Tobacco etch virus carrying an eGFP fluorescent marker in two semi-permissive host species, Nicotiana benthamiana and Datura stramonium, for which it has a large difference in virulence. We compared the results to those previously obtained in the natural host, Nicotiana tabacum, where we have shown that carriage of eGFP has a high fitness cost and its loss serves as a real-time indicator of adaptation.Theory suggests that high virulence could hinder between-host transmission of microparasites, and that virulence therefore will evolve to lower levels. Alternatively, highly virulent microparasites could also curtail host development, thereby limiting both the host resources available to them and their own within-host effective population size. In this case, high virulence might restrain the mutation supply rate and increase the strength with which genetic drift acts on microparasite populations. Thereby, this alternative explanation limits the microparasites’ potential to adapt to the host and ultimately the ability to evolve lower virulence. As a first exploration of this hypothesis, we evolved D. stramonium. This result was consistent with the observation that there was a fitness cost of eGFP in this host, while surprisingly no fitness cost was observed in the host for which the virus has high virulence, N. benthamiana. Furthermore, in both hosts we observed increases in viral fitness in few lineages, and host-specific convergent evolution at the genomic level was only found in N. benthamiana.After over half a year of evolution, we sequenced the genomes of the evolved lineages and measured their fitness. During the evolution experiment, marker loss leading to viable virus variants was only observed in one lineage of the host for which the virus has low virulence, The results of this study do not lend support to the hypothesis that high virulence impedes microparasites’ evolution. Rather, they exemplify that jumps between host species can be game changers for evolutionary dynamics. When considering the evolution of genome architecture, host species jumps might play a very important role, by allowing evolutionary intermediates to be competitive.The online version of this article (doi:10.1186/s12862-017-0881-7) contains supplementary material, which is available to authorized users. From both applied and fundamental perspectives, virulence is a key phenotypic trait of microparasites. In medicine and agriculture, it is crucial to understand mechanistically how microparasites harm the host, in order to devise effective interventions. From a more fundamental perspective, evolutionary biologists have long been interested in understanding why many microparasites are highly virulent. It has been suggested that virulence reduces between-host transmission, and that selection would therefore act to maximize between-host transmission by reducing virulence , 2. HighThe tradeoff hypothesis forms the cornerstone for theoretical frameworks considering the evolution of virulence in many different pathosystems. Many important additions to the framework have been made, for example recognizing that within-host competition and opportunism can lead to increases in virulence –10. Morei) a low effective population size, (ii) a non-static optimum virulence, (iii) large variations in virulence on the fitness landscape, and (iv) reduced host-development, could limit the rate at which lower virulence evolves, meaning that high virulence might persist longer than suggested by the simple tradeoff model [Conversely, virulence itself could also have profound effects on evolution, including its own evolutionary dynamics . This reff model .There are many reasons why high virulence in host-pathogen interactions could emerge, but the most likely avenue is probably a change of host species. For example, infection of Ebola virus in bats is asymptomatic, while in humans and other primates the death rate is high . ChangesTobacco etch virus , a (+)ssRNA virus with a 9.5 kb genome that infects a wide-range of host plants, and an experimental evolution approach. To consider the effect of virulence  on virus adaptation, we looked for two natural host species in which (i) there was some evidence that TEV potential for adaptation would be roughly similar, and (ii) there was a large difference in virulence. The distribution of mutational fitness effects (DMFE) of TEV has been compared in eight host species, and this study concluded that there were strong virus genotype-by-host species interactions [Nicotiana tabacum, the DMFE changed drastically; many mutations that were neutral or deleterious in N. tabacum, became beneficial. However, for two related host species, Nicotiana benthamiana and Datura stramonium, most mutations tested remained neutral or deleterious [N. benthamiana will typically result in heavy stunting and the death of the plant within a matter of weeks, whereas TEV infection of D. stramonium is virtually asymptomatic. These symptoms are very different from symptoms observed for TEV in its natural host N. tabacum, which does not lead to plant death but consist of vein clearing, mosaic mottling, chlorosis, and stunting [Here we address this question using ractions . For maneterious , implyineterious . On the stunting , 20. WhiN. benthamiana and D. stramonium. By serially passaging each independent lineage in a single plant every round, our study maximizes within-host selection. This setup allows us to exclusively focus on the effects of within-host selection, although for our model system we expect to see large differences in the resulting population size and the extent of virus movement within the host. Moreover, to immediately gauge whether adaptive evolution might be occurring, we passaged a TEV variant expressing a marker protein , the ancestral virus and evolved lineages were sequenced by Illumina technology. According to the above hypothesis that high virulence may impair the rate of microparasite evolution, we expect that adaptive evolution would occur more quickly in the host species for which TEV has lower virulence, D. stramonium, than in the host species for which it has high virulence, N. benthamiana. Hence, we expected that in D. stramonium (i) the eGFP marker would be lost more rapidly, (ii) there would be more sequence-level convergent evolution, and (iii) there would be larger increases in within-host competitive fitness. However, our experiments did not confirm these simple hypotheses. First of all, the loss of eGFP could not be used as an indicator of adaptation in neither D. stramonium nor N. benthamiana. Second, host-specific convergent evolution at the genomic level was only found in N. benthamiana. Third, in both hosts we observe only one evolved lineage with increases in within-host competitive fitness, and surprisingly the eGFP marker does not seem to have a fitness cost in N. benthamiana. These results were unexpected based on our previous work in N. tabacum [As a first exploration of the effects of virulence on microparasite evolution, we therefore decided to evolve TEV in ein Fig. , the enhrescence . Therefo tabacum , but theN. tabacum plants [BglII prior to in vitro RNA synthesis using the mMESSAGE mMACHINE® SP6 Transciption Kit (Ambion), as described in [N. tabacum L var Xanthi NN plants was mechanically inoculated with 5 μg of transcribed RNA. All symptomatic tissue was collected 7 days post-inoculation (dpi).The TEV genome used to generate TEV-eGFP virus was originally isolated from m plants . To genem plants  was lineribed in . The thi2PO4, pH 7.0, 3% polyethylene glycol 6000). From this mixture, 20 μl were then mechanically inoculated on the sixth true leaf of 4-week old N. benthamiana Domin plants and on the third true leaf of 4-week old D. stramonium L plants. Ten independent replicates were used for each host plant. Based on a previous study done in N. tabacum [D. stramonium were done every 9 weeks. In N. benthamiana the virus induces host mortality, and therefore the passages had to be restricted to 6 weeks for this host. At the end of the designated passage duration all leaves above the inoculated one were collected and stored at −80 °C. For subsequent passages the frozen tissue was homogenized and a sample was ground and resuspended with an equal amount of phosphate buffer [D. stramonium (27 weeks of evolution) and five 6-week passages for lineages evolving in N. benthamiana (30 weeks of evolution), making the total time of evolution similar in both hosts. For both D. stramonium and N. benthamiana, all individual plants used were grown from large stocks of seeds collected from self-pollinated individual plants, therefore all plants for each host were of identical genotype. All plants were kept in a biosafety level 2 greenhouse at 24 ° C with 16 h light:8 h dark photoperiod.For the serial passage experiments, 500 mg homogenized stock tissue was ground into fine powder and diluted in 500 μl phosphate buffer . Reverse transcription (RT) was performed using MMuLV reverse transcriptase (Thermo Scientific) and reverse primer 5’-CGCACTACATAGGAGAATTAG-3’ located in the 3’UTR of the TEV-eGFP genome . PCR was then performed with Taq DNA polymerase (Roche) and primers flanking the eGFP gene: forward 5’-GCAATCAAGCATTCTACTTC-3’ (positions 48–67), and reverse 5’-CCTGATATGTTTCCTGATAAC-3’ (positions 2530–2550). PCR products were resolved by electrophoresis on 1% agarose gels.To determine whether deletions occurred at the www.genoscreen.com). Illumina HiSeq2500 2 × 100 bp paired-end libraries with dual-index adaptors were prepared along with an internal PhiX control. Libraries were prepared using the Nextera XT DNA Library Preparation Kit (Illumina Inc.). Sequencing quality control was performed by GenoScreen, based on PhiX error rate and Q30 values.For Illumina next-generation sequencing (NGS) of the evolved and ancestral lineages, the viral genomes were amplified by RT-PCR using AccuScript Hi-Fi (Agilent Technologies) reverse transcriptase and Phusion DNA polymerase (Thermo Scientific), with six independent replicates that were pooled. Each virus was amplified using three primer sets, generating three amplicons of similar size (set 1: 5’-GCAATCAAGCATTCTACTTCTATTGCAGC-3’ and 5’-CCTGATATGTTTCCTGATAAC-3’ (positions 48–76 and 2530–2550); set 2: 5’-ACACGTACTGGCTGTCAGCG-3’ and 5’-CATCAATGTCAATGGTTACAC-3’ (positions 2217–2236 and 5324–5344); set 3: 5’-CCCGTGAAACTCAAGATAG-3’ and 5’-CGCACTACATAGGAGAATTAG-3’ (positions 5044–5062 and 10235–10255). Equimolar mixtures of the three PCR products were made. Sequencing was performed at GenoScreen  was done using FASTX-Toolkit v.0.0.14 . De-replCP) were used: forward 5’-TTGGTCTTGATGGCAACGTG-3’ (positions 9968–9987) and reverse 5’-TGTGCCGTTCAGTGTCTTCCT-3’ (positions 9998–10018). The StepOne Software v.2.2.2 (Applied Biosystems) was used to analyze the data. The concentration of genome equivalents per 100 mg of tissue was then normalized to that of the sample with the lowest concentration, using phosphate buffer.Prior to performing assays, the genome equivalents per 100 mg of tissue of the ancestral virus stocks and all evolved lineages were determined for subsequent