Viruses cause significant yield and quality losses in a wide variety of cultivated crops. Hence, the detection and identification of viruses is a crucial facet of successful crop production and of great significance in terms of world food security. Whilst the adoption of molecular techniques such as RT-PCR has increased the speed and accuracy of viral diagnostics, such techniques only allow the detection of known viruses, i.e., each test is specific to one or a small number of related viruses. Therefore, unknown viruses can be missed and testing can be slow and expensive if molecular tests are unavailable. Methods for simultaneous detection of multiple viruses have been developed, and (NGS) is now a principal focus of this area, as it enables unbiased and hypothesis-free testing of plant samples. The development of NGS protocols capable of detecting multiple known and emergent viruses present in infected material is proving to be a major advance for crops, nuclear stocks or imported plants and germplasm, in which disease symptoms are absent, unspecific or only triggered by multiple viruses. Researchers want to answer the question “how many different viruses are present in this crop plant?” without knowing what they are looking for: RNA-sequencing (RNA-seq) of plant material allows this question to be addressed. As well as needing efficient nucleic acid extraction and enrichment protocols, virus detection using RNA-seq requires fast and robust bioinformatics methods to enable host sequence removal and virus classification. In this review recent studies that use RNA-seq for virus detection in a variety of crop plants are discussed with specific emphasis on the computational methods implemented. The main features of a number of specific bioinformatics workflows developed for virus detection from NGS data are also outlined and possible reasons why these have not yet been widely adopted are discussed. The review concludes by discussing the future directions of this field, including the use of bioinformatics tools for virus detection deployed in analytical environments using cloud computing. Rapid detection and identification of viruses in cultivated plants is very important for successful crop production. Viruses cause significant yield and quality losses in a wide variety of agricultural crops and have an important negative economic impact Rybicki, . All typWhilst the adoption of molecular techniques such as reverse transcriptase-polymerase chain reaction (RT-PCR) has increased the speed and accuracy of viral disease diagnosis in crops, such techniques only allow the detection of known viruses, i.e., each test is specific to one or a small number of related viruses  and CLC Genomics Workbench (www.clcbio.com)] were used to de novo assemble reads into contigs. Contigs with lengths >1,000 nucleotides were then aligned to the GenBank database  and a single virus isolate was detected in one wild garlic plant . In total 41 virus isolates were identified including potyviruses , allexiviruses  and carlaviruses . This study was the first to obtain the complete genomes of two isolates of GarVD, and to show the presence of the potexvirus Asparagus virus 3 in wild garlic (which grows as a weed) in Australia.The viral content of garlic has been analyzed using RNA-seq to make the case for using multiplex methods for virus detection in the context of plant quarantine systems  using RNA-seq analysis , PepLCBV (Pepper leaf curl Bangladesh virus), and TVCV (Tobacco vein clearing virus) having the highest number of contigs matched. In addition this study identified a novel virus, Pepper Virus A (PepVA).Multiple viral infections have also been identified in pepper plants (Pyrus pyrifolia) transcriptome helped to confirmed this  in a merlot vineyard in South Africa  is known to be infected by more than 30 viruses  have recently been lost from Citrus sudden death (CSD) disease in the Sao Paulo State of Brazil. It was thought that CSD was caused by a variant of the Citrus tristeza virus (CTV) and RNA-seq was performed on CSD-symptomatic and -asymptomatic plants to test this hypothesis  and Trinity  co-infection of individual plants with more than one virus, (b) the identification of viruses in asymptomatic plants, (c) different viruses or levels of viruses associated with different parts of the plant, (d) different analysis tools giving rise to different viruses being detected, (e) the identification of novel viruses and/or novel virus isolates, and (f) identification of viruses in specific geographical regions or in host species where they have not been observed previously. As summarized, these studies were conducted using different virus detection workflows that included different algorithms, tools and databases. The main elements of many of the methods included (a) quality control of the raw reads, (b) assembly of raw reads into contigs, (c) the removal of host sequences by alignment to a host genome and (d) identification of viral reads by mapping to a virus database Figure . Whilst The need to achieve the types of analyses described in the previous section has given rise to a number of bioinformatics tools designed to complete the analysis in a workflow. Recent methods  are summarized in Table k-mer profiling  uploading raw sequence reads (comprising both host and virus) from a sequencing platform, (2) conducting quality control measures on raw data files, including trimming of poor quality reads and adaptor sequences, (3) identifying and removing host reads, (4) identifying known viruses and ideally (5) providing a method for the identification of novel viruses and/or strains  comes in analyzing the data in a meaningful way. In small research groups without a bioinformatician or access to a bioinformatics core facility, sequence analysis is often conducted by the non-expert using online resources. Whilst the latest published method might offer “better” virus detection, it is of little use to the non-expert if the software requires local installation, knowledge of the Linux operating system, is dependent upon the installation of additional programs or modules or the installation of a separate analytical environment. So we asked the question; of those tools in Table Those tools providing online access, not requiring local installation of software or analysis environments, and with the potential to analyse plant samples are Taxonomer , but of the 13 originally identified in pepper the tool successfully identified 8 . The exclusion of plants as a k-mer database for classification influences the results given by this tool. Better results were obtained for pepper, which might reflect the paired-end nature of the RNA-seq data, or the fact that the default k-mer size (21) used to create the k-mer databases might be more suited to one dataset than the other. However, because this tool is using k-mer profiling and matching rather than mapping and assembly it is incredibly quick. It took <10 h to return results for the 9.7 M reads of the pepper transcriptome. These results indicate that as a first automatic screening of RNA-seq data Taxonomer  the upload of large NGS raw read files, (b) computer intensive data processing steps , (c) reliance upon pre-computed custom databases and (d) how to make the tools available. In addition, the problem of identifying novel viruses is not directly addressed by any bioinformatics tool, as it requires iterative rounds of assembly and mapping by a user with expert knowledge of viral genomes. The problem of tool availability is one of the most difficult ones to solve. A webserver is the best option for the non-expert (as exemplified above), but this requires significant computer hardware at the remote site and can be accompanied by difficulties of uploading large files [although this was successfully achieved for Taxonomer (Flygare et al., The use of web based analytical environments such as Galaxy (Afgan et al., k-mer based methods could be incorporated into an analytical environment such as Galaxy (Afgan et al., Galaxy (Afgan et al., SJ: formulated the review and wrote 70% of the review. AB: collated information for the tools reviewed. SM: 10% contribution to writing review. LT: 20% contribution to writing review and coordinated work for review.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


The multicentre randomised controlled PEPaNIC trial showed that withholding parenteral nutrition (PN) during the first week of critical illness in children was clinically superior to providing early PN. This study describes the cost-effectiveness of this new nutritional strategy.n = 673 versus n = 670 patients) in the Belgian and Dutch study populations from a hospital perspective, using Student’s t test with bootstrapping. Main cost drivers were identified and the impact of new infections on the total costs was assessed.Direct medical costs were calculated with use of a micro-costing approach. We compared the costs of late versus early initiation of PN (p = 0.007) than for patients receiving early PN . Since late PN was more effective and less costly, this strategy was superior to early PN. The lower costs for PN only contributed 2.1% to the total cost reduction. The main cost driver was intensive care hospitalisation costs . The patients who acquired a new infection (14%) were responsible for 41% of the total costs. Sensitivity analyses confirmed consistency across both healthcare systems.Mean direct medical costs for patients receiving late PN  were 21% lower  contains supplementary material, which is available to authorized users. Healthcare costs are growing worldwide. Intensive care is responsible for a substantial proportion of all healthcare expenses, particularly prolonged intensive care and palliative care –4. Intenn = 1.440) concluded that withholding parenteral nutrition (PN) during the first week of critical illness in children was clinically superior to providing PN within 24 hours when enteral nutrition was insufficient [Recently, a multicentre, randomised, controlled, parallel-group, superiority trial, with the acronym PEPaNIC . Our cost-effectiveness analysis was predesigned, offering a unique opportunity for a micro-costing approach . With thWe hypothesised that withholding PN for one week is a cost-saving strategy comprising more than merely omitting the costs of PN itself. The aims of this study were (1) to compare total direct medical costs of early versus late initiation of PN in the PICU from a hospital perspective in an international context, (2) to provide detailed insight into the distribution of cost components, and (3) to assess the impact of acquiring a new infection in the PICU on direct medical costs.n = 717) received no PN during the first week of critical illness. Patients assigned to the group with early initiation of PN (n = 723) received PN within 24 hours, according to the local standards. After the first week, when patients were still in the PICU and EN was insufficient to meet nutritional goals, PN was administered equally in both groups according to standard nutrition protocols [A total of 1440 critically ill children, aged 0 (term neonates) to 17 years, from three large tertiary referral PICUs in three countries  were randomly assigned to early initiation of PN (standard care) or late initiation of PN (intervention). Initiation and dose of enteral nutrition (EN) and the administration of trace elements, minerals and vitamins were identical in both groups. Patients assigned to the group with late initiation of PN  . HoweverIn Belgium, healthcare costs are reimbursed by sickness funds and private insurance companies. Since all healthcare activities are represented in the patients’ invoices, these invoices can be used to accurately quantify healthcare consumption. However, total healthcare costs are mainly covered by advance payments to the hospital, directly by the government. Consequently, for healthcare activities for which the hospital receives these advance payments, only 25% of the costs are represented in the patients’ invoices. When this is corrected to 100%, they reflect real healthcare costs from a hospital perspective [The participating clinicians filled out standardised case report forms during the ICU stay, including duration of ICU dependency, post-ICU hospitalisation, mechanical ventilation, renal replacement therapy (RRT) and mechanical hemodynamic support. LOS encompassed both index and transferral hospitals. PN consumption was obtained from the study database for Dutch patients and from the invoices for Belgian patients. Detailed information on diagnostic