was widespread in small-scale diversified vegetable farms in Belgium where tomato is grown in soil under tunnels, occurring in approximately one-third of such farms. However, outbreaks were sporadic, and were associated at least once with the cultivation in tomato tunnels of perennial plants that can serve as a reservoir host for the virus and its vector. To further explore this phenomenon and manage the virus, studying the ecology of the vector would be beneficial.

Correction: Haegeman et al. Looking beyond Virus Detection in RNA Sequencing Data: Lessons Learned from a Community-Based Effort to Detect Cellular Plant Pathogens and Pests. Plants 2023, 12, 2139.

In the original publication [...].

First report of Melon chlorotic spot virus in cultivated sorrel (Rumex acetosa) in Belgium.

In 2020, symptoms of putative viral origin were observed on 7% of tomatoes in an organic vegetable farm in Belgium (deformed uneven ripened fruits, vein clearing, mosaic and purple leaves, stunted plants). The leaves of twenty symptomatic plants were collected, pooled and screened for viruses using high throughput sequencing technologies (HTS) on Illumina NextSeq500 following a virion-associated nucleic acid (VANA) protocol (Temple et al., 2021, Be_SL1). In total, 3,665,498 reads (PE150) were generated. Bioinformatic analyses (denovo assembly, tblastx search on NCBI and mapping) using Geneious Prime® 2020.1.2 revealed the presence of three viruses known to infect tomatoes: Physostegia chlorotic mottle virus (PhCMoV), 547,142 reads map on NC_055466, potato virus Y (PVY), 4056 reads map on MW595184, and melon chlorotic spot virus (MeCSV), 55 reads mapped to six out of the eight different MeCSV segments (NC_040448-55). Tomato plants have already been artificially inoculated by MeCSV (Lecoq et al., 2019) but this detection (confirmed by independent RT-PCR on the pooled sample) is the first one in natural condition on farm. The high prevalence of symptoms triggered the research of alternative perennial hosts that can serve as a reservoir during inter-cropping season. One plant of Rumex acetosa showing vein clearing (CT-122) was collected in the same greenhouse the year after. Total RNA was extracted, followed by ribodepletion, and Illumina HTS using the protocol described in Temple et al., (2021) for Be_GP1. In total, 4,549,721 PE150 reads were obtained and bioinformatic analyses confirmed the presence of MeCSV (8,816 reads mapped on eight RNA segments NC_040448-55 with an average 96,52% coverage of the reference sequences, supplementary table 1) and suggested the presence of an unclassified partitivirus. Consensus sequences were extracted for each segment of MeCSV (OQ818038-45) and showed between 83% and 87% of nucleotide identity with the reference sequences NC_040448-55. RNA1 segment was used to design MeCSV-specific RT-PCR primers for detection (MeCSV-125F 5'-TTTAAGGCCAGATCCAGAGGTTC-3'/ MeCSV-498R 5'-TGGATGTGACAACCTGGTAGTAC-3'). Thereafter, in July 2022, 42 R. acetosa plants were collected in the same greenhouse. Among them, seven plants showed vein clearing, two showed yellowing with necrosis, two exhibited yellowing and vein clearing (Supplementary figure 1), and one showed mosaic. The 42 plants were subjected to RNA extraction and RT-PCR for MeCSV (Supplementary figure 2) and PhCMoV detection. MeCSV was detected in 13 plants (two asymptomatic plants and all the symptomatic plants except the one exhibiting mosaic where PhCMoV was detected). PhCMoV was also detected in three plants with vein clearing, one with yellowing and one of the two asymptomatic plants infected by MeCSV. Our results report the first detection of MeCSV in R. acetosa and the first detection of MeCSV in Belgium. In addition, according to the hierarchical approach for assessing causal relationships in plant virology (Fox et al., 2020), a preliminary association was observed between symptoms and MeCSV detection [6% prevalence on asymptomatic plants and 92% prevalence on diseased plants (from which seven symptomatic samples were not co-infected by PhCMoV)]. Symptom causality should be further investigated but this results are important for disease management because they suggested that cultivated perennial R. acetosa may serve as a reservoir for two emergent plant viruses (PhCMoV and MeCSV) (Lecoq et al., 2019, Temple et al., 2021).