fitness assays. The InviTrap Spin Plant RNA Mini Kit (Stratec Molecular) was used to isolate total RNA of 100 mg homogenized infected tissue. Real-time quantitative RT-PCR (RT-qPCR) was performed using the One Step SYBR PrimeScript RT-PCR Kit II (Takara), in accordance with manufacturer instructions, in a StepOnePlus Real-Time PCR System (Applied Biosystems). Specific primers for the coat protein gene  using specific primers: forward 5’-CGGCGAGTTCATCTACAAGG-3’ (positions 360 to 379) and reverse 5’-TGGTCTTCTTCTGCATTACGG-3’ (positions 416–436). The ratio of the evolved and ancestral lineages to TEV-mCherry (R) is then R=(nCP-nmCherry)/(nmCherry), where nCP and nmCherry are the RT-qPCR measured copy numbers of CP and mCherry, respectively. Then we can estimate the within-host competitive fitness as R0 is the ratio at the start of the experiment and Rt the ratio after t days of competition [To measure within-host competitive fitness, we used TEV carrying a red fluorescent protein: TEV-mCherry as a common competitor. This virus has a similar insert size and within-host fitness compared with TEV-eGFP . All ancpetition . The stapetition  and IBM N. benthamiana and D. stramonium, as described in Zwart et al. 2014 [eGFP as well as rapid convergent evolution in N. tabacum [eGFP as a real time measure of adaptation. Although 9-week passages could be performed in D. stramonium, for N. benthamiana this was not possible due to virus-induced host mortality. These plants died after 6 weeks of infection, and therefore we were forced to collect tissue at this time point. As D. stramonium grows to similar heights as N. tabacum when infected with TEV, and N. benthamiana does not grow much after infection, we chose to maximize infection duration to make the results comparable to those obtained in N. tabacum [D. stramonium and – to keep the total evolutionary time comparable – five 6-week passages in N. benthamiana. In D. stramonium all ten lineages initiated were completed, whereas in N. benthamiana only 6/10 lineages were completed. The remaining four N. benthamiana lineages failed to cause infection in subsequent rounds of passaging, and were therefore halted. Initial symptomatology of TEV-eGFP in N. benthamiana was very mild, while this symptomatology was more severe in the second and subsequent passages, possibly indicating adaptation of the virus to this alternative host. In D. stramonium the symptomatology was constant along the evolution experiment.TEV-eGFP was mechanically passaged in al. 2014 . In this tabacum . We ther tabacum . We perfN. tabacum, we expected that the exogenous eGFP gene sequence would be rapidly purged [eGFP marker was limited in both hosts, by (i) the high levels of autofluorescence in the highly symptomatic N. benthamiana leaves, and (ii) the patchy fluorescence in the D. stramonium tissue. Therefore, unlike for TEV-eGFP in N. tabacum, the fluorescent marker was of limited use here. Nevertheless, all N. benthamiana lineages appeared to have some fluorescence until the end of the evolution experiment, and we observed a loss of fluorescence in only 1/10 D. stramonium lineages in the third 9-week passage.Based only on previous results in y purged , 31, 32,eGFP insert was performed. This RT-PCR assay can therefore detect deletions in the eGFP gene, even when deletions extend well into the downstream HC-Pro gene [D. stramonium lineage with a loss of fluorescence , compared to a higher average coverage outside this region . The large deletion included the N-terminal region of HC-Pro, as observed for other deletions that occur after gene insertions before this gene [D. stramonium and N. benthamiana, coverage over the genome was largely uniform and similar to the ancestral virus population, indicating that there were indeed no genomic deletions present at appreciable frequencies.All evolved and the ancestral TEV-eGFP lineages were fully sequenced by Illumina technology (SRA accession: SRP075180). The consensus sequence of the ancestral TEV-eGFP population was used as a reference for mapping the evolved lineages. The deletion observed by RT-PCR Fig.  in one ohis gene , 36. ForN. benthamiana and D. stramonium to the ancestral population  mutations per lineage. In the evolved D. stramonium lineages 239 unique mutations were found, with a median of 31.5 (range: 16–35) mutations per lineage. In the evolved N. tabacum lineages, 183 unique mutations were found, with a median of 21.5 (range: 17–36) mutations per lineage. Note that fixed single nucleotide mutations (frequency > 50%) are also detected in the evolved lineages  than either N. benthamiana or D. stramonium share with N. tabacum . However, most of these mutations are present in only a few lineages and at low frequency  that is shared between all three hosts. However, this mutation was present at a low frequency and not detected in all ges Fig. . The N. utations 5 than eiD. stramonium and N. tabacum, are present in the highest number of lineages and reach higher frequencies among all shared mutations detected in the three hosts. These mutations were already present in the ancestral population, nevertheless, the frequencies at which these mutations are present display interesting patterns. In both D. stramonium and N. tabacum the mutations A7479C and A8253C are always detected at the same frequency within each lineage, suggesting a strong linkage between them . In both host species, we found no statistically significant differences (t-test with Holm-Bonferroni correction) between TEV, TEV-eGFP and the lineages of TEV-eGFP evolved in that host , there was no difference in N. benthamiana . Our results therefore suggest that although there is a fitness cost associated with the eGFP gene in N. tabacum [D. stramonium, there is none in N. benthamiana. Interestingly, N. tabacum and N. benthamiana are more closely related to each other than either species is to D. stramonium, and yet the host species has a strong effect on the costs of a heterologous gene. This observation clearly clashes with our expectation that eGFP would have a fitness cost.We then measured within-host competitive fitness by means of head-to-head competition experiments with TEV-mCherry, a virus with a different marker but similar fitness to TEV-eGFP . When se tabacum  and D. sD. stramonium, we observed a significant increase in competitive fitness compared to the ancestral TEV-eGFP . This lineage is the only one to have a deletion in the eGFP insert. In N. benthamiana, 1/6 lineages had a significant increase in within-host fitness . However, this increase in fitness probably is not associated with the large genomic deletion for three reasons: (i) the wild-type TEV without the eGFP gene has a similar fitness compared to the ancestral TEV-eGFP, suggesting deletions in eGFP would not be beneficial, (ii) the RT-PCR results show that this variant occurs at a low frequency in the population, and therefore is unlikely to affect strongly the results of the competition assay, and (iii) this deletion variant remains at low frequency during the next round of passaging , however, after the Holm-Bonferroni correction not significantly. Interestingly, the lineage that did increase its fitness significantly (L4) is the only lineage that contains mutations in the 6 K2 protein in this host  could also be subjected to such an interaction. These results suggest that when considering the evolution of genome architecture, host species might play a very important role, by allowing evolutionary intermediates to be competitive. For example, for TEV we have shown that the evolution of an alternative gene order through duplication of the NIb replicase gene is highly unlikely, as this intermediate step leads to significant decreases in fitness, making the trajectory to alternative gene orders inaccessible [eGFP insert has, then an alternative host species could act as a stepping-stone and hereby increase the accessibility of the evolutionary trajectories to alternative genome architectures. Similar effects of environmental change have been noted in other studies [These results are at odds with our expectations, but they nevertheless have some interesting implications. First, host species changes can apparently ameliorate the costs of exogenous genes. Although strong virus genotype-by-host species interactions have been previously shown for TEV , we did cessible . We havecessible . If gene studies . The gen studies .Upon passaging in each alternative host species, only a single lineage evolved higher fitness. The low rate of adaptation observed was consistent with a previous report , althougeGFP – which is unstable in its typical host, has shown to be more stable in two alternative host species for which TEV has both lower and higher virulence than in the typical host. In addition, eGFP does not appear to have any fitness effects in the host for which TEV has high virulence. These observations clashed with the hypothesis that high virulence slows down the rate of adaptation. Moreover, when considering the evolution of genome architecture, host species jumps might play a very important role, by allowing evolutionary intermediates to be competitive.A host species jump can be a game changer for evolutionary dynamics. An exogenous sequence –


In 2010, Alzheimer's Disease International presented estimates of the global cost of illness (COI) of dementia. Since then, new studies have been conducted, and the number of people with dementia has increased. Here, we present an update of the global cost estimates.This is a societal, prevalence-based global COI study.The worldwide costs of dementia were estimated at United States (US) $818 billion in 2015, an increase of 35% since 2010; 86% of the costs occur in high-income countries. Costs of informal care and the direct costs of social care still contribute similar proportions of total costs, whereas the costs in the medical sector are much lower. The threshold of US $1 trillion will be crossed by 2018.Worldwide costs of dementia are enormous and still inequitably distributed. The increase in costs arises from increases in numbers of people with dementia and in increases in per person costs. •The worldwide costs of dementia were estimated at United States (US) $818 billion in 2015.•This estimated worldwide costs represent an increase of 35% since 2010.•Eighty-six percent of the costs occur in high-income countries.•Costs of informal care and the direct costs of social care still contribute similar proportions of total costs, whereas the costs in the medical sector are much lower.