procedures, medication, blood products, surgery and consultations were obtained from the data management system of the hospital for Dutch patients and from the invoices for Belgian patients.Healthcare consumption was divided into ten cost categories: (1) ICU hospitalisation ; (2) post-ICU hospitalisation ; (3) PN; (4) medication; (5) laboratory diagnostics; (6) other diagnostics; (7) ventilator support; (8) RRT and mechanical haemodynamic support; (9) surgery; and (10) consultations from other specialists.The cost-effectiveness analyses were based on the Dutch and Belgian guidelines for performing costs studies , 11. FurIn the Netherlands, the unit prices were available from the hospital’s financial database, and were adjusted to the year 2014. For hospital days (non-ICU), a national guiding price per day was used, because children were referred to different hospitals, charging different prices . The daiIn Belgium, financial data were registered by the billing and warehousing collaborators of the index hospital as this is standard procedure for invoicing. The unit prices were official, nationally fixed prices adjusted to the year 2014, and were converted to 100%, if necessary, to obtain real costs from a hospital perspective [Costs of medication were categorised according to the first level of the Anatomical Therapeutic Chemical (ATC) classification, which is the World Health Organisation (WHO) tool for drug utilisation research . Each drThe primary endpoint was the difference in total direct medical costs, from a hospital perspective, between early and late initiation of PN. Furthermore, the ten cost categories were analysed separately. In order to give insight into costs among different groups of patients, we compared total direct medical costs of early initiation of PN with late initiation of PN in the stratification groups as used for the PEPaNIC trial: “Surgical cardiac”, “Surgical other”, “Medical neurological” and “Medical other”, and age groups younger and older than one year . AdditioThe PEPaNIC trial was a priori statistically powered to detect a difference in new infections. Therefore, the statistical power to detect differences in total direct medical costs was dependent on the number of patients enrolled in the original PEPaNIC trial. This cost analysis was an a priori planned secondary analysis.Costs were reported in euro (€), as mean (SD and IQR), as recommended for cost analyses . IQR wast test with bootstrapping (×1000) [p values <0.05 were considered statistically significant. Effects were reported as mean difference or odds ratio (OR) with the corresponding 95% confidence interval (CI). The OR for acquiring a new infection was adjusted for age, risk of malnutrition (STRONGkids group), treatment centre, admission diagnosis, and degree of organ failure (PeLOD score), in line with the PEPaNIC trial [Costs were compared univariably using Student’s one-tailed  (×1000) , LOS wasIC trial , and alsThe total costs were analysed using prices from the Belgian healthcare system for all patients.The total costs were analysed using prices from the Dutch healthcare system for all patients.The total costs were analysed separately in the Belgian patients.The total costs were analysed separately in the Dutch patients.As only the hospitalisation costs of the post-ICU period were included in the primary analysis, the additional post-ICU costs  were left out. Since this could underestimate our results, the estimated additional post-ICU costs were added in the third sensitivity analysis. These additional post-ICU costs were estimated based on the invoices of the Belgian patients.Sensitivity analyses were conducted as follows:We compared the total direct medical costs of late initiation of PN (N = 673 patients) with those of early initiation of PN (N = 670 patients) in the Dutch and Belgian study populations. The patients’ baseline characteristics and main clinical outcomes are described in Table p = 0.007) per patient , which is a saving of 21% , p < 0.001), which might be caused by differences in patient populations. In contrast, the Belgian costs per day in ICU  were higher (factor 1.18) than the Dutch costs (p < 0.001). Almost all cost categories showed lower costs with late initiation of PN than with early initiation of PN. The largest reduction was in ICU hospitalisation costs ), medication costs ), and ventilator support costs )    was not apparently related to proportional cost reduction with late initiation of PN  (Table p = 0.001) with early initiation of PN and from €20.600 to €78.210 , p = 0.001) with late initiation of PN, predominantly caused by ICU hospitalisation costs , p = 0.002; late-PN group: difference €27.530, 95% CI , p = 0.001).The proportion of patients with a new infection acquired in the ICU was smaller with late initiation of PN than with early initiation of PN  and J (anti-infectives). This corroborates the finding that late initiation of PN reduces the proportion of patients with new infections, as it also does in adults . AdditioThe strength of this study is the micro-costing approach, reflecting real costs that incurred. Additionally, our findings appeared robust across two healthcare systems. We have carefully checked whether combining the Dutch and Belgian populations would compromise our results by performing sensitivity analyses, which have shown unanimously a cost reduction with late PN, which was well within the range of the confidence interval of the base case. These results may support that the international character of this study increased external validity and, possibly, applicability to other European countries.Some limitations should also be addressed. First, the Dutch daily costs of mechanical ventilation and renal replacement therapy had to be estimated, based on published literature on ICU costs , 14. SecThe cost analyses showed that late initiation of PN reduced the direct medical costs by 21% in critically ill children as compared with early initiation of PN, beyond the expected lower costs for the use of PN itself. Avoiding new infections by late initiation of PN yielded a large cost reduction. Withholding PN during the first week of critical illness in children can thus be recommended both from a clinical and a health-economic perspective.Additional file 1:Pareto charts of the cost categories in Belgian and Dutch patients, shown separately. (DOC 183 kb)Additional file 2:Table showing total healthcare costs split by age into two groups. (DOC 28 kb)Additional file 3:Table showing total healthcare costs split by diagnosis into four groups. (DOC 31 kb)Additional file 4:Table showing resource utilisation and costs per centre separately in Belgian and Dutch patients respectively. (DOC 37 kb)


CCL8/CXCL11), we screened 92 asthmatic and 69 healthy children without illness for respiratory virus infections.Respiratory illness caused by viral infection is associated with the development and exacerbation of childhood asthma. Little is known about the effects of respiratory viral infections in the absence of illness. Using quantitative PCR (qPCR) for common respiratory viruses and for two genes known to be highly upregulated in viral infections  contains supplementary material, which is available to authorized users. The detection of viruses from human biological samples and the determination of their influence on the host cell transcriptome are paramount for understanding complex human diseases that are initiated or exacerbated by virus infections and their sequelae. Even virus detection alone has proven challenging for current methods. First, PCR-based viral amplicon detection strategies are susceptible to cross-reactivity, lack strain specificity, and are inefficient for broad screening due to the lack of a common gene shared across virus species –3. SolutAnother strategy is to perform shotgun sequencing of nucleic acids isolated from the entire, unseparated clinical sample . This method has been previously applied to total nucleic acids (RNA and DNA) extracted from clinical samples for viral detection –13. AlthUpper respiratory tract infections are among the most prevalent of all viral infections in humans and render a dramatic cost on the health care system in terms of lost economic productivity and general well-being. Beyond their acute effects, respiratory virus infections are strongly associated with the development, symptoms, and exacerbation of asthma , 18. ForIn this study, we detail methods for the detection of common respiratory viruses in asthmatic and healthy children using polyA-selected whole transcriptome sequencing. Using these efficient methods, we found that a large proportion of children without respiratory illness were carrying pathogenic and transcriptionally active respiratory viruses. Virus detection using a dual RNA-seq workflow resulted in 86% sensitivity when compared to quantitative PCR (qPCR)-based screening. Additionally, we detected respiratory viruses not targeted by viral qPCR primers in two subjects with high expression of viral response genes, demonstrating the versatility of this method. Despite absence of respiratory illness, viral carriers exhibited a dramatically altered nasal epithelial transcriptome, reflective of active viral infection. Virus levels determined by RNA-seq correlated strongly with host airway viral response gene expression levels. Even virus levels at the limits of detection by qPCR and RNA sequencing had a discernible effect on the host airway epithelial transcriptome. We detail modules of activated gene expression in viral carriers reflective of epithelial cell subtypes, as well as immune cell types. We also report modules of asthmogenic genes that are strongly associated with viral infection. We conclude that viral infection, even in the absence of observable illness, induces epithelial responses in children with and without asthma.CCL8 and CXCL11, were previously reported as among the most upregulated during the peak stage of acute respiratory illness [CCL8 and CXCL11 gene expression and virus levels . Two subjects that were ranked in the top fifth percentile of expression for both biomarker genes were negative for virus by qPCR, and were therefore suspected to be carriers of viral species not covered by the qPCR panel  cohort subjects  were infected with a respiratory virus, despite the absence of respiratory illness  to 164,870 reads  generated per sample. Viral genome read depth plots were generated for all virus-infected samples with >20 viral reads . Therefore, RNA-seq viral detection at this low read depth is highly quantitative, is nearly as sensitive as qPCR viral assay, and has likely unlimited breadth of detection. Examining all subjects either qPCR or RNA-seq positive for virus, we observed a skew in the frequency of virus-infected subjects by season (P = 0.042). This skew was driven by a significant decrease in viral infection frequency in summer  and a trend toward increased infection in the fall .Examining the two qPCR-negative, but suspected virus carriers based on nasal airway epithelial viral biomarker expression, we detected human parainfluenza virus 4a (HPIV-4a) in one sample and influenzavirus B in the other sample. Neither viral species was tested in our qPCR assays. Examining all samples with virus detected by both methods, there was a strong positive correlation between qPCR viral signal and the proportion of viral reads in RNA-seq data  and (2) Virus-Low: remaining subjects harboring a respiratory virus (n = 10)  and many interferon-induced genes . Moreover, Gene Ontology (GO) analysis of the top differentially expressed genes  resulted in hits for defense response to virus (P = 4.5 × 10−23) and the virus responsive, interferon-gamma-mediated signaling pathway (P = 2.1 × 10−21)  Virus-High subjects: with viral genome coverage of > =1x  [We next examined whether genes previously shown to be upregulated in acute viral infection of the nasal airway are discriminatory for infected subjects without illness. We found 55 of the 56 genes previously reported as upregulated during the peak stage of acute viral respiratory illness were upregulated in our Virus-High subjects  .P < 2.2 × 10−16). These results indicate that respiratory virus infection of the airway epithelium without clinical illness can mediate epithelial expression changes characteristic of active acute infection.Secondly, we determined the in vitro primary airway epithelial transcriptional response to acute respiratory virus infection to draw comparisons to the transcriptional signature exhibited in vivo among the Virus-High subjects without illness. To accomplish