Cont-ID: detection of sample cross-contamination in viral metagenomic data.

BACKGROUND: High-throughput sequencing (HTS) technologies completed by the bioinformatic analysis of the generated data are becoming an important detection technique for virus diagnostics. They have the potential to replace or complement the current PCR-based methods thanks to their improved inclusivity and analytical sensitivity, as well as their overall good repeatability and reproducibility. Cross-contamination is a well-known phenomenon in molecular diagnostics and corresponds to the exchange of genetic material between samples. Cross-contamination management was a key drawback during the development of PCR-based detection and is now adequately monitored in routine diagnostics. HTS technologies are facing similar difficulties due to their very high analytical sensitivity. As a single viral read could be detected in millions of sequencing reads, it is mandatory to fix a detection threshold that will be informed by estimated cross-contamination. Cross-contamination monitoring should therefore be a priority when detecting viruses by HTS technologies. RESULTS: We present Cont-ID, a bioinformatic tool designed to check for cross-contamination by analysing the relative abundance of virus sequencing reads identified in sequence metagenomic datasets and their duplication between samples. It can be applied when the samples in a sequencing batch have been processed in parallel in the laboratory and with at least one specific external control called Alien control. Using 273 real datasets, including 68 virus species from different hosts (fruit tree, plant, human) and several library preparation protocols (Ribodepleted total RNA, small RNA and double-stranded RNA), we demonstrated that Cont-ID classifies with high accuracy (91%) viral species detection into (true) infection or (cross) contamination. This classification raises confidence in the detection and facilitates the downstream interpretation and confirmation of the results by prioritising the virus detections that should be confirmed. CONCLUSIONS: Cross-contamination between samples when detecting viruses using HTS (Illumina technology) can be monitored and highlighted by Cont-ID (provided an alien control is present). Cont-ID is based on a flexible methodology relying on the output of bioinformatics analyses of the sequencing reads and considering the contamination pattern specific to each batch of samples. The Cont-ID method is adaptable so that each laboratory can optimise it before its validation and routine use.

Going beyond consensus genome sequences: An innovative SNP-based methodology reconstructs different Ugandan cassava brown streak virus haplotypes at a nationwide scale in Rwanda.

Cassava Brown Streak Disease (CBSD), which is caused by cassava brown streak virus (CBSV) and Ugandan cassava brown streak virus (UCBSV), represents one of the most devastating threats to cassava production in Africa, including in Rwanda where a dramatic epidemic in 2014 dropped cassava yield from 3.3 million to 900,000 tonnes (1). Studying viral genetic diversity at the genome level is essential in disease management, as it can provide valuable information on the origin and dynamics of epidemic events. To fill the current lack of genome-based diversity studies of UCBSV, we performed a nationwide survey of cassava ipomovirus genomic sequences in Rwanda by high-throughput sequencing (HTS) of pools of plants sampled from 130 cassava fields in thirteen cassava-producing districts, spanning seven agro-ecological zones with contrasting climatic conditions and different cassava cultivars. HTS allowed the assembly of a nearly complete consensus genome of UCBSV in twelve districts. The phylogenetic analysis revealed high homology between UCBSV genome sequences, with a maximum of 0.8 per cent divergence between genomes at the nucleotide level. An in-depth investigation based on Single Nucleotide Polymorphisms (SNPs) was conducted to explore the genome diversity beyond the consensus sequences. First, to ensure the validity of the result, a panel of SNPs was confirmed by independent reverse transcription polymerase chain reaction (RT-PCR) and Sanger sequencing. Furthermore, the combination of fixation index (FST) calculation and Principal Component Analysis (PCA) based on SNP patterns identified three different UCBSV haplotypes geographically clustered. The haplotype 2 (H2) was restricted to the central regions, where the NAROCAS 1 cultivar is predominantly farmed. RT-PCR and Sanger sequencing of individual NAROCAS1 plants confirmed their association with H2. Haplotype 1 was widely spread, with a 100 per cent occurrence in the Eastern region, while Haplotype 3 was only found in the Western region. These haplotypes' associations with specific cultivars or regions would need further confirmation. Our results prove that a much more complex picture of genetic diversity can be deciphered beyond the consensus sequences, with practical implications on virus epidemiology, evolution, and disease management. Our methodology proposes a high-resolution analysis of genome diversity beyond the consensus between and within samples. It can be used at various scales, from individual plants to pooled samples of virus-infected plants. Our findings also showed how subtle genetic differences could be informative on the potential impact of agricultural practices, as the presence and frequency of a virus haplotype could be correlated with the dissemination and adoption of improved cultivars.