•The threshold of US $1 trillion will be crossed by 2018. Regarding the numbers affected by dementia, this is based on a fully systematic updated review of prevalence studies As in 2010, for countries with no cost data, cost estimations are derived by imputation P < .001).For the 2010 cost estimates, there was only one published COI study from Latin America 2.2For the current estimates, all costs are expressed as 2015 US dollars. The International Monetary Fund/World Economic Outlook (IMF/WEO) database of consumer price indices (CPIs) was used to generate cost adjustments, between 2010 and 2015, for each country Two other issues are also important when interpreting comparisons between 2010 and 2015 costs. First, there have been shifts in the WB classification of country income level between 2010 and 2015 . To facilitate “like-for-like” comparisons between 2015 and 2010, the 2015 costs by country income level are presented according to a) the current 2015 WB classification and b) the 2010 WB classification. Second, the revised estimates of regional dementia prevalence arguably provide a better estimate of numbers of people with dementia in 2010 and 2015. For the World Alzheimer Report 2009 Using the trends (2010–2015) in per capita cost and numbers of people with dementia, each based on WAR 2015 prevalence, it is technically possible to make tentative forecasts of rates of future growth in costs. We present the estimated costs in 2030 and an estimate of the date when global cost will cross the threshold of US $1 trillion. To make a forecast of future trends in the global cost of dementia, we need to estimate trends in the numbers of people with dementia and trends in the per person costs. Trends per annum between 2010 and 2015 need to be estimated on a like-for-like basis. This means a) applying the WAR 2015 prevalence estimates to the 2010 and 2015 population structures to estimate numbers of people with dementia at both time points and b) using the same approach to weight the mean per capita costs.2.3Three sensitivity analyses have been included. In the 2010 report, the most significant effect in the sensitivity analysis was the method of quantifying informal care The CPI is used for cost adjustments between 2010 and 2015 in the base option. In a second sensitivity analysis, the change in GDP in the different countries is used instead for the cost adjustments.In a third “fixed-cost” sensitivity analysis, a crude prevalence-based alternative is presented, without any new COI data included and without cost adjustments. This sensitivity analysis focuses solely on the impact on costs of the changes in numbers of people affected.33.1In the base option, the global costs of dementia have increased from US $604 bn in 2010 to US $818 bn in 2015 , an incrThe proportion of costs incurred in HIC is similar to that reported in the WAR 2010. Because many countries that were classified as low-income countries (LIC) or LMIC in 2010 have been “upgraded,” the proportion of worldwide costs incurred in upper middle-income countries (UMIC) has increased from 5.4% to 10.5%, and the proportion incurred in LIC and LMIC has decreased commensurately compared with 2010.The effect of the WB reclassification of country income status is clearer if we compare 2010 and 2015 cost distributions, on a like-for-like basis, using the 2010 WB classification for both time points . On thisTo complete the adjustments for a like-for-like comparison, we adjusted the 2010 COI estimates to take account of the revised prevalence estimates, which were used to estimate the 2015 costs see . DespiteThe G7 countries have initiated and lead the “Global Action against Dementia.” In The pattern of distribution of costs between the three major subcategories  has not changed substantially . The pro3.2Direct comparison of costs per person by WB country income level is complicated both by the year of the WB classification (2010 vs. 2015) and the basis for prevalence estimates (WAR 2009 vs WAR 2015). The optimal like-for-like comparison uses the WB classification of 2010 and the WAR 2015 prevalence estimates for both the 2010 and 2015 .3.3Depending on how informal care is quantified, there is a great variability in worldwide costs, from US $651 bn (only basic ADLs) to US $1057 bn , but with little variation in distribution by country income level .If the change in per capita GDP is used to update costs from 2010 to 2015 , the totIf a prevalence-based option is used (holding the costs per person fixed and ignoring new COI data), worldwide costs increase by US $91.2 bn (15.1%) , suggest3.4If we use the adjusted prevalence numbers for 2010, there would have been 40.1 million with dementia in 2010, and the numbers would have increased by 16.6% or by 3.3% per year. Between 2010 and 2015, the average worldwide cost per person  increased from US $15,122 to 17,483 per year (an increase of 15.6% or 3.1 % per year).The overall annual trends can then be calculated as the product from increasing numbers (1.033) and increasing per capita costs (1.031) = 1.033 × 1.031 = 1.065 or around 6.5% per annum. By applying this figure, the costs in 2030 will be around US $2 trillion, and the threshold of US $1 trillion will be crossed in 2018 .4Forbes, 2015 ranking).The global societal economic cost of dementia, US $818 bn, is an enormous sum, similar in magnitude to the GDP of countries like Indonesia, The Netherlands, and Turkey, the 16th to 18th largest economies in the world. The global costs are also larger than the market values of companies such as Apple (US $742 bn), Google (US $368 bn), and Exxon (US $357 bn)  but lower than those in HIC (1.4%). The uneven distribution of global costs is even more striking when stratified according to G7 (62 % of worldwide costs) or G20 membership .Our sensitivity analysis confirms that the assumptions regarding costing of informal care have a great impact on the total costs. Although difficult to quantify, supervision is an important and significant part of daily informal care with significant opportunity cost for carers. If that component is included, the costs increase considerably. Transparency regarding assumptions is crucial to make comparisons meaningful in any COI analysis.Our current estimates of global societal costs of dementia have increased by around 35% compared with those published in the World Alzheimer Report 2010. Interpreting these increases is complex given the multiplicity of plausible underlying explanations whether it is because of increasing burden of dementia or because the methods for estimating the dementia burden has changed.Increases in aggregated costs can arise from increases in numbers of people with dementia and/or increases in per person costs. The exploratory analyses that we have conducted suggest that these two elements each contribute around one half of the total increase. We have adjusted costs between 2010 and 2015 according to CPIs in each country. As developing economies grow, the cost of salaries and services tend to inflate more rapidly than prices (a “positive income elasticity effect”); so, this approach may have underestimated cost inflation in LAMIC relative to HIC, as indicated by our GDP-based inflation sensitivity analysis. In either scenario, cost inflation can have accounted for only part of the increase in per capita costs.a)we have estimated them better, with more up-to-date studies,b)some services have become more costly, andc)new services have been established, the coverage of existing services has improved, or existing service users are using the same services more intensively.Per capita costs may also increase because of the following:We do not have adequate data to discern between these three sets of explanations. Some studies suggest that the proportion of people with dementia living in residential care has begun to decline in HIC, consistent with policy initiatives to provide care at home where possible Economic development is proceeding apace in many LIC and, particularly, middle-income countries. This has posed a challenge for us in making meaningful comparisons between country income level groups for 2010 and 2015 because a significant number of countries, some of them very populous, have moved “upward” in the WB classification such as China, Bangladesh, Thailand, Iran, Russia, Poland, Kenya, and Argentina. The average cost per person with dementia in the higher WB groups is “diluted” by newly promoted countries with lower economic strength than the original countries in that particular WB group. At the same time, the remaining lower income countries are “drained” by the loss of more prosperous countries that have moved upward in the WB classification. We addressed this problem by stratifying the 2015 estimates according to the 2010 and the 2015 classification. The long-term care sector is very underdeveloped in most LAMIC, but economic growth, accompanied by social and demographic change, may increase demand resulting in the establishment and/or expansion of a formal long-term care sector as a complement to informal care.Although the basics for the global cost estimates are available COI studies of dementia, the costing model imputes missing country data based on the assumed relationship between the economic strength of a country and resources for dementia care. COI studies from LAMIC are rare, with, therefore, a greater reliance on imputation for these countries. Nevertheless, the correlation between the GDP per capita and direct costs per person with dementia seems to be robust.The current report is not a complete systematic update, although some important new COI studies are added and data on resource use and costs from the 10/66 Dementia Research Group. However, the number of cost components that are included in COI studies varies, which can make comparisons problematic. For example, in the new UK report, a cost estimate of people who had gone missing because of dementia was included, The cost forecasts should be treated with particular caution. Besides the generic heterogeneity of COI studies, we also had to make assumptions regarding the appropriate age-specific prevalence estimates to use at each time point. Furthermore, the dynamics of change in care patterns across regions and the potential for effective primary prevention programs for dementia are all hard to forecast.1.Systematic review: The estimated numbers affected by dementia are based on a fully systematic updated review of prevalence studies. We did not carry out a fully systematic review of cost of illness (COI) studies, but we identified several important new studies and used these to replace older data.2.Interpretation: Worldwide costs of dementia are enormous and still inequitably distributed. The increase in costs arises from increases in numbers of people with dementia and in increases in per person costs.3.Future directions: We hope that more service utilization and COI studies will be carried out, improving the overall quality, coverage, and recency of the evidence base, which, coupled with an ongoing commitment to monitor trends in prevalence and numbers, will allow us to estimate global costs and trends with more accuracy. We are eager to integrate this work within plans for a Global Observatory to be coordinated by the World Health Organization.It is our hope that more service utilization and COI studies will be carried out, improving the overall quality, coverage, and recency of the evidence base, which, coupled with an ongoing commitment to monitor trends in prevalence and numbers, will allow us to estimate global costs and trends with more accuracy. We are eager to integrate this work within plans for a Global Observatory to be coordinated by the World Health Organization.