this, we performed whole transcriptome paired differential expression analysis of HRV-A16-infected and mock-infected mucociliary differentiated airway epithelial cell cultures from three donors ). Closer investigation of those genes revealed downregulation of the ribosomal subunit genes, which predicted activation of EIF2AK2. The EIF2AK2 gene encodes for a kinase which is activated by virus infection to inhibit expression of translational machinery, as a host viral defense mechanism [EIF2AK2 expression was among the 58 significantly upregulated genes in the Virus-Low subjects. The upregulated genes showed a significant enrichment in non-activated (P = 3.89 × 10−09) and activated neutrophil (P = 1.82 × 10−07) signatures, as well as an activated macrophage signature (P = 3.20 × 10−02). These 100 genes separated the Virus-Low subjects from No-Virus subjects in an MDS analysis  between the Virus-Low and No-Virus subjects   to the 8CCL8 among the 199 genes, suggesting that this gene is only expressed by the immune cells infiltrating the nasal airway. We found strong over-representation of these 199 in vivo infection-specific genes in the blue and pink modules by hypergeometric testing , with no over-representation of these genes found among the remaining expression modules. We then explored which activated leukocyte populations might be represented by these modules by examining enrichment of the module genes in the publicly available expression datasets of specific activated immune cell populations [Five of the detected modules  had highly correlated expression patterns, which were characterized by high module eigengene expression values in Virus-High subjects and low values in the No-Virus samples, regardless of asthma status Table . Enrichmulations  (AdditioP = 1.52 × 10−33) and genes involved in the eIF2 signaling pathway, and had a statistically significant overlap with the genes differentially expressed in the Virus-Low group  [https://www.qiagenbioinformatics.com/products/ingenuity-pathway-analysis/) predicted IL-13, the primary driver of Th2 inflammation [RFX3 transcription factor binding sites. The RFX family of transcription factors is known to drive the expression of genes involved in motile cilia formation of metazoans [The remaining three modules were associated to varying degrees with asthma among non-viral carrying samples Table . In fact ALOX15) , 33 wereammation , to be tammation . Lastly,etazoans .Dual RNA sequencing of host and microbe has been proposed as a groundbreaking method to simultaneously detect/quantify microbes and reveal their influence on the host transcriptome . To date7/sample) was sufficient to detect virus infection at species and even strain level among subjects without illness.We suspect that several features of our study design aided in successful virus detection in these samples. First, our immediate lysis of the complete sample and application of the total lysate onto the RNA column without pre-processing steps allowed us to avoid cumbersome, potentially biased, separation methods that could have resulted in loss of viral RNA. Secondly, we took advantage of the fact that most respiratory viruses have polyadenylated RNA genomes and that their expressed transcripts are also polyadenylated –41. We pDetection of viruses in asymptomatic children has been previously reported by multiple PCR studies, which detected viruses in 33–52% of asymptomatic subjects using nasopharyngeal swabs and washings , 42–45. EIF2AK2, leading to inhibition of viral replication, and infiltration of airway epithelium by activated neutrophils.The dual RNA-seq method applied to host-dominated samples allowed us to determine that a clinically “silent” carriage of respiratory viruses results in dramatic alterations of the airway molecular phenotype with 8126 genes significantly affected. Comparison of acute in vitro experimental viral infection of airway epithelium and GO analyses of viral infection categories revealed high similarity between signatures of viral carriage without illness and active viral response. We did not observe significant differences in airway expression between asthmatic and healthy control subjects carrying a respiratory virus. We did note, however, that three of the nine modules associated with viral carriage were also associated with asthma status in uninfected subjects. Interestingly, we found that genes associated with type 2 airway inflammation, a common airway endotype in asthma, were also expressed much lower in virus-infected asthmatic and healthy children than in subjects without any viral reads detected. The association of viral infection with dampened type 2 inflammation may be due to anti-viral immune cells infiltrating the airways. Supporting this, we found viral gene response modules strongly characteristic of activated macrophage and neutrophil populations. This finding is significant, as it strongly suggests that not only are epithelial cells responding to the presence of a virus, but that the local immune system is being directed by the level of virus carriage we detect. Additionally, we identified a subset of the differentially expressed genes that were significantly altered even in subjects with very few viral reads present. These genes represented host suppression of ribosomal subunit genes by activated We acknowledge multiple factors in our study that limit interpretation of our results and raise important questions beyond the scope of this work. Namely, mild respiratory illness may not have been reported or recognized in some subjects due to community recruitment. Additionally, symptoms and severity of rhinitis were not explicitly scored on study subjects, preventing tests of association here. Additionally, the cross-sectional nature of our study does not allow us to determine if the viral carriage we detect pre-dates, post-dates, or is unrelated to a clinically significant viral infection. It is unlikely that our detection post-dates infection, since a recent respiratory illness (6 weeks prior) was among the study exclusion criteria for the asthmatics. We acknowledge that the lack of recruitment of symptomatic patients to the study prevented us from conducting a comprehensive comparison of the effects of the viral infection without illness to viral infection effects in patients with illness. Moreover, the collection of only a single sample from subjects did not allow us to determine the persistence of this viral carriage. Furthermore, the polyA-enrichment protocol limits this method to detection of viruses with polyadenylated genomes and transcripts and would miss any viruses without those characteristics potentially present in the samples. Finally, while dual RNA-seq was initially proposed for studying host-microbiome interactions in bacterial infections , the appWe applied a protocol and analytical workflow for dual RNA-seq of nasal airway epithelial brushings to concurrently detect respiratory viruses and generate the host airway transcriptome in one sample preparation and sequencing experiment. The viral detection with this method achieved 86% sensitivity when compared with qPCR-based respiratory virus detection. The sensitivity, specificity, and scope of this method resulted in the detection of multiple respiratory viruses and provided sufficient resolution to distinguish between virus species and strains in infected subjects with low total viral read percentages. Co-generation of the host transcriptome data allowed us to determine that molecular function of the airway is greatly altered by a “silent” virus carriage, which is characterized by immune cell infiltration of the airway, downregulation of ciliated cell gene expression, and modulation of type 2 inflammatory and other asthma-associated gene expression patterns.All nasal brushing analysis subjects included in this study were recruited as a part of the Genes-environments and Admixture in Latino Americans II (GALA II) childhood asthma cohort. The asthmatics and controls included in this study were randomly selected. Asthma was defined by physician diagnosis and the presence of at least two asthma symptoms . Study recruitment excluded subjects with respiratory illness as judged by a recruiting nurse evaluating cold symptoms. Additional study exclusion for asthmatics included a reported respiratory illness in the past 6 weeks. Clinical characteristics including medication usage and asthma symptoms in the past 2 weeks are listed in Additional file Cytology brushes were used to collect airway epithelium from the posterior surface of the inferior turbinate from children with and without asthma (controls) as part of the GALA II study  , respiratory syncytial virus (RSV), human metapneumovirus (HMPV), human parainfluenza virus 1 (HPIV1), human parainfluenza virus 2 (HPIV2), and human parainfluenza virus 3 (HPIV3). Each assay was conducted using RNA extracted from the nasal airway brushings of 161 GALA II study subjects . Specifically, RNA was reverse transcribed using oligo-dT primers and SuperScript III Reverse Transcriptase (Invitrogen). The cDNA synthesized for each sample was used for qPCR assays (5 ng per reaction) using specific primers and probes for each viral species as previously described . The qPCCCL8 and CXCL11 genes was measured by qPCR assays in RNA extracted from the nasal airway brushings of the same cohort of 161 GALA II study subjects  as used for the virus detection qPCR assays. The cDNA was synthesized as described above, and each qPCR reaction was run using 5 ng of cDNA template and custom PrimeTime qPCR assays for the biomarkers CCL8 (Hs.PT.58.39289889.g), CXCL11 (Hs.PT.58.26723814), and the housekeeping gene GusB (Hs.PT.51.2648420) (IDT Technologies). The qPCR amplification cycling was conducted as follows: 3 minutes at 95 °C, followed by 40 cycles of denaturing for 10 seconds at 95 °C, and annealing for 30 seconds at 60 °C. The Ct values for CCL8 and CXCL11 were normalized to GusB expression levels within each sample, and gene expression values were determined using the comparative Ct analysis method [Expression of the CCL8 and CXCL11 expression, and 25 randomly selected samples with no suspected asymptomatic virus carriage. Barcodes and adapters compatible with the Ion Torrent Proton sequencing instrument were used. Sequencing was conducted with P1 chips. The viral pathogen detection pipeline is schematically illustrated in Fig. Kapa Biosystems mRNA-seq library kits  were used to generate sequencing libraries for Ion Torrent whole transcriptome sequencing for the 21 samples with respiratory virus detected by qPCR, 2 samples with suspected viral infection based on high https://www.qiagenbioinformatics.com/products/ingenuity-pathway-analysis/). Enrichment for type 2 inflammation genes was performed with hypergeometric testing using a list of 70 genes from Poole et al., 2014 [Reads uniquely mapping as human with GSNAP  were usel., 2014 . Enrichml., 2014  obtainedl., 2014  and Genel., 2014 , in the l., 2014 . All othl., 2014  for genel., 2014  for genel., 2014  implemen5 cells per insert. At 24 hours post-plating, airway media 1 was replaced with airway medium 2 containing 2% Ultroser G [2; control inserts were incubated with X-Vivo media alone in the apical chamber. Both the apical and basolateral chambers of the inserts were washed three times with warmed PBS, fresh airway media 2 containing USG was added to the basolateral chamber, and the apical chamber was left at the air-liquid interface for an additional 24 hours in a 37 °C incubator. Inserts were washed with PBS, cell monolayers lysed in RLT buffer, and RNA was extracted using an RNA Miniprep Kit (QIAGEN).Human tracheal airway epithelial cells from three donors were cultured using a modified Schlegel method as previously described –67. Basatroser G . CultureP values <0.01, and absolute log2 expression fold changes > =1 were then used to assess whether viral infections without illness in vivo demonstrate similar expression changes as in vitro airway epithelial HRV infection.RNA-seq libraries were prepared using the standard protocol for the Ion AmpliSeq Transcriptome Human Gene Expression Kit. The prepared libraries were multiplexed and sequenced on the Ion Torrent Proton sequencer. Raw sequencing reads were mapped to human transcriptome reference hg19) and gene count tables were generated with ampliseqRNA plugin v.5.0.0.0 and Torrent Suite v5.0.4 (Additional file 9 and genA second nasal brushing collected at the same time as the brushing used for RNA-seq was solubilized, and the cells were cytospun, H&E stained, and imaged by standard methods.


