A crucial factor in mitigating respiratory viral outbreaks is early determination of the duration of the incubation period and, accordingly, the required quarantine time for potentially exposed individuals. At the time of the COVID-19 pandemic, optimization of quarantine regimes becomes paramount for public health, societal well-being, and global economy. However, biological factors that determine the duration of the virus incubation period remain poorly understood.We demonstrate a strong positive correlation between the length of the incubation period and disease severity for a wide range of human pathogenic viruses. Using a machine learning approach, we develop a predictive model that accurately estimates, solely from several virus genome features, in particular, the number of protein-coding genes and the GC content, the incubation time ranges for diverse human pathogenic RNA viruses including SARS-CoV-2. The predictive approach described here can directly help in establishing the appropriate quarantine durations and thus facilitate controlling future outbreaks.The length of the incubation period in viral diseases strongly correlates with disease severity, emphasizing the biological and epidemiological importance of the incubation period. Perhaps, surprisingly, incubation times of pathogenic RNA viruses can be accurately predicted solely from generic features of virus genomes. Elucidation of the biological underpinnings of the connections between these features and disease progression can be expected to reveal key aspects of virus pathogenesis. The recent outbreak of the novel SARS-CoV-2 coronavirus and the resulting COVID-19 disease has led to an unprecedented worldwide emergency . The lenThe length of the incubation period varies both across and within virus families . InvestiHere, we comprehensively assess the incubation periods of different viruses that cause human diseases. We find that, when comparing across different virus species, a longer virus incubation period is significantly associated with a more severe disease presentation. This trend is maintained within and across virus families, regardless of the affected tissue, and is especially strong among coronaviruses, and overall, for human respiratory diseases. For an in-depth examination and construction of a predictive model, we narrowed our focus to respiratory, non-segmented, single-strand RNA (ssRNA) viruses and analyzed different genomic characteristics of these viruses. We identified features that are predictive of the incubation time and are generalizable across virus families. Based on these features, we developed an elastic net regression model that predicts virus incubation periods. We extensively validated the robustness of this model and the selected features for the prediction of the incubation time across diverse viruses and virus families, to enable accurate early estimation of the incubation period for future outbreaks.p value 1.1e−5). This trend is strongest when considering all 41 viruses and diseases . Given that the quarantine time is defined as the upper limit of the virus incubation time, we extracted the upper estimates of the incubation periods for all viruses in the analyzed set  and an empirical, non-parametric test, to estimate, for each feature, whether it varies more across virus families than within each family see the “c. We denCoronaviridae as the training set. By training on a single viral family, we allow for a test set with the largest possible number of families, encompassing high genomic diversity and allowing for a comprehensive evaluation of the model. Moreover, coronaviruses include viruses with both high and low incubation periods, providing a good representation of the range of incubation period values. Thus, we trained an elastic net model on the 7 human-infecting viruses of the family Coronaviridae . Specifically, for the virus with the longest known incubation period, measles, the longest incubation time, 9.7 days, was predicted. Although measles was assigned an upper limit incubation period of 14 days in our data, the majority of the available reports are indeed in the range of 9–12 days [Next, we divided the analyzed dataset into training and test sets. To maintain a large, diverse, and independent test set that spans multiple virus families, we selected the 7 human-infecting viruses of the family dae Fig. a, using dae Fig. b. The tedae Fig. b, attest–12 days . The sec–12 days .Fig. 3AExploration of the model indicated that the strongest predictive features were the number of protein-coding genes and GC content, with higher values in either feature corresponding to a longer incubation time Fig. c. ElucidTo assess the robustness of the selected features, we tested models trained with different partitioning of the data into train and test sets. We found that these changes did not significantly change the performance of the models, further attesting to the robustness of the signal obtained using the four family-generic features Fig. d. By conTo evaluate the utility of our model, we examined how this method would have performed during the early stages of the current COVID-19 pandemic. To this end, we removed SARS-CoV-2 from the training data and trained the model on the remaining 6 CoV only, with the caveat that this training set is poorly balanced as it contains only 2 viruses with incubation times longer than 3 days and, therefore, might underestimate when predicting viruses with long incubation times. The incubation period of SARS-CoV-2 is still being determined, with the recommended quarantine time conservatively set at 14 days. Recent reports indicate that the vast majority of symptomatic patients develop symptoms within 10.5 days, generally, within 5 days , 26. Desp value < 1e−3). On average, the predicted range captures 54% of the true range for viruses in the test set; at least, 30% of the true range is covered for all viruses in the test set, and at least 50% is covered in five of the seven viruses. The average absolute deviation is 1.6 days from the lower incubation range and 1.8 days from the upper incubation range.We further expanded the approach to facilitate an interval prediction, to provide for the prediction of the full range of incubation periods for a novel virus. Given that there is no consensus as to how to define standard errors or confidence intervals for elastic net regression models –30, we iFiloviridae (negative-sense RNA viruses) and Flaviviridae (positive-sense RNA viruses) that cause hemorrhagic fevers. The hemorrhagic fever viruses were selected because they consist of a large enough set of viruses that are not associated with a specific tissue, and thus appear to be less likely to introduce bias in evaluation. Indeed, the model accurately predicted the incubation period of these viruses, including 3 types of Ebola viruses, Marburg virus, dengue virus, yellow fever virus, and tick-borne encephalitis virus .Given the success of the model when applied to respiratory viruses, we sought to examine whether the genomic characteristics and model that was effective for respiratory diseases would be generalizable to non-respiratory viruses. Given that the model construction and evaluation was limited to respiratory viruses, an evaluation on other diseases or types of viruses may be confounded by the different tissue types. To mitigate possible confounders resulting from genome structure and affected tissue types, we focused on non-segmented ssRNA viruses of the families The emergence of novel viruses that can cause pandemics remains a major threat to human health as compellingly demonstrated by the COVID-19 pandemic. A major challenge in dealing with such outbreaks is the initial lack of biological and clinical knowledge of the infectious agent, which can lead to potentially avoidable fatalities until the causative agent is thoroughly characterized. Therefore, to mitigate emerging outbreaks, rapid estimation of the incubation period of novel viruses is vital, in order to define the appropriate quarantine period and to estimate the rate of virus spread. Furthermore, we show here that the length of the incubation period in human viral diseases significantly correlates with the disease severity which further underlines the importance of the accurate prediction of the incubation time.With recent advances in sequencing technology, genomic sequences of multiple isolates of novel viruses become available shortly after the virus emerges. Here, we comprehensively examined genomic features that could be predictive of the virus incubation times of human pathogenic ssRNA viruses and identified four family-generic features that consistently predict the incubation periods with high accuracy. Using these features, we developed a robust model that is predictive of incubation times for respiratory ssRNA viruses, the most common cause of viral pandemics . DespiteWe also investigated the links between incubation periods of different disease-causing viruses and the disease severity and found that viruses with long incubation periods tend to cause severe disease. Although the relationship between incubation periods and disease severity has been assessed previously for specific viral diseases –8, to ouThe underlying molecular and biological mechanisms of the dependencies between the family-generic genomic features, the incubation times, and disease severity remain to be directly and functionally investigated. One contributing factor could be a direct mechanistic connection between increased translation times in viruses with many genes and high GC content and longer incubation periods. Additionally, longer incubation periods are indicative of complex virus-host interactions that consequently present with more severe disease symptoms. This explanation is compatible with the observations in coronaviruses, whereby the highly virulent strains with long characteristic incubation periods encode several accessory proteins , 22 thatWe demonstrated a robust association between virus incubation times and the severity of disease presentation and identified a set of viral genomic features that is highly predictive of incubation times. To our knowledge, this work is the first to demonstrate that incubation periods of