Lagovirus europaeus GI.2, also known as RHDV2 or RHDVb, is an emerging virus that causes rabbit haemorrhagic disease (RHD) in European rabbits (Oryctolagus cuniculus). In contrast to L. europaeus GI.1 (or RHDV/RHDVa) viruses that are only pathogenic for adults, GI.2 causes clinical disease in both adults and kittens. However, detailed descriptions of the pathology of this virus that may provide insight into its pathogenicity and emergence are lacking. Using an Australian GI.2 field strain isolated in 2015, we provide the first detailed description of pathology, viral antigen distribution and tissue load of GI.2 in adult and 5-week old New Zealand white rabbits using histology, immunohistochemistry and RT-qPCR. Liver was the target organ, but in contrast to GI.1 viruses, lesions and inflammatory responses did not differ between adults and kittens. Lymphocytic inflammation, proposed to be protective in kittens infected with GI.1, was notably absent. We also present the first descriptions of bone marrow changes in RHD, including decreased myeloid-to-erythroid ratio. Consistent with other pathogenic lagoviruses, intracellular viral antigen was demonstrated in hepatocytes and cells of the mononuclear phagocytic system. In terminal stages of disease, viral loads were highest in liver, serum and spleen. Despite the small sample size, our data suggest that unlike early European GI.2 strains, the pathogenicity of the Australian GI.2 virus is similar to GI.1 viruses. Additionally, GI.2 was fatal for all (n = 5) inoculated kittens in this study. This may significantly alter RHD epidemiology in the field, and may impact biocontrol programs for invasive rabbits in Australia where GI.1 viruses are intentionally released. Oryctolagus cuniculus) that primarily affects the liver ) In extrahepatic tissues, lesions included thrombi and haemorrhage typical of disseminated intravascular coagulation (DIC) , splenicUsing immunohistochemistry, presence of viral antigen was clearly associated with hepatic lesions and degenerate and dead hepatocytes and antigen spread from periportal areas towards the central vein as disease progressed. Location of virus within hepatocytes was primarily intracytoplasmic and finely stippled, although rimming of the cell membrane, as described by Park and Itakura  for GI.1In addition to hepatocytes, viral antigen was also detected within cytoplasm of cells of the mononuclear phagocytic system. These include Kupffer cells in the liver, macrophages within the spleen, bone marrow and lungs, as well as cells consistent with intravascular monocytes or even tissue macrophages that have re-entered circulation in various tissues. While functions of these cells are diverse, they are phagocytic and can play a role in both innate and adaptive immunity . Within Within lymphoid tissues, viral antigen was not present in lymphocytes or associated with lymphocytolysis or lymphoid depletion. This suggests that lymphocytolysis is the result of a secondary mechanism, for example increased glucocorticoids associated with stress as is seen in lymphoid tissues, especially the thymus .8 viral copies per mg and in just over half of the tissues containing 107 viral copies per mg tissue. However, 106 viral copies per mg tissue was below the detection limit for the immunohistochemical analysis of this material. We are confident that staining, when present, corresponds to viral antigen, but we cannot exclude the possibility that tissues or cells containing lower amounts of virus were not detected with immunohistochemistry. While PCR is more sensitive, it does not allow for specific in situ localization of virus within tissues nor can it be correlated with microscopic lesions. Using immunohistochemistry, intracellular virus presence was seen in liver and in cells of the mononuclear phagocytic system in the spleen, bone marrow, lungs and intravascular monocytes. However, virus was also detected in high levels in the serum and in reasonable amounts (106 copies per mg) in numerous other tissues, including trachea and small intestine. The lack of lesions in these tissues suggests PCR is likely detecting viral RNA in free viral particles in the blood in these tissues, as well as in the lumen of the intestine from virus excreted via the bile, respectively. Additionally, the high viral load in bone marrow may contribute to the epidemiology of RHD in wild rabbit populations by prolonging environmental persistence of virus when all other tissues except for the skeleton are gone, provided the virus material in bone marrow remains infectious.Assessment of immunohistochemical staining of inoculated animals in conjunction with both the negative tissue and immunoglobulin controls allowed us to conclude that the immunohistochemistry performed on this material was very specific and that non-specific staining and background staining were absent. However, the analysis required a large amount of virus to be present before antigen could be detected in situ. Antigen was readily detected in tissues with 10To conclude, unlike early GI.2 viruses . Mahar e


Maize chlorotic mottle virus (MCMV) and a specific member of the Potyviridae, such as Sugarcane mosaic virus (SCMV), Wheat streak mosaic virus (WSMV) or Johnson grass mosaic virus (JGMV). Typical maize lethal necrosis symptoms include severe yellowing and leaf drying from the edges. In Kenya, we detected plants showing typical and atypical symptoms. Both groups of plants often tested negative for SCMV by ELISA.Maize lethal necrosis is caused by a synergistic co-infection of We used next-generation sequencing to identify viruses associated to maize lethal necrosis in Kenya through a metagenomics analysis. Symptomatic and asymptomatic leaf samples were collected from maize and sorghum representing sixteen counties.Maize streak virus (MSV) and Maize yellow dwarf virus-RMV (MYDV-RMV). These four viruses  were found together in 30 of 68 samples. A geographic analysis showed that these viruses are widely distributed in Kenya. Phylogenetic analyses of nucleotide sequences showed that MCMV, MYDV-RMV and MSV are similar to isolates from East Africa and other parts of the world. Single nucleotide polymorphism, nucleotide and polyprotein sequence alignments identified three genetically distinct groups of SCMV in Kenya. Variation mapped to sequences at the border of NIb and the coat protein. Partial genome sequences were obtained for other four potyviruses and one polerovirus.Complete and partial genomes were assembled for MCMV, SCMV, Our results uncover the complexity of the maize lethal necrosis epidemic in Kenya. MCMV, SCMV, MSV and MYDV-RMV are widely distributed and infect both maize and sorghum. SCMV population in Kenya is diverse and consists of numerous strains that are genetically different to isolates from other parts of the world. Several potyviruses, and possibly poleroviruses, are also involved.The online version of this article (10.1186/s12985-018-0999-2) contains supplementary material, which is available to authorized users. Zea mays L.) is one of the most important cereals in Sub-Saharan Africa and is grown in approximately 25 million hectares  and napier grass (Pennisetum purpureum S.) were also included to determine their potential as alternate hosts. Viruses present were identified by metagenomics using next-generation sequencing of total RNA and bioinformatics. Viral presence was determined for each individual sample using de-novo assembled contigs.We hypothesized that uncharacterized viruses synergistically interact with MCMV to cause maize lethal necrosis, and there is genetic variation between SCMV and MCMV in East Africa compared to the rest of the world. To test these hypotheses, we collected samples from symptomatic and asymptomatic maize leaves in sixteen counties in Kenya. Cultivated and wild sorghum In the phylogenetic analysis, samples that cluster together belong to the same group based on variation between NIb and the coat protein Fig. . HoweverSamples from the counties of Kirinyaga and Uasin Gishu clustered near isolates from Ethiopia, while samples from Bomet, Migori, Transzonia and Kericho clustered near isolates from Rwanda Fig. . Thus, tVariation described above for SCMV in Kenya is unlikely to be sequencing error, because similar deletions are present in published SCMV isolates and because variation mapped to a common area in all samples analyzed Fig. . FurtherResults described above show that SCMV from Kenya exhibits high genetic variation that formed six clusters based on genome sequence. Kenya samples and isolates from other parts of the world can be divided into at least three groups based on nucleotide and amino acid sequence at the C terminus of NIb and N terminus of the coat protein Fig. .MSV described in this study showed 96 to 100% similarity to the South African isolate AF329878.1) used as reference Fig. . Eight c78.1 usedMaize yellow mosaic virus and Maize yellow dwarf virus-RMV2 were included for comparison. Sequences from Kenya obtained in this study were 97 to 100% similar to  isolate from Nigeria  was detected in maize plants showing lethal necrosis-like symptoms in Rwanda Hubei Poty-like virus 1, Scallion mosaic virus and JGMV  Additional file 8:MSV contigs used for phylogenetic analysis. (FASTA 20 kb)Additional file 9:MYDV-RMV contigs used for phylogenetic analysis. (FASTA 27 kb)


The Second Annual Meeting of the European Virus Bioinformatics Center (EVBC), held in Utrecht, Netherlands, focused on computational approaches in virology, with topics including (but not limited to) virus discovery, diagnostics, (meta-)genomics, modeling, epidemiology, molecular structure, evolution, and viral ecology. The goals of the Second Annual Meeting were threefold: (i) to bring together virologists and bioinformaticians from across the academic, industrial, professional, and training sectors to share best practice; (ii) to provide a meaningful and interactive scientific environment to promote discussion and collaboration between students, postdoctoral fellows, and both new and established investigators; (iii) to inspire and suggest new research directions and questions. Approximately 120 researchers from around the world attended the Second Annual Meeting of the EVBC this year, including 15 renowned international speakers. This report presents an overview of new developments and novel research findings that emerged during the meeting. Bringing together the expertise of bioinformaticians and virologists is crucial, because often fundamental computational issues need to be discussed that emerge from specific questions arising in virus research. The issues are further accentuated by the fact that the era of big data has also reached virology, in full strength. The European Virus Bioinformatics Center (EVBC) aims at reinforcing the synergy between bioinformatics and virology at all levels, including national and international funding scales, which is an urgent issue ,2. CollaA number of presentations were given by leading virologists and bioinformaticians; highlights included the following:Metagenomics is changing the existing ideas on biodiversity and on the diversity and scope of the earth’s virome in particular. Already at this time, the number of new viruses that are being discovered by metagenomic approaches  by far exceeds that identified by traditional approaches. Accordingly, the International Committee on Taxonomy of Viruses (ICTV) has adopted new rules that allow new virus species and higher taxa to be formally recognized on the basis of metagenomic sequence alone, provided that the respective genome(s) is (are) (nearly) complete and that adequate genome analysis is presented . MetavirIt should be emphasized that, to take the full advantage of the rapid proliferation of metagenomic data, it is essential to apply the full armory of the most powerful and robust methods for protein-sequence and -structure analysis. In the years to come, metaviromics can be expected to advance at an accelerating rate and, combined with strategic choice of virus models for experimental study, will be the foundation of the new virology. One of the expected outcomes of the advances of metaviromics is a complete overhaul of virus taxonomy.Virus evolution is driven not only by the inheritance of genetic modification but also by the acquisition of foreign DNA. The