Arracacha virus A from a Peruvian arracacha sample collected in 1975 and compare it with the genomes of other nepoviruses. Its RNA1 and RNA2 both had greatest amino acid identities with those of the subgroup A nepovirus Melon mild mottle virus.We present here the first complete genomic sequence of  Arracaccia xanthorhiza), family Apiaceae] showing pronounced leaf mosaic symptoms. The virus was mechanically transmissible to 38 species from 10 plant families. Following characterization using electron microscopy, density centrifugation, and serology, it was identified as a member of the Nepovirus genus and named Arracacha virus A (AVA)  . In 1978In 2015, total RNA was extracted from the freeze-dried AVA-infected leaf material using an RNeasy kit , including the optional DNase treatment. An indexed plant ribosome-subtracted sequencing library was then produced from the total RNA using the ScriptSeq complete plant leaf kit , according to the manufacturer’s instructions. The indexed library was then sequenced along with others on a MiSeq instrument (Illumina), using a 600-cycle V3 kit. The resulting 492,656 paired reads were trimmed on the 3′ end to a quality score of 20 using Sickle (Melon mild mottle virus (39%) (Grapevine fanleaf virus (36%) (Melon mild mottle virus and Potato black ringspot virus (Nepovirus genus.The AVA RNA1 encoded a putative 266-kDa polyprotein with an amino acid identity resembling those of the subgroup A nepoviruses us 39%)  and Grapus (36%) . The AVA%  and GrKY569301 (RNA1) and KY569302 (RNA2).The sequences were deposited in GenBank under accession numbers


Nepovirus. Sequence comparisons using the Pro-Pol region and the coat protein, including phylogenetic analysis of these regions, showed closest relationships with nepoviruses. The data obtained support the taxonomical status of this new virus  as a member of the genus Nepovirus, subgroup B.The complete bipartite genome (RNA1 and RNA2) of a new nepovirus infecting potato was obtained using small RNA sequencing and assembly complemented by Sanger sequencing. Each RNA encodes a single polyprotein, flanked by 5’ and 3’ untranslate regions (UTR) and followed by a poly (A) tail. The putative polyproteins encoded by RNA1 and RNA2 had sets of motifs which are characteristic of viruses in the genus The online version of this article (doi:10.1007/s00705-016-3147-6) contains supplementary material, which is available to authorized users. Nepovirus  of plant viruses has been divided into three subgroups  based on the length and packaging of RNA2, serological properties, cleavage site specificity of the proteinase, and phylogenetic analysis of the coat protein sequence [Tobacco ring spot virus (TRSV) [Potato black ring spot virus (PBRSV) [Tomato black ring virus (TBRV) has been reported to infect potato, but only in Europe. Infection of TBRV in potatoes is normally only sporadic, and the virus is considered of only minor importance in this crop [The genus sequence . There a (PBRSV) ; however (PBRSV)  confirme (PBRSV) , but thehis crop . In thishis crop , 8.Leaves of native potato plants that showed calico symptoms were collected during the rainy season March, 2010) at Quichas  . Total RNA was extracted from these leaves using Trizol reagent  following the manufacturer’s instructions. Small RNAs were isolated of one plant as described previously , and the at QuichNepovirus, subgroup B. Both RNAs . A phylogenetic tree generated using alignments of these regions located PVB in the subgroup B of the genus Nepovirus  tail, respectively. Their predicted genomic organization is similar to that of other members of the genus Primers, that amplify the polymerase region and were used to confirm the genome obtained, were also used to detect this virus in leaves of additional potato plants with calico symptoms collected from Pasco and Junín (departments in Peru) . From 151 samples from Pasco, 28 were positive (19%); however, out of 67 samples evaluated from Junín, only two were positive (3%) (Table S2). The amplified 1,977 bp RdRp fragment of some positive samples were also sequenced to evaluate the PVB variability. In the phylogenetic tree produced with these sequences, two groups could be distinguished (86.8% average nt identity between the two groups and >98.7% or 95.7% identity within the two groups respectively), but there seemed to be little geographic relationship Nepovirus within subgroup B, according to [Xiphinema, Longidorus, or Paralongidorus in the order Dorylaimida, family Londigoridae [Longidorus is so far the only nematode genus reported to transmit subgroup B nepoviruses, whereas the genus Xiphinema and Paralongidorus were reported to transmit subgroup A and C nepoviruses. Genus Longidorus is considered a quarantine species by the National Agriculture Health Service  [et al. [Longidorus spp., which had been collected in Peru  and Ciancio et al [Longidorus spp. in Peru. The phylogenetic tree using the symptomatic plants sampled from Pasco and Huancayo show that variability is present in this virus, similar to GFLV as determined by Oliver et al. [The sequence similarity found, the organization genome and the phylogenetic analysis indicated that PVB corresponds to a new virus species belonging to the genus rding to . Many neigoridae . LongidoSpanish) . However [et al.  reportedio et al , 16 alsor et al.  where RdFig. S1 Line graph showing sequencing coverage and depth over the a) RNA1 and b) RNA2 of PVB by siRNA reads of positive  and negative  sense. X axis represents nucleotide position and Y axis represents the fold sequence coverage (frequency) of each nucleotide position (PPTX 410 kb)Fig. S2 Location of fields evaluated. (Purple dots indicate fields where virus was detected and red dots indicate fields where no virus was detected) (PPTX 859 kb)Fig. S3 Phylogenetic tree of PVB isolates constructed from polymerase region amplified showing 2 putative groups. PVB_RNA1 is the sample analyzed by deep sequencing (PPTX 36 kb)Supplementary material 4 (DOCX 19 kb)Below is the link to the electronic supplementary material.