respiratory ssRNA viruses can be accurately predicted by genome analysis alone. The model established through this work and the genomic features that were used for training can directly facilitate early and accurate estimation of the required quarantine time for future pandemics and help the responsible agencies set initial guidelines accordingly. Furthermore, these results have clear applications for controlling the spread of emergent ssRNA respiratory viruses, the most common cause of pandemics. Future work can expand this method to encompass additional virus families of interest and aid in mitigating the effect of potentially deadly zoonotic outbreaks.The incubation time for each of the strains of each of the 41 viruses was collected from the literature , HKU1-CoV (n = 39), NL63-CoV (n = 60), and OC43-CoV (n = 161). For these coronaviruses, which are causative agents of common colds, a 3-day incubation period was assigned, following the majority of reports [ reports , 34.bMERS-CoV (n = 284). A 14-day incubation period was assigned to MERS-CoV, per previous reports [ reports .cSARS-CoV (n = 273). The estimates show 13 days as an upper limit in the majority of reports [ reports , 36.dSARS-CoV-2 (n = 92). Although more data is needed to assess the incubation period of SARS-CoV-2, we set the duration to 14 days given the recommended quarantine times [eMeasles virus (n = 213). There is a considerable range of reported incubation periods, with the majority of reports indicating 9–12 days and some reports going several days beyond that. Thus, we set the incubation period to 14 days [ 14 days .fRespiratory syncytial virus . For RSV, the incubation period was set to 8 days, in accordance with the higher range of the majority of reports [ reports .gParainfluenza . The parainfluenza incubation period was consistently reported to be between 2 and 6 days and therefore was assigned the upper limit of 6 days [hRhinovirus (n = 244). Per previous reports, a 4-day incubation period was assigned to rhinovirus [rus n = 24. Per priMetapneumovirus (n = 162). Six days was assigned to human metapneumovirus, given the commonly reported range of 4–6 days [4–6 days .The rationale for the selected incubation times for the 14 ssRNA respiratory viruses used in model construction and assessment was as follows:We also assigned each of the 41 viruses with a binary severity annotation, of either severe or mild. Diseases with extreme immune responses, fevers, or other extreme symptoms were considered severe, along with diseases with high death rates. Diseases that cause mild respiratory symptoms or diseases that are otherwise benign were considered mild. In cases where either the Centers for Disease Control and Prevention (CDC) or the WHO explicitly described a disease as either severe or mild, that description was applied as the severity annotation. The disease presentations and severity determined, along with the rationale for the determined severity, are detailed in Additional file Each of the 41 viruses was also classified by its symptoms and affected tissues, based on CDC and WHO descriptions, falling into one of these categories: central nervous system (CNS), fever, gastro, gastro/CNS, hemorrhagic fever, immune system, liver, skin, and swollen glands.Reference genome sequences and GenBank files were downloaded from the NCBI  for eachaGenome length. The number of nucleotides in the reference genome sequence. Rationale: The length of the genome might correlate with virus reproduction time.bNumber of genes. The number of genes in the reference genome’s associated GenBank file. We verified for each virus that there were no undetected genes within its genome using MetaGeneMark [GeneMark  gene precPositive or negative strand RNA. Whether the RNA virus is positive strand or negative strand. This was set to 1 if the virus has a positive strand genome and to 0 if it has a negative strand genome. Rationale: The positive- or negative-sense RNA might correlate with the time required to begin translation; negative ssRNA viruses require an additional stage to synthesize the positive-sense antigenome before translation, and accordingly, could correlate with the reproduction time.dCodon adaptation index (CAI). The CAI was used to analyze the codon usage bias of each virus in comparison to human. The CAI was calculated by concatenating all the coding sequences (CDS) in each virus reference genome GenBank file and using the Biopython [CodonAdaptationIndex class set to a reference human codon usage table [iopython , 45 softge table . RationaeGC content. This was calculated for each reference genome using Biopython [iopython . Rationaiopython  and thusfMutation rate. Raw mutation rates were estimated per each virus genome alignment, without accounting for selection bias, by detecting the ancestral base for every base in the genome for every non-leaf node in the tree using maximum parsimony. Then, at each branch point, the transitions between both sides of the branch were counted, and the average count was then divided by the length of the genome for the final estimate. Rationale: The mutation rates could correlate with the reproduction time [ion time .gAverage and variance of the changes in each position of the alignment. The change in alignment position is defined as the number of different values observed in each position of the virus alignment, divided by the number of strains in the alignment. The average and variance of these values are used as features. Rationale: The position change mean and variance might correlate with the translation efficiency and regulation among different genomic regions and, thus, with the viral incubation period.The following genomic features with potential links to viral replication time and efficiency were evaluated:Features that rely on the multiple sequence alignment of different strains of the same virus were always normalized by the number of strains available, in order to avoid biases that could result from different strain counts per virus.https://github.com/lucasnell/TaJoCGI) with standard criteria [CpG islands were searched for in each reference genome using a Python implementation . One-way ANOVA tests the null hypothesis that the means of the measurement variable are the same for the different categories of data, against the alternative hypothesis that they are not all the same. Hence, lower assigned he SciPy  package.p value to be valid, are not guaranteed and are difficult to evaluate. We hence implemented a second, empirical test, which is not parametric and does not rely on any assumptions. This empirical test evaluates, for a given feature, if its variance within virus families is smaller than would be observed by random assignment of families to viruses. We reason that a feature which is associated with the virus family would have significantly smaller variance within the true family assignment than within a random family assignment. The null hypothesis is that the variance of the features within each family is similar to the variance across families, and the alternative hypothesis is that the variance of the features within each family is smaller than the variance across families. To perform the empirical test, the feature variance within each virus family is calculated and averaged. Next, the feature values are randomly permuted 1000 times and the same calculation is performed, to generate a null distribution. Let the number of times the variance of the permuted values is less than the variance of the real values be X. The p value is calculated as (X + 1)/(1000 + 1). Thus, a lower p value indicates that the feature’s within-family variance is smaller than our null expectation. We search for features with a p value greater than 0.05, for which we conclude that the variance within the actual families is not smaller than that within randomly assigned families. This evaluation does not necessarily indicate that the family-specific features are poor predictors, rather, that, with the data available, it would not be possible to discern whether the signal from these features is primarily driven by the variation between virus families.The ANOVA test assumes that the samples are independent, taken from normally distributed populations with equal standard deviations between the groups. These assumptions, which must be satisfied for the associated L by:The elastic net method  is a genλ1, λ2. Elastic net was chosen because it has characteristics of both LASSO and Ridge regression, which are controlled by the penalties coefficients, thus outperforming other regularization and variable selection approaches [for any fixed, non-negative proaches .The elastic net model was constructed in Python using the scikit-learn  ElasticNCoronaviridae family), with the first model trained on the lower estimates of the incubation period of coronaviruses and the second model trained on the highest reported estimate of the incubation periods.Given that there is no consensus as to how to define standard errors or confidence intervals for LASSO, Ridge, and elastic net estimates –30, we dX. The p value is calculated as (X + 1)/(1000 + 1).To evaluate the significance of the correlation between the predicted incubation intervals and the true intervals, we applied a permutation test. We calculated the average deviation of the predicted ranges from the true incubation ranges across all viruses in the test set, which is 1.7 days. We then shuffle the true intervals 1000 times, to generate a null distribution. Let the number of times the average deviation of the predicted range from the permuted range is less than or equal to the average deviation of the predicted range from the true range be Additional file 1: Figure S1. The performance of models trained with family-generic features. Figure S2. Model performance for ranging incubation time assignment. Table S1. Virus and disease features for 41 collected viruses. Table S2. Family-generic features for the 14 viruses studied.Additional file 2. GenBank file with the reference genomes used for each of the studied viruses.Additional file 3. Accessions of the nucleotide sequences used for each of the 14 viruses studied. The sequence alignments are available through Zenodo (https://zenodo.org/record/4239675).