evolutionary processes that affect genomic diversity include point mutation, recombination, and gene turnover. The temporal dynamics of these molecular events are crucial for our understanding of virus genome evolution. Heterochronous sequences, that is, sequences from isolates that were sampled at different time points, can provide detailed evidence for the evolutionary processes that shaped the populations over the sampling time. Evolutionary rates have been estimated for bacteria and for eukaryotic viruses but only rarely for bacteriophages. Phages are recognized as major contributors to bacterial evolution and ecology in nature. Thus, the estimation of phage evolutionary rates provides the basis for a quantitative assessment of phage evolutionary rates that are in action during phage bacteria antagonistic coevolution.Lactococcus lactis strain from a single dairy over 29 years. The analysis pipeline used was based on publicly available tools that were combined with the assessment of temporal signals at all stages of the analysis. Furthermore, it was necessary to disentangle vertical and horizontal evolutionary processes to detect a separate molecular clock signal in substitutions originating from mutational processes and in recombination events. Using this approach, we estimated substitution and recombination rates individually. The substitution rate of Staphylococcus aureus [Streptococcus pneumoniae lineage isolated over 20 years [We recently estimated evolutionary rates from heterochronous dsDNA phage genomes ; 34 isols aureus  and 7.2 20 years . Thus, oThe analysis of heterochronous sequencing data requires appropriate mathematical models and bioinformatic tools. Models and tools for substitution rate estimation from heterochronous data are well established . It is David presented his research group and collaborator’s work on virus–host molecular interaction networks. Here, the focus was on the intracellular ”living” aspect of the virus, the exploitation of the host system. This directed the study of viruses on both their own and their host’s genome/proteome and the combined molecular interactions involved in the intracellular dynamics of infection. Most research in this area has been on HIV-1, as it is for this system that the majority of experimental work exists. This data was first painstakingly captured from the literature and visualized 10 years ago . In partIn more recent work, we have applied control theory to the virus–host interaction network . A systeTo support the development of novel or improved antiviral strategies such as vaccines and biomarkers for personalized medicine, ”omics tools” are used to study the induction and regulation of the host (immune) response to viral infections. In a biomarker study, we investigated whether there exists a blood genomic signature that can accurately predict the course of respiratory syncytial virus (RSV) infection in young infants. RSV causes infections that range from the common cold to severe lower respiratory tract infection requiring high-level medical care. The prediction of the course of disease in individual patients is challenging at first visits to pediatric wards, as RSV infections may rapidly progress to severe disease. We used early blood microarray transcriptome profiles collected from 39 hospitalized infants  that were followed until recovery and for whom the level of disease severity was determined retrospectively. Applying support vector machine learning on age-by-sex standardized transcriptomic data, an 84-gene signature was identified that discriminated hospitalized infants with eventually less severe RSV infection from infants that suffered from the most severe RSV disease. This signature yielded an area under the receiver operating characteristic curve (AUC) of 0.966 using leave-one-out cross-validation on the experimental data and an AUC of 0.858 on an independent validation cohort consisting of 53 infants . The preVarroa destructor, which vectors RNA viruses, including deformed wing virus , a leading culprit of colony losses. Many bee viruses have been sequenced, and structural features are now available for viruses such as DWV. DWV consists of at least three distinct genotypes, two of which have been shown to be differentially virulent in honeybees. Molecular studies have demonstrated that DWV has a mean evolutionary rate of 1.35 × V. destructor transmission on virus evolution represents an important question in bee virus research. Because of the nature of the V. destructor life cycle, predictions can be made about the potential impact of the mite on virus virulence evolution. Specifically, the developing honeybee host pupa should remain alive until close to the completion of metamorphosis to provide sufficient time for successful mite reproduction, including offspring mating. For optimal transmission, any virus found in a mature and mated daughter mite will hold a significant selective advantage over a virus found in an immature or unmated daughter mite—placing a cost on virus virulence that impacts honeybee pupae before mites can mate. On the other side, viruses replicating too slowly and with delayed virulence effects will hold a selective handicap because fewer transmission units will be found in mated mites. I have hypothesized that the evolution of virus virulence shifted following the arrival of V. destructor, with viruses, including recombinants and/or specific viral genotypes, being selected for a level of virulence in pupae  that maximizes R0, which represents the basic reproductive number of the virus in the host population. R0 is defined by the number of subsequent infections caused by a single infection, and it must be greater than 1 for an infection to spread in a population. It is enhanced by maximizing the number of transmission units passed to uninfected susceptible vectors and ultimately hosts emergence of viruses. These viruses are predominantly positive single-stranded (+ss) RNA viruses belonging to the Picornavirales. Managed honeybees are often infested with the invasive mite, ly hosts .Apis mellifera), DWV can infect other Asian honeybee species, such as Apis ceranae. Aside from honeybees, DWV has been found widely in bumblebees, including solitary bees, and in wasps, and there is evidence that it can actively replicate in several Bombus and solitary-bee species. Whether the arrival of the V. destructor mite in A. mellifera has driven the viral emergence in non-Apis bees is a target of ongoing research.Honeybee viruses are also shared with sympatric wild bees, and viral prevalence and sequence data indicate frequent virus transmission between managed and wild-bee species. In addition to infecting the western honeybee (GenSeed-HMM [TABAJARA (TABAJARA is able to find blocks that are either (1) conserved across all sequences or (2) discriminative for two or more specific groups of sequences. The program uses different metrics to ascribe position-specific scores along the whole alignment and then uses a sliding window to find top-scoring regions. Selected alignment blocks are then extracted and used to build profile HMMs. To validate such models, we used sequence data from phages of the Microviridae family and members of the Flavivirus genus. In both viral groups, we were able to obtain wide-range seeds  and narrow-range seeds, exclusive to specific Microviridae subfamilies (Alpavirinae and Gokushovirinae) or to particular Flavivirus species . Additionally, using TABAJARA’s generated profile HMMs as seeds, we succeeded to reconstruct specific viral sequences with the GenSeed-HMM program using different metagenomic datasets. Finally, we also report the development of e-Finder, a program that uses profile HMMs to identify clusters of genes in a specified syntenic context. This tool allows the detection of viral and nonviral elements such as prophages, transposons, CRISPR-Cas systems, and operons in assembled genomes. These programs constitute a toolbox and can be used alone or in combination to detect and classify known viruses as well as distantly related viruses that may represent potentially emerging pathogens. This work was done by the team composed of Liliane S. Oliveira, Dolores U. Mehnert, Paolo M. A. Zanotto, Alan M. Durham, Alejandro Reyes, and Arthur Gruber.Some of the most devastating pandemic diseases have arisen through the transmission of emerging viruses that have not been identified before the tragic consequences of their dissemination. The detection of novel viruses is a challenging task because of their high evolutionary rates, which result in high sequence divergence. The development of new computational approaches is, therefore, of utmost importance. Profile HMMs are a powerful way of modeling sequence diversity and constitute a very sensitive approach to detecting emerging viruses . Our groSeed-HMM , a tool TABAJARA , a tool Historically, enterovirus D68 (EV-D68) has only been associated with respiratory illnesses. However, in the summer of 2014, an EV-D68 outbreak coincided with a spike in polio-like acute flaccid myelitis/paralysis (AFM) cases. Statistical analysis suggested that the number of AFM cases was significantly higher during the EV-D68 outbreak than in historical controls. These reports have raised concerns that the EV-D68 virus could have been the causative agent of AFM during this recent outbreak. We recently reported a phylogenetic analysis of the 2014 outbreak and found that isolates associated with AFM belonged to a single phylogenetic subclade, B1 . To deteThis work was done by David M. Brown, Lauren M. Oldfield, Alison M. Hixon, Yun Zhang, Mark Novotny, Wei Wang, Suman Das, Reed S. Shabman, Kenneth Tyler, and Richard H. Scheuermann. The study is funded by the National Institute of Allergy and Infectious Diseases (NIH/DHHS) under Contract No. HHSN272201200005C.n = 355) and irritable bowel syndrome (n = 400). We tested three tools commonly used for the analysis of gut metagenomics data: (1) MetaPhlAn; (2) Kraken; and (3) DUDes. All three tools detected viruses in only a minority of the Lifelines-DEEP samples , with moderate overlap across the three methods . Other virome-specific tools and de novo data assembly methods are therefore required to determine the true viral proportion and abundance in metagenomics data. Data analysis for this project was performed by Sanzhima Garmaeva, PhD student in the Department of Genetics, UMCG.The human gut microbiome contains millions of viruses, bacteria, protozoa, and fungi. The abundance of bacterial species and the diversity of bacterial compositions have now been linked to many host diseases and conditions, in particular, to predispositions to autoimmune diseases, metabolic conditions, obesity, and cancer. Although the bacterial part of the human microbiome has been relatively well studied, the virome contribution remains largely unexplored, despite gut viruses forming a substantial part of the total microbiome: the proportion of viruses in adults is estimated to be 5–10% of the number of bacteria. Several pioneering studies have indicated that viruses are relatively stable in time and are associated with gut diseases, particularly with inflammatory bowel disease. Virome-specific isolation of nucleic acids from stool samples requires additional, currently laborious, methods. However, given the high abundance of viruses in the gut, metagenomic sequencing of all DNA isolated from stool should contain a substantial proportion of viral DNA. In this work, we aimed to investigate the gut virome abundance in a population cohort, Lifelines-DEEP (1179 samples), and compared it that of with patients suffering from inflammatory bowel disease . First, we developed a method to estimate the proportion of cellular sequences in viromes. A quarter of the published datasets were found to contain a substantial number of sequences originating from cellular genomes, either as a result of shortcomings in experimental protocols, as virus-like particles (VLPs) are described as difficult to purify from some matrices , or because of VLPs containing cellular DNA . When considering viromes with no cellular DNA detected, a significant number of cellular metabolism genes were retrieved, for example, some ribosomal proteins, suggesting that the presence of auxiliary genes involved in various metabolic pathways within viral genomes is a general