Most importantly, for the first time, we show that the virus-producing phase duration, which lasts 11 h (9.8–12 h), follows a normal-like distribution, and not an exponential distribution as is typically assumed. We explore the significance of this finding and its impact on analysis of plasma viral load decays in HIV patients under antiviral therapy. We find that incorrect assumptions about the eclipse and virus-producing phase distributions can lead to an overestimation of antiviral efficacy. Additionally, our predictions for the rate of plasma HIV decay under integrase inhibitor therapy offer an opportunity to confirm whether HIV production duration in vivo also follows a normal distribution, as demonstrated here for SHIV infections in vitro.The duration of the eclipse phase, from cell infection to the production and release of the first virion progeny, immediately followed by the virus-production phase, from the first to the last virion progeny, are important steps in a viral infection, by setting the pace of infection progression and modulating the response to antiviral therapy. Using a mathematical model (MM) and data for the infection of HSC-F cells with SHIV  The eclipse phase is defined as the time which elapses between the entry of the first virion which successfully infects the cell and the release of the first virion produced by that newly infected cell. The virus-producing phase, which the cells enter immediately upon leaving the eclipse phase, is defined as the time which elapses between production of the first and last virions by an infected cell, often followed by apoptosis of that cell.In this study, we sought to determine the distributions that describe the amount of time simian CD4nE ≈ 3.5, a finding we reconfirm herein using a different approach. This shape parameter, which we determine herein for both the eclipse and virus-producing phases, is important for a number of reasons. With respect to the eclipse phase, a shape parameter of nE = 1 indicates that cells spend an exponentially-distributed amount of time in the eclipse phase, whereas nE = 20) indicates they spend a normally-distributed time in that phase. An exponentially distributed eclipse length implies that some cells can theoretically produce virus immediately upon infection, which is not biologically possibleIn previous work by our groupnE ≠ 1), it is not normal either (nE  1). Instead, it lies in between (nE = 4), i.e. a distribution that does enforce a delay before initiation of virus production, unlike the exponential distribution, but still keeps an exponential-like distribution for longer waiting times, unlike the very symmetric normal distribution. In other words, it allows for some cells to take a much longer than average time to produce their first virion progeny, referred to as a fat-tailed distribution. We believe this is because one of the processes involved in early SHIV replication is significantly longer than others, and possibly accounts for most of the eclipse phase’s duration. We suspect this step to be the integration of the reverse-transcribed SHIV DNA into the host cell’s genome. In contrast, we have shown that a virus like influenza A which replicates its segmented, negative-strand vRNA using its own polymerase, i.e. following a process devoid of this particular bottleneck, has an eclipse phase duration that follows a normal distribution23Interestingly, in our previous investigationeen nE = , i.e. a nI = 1) would suggest that the process which leads to the termination of SHIV production in vitro is stochastic, completely independent of the time elapsed since cell infection. It would imply that cessation of virus production by SHIV-infected cells in vitro is not the result of accumulation of toxicity or exhaustion of intracellular host resources by virus replication, nor is it a virus production shut-down built into the virus replication cycle. It is biologically unlikely, and possibly unrealistic, that cessation of virus production not be the result of at least one of these processes. Yet, all mathematical models (MMs) of SHIV to date have invariably assumed the virus-producing phase, i.e. the duration of virus progeny production by SHIV-infected cells, to be exponentially distributed. Herein we show that, at least in SHIV-infected HSC-F cellsin vitro, the duration of the virus-producing phase decisively does not follow an exponential distribution, but rather a normal-like distribution. We also evaluate the impact of assuming an exponentially vs a normally distributed virus-producing phase on the analysis of viral load decays observed in HIV patients treated with various antiviral regimens.While we reconfirm this results for the eclipse phase distribution herein, our main focus in the present work is on determining, for the first time, the shape parameter which describes the phase immediately following the eclipse phase, namely the virus-producing phase, i.e., the duration for which cells infected with SHIV will produce and release virion progeny before this process is shut down, possibly as cells undergo apoptosis. An exponentially-distributed virus-producing phase  to a normal  — to identify this shape parameter for the duration of the eclipse phase. This non-dynamical approach is very attractive because the shape of the eclipse phase length distribution can be directly observed from this data alone, with the mathematical analysis providing a quantitative confirmation of what can already be seen.In previous work50/cell. The total virus concentration (vRNA/mL), the fraction of viable HSC-F cells, and the fraction of virus-producing  were determined at regular intervals over the course of the infection.Herein, we use a more indirect, dynamical approach by explicitly representing the kinetics of SHIV infection with MM 1), presented in the Methods section. This different approach enables us to relax the assumption that all cells were simultaneously infected by the initial inoculum, and allows us to also determine the distribution of the virus-producing phase duration, which until now has been assumed to be exponentially distributed. The experimental data used in the present analysis includes that used in our previous work, presentnI = 1), as is typically assumed in all existing MMs for (S)HIV, or that it is normally distributed . While both distributions visually seem to provide reasonable fit to the data, the fit which assumes that SHIV-infected cells produce virus over a normally distributed amount of time is better  versus normally (τE = 18–20 h) in the eclipse phase before they begin producing SHIV-KS661 progeny. Once underway, virus production proceeds at a rate of 5,000  SHIV virion per cell per day which infected cells maintain for 11 h (95% CR: τI = 9.8–12 h) before presumably undergoing apoptosis. This results in a total burst size of 2,500  SHIV-KS661 virion produced by each SHIV-infected HSC-F cell over its virus-producing lifespan. Despite this high virus yield, infection progresses slowly with 18 h (95% CR: tinf = 14–25 h) elapsed between the start of virion progeny production and infection of the first cell by that progeny, resulting in a modest basic reproductive number of 1.7 (95% CR: R0 = 0.91–2.9). We also confirm our earlier finding that the duration of the eclipse phase follows a fat-tailed distribution that is somewhere between exponential and normal, with a shape parameter value of 4 (95% CR: nE = [3–5]), in agreement with the value of 3.5 obtained previously using a different approachTo investigate this further, we used a Markov chain Monte Carlo (MCMC) approach to determine the posterior likelihood distribution (PLD) for each of the MM parameters. In particular, we sought to determine the likelihood that the virus-producing phase is exponentially nI =  versus nnI. Because values of nI ∈ . As such, the PLD for nI is not a true posterior likelihood density. Nonetheless, this enables us to identify that the mode of the PLD is 12, with a 95% CR of . Furthermore, out of the >7,000,000 MCMC-accepted parameters, corresponding to roughly 100,000 independent parameter estimates (given our autocorrelation length of ~70), not a single one had nI = 1. Therefore, based on Feldman and CousinsnI = 1) is no more than 3 in 100,000 or <10−4.Of greatest interest, however, is the PLD of the parameter characterizing the shape of the distribution for the duration of the virus-production phase, nI fixed to values ∈ . Leaving parameter nI as a free parameter to be fitted was not appropriate given that values of nI can only take on integer values (which causes the fitter to misbehave). We find that fits for nI ∈  have a best-fit likelihood (BFL) >85% that of the very best BFL, obtained here for nI = 20. In particular, we find the BFL increases monotonically from nI = 1 to nI = 20, with the BFL for nI = 1 being <10−4 that for nI = 20. In other words, both the PLD and BFL for parameter nI unambiguously, statistically significantly exclude the possibility that SHIV-infected cells could produce virus progeny for an exponentially distributed (nI = 1) amount of time. Instead, the duration of the virus-producing phase is consistent with a mildly fat-tailed or more normal-like distribution.In The shape of the distribution for the time spent by cells in the eclipse and virus-producing phases can appear to be a theoretical concern of little relevance to our understanding of, and therapeutic approach to, HIV. However, the increasing prevalence of MM analyses, and the ability they confer to determine antiviral efficacy based solely on early viral load decays observed in treated patients, has made them an essential part of the toolkit used in developing, evaluating, and optimizing novel HIV therapies. All MMs must invariably make assumptions and simplifications which, occasionally, can lead to misinterpretations or inaccurate quantification. Here, we tackle one such simplification in the context of our findings regarding the shape parameters of the eclipse and virus-producing phase distributions.in vitro that the duration of the SHIV eclipse phase is fat-tailed distributed, and there is little reason to believe that this would not be the case in vivo. Though we have also established the duration of the virus-producing phase is normally distributed in vitro, this might not be the case in vivo where host factors and immune responses could abrogate or otherwise significantly affect the actual duration of virus production by HIV-infected cells. Therefore, it is important to understand how the decays predicted using the traditional MM , differ from those of the more biologically correct MMs with a fat-tailed distributed eclipse phase and either an exponential  or normally  distributed eclipse phase. Herein, we explore the impact of this finding on interpretations of antiviral efficacy based on observed patterns of early plasma viral load decay upon therapy initiation in HIV patients.To date, almost all MMs applied to the analysis of HIV infection kinetics have assumed that the durations of the eclipse phase and of virus production by HIV-infected cell are exponentially distributed. In other words, these MMs assume a cell that has just been infected can immediately begin producing virus, and that a cell which has just begun to produce and release HIV progeny is as likely to cease production and undergo apoptosis as one that has been producing virus for hours or even days. In the previous section, we established in vivo HIV clearance rate, antiviral efficacy, and the durations of the eclipse and virus-producing phases. We investigate how that impact in turn depends on the assumptions made regarding the distributions of the eclipse and virus-producing phases . The last row of In The traditional  MM and the two variants considered here all predict a biphasic decay under monotherapy with a INI for most parameter values, as is typically observed in INI-treated HIV patients, without the need to resort to assuming one short-lived and one long-lived infected cell populationcbody) is greater than ~5 h−1 and the duration of virus production is less than ~11 h. While it is now believed the viral clearance rate is greater than 5 h−1, and likely as high as 23 h−1 in vivo is indeed less than 11 h. If it is not, the MM  predicts the duration of virus production would affect both the first and second phase of viral load decay, but not the depth of the shoulder.The MM which assumes a normally distributed duration of virus production  predicts a very sharp decay at a rate proportional to the viral clearance rate, which stops in a shoulder whose depth depends on the antiviral efficacy, followed by a second phase of decay whose rate depends on the duration of the eclipse phase. This shape is observed provided the viral clearance rate  combined with a Markov chain Monte Carlo approach to determine the shape of the distribution describing the time spent by SHIV-infected HSC-F cells in the eclipse and virus-producing phases. In previous work−4) the hypothesis that the duration of virus production by SHIV-infected HSC-F cells follows an exponential distribution. Instead, we find that the Gamma shape parameter for the distribution of