Virus diseases are among the main biotic factors constraining common bean (Phaseolus vulgaris L.) production in Tanzania. Disease management requires information on types, distribution, incidence, and genetic variation of the causal viruses, which is currently limited. Thus, a countrywide comprehensive survey was conducted. Use of a next-generation sequencing technique enabled simultaneous detection of 15 viruses belonging to 11 genera. De novo assembly resulted in many contigs, including complete or nearly complete sequences of Bean common mosaic virus (BCMV), Bean common mosaic necrosis virus (BCMNV), and Southern bean mosaic virus (SBMV). Some viruses  were detected for the first time in common bean in Tanzania. Visually assessed virus-like disease incidence ranged from 0 to 98% but reverse-transcription polymerase chain reaction-based incidence of BCMV and BCMNV  was mostly less than 40%. The Sanger-based nucleotide sequences encoding coat proteins of BCMV and BCMNV isolates were 90.2 to 100% and 97.1 to 100% identical to each other, respectively. Phylogenetic analysis showed that BCMV isolates were more diverse than BCMNV isolates. The information generated in this study will contribute to the development of molecular diagnostic tools and strategies for management of virus diseases nationally and internationally. Tanzania is the largest producer  of common bean (Phaseolus vulgaris L.) in sub-Saharan Africa FAO . Common Many viruses are known to infect and cause diseases in common bean plants and can cause yield losses as high as 100% .*The e-Xtra logo stands for “electronic extra” and indicates that two supplementary figures and two supplementary tables are published online.Common bean is grown in many geographically isolated parts of the country and, consequently, genetically distinct known and unknown viruses may occur. Molecular and biological information are required for determining genetic diversities of plant viruses, which then helps in developing diagnostic tools and predicting emergence of new strains or viruses. Furthermore, information on distribution and types of viruses that infect common bean is required for strategic breeding and deployment of planting material, as well as for guiding decision-making on imposing quarantine. In past research, ELISA was used to detect viruses in Tanzania  determine the distribution and incidence of virus-like disease symptoms, (ii) map the distribution of BCMV and BCMNV (the most commonly reported viruses from Tanzania), (3) universally detect viruses that infect common bean in Tanzania, and (4) generate molecular information for genetic diversity studies and development of diagnostic tools.Survey areas and field selection. Surveys were carried out in 23 administrative districts  in five national agricultural research zones  in Tanzania. These 23 districts are found in 12 administrative regions, which border eight countries . In eachSample collection and visual assessment of virus-like disease incidence. In each selected common bean field, virus disease incidence was visually assessed by observations on 50 randomly selected plants. Five points were randomly chosen in each field and observations of virus-like disease symptoms were made on 10 plants at each point. The plants were scored as either diseased or not, and symptoms were recorded in a field disease survey sheet. The incidence for virus-like disease symptoms was then computed as the percentage of plants exhibiting symptoms . Overall disease symptom incidence for each district was calculated by dividing the total number of plants with symptoms by the total number of plants on which observations were made in that particular district.Reverse-transcription polymerase chain reaction-based determination of BCMNV and BCMV incidence. From each surveyed field, 30 leaf samples  were randomly collected from 30 different plants, randomly selected from among the 50 common bean plants on which symptoms were observed. The collected leaf samples were placed in sampling bags containing silica gel. Another sample from the same plants was placed between two flip-chart paper sheets and pressed using a plant press and stored at room temperature until use. In total, 7,756 common bean leaf samples were collected from 279 fields and brought to the laboratory at the Mikocheni Agricultural Research Institute (MARI). RNA was extracted from each sample as explained below. Then, reverse-transcription polymerase chain reaction (RT-PCR) was performed. RT-PCR-based incidence was calculated as the percentage of plants singly infected with BCMNV and BCMV. All plants infected with each virus were summed up to calculate incidence for each virus in each district. Samples infected with both viruses were recorded after determining individually infected samples. In each district, prevalence for BCMV and BCMNV was recorded as the percentage of fields with infected plants.RNA extraction. RNA was extracted from either silica gel desiccated or plant-press pressed dry common bean leaf samples using a modified cetyltrimethylammonium bromide (CTAB) method. The CTAB buffers contained 2% CTAB, 100 mM Tris-HCl, 20 mM EDTA, 2.5 M NaCl, freshly prepared 1% sodium sulfite, 2% polyvinylpyrrolidone, and 2.5% 2-mercaptoethanol in nuclease-free water. Other procedures were as reported recently for RNA extracted at MARI  synthesis was done using Moloney Murine Leukemia Virus reverse transcription  following a modified manufacturer’s protocol. The first mix contained 1 mg of RNA, 1 ml of 100 mM oligo (dT)18 or random hexamer , 1 ml of dNTP, and diethyl pyrocarbonate-treated water to a volume of 10 ml. The mixture was heated at 65 °C for 5 min and spun down after chilling on ice for 2 min. The second master mix was prepared according to NEB’s standard protocol. Total volume for cDNA synthesis reaction was 20 ml. Random hexamer and oligo dT18-21 primed reactions were incubated at 37 and 42°C, respectively, for 90 min, and enzymes were inactivated at 65 °C for 20 min. For determination of virus incidence, equal amounts of RNA extracted from five plants collected from the same field were pooled prior to cDNA synthesis. The pools that tested positive were marked and previous plant RNA samples were retrieved and tested individually by RT-PCR to identify the infected plant samples.PCR. To determine incidences of BCMV and BCMNV, PCR were run using different pairs of primers . These pAccuPower PCR PreMix was used in routine detection of BCMNV and BCMV and determination of incidence using primer pairs BCMNVF1/BCMNVR1 and BCMV1F/BCMV1R, respectively. To a 0.2 ml tube containing AccuPower PCR PreMix, 15 ml of diethyl pyrocarbonate-treated water, 1 ml of each of the forward and reverse primers (10 mM), and 3 ml of cDNA template were added to make a total volume of 20 ml. For both pairs of primers, the PCR program was as follows: initial denaturation was for 2 min at 94°C; followed by 35 cycles at 94°C for 25 s, 50°C for 30 s, and 72°C for 1 min (primerpair BCMNVF1/BCMNVR1) or 30 s (primer pair BCMV1F/BCMV1R); and final extension at 72°C for 10 min. The PCR products were run in a 1% agarose gel stained with ethidium bromide. Gel images were captured using a Benchtop UV Transilluminator  under UV light. Gel images were used to score for infection status, and BCMV and BCMNV incidences were calculated as percentages of samples infected with each virus, with the sampling domain being first a field and then a district , Mbeya Zonal Referral Hospital Laboratory (Tanzania), and Bioneer. PCR products were purified using PCR purification kits (Bioneer) or treated with exonuclease I and calf intestinal alkaline phosphatase (NEB) following the enzyme manufacturers’ instructions, then sequenced on both strands.https://www.csc.fi; Finland) accessed between January 2016 and October 2017. The files received from Fasteris SA were unzipped using the command “tar-vxf filename”. Then, all reads of sizes not within 21 to 24 nucleotides (nt) were deleted. The remaining reads were analyzed using two approaches: de novo assembly was first done on each read size separately and, later, the inserts for these four sizes were combined  using the command “cat *.fastq > filename.fastq’ to obtain one fastq file and assembled using the command “virus_detect.pl *.fastq” . Offline analysis on desktop or laptop computers  using VirusDetect v.1.6 was possible for “not combined” reads but failed for some combined inserts . The contigs obtained were inspected for open reading frames using the Expasy-translate tool (https://www.expasy. org/). To obtain and manually edit longer nucleotide sequences, contigs obtained by analyzing inserts of sizes 21 or 22 nt were aligned against identical contigs obtained through analysis of combined inserts. For the nonpooled sample HXH-4 (isolate TZ: Mor533:2015), the contigs that mapped to the same reference sequence or to too-closely related virus sequences were assembled using the SeqMan program  and cross-checked using Sanger sequencing.Sequencing of small RNA and data analysis. Equal amounts (7 mg) of total RNA extracted from 30 plants from each of the five zones were separately pooled to make six (two samples for the Lake zone) zonal pooled RNA samples: HXH-1 (southern highlands zone), HXH-2 (eastern zone), HXH-3 (northern zone), HXH-6 , and HXH-7 (Lake zone), and HXH-15 (western zone). Moreover, there were two nonpooled RNA samples (HXH-4 and HXH-5), and the HXH-4 sample also contained RNA extracted from cassava, a subject for another study. The 30 leaf samples from which RNA was extracted for NGS were selected based on severity or uniqueness of disease symptoms observed on common bean plants in fields but, for each pool, it was ensured that at least a sixth of the samples were from asymptomatic plants. For sequencing, total RNA was shipped on dry ice to Fasteris SA in Switzerland. Then, the small RNA were isolated (acrylamide gel size selection) and