Benchmarking of virome metagenomic analysis approaches using a large, 60+ members, viral synthetic community.

IMPORTANCE: We report here efforts to benchmark performance of two widespread approaches for virome analysis, which target either virion-associated nucleic acids (VANA) or highly purified double-stranded RNAs (dsRNAs). This was achieved using synthetic communities of varying complexity levels, up to a highly complex community of 72 viral agents (115 viral molecules) comprising isolates from 21 families and 61 genera of plant viruses. The results obtained confirm that the dsRNA-based approach provides a more complete representation of the RNA virome, in particular, for high complexity ones. However, for viromes of low to medium complexity, VANA appears a reasonable alternative and would be the preferred choice if analysis of DNA viruses is of importance. Several parameters impacting performance were identified as well as a direct relationship between the completeness of virome description and sample sequencing depth. The strategy, results, and tools used here should prove useful in a range of virome analysis efforts.

Glucosylation prevents plant defense activation in phloem-feeding insects.

The metabolic adaptations by which phloem-feeding insects counteract plant defense compounds are poorly known. Two-component plant defenses, such as glucosinolates, consist of a glucosylated protoxin that is activated by a glycoside hydrolase upon plant damage. Phloem-feeding herbivores are not generally believed to be negatively impacted by two-component defenses due to their slender piercing-sucking mouthparts, which minimize plant damage. However, here we document that glucosinolates are indeed activated during feeding by the whitefly Bemisia tabaci. This phloem feeder was also found to detoxify the majority of the glucosinolates it ingests by the stereoselective addition of glucose moieties, which prevents hydrolytic activation of these defense compounds. Glucosylation of glucosinolates in B. tabaci was accomplished via a transglucosidation mechanism, and two glycoside hydrolase family 13 (GH13) enzymes were shown to catalyze these reactions. This detoxification reaction was also found in a range of other phloem-feeding herbivores.

High molecular diversity of full-length genome sequences of zucchini yellow fleck virus from Europe.

Zucchini yellow fleck virus (ZYFV), genus Potyvirus, is the causal agent of a disease of cucurbits. The genome sequences of seven ZYFV isolates of different origin were determined, two of which were reconstructed from a squash (Cucurbita sp.) collected in 2017 in Greece, while the others, accessions from the DSMZ Plant Virus Collection, were from samples collected in Italy, Greece, and France in the 1980s and 1990s. A high level of molecular diversity, well dispersed along the genome, was observed, but this was within the limits for assignment of the virus isolates to the same species. P1 was the most diverse gene, and isolates from squash contained an insertion in this gene.

A novel nepovirus causing a chlorotic fleck disease on common bean (Phaseolus vulgaris L.).

Two common bean leaf samples from Ethiopia that had shown chlorotic fleck and veinal mosaic symptoms but tested ELISA-negative for known viruses were mechanically transmitted to herbaceous hosts to obtain virus isolates ET-773/4 and ET-779. Virus purification from Chenopodium quinoa systemically infected with ET-773/4 yielded icosahedral particles measuring ~ 30 nm in diameter and containing a single capsid protein of ~ 58 kDa, suggesting a nepovirus infection. Analysis of nucleotide sequences generated from RNA1 and RNA2 of the isolates indicated that they represent a distinct virus species in the genus Nepovirus. Surprisingly, the most closely related sequence in the GenBank database was that of Hobart nepovirus 3, an incompletely described metagenomic sequence obtained from honey bees in Tasmania. This new nepovirus from Ethiopia is provisionally named "bean chlorotic fleck virus".

Characterization of yam mosaic viruses from Brazil reveals a new phylogenetic group and possible incursion from the African continent.