The First Virome of a Russian Vineyard.

Among other pathogens, more than 80 viruses infect grapevine. The aim of this work was to study the virome diversity of grapevine viruses and mycoviruses of a vineyard using high-throughput sequencing technologies. The grapevine virome was studied in symptomatic vines of the Rkatsiteli cultivar (V. vinifera) collected at the vineyards of the Krasnodar Krai in Russia. Ribosomal-depleted total RNA and isolated small RNAs were used for library preparation and high-throughput sequencing. Six grapevine-infecting viruses and two viroids were validated by RT-PCR and analyzed phylogenetically. We identified the presence of grapevine leafroll-associated virus 3, grapevine Pinot gris virus, grapevine virus T, grapevine rupestris stem-pitting-associated virus, grapevine fleck virus, and grapevine rupestris vein feathering virus, as well as two viroids, grapevine yellow speckle viroid 1 and hop stunt viroid. We also studied the mycovirome of the vineyard and identified nine viruses with single-stranded positive-sense RNA genomes: alternaria arborescens mitovirus 1, botrytis cinerea mitovirus 1, botrytis cinerea mitovirus 2, botrytis cinerea mitovirus 3, botrytis cinerea mitovirus 4, sclerotinia sclerotiorum mitovirus 3, botrytis cinerea hypovirus 1, grapevine-associated narnavirus 1, and botrytis virus F. In addition, we identified botrytis cinerea hypovirus 1 satellite-like RNA and two single-stranded negative-sense RNA viruses. This is the first study of grapevine mycoviruses in Russia. The obtained result will contribute to the development of biocontrol strategies in the future.

Detection of single nucleotide polymorphisms in virus genomes assembled from high-throughput sequencing data: large-scale performance testing of sequence analysis strategies.

Recent developments in high-throughput sequencing (HTS) technologies and bioinformatics have drastically changed research in virology, especially for virus discovery. Indeed, proper monitoring of the viral population requires information on the different isolates circulating in the studied area. For this purpose, HTS has greatly facilitated the sequencing of new genomes of detected viruses and their comparison. However, bioinformatics analyses allowing reconstruction of genome sequences and detection of single nucleotide polymorphisms (SNPs) can potentially create bias and has not been widely addressed so far. Therefore, more knowledge is required on the limitations of predicting SNPs based on HTS-generated sequence samples. To address this issue, we compared the ability of 14 plant virology laboratories, each employing a different bioinformatics pipeline, to detect 21 variants of pepino mosaic virus (PepMV) in three samples through large-scale performance testing (PT) using three artificially designed datasets. To evaluate the impact of bioinformatics analyses, they were divided into three key steps: reads pre-processing, virus-isolate identification, and variant calling. Each step was evaluated independently through an original, PT design including discussion and validation between participants at each step. Overall, this work underlines key parameters influencing SNPs detection and proposes recommendations for reliable variant calling for plant viruses. The identification of the closest reference, mapping parameters and manual validation of the detection were recognized as the most impactful analysis steps for the success of the SNPs detections. Strategies to improve the prediction of SNPs are also discussed.