trend in the virosphere . We thenConsidering the fact that viromes can contain a substantial number of sequences originating from cellular genomes, a tool was developed to identify viral sequences in such datasets. Using both homology to reference viral sequences and viral genome characteristics, VirSorter complements existing prophage prediction software and was proved to be able to identify viral signals in assembled sequence (contigs) as short as 3 kb .Once the viral contigs are identified, determining the identity of their hosts is crucial for deciphering the interactions and dynamics between microbes and their viruses and thus for our ecological understanding of the microbiome. To determine the hosts of the newly sequenced viruses, we used the fact that viruses tend to have a genomic signature similar to their prokaryotic hosts. Using homogeneous Markov models, our tool WisH was found to predict hosts for short phage genomic fragments with a better accuracy than existing tools such as VirHostMatcher . FurtherUsing bioinformatic methods and software, we studied viral communities in aquatic systems such as freshwater lakes and hypersalin ponds, and in the context of the Virus-X EU project (Horizon 2020 Project No. 685778), we mostly focused on Icelandic hot springs. The analysis of viromes informs us about the composition, diversity, and dynamics of the viral communities in these environments and allowed us to analyze the main viral families retrieved in these datasets, mostly Caudovirales and ssDNA viruses such as Microviridae.This work was done by Simon Roux, Clovis Galiez, Jonathan Vincent, Marie-Agnès Petit, Matthew B. Sullivan, Johannes Söding, Didier Debroas, Mart Krupovic, and François Enault.Zika virus (ZIKV) is responsible for an ongoing outbreak concentrated in South and Central America and the Caribbean, with travel-based cases being reported around the globe. In addition, new outbreak clusters located in the southeastern United States have been attributed to autochthonous transmission. As multi-disciplinary collaborations are forming to combat the ZIKV outbreak, it is imperative to authenticate and sequence-verify existing reagents prior to performing infection experiments to better understand and combat increasing virulence. Here, we report high-quality sequence data for multiple ZIKV strains available from the Biodefense and Emerging Infections Research Resources Repository (BEI Resources). These sequence data include the historical reference strain from the African lineage (MR-766), the Asian lineage derived American reference strain (PRVABC59), and several other strains collected from around the world during the 2015 outbreak with documented passage histories. We used next-generation sequencing coupled with 3’ rapid amplification of cDNA ends (RACE) and viral genome annotation pipelines to generate consensus sequence records in GenBank. We applied a deep-sequencing analysis method to identify minor variants, which exist as natural quasi-species within viral stocks. We detected minor variants that consistently resulted in nonsynonymous substitutions at multiple codons among a subset of the Asian strains. Interestingly, the nonstructural protein 1 (NS1) and membrane glycoprotein (prM) coding regions had the highest number of minor variants in the Asian and African lineages, respectively. The evolutionary relationships for these strains were determined using phylogenetic methods, and a single recombinant sequence was identified. These bioinformatics analyses of the sequencing results confirm that the BEI Resources virus stocks available to the scientific research community adequately represent the viral population diversity of ZIKV and justify additional wet-lab experiments. In addition, we used peptide arrays consisting of 866 15-mer peptides (in quadruplicate) to screen 140 well-characterized human convalescent sera for peptides that differentiate between past infection with multiple mosquito-borne viruses. Peptides representing dengue virus serotypes 1–4 and West Nile, Chikungunya, and Zika viruses were synthesized chemically and linked covalently to glass slides prior to measuring peptide-specific binding of anti-virus IgG for these seven mosquito-borne viruses. The data from all arrays were combined prior to applying multiple rounds of machine learning, a weighting scheme, and a B-cell epitope prediction algorithm. Together, this novel computational workflow identified pools of 10 immunodominant 15-mer peptides for each of the viruses. An indirect ELISA protocol was optimized to enable the validation of our selected 15-mer peptides against large collections of clinical serum samples. These experiments will enable the quantification of the diversity in antibody responses against mosquito-borne viruses in human patients and can be used to enhance vaccine development efforts, improve point-of-care diagnostics, and enable more accurate calculation of seroprevalence in endemic areas.Human influenza viruses cause short-term respiratory infections with considerable morbidity and mortality in seasonal epidemics. A trivalent or quadrivalent vaccine protects against the two circulating subtypes of influenza A (pH1N1 and H3N2) and against one or two lineages of influenza B viruses. Because of the rapid antigenic evolution of the surface proteins, primarily the hemagglutinin, the vaccine requires regular updates to remain effective. The World Health Organization (WHO) maintains a global surveillance system and collects and analyzes data biannually to recommend strains included in the vaccine for the next influenza seasons. Because of the lengthy vaccine production process, this update has to be performed one year in advance. This is the “vaccine strain prediction problem”, in which predicting a strain representing the predominant antigenic virus type has to be made one year ahead of time. A false or late prediction results in vaccines with suboptimal protection and an increase in influenza-related cases and mortality .Over the last 10 years, we have worked on computational methods for predicting a necessary vaccine strain, because of the emergence of a novel antigenic type, and investigated which strains could be used for this update. In , we descAD-plots, however, do not give us information about the antigenicity-altering nature of the respective alleles; thus they do not directly point to antigenically altered alleles rising to predominance. We thus devised antigenic trees, or more generally, phenotype trees , a methoDifferently from HA sequence data, which is made public in a timely manner , only liWe added a statistical significance measure to the AD-plots for identifying alleles—now corresponding to individual amino acid changes on a specific branch—rising to predominance. These “sweep dynamics” (SD) plots indicate alleles increasing significantly in frequency over consecutive seasons and with abundances above 50%—thus “sweeping” towards predominance. This, together with antigenic patch information, provided the basis for a computational vaccine strain prediction procedure . We obseIn many organisms, multiple copies of parts of the genome can be present, and the number of copies present can vary within populations. We refer to such genomic diversity as copy number variation (CNV). In bacteria, CNV plays an important role in adaptation, for example, in the presence of antibiotics. Although the beneficial effects of CNV are often small, the mutation supply for CNV is very large. Given the amount of standing genetic variation present in most bacterial populations, selection can immediately act on CNV. CNV is therefore typically the first line of bacterial genetic adaptation and is often followed later by single-nucleotide variants with greater beneficial effects and a reversion of CNV. Although CNV plays an important role in bacterial adaptation, we know very little about the role of CNV in virus adaptation. Virus genomes tend to be highly streamlined: any inserted sequences—whether duplications of virus genes or heterologous genes—typically are rapidly purged. One might therefore expect that CNV does not play a role in virus adaptation, but surprisingly there are examples to the contrary. CNV is known to play a transient role in poxvirus adaptation to new hosts: influenza A virus can downregulate the frequency of the genome segment coding for its neuraminidase, and baculoviruses can regulate expression of infectivity factors through polymorphic genomic deletions. Multipartite (or multi-component) viruses take a more radical approach and package their different genome segments into different virus particles. At least one virus particle containing each genome segment must then reach a new cell for the virus to be successfully transmitted. This strange genome and virus particle organization comes at a huge cost: a predicted inefficient transmission of the virus, both within and between hosts. Why has strange genome organization arisen? Here, we explored this issue for a tripartite plant RNA virus, alfalfa mosaic virus. First, we revisited classical virological work and considered infection kinetics in detail, documenting that multipartition does indeed impose a huge cost on virus infectivity. Second, we found that the different genome segments are not present at the same frequency, similar to observations with nanoviruses. When perturbed, the frequency of these segments converges to a stable equilibrium, which is host-species dependent. These observations suggest that changes in the frequency of genome segments might be a strategy for adapting to different environments, for example, because they lead to differences in the expression of viral genes. Third, models of virus evolution show the importance of genetic bottlenecks for adaptation by changes in the frequency of genome segments. These bottlenecks generate the variation in segment frequencies on which selection can then act, which allows for rapid, “mutation-free” adaptation to different environments. Finally, we used these models of virus evolution to consider how heterogeneous environments must be to favor a multipartite over a monopartite genome organization. Changes in genome segment frequencies might therefore play a similar role to CNV in other viruses and bacteria, although the lack of linkage between these copies imposes both unique costs to infectivity and a very large, continuous supply of variation for natural selection to act on. These results stress that CNV can sometimes play an important role in virus adaptation and suggests that it be given due consideration when considering high-throughput sequencing data.V-pipe. The workflow integrates tools for the assessment of the viral diversity at the levels of both single nucleotide variants (SNVs) and viral haplotypes. V-pipe is an automated and easy-to-use framework delivering reproducible results. Furthermore, it features a modular and extensible architecture that enables developers to easily test their own tools, contributing towards the establishment of best practices for clinical diagnostics. This work was done by Susana Posada-Céspedes, David Seifert, Tobias Marschall, and Niko Beerenwinkel.RNA viruses are responsible for various infectious diseases in humans, animals, and crops, representing a burden to human health as well as causing substantial economic losses. One major limitation when treating viral infections is the great genetic diversity featured by RNA viruses. The existence of a heterogeneous mixture of viral strains has implications on viral pathogenesis, virulence, and disease progression. HTS technologies have opened up new possibilities for in-depth characterization of the diversity of viral samples, and the ultimate goal is to define standards for research as well as to incorporate the use of this technology into clinical diagnosis. In order to support HTS-based viral genomics, we devised and implemented a bioinformatics pipeline, The field of phylodynamics has witnessed a rich development of statistical inference tools with increasing levels of sophistication, but these tools have traditionally focused on sequences as their sole data source. Integrating various sources of information with genomic data promises to deliver more precise insights into infectious diseases and to increase opportunities for statistical hypothesis testing.Emerging