cDNA libraries were prepared and sequenced using Illumina HiSeq 2500  as described previously ; vein clearing; leaf distortion, puckering, and rugosity; mosaic; upward and downward leaf curl; stunted growth; purpling; mild to conspicuous yellow spots or patches; mottling; and necrosis on leaves . In total, RNA from 180 individual symptomatic and asymptomatic plants was sequenced by targeting virus-derived small RNA of sizes to 24 nt, which are generated along with genomic small RNA during plant defense , Sobemovirus (unassigned), Alphaendornavirus (Endornaviridae), Carlavirus (Betaflexiviridae), Cucumovirus (Bromoviridae), Umbravirus (Tombusviridae), Crinivirus (Closteroviridae), Begomovirus (Geminiviridae), Cytorhabdovirus (Rhabdoviridae), and Caulimovirus and Soymovirus (Caulimoviridae) . The Blast searches using contig sequences obtained in this study matched sequences of over 32 viruses in the database. The coverage, sequencing depth, and number of contigs for these viruses were different (Supplementary Table S2).The sequencing depths ranged from 5.2x for Bean yellow disorder virus  in sample HXH-3 to 5,632x for SBMV in sample HXH-15. Some contig sequences obtained through de novo assembly were related to more than one virus in the sequence database ; the most likely viruses infecting plants whose RNA was included in the sequenced samples are shown in The commonest viruses in samples were BCMNV, PvEV-1, and PvEV-2, which were detected in samples from at least three agricultural research zones . BCMNV wOther viruses detected were CPMMV (HXH-2 and HXH-3), PeMoV , SBMV , CABMV (HXH-6), BnYDV (HXH-3), CMV (HXH-2), unidentified umbravirus closely related to Carrot mottle mimic virus (CMoMV), Carrot mottle virus (CMoV), Opium poppy mosaic virus (OPMV), Ethiopian tobacco bushy top virus (ETBTV), Tobacco bushy top virus (TBTV) (HXH-2), Tobacco mottle virus (TMoV) (HXH-7), Northern cereal mosaic virus (NCMV) (HXH-3), and a caulimovirus most closely related to Strawberry vein banding virus (SVBV) and other caulimo-viruses (HXH-7) . A sequeNGS sequences of BCMNV. De novo assembly of NGS data generated complete or nearly complete genomes for BCMNV. In the pooled RNA sample HXH-1, a contig of 9.6 kb  was obtained. Alignment against the complete sequence of strain TN1 (accession number KY659306) showed it to be a complete sequence and that the two sequences were 99% similar at both nucleotide and amino acid sequence levels. In the pooled RNA sample HXH-2, the contig obtained from reads of size nt  was closely related to a published sequence of BCMNV isolate 1755b (accession number KY659305). This contig sequence translated to yield a partial first potyviral protein (P1) and the other nine typical potyviral proteins  for pooled RNA sample HXH-2 (eastern zone). This sequence  was 99% similar to that of strain NL-1 (accession number AY112735). In another pooled RNA sample, HXH-3, a 7.1-kb contig was obtained (accession number MF405188) and was closely related to sequence of strain NL-1 (accession number AY112735).In a nonpooled RNA sample (HXH-4), a complete sequence of BCMV  was obtained by aligning contigs obtained by de novo assembly of read size 21 nt and combined inserts using SeqMan v. 5.03. National Center for Biotechnology Information Blast showed it was 92% similar to isolate RU1 (accession number GQ219793)  and BCMV (n = 19). These sequences were used to generate a phylogenetic tree for BCMNV and BCMV isolates. Phylogenetic analysis of these sequences (620 nt in size) at the conserved 3' end resulted in two groups of virus species: BCMV and BCMNV . FurtherWe detected 15 viruses belonging to 11 genera in the common bean samples collected from all over Tanzania. They included viruses reported in previous surveys of common bean virus diseases in the country—BCMNV, BCMV, CMV, and CPMMV  and a caulimovirus (pooled RNA sample HXH-7). Moreover, it is worth noting that small RNA were extracted from samples stored in silica gel or dried using a plant press. We are unaware of previous work that used samples stored under similar conditions but it is reasonable that the use of dry leaf samples could affect the amount of small RNA extracted and, thus, the coverage and viruses detected. However, in this study, it was possible to obtain complete or nearly complete nucleotide sequences from some of these samples.NGS technology is still in its infancy, and the possibility of sequencing errors and further problems is expected during de novo assembly of reads. There are concerns that sequences derived from pools of plant material can be chimeras artificially assembled from pieces of multiple viruses  were analyzed. The viruses detected following analysis of combined inserts or separate reads of sizes 21 to 24 nt were the same  but the contigs obtained differed in size. Interestingly, when the contigs overlapped, they were identical to each other. Although not a subject of this work, it is noteworthy that SBMV was still reliably detectable in reads of >25 nt but not >35 nt. Analyzing sequences first as combined reads and then separately enabled the obtaining of two sequences for alignment and manual editing. Furthermore, it took less time to assemble sequences and less computational capability was required when reads of different sizes were analyzed separately. This is particularly important in developing countries where supercomputers are generally lacking  and southern highlands areas. The factors driving the spread of viruses that infect common bean in Tanzania remain largely unknown. Some viruses detected in this work are known to be transmitted through seed at different efficiencies  used in NGS; it is not related to the detection sensitivity of NGS and RT-PCR methods. Therefore, it is likely that the chance of detection of BCMV, and possibly other viruses, may rise with an increased number of pooled RNA samples per zone.The results showed that isolates of BCMV were more diverse than those of BCMNV. Occurrence of many strains of BCMV has been known for quite a long time through studies on genetic interaction between this virus and common bean genotypes  infecting common bean plants that could be responsible for the unexplained symptoms in fields throughout the country. Thus, plant breeders and pathologists should investigate the damage and yield losses caused by these viruses and also consider any possible interactions between pathogenic viruses and viruses whose pathogenic roles remain undetermined . We anticipate that the results reported herein will form the basis for future studies on common bean viruses as well as guide plant breeders and plant pathologists in developing strategies for management of common bean virus diseases in Tanzania. For example, this information can be used in selecting seed multiplication sites or deploying planting material. To the best of our knowledge, this work represents the first comprehensive survey for common bean viruses in Tanzania and provides unprecedented molecular evidence for occurrence of different viruses in common bean plants in the country.


Dear Editor:The article entitled “Rabies virus monitoring in bat populations in Rondônia state,Brazil” is very interesting-This study focused on rabies virus, and bat brain and blood samples were collectedbetween 2010 and 2015. Bat brain and blood samples were valuable and rare in terms ofscientific significance; thus, the lyssavirus should be further monitored in Brazil.According to the study, “Rabies diagnosis was made using a fluorescent antibody testFAT,” only one test was used to assess the presence of the rabies virus. Heminested PCRassays should also be used for the detection of six genotypes of rabies andrabies-related virusesLyssavirus. Base on the literature,16 Lyssavirus species, excluding Ikoma lyssavirus and Mokolalyssavirus, have been reported in bats,,Rabies viruses belong to the genus


Potyviridae family and one to the Bunyavirales order. Due to the ability of potyviruses to enhance heterologous virus replication, it will be important to assess the presence of such a virus in the grapevine population to understand its ecological role. Furthermore, the association of the cogu-like virus with esca symptomatic samples opens new questions and the necessity of a more detailed characterization of this virus.The concept of plant as a holobiont is now spreading among the scientific community and the importance to study plant-associated microorganisms is becoming more and more necessary. Along with bacteria and fungi, also viruses can play important roles during the holobiont-environment interactions. In grapevine, viruses are studied mainly as pathological agents, and many species (more than 80) are known to be able to replicate inside its tissues. In this study two new viral species associated with grape wood tissues are presented, one belongs to the  Grapevine is one of the most important cultivated crops in Europe and studies on its genetic variability were performed to understand varietal characteristics, unveiling only a small part of the complex biodiversity observed within these species . A furthVitis spp. host one of the largest number of viruses among cultivated crop species, which is probably linked to a very long history of domestication and coexistence, an extensive exchange of germplasm on a global scale and the vegetative propagation [pagation . The effpagation . In spitpagation  or to ampagation .Among grapevine trunk diseases (GTDs), esca syndrome is one of the most complex, characterized by simultaneous infection of several fungi, which lead to important reduction in yield and quality of fruits and wines . The sitThe present study was conducted in an experimental vineyard of CREA - Research Centre for Viticulture and Enology (CREA-VE) located in Spresiano (TV), Veneto region, Italy (elevation is 56 m a.s.l and a warm temperature climate) . SamplesVineyard was visually monitored, plant by