Diversity and Pathobiology of an Ilarvirus Unexpectedly Detected in Diverse Plants and Global Sequencing Data.

High-throughput sequencing (HTS) and sequence mining tools revolutionized virus detection and discovery in recent years, and implementing them with classical plant virology techniques results in a powerful approach to characterize viruses. An example of a virus discovered through HTS is Solanum nigrum ilarvirus 1 (SnIV1) (Bromoviridae), which was recently reported in various solanaceous plants from France, Slovenia, Greece, and South Africa. It was likewise detected in grapevines (Vitaceae) and several Fabaceae and Rosaceae plant species. Such a diverse set of source organisms is atypical for ilarviruses, thus warranting further investigation. In this study, modern and classical virological tools were combined to accelerate the characterization of SnIV1. Through HTS-based virome surveys, mining of sequence read archive datasets, and a literature search, SnIV1 was further identified from diverse plant and non-plant sources globally. SnIV1 isolates showed relatively low variability compared with other phylogenetically related ilarviruses. Phylogenetic analyses showed a distinct basal clade of isolates from Europe, whereas the rest formed clades of mixed geographic origin. Furthermore, systemic infection of SnIV1 in Solanum villosum and its mechanical and graft transmissibility to solanaceous species were demonstrated. Near-identical SnIV1 genomes from the inoculum (S. villosum) and inoculated Nicotiana benthamiana were sequenced, thus partially fulfilling Koch's postulates. SnIV1 was shown to be seed-transmitted and potentially pollen-borne, has spherical virions, and possibly induces histopathological changes in infected N. benthamiana leaf tissues. Overall, this study provides information to better understand the diversity, global presence, and pathobiology of SnIV1; however, its possible emergence as a destructive pathogen remains uncertain. [Formula: see text] Copyright © 2023 The Author(s). This is an open access article distributed under the CC BY 4.0 International license.

Looking beyond Virus Detection in RNA Sequencing Data: Lessons Learned from a Community-Based Effort to Detect Cellular Plant Pathogens and Pests.

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.

Impact of Two Phosphorus Fertilizer Formulations on Wheat Physiology, Rhizosphere, and Rhizoplane Microbiota.

Phosphorus (P) is the second most important macronutrient for crop growth and a limiting factor in food production. Choosing the right P fertilizer formulation is important for crop production systems because P is not mobile in soils, and placing phosphate fertilizers is a major management decision. In addition, root microorganisms play an important role in helping phosphorus fertilization management by regulating soil properties and fertility through different pathways. Our study evaluated the impact of two phosphorous formulations (polyphosphates and orthophosphates) on physiological traits of wheat related to yield (photosynthetic parameters, biomass, and root morphology) and its associated microbiota. A greenhouse experiment was conducted using agricultural soil deficient in P (1.49%). Phenotyping technologies were used at the tillering, stem elongation, heading, flowering, and grain-filling stages. The evaluation of wheat physiological traits revealed highly significant differences between treated and untreated plants but not between phosphorous fertilizers. High-throughput sequencing technologies were applied to analyse the wheat rhizosphere and rhizoplane microbiota at the tillering and the grain-filling growth stages. The alpha- and beta-diversity analyses of bacterial and fungal microbiota revealed differences between fertilized and non-fertilized wheat, rhizosphere, and rhizoplane, and the tillering and grain-filling growth stages. Our study provides new information on the composition of the wheat microbiota in the rhizosphere and rhizoplane during growth stages (Z39 and Z69) under polyphosphate and orthophosphate fertilization. Hence, a deeper understanding of this interaction could provide better insights into managing microbial communities to promote beneficial plant-microbiome interactions for P uptake.