concepts of data integration are now stimulating new advances in Bayesian evolutionary inference methodology. We have worked on such methodology in the BEAST software, which represents a coherent statistical framework for integrated analyses of sequences and traits using Bayesian inference techniques. These approaches were applied in various outbreak scenarios and real-time genomic epidemiology. For discrete traits, we have developed generalized linear modeling extensions of continuous-time Markov chain processes that allow the integrating and testing of covariates. Applications using this approach have focused on the dynamics of spatial spread for viruses such as influenza and Ebola. We have also developed equivalent random walk models for continuous traits to test specific hypotheses about the impact of border closures on Ebola dispersal frequency. The 2013–2016 West African Ebola epidemic marked the start of real-time genomic sequencing, and this methodology can make an important impact on outbreak responses. Recent work during the Lassa fever virus outbreak demonstrated this and brings about new bioinformatics challenges.One important facet of the annual EVBC meeting was the poster sessions. The friendly atmosphere was instrumental to developing fruitful discussions during the long poster sessions combined with lunches and dinners.The second EVBC meeting was a success in its primary aims of bringing virologists and bioinformaticians together to share ideas, agree on differences of opinion, and create a future action agenda.Collectively, this meeting hosted 15 oral presentations and 2 long poster sessions over a two day period with around 120 participants. This report presents an overview of salient new developments and novel research findings that emerged during the second EVBC annual meeting. We hope that the highlights provided in this report will encourage interested researchers to join us at the Third Annual Meeting of the European Virus Bioinformatics Center, which will be held in 2019 at the University of Glasgow; wish to see you all again.Name Affiliation City-CountryAkbar Adjie PratamaUniversity of GroningenGroningen-NetherlandsAlessandro RossiUtrecht UniversityUtrecht-NetherlandsAlexander SchoenhuthCentrum Wiskunde & Informatica Amsterdam-NetherlandsAlexander KurilshikovUniversity Medical Center GroningenGroningen-NetherlandsAlexandra BelanovaFree University of BerlinBerlin-GermanyAlexandra ZhernakovaUniversity Medical Centre GroningeGroningen-NetherlandsAli ElbeheryHelmholtz Center MunichMunich-GermanyAlice FusaroIstituto Zooprofilattico Sperimentale delle VenezieLegnaro-ItalyAlice McHardyHelmholtz Center for Infection ResearchBraunschweig-GermanyAna Rita CostaDelft University of TechnologyDelft-NetherlandsAnita SchurchUniversity Medical Center UtrechtUtrecht-NetherlandsAnne KupczokKiel UniversityKiel-GermanyAnnelies KronemanNetherlands National Institute for Public Health and the EnvironmentBilthoven-NetherlandsArno C. AndewegErasmus Medical CenterRotterdam-NetherlandsArthur GruberUniversity of São PauloSão Paulo-BrazilArthur EdridgeUniversity of AmsterdamAmsterdam-NetherlandsAvraam TapinosUniversity of ManchesterManchester-UKBas Oude MunninkErasmus University Medical CenterRotterdam-NetherlandsBas E. DutilhUtrecht UniversityUtrecht-NetherlandsBashar IbrahimFriedrich Schiller University JenaJena-GermanyBastiaan Von MeijenfeldtUniversity of UtrechtUtrecht-NetherlandsBen StampMRC-University of Glasgow Centre for Virus ResearchGlasgow-ScotlandBrett PickettJ. Craig Venter InstituteRockville-USACeren SimsekKatholieke Universiteit LeuvenLeuven-BelgiumCesare GruberNational Institute for Infectious Diseases Rome-ItalyChenyan ShiKatholieke Universiteit LeuvenLeuven-BelgiumCormac KinsellaUniversity of AmsterdamAmsterdam-NetherlandsC. Aparicio-MaldonadoDelft University of TechnologyDelft-NetherlandsDaniel GarzaCMBINijemegen-NetherlandsDaniela BezemerHIV Monitoring FoundationAmsterdam-NetherlandsDavid RobertsonMRC-University of Glasgow Centre for Virus ResearchGlasgow-ScotlandDavid NieuwenhuijseErasmus University Medical CenterRotterdam-NetherlandsDaniel DesiroFriedrich Schiller University JenaJena-GermanyDennis SchmitzNetherlands National Institute for Public Health and the EnvironmentUtrecht-NetherlandsDino McMahonFree University of BerlinBerlin-GermanyDivyae PrasadUtrecht UniversityUtrecht-NetherlandsEduardo De EsesarteUtrecht UniversityUtrecht-NetherlandsErik De VriesUtrecht UniversityUtrecht-NetherlandsEric HesterRadboud UniversityNijmegen-NetherlandsEugene KooninNational Center for Biotechnology InformationBethesda-USAEva WeissUniversity of YorkYork-UKFrancesca YoungMRC-University of Glasgow Centre for Virus ResearchGlasgow-UKFrançois EnaultUniversité Clermont AuvergneClermont Ferrand-FranceFrank Van KuppeveldUtrecht UniversityUtrecht-NetherlandsFranklin NobregaDelft University of TechnologyDelft-NetherlandsGianpiero ZamperinIstituto Zooprofilattico Sperimentale delle VenezieLegnaro-ItalyGonçalo PiedadeRoyal Netherlands Institute of Sea Research’t Horntje-NetherlandsGuillaume BeauclairInstitutPasteurParis-FranceHarry VennemaNetherlands National Institute for Public Health and the EnvironmentBilthoven-NetherlandsHilde HerremaUniversity of AmsterdamAmsterdam-NetherlandsHimanshu ManchandaUniversity of GreifswaldGreifswald-GermanyJelle MatthijnssensKatholieke Universiteit LeuvenLeuven-BelgiumJelmer FaberRadboud UniversityNijmegen-NetherlandsJenna KellyInstitute of Virology and ImmunologyBern-SwitzerlandJoan Martí-Carreras Katholieke Universiteit LeuvenLeuven-BelgiumJoanna KaczorowskaUniversity of AmsterdamAmsterdam-NetherlandsJoseph BusbyMRC-University of Glasgow Centre for Virus ResearchGlasgow-UKJulian SusatKiel UniversityKiel-GermanyKaat RamaekersRega Institute for Medical ResearchLeuven-BelgiumKathrin TrappeRobert Koch-InstituteBerlin-GermanyKevin LamkiewiczFriedrich Schiller University JenaJena-GermanyKim NgStatens Serum InstituteCopenhagen-DenmarkKoen DeforcheEmweb Genome DetectiveHerent-BelgiumKoenraad Van DoorslaerUniversity of ArizonaTucson-United StatesKsenia ArkhipovaUtrecht UniversityUtrecht-NetherlandsLeen BellerKatholieke Universiteit LeuvenLeuven-BelgiumLi DengHelmholtz Centre MunichMunich-GermanyLia Van Der HoekUniversity of AmsterdamAmsterdam-NetherlandsLisa FalkAmsterdam Medical CenterAmsterdam-NetherlandsLore Van Espen Katholieke Universiteit LeuvenLeuven-BelgiumLukasz RabalskiUniversity of GdanskGdansk-PolskaMartin DeijsUniversity of AmsterdamAmsterdam-NetherlandsMartin HölzerFriedrich Schiller University JenaJena-GermanyMaike HerrmannPaul-Ehrlich-InstituteLangen-GermanyManja MarzFriedrich Schiller University JenaJena-GermanyMareike DörrPaul-Ehrlich-InstituteLangen-DeutschlandMargo SchullerUtrecht UniversityUtrecht-NetherlandsMarijn Thijssen Katholieke Universiteit LeuvenLeuven-BelgiumMaria Ines GismondiNational Institute for Agriculture ResearchBuenos Aires-ArgentinaMark ZwartNetherlands Institute for EcologyWageningen-NetherlandsMarkus UlrichRobert Koch InstituteBerlin-GermanyMatthew CottenErasmus University Medical CenterRotterdam-NetherlandsMengmeng FanRega InstituteLeuven-BelgiumMichael HuberUniversity of ZurichZurich-SwitzerlandMichael WolfingerMedical University of ViennaVienna-AustriaMichel Christoph KochUniversity of BernBern-SwitzerlandMy PhanErasmus University Medical CenterRotterdam-NetherlandsOsvaldo ZagordiUniversity of ZurichSwitzerlandPhilippe Le MercierSwiss Institute of BioinformaticsGeneva-SwitzerlandPhilippe LemeyKatholieke Universiteit LeuvenLeuven-BelgiumRebecca HalbachRadboud University Medical Center Nijmegen-NetherlandsRichard ScheuermannJ. Craig Venter InstituteLa Jolla-USARobert GiffordMRC-University of Glasgow Centre for Virus ResearchGlasgow-UKRonald DijkmanInstitute of Virology and ImmunologyBern-SwitzerlandRonald Van RijRadboud University Medical CenterNijmegen-NetherlandsSam NooijNetherlands National Institute for Public Health and the EnvironmentBilthoven-NetherlandsSander Van BoheemenErasmus University Medical CenterRotterdam-NetherlandsSanzhima GarmaevaUniversity of GroningenGroningen-NetherlandsS. Calvignac-SpencerRobert Koch InstituteBerlin-GermanyShivaprasad PatilKatholieke Universiteit LeuvenLeuven-BelgiumStan BrounsDelft University of TechnologyDelft-NetherlandsSusana Posada CéspedesETH ZurichBasel-SwitzerlandSyriam Na AyudhyaErasmus University Medical CenterRotterdam-NetherlandsThierry JanssensNetherlands National Institute for Public Health and the EnvironmentBilthoven-NetherlandsThor JohannesenStatens Serum InstituteCopenhagen-DenmarkVerena KufnerUniversity of ZurichZurich-SwitzerlandWannisa RitmahanVrije UniversiteitUtrecht-NetherlandsWard DeboutteKatholieke UniversiteitLeuven-BelgiumWim DumonCreating Innovative SoftwareLeuven-BelgiumYifan ZhuWageningne UniversityWageningen-Netherlands


Hantavirus cardiopulmonary syndrome in North America is caused by Sin Nombre virus (SNV) and poses a public health problem.We identified T-cell epitopes restricted to HLA alleles commonly seen in the N. American population. Nucleocapsid (N) protein is 428aminoacid in length and binds to RNA and functions also as a key molecule between virus and host cell processes. The predictedepitopes from N protein that bind to class I MHC were analyzed for human proteasomes cleavage, TAP efficiency, immunogenicityand antigenicity. We identified 8 epitopes through MHC binding prediction, proteasomal cleavage prediction and TAP efficiency.Epitope VMGVIGFSF had highest Vaxijen score and the epitope, TNRAYFITR had highest immunogenicity score. EpitopeAAVSALETK and TIACGLFPA had 100% homology to many HCPS causing viruses. Our study focused on T-cell epitope predictionspecific to restricted HLA haplotypes of racial groups in North America for the potential vaccine development. Among the candidateepitopes, FLAARCPFL was conserved in SNV, which is suitable for vaccine specific to the virus genotype. Peptide-based vaccines canbe designed to include multiple determinants from several hantavirus genotypes, or multiple epitopes from the same genotype.Thereby, immune response will focus solely on relevant epitopes, avoiding non-protective responses or immune evasion. The otheradvantages include absence of infectious material unlike in live or attenuated vaccines. There is no risk of reversion or formation ofadverse reassortants leading to virulence and no risk of genetic integration or recombination forming a rationale for vaccine designincluding for distinct geographical regions. Sin Nombre virus (SNV) belongs to Hantavirus genus (FamilyBunyaviridae). Goldsmith et al.  documentYe et al.  reportedThe other fatal infection caused by hantaviruses is hemmorhagicfever with renal syndrome (HFRS). This is seen predominantly inAsian countries. Increased vascular permeability and leakage inthe kidneys and the lungs are responsible for characteristicdifference in the respective disease caused by the differentgenotypes. A prophylactic T cell epitope based vaccine couldinduce CTL immunity, which will protect against viral diseaselike in the case of Dengue virus .As in the case of vaccine preventable viral diseases, preexisting Tand B cell immunity could avert disease. Good CD4 T cellpriming by peptide vaccination could improve antibody responsealso during natural infection that could occur in the immunizedindividuals, "primed by vaccines, boosted by natural infection" isa good vaccine strategy . InfectiThe increased understanding of antigen recognition at molecularlevel has resulted in the development of rationally designedpeptide vaccines. In the present study, we usedimmunoinformatics strategies for designing vaccine candidate Tcellepitopes. These peptide’s epitopes are important towardsdevelopment of T-cell epitope-based vaccines that could bind tospecific Class I MHC and thereby stimulate T-cell immuneresponses.We aimed to identify candidate T-cell epitopes of SNV that arerestricted to HLA alleles common to North American populationwhere this virus is widespread. The epitopes that bind to Class IMHC that is also cleaved at the flanking regions by humanproteasomes and transporter associated with antigen processing(TAP) efficiency was also analyzed.All available complete S segment amino acid (aa) sequences(n=11) of strains of Sin Nombre virus that causes HantavitusCardiopulmonary Syndrome were retrieved from GenBankdatabase  as of OcWe selected the top 30 human Class I MHC