plant, to determine sanitary status and presence of esca-related symptoms for 4 years. Wood tissue was collected from 9 continuously asymptomatic plants (AS) and from 9 plants continuously symptomatic (SY) (tiger striped leaves and/or apoplexy) which showed symptoms at the collection date (16 September 2017). The wood tissue was sampled using a sterile corer, which allowed extracting a transversal wood fragment from the main trunk at the crown ramification level. Wood fragments were stored in sterile 50 mL conical tubes at −80 °C until further analysis.g for 20 min at 4 °C. Supernatant was recovered, transferred to a new 15 mL conical tube to perform a second chloroform:isoamyl alcohol extraction. The supernatant was retained, transferred in a new tube and amended with an equal volume of 100% isopropyl alcohol. Nucleic acids were allowed to precipitate at −20 °C for 30 min and then were collected by centrifuging at 8000× g for 40 min at 4 °C. The pellet was then washed with 70% ethanol, dried and resuspended in 250 µL TE buffer . Total RNA was recovered using the Spectrum plant Total RNA kit : 500 µL of Binding buffer were added to the 250 µL of total nucleic acid and loaded onto the binding column. Then, washing steps were doubled (2 times Wash buffer 1 and 4 times Wash buffer 2) and final elution was performed in 40 µL. Quantity and quality of RNAs were checked using NanoDrop One apparatus  and by running a 1% agarose gel in 0.5 % TBE buffer .Extraction of RNA was performed by making 3 pools of samples from 3 plants for each condition (AS and SY). To obtain total RNA from wood tissue a modified version of the protocol published by Gambino and co-authors in 2008  was usedThe obtained samples were sent to Macrogen Inc.  for rRNA depletion , cDNA libraries construction  and sequencing by Illumina Novaseq technology with an output of 100M paired-end reds of 100 bp for each library.De novo assembly from total-RNA sequencing was performed using high quality and cleaned reads selected using Trimmomatic [http://www.ncbi.nlm.nih.gov/gorf/orfig.cgi), blasted against the nr NCBI databases, and then the deduced protein molecular weight was calculated using the ExPASy online tool (https://web.expasy.org/compute_pi/). Conserved domain search was performed using the CDD/SPARCLE tool from NCBI [mmomatic . For conmmomatic , then blmmomatic . Alignmemmomatic  and SAMtmmomatic . Coding rom NCBI .To confirm that the viral contigs were not artifacts, quantitative RT-PCR (qRT-PCR) was performed for each RNA-dependent RNA polymerase (RdRP). First, cDNA was synthetized from total RNA following the manufacturer instructions provided for the High-Capacity cDNA Reverse Transcription kit . Specific primers  and iTaqThe occurrence of identified viruses was assessed on grapevine samples collected in 2012–2019 and others collected in 2005 that were stored in the CREA-VE collection at −80 °C as total RNA extracts. RNA was extracted from the phloem tissue of woody canes or leaves according to Bertazzon et al. 2017  and testNicotiana benthamiana and Chenopodium quinoa was performed. Homogenates of virus-infected plants were rubbed on the leaves surface of the two herbaceous hosts. After 7 and 15 days inoculated and non-inoculated leaves were harvested to extract RNA and test with qRT-PCR the presence of viruses.An attempt to transmit the two identified viruses to herbaceous host The present virome analysis performed on the metagenomics samples of 6 libraries from grapevine wood tissue (3 esca asymptomatic and 3 esca symptomatic) retrieved over 150 contigs carrying RdRP signature motifs . Here, wThe second virus, detectable only in the three symptomatic esca samples as reported in Blast search for the poty-like virus displayed that the first two hits in the nr database are macluraviruses (Narcisus latent virus—QDC21212.1 and Yam chlorotic necrosis virus—AWH61232.1) whereas the third match is a Bymovirus (Barley mild mosaic virus—BAA01742.1). For this reason sequences of potyviruses were used to build a phylogenetic tree. As reported in Searching for similarities in the nr database, the RdRP segment of the bunya-like virus displayed similarities with two recently reported cogu-like viruses (Grapevine associated cogu-like virus 2—QIJ25707.1 and Grapevine associated cogu-like virus 3—QIJ25710.1), with a Laulavirus (Laurel Lake virus—YP_009667028.1 in the Phenuiviridae family) and with a Coguvirus (Citrus concave gum-associated virus—QDK54399). As reported in The occurrence of the two newly identified viruses was investigated on 91 grapevine samples belonging to 64 cultivars collected between 2012 and 2019 from commercial vineyards and germplasm collections of the major grapevine growing regions around Europe . Fifty-sThe mechanical inoculation on herbaceous plants revealed that none of the two viruses were able to replicate in such hosts at both 7 dpi and 15 dpi.Viruses are the most frequent causal agents of emerging infectious diseases in crops ,29, and Potyvirus probably occurred in the past [P. viticola [Macluravirus, Bymovirus and Bevemovirus while PaPlV1 is far from any known potyviral family.Potyviruses are a large and agriculturally important group of plant viruses which can lead to severe losses in crop quality and yield, as in the case of Potato virus Y (PVY), Plum pox virus (PPV), Soybean mosaic virus (SMV) or Zucchini yellow mosaic virus (ZYMV) . Interesthe past . The relviticola , the virBunyavirales order [Coguvirus genus there is the Citrus concave gum-associated virus, which was recently demonstrated to play a role during the development of a wood disease named as citrus disease concave gum-blind pocket (CG) [Coguviruses are a group of recently characterized plant viruses, closely related to phenuiviruses and inside the es order . Intereses order , the vires order ,42. Anotket (CG) ,44. In aket (CG) ,46. Receket (CG) . It is iket (CG) ,49,50. Fket (CG) ,54,55,56Potyviridae family and one to the Bunyavirales order that are associated with grapevine plants. The biological impact of such viruses on the plant physiology is still to be elucidated but their relatedness to plant pathogenic viruses can help explaining the high susceptibility of Vitis spp. to viral infection (at least for the GaPlV1). To deepen this aspect some experiments on virus host-range are ongoing in controlled conditions. In parallel, further analyses are ongoing to understand if the cogu-like GaClV4 can play part in the development of esca syndrome, which leads to an important impairment of grape physiological performances and to a complex wood disease. To achieve this results wood metatranscriptome analysis are now under evaluation to observe plant, fungal and viral interactions.In the present work we reported for the first time two new viral species, one belonging to the


Numerous potyvirus studies, including virus biology, transmission, viral protein function, as well as virus–host interaction, have greatly benefited from the utilization of reverse genetic techniques. Reverse genetics of RNA viruses refers to the manipulation of viral genomes, transfection of the modified cDNAs into cells, and the production of live infectious progenies, either wild-type or mutated. Reverse genetic technology provides an opportunity of developing potyviruses into vectors for improving agronomic traits in plants, as a reporter system for tracking virus infection in hosts or a production system for target proteins. Therefore, this review provides an overview on the breakthroughs achieved in potyvirus research through the implementation of reverse genetic systems. Reverse genetics of RNA viruses refers to the generation of recombinant viruses through site-directed mutagenesis such as substitution, deletion or insertion . This coPotyvirus is a genus of virus that belongs to the family Potyviridae. Potyviruses are among the most economically important and widely spread groups of plant viruses [Potato virus Y as the type species [ viruses . The gen species . The pic species  is trans species . Potyvir species . The mem species . The sin species ,16 gives species ,18. Addi species ,20.Brome mosaic virus [Cauliflower mosaic virus 35S promoter in a binary vector. Cells transformed with the plasmids containing virus cDNA clones are then introduced into plants through agroinfiltration, particle bombardment, or rubbing onto the leaf’s surface [Infectious clone technology represents the most commonly applied reverse genetics system. Cloning of an infectious clone was first described for ic virus . Since tic virus ,23. On t surface ,25. In tPoint mutation refers to a change occurred within a gene due to a single base pair alteration in the DNA sequence. During translation, conversion of RNA copied from the DNA into a sequence of amino acids would take place and point mutations usually cause a variety of effects on the protein synthesized at the final stage .Potato virus A (PVA). However, aphid transmissibility of the virus was still retained [Clover yellow vein virus, pClYVV cDNA clones containing no poly(A), poly(A) with shorter A residues, or various oligonucleotide sequences downstream were constructed. All RNA progenies obtained from the pClYVV cDNA constructs had poly(A) tails with infectivity varies along the sequences introduced. This suggested the addition of poly(A) to be independent of template, yet essential to maintain the infectivity of potyviral cDNA [Plum pox virus (PPV) revealed that the region between nucleotides 39 and 145 contributes to competitive fitness of the viral population [Turnip mosaic virus, TuMV-pXBS7/TuMV-pXBS8 chimeric viruses have allowed the mapping of a symptom severity determinant in the 3′-terminal UTR of pXBS8-derived virus [Mutagenesis studies aimed to characterize the phenotypic consequences resulting from genome modification, based on how the progenies differ from their respective wild type . To dateretained . Furtherral cDNA . Besidespulation . A pointed virus .Papaya ringspot virus (PRSV) were changed to aspartic acid and lysine respectively. Consequently, PRSV mild mutants with a potential to cross-protect Cucumis melo plants against wild type PRSV-W were obtained [Bean yellow mosaic virus (BYMV) was generated by exchanging an amino acid within the large ORF, leucine with serine. BYMV-M11 mutant conferred a complete cross protection against BYMV isolates from gladiolus, incomplete against BYMV isolates from other hosts, partial against a CIYVV isolate [Zucchini yellow mosaic virus (ZYMV) HC-Pro were substituted with isoleucine and asparagine respectively. The attenuated mutants were found to induce only mild symptoms with recovering and protected squash plants completely against the severe Taiwan strain, ZYMV TW-TN3 [Cross protection is conferred by pre-infecting the host crops with a mild virus strain to prevent the infection by another severe or closely-related strain of that virus . This stobtained . Similar isolate . An argiV TW-TN3 . AnotherV TW-TN3 .Mutagenesis studies on potyvirus infectious clones allowed the mapping of viral determinants responsible for viral genome replication, local and systemic movement of virus, symptomatology and host species range  Table 2Table 2. Potato virus Y, PVY-SON41 was demonstrated as the avirulence factor corresponding to Pvr resistance gene in pepper. A single substitution of adenosine nucleotide to guanosine at position 8424 in that region is sufficient for the virulence [The differential infectivity of UK 1 and JPN 1 strains of TuMV in Ethiopian mustard was studied to map the viral determinants involved . Isolateirulence .Brassica oleracea L.). Meanwhile, Tu-3 induced systemic chlorotic and ringspot symptoms in infected cabbage but not radish. The genomic region encoding C terminus of HC-Pro, all of P3 and N terminus of 6K1 was exchanged between pTuC and pTuR1 chimeras. The only difference between pTuR1 and pTuC was identified within the amino acid sequence of P3 gene. Hence, P3 gene was suggested to be involved in the differential phenotypes caused by TuMV isolates in both hosts.The differential responses of UK 1 and JPN 1 strains of TuMV in different hosts; brassicas  and radish cultivars , Daikon) were investigated . AlthougJohnsongrass mosaic virus (JGMV) strains, Johnsongrass infecting JGMV-Jg and Krish strain JGMV-Kr, was studied. Transcripts of JGMV-Jg full-length chimera containing coat protein sequences from JGMV-Kr were infectious in Krish resistant sorghums, thus confirming the role of JGMV-Kr coat protein in its host specificity [Chenopodiaceae and Cucuribitaceae families whereas PRSV P infects plants in papaya family (Caricaceae) additionally [Host specificity of two different cificity . Similartionally . Host astionally . A singltionally .Bean common mosaic virus (BCMV) interaction with its host, bean genotypes carrying different combinations of resistance genes . The experimental plants were agroinoculated with an infectious clone of RU1 strain, pCA-RU1-GUS containing UidA gene. In situ histochemical GUS assays revealed that DW, The Prince, CRM, SP, and SGR cultivars (carrying bc-u resistance gene) were all systemically infected. However, the genotypes carrying the I gene alone (Widusa) or in combination with bc-1 , bc-12/bc-22 (IVT-7233), and bc-3  showed only a weak blue staining. These resistance responses against BCMV-RU1 are largely in agreement with previous results obtained through immunological method and symptom descriptions based analysis [I conferred a complete protection against BCMV-RU1 while bc-genes do not provide any. Besides that, the host defence response of cucurbit genotype, Dina-1 against ZYMV-NAA potyvirus has also been focused on previously [Naderpour and Johansen  studied analysis . The stueviously . Switche2 vesicles too. TuMV 6K2 fused to photoactivable GFP (PAGFP) was used to monitor the vesicle movement. Viral egress is shown to begin with the budding of 6K2 vesicles at ER export site in the globular structure. The virus then travels to plasma membrane and plasmodesmata to be delivered into neighboring cells. Some peripheral vesicles were also observed to be recycled back to the globular structure. This indicated a functional linkage between the peripheral vesicles and perinuclear structure. Although the Golgi apparatus and ER lost their organization due to the amalgamation, they were still connected to the host secretory pathway (ER-to-Golgi transport). The importance of this connection was investigated by inhibiting the pathway. As a result, the disruption enhanced the clustering of peripheral 6K2 vesicles with COPII coatamers, leading to an inhibition of cell-to-cell movement of virus. This suggests the requirement of a functional secretory pathway for a successful intercellular propagation of TuMV.To learn more on mechanisms of interrelation between potyvirus and host, the impact induced by TuMV infection on the endomembranes of host early secretory pathway was examined . TuMV inTobacco etch virus (TEV) and Arabidopsis thaliana proteins was also investigated [Arabidopsis thaliana proteins targeted by viral proteins were identified through affinity purification followed by mass spectrometry analysis (AP-MS). VPg and NIaPro specifically targeted 89 and 76 of these proteins, respectively. Overall, a total of 67 proteins targeted by both domains were considered to be the targets of full-length NIa.Along with these host-viral factor interactions, the interplay between stigated . An affiApart from the mature proteins, proteolytic processing of the potyviral polyprotein also produced multiple partially processed intermediates . The difTobacco vein mottling virus, TVMV-WT. The mutation suggested might have altered the motif structure and thus the binding property of HC-Pro too [r lacking 207 nucleotides in HC-Pro sequence exhibited an aphid-non-transmissible phenotype. However, its transmission activity was restored partially by pre-feeding the aphids on active HC-Pro from PVY. This confirms the helper activity of the N-terminal domain of HC-Pro [Potyviral HC-Pro and CP proteins were reported to have a crucial role in efficient aphid transmission . In line-Pro too . Likewisf HC-Pro . A mutatf HC-Pro . The motf HC-Pro .Soybean mosaic virus, SMV-G7H. A highly conserved histidine in the CP C-terminus and an arginine near the cleavage site at HC-Pro C-terminus were mutated and the results obtained showed that both amino acids are necessary to maintain the interaction for a successful transmission of SMV by aphids. Moreover, an amino acid substitution in the DAG motif was found to have disrupted the CP–HC-Pro interaction in YTHS.Seo et al.  conducteTobacco vein banding mosaic virus, TVBMV-HN39 infectious clone, pCaTVBMV-GFP were deleted. As a consequence, the mutant caused no systemic infection in inoculated Nicotiana benthamiana plants. According to the RNA secondary structures prediction, the deleted region is able to form a stem-loop (SL) like structure. Progenies derived from TVBMV mutants lacking nucleotides between positions 1 and 20 and 15 and 35 within 3′-UTR were found to have restored the 5′-end SL like structures and systemically infected tobacco plants. Hence, the 5′-terminal stem loop was proposed to be neccessary for TVBMV systemic infection [Clover yellow vein virus (CYVV-NZ) has been reported previously [In order to figure out the function of 3′-UTRs of potyviruses, the sequences between nucleotide positions 8–42 in the 3′ UTR of a nfection . Formatieviously .Apart from bacterial and yeast expression systems, the plant viral vectors also provide a fast and efficient approach for synthesis of specific proteins in plant cells . In thisStrawberry vein banding virus (SVBV) viral promoter was inoculated into experimental host plants [Viral vectors are usually tested through an expression of well-analyzable reporter genes in plants . With ret plants  (Table 3t plants  (Table 3Brome mosaic virus (BMV) to be developed into a plant virus vector was successfully demonstrated in 1986 [in planta (N. benthamiana using a Pepper mottle virus, PepMov-based vector led to an increased senescence along with milder symptoms [Rosea1 tagged infectious clone of PVY was developed, conferring benefits to molecular farming by rapidly produced larger amounts of anthocyanins in biofactory crops [The potential of  in 1986 . Since tn planta . The maisymptoms . Anothersymptoms . For an symptoms . Likewisry crops .Reverse genetics in virology relies on cDNA intermediates in order to genetically manipulate RNA viruses and further produce biologically active RNA molecules. Likewise, the available infectious full-length cDNA clones of potyviruses enable countless reverse genetics studies on phenotypic alteration and cross-protection by mutated viruses as well as in determining viral elements responsible for a particular biological characteristic of the virus. Apart from improving our understanding on the complexities of interactions between host and viral factors, reverse genetics strategies have also made various applications of recombinant vectors possible. Furthermore, the approach contributed immeasurably to the elucidation of basic functions of potyviral proteins, certain motifs or genome sequences in viral replication, transmission, and cell-to-cell movement. All these findings, in conjunction with different approaches such as transciptomics and proteomics analyses, would lead to the building of a larger network that helps to further explore potyviruses, especially in the identification of more durable resistance genes. Hence, reverse genetics technologies of potyviruses are believed to hold great promise for commercial applications in the future. Despite these breakthroughs, although various viral determinants have been identified through plant–potyvirus pathosystems, the host targets of those determinants are yet to be characterized in the future.