time SHIV-cells spend in the virus-producing phase is ~12, consistent with a mildly fat-tailed or normal-like distribution . To our knowledge, this is the first time the virus-producing lifespan of SHIV-infected cells in vitro has ever been shown to follow a normal-like distribution, rather than an exponential distribution as has been assumed in all MMs for (S)HIV until now. This finding is consistent with earlier work by Petravic et al.in vitro are inconsistent with an exponential distribution. Due to the nature of the data used in their analysis, Petravic et al. assumed, rather than identified, that the duration of both the eclipse and virus-production phases followed a fat-tailed, log-normal-like distribution. Such a distribution is consistent with that identified here for the duration of the eclipse phase, but differs from the more normal-like distribution favoured herein by our MCMC analysis for the virus-production phase. However, since Petravic et al. assumed rather than determined the distribution, it is likely that a normally distributed virus-production phase would also successfully reproduce their data.However, the primary aim of the present work was to extract the shape parameter for the phase which follows the eclipse phase, namely the virus-producing phase, i.e. the time elapsed between production of the first and last virus progeny by a productively SHIV-infected cell. MMs for (S)HIV infection kinetics have, up until this point, almost always assumed that the virus-producing phase is exponentially distributed. Herein, our experimental data, MM, and analysis, enable us to statistically exclude  post-infection, and cease approximately 11 h  after they have begun, or 30 h  after the successful entry of the virion which infected them. This appears to be consistent with the distributions parametrised by Petravic et al.in vitro whose mode we visually estimate to be about 28 h (τE) and 12 h (τI), respectively. In contrast, our estimates for the duration of the virus-producing cell lifespan (τI) obtained herein is 1.7–2.1× longer than that obtained in previous workin vitro, was 1.7 , lower than previously estimated in vivo ranges of 4.3–13 assuming no eclipse phase or 5.4–54 assuming an exponential eclipse phase, both estimated in ref. Use of a normally rather than an exponentially distributed virus-producing cell lifespan can also impact estimates of the key SHIV kinetic parameters from MM analysis. Our results establish that SHIV-infected cells begin progeny virus production and release approximately 19 h  pI ∈ 9.8,  h) afterin vivo, such as that by Althaus et al. for HIVet al. for hepatitis C virusMMs are widely used to analyse and interpret the decay of plasma HIV load in patients treated with antivirals. Hence, we also investigated the impact of assuming the eclipse and virus-producing phases are exponentially distributed, as is typically done, in analysing and interpreting said decays. Assuming the eclipse phase duration is exponentially-distributed, which is inconsistent with our findings herein, can cause an overestimation of the antiviral efficacy or an underestimation of the duration of the eclipse or virus-producing phases. The over/under-estimation is even more significant if the true duration of virus-production is normally, rather than exponentially distributed. Having found a 10-fold difference in the antiviral efficacy estimated by MMs with an exponential vs normally distributed virus-producing cell lifespan, we expect these parameter over/under-estimation from viral decay data observed under INI therapy would be statistically significant. In turn, these statistically significant differences in parameter value estimates could potentially have an impact on therapeutic decisions. Actual analysis of viral load decays under therapy using these different MMs is needed to confirm this possibility, and to identify which parameter(s) would be most significantly affected. Previous works analysing plasma viral load decays under antiviral therapy in vivo. However, under the assumption of a normally-distributed virus-production phase, and when that phase is less than ~11 h in duration, the MM-predicted viral load decay is very sharp, occurring over a few hours, with a drop proportional to the efficacy of the INI therapy. This pattern cannot be reproduced under the assumption of an exponential duration of virus-production. Observing such a pattern under INI therapy would require more frequent sampling early after therapy initiation, and would provide a strong confirmation that the duration of virus production by HIV-infected cells in vivo follow a normal-like distribution.We furthermore find that under antiviral therapy with an integrase inhibitor (INI), the shape of the MM-predicted decay differs drastically between the assumption of a normally vs exponentially distributed duration of virus production. The true decays observed in HIV patients under INI therapyin vitro occurs some relatively fixed amount of time after the start of virus production and release. This implies that the cause of this cessation is likely a consequence of that production and release process, such as the accumulation of damage  or signalling . Recently, measuring intracellular HIV-1 replication kinetics alongside gene expression, with high temporal resolution, has become possibleA normally distributed duration of virus production indicates that the time of cessation of virus production by SHIV-infected cells in vitro infection of HSC-F cells with SHIV-KS661. However, in the context of an in vivo HIV infection, the host immune response, absent in our in vitro analysis, might alter the distribution and duration of the virus-production phase. For example, killing of virus-producing cells by the host immune response might lead to an exponentially distributed virus-producing phase, but only if HIV-infected cells which have just begun virus production are killed at the same rates as those which have been producing HIV progeny for a while. It would furthermore require that a majority of HIV-producing cells cease virus production because of that host immune response so that cells exhibiting an exponentially distributed infectious lifespan dominates over those exhibiting their ‘natural’, normal-like duration of virus production. Viral load decay rates — believed to be proportional to the duration of the virus production phase — were reported to be the same in the presence and absence of CD8+ T cells in macaques chronically infected with SIV under combination antiretroviral therapy1617+ T cell in vivo would not significantly affect virus-production duration. Additionally, while the rate of host-mediated killing of HIV-infected cells is high in the acute phase of an HIV infection, this rate is likely much lower in the chronic phase of the disease, when antiviral therapy is administered and studied. Using a mathematical modelling analysis, Ganusov et al.in vivo also follows a normal distribution, like that characterized herein for the SHIV-infection of HSC-F cells in vitro.Our results are based on analysis of These experimental procedures were outlined in ref. These experimental procedures were outlined in ref. 9E) and in the subsequent virus-producing infectious phase (I), we follow previous work12In order to compare distributions ranging from exponential, to normal-like, to Dirac delta-like for the duration spent by cells in the eclipse phase  virus at a constant rates pRNA, respectively. Ultimately, virus-producing infectious cells cease virus production, possibly undergoing apoptosis, after spending an average time τI in the virus-producing state. Total virus, VRNA, quantified via real-time quantitative PCR in units of vRNA/mL, was measured experimentally over the course of the infection. Infectious virus, 50/mL was not measured experimentally. The rate of cell infection is dependent on the concentration of infectious virus, not total virus. The ratio of infectious to total virus is not constant over the course of an in vitro SHIV infection due to the differing rates at which infectious virus loses infectivity compared to the rate at which total virus degrades or breaks down, i.e., cRNA for VRNA where Herein, susceptible, target HSC-F cells are infected at rate nE and nI) can only take on integer values. In nE (or nI) separate compartments, each lasting an exponentially-distributed time of equal average length τE/nE (or τI/nI). As such, cells will spend on average τE (or τI) time in the eclipse (or infectious) state prior to transitioning to the infectious (or dead) state.The time spent by newly infected cells in each of the eclipse and virus-producing phases is represented in MM (1) by the Erlang distribution, a special case of the Gamma distribution in which the shape parameter  are taken from separate wells (independent replicates) such that each time point corresponds to an infection left undisturbed since rinsing, up until sampling. Thus, at time t = −1 h, we assume that no cell is initially infected (Ei = Ij = D = 0). We further assume that not all HSC-F cells are susceptible to SHIV infection (T(−1 h) = 0.9 × 106), because ~10% of cells appear to have remained uninfected by the end of the experiment , and at serial 2-fold dilutions down to 2.1, 1.1, 0.53, and 0.26 TCID50/cell in four additional experiments. Mathematically, this is represented by setting the initial infectious virus concentration to 6 TCID50/mL. However, since there is poor correspondence between virus infectiousness across separate experiments50 is a relative rather than an absolute measure of virus infectiousness2150 in our SHIV-KS661 samples, specifically, the ratio of the initial (t = 0) data points in et al.The experimental infections were preformed at five different virus concentrations, namely at an undiluted infectious SHIV-KS661 concentration of 4.2 TCID50/cell), the residual virus post-rinse was not proportional to the inoculum, but rather seemed to reduce to the residual virus down to ~1.4 × 109 vRNA/mL, whereas at the lower virus inocula, the rinse did seem to result in residual virus proportional to the inocula. Therefore, in our MM, we simulate the rinse by multiplying both VRNA(0) at time t = 0 by VRNA), yet has no impact on our simulated infection kinetics which instead depends on infectious virus β will be relatively, rather than absolutely accurate, which is always the caseAfter the 1 h incubation period, the cells are rinsed three times to remove excess virus. Based on the experimental measurements presented in β, pRNA, cRNA, τE, τI, nE, and nI. From our previous work reported in Iwami et al.β, pRNA, τE, τI, nE, nI) and one initial condition (Base MOI) to be estimated by our analysis. In performing the nonlinear least-square fits  and best fit for a normal-like distribution (nI = 20) are presented in In addition to its initial conditions, MM (1) contains a total of 9 parameters: are fits  and 3, wVRNA, compared the fraction of virus-producing cells tagged via anti-SIV Nef monoclonal antibodies and quantified via FACS to the sum of all MM variables corresponding to the fraction of cells in the infectious, virus-producing phase D corresponding to the fraction of dead cells. In our nonlinear least-square regressions to identify the best-fit, 6-parameter set for two different values of nI, we aimed to maximize the goodness-of-fit by minimizing the sum-of-squared residuals (SSR) between the experimental data, weighted for each of VRNA, I, and D as follows:In matching the experimental data to variables of our MMs, we compared the experimentally quantified total virus concentration via real-time quantitative PCR (vRNA/mL) to MM variable σI = 0.047, and σD = 0.080 correspond to the standard deviations of the pooled residuals for each of nI ∈ . Iii and Ddi in the above correspond to fraction rather than number of cells. The SSR calculation directly uses the fraction of cells, and no transformation (e.g. logit function) is applied in calculating the SSR for the fractions of infectious or dead cells. This is because we found that the distribution of the best-fit residuals of the cell fraction data resembles a Gaussian while that for the residuals of the logit-transformed cell fraction data does not (not shown).where nI ∈ , divided by the likelihood of the very best fit (nI = 1) so that the latter’s likelihood is one.The nonlinear regression was performed using successive applications of python’s scipy implementations of the Levenberg-Marquardt (scipy.optimize.leastsq) and Nelder-Mead downhill simplex (scipy.optimize.fmin) methods. Additionally, we used emcee, a python module implementation of the Markov chain Monte Carlo (MCMC) methodεIN), we modified MM (1) as followsTo simulate therapy with an integrase inhibitor  prior to therapy initiation is given byτE = 19 h, τI = 11 h, nE = 1 or 4 , and nI = 1 or 90 , based on where we set How to cite this article: Beauchemin, C. A. A. et al. Duration of SHIV production by infected cells is not exponentially distributed: Implications for estimates of infection parameters and antiviral efficacy. Sci. Rep.7, 42765; doi: 10.1038/srep42765 (2017).Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.