alleles reported forWhites, Blacks, Hispanics and Asian or Pacific Islanderpopulation groups of the North American population . TheselUsing the identified consensus aa sequences as the input, T-cellepitopes that bind to MHC Class I were predicted usingNetMHCpan 3.1 online server. This program predicts binding ofpeptides to any MHC molecule of known sequence usingartificial neural networks (ANNs) . The epiThis was predicted using MAPPP (MHC-I Antigenic PeptideProcessing Prediction) program . The proTo predict the candidate epitope(s) based on the processing of thepeptide(s) in vivo, the transporter of antigenic peptides (TAP)proteins' transport efficiency was tested using TAPPred serverprogram . The preThe identified epitope(s) were used to predict whole proteinantigenicity (protective antigen) using Vaxijen 2.0 server programwith a threshold limit of 0.5 . The thrA consensus sequence of Sin Nombre virus of length 428 aa wasidentified from all available complete S segment sequence codingfor nucleocapsid protein (N protein). A total of 120 HLA types were selected for their preponderance in the North Americanracial groups. Analysis for epitopes restricted to specified class IMHC resulted in 478 possible epitopes . The results are presented in Common HLA alleles were found in the four groups of NorthAmerican population and many common T-cell epitopes wereidentified from different HLA alleles due to promiscuouspresentation of the same T-cell epitope via two or more HLAclass I molecules. Therefore, a non-redundant 63 HLA alleles wasgenerated and epitope dataset (n=85) were identified restricted tothese alleles. Among the top 30 alleles in North Americanpopulation, alleles A*02:01, B*44:03, C*03:04, C*04:01, C*06:02,C*07:02 were present in all four population groups.TAPpred analysis was carried out using full-length consensusamino acid sequence of Sin Nombre nucleocapsid coding protein.The analysis resulted in 420 possible epitopes with varyingaffinities classified as high (n=164), intermediate (186) and low ordetectable (n=70). A total of 47 epitopes were identified both byNetMHCpan 3.0 and TAPpred programs. These epitopes wereanalyzed for proteasome cleavage analysis.Further screening based on proteasome cleavage resulted in 8epitopes with scores ranging from 0.5009 to 1 . AmongtEpitope VMGVIGFSF was predicted to be restricted to bind in thebinding groove of 5 HLA types viz. A*23:01, A*24:02, A*32:01,B*15:01 and B*15:03. These types are spread in one or other offour population groups. Protein BLAST analysis of the epitoperesulted in 100% homology to Puumala virus that causes milderNephropathia epidemica, and Khabarovsk virus that causesHFRS suitable for multigenotype vaccine.Epitope AAVSALETK is restricted only to A*11:01. These allelesare widespread in Whites, Hispanics and Pacific Islanderpopulation groups. BLAST analysis of this epitope resulted in100% homology to many HCPS causing viruses: Convict CreekCanal virus, Bayou virus, New York virus, Montano virus, Jaboravirus, and El Moro Canyon virus in addition to Sin Nombrevirus.Epitope FLAARCPFL was predicted to bind to 9 different HLAalleles A*02:01, A*02:03, A*02:06, A*02:07, B*08:01, C*01:02,C*04:01, C*17:01, and C*18:01. Of these, A*02:01 and C*04:01 waspresent in all four population groups. Other 7 alleles are presentin one or other population groups. BLAST analysis of this epitoperesulted in 100% homology to Sin Nombre virus.Epitope QSRRAAVSA was restricted to HLA A*30:01 that ispresent only in top 30 alleles of black population groups. EpitopeTNRAYFITR was predicted to bind to HLA A*31:01 and A*33:03. These alleles are among the top 30 alleles of Blacks, Hispanicsand Pacific Islander population groups. BLAST analysis of thisepitope resulted in 100% homology to Tula virus, Bayou virus,LANV-2, Montano virus, El Moro Canyon virus, Convict CreekCanal virus in addition to Sin Nombre virus which all causeHCPS.Epitope TIACGLFPA was restricted to HLA A*02:01, A*02:03,A*02:06, and A*68:02 spread in the four population groups.BLAST analysis of this epitope resulted in 100% homology toAndes virus, Convict Creek Canal virus, LANV-2, Araucariavirus, Choclo virus, New York virus, RIOMV-4, and Juquitibavirus which all cause HCPS.Sin Nombre virus is an important etiological agent of HCPSmainly in North America . SporadiSchountz et al.  demonstrHLA haplotypes of host are crucial determinants of both B and Tcell specific immune response. Hooper et al.  havesucSchountz et al.  examinedHLA allele sequence are very diverse belonging to six differentclasses , a total of 11406 alleles have beenidentified as of October 2016 (IPD-IMGT/HLA database release3.26.0) . Human cHLA molecules significantly overlap in peptide bindingspecificity. Class I HLA peptide binding shows a high degree(>60%) of promiscuity . HLA allHLA allele frequencies exhibit ethnic variation, with some allelesfound widely distributed among populations and others almostexclusively within a particular ethnic group. The Class I and IIloci reside on a relatively small region of human chromosome 6and specific haplotypes. Apparently, they are present at highfrequencies in founding populations or were selected forgenerating immune response to the infectious organisms. In thissetting, linkage disequilibrium results in a significant overrepresentation of certain haplotypes . An ethnHantavirus specific CD8+ and CD4+ CTL are thought tocontribute to the immunopathology and capillary leak syndromeobserved in the HCPS . KilpatrThe present approach is to use peptide sequence data forexperimental determination of affinity. Such findings have beenused in the construction of many T-cell epitope predictionalgorithms and the outcome of such analysis is robust .HoweverConventional experimental HLA typing using next generationsequencing tool and mapping an optimal CD8 T-cell epitope islaborious and expensive. Now, bioinformatic tools have beendeveloped that predict peptides that bind to a specific MHCmolecule. Though the experimental fine mapping of epitopes areunmatched in their efficacy . PredictThe application of information from the fields ofpharmacogenomics, pharmacogenetics and bioinformatics tovaccine design termed ‘vaccinomics’ has potential advantages.The conventional experimental approaches are seen as abottleneck toward developing new vaccines simply because ofthe possibility of potential candidate epitopes being leftunnoticed. Availability of pathogen genomes is now the keywealth of information and the computer programs developedwith extremely powerful algorithms can handle even a hugedataset for informatics-based approach towards vaccine design.Moreover, possibility of T-cell epitope prediction that bind tospecific HLA-class/allele, transporter of antigen processing(TAP) affinity prediction and proteasomal cleavage predictionare highly beneficial. Screening peptide-based vaccines using insilico bioinformatic approach has been shown to be particularlyuseful when hyper variable viruses like HIV and HCV areexamined . We alsoIn the course of Class I MHC presentation, antigens that aresynthesized in the cytosol undergo proteasomal degradation andTransporter associated with Antigen Presentation (TAP)molecules  transporPreviously, we had demonstrated immunodominant B-cellepitope of SNV in the N protein . The 3D MAPPP, which stands for MHC-I Antigenic Peptide ProcessingPrediction, predicts proteasomal cleavage with peptide anchoringto MHC I molecules. This program accepts length of fragmentsbetween 9 and 11. Though a TAP transporter can translocatepeptides of 8-40 amino acids, with preference for peptides oflength 8 to 11 amino acids, many programs including TAPpredused in our study predicts nonamers (9-mer) only. Therefore, 10-mer epitopes predicted in MHC binding program and MAPPPprogram, were eliminated in the TAP efficiency analysis. Due tothis reason, the finalized epitopes were all nonamers.The steps of MHC class I antigen presentation pathway areevaluated by three scoring systems. 1. proteasomal score whichreflects the efficiency of antigen-processing examining cleavagesite usage releasing the peptide C-terminus. 2. TAP score predictstransporter molecule associated with the epitope transport. Thisis achieved by estimation of the binding of a given peptide toTAP. The highest affinity score for a peptide indicates the highesttransport rates and affinity for the MHC molecule. The scores areexpressed logarithmically; higher values indicate higherpredicted efficiency.Following this, the identification of variables that influenceimmunogenicity has also been identified as an important step inthe investigation of T-cell epitopes and understanding of cellularimmune responses . In the Highlights of our study include T-cell epitope prediction specificto geographically restricted HLAs for the potential vaccinedevelopment for hantavirus infection. Among the candidateepitopes identified in our study, FLAARCPFL was conserved inSin Nombre virus, which is suitable for a vaccine specific to thisvirus genotype. Other epitopes were conserved across the HCPScausing hantaviruses suitable for pan-hantavirus vaccine. Thedata generated in this study has an intriguing potential for morerational approaches for vaccine design. SNV continues to be asignificant cause of morbidity and mortality in N. America andits control is not possible because of several epidemiologicalfeatures and lack of specific therapy. Development andapplication of an effective vaccine may be one importantapproach to be explored for the control of SNV infection.None


Crystalline nanoparticles or nanoprecipitates with a cubic structure often have near polyhedral shapes composed of low-index planes with {100}, {111} and {110}. To consider such near polyhedral shapes, algebraic formulas of extended superspheres that can express intermediate shapes between spheres and various polyhedra have been presented. Four extended superspheres, (i) {100} regular-hexahedral; (ii) {111} regular-octahedral (iii) {110} rhombic-dodecahedral and (iv) {100}-{111}-{110} rhombicuboctahedral superspheres are treated in this study. A measure ∏ to indicate the degree of polyhedrality is presented to discuss shape transitions of the extended superspheres. As an application of ∏ superspherical coherent precipitate is shown. R when p = 2 and a cube with edges 2R as p. To consider intermediate shapes of nanoparticles or nanoprecipitates between a sphere and cube, a solid figure called a supersphere was discussed in previous studies ,2. An eqorted in  that Eqund |z|=R . Shape tIn the case of crystals having cubic structures, nanoparticles or nanoprecipitates often have near polyhedral shapes composed of low-index planes with {100}, {111} and {110} ,6. TheseOnaka recently extended Equation (1) and derived algebraic formulas to describe intermediate shapes between spheres and various convex polyhedra ,11. Now p in Equation (1), p has been hence used as the measure of the degree of polyhedrality1/p=bR . The par a and b . In the Sphere is the solid figure having the minimum surface area under constant volume. The shape transitions of the extended superspheres from spheres to polyhedra cause the increase of surface area when the volume is kept constant. When t volume ,12. The lyhedral ,23.N with increasing The shape transitions of the extended superspheres from spheres to various polyhedra represented by the relationship between To compare the changes in For a sphere and polyhedron, we have The parameter We have considered relation  which isrelation .It is well known that the total surface or interface energy changes when shapes of particles or precipitates change. Similarly, mechanical energy such as elastic strain energy is also changed by shape changes of misfit precipitates in alloys ,10,14. AThe situation to consider the elastic-strain energy is summarized in cipitate , where δ, η or Π . Figure polation  as shownAs shown in Crystalline nanoparticles or nanoprecipitates often have near polyhedral shapes composed of low-index planes. Intermediate shapes between spheres and various convex polyhedra can be approximated with the concept of the extended superspheres. Four extended superspheres, (i) {100} regular-hexahedral; (ii) {111} regular-octahedral, (iii) {110} rhombic-dodecahedral and (iv) {100}-{111}-{110} rhombicuboctahedral superspheres have been treated in this study. A measure