The pathogenic mechanisms underlying the Biology and Biochemistry of viral infections are known to depend on the lipid metabolism of infected cells. From a lipidomics viewpoint, there are a variety of mechanisms involving virus infection that encompass virus entry, the disturbance of host cell lipid metabolism, and the role played by diverse lipids in regard to the infection effectiveness. All these aspects have currently been tackled separately as independent issues and focused on the function of proteins. Here, we review the role of cholesterol and other lipids in ssRNA+ infection. Picornaviridae, Coronaviridae, and Flaviviridae .,66.65,66d) , where t pathway ,66. Duri pathway ; after v pathway ,69. Two membrane . As commrane [2+ . In in vrane [2+ . Activatrane [2+ ,71,72,73All these results clearly bring evidence that the lipid environment surrounding proteins involved in virus infection has a relevant function in the virus entry mechanism. Different lipids are essential for virus docking to the cell receptor either serving directly as (co)-receptors or providing the appropriate environment (lipid rafts) for the necessary reactions . In addition, the virus, through specific protein conformational changes, takes advantage of several cell signaling pathways controlled by diverse membrane lipids. This process allows the virus to govern the cell metabolism following endocytosis of the viral genetic molecules.de novo synthesis of fatty acids in order to generate the scaffold membranes, the replication complexes (RCs), as well as for energy production in the β-oxidation pathway in the mitochondria. Concurrently, the cell metabolism needs to be kept above a threshold level to avoid exhaustion of the host cell. Full understanding of the mechanisms and related factors involved in virus–host interaction is a requisite for developing efficient antiviral infection therapies.After the virus or its genome gets inside the infected cell, ssRNA+ viruses and other enveloped ones that replicate in the cytoplasm manage the cell metabolism to develop the replication scaffold, this membrane structure bolstering the so-called ‘virus factory’ ,78,79,80Flaviviridae) uses DMVs instead [Faviviridae [Togaviridae and Picornaviridae [Nodaviridae) [cis-Golgi at the budding stage 36–48 h after infection, this latter transformation being coincident with the formation of vesicle packets [The scaffold structure raised for building the viral factory varies between different virus in their morphology and possibly lipid composition. Flaviviruses develop a so-called ‘membranous network’ (MN) in a spherule/invagination type, while coronavirus does through a quarter-like type delimited by ‘double membrane vesicles’ (DMVs). Nonetheless, HCV  , or fromviridae) ,82. Vira packets ,79,83. I packets ,80,82. EEnveloped viruses such as ssRNA+ viruses have a membrane lipid whose profile is different to that of the original organelle membrane when the envelope is created. Since the viral membrane is known to be enriched in cholesterol, sphingolipids, and phospholipids with saturated acyl chains, the DMV is believed to be also primarily composed of such classes of lipids. An unusual sphingolipid, dehydrosphingomyelin, along with PS and plasmalogens of PE were reported in the HIV envelope . A role de novo lipid synthesis has also been evidenced for WNV, from the Flaviviridae family as HCV, to proceed in a PI4P-independent fashion and, concurrently, it is not related to PI4KIII signaling [However, the most striking and known lipid-related factor associated to the MNs’ development is the PI4KIII signaling pathway. The PI4Pα isoform, which is mainly expressed in the ER, has been shown to be a key factor for HCV replication, whereas the PI4KIIIβ is found in the Golgi and is required by Picornaviruses and some HCV strains . This enignaling . There iignaling , anotherignaling ,93. Sincignaling ,94. Noneignaling .Picornaviridae family, non-enveloped viruses, have been reported to subvert the autophagosome pathway as a means to exit the infected cell without membrane lysis; support for this spreading mechanism comes from the finding of numerous extracelular vesicles that are enriched in phosphatidylserine phospholipids [The autophatocytic pathway has also been associated to the start of HCV infection, but it seems not to be necessary for the infection to go on . Later oholipids . The besholipids ,101. Lipholipids  through holipids . Regardiholipids  early shholipids  has founSimilar to viral entry, cholesterol has been found to be also relevant in the RCs’ membranes ,82. Up tBlocking cholesterol suitability for the membraneous network or endosomes used for the virus replication and internalization has been demonstrated to inhibit the virus life cycle in a number of unrelated viruses. Disruption of the SREBP pathway restrains the Andes virus (ANDV), an ssRNA- virus, internalization, although it does not bind to the cell surface receptor . In addiThe replication of Rabies virus (RABV), an ssRNA virus, is halted by the action of viperin  in RAW264.7 cells. This protein is induced by the RABV, IFV, HIV, or HCV infection through promotion of the innate immune response bound to the TLR4 signaling pathway. The inhibitory activity of viperin on virus budding is related to its capability to substantially drop the contents of cholesterol and sphingomyelin in the replication membranes , thus po2 (PLA2) such as lysophospholipids (LPPLs) and free arachidonic acid (AA) were also found in patients as compared to healthy voluntiers, with a correlation between the level of AA and the ratio of LPI(18:0) to total 18:0-PIs being observed as well. These results show a potential high sensitivity of SARS-CoV patients to PLA2 activity. In the general context, the metabolome of these patients pointed to hyperlipidemia, cardiovascular abnormalities, and glucose metabolism alteration as a delayed efffect of the viral infection. Nonetheless, the authors acknowledge that some of the related metabolic disturbations are likely owed to the pharmacological treatment. High levels of PLA2 group IID (PLA2G2D) in lungs of middle-aged mice as compared to young mice had previously been associated to a fatal or worse outcome [2 (PGD2), which impaired the efficient function of the immune system [2 favors virus replication as a factor required for DMVs’ formation. In this study, linoleic acid (LA) or AA supplementation to the culture cells suppressed replication, which is a result that may be interpreted as a demonstration of the perturbation of the LA/AA axis of the lipid metabolism.Remodeling of the lipid metabolism by virus infection may leave signals at the organism level even some years after healing. The metabolome profile of patients undergoing SARS-CoV-1 infection during the outbreak of 2002–2003 was assessed 12 years after overcoming the pathology . An outs outcome . The aute system . In the e system . Using ae system . The maiIn the COVID-19 outbreak, it has been suggested that increasing the levels of vitamin D could help fighting against the SARS-CoV infection . This su2+ flux by viroporins might favor the membrane fusion through the interaction of this cation with the phospholipid headgroups and concurrently facilitate the required dehydratation reaction. Viroporins are not required for virus replication with the exception of rotaviruses and picornaviruses; thus, whether this function is exerted through the ion channels or another property of viroporins remains an issue still unknown [Lipids, as components of membranes, are related to viroporins, which are specific viral proteins that are known to create ion channels for ion trafficking ,126,127. unknown . The lip unknown . FurtherRemodeling of the virus-induced host cell lipid metabolism is a remarkable feature of the viral infection that affects viral entry, replication of the genomic material, and the releasing of progeny. A comperhensive view of the process is illustrated in