Yam (Dioscorea spp.) is an important crop for smallholder farmers in the Northeast region of Brazil. Wherever yam is grown, diseases caused by yam mosaic virus (YMV) are prevalent. In the present study, the diversity of YMV infecting Dioscorea cayennensis-rotundata was analyzed. In addition, five species of Dioscorea (D. alata, D. altissima, D. bulbifera, D. subhastata, and D. trifida) commonly found in Brazil were analyzed using ELISA and high-throughput sequencing (HTS). YMV was detected only in D. cayennensis-rotundata, of which 66.7% of the samples tested positive in ELISA. Three YMV genome sequences were assembled from HTS and one by Sanger sequencing to group the sequences in a clade phylogenetically distinct from YMV from other origins. Temporal phylogenetic analyses estimated the mean evolutionary rate for the CP gene of YMV as 1.76 × 10-3 substitutions per site per year, and the time to the most recent common ancestor as 168.68 years (95% Highest Posterior Density, HPD: 48.56-363.28 years), with a most likely geographic origin in the African continent. The data presented in this study contribute to reveal key aspects of the probable epidemiological history of YMV in Brazil.

Molecular analysis of Greek isolates of cucumber mosaic virus from vegetables shows a low prevalence of satellite RNAs and suggests the presence of host-associated virus strains.

Cucumber mosaic virus (CMV) is a generalist pathogen that infects many economically important crops in Greece. The present study was designed to evaluate the genetic variability of Greek CMV isolates in combination with their satellite RNAs (satRNAs). To achieve this goal, 77 CMV isolates were collected from symptomatic Greek vegetables, mainly tomatoes and cucurbits, alongside their neighboring crops, during a four-year period from 2015 to 2018. Phylogenetic analysis of a partial coat protein (CP) gene segment revealed that all of the isolates belong to CMV subgroups IA and IB and that they are closely related to previously reported Greek isolates. It should be noted, however, that the latter mainly included tomato isolates. Network analysis of the evolutionary relationships among the CP sequences of the Greek isolates in comparison to the corresponding sequences obtained from the GenBank database indicated two predominant common ancestors and at least three differentiated peripherals, and possibly host-associated (tomatoes, legumes, cucurbits) haplogroups (strain groups). More specifically, host-adaptive evolution can be postulated regarding the tomato isolates in subgroup IB. Necrogenic or non-necrogenic satRNAs were detected in four samples from tomato and melon, and this is the first report of non-necrogenic satRNAs in CMV in Greece.

Origin-Destination Flow Estimation from Link Count Data Only.

All established models in transportation engineering that estimate the numbers of trips between origins and destinations from vehicle counts use some form of a priori knowledge of the traffic. This paper, in contrast, presents a new origin-destination flow estimation model that uses only vehicle counts observed by traffic count sensors; it requires neither historical origin-destination trip data for the estimation nor any assumed distribution of flow. This approach utilises a method of statistical origin-destination flow estimation in computer networks, and transfers the principles to the domain of road traffic by applying transport-geographic constraints in order to keep traffic embedded in physical space. Being purely stochastic, our model overcomes the conceptual weaknesses of the existing models, and additionally estimates travel times of individual vehicles. The model has been implemented in a real-world road network in the city of Melbourne, Australia. The model was validated with simulated data and real-world observations from two different data sources. The validation results show that all the origin-destination flows were estimated with a good accuracy score using link count data only. Additionally, the estimated travel times by the model were close approximations to the observed travel times in the real world.

A Recurrent Deep Network for Estimating the Pose of Real Indoor Images from Synthetic Image Sequences.

Recently, deep convolutional neural networks (CNN) have become popular for indoor visual localisation, where the networks learn to regress the camera pose from images directly. However, these approaches perform a 3D image-based reconstruction of the indoor spaces beforehand to determine camera poses, which is a challenge for large indoor spaces. Synthetic images derived from 3D indoor models have been used to eliminate the requirement of 3D reconstruction. A limitation of the approach is the low accuracy that occurs as a result of estimating the pose of each image frame independently. In this article, a visual localisation approach is proposed that exploits the spatio-temporal information from synthetic image sequences to improve localisation accuracy. A deep Bayesian recurrent CNN is fine-tuned using synthetic image sequences obtained from a building information model (BIM) to regress the pose of real image sequences. The results of the experiments indicate that the proposed approach estimates a smoother trajectory with smaller inter-frame error as compared to existing methods. The achievable accuracy with the proposed approach is 1.6 m, which is an improvement of approximately thirty per cent compared to the existing approaches. A Keras implementation can be found in our Github repository.