The preferential orbital occupancy of eg(x2–y2) in La0.67Sr0.33MnO3 layers induced by the tensile strain of BaTiO3 layers is identified by X-ray linear dichroism measurements. Our results reveal that controlling orbital ordering can effectively improve the Curie temperature of La0.67Sr0.33MnO3 films and that in-plane orbital occupancy is beneficial to the double exchange ferromagnetic coupling of thin-film samples. These findings create new opportunities for the design and control of magnetism in artificial structures and pave the way to a variety of novel magnetoelectronic applications that operate far above room temperature.Recent theoretical studies indicated that the Curie temperature of perovskite manganite thin films can be increased by more than an order of magnitude by applying appropriate interfacial strain to control orbital ordering. In this work, we demonstrate that the regular intercalation of BaTiO TC) decreases with the reduction of film thickness, which limits their potential for spintronic devices such as field-effect transistors, magnetic tunnel junctions, spin valves, and nonvolatile magnetic memory n superlattice  samples were synthesized on (001) SrTiO3 substrates using PLD. A stoichiometric polycrystalline target was used in a 100-mTorr oxygen environment at a substrate temperature of 725 and 780 °C for LSMO and BTO, respectively. A KrF excimer laser (λ = 248 nm) with a 2 Hz repetition rate was employed. Energy of 350 and 300 mJ was focused on the targets to obtain the LSMO and BTO layers, respectively. After the growth, the samples were annealed in a 300-Torr oxygen atmosphere in situ for 1 h to improve their quality and reduce their inherent oxygen deficit and then cooled to room temperature. As a reference, two LSMO films with 3 and 40 u.c. thickness (denoted as LSMO(3) and LSMO(40), respectively) were also prepared using PLD under the same conditions for comparison with the SL-n superlattices. To grow films epitaxially with atomic precision, we prepared an atomically flat, single-terminated SrTiO3 surface by etching in an NH4F-buffered HF solution (BHF) and subsequently annealing in an oxygen atmosphere at a temperature of 960 °C. The surface topography of a BHF-treated, bare (001) SrTiO3 substrate was characterized by atomic force microscopy (AFM) analysis, as shown in Fig. 001)-oriented , and the in-plane direction was obtained with E//[100], as shown in Fig. 2-edge peak (ΔXLD) represents the difference between the relative occupancies of the eg(x2 − y2/3z2 − r2) orbitals. A positive/negative ΔXLD (on average) is ascribed attributed to a preferential occupancy of the eg(3z2 − r2)/(x2 − y2) orbitals for (001) LSMO films. Figure 2-edge peak is negative, implying a preferential occupancy of the eg(x2–y2) orbital  orbital occupancy in the LSMO layers, achieving high TC. This negative value of the ΔXLD area is also evidence that the Mn3+ ions in the LSMO triple layers have the same orbital occupancy, which contributes to high-temperature ferromagnetism. Also, the absolute value of ΔXLD for the SL-10 sample is significantly larger than that of the SL-3 sample, which corresponds to the increased TC seen in Fig. In our LSMO/BTO samples, the lattice parameter of the BTO . The TMI values of 178 and 310 K for samples SL-3 and SL-10, respectively, correspond to the TC shown in Fig. TC from a paramagnetic insulating phase to a ferromagnetic metallic phase. Thus, the high-temperature ferromagnetism originates from in-plane double exchange interactions between the Mn3+ and Mn4+ ions as shown in Fig. g(x2–y2) with O 2px and O 2py creates stronger ferromagnetic coupling than that between (more empty) Mn eg(3z2–r2).Figure TC and manganese eg orbital occupancy was revealed combined with XLD spectra. We showed that the regular intercalation of BTO layers between LSMO layers effectively enhances ferromagnetic order and increases the TC of LSMO/BTO superlattices. The preferential orbital occupancy of eg(x2–y2) in LSMO layers induced by tensile strain of BTO layers is beneficial to the in-plane double exchange ferromagnetic coupling between Mn3+ and Mn4+ ions, resulting in a large TC. Our findings create new opportunities for the design and control of magnetism in artificial structures and offer considerable potential for applications in novel magnetoelectronic applications, including nonvolatile magnetic memory working far above room temperature.In summary, LSMO/BTO superlattices were prepared using PLD and the relationship between high


In 2013–2016, West Africa experienced the largest and longest Ebola virus disease outbreak ever documented. The wide geographic spread and magnitude of the outbreak often limited the timely and rapid testing of diagnostic samples from patients with suspected Ebola virus disease, raising questions regarding the optimal storage and shipping conditions of clinically relevant specimens, including EDTA-whole blood, plasma, capillary blood, urine and seminal fluid . Therefore, the aim of our study was to identify the extent to which storage temperature and clinical specimen type influence Ebola virus viability. Virus infectivity was determined using a fluorescent focus-forming assay. In our study, we show that Ebola virus was the most stable in EDTA-whole blood and plasma samples, whereas rapid decay of infectivity was observed in simulated capillary blood, urine and semen samples, especially when these samples were stored at higher temperatures. The analysis of variance results demonstrated that both temperature and clinical specimen type have significant effects on virus viability, whereas donor differences were not observed. Repeated freeze and thaw cycles of the samples also had a notable impact on virus viability in EDTA-whole blood and urine. Due to the rapid temperature- and specimen-dependent degradation of the virus observed here, our study highlights the importance of proper clinical sample storage at low temperatures during transportation and laboratory analysis. According to the recommendations of the World Health Organization and the Pan American Health Organization, samples can be refrigerated (2–8 °C) for up to a week. However, shipping of the samples to reference laboratories during the first 48 h after collection is highly recommended and may influence test reliability2. The RNA of Ebola virus (EBOV) is known to be relatively stable in whole blood and serum/plasma samples for weeks under African environmental conditions, depending on the initial viral load5. However, alternative sample types, including oral swabs and capillary blood samples, are also evaluated for nucleic acid-based diagnosis, as are urine and semen samples from which EBOV can be detected by PCR for several weeks or even months after symptoms onset8. The environmental stability of the virus has also been studied, and the potential persistence of its viral RNA under hospital circumstances has been determined10. EBOV RNA in Ebola treatment centers was found to be associated with surfaces that come into close contact with patients and infectious body fluids, such as caregiver gloves, beds and blankets10. Studies confirmed that EBOV maintains infectivity in liquid blood samples for a longer period of time than in dried blood but that relative humidity and temperature can also impact virus viability11. While adequate storage conditions of clinical specimens for nucleic acid-based diagnosis are well studied, knowledge regarding the stability of infectious EBOV in different clinical specimens stored under various conditions is limited. Such information is critical in order to obtain reliable data about the potential infectiousness of secretions from patients with Ebola virus disease (EVD). Several longitudinal studies have also addressed the persistence of EBOV in different body fluids, such as the seminal fluids of male survivors. This information is critical to assess the risk of transmission of EBOV from survivors within the community15. However, poor transport and storage conditions of clinical diagnostic samples can reduce virus viability and complicate infectivity studies. Identifying the effect of inappropriate storage conditions is critical for confirming the reliability of longitudinal persistence studies by virus isolation. Therefore, our aim was to determine the viability of the EBOV strain Makona during short-term storage in different clinical sample specimens, such as EDTA-whole blood, plasma, simulated capillary blood, urine and semen, under a range of simulated African environmental conditions.Ebola outbreaks, especially those that occurred in 2013–2016 in West Africa, pose significant challenges for outbreak response teams with respect to ensuring adequate conditions for the collection, transport, storage and processing of different biological specimens for laboratory testing5 fluorescent focus unit (FFU)/mL; then, the samples were stored at 37, 23 and 4 °C and at −80 °C as a control. Infective virus titer was determined at indicated time points  in all specimens using a fluorescent focus-forming assay. Virus viability was most stable in EDTA-whole blood . In the case of EDTA-whole blood, an overall 1.11 log10 decrease in virus infectivity was observed after 3 cycles of freezing and thawing (data not shown).P = 0.71).Comparison of the initial and post-storage RNA quantity by real-time reverse transcription-polymerase chain reaction (RT-PCR) did not show significant virus RNA reduction under any of the tested conditions  during the 5-day storage period (P < 0.001) with accelerated decay at 37 °C. According to our results, virus infectivity also decays with different kinetics at different temperatures in different specimens. Different types of the specimens showed a significant influence on virus viability at 37 °C (P < 0.001) and 23 °C (P = 0.005) but no significant effect at 4 °C (P = 0.269), confirming that EBOV is relatively stable and that this stability was independent of the matrix at low temperature. Samples from different donors showed no significant effect (P = 0.968) during the 5-day storage period. The results of semen samples were not included in the statistical analysis because of the low number of replicates due to cytotoxic effects on cell culture.Statistical analysis of the obtained data showed that temperature had a significant effect on virus viability  were assessed.The aim of our study was to assess factors that may affect virus isolation efficiency due to inappropriate shipping or storage conditions, which may impact longitudinal studies examining the infectiousness of different body fluids and clinical samples from EVD survivors. Moreover, virus isolation is important to study virus persistence and intra-host phenotypic changes and for various immunological studies. After sampling, samples in the field are often transported and/or stored at approximately 4 °C until further processing or short term at room temperature in Africa; room temperatures can vary between 20 and 40 °C depending on the time of day and season18. Our results showed that the virus maintains long-term infectivity in whole