Grapevine Pinot gris virus (GPGV) is a putative causal agent of grapevine leaf mottling and deformation disease that has been reported worldwide throughout the grapevine-growing regions. Fifty-four grapevines collected from five Algerian grapevine-growing regions were tested for the presence of GPGV in phloem tissues. Eight of the tested grapevines were infected by GPGV. Viromes of two selected Vitis vinifera cv. Sabel grapevines infected by GPGV and showing virus-like symptoms were analyzed by small RNA sequencing. Phylogenetic analyses of the partial coding sequence (cds) of the RNA-dependent RNA polymerase (RdRp) domain showed that all Algerian GPGV isolates were grouped with some already-described asymptomatic isolates. This study provides the first survey of the occurrence of GPGV in Algeria. Moreover, Grapevine fleck virus, Grapevine rupestris stem pitting-associated virus, Grapevine virus B, Grapevine rupestris vein feathering virus, Hop stunt viroid and Grapevine yellow speckle viroid 1 were detected in Algeria for the first time. Grapevine Pinot gris virus (GPGV) is a member of the genus Trichovirus in the family Betaflexiviridae. The virus was initially described in the Italian grapevine cv. Pinot gris in which it causes grapevine leaf mottling and deformation disease (GLMD) [e (GLMD) ,2. GPGV e (GLMD) , and wase (GLMD) , Armeniae (GLMD) , Australe (GLMD) , Brazil e (GLMD) , Chile [e (GLMD)  and Pakie (GLMD) .It is not easy to assess the economic impact of GPGV because many strains do not provoke GLMD symptoms ,3,10. SeApple chlorotic leaf spot virus [The genomic RNA of GPGV consists of three open reading frames (ORFs). ORF1 represents 1865 amino acids (aa) (214 kDa) and encodes replicase-associated proteins, methyltransferase (44–333 aa), helicase (1040–1277 aa) and RNA-dependent RNA polymerase (RdRp) 1447–1797 aa). ORF2 encodes a 376 aa (42 kDa) polypeptide homologous to a movement protein, and ORF3 encodes the 195 aa (22 kDa) putative coat protein , ORF1 of97 aa. ORThe presence of sequence variations in GPGV isolates remains unknown worldwide. There have been a few studies on the variability of the GPGV genome, and they have suggested that the genome is genetically diverse and consists of numerous haplotypes ,12,18,19Grapevine leafroll-associated virus-1 [Grapevine leafroll-associated virus-2 [Grapevine leafroll-associated virus-3 [The grapevine virome is not well described in Algeria. There have been surveys of  virus-1 , Grapevi virus-2  and Grap virus-3 ; howeverIn June, 2018, field surveys were conducted in nine vineyards located in five wine-growing regions in Algeria: Médéa (Benchicao), Tipaza (Hamr El Ain), Tipaza (Hadjout), Boumerdes and Alger . Fifty-f® G2 Flexi DNA Polymerase . To broaden our knowledge of GPGV occurrence in Algeria, we used PCR assays targeting the RdRp domain of the replicase gene [RNA was extracted directly from 1 g of scraped phloem using the Spectrum Plant Total RNA Kit . RNA was retrotranscribed to cDNA as described by Eichmeier et al. . Subsequase gene . PCR ampase gene .To determine the phylogeny that can be linked to the symptomatic manifestations of the GPGV isolates, sequences available in GenBank and sequences from our previous phylogenetic studies were used, showed the symptomatic manifestations of GPGV infection causing GLMD. We placed the new sequences of the Algerian RdRp domains into the phylogenetic pattern published by Eichmeier et al.  using thThe same extracted total RNA obtained for RT-PCR was used for library preparation. A small RNA library was constructed using the TruSeq Small RNA Library Preparation Kit  and purification and quality control were done as described by Eichmeier et al. . For thehttp://hannonlab.cshl.edu/fastx_toolkit/), specifying the Q30 parameter, was used to remove the adaptors (TGGAATTC), and sequences shorter than 15 nucleotides were discarded. Contigs of individual reads were assembled de novo using Velvet-1.2.10 [−5 [Quality control was performed by FastQC-0.10.1 software . A FASTXt-1.2.10  with k-m2.10 [−5 . The sam2.10 [−5 . Then, sThe presence of the viruses was determined based on the consensus of the results regarding the BLASTn contigs and mapped reads in the references. In contrast to our previous studies, where the sequencing depth was greater ,28, in tFifty-four grapevines were tested for the presence of GPGV in phloem tissues. We detected eight GPGV-positive grapevines . We idenGrapevines in the Boumerdes region showed grapevine leaf deformation  but did Molecular phylogenetic analysis based on the RdRp domain sequences compared 44 sequences from Italy and Slovakia , Poland Grapevine virus B and Grapevine rupestris vein feathering virus were detected only in AL_41. The results of small RNA sequencing were verified by RT-PCR detection, which indicated that all the detected viruses and viroids were indeed present in the tested materials, thus achieving verification by at least two methods (see Discussion and Sequenced libraries represented the sRNA populations extracted from the two selected grapevines: AL_41 and AL_42 of cv. Sabel from the Bourmedes region. The libraries were sequenced by the sequencing by synthesis (SBS) approach and contained 1,588,329 reads (AL_41) and 1,604,641 reads (AL_42). De novo assembly of the sequenced reads and a BLAST search for homologies of the obtained contigs identified eight viruses and two viroids in two grapevines . Two virGrapevine fleck virus (GFkV), genus Maculavirus, family Tymoviridae, was detected in both grapevines. A total of 382 reads were assembled for grapevine AL_41 (genome coverage 51%) and 348 reads for AL_42 (genome coverage 53%). GFkV causes latent infections in Vitis vinifera cultivars, but induces specific foliar symptoms in the indicator host, Vitis rupestris. The foliar symptoms include clearing of the veinlets in young leaves. Those symptoms were not observed.Grapevine rupestris stem pitting-associated virus (GRSPaV), belonging to the genus Foveavirus, family Betaflexiviridae, was detected in both AL_41 and AL_42 grapevines. A total of 227 reads were assembled by CLC Genomics WB 6.5.1 (genome coverage 17%) for AL_41 and 216 reads (genome coverage 19%) for AL_42. GRSPaV infection was confirmed by RT-PCR in both isolates. Symptoms of GRSPaV, modified wood (pitting), were not observed.Hop stunt viroid and Grapevine yellow speckle viroid 1 were detected in both grapevines. These viroids are reported to occur worldwide in wine-producing countries as latent viroids in grapevines. Their economic impact on grapevines has not been reported.GPGV was reliably detected in both grapevines, with a genome coverage ranging from 74% and 349 reads (AL_41) to 89% and 549 reads (AL_42).Grapevine virus B (GVB), genus Vitivirus, family Betaflexiviridae, was detected in plant AL_41, and 149 reads were assembled by CLC Genomics WB 6.5.1 and genome coverage was only 3%. RT-PCR clearly confirmed the presence of the virus. The virus is associated with rugose wood symptoms in grapevines and the symptoms were not observed in grapevine AL_41.Grapevine rupestris vein feathering virus (GRVFV), genus Marafivirus, family Tymoviridae, was detected in plant AL_41, 371 reads were assembled and genome coverage was 13%. RT-PCR confirmed the presence of the virus. The virus causes asteroid-like symptoms that were not observed on grapevine AL_41.Grapevine leafroll-associated virus 2 (GLRaV-2), genus Ampelovirus, family Closteroviridae, was detected in plants AL_41  and AL_42 . The leafroll symptoms were not observed.Grapevine leafroll-associated virus 3 (GLRaV-3), genus Ampelovirus, family Closteroviridae, was detected in plants AL_41  and AL_42 . The virus had the greatest number of reads among all of the viruses. The leafroll symptoms were not observed.The survey of GPGV was performed according to the observed symptoms in 54 grapevines in five Algerian regions. In Algeria, there is no clear evidence of the presence of grapevine viruses in the vineyards, except for the surveys of GLRaV-1 , GLRaV-2We detected GPGV in 8 out of 54 grapevines (15% of the tested grapevines). We observed the symptoms as described in the Results, but none of the symptoms (GLMD) appeared to be linked with GPGV infection. This observation is supported by the phylogenetic analysis of the partial RdRp domain as initially described by Saldarelli et al. . The etiIn this study, we detected GLRaV-2 and GLRaV-3 in agreement with the studies of Lehad et al. ,22. AccoLehad et al.  reportedTo the best of our knowledge, this study is the first to report the detection of Grapevine fleck virus, Grapevine rupestris stem pitting-associated virus, Grapevine virus B, and Grapevine rupestris vein feathering virus, and viroids Hop stunt viroid and Grapevine yellow speckle viroid 1 in Algeria.Grapevine fleck virus, Grapevine rupestris stem pitting-associated virus, Grapevine virus B, Grapevine rupestris vein feathering virus and viroids Hop stunt viroid and Grapevine yellow speckle viroid 1 are reported in Algeria for the first time.The outcomes of this study provide novel insights into the presence of GPGV in grapevines in Algeria. The results revealed that GPGV did not show typical symptomatic behavior (GMLD) in eight out of fifty-four sampled grapevines. The GPGV isolates were mostly clustered in a separate group, showing that GPGV in Algeria consists of local strains. Additionally, based on high-throughput small RNA sequencing, the two selected cv. Sabel grapevines showed infection with nine viruses and viroids.