Identification of a novel nanovirus in parsley.

Using next-generation sequencing to characterize agents associated with a severe stunting disease of parsley from Germany, we identified a hitherto undescribed virus. We sequenced total RNA and rolling-circle-amplified DNA from diseased plants. The genome sequence of the virus shows that it is a member of the genus Nanovirus, but it lacks DNA-U4. In addition to the seven genomic DNAs of the virus, we identified a second DNA-R and seven distinct alphasatellites associated with the disease. We propose the name "parsley severe stunt associated virus" (PSSaV) for this novel nanovirus.

Molecular analysis of maize (Zea mays L.)-infecting mastreviruses in Ethiopia reveals marked diversity of virus genomes and a novel species.

Maize (Zea mays L.) is host for more than 50 virus species worldwide with Maize streak virus (MSV) (genus Mastrevirus) causing significant yield losses in Africa. A survey for viruses infecting maize was conducted in major growing regions of Ethiopia. To test for DNA viruses, in particular mastreviruses, rolling circle amplification was performed for the analysis of virus composition in assayed samples. Following the analysis of the entire virus genomes, three genetic groups, each representing distinct virus species, were identified. The first group was almost identical with the A-strain of MSV. The next sequence-cluster shared 96-98% identity with isolates of Maize streak reunion virus (MSRV) confirming the presence of this virus also in continental East Africa. Sequence analysis of additional virus genomes (each 2846 nt) in length revealed only a limited 70-71% nt identity with MSRV isolates and an even lower identity (< 64%) with sequences of mastreviruses described elsewhere. Our analysis suggests a novel virus species, which is tentatively named maize streak dwarfing virus (MSDV). The pairwise comparison of capsid protein and replication-associated protein (Rep) of the novel species revealed a limited identity of 63% and 68% with the respective protein sequences of MSRV. The incidence of the virus species in the maize regions of Ethiopia was studied across 89 samples collected during four growing seasons. PCR analysis with general and specific mastrevirus primers showed that MSV is the most incident virus (39.3%) followed by MSRV (14.6%) and MSDV (12.4%). Identification of three different mastrevirus species in a confined geographical location on the same host, maize, is unprecedented, and suggests that Ethiopia may be one of the potential hot spots for diversity of maize-infecting mastreviruses.

Correction to: Molecular analysis of maize (Zea mays L.)-infecting mastreviruses in Ethiopia reveals marked diversity of virus genomes and a novel species.

The original version of this article unfortunately contained errors in the "Results" section.

Localization of cassava brown streak virus in Nicotiana rustica and cassava Manihot esculenta (Crantz) using RNAscope® in situ hybridization.

BACKGROUND: Cassava brown streak disease (CBSD) has a viral aetiology and is caused by viruses belonging to the genus Ipomovirus (family Potyviridae), Cassava brown streak virus (CBSV) and Ugandan cassava brown streak virus (UCBSV). Molecular and serological methods are available for detection, discrimination and quantification of cassava brown streak viruses (CBSVs) in infected plants. However, precise determination of the viral RNA localization in infected host tissues is still not possible pending appropriate methods. RESULTS: We have developed an in situ hybridization (ISH) assay based on RNAscope® technology that allows the sensitive detection and localization of CBSV RNA in plant tissues. The method was initially developed in the experimental host Nicotiana rustica and was then further adapted to cassava. Highly sensitive and specific detection of CBSV RNA was achieved without background and hybridization signals in sections prepared from non-infected tissues. The tissue tropism of CBSV RNAs appeared different between N. rustica and cassava. CONCLUSIONS: This study provides a robust method for CBSV detection in the experimental host and in cassava. The protocol will be used to study CBSV tropism in various cassava genotypes, as well as CBSVs/cassava interactions in single and mixed infections.

Variability in P1 gene redefines phylogenetic relationships among cassava brown streak viruses.