blood and plasma; infectivity decay in these samples was less than 1.5 log10 after 120 h, even at higher temperatures. Similar results have been described by Fischer et al.11. This prolonged infectivity could be due to the protective role of proteins in whole blood or plasma samples19. In one long-term stability study, EBOV suspended in guinea pig sera could be isolated for up to 46 days20. However, Prescott et al.21 investigated the postmortem stability of EBOV and found that the virus can be isolated from blood obtained from the body cavity of killed cynomolgus macaques for up to only 9 days. Venous blood sampling requires trained and qualified medical personnel and is difficult to perform on newborns and infants or people with religious convictions prohibiting such medical interventions. Capillary blood sampling is less invasive, has only minimal risk of needle stick injuries and can be useful for the diagnosis of patients with suspected EVD7. Therefore, as an alternative to whole blood, we aimed to determine the suitability of simulated capillary blood samples absorbed onto swab devices for virus isolation. The virus completely lost infectivity at 37 °C by 96–120 h and showed a 2.84 log10 reduction of infectivity at 23 °C by 120 h. This rapid loss of infectivity may be due to the rapid drying process, which is enhanced by the material of the swab applicator device. According to different environmental studies, studies on the viability of EBOV after drying blood on different surfaces led to disparate results. The average loss of infectivity ranged from 1 to 7 log10 reduction within 24–96 h at 21 °C depending on the surface and on the relative humidity, which appears to have an impact on virus viability, especially at higher temperatures22.Whole blood and plasma are recommended for the detection of EBOV; hence, most diagnostic tests are validated for these two types of specimens23. However, urine samples are one of the body fluids that is most affected by storage, particularly when they are stored at 37 °C. Our study is the first to demonstrate the critical time window of 48–96 h for virus isolation from urine samples at higher temperatures. Notably, according to our data, infective virus titer can also decrease substantially within the first 12–24 h after sampling, depending on storage temperature. The low amount of protein and the presence of bacteria, proteases and RNases may contribute to the increased decay of virus infectivity3. Moreover, the presence of chemical components, such as ammonia, urea and a low pH, may have an additional impact, resulting in rapid virus degradation25.Among clinical specimens, urine samples can be useful for monitoring disease progress and are easy to collect14 infectious EBOV can be detected in the seminal fluids of male survivors for up to 233 days, emphasizing the potential for sexual transmission. However, the effect of short-term storage at different temperatures on EBOV viability in semen has not been previously evaluated. Similar to urine and capillary blood, complete infectivity loss was observed in semen at 120 h when stored at 37 °C. Again, this result may be due to the presence of bacteria and proteolytic enzymes, which could have an effect on the decay rate. A slower reduction in infectivity was found at 23 °C with 2 log10 reduction, strengthening the findings published by Fischer et al26.According to Sissoko et al.,20. Because the virus remains infective at room temperature or lower temperatures for longer than 120 h in some clinical specimen types, additional experiments are needed to determine the prolonged time period until the complete loss of virus infectivity. Moreover, EBOV strains/isolates could differ in their decay rates under different environmental conditions; therefore, more studies are needed to reveal these variations and determine the underlying biological mechanisms. Additionally, dried blood spot analysis could be a useful alternative for safely collecting, shipping and storing EVD blood samples, especially during outbreak emergencies during which sample logistics can be a major challenge. Finally, the fluorescent focus assay has not been validated for EBOV in clinical specimens; thus far, this method has been used in only simulated clinical specimens to determine virus infectivity. To implement this method for clinical diagnostic purposes, further validation of the assay is necessary. Statistical analysis of our data clearly demonstrated that temperature significantly affected virus infectivity, and thus inappropriate storage conditions, such as storage at 37 °C, reduced the efficacy of virus isolation. Further, specimen type had a significant effect on virus viability at 37 and 23 °C, which is important to consider when transporting clinical samples. The clustering method used for visual analysis confirmed that degradation of the Ebola virus was accelerated at 37 °C and that virus infectivity decay followed substantially different kinetics in distinct specimen types. Fischer et al.11 demonstrated that EBOV strain Makona viability decay in blood was independent of the environment, which is in agreement with our findings. However, we observed significant infectivity loss in capillary blood samples. Only minimal virus degradation was observed at 4 °C, confirming that EBOV is relatively stable and independent of the matrix at low temperatures. According to analysis of variance (ANOVA) and cluster analysis, individual donor differences showed no significant effect on virus viability during short-term storage.Our results showed that virus recovery from cell culture media was also substantially higher when the samples were stored at 4 °C than at higher temperatures, which is in agreement with the previous work of Piercy et al.27.Previously, no information was available concerning the effects of repeated freeze–thaw cycles on the degradation of EBOV in different clinically relevant sample specimens. Our results show that the most affected body fluid was EDTA-whole blood with a 1.11 log10 reduction in virus infectivity. Repeated freezing and thawing may have caused structural damage to the virion, thereby reducing virus viability28. Nonetheless, some EVD patients remained real-time RT-PCR positive in different body fluids, such as urine, sweat, feces and semen, with high Ct values that indicated potentially low infective viral loads29. Although these sample types are critical to estimating the risk of infectivity and virus transmission by providing valuable information about the shedding of contagious EBOV into body fluids during the acute and convalescent phase of EVD patients, they are also subjected to the greatest degradation of EBOV during inappropriate storage conditions. In conclusion, our study highlights the need for proper sample storage  during transportation and to avoid repeated thawing and refreezing during short- and long-term storage of samples in which virus isolation will be performed.During the 2013–2016 West African Ebola outbreak, the criterion to discharge convalescent patients from Ebola treatment centers was two consecutive EBOV PCR negative blood samplesHomo sapiens-tc/GIN/2014/Makona-WPGC05 strain . Cells were grown in RPMI-1640  cell culture media supplemented with 5% fetal bovine serum , penicillin and streptomycin (Sigma-Aldrich) and were maintained as adherent cell lines at 37 °C and 5% CO2. The infected cell culture supernatant was collected 5 days post infection, centrifuged at 3500 rpm for 20 min at 4 °C and aliquoted for storage at −80 °C until further use. All work with infectious Ebola virus was performed at the National Public Health Institute, National Biosafety Laboratory in Hungary under biosafety level 4 (BSL-4) conditions.Vero E6 cells were used for in vitro propagation and titration of the Ebola virus/Ebola virus viability was determined in five different types of diagnostically relevant specimens, including EDTA-whole blood, plasma, simulated capillary blood, urine and semen, obtained from healthy volunteers. RPMI-1640 cell culture media supplemented with penicillin and streptomycin were also tested. EDTA-whole blood was collected by venipuncture from four volunteers using BD Vacutainer K2E , and the plasma was obtained by centrifugation of EDTA-whole blood at 3500 rpm for 10 min. To simulate capillary blood samples, 50 µL of EDTA-whole blood from two individuals was transferred to and absorbed on swab collection applicators . The applicators were placed back into their cases for storage and swirled into 500 µL phosphate-buffered saline prior to testing. Urine samples obtained from four volunteers and semen samples from three male donors were centrifuged at 3500 rpm for 10 min before use in the experiment. All samples were tested for cytotoxicity, bacterial and fungal contamination and diluted 1:10 in RPMI-1640 cell culture media.5 FFU/mL after accounting for inhibitory effect of the sample on the FFU assay. The samples were then aliquoted and stored at different temperatures  for 0, 12, 24, 48, 72, 96 or 120 h. At the indicated time points, aliquots of each sample were collected and stored at −80 °C until titration at the end of the experiment. The influence of repeated freeze–thaw cycles on virus infectivity was also tested. Aliquots of EDTA-whole blood, plasma, urine and RPMI-1640 samples were frozen to −80 °C for 1 h, then thawed and stored at 23 °C for another hour. The freeze–thaw cycle was then repeated two additional times. The titer of the virus was determined after each freeze–thaw cycle.Two replicate samples of each type were spiked with EBOV to achieve a final titer of 1030.Viral RNA was extracted using the Roche High Pure Viral RNA Kit  following the manufacturer’s instructions but with an additional wash step (with Wash Buffer) to reduce potential PCR inhibitors. Real-time RT-PCR was conducted using Roche LightCycler 480 RNA Master Hydrolysis Probes (Roche) reagents with primers and probes targeting the GP gene of the Ebola virus on the LightCycler 2.0 (Roche) platform31 with minor modifications. Quantification of the virus titer was performed using a fluorescence microscope and is expressed in FFU/mL. In the case of end-point samples, the absolute infectivity loss was also confirmed by virus isolation using three blind passages on cell culture.After the indicated storage period, each sample was titrated in triplicate in 96-well plates according to the protocol described by Canakoglu et al.Informed consent to publish was obtained from all volunteers included in this study.P < 0.05. Decay rates derived from the slopes of the fitted linear curves were estimated using the ordinary least squares method.Statistical analysis was performed with the Statistica Software package  using ANOVA to identify factors  that may impact virus viability during shipping or storage. The results were deemed to be significant with A clustering algorithm was applied for visual comparison of the observed factors of temperature, type of specimen and donor using Tableau Software  with relative distances calculated using the Euclidean distance method.