Managing the deluge of newly discovered plant viruses and viroids: an optimized scientific and regulatory framework for their characterization and risk analysis.

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.

Co-diet supplementation of low density polyethylene and honeybee wax did not influence the core gut bacteria and associated enzymes of Galleria mellonella larvae (Lepidoptera: Pyralidae) / La suplementación en la dieta conjunta de polietileno de baja densidad y cera de abeja no influyó en las bacterias intestinales centrales y las enzimas asociadas de las larvas de Galleria mellonella (Lepidoptera: Pyralidae)

The current plastic pollution throughout the world is a rising concern that demands the optimization of biodegradation processes. One avenue for this is to identify plastic-degrading bacteria and associated enzymes from the gut bacteria of insect models such as Tenebrio molitor, Plodia interpunctella or Galleria mellonella that have the ability to ingest and rapidly degrade polyethylene. Therefore, this study takes part in understanding the role of the gut bacteria by investigating G. mellonella as a biological model feeding with a diet based on honeybee wax mixed or not with low-density polyethylene. Gut microbiome was analyzed by high throughput 16S rRNA sequencing, and Enterococcaceae and Oxalobacteraceae were found to be the major bacterial families. Compared to the control, the supplementation of low-density polyethylene did not cause significant modification of the bacterial microbiota at community and taxa levels, suggesting bacterial microbiome resilience. The bacterial proteome analysis of gut contents was encouraging for the identification of plastic degrading enzymes such as the phenylacetaldehyde dehydrogenase which participate in styrene degradation. This study allowed a better characterization of the gut bacteria of G. mellonella and provided a basis for the further study of biodegradation of polyethylene based on the bacterial microbiota from insect guts.(AU)

First report of lettuce ring necrosis virus in chili pepper and tomato in Belgium and The Netherlands.

Lettuce ring necrosis virus (LRNV), genus Ophiovirus, was detected by the Netherlands Institute for Vectors, Invasive plants and Plant health (NIVIP) in June and November of 2021 in two samples of chili pepper fruits (Capsicum spp.), both in mixed infection with other viruses. The first sample originated from a production site in Belgium (Sample ID: 40009704) and the second from a production site in the Netherlands (Sample ID: 41115269). One of the fruits of 40009704 showed a light purple circular pattern, while fruits from 41115269 showed colored (ring)spots. The samples were analyzed using Illumina sequencing on a NovaSeq 6000 platform (PE 150) as described previously (Hammond et al., 2021), obtaining 39.9M and 22.8M total reads for 40009704 and 41115269. The corresponding sequence read archives (SRA) were deposited in the NCBI SRA database under BioProject accession number PRJNA917231. From both samples, the nearly complete genome of LRNV (RNA1-4) was obtained and deposited in GenBank (40009704, OQ160823- OQ160826 (7616, 1799, 1502, 1382 nt, mapped reads: 40K, 12K, 114K, 12K , average read coverage (ARC): 0.8K, 0.9K, 11.3K and 1.1K); 41115269, OQ160827- OQ160830 (7616, 1801, 1518, 1389 nt, mapped reads: 112K, 7K, 357K, 55K reads, ARC: 2.2K, 0.6K, 34K and 5.8K)). The shared sequence identities with the Genbank reference sequence of LRNV (NC_006051-NC_006051) were 99.2 and 99.2% (RNA1), 99.1 and 99.1% (RNA2), 98.3 and 98.8% (RNA3), 99.0 and 98.9% (RNA4) for 40009704 and 41115269 respectively. The shared sequence identities between 40009704 and 41115269 were 99.9 (RNA1), 99.0 (RNA2), 99.1 (RNA3) and 99.5% (RNA4). In addition to LRNV, the ophiovirus ranunculus white mottle virus (RWMV) was detected in both samples (OQ160831-OQ160834; OQ160835-OQ160838), while the tobamovirus pepper mild mottle virus (PMMoV) was present in the fruits of 41115269 (OQ160839). Since RWMV has been associated with leaf symptoms in pepper (Gambley et al., 2019; Rivarez et al., 2022) and the colored (ring)spots of 41115269 were very similar to reported symptoms of PMMoV-infected pepper fruits (Martínez-Ochoa et al., 2003), it remains unclear whether LRNV contributed to the observed symptoms. Additionally, LRNV was detected in tomato (Solanum lycopersicum) in Belgium in 2020. In the frame of a metagenomic survey using Virion-Associated Nucleic Acids (VANA)-based protocol (Maclot et al., 2021) on a Nextseq 500 platform (PE 150), partial genome sequences of LRNV were detected in two pools of tomato plants. One pool was made of 44 asymptomatic cultivars from a non-commercial grower (one sample per cultivar) yielding 118K total reads of which 84, 59, 335, and 18 reads mapped on RNA1, 2, 3, and 4, covering 35%, 69%, 100% and 55% of the genome, respectively. The other pool consisted of 15 plants from one cultivar from a production site yielding 3.1M total reads of which 6 and 5 reads mapped on RNA3 and 4, respectively. The detection of LRNV was confirmed for both pooled samples using the real-time RT-PCR method, targeting the CP gene, as described by Maachi et al. (2021). To our knowledge this is the first report of LRNV in pepper anywhere in the world. Additionally, although the disease lettuce ring necrosis in lettuce (Lactuca sativa) has been described in Belgium and the Netherlands before the causal agent was identified (Bos & Huijberts, 1996), this is the first official report of this virus in Belgium and the Netherlands. This publication resulted from pre-publication data sharing of sequences and biological data among plant virologists to provide more context to two independent findings (Hammond et al., 2021).