BACKGROUND: Cassava brown streak disease is emerging as the most important viral disease of cassava in Africa, and is consequently a threat to food security. Two distinct species of the genus Ipomovirus (family Potyviridae) cause the disease: Cassava brown streak virus (CBSV) and Ugandan cassava brown streak virus (UCBSV). To understand the evolutionary relationships among the viruses, 64 nucleotide sequences from the variable P1 gene from major cassava producing areas of east and central-southern Africa were determined. METHODS: We sequenced an amplicon of the P1 region of 31 isolates from Malawi and Tanzania. In addition to these, 33 previously reported sequences of virus isolates from Uganda, Kenya, Tanzania, Malawi and Mozambique were added to the analysis. RESULTS: Phylogenetic analyses revealed three major P1 clades of Cassava brown streak viruses (CBSVs): in addition to a clade of most CBSV and a clade containing all UCBSV, a novel, intermediate clade of CBSV isolates which has been tentatively called CBSV-Tanzania (CBSV-TZ). Virus isolates of the distinctive CBSV-TZ had nucleotide identities as low as 63.2 and 63.7% with other members of CBSV and UCBSV respectively. CONCLUSIONS: Grouping of P1 gene sequences indicated for distinct sub-populations of CBSV, but not UCBSV. Representatives of all three clades were found in both Tanzania and Malawi.

Analysis of the complete genome sequence of euphorbia ringspot virus, an atypical member of the genus Potyvirus.

The complete genome sequence of an isolate of euphorbia ringspot virus (EuRSV) was determined by deep sequencing and rapid amplification of cDNA ends (RACE) RT-PCR. It has an RNA genome of 10,154 nucleotides in size, excluding the poly(A) tail, and encodes a polyprotein of 3265 amino acids. Phylogenetic analysis from this study supports the earlier taxonomic assignment to the genus Potyvirus; however, a gene encoding the HAM1h protein, inserted between NIb and CP of the EuRSV genome, which was previously only observed for cassava brown streak virus and Ugandan cassava brown streak virus of the genus Ipomovirus, is an unusual feature of this potyvirus, which otherwise has typical potyvirus genome features.

Virus surveys of Capsicum spp. in the Republic of Benin reveal the prevalence of pepper vein yellows virus and the identification of a previously uncharacterised polerovirus species.

Surveys were conducted in 2014 and 2015 in Southern and Northern Benin, respectively, to identify the viruses infecting peppers (Capsicum spp.). The samples were screened by ELISA for cucumber mosaic virus (CMV), pepper veinal mottle virus (PVMV), potato virus Y (PVY) and tomato yellow leaf curl virus (TYLCV). A generic reverse transcription PCR (RT-PCR) was used to test for the presence of poleroviruses. ELISA tests confirmed the prevalence of all viruses, while the RT-PCR detected pepper vein yellows virus (PeVYV) which is reported for the first time in Benin. A further, divergent polerovirus isolate was detected from a single pepper sample originating from southern Benin. Screening of samples collected from solanaceous plants during virus surveys in Mali (conducted in 2009) also detected this divergent polerovirus isolate in two samples from African eggplants. The complete genome sequence was obtained from the Mali isolate using transcriptome sequencing and by conventional Sanger sequencing of overlapping RT-PCR products. Based on the sequence characteristics of this isolate we propose a new polerovirus species, African eggplant yellowing virus (AeYV).

High-resolution identification and abundance profiling of cassava (Manihot esculenta Crantz) microRNAs.

BACKGROUND: Small RNAs (sRNAs) are endogenous sRNAs that play regulatory roles in plant growth, development, and biotic and abiotic stress responses. In plants, one subset of sRNAs, microRNAs (miRNAs) exhibit tissue-differential expression and regulate gene expression mainly through direct cleavage of mRNA or indirectly via production of secondary phased siRNAs (phasiRNAs) that silence cognate target transcripts in trans. RESULTS: Here, we have identified cassava (Manihot esculenta Crantz) miRNAs using high resolution sequencing of sRNA libraries from leaf, stem, callus, male and female flower tissues. To analyze the data, we built a cassava genome database and, via sequence analysis and secondary structure prediction, 38 miRNAs not previously reported in cassava were identified. These new cassava miRNAs included two miRNAs not previously been reported in any plant species. The miRNAs exhibited tissue-differential accumulation as confirmed by quantitative RT-PCR and Northern blot analysis, largely reflecting levels observed in sequencing data. Some of the miRNAs identified were predicted to trigger production of secondary phased siRNAs (phasiRNAs) from 80 PHAS loci. CONCLUSIONS: Cassava is a woody perennial shrub, grown principally for its starch-rich storage roots, which are rich in calories. In this study, new miRNAs were identified and their expression was validated using qRT-PCR of RNA from five different tissues. The data obtained expand the list of annotated miRNAs and provide additional new resources for cassava improvement research.