Long-Term Anthropogenic Management and Associated Loss of Plant Diversity Deeply Impact Virome Richness and Composition of Poaceae Communities.

Modern agriculture has influenced plant virus emergence through ecosystem simplification, introduction of new host species, and reduction in crop genetic diversity. Therefore, it is crucial to better understand virus distributions across cultivated and uncultivated communities in agro-ecological interfaces, as well as virus exchange among them. Here, we advance fundamental understanding in this area by characterizing the virome of three co-occurring replicated Poaceae community types that represent a gradient of grass species richness and management intensity, from highly managed crop monocultures to little-managed, species-rich grasslands. We performed a large-scale study on 950 wild and cultivated Poaceae over 2 years, combining untargeted virome analysis down to the virus species level with targeted detection of three plant viruses. Deep sequencing revealed (i) a diversified and largely unknown Poaceae virome (at least 51 virus species or taxa), with an abundance of so-called persistent viruses; (ii) an increase of virome richness with grass species richness within the community; (iii) stability of virome richness over time but a large viral intraspecific variability; and (iv) contrasting patterns of virus prevalence, coinfections, and spatial distribution among plant communities and species. Our findings highlight the complex structure of plant virus communities in nature and suggest the influence of anthropogenic management on viral distribution and prevalence. IMPORTANCE Because viruses have been mostly studied in cultivated plants, little is known about virus diversity and ecology in less-managed vegetation or about the influence of human management and agriculture on virome composition. Poaceae (grass family)-dominated communities provide invaluable opportunities to examine these ecological issues, as they are distributed worldwide across agro-ecological gradients, are essential for food security and conservation, and can be infected by numerous viruses. Here, we used multiple levels of analysis that considered plant communities, individual plants, virus species, and haplotypes to broaden understanding of the Poaceae virome and to evaluate host-parasite richness relationships within agro-ecological landscapes in our study area. We emphasized the influence of grass diversity and land use on the composition of viral communities and their life history strategies, and we demonstrated the complexity of plant-virus interactions in less-managed grass communities, such as the higher virus prevalence and overrepresentation of mixed virus infection compared to theoretical predictions.

Analysis of the Genetic Diversity of Two Rhopalosiphum Species from China and Europe Based on Nuclear and Mitochondrial Genes.

Population genetic studies can reveal clues about the evolution of adaptive strategies of aphid species in agroecosystems and demonstrate the influence of environmental factors on the genetic diversity and gene flow among aphid populations. To investigate the genetic diversity of two Rhopalosiphum aphid species from different geographical regions, 32 populations (n = 535) of the bird cherry-oat aphid (Rhopalosiphum padi Linnaeus) and 38 populations (n = 808) of the corn leaf aphid (Rhopalosiphum maidis Fitch) from China and Europe were analyzed using one nuclear (elongation factor-1 alpha) and two mitochondrial (cytochrome oxidase I and II) genes. Based on the COI-COII sequencing, two obvious clades between Chinese and European populations and a low level of gene flow (Nm = 0.15) were detected in R. padi, while no geographical-associated genetic variation was found for EF-1α in this species. All genes in R. maidis had low genetic variation, indicating a high level of gene flow (Nm = 5.31 of COI-COII and Nm = 2.89 of EF-1α). Based on the mitochondrial result of R. padi, we concluded that the long distance between China and Europe may be interrupting the gene flow. The discordant results of nuclear gene analyses in R. padi may be due to the slower evolution of nuclear genes compared to mitochondrial genes. The gene exchange may occur gradually with the potential for continuous migration of the aphid. This study facilitates the design of control strategies for these pests.

Co-diet supplementation of low density polyethylene and honeybee wax did not influence the core gut bacteria and associated enzymes of Galleria mellonella larvae (Lepidoptera: Pyralidae).

The current plastic pollution throughout the world is a rising concern that demands the optimization of biodegradation processes. One avenue for this is to identify plastic-degrading bacteria and associated enzymes from the gut bacteria of insect models such as Tenebrio molitor, Plodia interpunctella or Galleria mellonella that have the ability to ingest and rapidly degrade polyethylene. Therefore, this study takes part in understanding the role of the gut bacteria by investigating G. mellonella as a biological model feeding with a diet based on honeybee wax mixed or not with low-density polyethylene. Gut microbiome was analyzed by high throughput 16S rRNA sequencing, and Enterococcaceae and Oxalobacteraceae were found to be the major bacterial families. Compared to the control, the supplementation of low-density polyethylene did not cause significant modification of the bacterial microbiota at community and taxa levels, suggesting bacterial microbiome resilience. The bacterial proteome analysis of gut contents was encouraging for the identification of plastic degrading enzymes such as the phenylacetaldehyde dehydrogenase which participate in styrene degradation. This study allowed a better characterization of the gut bacteria of G. mellonella and provided a basis for the further study of biodegradation of polyethylene based on the bacterial microbiota from insect guts.

The Expanding Menagerie of Prunus-Infecting Luteoviruses.

Members of the genus Luteovirus are responsible for economically destructive plant diseases worldwide. Over the past few years, three luteoviruses infecting Prunus trees have been characterized. However, the biological properties, prevalence, and genetic diversity of those viruses have not yet been studied. High-throughput sequencing of samples of various wild, cultivated, and ornamental Prunus species enabled the identification of four novel species in the genus Luteovirus for which we obtained complete or nearly complete genomes. Additionally, we identified another new putative species recovered from Sequence Read Archive data. Furthermore, we conducted a survey on peach-infecting luteoviruses in eight European countries. Analyses of 350 leaf samples collected from germplasm, production orchards, and private gardens showed that peach-associated luteovirus (PaLV), nectarine stem pitting-associated virus (NSPaV), and a novel luteovirus, peach-associated luteovirus 2 (PaLV2), are present in all countries; the most prevalent virus was NSPaV, followed by PaLV. The genetic diversity of these viruses was also analyzed. Moreover, the biological indexing on GF305 peach indicator plants demonstrated that PaLV and PaLV2, like NSPaV, are transmitted by graft at relatively low rates. No clear viral symptoms have been observed in either graft-inoculated GF305 indicators or different peach tree varieties observed in an orchard. The data generated during this study provide a broader overview of the genetic diversity, geographical distribution, and prevalence of peach-infecting luteoviruses and suggest that these viruses are likely asymptomatic in peach under most circumstances.