A Time-Aware Routing Map for Indoor Evacuation.

Knowledge of dynamic environments expires over time. Thus, using static maps of the environment for decision making is problematic, especially in emergency situations, such as evacuations. This paper suggests a fading memory model for mapping dynamic environments: a mechanism to put less trust on older knowledge in decision making. The model has been assessed by simulating indoor evacuations, adopting and comparing various strategies in decision making. Results suggest that fading memory generally improves this decision making.

Automated Urban Travel Interpretation: A Bottom-up Approach for Trajectory Segmentation.

Understanding travel behavior is critical for an effective urban planning as well as for enabling various context-aware service provisions to support mobility as a service (MaaS). Both applications rely on the sensor traces generated by travellers' smartphones. These traces can be used to interpret travel modes, both for generating automated travel diaries as well as for real-time travel mode detection. Current approaches segment a trajectory by certain criteria, e.g., drop in speed. However, these criteria are heuristic, and, thus, existing approaches are subjective and involve significant vagueness and uncertainty in activity transitions in space and time. Also, segmentation approaches are not suited for real time interpretation of open-ended segments, and cannot cope with the frequent gaps in the location traces. In order to address all these challenges a novel, state based bottom-up approach is proposed. This approach assumes a fixed atomic segment of a homogeneous state, instead of an event-based segment, and a progressive iteration until a new state is found. The research investigates how an atomic state-based approach can be developed in such a way that can work in real time, near-real time and offline mode and in different environmental conditions with their varying quality of sensor traces. The results show the proposed bottom-up model outperforms the existing event-based segmentation models in terms of adaptivity, flexibility, accuracy and richness in information delivery pertinent to automated travel behavior interpretation.

First full-length genome sequence of the polerovirus luffa aphid-borne yellows virus (LABYV) reveals the presence of at least two consensus sequences in an isolate from Thailand.

Luffa aphid-borne yellows virus (LABYV) was proposed as the name for a previously undescribed polerovirus based on partial genome sequences obtained from samples of cucurbit plants collected in Thailand between 2008 and 2013. In this study, we determined the first full-length genome sequence of LABYV. Based on phylogenetic analysis and genome properties, it is clear that this virus represents a distinct species in the genus Polerovirus. Analysis of sequences from sample TH24, which was collected in 2010 from a luffa plant in Thailand, reveals the presence of two different full-length genome consensus sequences.

Optimal Strategies for Interception, Detection, and Eradication in Plant Biosecurity.

The introduction of invasive species causes damages from the economic and ecological point of view. Interception of plant pests and eradication of the established populations are two management options to prevent or limit the risk posed by an invasive species. Management options generate costs related to the interception at the point of entry, and the detection and eradication of established field populations. Risk managers have to decide how to allocate resources between interception, field detection, containment, and eradication minimizing the expected total costs. In this work is considered an optimization problem aiming at determining the optimal allocation of resources to minimize the expected total costs of the introduction of Bemisia tabaci-transmitted viruses in Europe. The optimization problem takes into account a probabilistic model for the estimation of the percentage of viruliferous insect populations arriving through the trade of commodities, and a population dynamics model describing the process of the vector populations' establishment and spread. The time of field detection of viruliferous insect populations is considered as a random variable. The solution of the optimization problem allows to determine the optimal allocation of the search effort between interception and detection/eradication. The behavior of the search effort as a function of efficacy or search in interception and in detection is then analyzed. The importance of the vector population growth rate and the probability of virus establishment are also considered in the analysis of the optimization problem.