Risk factors associated with cassava brown streak disease dissemination through seed pathways in Eastern D.R. Congo.

Vegetatively propagated crops are particularly prone to disease dissemination through their seed systems. Strict phytosanitary measures are important to limit the impact of diseases as illustrated by the potato seed system in Europe. Cassava brown streak disease (CBSD) is a devastating disease caused by two viral species collectively named cassava brown streak viruses (CBSVs). CBSD can cause substantial root yield losses of up to 100% in the worst affected areas and is easily transmitted through stem cuttings. In Eastern and Central Africa, the epidemiology of CBSVs in the local socio-economical context of production remains poorly known while a better understanding would be an asset to properly manage the disease. This lack of information explains partially the limited efficiency of current regulatory schemes in increasing the availability of quality seed to smallholders and mitigating the spread of pests and diseases. This study surveyed the epidemiology of CBSVs in Uvira territory, Eastern D.R. Congo, and its drivers using a multivariate approach combining farmer's interview, field observation, sampling and molecular detection of CBSVs. Investigation on the epidemiology of CBSD revealed that three clusters in the study area could be identified using five most significant factors: (i) symptoms incidence, (ii) number of whiteflies, (iii) types of foliar symptoms, (iv) cutting's pathways and (v) plant age. Among the three clusters identified, one proved to be potentially interesting for seed multiplication activities since the disease pressure was the lowest. Through risk assessment, we also identified several key socio-economic determinants on disease epidemy: (i) factors related to farmer's knowledge and awareness (knowledge of cassava pests and diseases, knowledge of management practices, support from extension services and management strategies applied), (ii) factors related to the geographical location of farmer's fields (proximity to borders, proximity to town, distance to acquire cuttings), as well as (iii) the pathways used to acquire cuttings.

Identification of a novel vitivirus from pineapple in Reunion Island.

We report the complete genome sequence of a novel member of the genus Vitivirus (family Betaflexiviridae, subfamily Trivirinae) infecting pineapple. The complete genome sequence of this virus was obtained from total RNA extracted from pineapple leaf samples collected in Reunion Island, using a combination of high-throughput sequencing technologies. The viral genome is 6,757 nt long, excluding the poly(A) tail, and shares all the hallmarks of vitiviruses. Phylogenetic analysis performed on the replication-associated protein and capsid protein gene sequences unambiguously place this new virus, for which we propose the name "pineapple virus A", in the genus Vitivirus.

Virion-Associated Nucleic Acid-Based Metagenomics: A Decade of Advances in Molecular Characterization of Plant Viruses.

Over the last decade, viral metagenomic studies have resulted in the discovery of thousands of previously unknown viruses. These studies are likely to play a pivotal role in obtaining an accurate and robust understanding of how viruses affect the stability and productivity of ecosystems. Among the metagenomics-based approaches that have been developed since the beginning of the 21st century, shotgun metagenomics applied specifically to virion-associated nucleic acids (VANA) has been used to disentangle the diversity of the viral world. We summarize herein the results of 24 VANA-based studies, focusing on plant and insect samples conducted over the last decade (2010 to 2020). Collectively, viruses from 85 different families were reliably detected in these studies, including capsidless RNA viruses that replicate in fungi, oomycetes, and plants. Finally, strengths and weaknesses of the VANA approach are summarized and perspectives of applications in detection, epidemiological surveillance, environmental monitoring, and ecology of plant viruses are provided. [Formula: see text] Copyright © 2022 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.